Bio


Christina Curtis, PhD, MSc is the RZ Cao Professor of Medicine, Genetics and Biomedical Data Science at Stanford University where she also serves as the Director of Artificial Intelligence and Cancer Genomics and of Breast Cancer Translational Research. Dr. Curtis’s laboratory leverages computational modeling, high-throughput molecular profiling and experimentation to develop new ways to prevent, diagnose and treat cancer. Her research has redefined the molecular map of breast cancer and led to new paradigms in understanding the origins of human cancers, as well as how they evolve and metastasize. Dr. Curtis has been the recipient of numerous awards, including the National Institutes of Health (NIH) Director's Pioneer Award (2018) and the American Association for Cancer Research (AACR) Award for Outstanding Achievement in Basic Science (2022). She is a Kavli Fellow of the National Academy of Sciences, a Susan G. Komen Scholar, and a Chan Zuckerberg Biohub Investigator. Dr. Curtis is a member of Board of Reviewing Editors at Science, the AACR Board of Directors, and is a scientific advisor to biotech/biopharma.

Academic Appointments


Administrative Appointments


  • Director, Artificial Intelligence and Cancer Genomics, Stanford Cancer Institute (2022 - Present)
  • Director, Breast Cancer Translational Research, Stanford Cancer Institute (2021 - Present)
  • Co-Director, Molecular Tumor Board, Stanford Cancer Institute (2014 - Present)

Honors & Awards


  • Outstanding Achievement in Basic Science, American Association for Cancer Research (AACR) (2022)
  • Investigator, Chan Zuckerberg Biohub (2022)
  • Julius B Kahn Visiting Professor, Northwestern University, Department of Pharmacology (2021)
  • Rising Leader, Life Sciences, In Vivo (2021)
  • Stanford Prize in Population Genetics and Society, Stanford University (2020)
  • Komen Scholar, Susan G. Komen (2020)
  • NIH Director's Pioneer Award, NIH (2018)
  • Kavli Frontier of Science Fellow, National Academy of Science (USA) (2016)
  • Career Development Award, American Association for Cancer Research (AACR): Triple Negative Breast Cancer Foundation (2016)
  • Career Development Award, STOP Cancer (2012)
  • V Scholar Award, V Foundation for Cancer Research (2012)
  • Scholar-In-Training Award, American Association for Cancer Research (2009)

Boards, Advisory Committees, Professional Organizations


  • Scientific Advisory Board, Singapore Cancer Science Institute (2023 - Present)
  • Scientific Advisory Board, NY Genome Center (2023 - Present)
  • Board of Directors, American Association for Cancer Research (AACR) (2022 - Present)
  • Board of Reviewing Editors, Science (2022 - Present)
  • Scientific Advisory Board, Bristol Myers Squibb, Oncology/TME (2022 - Present)
  • Scientific Advisory Board, DeepCell (2021 - Present)
  • Scientific Advisory Board, Columbia University, Herbert Irving Comprehensive Cancer Center (2020 - Present)
  • Scientific Advisory Board, ResistanceBio (2020 - Present)
  • Scientific Advisory Board, Genentech, Oncology (2020 - Present)
  • Scientific Advisory Board, Nanostring (2020 - Present)
  • Scientific Advisory Board, Susan G. Komen Big Data Initiative, Share for Cures (2019 - Present)
  • Scientific Advisory Board, GRAIL (2017 - 2019)
  • Scientific Advisory Board, Ontario Institute for Cancer Research, Adaptive Oncology Program (2017 - Present)
  • Scientific Advisory Board, Cancer Research UK Early Detection Committee (2017 - 2020)
  • Editorial Board Member, Cancer Discovery (2020 - Present)
  • Editorial Board Member, Cell Systems (2019 - Present)
  • Editorial Board Member, Journal of Computational Biology (2017 - Present)
  • Editorial Board Member, ASCO Journal of Clinical Oncology: Precision Oncology (2016 - Present)
  • Associate Editor, Breast Cancer Research (2015 - 2020)

Professional Education


  • Postdoctoral Fellow, University of Cambridge, Computational Biology
  • PhD, University of Southern California, Molecular and Computational Biology
  • MS, University of Southern California, Bioinformatics and Computational Biology
  • MSc, University of Heidelberg, Germany, Molecular Biology

Community and International Work


  • Stanford Breast Cancer Metastasis Center

    Topic

    Breast cancer therapy, metastasis

    Partnering Organization(s)

    National Cancer Institute

    Ongoing Project

    Yes

    Opportunities for Student Involvement

    Yes

  • NCI/CTEP Translational Bioinformatics Committee

    Topic

    Bioinformatics /Translational cancer research/clinical trials

    Partnering Organization(s)

    NCI

    Ongoing Project

    Yes

    Opportunities for Student Involvement

    No

  • Human Tumor Atlas Network

    Topic

    Molecular characterization of cancer and pre-cancer

    Partnering Organization(s)

    NCI

    Ongoing Project

    Yes

    Opportunities for Student Involvement

    Yes

  • The Cancer Genome Atlas, Data Analysis Working Groups

    Topic

    Cancer Genomics

    Partnering Organization(s)

    NCI/TCGA

    Location

    US

    Ongoing Project

    Yes

    Opportunities for Student Involvement

    Yes

Current Research and Scholarly Interests


We are interested in elucidating tumor evolutionary dynamics, novel therapeutic targets, and the genotype to phenotype map in cancer. A unifying theme of our research is to exploit ‘omic’ data derived from clinically annotated samples in robust computational frameworks coupled with iterative experimental validation in order to advance our understanding of cancer systems biology. In particular, we employ advanced genomic techniques, computational and mathematical modeling, and powerful model systems in order to:
1.) Model the evolutionary dynamics of tumor progression and therapeutic resistance and metastasis
2) Elucidate disease etiology and novel molecular targets through integrative analyses of high-throughput omic data
3) Develop techniques for the systems-level interpretation of genotype-phenotype associations in cancer

Our research is funded by the NIH/NCI, NHGRI, Department of Defense, Breast Cancer Research Foundation, American Association for Cancer Research, Susan G. Komen Foundation, Emerson Collective and V Foundation for Cancer Research.

Clinical Trials


  • Umbrella Trial Testing Integrative Subtype-Targeted Therapeutics in HR+ /HER2-Negative Breast Cancer Recruiting

    The purpose of this study is to learn if adding a new drug that is targeted at a specific genetic change found in some breast tumors pre-operatively will slow the growth of the tumor more than standard anti-hormone therapy used to treat this type of breast cancer. Different therapies are being tested based on the specific gene changes in the tumor. Not every tumor will have a gene change that is being studied.

    View full details

  • Study of Infigratinib in Combination With Tamoxifen in Hormone Receptor Positive, HER2 Negative, FGFR Altered Advanced Breast Cancer Not Recruiting

    The purpose of the study is identify the dose(s) of infigratinib to use in combination with tamoxifen to treat patients with a particular type of advanced breast cancer (hormone receptor-positive, HER2-negative, FGFR-altered breast cancer)

    Stanford is currently not accepting patients for this trial. For more information, please contact Lisa Kody, 650-498-8583.

    View full details

2023-24 Courses


Stanford Advisees


Graduate and Fellowship Programs


All Publications


  • A microwell platform for high-throughput longitudinal phenotyping and selective retrieval of organoids. Cell systems Sockell, A., Wong, W., Longwell, S., Vu, T., Karlsson, K., Mokhtari, D., Schaepe, J., Lo, Y., Cornelius, V., Kuo, C., Van Valen, D., Curtis, C., Fordyce, P. M. 2023; 14 (9): 764

    Abstract

    Organoids are powerful experimental models for studying the ontogeny and progression of various diseases including cancer. Organoids are conventionally cultured in bulk using an extracellular matrix mimic. However, bulk-cultured organoids physically overlap, making it impossible to track the growth of individual organoids over time in high throughput. Moreover, local spatial variations in bulk matrix properties make it difficult to assess whether observed phenotypic heterogeneity between organoids results from intrinsic cell differences or differences in the microenvironment. Here, we developed a microwell-based method that enables high-throughput quantification of image-based parameters for organoids grown from single cells, which can further be retrieved from their microwells for molecular profiling. Coupled with a deep learning image-processing pipeline, we characterized phenotypic traits including growth rates, cellular movement, and apical-basal polarity in two CRISPR-engineered human gastric organoid models, identifying genomic changes associated with increased growth rate and changes in accessibility and expression correlated with apical-basal polarity. A record of this paper's transparent peer review process is included in the supplemental information.

    View details for DOI 10.1016/j.cels.2023.08.002

    View details for PubMedID 37734323

  • Deterministic evolution and stringent selection during preneoplasia. Nature Karlsson, K., Przybilla, M. J., Kotler, E., Khan, A., Xu, H., Karagyozova, K., Sockell, A., Wong, W. H., Liu, K., Mah, A., Lo, Y. H., Lu, B., Houlahan, K. E., Ma, Z., Suarez, C. J., Barnes, C. P., Kuo, C. J., Curtis, C. 2023

    Abstract

    The earliest events during human tumour initiation, although poorly characterized, may hold clues to malignancy detection and prevention1. Here we model occult preneoplasia by biallelic inactivation of TP53, a common early event in gastric cancer, in human gastric organoids. Causal relationships between this initiating genetic lesion and resulting phenotypes were established using experimental evolution in multiple clonally derived cultures over 2 years. TP53 loss elicited progressive aneuploidy, including copy number alterations and structural variants prevalent in gastric cancers, with evident preferred orders. Longitudinal single-cell sequencing of TP53-deficient gastric organoids similarly indicates progression towards malignant transcriptional programmes. Moreover, high-throughput lineage tracing with expressed cellular barcodes demonstrates reproducible dynamics whereby initially rare subclones with shared transcriptional programmes repeatedly attain clonal dominance. This powerful platform for experimental evolution exposes stringent selection, clonal interference and a marked degree of phenotypic convergence in premalignant epithelial organoids. These data imply predictability in the earliest stages of tumorigenesis and show evolutionary constraints and barriers to malignant transformation, with implications for earlier detection and interception of aggressive, genome-instable tumours.

    View details for DOI 10.1038/s41586-023-06102-8

    View details for PubMedID 37258665

    View details for PubMedCentralID 5656752

  • Germline-mediated immunoediting sculpts breast cancer subtypes and metastatic proclivity. bioRxiv : the preprint server for biology Houlahan, K. E., Khan, A., Greenwald, N. F., West, R. B., Angelo, M., Curtis, C. 2023

    Abstract

    Cancer represents a broad spectrum of molecularly and morphologically diverse diseases. Individuals with the same clinical diagnosis can have tumors with drastically different molecular profiles and clinical response to treatment. It remains unclear when these differences arise during disease course and why some tumors are addicted to one oncogenic pathway over another. Somatic genomic aberrations occur within the context of an individual's germline genome, which can vary across millions of polymorphic sites. An open question is whether germline differences influence somatic tumor evolution. Interrogating 3,855 breast cancer lesions, spanning pre-invasive to metastatic disease, we demonstrate that germline variants in highly expressed and amplified genes influence somatic evolution by modulating immunoediting at early stages of tumor development. Specifically, we show that the burden of germline-derived epitopes in recurrently amplified genes selects against somatic gene amplification in breast cancer. For example, individuals with a high burden of germline-derived epitopes in ERBB2, encoding human epidermal growth factor receptor 2 (HER2), are significantly less likely to develop HER2-positive breast cancer compared to other subtypes. The same holds true for recurrent amplicons that define four subgroups of ER-positive breast cancers at high risk of distant relapse. High epitope burden in these recurrently amplified regions is associated with decreased likelihood of developing high risk ER-positive cancer. Tumors that overcome such immune-mediated negative selection are more aggressive and demonstrate an "immune cold" phenotype. These data show the germline genome plays a previously unappreciated role in dictating somatic evolution. Exploiting germline-mediated immunoediting may inform the development of biomarkers that refine risk stratification within breast cancer subtypes.

    View details for DOI 10.1101/2023.03.15.532870

    View details for PubMedID 36993286

    View details for PubMedCentralID PMC10055121

  • Spatial proteomic characterization of HER2-positive breast tumors through neoadjuvant therapy predicts response. Nature cancer McNamara, K. L., Caswell-Jin, J. L., Joshi, R., Ma, Z., Kotler, E., Bean, G. R., Kriner, M., Zhou, Z., Hoang, M., Beechem, J., Zoeller, J., Press, M. F., Slamon, D. J., Hurvitz, S. A., Curtis, C. 2021; 2 (4): 400-413

    Abstract

    The addition of HER2-targeted agents to neoadjuvant chemotherapy has dramatically improved pathological complete response (pCR) rates in early-stage, HER2-positive breast cancer. Nonetheless, up to 50% of patients have residual disease after treatment, while others are likely overtreated. Here, we performed multiplex spatial proteomic characterization of 122 samples from 57 HER2-positive breast tumors from the neoadjuvant TRIO-US B07 clinical trial sampled pre-treatment, after 14-21 d of HER2-targeted therapy and at surgery. We demonstrated that proteomic changes after a single cycle of HER2-targeted therapy aids the identification of tumors that ultimately undergo pCR, outperforming pre-treatment measures or transcriptomic changes. We further developed and validated a classifier that robustly predicted pCR using a single marker, CD45, measured on treatment, and showed that CD45-positive cell counts measured via conventional immunohistochemistry perform comparably. These results demonstrate robust biomarkers that can be used to enable the stratification of sensitive tumors early during neoadjuvant HER2-targeted therapy, with implications for tailoring subsequent therapy.

    View details for DOI 10.1038/s43018-021-00190-z

    View details for PubMedID 34966897

    View details for PubMedCentralID PMC8713949

  • Characterizing the ecological and evolutionary dynamics of cancer. Nature genetics Zahir, N. n., Sun, R. n., Gallahan, D. n., Gatenby, R. A., Curtis, C. n. 2020

    Abstract

    Tumor initiation and progression are somatic evolutionary processes driven by the accumulation of genetic alterations, some of which confer selective fitness advantages to the host cell. This gene-centric model has shaped the field of cancer biology and advanced understanding of cancer pathophysiology. Importantly, however, each genotype encodes diverse phenotypic traits that permit acclimation to varied microenvironmental conditions. Epigenetic and transcriptional changes also contribute to the heritable phenotypic variation required for evolution. Additionally, interactions between cancer cells and surrounding stromal and immune cells through autonomous and non-autonomous signaling can influence competition for survival. Therefore, a mechanistic understanding of tumor progression must account for evolutionary and ecological dynamics. In this Perspective, we outline technological advances and model systems to characterize tumor progression through space and time. We discuss the importance of unifying experimentation with computational modeling and opportunities to inform cancer control.

    View details for DOI 10.1038/s41588-020-0668-4

    View details for PubMedID 32719518

  • Pathologic and molecular responses to neoadjuvant trastuzumab and/or lapatinib from a phase II randomized trial in HER2-positive breast cancer (TRIO-US B07). Nature communications Hurvitz, S. A., Caswell-Jin, J. L., McNamara, K. L., Zoeller, J. J., Bean, G. R., Dichmann, R., Perez, A., Patel, R., Zehngebot, L., Allen, H., Bosserman, L., DiCarlo, B., Kennedy, A., Giuliano, A., Calfa, C., Molthrop, D., Mani, A., Chen, H., Dering, J., Adams, B., Kotler, E., Press, M. F., Brugge, J. S., Curtis, C., Slamon, D. J. 2020; 11 (1): 5824

    Abstract

    In this multicenter, open-label, randomized phase II investigator-sponsored neoadjuvant trial with funding provided by Sanofi and GlaxoSmithKline (TRIO-US B07, Clinical Trials NCT00769470), participants with early-stage HER2-positive breast cancer (N=128) were recruited from 13 United States oncology centers throughout the Translational Research in Oncology network. Participants were randomized to receive trastuzumab (T; N=34), lapatinib (L; N=36), or both (TL; N=58) as HER2-targeted therapy, with each participant given one cycle of this designated anti-HER2 therapy alone followed by six cycles of standard combination chemotherapy with the same anti-HER2 therapy. The primary objective was to estimate the rate of pathologic complete response (pCR) at the time of surgery in each of the three arms. In the intent-to-treat population, we observed similar pCR rates between T (47%, 95% confidence interval [CI] 30-65%) and TL (52%, 95% CI 38-65%), and a lower pCR rate with L (25%, 95% CI 13-43%). In the T arm, 100% of participants completed all protocol-specified treatment prior to surgery, as compared to 69% in the L arm and 74% in the TL arm. Tumor or tumor bed tissue was collected whenever possible pre-treatment (N=110), after one cycle of HER2-targeted therapy alone (N=89), and at time of surgery (N=59). Higher-level amplification of HER2 and hormone receptor (HR)-negative status were associated with a higher pCR rate. Large shifts in the tumor, immune, and stromal gene expression occurred after one cycle of HER2-targeted therapy. In contrast to pCR rates, the L-containing arms exhibited greater proliferation reduction than T at this timepoint. Immune expression signatures increased in all arms after one cycle of HER2-targeted therapy, decreasing again by the time of surgery. Our results inform approaches to early assessment of sensitivity to anti-HER2 therapy and shed light on the role of the immune microenvironment in response to HER2-targeted agents.

    View details for DOI 10.1038/s41467-020-19494-2

    View details for PubMedID 33203854

  • Quantitative evidence for early metastatic seeding in colorectal cancer. Nature genetics Hu, Z., Ding, J., Ma, Z., Sun, R., Seoane, J. A., Scott Shaffer, J., Suarez, C. J., Berghoff, A. S., Cremolini, C., Falcone, A., Loupakis, F., Birner, P., Preusser, M., Lenz, H., Curtis, C. 2019

    Abstract

    Both the timing and molecular determinants of metastasis are unknown, hindering treatment and prevention efforts. Here we characterize the evolutionary dynamics of this lethal process by analyzing exome-sequencing data from 118biopsies from 23patients with colorectal cancer with metastases to the liver or brain. The data show that the genomic divergence between the primary tumor and metastasis is low and that canonical driver genes were acquired early. Analysis within a spatial tumor growth model and statistical inference framework indicates that early disseminated cells commonly (81%, 17 out of 21evaluable patients) seed metastases while the carcinoma is clinically undetectable (typically, less than 0.01cm3). We validated the association between early drivers and metastasis in an independent cohort of 2,751colorectal cancers, demonstrating their utility as biomarkers of metastasis. This conceptual and analytical framework provides quantitative in vivo evidence that systemic spread can occur early in colorectal cancer and illuminates strategies for patient stratification and therapeutic targeting of the canonical drivers of tumorigenesis.

    View details for DOI 10.1038/s41588-019-0423-x

    View details for PubMedID 31209394

  • Dynamics of breast-cancer relapse reveal late-recurring ER-positive genomic subgroups NATURE Rueda, O. M., Sammut, S., Seoane, J. A., Chin, S., Caswell-Jin, J. L., Callari, M., Batra, R., Pereira, B., Bruna, A., Ali, H., Provenzano, E., Liu, B., Parisien, M., Gillett, C., McKinney, S., Green, A. R., Murphy, L., Purushotham, A., Ellis, I. O., Pharoah, P. D., Rueda, C., Aparicio, S., Caldas, C., Curtis, C. 2019; 567 (7748): 399-+
  • Clonal replacement and heterogeneity in breast tumors treated with neoadjuvant HER2-targeted therapy. Nature communications Caswell-Jin, J. L., McNamara, K. n., Reiter, J. G., Sun, R. n., Hu, Z. n., Ma, Z. n., Ding, J. n., Suarez, C. J., Tilk, S. n., Raghavendra, A. n., Forte, V. n., Chin, S. F., Bardwell, H. n., Provenzano, E. n., Caldas, C. n., Lang, J. n., West, R. n., Tripathy, D. n., Press, M. F., Curtis, C. n. 2019; 10 (1): 657

    Abstract

    Genomic changes observed across treatment may result from either clonal evolution or geographically disparate sampling of heterogeneous tumors. Here we use computational modeling based on analysis of fifteen primary breast tumors and find that apparent clonal change between two tumor samples can frequently be explained by pre-treatment heterogeneity, such that at least two regions are necessary to detect treatment-induced clonal shifts. To assess for clonal replacement, we devise a summary statistic based on whole-exome sequencing of a pre-treatment biopsy and multi-region sampling of the post-treatment surgical specimen and apply this measure to five breast tumors treated with neoadjuvant HER2-targeted therapy. Two tumors underwent clonal replacement with treatment, and mathematical modeling indicates these two tumors had resistant subclones prior to treatment and rates of resistance-related genomic changes that were substantially larger than previous estimates. Our results provide a needed framework to incorporate primary tumor heterogeneity in investigating the evolution of resistance.

    View details for PubMedID 30737380

  • Chromatin regulators mediate anthracycline sensitivity in breast cancer. Nature medicine Seoane, J. A., Kirkland, J. G., Caswell-Jin, J. L., Crabtree, G. R., Curtis, C. n. 2019

    Abstract

    Anthracyclines are a highly effective component of curative breast cancer chemotherapy but are associated with substantial morbidity1,2. Because anthracyclines work in part by inhibiting topoisomerase-II (TOP2) on accessible DNA3,4, we hypothesized that chromatin regulatory genes (CRGs) that mediate DNA accessibility might predict anthracycline response. We studied the role of CRGs in anthracycline sensitivity in breast cancer through integrative analysis of patient and cell line data. We identified a consensus set of 38 CRGs associated with anthracycline response across ten cell line datasets. By evaluating the interaction between expression and treatment in predicting survival in a metacohort of 1006 patients with early-stage breast cancer, we identified 54 CRGs whose expression levels dictate anthracycline benefit across the clinical subgroups; of these CRGs, 12 overlapped with those identified in vitro. CRGs that promote DNA accessibility, including Trithorax complex members, were associated with anthracycline sensitivity when highly expressed, whereas CRGs that reduce accessibility, such as Polycomb complex proteins, were associated with decreased anthracycline sensitivity. We show that KDM4B modulates TOP2 accessibility to chromatin, elucidating a mechanism of TOP2 inhibitor sensitivity. These findings indicate that CRGs mediate anthracycline benefit by altering DNA accessibility, with implications for the stratification of patients with breast cancer and treatment decision making.

    View details for DOI 10.1038/s41591-019-0638-5

    View details for PubMedID 31700186

  • The chromatin accessibility landscape of primary human cancers. Science (New York, N.Y.) Corces, M. R., Granja, J. M., Shams, S. n., Louie, B. H., Seoane, J. A., Zhou, W. n., Silva, T. C., Groeneveld, C. n., Wong, C. K., Cho, S. W., Satpathy, A. T., Mumbach, M. R., Hoadley, K. A., Robertson, A. G., Sheffield, N. C., Felau, I. n., Castro, M. A., Berman, B. P., Staudt, L. M., Zenklusen, J. C., Laird, P. W., Curtis, C. n., Greenleaf, W. J., Chang, H. Y. 2018; 362 (6413)

    Abstract

    We present the genome-wide chromatin accessibility profiles of 410 tumor samples spanning 23 cancer types from The Cancer Genome Atlas (TCGA). We identify 562,709 transposase-accessible DNA elements that substantially extend the compendium of known cis-regulatory elements. Integration of ATAC-seq (the assay for transposase-accessible chromatin using sequencing) with TCGA multi-omic data identifies a large number of putative distal enhancers that distinguish molecular subtypes of cancers, uncovers specific driving transcription factors via protein-DNA footprints, and nominates long-range gene-regulatory interactions in cancer. These data reveal genetic risk loci of cancer predisposition as active DNA regulatory elements in cancer, identify gene-regulatory interactions underlying cancer immune evasion, and pinpoint noncoding mutations that drive enhancer activation and may affect patient survival. These results suggest a systematic approach to understanding the noncoding genome in cancer to advance diagnosis and therapy.

    View details for DOI 10.1126/science.aav1898

    View details for PubMedID 30361341

  • Between-region genetic divergence reflects the mode and tempo of tumor evolution. Nature genetics Sun, R., Hu, Z., Sottoriva, A., Graham, T. A., Harpak, A., Ma, Z., Fischer, J. M., Shibata, D., Curtis, C. 2017

    Abstract

    Given the implications of tumor dynamics for precision medicine, there is a need to systematically characterize the mode of evolution across diverse solid tumor types. In particular, methods to infer the role of natural selection within established human tumors are lacking. By simulating spatial tumor growth under different evolutionary modes and examining patterns of between-region subclonal genetic divergence from multiregion sequencing (MRS) data, we demonstrate that it is feasible to distinguish tumors driven by strong positive subclonal selection from those evolving neutrally or under weak selection, as the latter fail to dramatically alter subclonal composition. We developed a classifier based on measures of between-region subclonal genetic divergence and projected patient data into model space, finding different modes of evolution both within and between solid tumor types. Our findings have broad implications for how human tumors progress, how they accumulate intratumoral heterogeneity, and ultimately how they may be more effectively treated.

    View details for DOI 10.1038/ng.3891

    View details for PubMedID 28581503

  • A Big Bang model of human colorectal tumor growth. Nature genetics Sottoriva, A., Kang, H., Ma, Z., Graham, T. A., Salomon, M. P., Zhao, J., Marjoram, P., Siegmund, K., Press, M. F., Shibata, D., Curtis, C. 2015

    Abstract

    What happens in early, still undetectable human malignancies is unknown because direct observations are impractical. Here we present and validate a 'Big Bang' model, whereby tumors grow predominantly as a single expansion producing numerous intermixed subclones that are not subject to stringent selection and where both public (clonal) and most detectable private (subclonal) alterations arise early during growth. Genomic profiling of 349 individual glands from 15 colorectal tumors showed an absence of selective sweeps, uniformly high intratumoral heterogeneity (ITH) and subclone mixing in distant regions, as postulated by our model. We also verified the prediction that most detectable ITH originates from early private alterations and not from later clonal expansions, thus exposing the profile of the primordial tumor. Moreover, some tumors appear 'born to be bad', with subclone mixing indicative of early malignant potential. This new model provides a quantitative framework to interpret tumor growth dynamics and the origins of ITH, with important clinical implications.

    View details for DOI 10.1038/ng.3214

    View details for PubMedID 25665006

  • Serine starvation silences estrogen receptor signaling through histone hypoacetylation. Proceedings of the National Academy of Sciences of the United States of America Li, A. M., He, B., Karagiannis, D., Li, Y., Jiang, H., Srinivasan, P., Ramirez, Y., Zhou, M. N., Curtis, C., Gruber, J. J., Lu, C., Rankin, E. B., Ye, J. 2023; 120 (38): e2302489120

    Abstract

    Loss of estrogen receptor (ER) pathway activity promotes breast cancer progression, yet how this occurs remains poorly understood. Here, we show that serine starvation, a metabolic stress often found in breast cancer, represses estrogen receptor alpha (ERα) signaling by reprogramming glucose metabolism and epigenetics. Using isotope tracing and time-resolved metabolomic analyses, we demonstrate that serine is required to maintain glucose flux through glycolysis and the TCA cycle to support acetyl-CoA generation for histone acetylation. Consequently, limiting serine depletes histone H3 lysine 27 acetylation (H3K27ac), particularly at the promoter region of ER pathway genes including the gene encoding ERα, ESR1. Mechanistically, serine starvation impairs acetyl-CoA-dependent gene expression by inhibiting the entry of glycolytic carbon into the TCA cycle and down-regulating the mitochondrial citrate exporter SLC25A1, a critical enzyme in the production of nucleocytosolic acetyl-CoA from glucose. Consistent with this model, total H3K27ac and ERα expression are suppressed by SLC25A1 inhibition and restored by acetate, an alternate source of acetyl-CoA, in serine-free conditions. We thus uncover an unexpected role for serine in sustaining ER signaling through the regulation of acetyl-CoA metabolism.

    View details for DOI 10.1073/pnas.2302489120

    View details for PubMedID 37695911

  • Osteosarcoma PDX-Derived Cell Line Models for Preclinical Drug Evaluation Demonstrate Metastasis Inhibition by Dinaciclib through a Genome-Targeted Approach. Clinical cancer research : an official journal of the American Association for Cancer Research Schott, C. R., Koehne, A. L., Sayles, L. C., Young, E. P., Luck, C., Yu, K., Lee, A. G., Breese, M. R., Leung, S. G., Xu, H., Shah, A. T., Liu, H. Y., Spillinger, A., Behroozfard, I. H., Marini, K. D., Dinh, P. T., Pons Ventura, M. V., Vanderboon, E. N., Hazard, F. K., Cho, S. J., Avedian, R. S., Mohler, D. G., Zimel, M., Wustrack, R., Curtis, C., Sirota, M., Sweet-Cordero, E. A. 2023: OF1-OF16

    Abstract

    Models to study metastatic disease in rare cancers are needed to advance preclinical therapeutics and to gain insight into disease biology. Osteosarcoma is a rare cancer with a complex genomic landscape in which outcomes for patients with metastatic disease are poor. As osteosarcoma genomes are highly heterogeneous, multiple models are needed to fully elucidate key aspects of disease biology and to recapitulate clinically relevant phenotypes.Matched patient samples, patient-derived xenografts (PDX), and PDX-derived cell lines were comprehensively evaluated using whole-genome sequencing and RNA sequencing. The in vivo metastatic phenotype of the PDX-derived cell lines was characterized in both an intravenous and an orthotopic murine model. As a proof-of-concept study, we tested the preclinical effectiveness of a cyclin-dependent kinase inhibitor on the growth of metastatic tumors in an orthotopic amputation model.PDXs and PDX-derived cell lines largely maintained the expression profiles of the patient from which they were derived despite the emergence of whole-genome duplication in a subset of cell lines. The cell lines were heterogeneous in their metastatic capacity, and heterogeneous tissue tropism was observed in both intravenous and orthotopic models. Single-agent dinaciclib was effective at dramatically reducing the metastatic burden.The variation in metastasis predilection sites between osteosarcoma PDX-derived cell lines demonstrates their ability to recapitulate the spectrum of the disease observed in patients. We describe here a panel of new osteosarcoma PDX-derived cell lines that we believe will be of wide use to the osteosarcoma research community.

    View details for DOI 10.1158/1078-0432.CCR-23-0873

    View details for PubMedID 37703185

  • PhyloVelo enhances transcriptomic velocity field mapping using monotonically expressed genes. Nature biotechnology Wang, K., Hou, L., Wang, X., Zhai, X., Lu, Z., Zi, Z., Zhai, W., He, X., Curtis, C., Zhou, D., Hu, Z. 2023

    Abstract

    Single-cell RNA sequencing (scRNA-seq) is a powerful approach for studying cellular differentiation, but accurately tracking cell fate transitions can be challenging, especially in disease conditions. Here we introduce PhyloVelo, a computational framework that estimates the velocity of transcriptomic dynamics by using monotonically expressed genes (MEGs) or genes with expression patterns that either increase or decrease, but do not cycle, through phylogenetic time. Through integration of scRNA-seq data with lineage information, PhyloVelo identifies MEGs and reconstructs a transcriptomic velocity field. We validate PhyloVelo using simulated data and Caenorhabditis elegans ground truth data, successfully recovering linear, bifurcated and convergent differentiations. Applying PhyloVelo to seven lineage-traced scRNA-seq datasets, generated using CRISPR-Cas9 editing, lentiviral barcoding or immune repertoire profiling, demonstrates its high accuracy and robustness in inferring complex lineage trajectories while outperforming RNA velocity. Additionally, we discovered that MEGs across tissues and organisms share similar functions in translation and ribosome biogenesis.

    View details for DOI 10.1038/s41587-023-01887-5

    View details for PubMedID 37524958

    View details for PubMedCentralID 1414797

  • Author Correction: Combinatorial immunotherapies overcome MYC-driven immune evasion in triple negative breast cancer. Nature communications Lee, J. V., Housley, F., Yau, C., Nakagawa, R., Winkler, J., Anttila, J. M., Munne, P. M., Savelius, M., Houlahan, K. E., Van de Mark, D., Hemmati, G., Hernandez, G. A., Zhang, Y., Samson, S., Baas, C., Kok, M., Esserman, L. J., van 't Veer, L. J., Rugo, H. S., Curtis, C., Klefstrom, J., Matloubian, M., Goga, A. 2022; 13 (1): 7140

    View details for DOI 10.1038/s41467-022-34570-5

    View details for PubMedID 36414627

  • Molecular classification and biomarkers of clinical outcome in breast ductal carcinoma in situ: Analysis of TBCRC 038 and RAHBT cohorts. Cancer cell Strand, S. H., Rivero-Gutierrez, B., Houlahan, K. E., Seoane, J. A., King, L. M., Risom, T., Simpson, L. A., Vennam, S., Khan, A., Cisneros, L., Hardman, T., Harmon, B., Couch, F., Gallagher, K., Kilgore, M., Wei, S., DeMichele, A., King, T., McAuliffe, P. F., Nangia, J., Lee, J., Tseng, J., Storniolo, A. M., Thompson, A. M., Gupta, G. P., Burns, R., Veis, D. J., DeSchryver, K., Zhu, C., Matusiak, M., Wang, J., Zhu, S. X., Tappenden, J., Ding, D. Y., Zhang, D., Luo, J., Jiang, S., Varma, S., Anderson, L., Straub, C., Srivastava, S., Curtis, C., Tibshirani, R., Angelo, R. M., Hall, A., Owzar, K., Polyak, K., Maley, C., Marks, J. R., Colditz, G. A., Hwang, E. S., West, R. B. 2022

    Abstract

    Ductal carcinoma in situ (DCIS) is the most common precursor of invasive breast cancer (IBC), with variable propensity for progression. We perform multiscale, integrated molecular profiling of DCIS with clinical outcomes by analyzing 774 DCIS samples from 542 patients with 7.3 years median follow-up from the Translational Breast Cancer Research Consortium 038 study and the Resource of Archival Breast Tissue cohorts. We identify 812 genes associated with ipsilateral recurrence within 5 years from treatment and develop a classifier that predicts DCIS or IBC recurrence in both cohorts. Pathways associated with recurrence include proliferation, immune response, and metabolism. Distinct stromal expression patterns and immune cell compositions are identified. Our multiscale approach employed in situ methods to generate a spatially resolved atlas of breast precancers, where complementary modalities can be directly compared and correlated with conventional pathology findings, disease states, and clinical outcome.

    View details for DOI 10.1016/j.ccell.2022.10.021

    View details for PubMedID 36400020

  • ZFP281 drives a mesenchymal-like dormancy program in early disseminated breast cancer cells that prevents metastatic outgrowth in the lung. Nature cancer Nobre, A. R., Dalla, E., Yang, J., Huang, X., Wullkopf, L., Risson, E., Razghandi, P., Anton, M. L., Zheng, W., Seoane, J. A., Curtis, C., Kenigsberg, E., Wang, J., Aguirre-Ghiso, J. A. 2022

    Abstract

    Increasing evidence shows that cancer cells can disseminate from early evolved primary lesions much earlier than the classical metastasis models predicted. Here, we reveal at a single-cell resolution that mesenchymal-like (M-like) and pluripotency-like programs coordinate dissemination and a long-lived dormancy program of early disseminated cancer cells (DCCs). The transcription factor ZFP281 induces a permissive state for heterogeneous M-like transcriptional programs, which associate with a dormancy signature and phenotype in vivo. Downregulation of ZFP281 leads to a loss of an invasive, M-like dormancy phenotype and a switch to lung metastatic outgrowth. We also show that FGF2 and TWIST1 induce ZFP281 expression to induce the M-like state, which is linked to CDH1 downregulation and upregulation of CDH11. We found that ZFP281 not only controls the early dissemination of cancer cells but also locks early DCCs in a dormant state by preventing the acquisition of an epithelial-like proliferative program and consequent metastases outgrowth.

    View details for DOI 10.1038/s43018-022-00424-8

    View details for PubMedID 36050483

  • Most cancers carry a substantial deleterious load due to Hill-Robertson interference. eLife Tilk, S., Tkachenko, S., Curtis, C., Petrov, D. A., McFarland, C. D. 2022; 11

    Abstract

    Cancer genomes exhibit surprisingly weak signatures of negative selection1,2. This may be because selective pressures are relaxed or because genome-wide linkage prevents deleterious mutations from being removed (Hill-Robertson interference)3. By stratifying tumors by their genome-wide mutational burden, we observe negative selection (dN/dS ~ 0.56) in low mutational burden tumors, while remaining cancers exhibit dN/dS ratios ~1. This suggests that most tumors do not remove deleterious passengers. To buffer against deleterious passengers, tumors upregulate heat shock pathways as their mutational burden increases. Finally, evolutionary modeling finds that Hill-Robertson interference alone can reproduce patterns of attenuated selection and estimates the total fitness cost of passengers to be 46% per cell on average. Collectively, our findings suggest that the lack of observed negative selection in most tumors is not due to relaxed selective pressures, but rather the inability of selection to remove deleterious mutations in the presence of genome-wide linkage.

    View details for DOI 10.7554/eLife.67790

    View details for PubMedID 36047771

  • "Fateful" encounter: Lineage tracing meets phylogeny to unravel mysteries of cancer progression. Developmental cell Wong, W. H., Curtis, C. 2022; 57 (14): 1680-1682

    Abstract

    In a recent issue of Cell, Yang et al. utilize evolvable cellular barcodes to investigate the evolutionary trajectories of murine lung adenocarcinoma. Reconstructing the life histories of these tumors based on cellular barcodes reveals stringent selection and phenotypic differences across subclonal lineages.

    View details for DOI 10.1016/j.devcel.2022.07.002

    View details for PubMedID 35901781

  • Combinatorial immunotherapies overcome MYC-driven immune evasion in triple negative breast cancer. Nature communications Lee, J. V., Housley, F., Yau, C., Nakagawa, R., Winkler, J., Anttila, J. M., Munne, P. M., Savelius, M., Houlahan, K. E., Van de Mark, D., Hemmati, G., Hernandez, G. A., Zhang, Y., Samson, S., Baas, C., Esserman, L. J., van 't Veer, L. J., Rugo, H. S., Curtis, C., Klefström, J., Matloubian, M., Goga, A. 2022; 13 (1): 3671

    Abstract

    Few patients with triple negative breast cancer (TNBC) benefit from immune checkpoint inhibitors with complete and durable remissions being quite rare. Oncogenes can regulate tumor immune infiltration, however whether oncogenes dictate diminished response to immunotherapy and whether these effects are reversible remains poorly understood. Here, we report that TNBCs with elevated MYC expression are resistant to immune checkpoint inhibitor therapy. Using mouse models and patient data, we show that MYC signaling is associated with low tumor cell PD-L1, low overall immune cell infiltration, and low tumor cell MHC-I expression. Restoring interferon signaling in the tumor increases MHC-I expression. By combining a TLR9 agonist and an agonistic antibody against OX40 with anti-PD-L1, mice experience tumor regression and are protected from new TNBC tumor outgrowth. Our findings demonstrate that MYC-dependent immune evasion is reversible and druggable, and when strategically targeted, may improve outcomes for patients treated with immune checkpoint inhibitors.

    View details for DOI 10.1038/s41467-022-31238-y

    View details for PubMedID 35760778

  • Single-cell analyses define a continuum of cell state and composition changes in the malignant transformation of polyps to colorectal cancer. Nature genetics Becker, W. R., Nevins, S. A., Chen, D. C., Chiu, R., Horning, A. M., Guha, T. K., Laquindanum, R., Mills, M., Chaib, H., Ladabaum, U., Longacre, T., Shen, J., Esplin, E. D., Kundaje, A., Ford, J. M., Curtis, C., Snyder, M. P., Greenleaf, W. J. 2022

    Abstract

    To chart cell composition and cell state changes that occur during the transformation of healthy colon to precancerous adenomas to colorectal cancer (CRC), we generated single-cell chromatin accessibility profiles and single-cell transcriptomes from 1,000 to 10,000 cells per sample for 48 polyps, 27 normal tissues and 6 CRCs collected from patients with or without germline APC mutations. A large fraction of polyp and CRC cells exhibit a stem-like phenotype, and we define a continuum of epigenetic and transcriptional changes occurring in these stem-like cells as they progress from homeostasis to CRC. Advanced polyps contain increasing numbers of stem-like cells, regulatory T cells and a subtype of pre-cancer-associated fibroblasts. In the cancerous state, we observe T cell exhaustion, RUNX1-regulated cancer-associated fibroblasts and increasing accessibility associated with HNF4A motifs in epithelia. DNA methylation changes in sporadic CRC are strongly anti-correlated with accessibility changes along this continuum, further identifying regulatory markers for molecular staging of polyps.

    View details for DOI 10.1038/s41588-022-01088-x

    View details for PubMedID 35726067

  • Patient perspectives on window of opportunity clinical trials in early-stage breast cancer. Breast cancer research and treatment Parikh, D. A., Kody, L., Brain, S., Heditsian, D., Lee, V., Curtis, C., Karin, M. R., Wapnir, I. L., Patel, M. I., Sledge, G. W., Caswell-Jin, J. L. 2022

    Abstract

    Window of opportunity trials (WOT) are increasingly common in oncology research. In WOT participants receive a drug between diagnosis and anti-cancer treatment, usually for the purpose of investigating that drugs effect on cancer biology. This qualitative study aimed to understand patient perspectives on WOT.We recruited adults diagnosed with early-stage breast cancer awaiting definitive therapy at a single-academic medical center to participate in semi-structured interviews. Thematic and content analyses were performed to identify attitudes and factors that would influence decisions about WOT participation.We interviewed 25 women diagnosed with early-stage breast cancer. The most common positive attitudes toward trial participation were a desire to contribute to research and a hope for personal benefit, while the most common concerns were the potential for side effects and how they might impact fitness for planned treatment. Participants indicated family would be an important normative factor in decision-making and, during the COVID-19 pandemic, deemed the absence of family members during clinic visits a barrier to enrollment. Factors that could hinder participation included delay in standard treatment and the requirement for additional visits or procedures. Ultimately, most interviewees stated they would participate in a WOT if offered (N = 17/25).In this qualitative study, interviewees weighed altruism and hypothetical personal benefit against the possibility of side effect from a WOT. In-person family presence during trial discussion, challenging during COVID-19, was important for many. Our results may inform trial design and communication approaches in future window of opportunity efforts.

    View details for DOI 10.1007/s10549-022-06611-6

    View details for PubMedID 35538268

  • The Mettl3 epitranscriptomic writer amplifies p53 stress responses. Molecular cell Raj, N., Wang, M., Seoane, J. A., Zhao, R. L., Kaiser, A. M., Moonie, N. A., Demeter, J., Boutelle, A. M., Kerr, C. H., Mulligan, A. S., Moffatt, C., Zeng, S. X., Lu, H., Barna, M., Curtis, C., Chang, H. Y., Jackson, P. K., Attardi, L. D. 2022

    Abstract

    The p53 transcription factor drives anti-proliferative gene expression programs in response to diverse stressors, including DNA damage and oncogenic signaling. Here, we seek to uncover new mechanisms through which p53 regulates gene expression using tandem affinity purification/mass spectrometry to identify p53-interacting proteins. This approach identified METTL3, an m6A RNA-methyltransferase complex (MTC) constituent, as a p53 interactor. We find that METTL3 promotes p53 protein stabilization and target gene expression in response to DNA damage and oncogenic signals, by both catalytic activity-dependent and independent mechanisms. METTL3 also enhances p53 tumor suppressor activity in invivo mouse cancer models and human cancer cells. Notably, METTL3 only promotes tumor suppression in the context of intact p53. Analysis of human cancer genome data further supports the notion that the MTC reinforces p53 function in human cancer. Together, these studies reveal a fundamental role for METTL3 in amplifying p53 signaling in response to cellular stress.

    View details for DOI 10.1016/j.molcel.2022.04.010

    View details for PubMedID 35512709

  • MITI minimum information guidelines for highly multiplexed tissue images. Nature methods Schapiro, D., Yapp, C., Sokolov, A., Reynolds, S. M., Chen, Y., Sudar, D., Xie, Y., Muhlich, J., Arias-Camison, R., Arena, S., Taylor, A. J., Nikolov, M., Tyler, M., Lin, J., Burlingame, E. A., Human Tumor Atlas Network, Chang, Y. H., Farhi, S. L., Thorsson, V., Venkatamohan, N., Drewes, J. L., Pe'er, D., Gutman, D. A., Herrmann, M. D., Gehlenborg, N., Bankhead, P., Roland, J. T., Herndon, J. M., Snyder, M. P., Angelo, M., Nolan, G., Swedlow, J. R., Schultz, N., Merrick, D. T., Mazzili, S. A., Cerami, E., Rodig, S. J., Santagata, S., Sorger, P. K., Abravanel, D. L., Achilefu, S., Ademuyiwa, F. O., Adey, A. C., Aft, R., Ahn, K. J., Alikarami, F., Alon, S., Ashenberg, O., Baker, E., Baker, G. J., Bandyopadhyay, S., Bayguinov, P., Beane, J., Becker, W., Bernt, K., Betts, C. B., Bletz, J., Blosser, T., Boire, A., Boland, G. M., Boyden, E. S., Bucher, E., Bueno, R., Cai, Q., Cambuli, F., Campbell, J., Cao, S., Caravan, W., Chaligne, R., Chan, J. M., Chasnoff, S., Chatterjee, D., Chen, A. A., Chen, C., Chen, C., Chen, B., Chen, F., Chen, S., Chheda, M. G., Chin, K., Cho, H., Chun, J., Cisneros, L., Coffey, R. J., Cohen, O., Colditz, G. A., Cole, K. A., Collins, N., Cotter, D., Coussens, L. M., Coy, S., Creason, A. L., Cui, Y., Zhou, D. C., Curtis, C., Davies, S. R., Bruijn, I., Delorey, T. M., Demir, E., Denardo, D., Diep, D., Ding, L., DiPersio, J., Dubinett, S. M., Eberlein, T. J., Eddy, J. A., Esplin, E. D., Factor, R. E., Fatahalian, K., Feiler, H. S., Fernandez, J., Fields, A., Fields, R. C., Fitzpatrick, J. A., Ford, J. M., Franklin, J., Fulton, B., Gaglia, G., Galdieri, L., Ganesh, K., Gao, J., Gaudio, B. L., Getz, G., Gibbs, D. L., Gillanders, W. E., Goecks, J., Goodwin, D., Gray, J. W., Greenleaf, W., Grimm, L. J., Gu, Q., Guerriero, J. L., Guha, T., Guimaraes, A. R., Gutierrez, B., Hacohen, N., Hanson, C. R., Harris, C. R., Hawkins, W. G., Heiser, C. N., Hoffer, J., Hollmann, T. J., Hsieh, J. J., Huang, J., Hunger, S. P., Hwang, E., Iacobuzio-Donahue, C., Iglesia, M. D., Islam, M., Izar, B., Jacobson, C. A., Janes, S., Jayasinghe, R. G., Jeudi, T., Johnson, B. E., Johnson, B. E., Ju, T., Kadara, H., Karnoub, E., Karpova, A., Khan, A., Kibbe, W., Kim, A. H., King, L. M., Kozlowski, E., Krishnamoorthy, P., Krueger, R., Kundaje, A., Ladabaum, U., Laquindanum, R., Lau, C., Lau, K. S., LeBoeuf, N. R., Lee, H., Lenburg, M., Leshchiner, I., Levy, R., Li, Y., Lian, C. G., Liang, W., Lim, K., Lin, Y., Liu, D., Liu, Q., Liu, R., Lo, J., Lo, P., Longabaugh, W. J., Longacre, T., Luckett, K., Ma, C., Maher, C., Maier, A., Makowski, D., Maley, C., Maliga, Z., Manoj, P., Maris, J. M., Markham, N., Marks, J. R., Martinez, D., Mashl, J., Masilionis, I., Massague, J., Mazurowski, M. A., McKinley, E. T., McMichael, J., Meyerson, M., Mills, G. B., Mitri, Z. I., Moorman, A., Mudd, J., Murphy, G. F., Deen, N. N., Navin, N. E., Nawy, T., Ness, R. M., Nevins, S., Nirmal, A. J., Novikov, E., Oh, S. T., Oldridge, D. A., Owzar, K., Pant, S. M., Park, W., Patti, G. J., Paul, K., Pelletier, R., Persson, D., Petty, C., Pfister, H., Polyak, K., Puram, S. V., Qiu, Q., Villalonga, A. Q., Ramirez, M. A., Rashid, R., Reeb, A. N., Reid, M. E., Remsik, J., Riesterer, J. L., Risom, T., Ritch, C. C., Rolong, A., Rudin, C. M., Ryser, M. D., Sato, K., Sears, C. L., Semenov, Y. R., Shen, J., Shoghi, K. I., Shrubsole, M. J., Shyr, Y., Sibley, A. B., Simmons, A. J., Sinha, A., Sivagnanam, S., Song, S., Southar-Smith, A., Spira, A. E., Cyr, J. S., Stefankiewicz, S., Storrs, E. P., Stover, E. H., Strand, S. H., Straub, C., Street, C., Su, T., Surrey, L. F., Suver, C., Tan, K., Terekhanova, N. V., Ternes, L., Thadi, A., Thomas, G., Tibshirani, R., Umeda, S., Uzun, Y., Vallius, T., Van Allen, E. R., Vandekar, S., Vega, P. N., Veis, D. J., Vennam, S., Verma, A., Vigneau, S., Wagle, N., Wahl, R., Walle, T., Wang, L., Warchol, S., Washington, M. K., Watson, C., Weimer, A. K., Wendl, M. C., West, R. B., White, S., Windon, A. L., Wu, H., Wu, C., Wu, Y., Wyczalkowski, M. A., Xu, J., Yao, L., Yu, W., Zhang, K., Zhu, X. 2022; 19 (3): 262-267

    View details for DOI 10.1038/s41592-022-01415-4

    View details for PubMedID 35277708

  • Inter-cellular CRISPR screens reveal regulators of cancer cell phagocytosis. Nature Kamber, R. A., Nishiga, Y., Morton, B., Banuelos, A. M., Barkal, A. A., Vences-Catalan, F., Gu, M., Fernandez, D., Seoane, J. A., Yao, D., Liu, K., Lin, S., Spees, K., Curtis, C., Jerby-Arnon, L., Weissman, I. L., Sage, J., Bassik, M. C. 2021

    Abstract

    Monoclonal antibody therapies targeting tumour antigens drive cancer cell elimination in large part by triggering macrophage phagocytosis of cancer cells1-7. However, cancer cells evade phagocytosis using mechanisms that are incompletely understood. Here we develop a platform for unbiased identification of factors that impede antibody-dependent cellular phagocytosis (ADCP) using complementary genome-wide CRISPR knockout and overexpression screens in both cancer cells and macrophages. In cancer cells, beyond known factors such as CD47, we identify many regulators of susceptibility to ADCP, including the poorly characterized enzyme adipocyte plasma membrane-associated protein (APMAP). We find that loss of APMAP synergizes with tumour antigen-targeting monoclonal antibodies and/or CD47-blocking monoclonal antibodies to drive markedly increased phagocytosis across a wide range of cancer cell types, including those that are otherwise resistant to ADCP. Additionally, we show that APMAP loss synergizes with several different tumour-targeting monoclonal antibodies to inhibit tumour growth in mice. Using genome-wide counterscreens in macrophages, we find that the G-protein-coupled receptor GPR84 mediates enhanced phagocytosis of APMAP-deficient cancer cells. This work reveals a cancer-intrinsic regulator of susceptibility to antibody-driven phagocytosis and, more broadly, expands our knowledge of the mechanisms governing cancer resistance to macrophage phagocytosis.

    View details for DOI 10.1038/s41586-021-03879-4

    View details for PubMedID 34497417

  • Preface. Biochimica et biophysica acta. Reviews on cancer Curtis, C., Chin, L. 2021: 188617

    View details for DOI 10.1016/j.bbcan.2021.188617

    View details for PubMedID 34419532

  • Transcriptome and genome evolution during HER2-amplified breast neoplasia. Breast cancer research : BCR Lu, P., Foley, J., Zhu, C., McNamara, K., Sirinukunwattana, K., Vennam, S., Varma, S., Fehri, H., Srivastava, A., Zhu, S., Rittscher, J., Mallick, P., Curtis, C., West, R. 2021; 23 (1): 73

    Abstract

    BACKGROUND: The acquisition of oncogenic drivers is a critical feature of cancer progression. For some carcinomas, it is clear that certain genetic drivers occur early in neoplasia and others late. Why these drivers are selected and how these changes alter the neoplasia's fitness is less understood.METHODS: Here we use spatially oriented genomic approaches to identify transcriptomic and genetic changes at the single-duct level within precursor neoplasia associated with invasive breast cancer. We study HER2 amplification in ductal carcinoma in situ (DCIS) as an event that can be both quantified and spatially located via fluorescence in situ hybridization (FISH) and immunohistochemistry on fixed paraffin-embedded tissue.RESULTS: By combining the HER2-FISH with the laser capture microdissection (LCM) Smart-3SEQ method, we found that HER2 amplification in DCIS alters the transcriptomic profiles and increases diversity of copy number variations (CNVs). Particularly, interferon signaling pathway is activated by HER2 amplification in DCIS, which may provide a prolonged interferon signaling activation in HER2-positive breast cancer. Multiple subclones of HER2-amplified DCIS with distinct CNV profiles are observed, suggesting that multiple events occurred for the acquisition of HER2 amplification. Notably, DCIS acquires key transcriptomic changes and CNV events prior to HER2 amplification, suggesting that pre-amplified DCIS may create a cellular state primed to gain HER2 amplification for growth advantage.CONCLUSION: By using genomic methods that are spatially oriented, this study identifies several features that appear to generate insights into neoplastic progression in precancer lesions at a single-duct level.

    View details for DOI 10.1186/s13058-021-01451-6

    View details for PubMedID 34266469

  • A CRISPR/Cas9-engineered ARID1A-deficient human gastric cancer organoid model reveals essential and non-essential modes of oncogenic transformation. Lo, Y., Kolahi, K. S., Du, Y., Chang, C., Krokhotin, A., Nair, A., Sobba, W. D., Karlsson, K., Jones, S. J., Longacre, T. A., Mah, A. T., Sockell, A., Seoane, J. A., Chen, J., Weissman, J. S., Curtis, C., Califano, A., Fu, H., Crabtree, G. R., Kuo, C. J. AMER ASSOC CANCER RESEARCH. 2021
  • A tumor "personality" test to guide therapeutic decision making. Cancer cell Houlahan, K. E., Curtis, C. 2021

    Abstract

    In this issue of Cancer Cell, Bagaev etal. discover conserved relationships between immune and stroma activity that are prognostic and predictive of response to immunotherapy across cancer types. The authors develop a visualization tool, akin to a tumor personality test, to integrate genomic and microenvironmental profiling and guide therapeutic decision-making.

    View details for DOI 10.1016/j.ccell.2021.04.018

    View details for PubMedID 34019808

  • The AMBRA1 E3 ligase adaptor regulates the stability of cyclinD. Nature Chaikovsky, A. C., Li, C., Jeng, E. E., Loebell, S., Lee, M. C., Murray, C. W., Cheng, R., Demeter, J., Swaney, D. L., Chen, S., Newton, B. W., Johnson, J. R., Drainas, A. P., Shue, Y. T., Seoane, J. A., Srinivasan, P., He, A., Yoshida, A., Hipkins, S. Q., McCrea, E., Poltorack, C. D., Krogan, N. J., Diehl, J. A., Kong, C., Jackson, P. K., Curtis, C., Petrov, D. A., Bassik, M. C., Winslow, M. M., Sage, J. 2021

    Abstract

    The initiation of cell division integrates a large number of intra- and extracellular inputs. D-type cyclins (hereafter, cyclinD) couple these inputs to the initiation of DNA replication1. Increased levels of cyclinD promote cell division by activating cyclin-dependent kinases4 and 6 (hereafter, CDK4/6), which in turn phosphorylate and inactivate the retinoblastoma tumour suppressor. Accordingly, increased levels and activity of cyclinD-CDK4/6 complexes are strongly linked to unchecked cell proliferation and cancer2,3. However, the mechanisms that regulate levels of cyclinD are incompletely understood4,5. Here we show that autophagy and beclin1 regulator1 (AMBRA1) is the main regulator of the degradation of cyclinD. We identified AMBRA1 in a genome-wide screen to investigate the genetic basis of the response to CDK4/6 inhibition. Loss of AMBRA1 results in high levels of cyclinD in cells and in mice, which promotes proliferation and decreases sensitivity to CDK4/6 inhibition. Mechanistically, AMBRA1 mediates ubiquitylation and proteasomal degradation of cyclinD as a substrate receptor for the cullin4 E3 ligase complex. Loss of AMBRA1 enhances the growth of lung adenocarcinoma in a mouse model, and low levels of AMBRA1 correlate with worse survival in patients with lung adenocarcinoma. Thus, AMBRA1 regulates cellular levels of cyclinD, and contributes to cancer development and the response of cancer cells to CDK4/6 inhibitors.

    View details for DOI 10.1038/s41586-021-03474-7

    View details for PubMedID 33854239

  • Integrating Quantitative Approaches in Cancer Research and Oncology TRENDS IN CANCER Barker, A. D., Gatenby, R., Finley, S. D., Leggett, S. E., Nelson, C. M., Curtis, C., Mathur, D., Xavier, J. B., Califano, A., Castillo, S. P., Yuan, Y., Davies, P. 2021; 7 (4): 270–75

    View details for DOI 10.1016/j.trecan.2021.01.011

    View details for Web of Science ID 000629738900002

    View details for PubMedID 33637445

  • The oncogene AAMDC links PI3K-AKT-mTOR signaling with metabolic reprograming in estrogen receptor-positive breast cancer. Nature communications Golden, E., Rashwan, R., Woodward, E. A., Sgro, A., Wang, E., Sorolla, A., Waryah, C., Tie, W. J., Cuyas, E., Ratajska, M., Kardas, I., Kozlowski, P., Johnstone, E. K., See, H. B., Duffy, C., Parry, J., Lagerborg, K. A., Czapiewski, P., Menendez, J. A., Gorczynski, A., Wasag, B., Pfleger, K. D., Curtis, C., Lee, B., Kim, J., Cursons, J., Pavlos, N. J., Biernat, W., Jain, M., Woo, A. J., Redfern, A., Blancafort, P. 2021; 12 (1): 1920

    Abstract

    Adipogenesis associated Mth938 domain containing (AAMDC) represents an uncharacterized oncogene amplified in aggressive estrogen receptor-positive breast cancers. We uncover that AAMDC regulates the expression of several metabolic enzymes involved in the one-carbon folate and methionine cycles, and lipid metabolism. We show that AAMDC controls PI3K-AKT-mTOR signaling, regulating the translation of ATF4 and MYC and modulating the transcriptional activity of AAMDC-dependent promoters. High AAMDC expression is associated with sensitization to dactolisib and everolimus, and these PI3K-mTOR inhibitors exhibit synergistic interactions with anti-estrogens in IntClust2 models. Ectopic AAMDC expression is sufficient to activate AKT signaling, resulting in estrogen-independent tumor growth. Thus, AAMDC-overexpressing tumors may be sensitive to PI3K-mTORC1 blockers in combination with anti-estrogens. Lastly, we provide evidence that AAMDC can interact with the RabGTPase-activating protein RabGAP1L, and that AAMDC, RabGAP1L, and Rab7a colocalize in endolysosomes. The discovery of the RabGAP1L-AAMDC assembly platform provides insights for the design of selective blockers to target malignancies having the AAMDC amplification.

    View details for DOI 10.1038/s41467-021-22101-7

    View details for PubMedID 33772001

  • An expanded universe of cancer targets. Cell Hahn, W. C., Bader, J. S., Braun, T. P., Califano, A., Clemons, P. A., Druker, B. J., Ewald, A. J., Fu, H., Jagu, S., Kemp, C. J., Kim, W., Kuo, C. J., McManus, M., B Mills, G., Mo, X., Sahni, N., Schreiber, S. L., Talamas, J. A., Tamayo, P., Tyner, J. W., Wagner, B. K., Weiss, W. A., Gerhard, D. S., Cancer Target Discovery and Development Network, Dancik, V., Gill, S., Hua, B., Sharifnia, T., Viswanathan, V., Zou, Y., Dela Cruz, F., Kung, A., Stockwell, B., Boehm, J., Dempster, J., Manguso, R., Vazquez, F., Cooper, L. A., Du, Y., Ivanov, A., Lonial, S., Moreno, C. S., Niu, Q., Owonikoko, T., Ramalingam, S., Reyna, M., Zhou, W., Grandori, C., Shmulevich, I., Swisher, E., Cai, J., Chan, I. S., Dunworth, M., Ge, Y., Georgess, D., Grasset, E. M., Henriet, E., Knutsdottir, H., Lerner, M. G., Padmanaban, V., Perrone, M. C., Suhail, Y., Tsehay, Y., Warrier, M., Morrow, Q., Nechiporuk, T., Long, N., Saultz, J., Kaempf, A., Minnier, J., Tognon, C. E., Kurtz, S. E., Agarwal, A., Brown, J., Watanabe-Smith, K., Vu, T. Q., Jacob, T., Yan, Y., Robinson, B., Lind, E. F., Kosaka, Y., Demir, E., Estabrook, J., Grzadkowski, M., Nikolova, O., Chen, K., Deneen, B., Liang, H., Bassik, M. C., Bhattacharya, A., Brennan, K., Curtis, C., Gevaert, O., Ji, H. P., Karlsson, K. A., Karagyozova, K., Lo, Y., Liu, K., Nakano, M., Sathe, A., Smith, A. R., Spees, K., Wong, W. H., Yuki, K., Hangauer, M., Kaufman, D. S., Balmain, A., Bollam, S. R., Chen, W., Fan, Q., Kersten, K., Krummel, M., Li, Y. R., Menard, M., Nasholm, N., Schmidt, C., Serwas, N. K., Yoda, H. 2021; 184 (5): 1142–55

    Abstract

    The characterization of cancer genomes has provided insight into somatically altered genes across tumors, transformed our understanding of cancer biology, and enabled tailoring of therapeutic strategies. However, the function of most cancer alleles remains mysterious, and many cancer features transcend their genomes. Consequently, tumor genomic characterization does not influence therapy for most patients. Approaches to understand the function and circuitry of cancer genes provide complementary approaches to elucidate both oncogene and non-oncogene dependencies. Emerging work indicates that the diversity of therapeutic targets engendered by non-oncogene dependencies is much larger than the list of recurrently mutated genes. Here we describe a framework for this expanded list of cancer targets, providing novel opportunities for clinical translation.

    View details for DOI 10.1016/j.cell.2021.02.020

    View details for PubMedID 33667368

  • Cell of Origin Influences Pancreatic Cancer Subtype CANCER DISCOVERY Flowers, B. M., Xu, H., Mulligan, A. S., Hanson, K. J., Seoane, J. A., Vogel, H., Curtis, C., Wood, L. D., Attardi, L. D. 2021; 11 (3): 660–77
  • Cell of Origin Influences Pancreatic Cancer Subtype. Cancer discovery Flowers, B. M., Xu, H., Mulligan, A. S., Hanson, K. J., Seoane, J. A., Vogel, H., Curtis, C., Wood, L. D., Attardi, L. D. 2021; 11 (3): 660-677

    Abstract

    Pancreatic ductal adenocarcinoma (PDAC) is a deadly disease with a 5-year survival rate of approximately 9%. An improved understanding of PDAC initiation and progression is paramount for discovering strategies to better detect and combat this disease. Although transcriptomic analyses have uncovered distinct molecular subtypes of human PDAC, the factors that influence subtype development remain unclear. Here, we interrogate the impact of cell of origin and different Trp53 alleles on tumor evolution, using a panel of tractable genetically engineered mouse models. Oncogenic KRAS expression, coupled with Trp53 deletion or point mutation, drives PDAC from both acinar and ductal cells. Gene-expression analysis reveals further that ductal cell-derived and acinar cell-derived tumor signatures are enriched in basal-like and classical subtypes of human PDAC, respectively. These findings highlight cell of origin as one factor that influences PDAC molecular subtypes and provide insight into the fundamental impact that the very earliest events in carcinogenesis can have on cancer evolution. SIGNIFICANCE: Although human PDAC has been classified into different molecular subtypes, the etiology of these distinct subtypes remains unclear. Using mouse genetics, we reveal that cell of origin is an important determinant of PDAC molecular subtype. Deciphering the biology underlying pancreatic cancer subtypes may reveal meaningful distinctions that could improve clinical intervention.This article is highlighted in the In This Issue feature, p. 521.

    View details for DOI 10.1158/2159-8290.CD-20-0633

    View details for PubMedID 34009137

  • Androgen receptor agonists as breast cancer therapeutics. Nature medicine Caswell-Jin, J. L., Curtis, C. 2021

    View details for DOI 10.1038/s41591-021-01242-8

    View details for PubMedID 33558723

  • The human tumor atlas network (HTAN) breast pre cancer atlas: A multi-omic integrative analysis of ductal carcinoma in situ (DCIS) and correlation with clinical outcomes Hwang, S., Strand, S. H., Rivero, B., King, L., Risom, T., Harmon, B., Couch, F., Gallagher, K., Kilgore, M., Wei, S., DeMichele, A., King, T., McAuliffe, P., Nangia, J., Storniolo, A., Thompson, A., Gupta, G., Lee, J., Tseng, J., Burns, R., Zhu, C., Matusiak, M., Zhu, S. X., Wang, J., Seoane, J., Tappenden, J., Ding, D., Zhang, D., Luo, J., Vennam, S., Varma, S., Simpson, L., Cisneros, L., Hardman, T., Anderson, L., Straub, C., Srivastava, S., Veis, D. J., Curtis, C., Tibshirani, R., Angelo, R., Hall, A., Owzar, K., Polyak, K., Maley, C., Marks, J., Colditz, G., West, R. B. AMER ASSOC CANCER RESEARCH. 2021
  • Molecular Heterogeneity and Evolution in Breast Cancer Annual review of cancer biology Caswell-Jin, J. L., Lorenz, C., Curtis, C. 2021; 5: 79-94
  • A High-Dimensional Window into the Micro-Environment of Triple Negative Breast Cancer. Cancers Nederlof, I. n., Horlings, H. M., Curtis, C. n., Kok, M. n. 2021; 13 (2)

    Abstract

    Providing effective personalized immunotherapy for triple negative breast cancer (TNBC) patients requires a detailed understanding of the composition of the tumor microenvironment. Both the tumor cell and non-tumor components of TNBC can exhibit tremendous heterogeneity in individual patients and change over time. Delineating cellular phenotypes and spatial topographies associated with distinct immunological states and the impact of chemotherapy will be necessary to optimally time immunotherapy. The clinical successes in immunotherapy have intensified research on the tumor microenvironment, aided by a plethora of high-dimensional technologies to define cellular phenotypes. These high-dimensional technologies include, but are not limited to, single cell RNA sequencing, spatial transcriptomics, T cell repertoire analyses, advanced flow cytometry, imaging mass cytometry, and their integration. In this review, we discuss the cellular phenotypes and spatial patterns of the lymphoid-, myeloid-, and stromal cells in the TNBC microenvironment and the potential value of mapping these features onto tumor cell genotypes.

    View details for DOI 10.3390/cancers13020316

    View details for PubMedID 33467084

  • A CRISPR/Cas9-engineered ARID1A-deficient human gastric cancer organoid model reveals essential and non-essential modes of oncogenic transformation. Cancer discovery Lo, Y. H., Kolahi, K. S., Du, Y. n., Chang, C. Y., Krokhotin, A. n., Nair, A. n., Sobba, W. D., Karlsson, K. n., Jones, S. J., Longacre, T. A., Mah, A. T., Tercan, B. n., Sockell, A. n., Xu, H. n., Seoane, J. A., Chen, J. n., Shmulevich, I. n., Weissman, J. S., Curtis, C. n., Califano, A. n., Fu, H. n., Crabtree, G. R., Kuo, C. J. 2021

    Abstract

    Mutations in ARID1A rank amongst the most common molecular aberrations in human cancer. However, oncogenic consequences of ARID1A mutation in human cells remain poorly defined due to lack of forward genetic models. Here, CRISPR/Cas9-mediated ARID1A knockout in primary TP53-/- human gastric organoids induced morphologic dysplasia, tumorigenicity and mucinous differentiation. Genetic Wnt/B-catenin activation rescued mucinous differentiation, but not hyperproliferation, suggesting alternative pathways of ARID1A KO-mediated transformation. ARID1A mutation induced transcriptional regulatory modules characteristic of MSI and EBV subtype human gastric cancer, including FOXM1-associated mitotic genes and BIRC5/survivin. Convergently, high-throughput compound screening indicated selective vulnerability of ARID1A-deficient organoids to inhibition of BIRC5/survivin, functionally implicating this pathway as an essential mediator of ARID1A KO-dependent early-stage gastric tumorigenesis. Overall, we define distinct pathways downstream of oncogenic ARID1A mutation, with non-essential Wnt-inhibited mucinous differentiation in parallel with essential transcriptional FOXM1/BIRC5-stimulated proliferation, illustrating the general utility of organoid-based forward genetic cancer analysis in human cells.

    View details for DOI 10.1158/2159-8290.CD-20-1109

    View details for PubMedID 33451982

  • Zmat3 Is a Key Splicing Regulator in the p53 Tumor Suppression Program. Molecular cell Bieging-Rolett, K. T., Kaiser, A. M., Morgens, D. W., Boutelle, A. M., Seoane, J. A., Van Nostrand, E. L., Zhu, C., Houlihan, S. L., Mello, S. S., Yee, B. A., McClendon, J., Pierce, S. E., Winters, I. P., Wang, M., Connolly, A. J., Lowe, S. W., Curtis, C., Yeo, G. W., Winslow, M. M., Bassik, M. C., Attardi, L. D. 2020; 80 (3): 452

    Abstract

    Although TP53 is the most commonly mutated gene in human cancers, the p53-dependent transcriptional programs mediating tumor suppression remain incompletely understood. Here, to uncover critical components downstream of p53 in tumor suppression, we perform unbiased RNAi and CRISPR-Cas9-based genetic screens invivo. These screens converge upon the p53-inducible gene Zmat3, encoding an RNA-binding protein, and we demonstrate that ZMAT3 is an important tumor suppressor downstream of p53 in mouse KrasG12D-driven lung and liver cancers and human carcinomas. Integrative analysis of the ZMAT3 RNA-binding landscape and transcriptomic profiling reveals that ZMAT3 directly modulates exon inclusion in transcripts encoding proteins of diverse functions, including the p53 inhibitors MDM4 and MDM2, splicing regulators, and components of varied cellular processes. Interestingly, these exons are enriched in NMD signals, and, accordingly, ZMAT3 broadly affects target transcript stability. Collectively, these studies reveal ZMAT3 as a novel RNA-splicing and homeostasis regulator and a key component of p53-mediated tumor suppression.

    View details for DOI 10.1016/j.molcel.2020.10.022

    View details for PubMedID 33157015

  • Understanding patient perspectives on window of opportunity clinical trials. Parikh, D., Kody, L., Brain, S., Heditsian, D., Lee, V., Curtis, C., Sledge, G. W., Caswell-Jin, J. AMER SOC CLINICAL ONCOLOGY. 2020
  • Reprogramming of serine metabolism during breast cancer progression Li, A., Ducker, G. S., Li, Y., Seoane, J. A., Xiao, Y., Melemenidis, S., Zhou, Y., Liu, L., Vanharanta, S., Graves, E. E., Rankin, E. B., Curtis, C., Massague, J., Rabinowitz, J. D., Thompson, C. B., Ye, J. AMER ASSOC CANCER RESEARCH. 2020
  • Looking backward in time to define the chronology of metastasis. Nature communications Hu, Z., Curtis, C. 2020; 11 (1): 3213

    View details for DOI 10.1038/s41467-020-16995-y

    View details for PubMedID 32587245

  • Translating Basic Cancer Discoveries to the Clinic CANCER CELL Mardis, E. R., Dawson, M. A., Curtis, C., Xu, R., Long, G. V., Scolyer, R. A., Bakhoum, S. F., Nam, D., Garnett, M., Huang, A. 2020; 37 (6): 735–37

    View details for Web of Science ID 000540245900001

    View details for PubMedID 32516583

  • Deconstructing the origins of PDAC development. Flowers, B., Xu, H., Hanson, K., Curtis, C., Vogel, H., Wood, L., Attardi., L. D. AMER ASSOC CANCER RESEARCH. 2020: 19
  • The Human Tumor Atlas Network: Charting Tumor Transitions across Space and Time at Single-Cell Resolution. Cell Rozenblatt-Rosen, O., Regev, A., Oberdoerffer, P., Nawy, T., Hupalowska, A., Rood, J. E., Ashenberg, O., Cerami, E., Coffey, R. J., Demir, E., Ding, L., Esplin, E. D., Ford, J. M., Goecks, J., Ghosh, S., Gray, J. W., Guinney, J., Hanlon, S. E., Hughes, S. K., Hwang, E. S., Iacobuzio-Donahue, C. A., Jane-Valbuena, J., Johnson, B. E., Lau, K. S., Lively, T., Mazzilli, S. A., Pe'er, D., Santagata, S., Shalek, A. K., Schapiro, D., Snyder, M. P., Sorger, P. K., Spira, A. E., Srivastava, S., Tan, K., West, R. B., Williams, E. H., Human Tumor Atlas Network, Aberle, D., Achilefu, S. I., Ademuyiwa, F. O., Adey, A. C., Aft, R. L., Agarwal, R., Aguilar, R. A., Alikarami, F., Allaj, V., Amos, C., Anders, R. A., Angelo, M. R., Anton, K., Ashenberg, O., Aster, J. C., Babur, O., Bahmani, A., Balsubramani, A., Barrett, D., Beane, J., Bender, D. E., Bernt, K., Berry, L., Betts, C. B., Bletz, J., Blise, K., Boire, A., Boland, G., Borowsky, A., Bosse, K., Bott, M., Boyden, E., Brooks, J., Bueno, R., Burlingame, E. A., Cai, Q., Campbell, J., Caravan, W., Cerami, E., Chaib, H., Chan, J. M., Chang, Y. H., Chatterjee, D., Chaudhary, O., Chen, A. A., Chen, B., Chen, C., Chen, C., Chen, F., Chen, Y., Chheda, M. G., Chin, K., Chiu, R., Chu, S., Chuaqui, R., Chun, J., Cisneros, L., Coffey, R. J., Colditz, G. A., Cole, K., Collins, N., Contrepois, K., Coussens, L. M., Creason, A. L., Crichton, D., Curtis, C., Davidsen, T., Davies, S. R., de Bruijn, I., Dellostritto, L., De Marzo, A., Demir, E., DeNardo, D. G., Diep, D., Ding, L., Diskin, S., Doan, X., Drewes, J., Dubinett, S., Dyer, M., Egger, J., Eng, J., Engelhardt, B., Erwin, G., Esplin, E. D., Esserman, L., Felmeister, A., Feiler, H. S., Fields, R. C., Fisher, S., Flaherty, K., Flournoy, J., Ford, J. M., Fortunato, A., Frangieh, A., Frye, J. L., Fulton, R. S., Galipeau, D., Gan, S., Gao, J., Gao, L., Gao, P., Gao, V. R., Geiger, T., George, A., Getz, G., Ghosh, S., Giannakis, M., Gibbs, D. L., Gillanders, W. E., Goecks, J., Goedegebuure, S. P., Gould, A., Gowers, K., Gray, J. W., Greenleaf, W., Gresham, J., Guerriero, J. L., Guha, T. K., Guimaraes, A. R., Guinney, J., Gutman, D., Hacohen, N., Hanlon, S., Hansen, C. R., Harismendy, O., Harris, K. A., Hata, A., Hayashi, A., Heiser, C., Helvie, K., Herndon, J. M., Hirst, G., Hodi, F., Hollmann, T., Horning, A., Hsieh, J. J., Hughes, S., Huh, W. J., Hunger, S., Hwang, S. E., Iacobuzio-Donahue, C. A., Ijaz, H., Izar, B., Jacobson, C. A., Janes, S., Jane-Valbuena, J., Jayasinghe, R. G., Jiang, L., Johnson, B. E., Johnson, B., Ju, T., Kadara, H., Kaestner, K., Kagan, J., Kalinke, L., Keith, R., Khan, A., Kibbe, W., Kim, A. H., Kim, E., Kim, J., Kolodzie, A., Kopytra, M., Kotler, E., Krueger, R., Krysan, K., Kundaje, A., Ladabaum, U., Lake, B. B., Lam, H., Laquindanum, R., Lau, K. S., Laughney, A. M., Lee, H., Lenburg, M., Leonard, C., Leshchiner, I., Levy, R., Li, J., Lian, C. G., Lim, K., Lin, J., Lin, Y., Liu, Q., Liu, R., Lively, T., Longabaugh, W. J., Longacre, T., Ma, C. X., Macedonia, M. C., Madison, T., Maher, C. A., Maitra, A., Makinen, N., Makowski, D., Maley, C., Maliga, Z., Mallo, D., Maris, J., Markham, N., Marks, J., Martinez, D., Mashl, R. J., Masilionais, I., Mason, J., Massague, J., Massion, P., Mattar, M., Mazurchuk, R., Mazutis, L., Mazzilli, S. A., McKinley, E. T., McMichael, J. F., Merrick, D., Meyerson, M., Miessner, J. R., Mills, G. B., Mills, M., Mondal, S. B., Mori, M., Mori, Y., Moses, E., Mosse, Y., Muhlich, J. L., Murphy, G. F., Navin, N. E., Nawy, T., Nederlof, M., Ness, R., Nevins, S., Nikolov, M., Nirmal, A. J., Nolan, G., Novikov, E., Oberdoerffer, P., O'Connell, B., Offin, M., Oh, S. T., Olson, A., Ooms, A., Ossandon, M., Owzar, K., Parmar, S., Patel, T., Patti, G. J., Pe'er, D., Pe'er, I., Peng, T., Persson, D., Petty, M., Pfister, H., Polyak, K., Pourfarhangi, K., Puram, S. V., Qiu, Q., Quintanal-Villalonga, A., Raj, A., Ramirez-Solano, M., Rashid, R., Reeb, A. N., Regev, A., Reid, M., Resnick, A., Reynolds, S. M., Riesterer, J. L., Rodig, S., Roland, J. T., Rosenfield, S., Rotem, A., Roy, S., Rozenblatt-Rosen, O., Rudin, C. M., Ryser, M. D., Santagata, S., Santi-Vicini, M., Sato, K., Schapiro, D., Schrag, D., Schultz, N., Sears, C. L., Sears, R. C., Sen, S., Sen, T., Shalek, A., Sheng, J., Sheng, Q., Shoghi, K. I., Shrubsole, M. J., Shyr, Y., Sibley, A. B., Siex, K., Simmons, A. J., Singer, D. S., Sivagnanam, S., Slyper, M., Snyder, M. P., Sokolov, A., Song, S., Sorger, P. K., Southard-Smith, A., Spira, A., Srivastava, S., Stein, J., Storm, P., Stover, E., Strand, S. H., Su, T., Sudar, D., Sullivan, R., Surrey, L., Suva, M., Tan, K., Terekhanova, N. V., Ternes, L., Thammavong, L., Thibault, G., Thomas, G. V., Thorsson, V., Todres, E., Tran, L., Tyler, M., Uzun, Y., Vachani, A., Van Allen, E., Vandekar, S., Veis, D. J., Vigneau, S., Vossough, A., Waanders, A., Wagle, N., Wang, L., Wendl, M. C., West, R., Williams, E. H., Wu, C., Wu, H., Wu, H., Wyczalkowski, M. A., Xie, Y., Yang, X., Yapp, C., Yu, W., Yuan, Y., Zhang, D., Zhang, K., Zhang, M., Zhang, N., Zhang, Y., Zhao, Y., Zhou, D. C., Zhou, Z., Zhu, H., Zhu, Q., Zhu, X., Zhu, Y., Zhuang, X. 2020; 181 (2): 236–49

    Abstract

    Crucial transitions in cancer-including tumor initiation, local expansion, metastasis, and therapeutic resistance-involve complex interactions between cells within the dynamic tumor ecosystem. Transformative single-cell genomics technologies and spatial multiplex in situ methods now provide an opportunity to interrogate this complexity at unprecedented resolution. The Human Tumor Atlas Network (HTAN), part of the National Cancer Institute (NCI) Cancer Moonshot Initiative, will establish a clinical, experimental, computational, and organizational framework to generate informative and accessible three-dimensional atlases of cancer transitions for a diverse set of tumor types. This effort complements both ongoing efforts to map healthy organs and previous large-scale cancer genomics approaches focused on bulk sequencing at a single point in time. Generating single-cell, multiparametric, longitudinal atlases and integrating them with clinical outcomes should help identify novel predictive biomarkers and features as well as therapeutically relevant cell types, cell states, and cellular interactions across transitions. The resulting tumor atlases should have a profound impact on our understanding of cancer biology and have the potential to improve cancer detection, prevention, and therapeutic discovery for better precision-medicine treatments of cancer patients and those at risk for cancer.

    View details for DOI 10.1016/j.cell.2020.03.053

    View details for PubMedID 32302568

  • CRISPR screens in cancer spheroids identify 3D growth-specific vulnerabilities. Nature Han, K., Pierce, S. E., Li, A., Spees, K., Anderson, G. R., Seoane, J. A., Lo, Y. H., Dubreuil, M., Olivas, M., Kamber, R. A., Wainberg, M., Kostyrko, K., Kelly, M. R., Yousefi, M., Simpkins, S. W., Yao, D., Lee, K., Kuo, C. J., Jackson, P. K., Sweet-Cordero, A., Kundaje, A., Gentles, A. J., Curtis, C., Winslow, M. M., Bassik, M. C. 2020; 580 (7801): 136-141

    Abstract

    Cancer genomics studies have identified thousands of putative cancer driver genes1. Development of high-throughput and accurate models to define the functions of these genes is a major challenge. Here we devised a scalable cancer-spheroid model and performed genome-wide CRISPR screens in 2D monolayers and 3D lung-cancer spheroids. CRISPR phenotypes in 3D more accurately recapitulated those of in vivo tumours, and genes with differential sensitivities between 2D and 3D conditions were highly enriched for genes that are mutated in lung cancers. These analyses also revealed drivers that are essential for cancer growth in 3D and in vivo, but not in 2D. Notably, we found that carboxypeptidase D is responsible for removal of a C-terminal RKRR motif2 from the α-chain of the insulin-like growth factor 1 receptor that is critical for receptor activity. Carboxypeptidase D expression correlates with patient outcomes in patients with lung cancer, and loss of carboxypeptidase D reduced tumour growth. Our results reveal key differences between 2D and 3D cancer models, and establish a generalizable strategy for performing CRISPR screens in spheroids to reveal cancer vulnerabilities.

    View details for DOI 10.1038/s41586-020-2099-x

    View details for PubMedID 32238925

  • CRISPR screens in cancer spheroids identify 3D growth-specific vulnerabilities NATURE Han, K., Pierce, S. E., Li, A., Spees, K., Anderson, G. R., Seoane, J. A., Lo, Y., Dubreuil, M., Olivas, M., Kamber, R. A., Wainberg, M., Kostyrko, K., Kelly, M. R., Yousefi, M., Simpkins, S. W., Yao, D., Lee, K., Kuo, C. J., Jackson, P. K., Sweet-Cordero, A., Kundaje, A., Gentles, A. J., Curtis, C., Winslow, M. M., Bassik, M. C. 2020
  • Characterizing the tumor and immune microenvironment through treatment to predict response to neoadjuvant HER2-targeted therapy using the Digital Spatial Profiler McNamara, K., Caswell-Jin, J. L., Ma, Z., Zoeller, J. J., Kriner, M., Zhou, Z., Reeves, J., Hoang, M., Beechem, J., Slamon, D. J., Press, M. F., Brugge, J., Hurvitz, S. A., Curtis, C. AMER ASSOC CANCER RESEARCH. 2020
  • Tumor expression and microenvironment in HER2-positive breast cancer before and on HER2-targeted therapy: Analysis of microarray expression data from the TRIO-US B07 trial Caswell-Jin, J. L., McNamara, K. L., Dering, J., Chen, H., Dichmann, R., Perez, A., Patel, R., Kotler, E., Zoeller, J. J., Brugge, J. S., Press, M. F., Slamon, D. J., Curtis, C., Hurvitz, S. A. AMER ASSOC CANCER RESEARCH. 2020
  • The m6A RNA demethylase FTO is a HIF-independent synthetic lethal partner with the VHL tumor suppressor. Proceedings of the National Academy of Sciences of the United States of America Xiao, Y. n., Thakkar, K. N., Zhao, H. n., Broughton, J. n., Li, Y. n., Seoane, J. A., Diep, A. N., Metzner, T. J., von Eyben, R. n., Dill, D. L., Brooks, J. D., Curtis, C. n., Leppert, J. T., Ye, J. n., Peehl, D. M., Giaccia, A. J., Sinha, S. n., Rankin, E. B. 2020

    Abstract

    Loss of the von Hippel-Lindau (VHL) tumor suppressor is a hallmark feature of renal clear cell carcinoma. VHL inactivation results in the constitutive activation of the hypoxia-inducible factors (HIFs) HIF-1 and HIF-2 and their downstream targets, including the proangiogenic factors VEGF and PDGF. However, antiangiogenic agents and HIF-2 inhibitors have limited efficacy in cancer therapy due to the development of resistance. Here we employed an innovative computational platform, Mining of Synthetic Lethals (MiSL), to identify synthetic lethal interactions with the loss of VHL through analysis of primary tumor genomic and transcriptomic data. Using this approach, we identified a synthetic lethal interaction between VHL and the m6A RNA demethylase FTO in renal cell carcinoma. MiSL identified FTO as a synthetic lethal partner of VHL because deletions of FTO are mutually exclusive with VHL loss in pan cancer datasets. Moreover, FTO expression is increased in VHL-deficient ccRCC tumors compared to normal adjacent tissue. Genetic inactivation of FTO using multiple orthogonal approaches revealed that FTO inhibition selectively reduces the growth and survival of VHL-deficient cells in vitro and in vivo. Notably, FTO inhibition reduced the survival of both HIF wild type and HIF-deficient tumors, identifying FTO as an HIF-independent vulnerability of VHL-deficient cancers. Integrated analysis of transcriptome-wide m6A-seq and mRNA-seq analysis identified the glutamine transporter SLC1A5 as an FTO target that promotes metabolic reprogramming and survival of VHL-deficient ccRCC cells. These findings identify FTO as a potential HIF-independent therapeutic target for the treatment of VHL-deficient renal cell carcinoma.

    View details for DOI 10.1073/pnas.2000516117

    View details for PubMedID 32817424

  • CHRISTINA CURTIS COMPUTING CANCER NATURE Curtis, C. 2020; 577 (7791): 586
  • Metabolic Profiling Reveals a Dependency of Human Metastatic Breast Cancer on Mitochondrial Serine and One-Carbon Unit Metabolism. Molecular cancer research : MCR Li, A. M., Ducker, G. S., Li, Y. n., Seoane, J. A., Xiao, Y. n., Melemenidis, S. n., Zhou, Y. n., Liu, L. n., Vanharanta, S. n., Graves, E. E., Rankin, E. B., Curtis, C. n., Massague, J. n., Rabinowitz, J. D., Thompson, C. B., Ye, J. n. 2020

    Abstract

    Breast cancer is the most common cancer among American women and a major cause of mortality. To identify metabolic pathways as potential targets to treat metastatic breast cancer, we performed metabolomics profiling on breast cancer cell line MDA-MB-231 and its tissue-tropic metastatic subclones. Here, we report that these subclones with increased metastatic potential display an altered metabolic profile compared to the parental population. In particular, the mitochondrial serine and one-carbon (1C) unit pathway is upregulated in metastatic subclones. Mechanistically, the mitochondrial serine and 1C unit pathway drives the faster proliferation of subclones through enhanced de novo purine biosynthesis. Inhibition of the first rate-limiting enzyme of the mitochondrial serine and 1C unit pathway, serine hydroxymethyltransferase (SHMT2), potently suppresses proliferation of metastatic subclones in culture and impairs growth of lung metastatic subclones at both primary and metastatic sites in mice. Some human breast cancers exhibit a significant association between the expression of genes in the mitochondrial serine and 1C unit pathway with disease outcome and higher expression of SHMT2 in metastatic tumor tissue compared to primary tumors. In addition to breast cancer, a few other cancer types, such as adrenocortical carcinoma (ACC) and kidney chromophobe cell carcinoma (KICH), also display increased SHMT2 expression during disease progression. Together, these results suggest that mitochondrial serine and 1C unit plays an important role in promoting cancer progression, particularly in late stage cancer. Implications: This study identifies mitochondrial serine and 1C unit metabolism as an important pathway during the progression of a subset of human breast cancers.

    View details for DOI 10.1158/1541-7786.MCR-19-0606

    View details for PubMedID 31941752

  • Novel insights into breast cancer copy number genetic heterogeneity revealed by single-cell genome sequencing. eLife Baslan, T. n., Kendall, J. n., Volyanskyy, K. n., McNamara, K. n., Cox, H. n., D'Italia, S. n., Ambrosio, F. n., Riggs, M. n., Rodgers, L. n., Leotta, A. n., Song, J. n., Mao, Y. n., Wu, J. n., Shah, R. n., Gularte-Mérida, R. n., Chadalavada, K. n., Nanjangud, G. n., Varadan, V. n., Gordon, A. n., Curtis, C. n., Krasnitz, A. n., Dimitrova, N. n., Harris, L. n., Wigler, M. n., Hicks, J. n. 2020; 9

    Abstract

    Copy number alterations (CNAs) play an important role in molding the genomes of breast cancers and have been shown to be clinically useful for prognostic and therapeutic purposes. However, our knowledge of intra-tumoral genetic heterogeneity of this important class of somatic alterations is limited. Here, using single-cell sequencing, we comprehensively map out the facets of copy number alteration heterogeneity in a cohort of breast cancer tumors. Ou/var/www/html/elife/12-05-2020/backup/r analyses reveal: genetic heterogeneity of non-tumor cells (i.e. stroma) within the tumor mass; the extent to which copy number heterogeneity impacts breast cancer genomes and the importance of both the genomic location and dosage of sub-clonal events; the pervasive nature of genetic heterogeneity of chromosomal amplifications; and the association of copy number heterogeneity with clinical and biological parameters such as polyploidy and estrogen receptor negative status. Our data highlight the power of single-cell genomics in dissecting, in its many forms, intra-tumoral genetic heterogeneity of CNAs, the magnitude with which CNA heterogeneity affects the genomes of breast cancers, and the potential importance of CNA heterogeneity in phenomena such as therapeutic resistance and disease relapse.

    View details for DOI 10.7554/eLife.51480

    View details for PubMedID 32401198

    View details for PubMedCentralID PMC7220379

  • Quantifying mutations in healthy blood. Science (New York, N.Y.) Curtis, C. n. 2020; 367 (6485): 1426–27

    View details for DOI 10.1126/science.aba9891

    View details for PubMedID 32217714

  • Deciphering the origins of PDAC development Flowers, B., Xu, H., Hanson, K., Curtis, C., Vogel, H., Wood, L. D., Attardi, L. D. AMER ASSOC CANCER RESEARCH. 2019
  • Elucidating the role of p53 in the cellular origins of pancreatic cancer development Flowers, B. M., Xu, H., Hanson, K., Curtis, C., Vogel, H., Wood, L. D., Attardi, L. D. AMER ASSOC CANCER RESEARCH. 2019
  • Chromatin state as a mechanism of anthracycline response in breast cancer Seoane, J. A., Kirkland, J. G., Caswell-Jin, J. L., Crabtree, G. R., Curtis, C. AMER ASSOC CANCER RESEARCH. 2019
  • Community assessment to advance computational prediction of cancer drug combinations in a pharmacogenomic screen NATURE COMMUNICATIONS Menden, M. P., Wang, D., Mason, M. J., Szalai, B., Bulusu, K. C., Guan, Y., Yu, T., Kang, J., Jeon, M., Wolfinger, R., Nguyen, T., Zaslavskiy, M., Jang, I., Ghazoui, Z., Ahsen, M., Vogel, R., Neto, E., Norman, T., Tang, E. Y., Garnett, M. J., Di Veroli, G. Y., Fawell, S., Stolovitzky, G., Guinney, J., Dry, J. R., Saez-Rodriguez, J., Abante, J., Abecassis, B., Aben, N., Aghamirzaie, D., Aittokallio, T., Akhtari, F. S., Al-lazikani, B., Alam, T., Allam, A., Allen, C., de Almeida, M., Altarawy, D., Alves, V., Amadoz, A., Anchang, B., Antolin, A. A., Ash, J. R., Romeo Aznar, V., Ba-alawi, W., Bagheri, M., Bajic, V., Ball, G., Ballester, P. J., Baptista, D., Bare, C., Bateson, M., Bender, A., Bertrand, D., Wijayawardena, B., Boroevich, K. A., Bosdriesz, E., Bougouffa, S., Bounova, G., Brouwer, T., Bryant, B., Calaza, M., Calderone, A., Calza, S., Capuzzi, S., Carbonell-Caballero, J., Carlin, D., Carter, H., Castagnoli, L., Celebi, R., Cesareni, G., Chang, H., Chen, G., Chen, H., Chen, H., Cheng, L., Chernomoretz, A., Chicco, D., Cho, K., Cho, S., Choi, D., Choi, J., Choi, K., Choi, M., De Cock, M., Coker, E., Cortes-Ciriano, I., Cserzo, M., Cubuk, C., Curtis, C., Van Daele, D., Dang, C. C., Dijkstra, T., Dopazo, J., Draghici, S., Drosou, A., Dumontier, M., Ehrhart, F., Eid, F., ElHefnawi, M., Elmarakeby, H., van Engelen, B., Engin, H., de Esch, I., Evelo, C., Falcao, A. O., Farag, S., Fernandez-Lozano, C., Fisch, K., Flobak, A., Fornari, C., Foroushani, A. K., Fotso, D., Fourches, D., Friend, S., Frigessi, A., Gao, F., Gao, X., Gerold, J. M., Gestraud, P., Ghosh, S., Gillberg, J., Godoy-Lorite, A., Godynyuk, L., Godzik, A., Goldenberg, A., Gomez-Cabrero, D., Gonen, M., de Graaf, C., Gray, H., Grechkin, M., Guimera, R., Guney, E., Haibe-Kains, B., Han, Y., Hase, T., He, D., He, L., Heath, L. S., Hellton, K. H., Helmer-Citterich, M., Hidalgo, M. R., Hidru, D., Hill, S. M., Hochreiter, S., Hong, S., Hovig, E., Hsueh, Y., Hu, Z., Huang, J. K., Huang, R., Hunyady, L., Hwang, J., Hwang, T., Hwang, W., Hwang, Y., Isayev, O., Walk, O., Jack, J., Jahandideh, S., Ji, J., Jo, Y., Kamola, P. J., Kanev, G. K., Karacosta, L., Karimi, M., Kaski, S., Kazanov, M., Khamis, A. M., Khan, S., Kiani, N. A., Kim, A., Kim, J., Kim, J., Kim, K., Kim, K., Kim, S., Kim, Y., Kim, Y., Kirk, P. W., Kitano, H., Klambauer, G., Knowles, D., Ko, M., Kohn-Luque, A., Kooistra, A. J., Kuenemann, M. A., Kuiper, M., Kurz, C., Kwon, M., van Laarhoven, T., Laegreid, A., Lederer, S., Lee, H., Lee, J., Lee, Y., Leppaho, E., Lewis, R., Li, J., Li, L., Liley, J., Lim, W., Lin, C., Liu, Y., Lopez, Y., Low, J., Lysenko, A., Machado, D., Madhukar, N., De Maeyer, D., Malpartida, A., Mamitsuka, H., Marabita, F., Marchal, K., Marttinen, P., Mason, D., Mazaheri, A., Mehmood, A., Mehreen, A., Michaut, M., Miller, R. A., Mitsopoulos, C., Modos, D., Van Moerbeke, M., Moo, K., Motsinger-Reif, A., Movva, R., Muraru, S., Muratov, E., Mushthofa, M., Nagarajan, N., Nakken, S., Nath, A., Neuvial, P., Newton, R., Ning, Z., De Niz, C., Oliva, B., Olsen, C., Palmeri, A., Panesar, B., Papadopoulos, S., Park, J., Park, S., Park, S., Pawitan, Y., Peluso, D., Pendyala, S., Peng, J., Perfetto, L., Pirro, S., Plevritis, S., Politi, R., Poon, H., Porta, E., Prellner, I., Preuer, K., Angel Pujana, M., Ramnarine, R., Reid, J. E., Reyal, F., Richardson, S., Ricketts, C., Rieswijk, L., Rocha, M., Rodriguez-Gonzalvez, C., Roell, K., Rotroff, D., de Ruiter, J. R., Rukawa, P., Sadacca, B., Safikhani, Z., Safitri, F., Sales-Pardo, M., Sauer, S., Schlichting, M., Seoane, J. A., Serra, J., Shang, M., Sharma, A., Sharma, H., Shen, Y., Shiga, M., Shin, M., Shkedy, Z., Shopsowitz, K., Sinai, S., Skola, D., Smirnov, P., Soerensen, I., Soerensen, P., Song, J., Song, S., Soufan, O., Spitzmueller, A., Steipe, B., Suphavilai, C., Tamayo, S., Tamborero, D., Tang, J., Tanoli, Z., Tarres-Deulofeu, M., Tegner, J., Thommesen, L., Tonekaboni, S., Tran, H., De Troyer, E., Truong, A., Tsunoda, T., Turu, G., Tzeng, G., Verbeke, L., Videla, S., Vis, D., Voronkov, A., Votis, K., Wang, A., Wang, H., Wang, P., Wang, S., Wang, W., Wang, X., Wang, X., Wennerberg, K., Wernisch, L., Wessels, L., van Westen, G. P., Westerman, B. A., White, S., Willighagen, E., Wurdinger, T., Xie, L., Xie, S., Xu, H., Yadav, B., Yau, C., Yeerna, H., Yin, J., Yu, M., Yu, M., Yun, S., Zakharov, A., Zamichos, A., Zanin, M., Zeng, L., Zenil, H., Zhang, F., Zhang, P., Zhang, W., Zhao, H., Zhao, L., Zheng, W., Zoufir, A., Zucknick, M., AstraZeneca-Sanger Drug Combinatio 2019; 10: 2674

    Abstract

    The effectiveness of most cancer targeted therapies is short-lived. Tumors often develop resistance that might be overcome with drug combinations. However, the number of possible combinations is vast, necessitating data-driven approaches to find optimal patient-specific treatments. Here we report AstraZeneca's large drug combination dataset, consisting of 11,576 experiments from 910 combinations across 85 molecularly characterized cancer cell lines, and results of a DREAM Challenge to evaluate computational strategies for predicting synergistic drug pairs and biomarkers. 160 teams participated to provide a comprehensive methodological development and benchmarking. Winning methods incorporate prior knowledge of drug-target interactions. Synergy is predicted with an accuracy matching biological replicates for >60% of combinations. However, 20% of drug combinations are poorly predicted by all methods. Genomic rationale for synergy predictions are identified, including ADAM17 inhibitor antagonism when combined with PIK3CB/D inhibition contrasting to synergy when combined with other PI3K-pathway inhibitors in PIK3CA mutant cells.

    View details for DOI 10.1038/s41467-019-09799-2

    View details for Web of Science ID 000471758500010

    View details for PubMedID 31209238

    View details for PubMedCentralID PMC6572829

  • Dynamics of breast-cancer relapse reveal late-recurring ER-positive genomic subgroups. Nature Rueda, O. M., Sammut, S., Seoane, J. A., Chin, S., Caswell-Jin, J. L., Callari, M., Batra, R., Pereira, B., Bruna, A., Ali, H. R., Provenzano, E., Liu, B., Parisien, M., Gillett, C., McKinney, S., Green, A. R., Murphy, L., Purushotham, A., Ellis, I. O., Pharoah, P. D., Rueda, C., Aparicio, S., Caldas, C., Curtis, C. 2019

    Abstract

    The rates and routes of lethal systemic spread in breast cancer are poorly understood owing to a lack of molecularly characterized patient cohorts with long-term, detailed follow-up data. Long-term follow-up is especially important for those with oestrogen-receptor (ER)-positive breast cancers, which can recur up to two decades after initial diagnosis1-6. It is therefore essential to identify patients who have a high risk of late relapse7-9. Here we present a statistical framework that models distinct disease stages (locoregional recurrence, distant recurrence, breast-cancer-related deathand death from other causes) and competing risks of mortality from breast cancer, while yielding individual risk-of-recurrence predictions. We apply this model to 3,240 patients with breast cancer, including 1,980 for whom molecular data are available, and delineate spatiotemporal patterns of relapse across different categories of molecular information (namely immunohistochemical subtypes; PAM50 subtypes, which are based on gene-expression patterns10,11; and integrative or IntClust subtypes, which are based on patterns of genomic copy-number alterations and gene expression12,13). We identify four late-recurring integrative subtypes, comprisingabout one quarter (26%) of tumours that are both positive for ER and negative for human epidermal growth factor receptor 2, each with characteristic tumour-driving alterations in genomic copy number and a high risk of recurrence (mean 47-62%) up to 20 years after diagnosis. We also define a subgroup of triple-negative breast cancers in which cancer rarely recurs after five years, and a separate subgroup in which patients remain at risk. Use of the integrative subtypes improves the prediction of late, distant relapse beyond what is possible with clinical covariates (nodal status, tumour size, tumour grade and immunohistochemical subtype). These findings highlight opportunities for improved patient stratification and biomarker-driven clinical trials.

    View details for PubMedID 30867590

  • Assessment of ERBB2/HER2 Status in HER2-Equivocal Breast Cancers by FISH and 2013/2014 ASCO-CAP Guidelines JAMA ONCOLOGY Press, M. F., Seoane, J. A., Curtis, C., Quinaux, E., Guzman, R., Sauter, G., Eiermann, W., Mackey, J. R., Robert, N., Pienkowski, T., Crown, J., Martin, M., Valero, V., Bee, V., Ma, Y., Villalobos, I., Slamon, D. J. 2019; 5 (3): 366-375
  • Clonal replacement and heterogeneity in breast tumors treated with neoadjuvant HER2-targeted therapy NATURE COMMUNICATIONS Caswell-Jin, J. L., McNamara, K., Reiter, J. G., Sun, R., Hu, Z., Ma, Z., Ding, J., Suarez, C. J., Tilk, S., Raghavendra, A., Forte, V., Chin, S., Bardwell, H., Provenzano, E., Caldas, C., Lang, J., West, R., Tripathy, D., Press, M. F., Curtis, C. 2019; 10
  • Publisher Correction: Clonal replacement and heterogeneity in breast tumors treated with neoadjuvant HER2-targeted therapy. Nature communications Caswell-Jin, J. L., McNamara, K. n., Reiter, J. G., Sun, R. n., Hu, Z. n., Ma, Z. n., Ding, J. n., Suarez, C. J., Tilk, S. n., Raghavendra, A. n., Forte, V. n., Chin, S. F., Bardwell, H. n., Provenzano, E. n., Caldas, C. n., Lang, J. n., West, R. n., Tripathy, D. n., Press, M. F., Curtis, C. n. 2019; 10 (1): 2433

    Abstract

    The original version of this Article omitted from the Author Contributions statement that 'R.S. and J.G.R contributed equally to this work.' This has been corrected in both the PDF and HTML versions of the Article.

    View details for DOI 10.1038/s41467-019-10456-x

    View details for PubMedID 31147552

  • Clonal replacement of tumor-specific T cells following PD-1 blockade. Nature medicine Yost, K. E., Satpathy, A. T., Wells, D. K., Qi, Y. n., Wang, C. n., Kageyama, R. n., McNamara, K. L., Granja, J. M., Sarin, K. Y., Brown, R. A., Gupta, R. K., Curtis, C. n., Bucktrout, S. L., Davis, M. M., Chang, A. L., Chang, H. Y. 2019

    Abstract

    Immunotherapies that block inhibitory checkpoint receptors on T cells have transformed the clinical care of patients with cancer1. However, whether the T cell response to checkpoint blockade relies on reinvigoration of pre-existing tumor-infiltrating lymphocytes or on recruitment of novel T cells remains unclear2-4. Here we performed paired single-cell RNA and T cell receptor sequencing on 79,046 cells from site-matched tumors from patients with basal or squamous cell carcinoma before and after anti-PD-1 therapy. Tracking T cell receptor clones and transcriptional phenotypes revealed coupling of tumor recognition, clonal expansion and T cell dysfunction marked by clonal expansion of CD8+CD39+ T cells, which co-expressed markers of chronic T cell activation and exhaustion. However, the expansion of T cell clones did not derive from pre-existing tumor-infiltrating T lymphocytes; instead, the expanded clones consisted of novel clonotypes that had not previously been observed in the same tumor. Clonal replacement of T cells was preferentially observed in exhausted CD8+ T cells and evident in patients with basal or squamous cell carcinoma. These results demonstrate that pre-existing tumor-specific T cells may have limited reinvigoration capacity, and that the T cell response to checkpoint blockade derives from a distinct repertoire of T cell clones that may have just recently entered the tumor.

    View details for DOI 10.1038/s41591-019-0522-3

    View details for PubMedID 31359002

  • Assessment of ERBB2/HER2 Status in HER2-Equivocal Breast Cancers by FISH and 2013/2014 ASCO-CAP Guidelines. JAMA oncology Press, M. F., Seoane, J. A., Curtis, C., Quinaux, E., Guzman, R., Sauter, G., Eiermann, W., Mackey, J. R., Robert, N., Pienkowski, T., Crown, J., Martin, M., Valero, V., Bee, V., Ma, Y., Villalobos, I., Slamon, D. J. 2018

    Abstract

    Importance: The 2013/2014 American Society of Clinical Oncology and College of American Pathologists (ASCO-CAP) guidelines for HER2 testing by fluorescence in situ hybridization (FISH) designated an "equivocal" category (average HER2 copies per tumor cell ≥4-6 with HER2/CEP17 ratio <2.0) to be resolved as negative or positive by assessments with alternative control probes. Approximately 4% to 12% of all invasive breast cancers are characterized as HER2-equivocal based on FISH.Objective: To evaluate the following hypotheses: (1) genetic loci used as alternative controls are heterozygously deleted in a substantial proportion of breast cancers; (2) use of these loci for assessment of HER2 by FISH leads to false-positive assessments; and (3) these HER2 false-positive breast cancer patients have outcomes that do not differ from clinical outcomes for patients with HER2-negative breast cancer.Design, Setting, and Participants: We retrospectively assessed the use of chromosome 17 p-arm and q-arm alternative control genomic sites (TP53, D17S122, SMS, RARA, TOP2A), as recommended by the 2013/2014 ASCO-CAP guidelines for HER2 testing, in patients whose data were available through Molecular Taxonomy of Breast Cancer International Consortium (METABRIC) and whose tissues were available through the Breast Cancer International Research Group clinical trials. We used data from an international cohort database of invasive breast cancers (1980 participants) and international clinical trial of adjuvant chemotherapy in invasive, node-positive breast cancer patients.Main Outcomes and Measures: The primary objectives were to (1) assess frequency of heterozygous deletions in chromosome 17 genomic sites used as FISH internal controls for evaluation of HER2 status among HER2-equivocal cancers; (2) characterize impact of using deleted sites for determination of HER2-to-internal-control-gene ratios; (3) assess HER2 protein expression in each subgroup; and (4) compare clinical outcomes for each subgroup.Results: Of the 1980 patients in METABRIC,1915 patients were fully evaluated. In addition, 100 HER2-equivocal breast cancers by FISH and 100 comparator FISH-negative breast cancers from the BCIRG-005 trial were analyzed. Heterozygous deletions, particularly in specific p-arm sites, were common in both HER2-amplified and HER2-not-amplified breast cancers. Use of alternative control probes from these regions to assess HER2 by FISH in HER2-equivocal as well as HER2-not-amplified breast cancers resulted in high rates of false-positive ratios (HER2-to-alternative control ratio ≥2.0) owing to heterozygous deletions of control p-arm genomic sites used in ratio denominators. Misclassification of HER2 status was observed not only in breast cancers with ASCO-CAP equivocal status but also in breast cancers with an average of fewer than 4.0 HER2 copies per tumor cell when using alternative control probes.Conclusions and Relevance: The indiscriminate use of alternative control probes to calculate HER2 FISH ratios in HER2-equivocal breast cancers may lead to false-positive interpretations of HER2 status resulting from unrecognized heterozygous deletions in 1 or more of these alternative control genomic sites and incorrect HER2 ratio determinations.

    View details for PubMedID 30520947

  • Tumor Molecular Profiling Aids in Determining Tissue of Origin and Therapy for Metastatic Adenocarcinoma in a Patient With Multiple Primary Malignancies. JCO precision oncology Costa, H. A., Reyes, R., Mills, M., Zehnder, J. L., Sledge, G., Curtis, C., Ford, J. M., Suarez, C. J. 2018; 2: 1-4

    View details for DOI 10.1200/PO.18.00177

    View details for PubMedID 35135146

  • Tumor Molecular Profiling Aids in Determining Tissue of Origin and Therapy for Metastatic Adenocarcinoma in a Patient With Multiple Primary Malignancies JCO PRECISION ONCOLOGY Costa, H. A., Reyes, R., Mills, M., Zehnder, J. L., Sledge, G., Curtis, C., Ford, J. M., Suarez, C. J. 2018; 2
  • A role for chromatin regulatory dynamics in breast cancer evolution. Nature medicine Probert, C., Curtis, C. 2018

    View details for PubMedID 30177822

  • Quantification of subclonal selection in cancer from bulk sequencing data (vol 50, pg 895, 2018) NATURE GENETICS Williams, M. J., Werner, B., Heide, T., Curtis, C., Barnes, C. P., Sottoriva, A., Graham, T. A. 2018; 50 (9): 1342

    Abstract

    In the version of this article originally published, in the "Theoretical framework of subclonal selection" section of the main text, ref. 11 instead of ref. 19 should have been cited at the end of the phrase "Our previously presented frequentist approach to detect subclonal selection from bulk sequencing data involves an R2 test statistic." The error has been corrected in the HTML and PDF versions of the article.

    View details for PubMedID 30022114

  • A role for chromatin regulatory dynamics in breast cancer evolution NATURE MEDICINE Probert, C., Curtis, C. 2018; 24 (9): 1309-1311
  • Harnessing Tumor Evolution to Circumvent Resistance TRENDS IN GENETICS Pogrebniak, K. L., Curtis, C. 2018; 34 (8): 639-651
  • Development of plasma cell-free DNA (cfDNA) assays for early cancer detection: first insights from the Circulating Cell-Free Genome Atlas Study (CCGA) Aravanis, A. A., Oxnard, G. R., Maddala, T., Hubbell, E., Venn, O., Jamshidi, A., Shen, L., Amini, H., Beausang, J. A., Betts, C., Civello, D., Davydov, K., Fazullina, S., Filippova, D., Gnerre, S., Gross, S., Hou, C., Jiang, R., Jung, B., Kurtzman, K., Melton, C., Nautiyal, S., Newman, J., Newman, J., Nicolaou, C., Rava, R., Sakarya, O., Satya, R., Shojaee, S., Steffen, K., Valouev, A., Xu, H., Yue, J., Zhang, N., Baselga, J., Lapham, R., Davis, D. G., Smith, D., Richards, D., Seiden, M. V., Swanton, C., Yeatman, T. J., Tibshirani, R., Curtis, C., Plevritis, S. K., Williams, R., Klein, E., Hartman, A., Liu, M. C. AMER ASSOC CANCER RESEARCH. 2018
  • Higher Absolute Lymphocyte Counts Predict Lower Mortality from Early-Stage Triple-Negative Breast Cancer CLINICAL CANCER RESEARCH Afghahi, A., Purington, N., Han, S. S., Desai, M., Pierson, E., Mathur, M. B., Seto, T., Thompson, C. A., Rigdon, J., Telli, M. L., Badve, S. S., Curtis, C. N., West, R. B., Horst, K., Gomez, S. L., Ford, J. M., Sledge, G. W., Kurian, A. W. 2018; 24 (12): 2851–58
  • Harnessing Tumor Evolution to Circumvent Resistance. Trends in genetics : TIG Pogrebniak, K. L., Curtis, C. 2018

    Abstract

    High-throughput sequencing can be used to measure changes in tumor composition across space and time. Specifically, comparisons of pre- and post-treatment samples can reveal the underlying clonal dynamics and resistance mechanisms. Here, we discuss evidence for distinct modes of tumor evolution and their implications for therapeutic strategies. In addition, we consider the utility of spatial tissue sampling schemes, single-cell analysis, and circulating tumor DNA to track tumor evolution and the emergence of resistance, as well as approaches that seek to forestall resistance by targeting tumor evolution. Ultimately, characterization of the (epi)genomic, transcriptomic, and phenotypic changes that occur during tumor progression coupled with computational and mathematical modeling of tumor evolutionary dynamics may inform personalized treatment strategies.

    View details for PubMedID 29903534

  • Quantification of subclonal selection in cancer from bulk sequencing data NATURE GENETICS Williams, M. J., Werner, B., Heide, T., Curtis, C., Barnes, C. P., Sottoriva, A., Graham, T. A. 2018; 50 (6): 895-+

    Abstract

    Subclonal architectures are prevalent across cancer types. However, the temporal evolutionary dynamics that produce tumor subclones remain unknown. Here we measure clone dynamics in human cancers by using computational modeling of subclonal selection and theoretical population genetics applied to high-throughput sequencing data. Our method determined the detectable subclonal architecture of tumor samples and simultaneously measured the selective advantage and time of appearance of each subclone. We demonstrate the accuracy of our approach and the extent to which evolutionary dynamics are recorded in the genome. Application of our method to high-depth sequencing data from breast, gastric, blood, colon and lung cancer samples, as well as metastatic deposits, showed that detectable subclones under selection, when present, consistently emerged early during tumor growth and had a large fitness advantage (>20%). Our quantitative framework provides new insight into the evolutionary trajectories of human cancers and facilitates predictive measurements in individual tumors from widely available sequencing data.

    View details for PubMedID 29808029

  • Promoter of lncRNA Gene PVT1 Is a Tumor-Suppressor DNA Boundary Element. Cell Cho, S. W., Xu, J., Sun, R., Mumbach, M. R., Carter, A. C., Chen, Y. G., Yost, K. E., Kim, J., He, J., Nevins, S. A., Chin, S., Caldas, C., Liu, S. J., Horlbeck, M. A., Lim, D. A., Weissman, J. S., Curtis, C., Chang, H. Y. 2018; 173 (6): 1398

    Abstract

    Noncoding mutations in cancer genomes are frequentbut challenging to interpret. PVT1 encodes an oncogenic lncRNA, but recurrent translocations and deletions in human cancers suggest alternative mechanisms. Here, we show that the PVT1 promoter has a tumor-suppressor function that is independent of PVT1 lncRNA. CRISPR interference of PVT1 promoter enhances breast cancer cell competition and growth invivo. The promoters of the PVT1 and the MYC oncogenes, located 55 kb apart on chromosome 8q24, compete for engagement with four intragenic enhancers in the PVT1 locus, thereby allowing the PVT1 promoter to regulate pause release of MYC transcription. PVT1 undergoes developmentally regulated monoallelic expression, and the PVT1 promoter inhibits MYC expression only from the same chromosome via promoter competition. Cancer genome sequencing identifies recurrent mutations encompassing the human PVT1 promoter, and genome editing verified that PVT1 promoter mutation promotes cancer cell growth. These results highlight regulatory sequences of lncRNA genes as potential disease-associated DNA elements.

    View details for PubMedID 29731168

  • AGBT meeting report GENOME BIOLOGY Bhatt, A. S., Curtis, C. 2018; 19: 60

    Abstract

    The Annual Advances in Genome Biology and Technology (AGBT) General Meeting was held in Orlando, Florida, USA, on the 12-15 February 2018. Professors Ami S. Bhatt and Christina Curtis from Stanford University, USA, report advances and applications in the field that were discussed at the meeting.

    View details for PubMedID 29784033

  • Breast cancer cell-free DNA (cfDNA) profiles reflect underlying tumor biology: The Circulating Cell-Free Genome Atlas (CCGA) study Liu, M. C., Maddala, T., Aravanis, A., Hubbell, E., Beausang, J. F., Filippova, D., Gross, S., Jamshidi, A., Kurtzman, K., Shen, L., Valouev, A., Venn, O., Zhang, N., Smith, D. A., Couch, F., Curtis, C., Williams, R., Klein, E. A., Hartman, A., Baselga, J. AMER SOC CLINICAL ONCOLOGY. 2018
  • Big Bang Tumor Growth and Clonal Evolution. Cold Spring Harbor perspectives in medicine Sun, R., Hu, Z., Curtis, C. 2018; 8 (5)

    Abstract

    The advent and application of next-generation sequencing (NGS) technologies to tumor genomes has reinvigorated efforts to understand clonal evolution. Although tumor progression has traditionally been viewed as a gradual stepwise process, recent studies suggest that evolutionary rates in tumors can be variable with periods of punctuated mutational bursts and relative stasis. For example, Big Bang dynamics have been reported, wherein after transformation, growth occurs in the absence of stringent selection, consistent with effectively neutral evolution. Although first noted in colorectal tumors, effective neutrality may be relatively common. Additionally, punctuated evolution resulting from mutational bursts and cataclysmic genomic alterations have been described. In this review, we contrast these findings with the conventional gradualist view of clonal evolution and describe potential clinical and therapeutic implications of different evolutionary modes and tempos.

    View details for PubMedID 28710260

  • Big Bang Tumor Growth and Clonal Evolution COLD SPRING HARBOR PERSPECTIVES IN MEDICINE Sun, R., Hu, Z., Curtis, C. 2018; 8 (5)
  • Organoids reveal cancer dynamics NATURE Kuo, C. J., Curtis, C. 2018; 556 (7702): 441–42

    View details for Web of Science ID 000430793000032

    View details for PubMedID 29686366

  • Mapping the in vivo fitness landscape of lung adenocarcinoma tumor suppression in mice NATURE GENETICS Rogers, Z. N., McFarland, C. D., Winters, I. P., Seoane, J. A., Brady, J. J., Yoon, S., Curtis, C., Petrov, D. A., Winslow, M. M. 2018; 50 (4): 483-+

    Abstract

    The functional impact of most genomic alterations found in cancer, alone or in combination, remains largely unknown. Here we integrate tumor barcoding, CRISPR/Cas9-mediated genome editing and ultra-deep barcode sequencing to interrogate pairwise combinations of tumor suppressor alterations in autochthonous mouse models of human lung adenocarcinoma. We map the tumor suppressive effects of 31 common lung adenocarcinoma genotypes and identify a landscape of context dependence and differential effect strengths.

    View details for PubMedID 29610476

  • Identification and validation of a novel drug target in an organoid model of esophageal cancer. Shukla, N., Salahudeen, A., de la O, S., Hart, D., Taylor, G., Zhu, J., Yuki, K., Seoane, J., Ma, Z., Ding, J., Han, K., Morgens, D., Bassik, M., Curtis, C., Kuo, C. AMER SOC CLINICAL ONCOLOGY. 2018
  • Higher Absolute Lymphocyte Counts Predict Lower Mortality from Early-Stage Triple-Negative Breast Cancer. Clinical cancer research : an official journal of the American Association for Cancer Research Afghahi, A. n., Purington, N. n., Han, S. S., Desai, M. n., Pierson, E. n., Mathur, M. B., Seto, T. n., Thompson, C. A., Rigdon, J. n., Telli, M. L., Badve, S. S., Curtis, C. n., West, R. B., Horst, K. n., Gomez, S. L., Ford, J. M., Sledge, G. W., Kurian, A. W. 2018

    Abstract

    Tumor-infiltrating lymphocytes (TILs) in pre-treatment biopsies are associated with improved survival in triple-negative breast cancer (TNBC). We investigated whether higher peripheral lymphocyte counts are associated with lower breast cancer-specific mortality (BCM) and overall mortality (OM) in TNBC.Data on treatments and diagnostic tests from electronic medical records of two healthcare systems were linked with demographic, clinical, pathologic, and mortality data from the California Cancer Registry. Multivariable regression models adjusted for age, race/ethnicity, socioeconomic status, cancer stage, grade, neoadjuvant/adjuvant chemotherapy use, radiotherapy use, and germline BRCA1/2 mutations were used to evaluate associations between absolute lymphocyte count (ALC), BCM and OM. For a subgroup with TILs data available, we explored the relationship between TILs and peripheral lymphocyte counts.1,463 Stage I-III TNBC patients were diagnosed from 2000-2014; 1113 (76%) received neoadjuvant/adjuvant chemotherapy within one year of diagnosis. Of 759 patients with available ALC data, 481 (63.4%) were ever lymphopenic (minimum ALC <1.0 K/μL). On multivariable analysis, higher minimum ALC, but not absolute neutrophil count, predicted lower OM (hazard ratio [HR]: 0.23, 95% confidence interval [CI]: 0.16-0.35) and BCM (HR: 0.19, CI: 0.11-0.34). Five-year probability of BCM was 15% for patients who were ever lymphopenic versus 4% for those who were not. An exploratory analysis (N=70) showed a significant association between TILs and higher peripheral lymphocyte counts during neoadjuvant chemotherapy.Higher peripheral lymphocyte counts predicted lower mortality from early-stage, potentially curable TNBC, suggesting that immune function may enhance the effectiveness of early TNBC treatment.

    View details for PubMedID 29581131

  • Intestinal Enteroendocrine Lineage Cells Possess Homeostatic and Injury-Inducible Stem Cell Activity. Cell stem cell Yan, K. S., Gevaert, O., Zheng, G. X., Anchang, B., Probert, C. S., Larkin, K. A., Davies, P. S., Cheng, Z. F., Kaddis, J. S., Han, A., Roelf, K., Calderon, R. I., Cynn, E., Hu, X., Mandleywala, K., Wilhelmy, J., Grimes, S. M., Corney, D. C., Boutet, S. C., Terry, J. M., Belgrader, P., Ziraldo, S. B., Mikkelsen, T. S., Wang, F., von Furstenberg, R. J., Smith, N. R., Chandrakesan, P., May, R., Chrissy, M. A., Jain, R., Cartwright, C. A., Niland, J. C., Hong, Y. K., Carrington, J., Breault, D. T., Epstein, J., Houchen, C. W., Lynch, J. P., Martin, M. G., Plevritis, S. K., Curtis, C., Ji, H. P., Li, L., Henning, S. J., Wong, M. H., Kuo, C. J. 2017; 21 (1): 78-90.e6

    Abstract

    Several cell populations have been reported to possess intestinal stem cell (ISC) activity during homeostasis and injury-induced regeneration. Here, we explored inter-relationships between putative mouse ISC populations by comparative RNA-sequencing (RNA-seq). The transcriptomes of multiple cycling ISC populations closely resembled Lgr5+ISCs, the most well-defined ISC pool, but Bmi1-GFP+cells were distinct and enriched for enteroendocrine (EE) markers, including Prox1. Prox1-GFP+cells exhibited sustained clonogenic growth in vitro, and lineage-tracing of Prox1+cells revealed long-lived clones during homeostasis and after radiation-induced injury in vivo. Single-cell mRNA-seq revealed two subsets of Prox1-GFP+cells, one of which resembled mature EE cells while the other displayed low-level EE gene expression but co-expressed tuft cell markers, Lgr5 and Ascl2, reminiscent of label-retaining secretory progenitors. Our data suggest that the EE lineage, including mature EE cells, comprises a reservoir of homeostatic and injury-inducible ISCs, extending our understanding of cellular plasticity and stemness.

    View details for DOI 10.1016/j.stem.2017.06.014

    View details for PubMedID 28686870

    View details for PubMedCentralID PMC5642297

  • A population genetics perspective on the determinants of intra-tumor heterogeneity. Biochimica et biophysica acta Hu, Z., Sun, R., Curtis, C. 2017; 1867 (2): 109-126

    Abstract

    Cancer results from the acquisition of somatic alterations in a microevolutionary process that typically occurs over many years, much of which is occult. Understanding the evolutionary dynamics that are operative at different stages of progression in individual tumors might inform the earlier detection, diagnosis, and treatment of cancer. Although these processes cannot be directly observed, the resultant spatiotemporal patterns of genetic variation amongst tumor cells encode their evolutionary histories. Such intra-tumor heterogeneity is pervasive not only at the genomic level, but also at the transcriptomic, phenotypic, and cellular levels. Given the implications for precision medicine, the accurate quantification of heterogeneity within and between tumors has become a major focus of current research. In this review, we provide a population genetics perspective on the determinants of intra-tumor heterogeneity and approaches to quantify genetic diversity. We summarize evidence for different modes of evolution based on recent cancer genome sequencing studies and discuss emerging evolutionary strategies to therapeutically exploit tumor heterogeneity. This article is part of a Special Issue entitled: Evolutionary principles - heterogeneity in cancer?, edited by Dr. Robert A. Gatenby.

    View details for DOI 10.1016/j.bbcan.2017.03.001

    View details for PubMedID 28274726

  • Bayesian Network Inference Modeling Identifies TRIB1 as a Novel Regulator of Cell-Cycle Progression and Survival in Cancer Cells CANCER RESEARCH Gendelman, R., Xing, H., Mirzoeva, O. K., Sarde, P., Curtis, C., Feiler, H. S., McDonagh, P., Gray, J. W., Khalil, I., Korn, W. M. 2017; 77 (7): 1575-1585

    Abstract

    Molecular networks governing responses to targeted therapies in cancer cells are complex dynamic systems that demonstrate nonintuitive behaviors. We applied a novel computational strategy to infer probabilistic causal relationships between network components based on gene expression. We constructed a model comprised of an ensemble of networks using multidimensional data from cell line models of cell-cycle arrest caused by inhibition of MEK1/2. Through simulation of a reverse-engineered Bayesian network model, we generated predictions of G1-S transition. The model identified known components of the cell-cycle machinery, such as CCND1, CCNE2, and CDC25A, as well as revealed novel regulators of G1-S transition, IER2, TRIB1, TRIM27. Experimental validation of model predictions confirmed 10 of 12 predicted genes to have a role in G1-S progression. Further analysis showed that TRIB1 regulated the cyclin D1 promoter via NFκB and AP-1 sites and sensitized cells to TRAIL-induced apoptosis. In clinical specimens of breast cancer, TRIB1 levels correlated with expression of NFκB and its target genes (IL8, CSF2), and TRIB1 copy number and expression were predictive of clinical outcome. Together, our results establish a critical role of TRIB1 in cell cycle and survival that is mediated via the modulation of NFκB signaling. Cancer Res; 77(7); 1575-85. ©2017 AACR.

    View details for DOI 10.1158/0008-5472.CAN-16-0512

    View details for Web of Science ID 000398262400006

    View details for PubMedID 28087598

  • Genome co-amplification upregulates a mitotic gene network activity that predicts outcome and response to mitotic protein inhibitors in breast cancer (vol 18, pg 70, 2016) BREAST CANCER RESEARCH Hu, Z., Mao, J., Curtis, C., Huang, G., Gu, S., Heiser, L., Lenburg, M. E., Korkola, J. E., Bayani, N., Samarajiwa, S., Seoane, J. A., Dane, M. A., Esch, A., Feiler, H. S., Wang, N. J., Hardwicke, M., Laquerre, S., Jackson, J., Wood, K. W., Weber, B., Spellman, P. T., Aparicio, S., Wooster, R., Caldas, C., Gray, J. W. 2017; 19: 17

    View details for PubMedID 28183333

    View details for PubMedCentralID PMC5301377

  • Integrated genomic characterization of oesophageal carcinoma NATURE Kim, J., Bowlby, R., Mungall, A. J., Robertson, A. G., Odze, R. D., Cherniack, A. D., Shih, J., Pedamallu, C. S., Cibulskis, C., Dunford, A., Meier, S. R., Kim, J., Raphael, B. J., Wu, H., Wong, A. M., Willis, J. E., Bass, A. J., Derks, S., Garman, K., McCall, S. J., Wiznerowicz, M., Pantazi, A., Parfenov, M., Thorsson, V., Shmulevich, I., Dhankani, V., Miller, M., Sakai, R., Wang, K., Schultz, N., Shen, R., Arora, A., Weinhold, N., Sanchez-Vega, F., Kelsen, D. P., Zhang, J., Felau, I., Demchok, J., Rabkin, C. S., Camargo, M. C., Zenklusen, J. C., Bowen, J., Leraas, K., Lichtenberg, T. M., Curtis, C., Seoane, J. A., Ojesina, A. I., Beer, D. G., Gulley, M. L., Pennathur, A., Luketich, J. D., Zhou, Z., Weisenberger, D. J., Akbani, R., Lee, J., Liu, W., Mills, G. B., Zhang, W., Reid, B. J., Hinoue, T., Laird, P. W., Shen, H., Piazuelo, M. B., Schneider, B. G., McLellan, M., Taylor-Weiner, A., Cibulskis, C., Lawrence, M., Cibulskis, K., Stewart, C., Getz, G., Lander, E., Gabriel, S. B., Ding, L., McLellan, M. D., Miller, C. A., Appelbaum, E. L., Cordes, M. G., Fronick, C. C., Fulton, L. A., Mardis, E. R., Wilson, R. K., Schmidt, H. K., Fulton, R. S., Ally, A., Balasundaram, M., Bowlby, R., Carlsen, R., Chuah, E., Dhalla, N., Holt, R. A., Jones, S. J., Kasaian, K., Brooks, D., Li, H. I., Ma, Y., Marra, M. A., Mayo, M., Moore, R. A., Mungall, A. J., Mungall, K. L., Robertson, A. G., Schein, J. E., Sipahimalani, P., Tam, A., Thiessen, N., Wong, T., Cherniack, A. D., Shih, J., Pedamallu, C. S., Beroukhim, R., Bullman, S., Cibulskis, C., Murray, B. A., Saksena, G., Schumacher, S. E., Gabriel, S., Meyerson, M., Hadjipanayis, A., Kucherlapati, R., Pantazi, A., Parfenov, M., Ren, X., Park, P. J., Lee, S., Kucherlapati, M., Yang, L., Baylin, S. B., Hoadley, K. A., Weisenberger, D. J., Bootwalla, M. S., Lai, P. H., Van den Berg, D. J., Berrios, M., Holbrook, A., Akbani, R., Hwang, J., Jang, H., Liu, W., Weinstein, J. N., Lee, J., Lu, Y., Sohn, B. H., Mills, G., Seth, S., Protopopov, A., Bristow, C. A., Mahadeshwar, H. S., Tang, J., Song, X., Zhang, J., Laird, P. W., Hinoue, T., Shen, H., Cho, J., Defrietas, T., Frazer, S., Gehlenborg, N., Heiman, D. I., Lawrence, M. S., Lin, P., Meier, S. R., Noble, M. S., Doug Voet, D., Zhang, H., Kim, J., Polak, P., Saksena, G., Chin, L., Getz, G., Wong, A. M., Raphael, B. J., Wu, H., Lee, S., Park, P. J., Yang, L., Thorsson, V., Bernard, B., Iype, L., Miller, M., Reynolds, S. M., Shmulevich, I., Dhankani, V., Abeshouse, A., Arora, A., Armenia, J., Kundra, R., Ladanyi, M., Kjong-Van Lehmann, Gao, J., Sander, C., Schultz, N., Sanchez-Vega, F., Shen, R., Weinhold, N., Chakravarty, D., Zhang, H., Radenbaugh, A., Hegde, A., Akbani, R., Liu, W., Weinstein, J. N., Chin, L., Bristow, C. A., Lu, Y., Penny, R., Crain, D., Gardner, J., Curley, E., Mallery, D., Morris, S., Paulauskis, J., Shelton, T., Shelton, C., Bowen, J., Frick, J., Gastier-Foster, J. M., Gerken, M., Leraas, K. M., Lichtenberg, T. M., Ramirez, N. C., Wise, L., Zmuda, E., Tarvin, K., Saller, C., Park, Y. S., Button, M., Carvalho, A. L., Reis, R. M., Matsushita, M. M., Lucchesi, F., de Oliveira, A. T., Le, X., Paklina, O., Setdikova, G., Lee, J., Bennett, J., Iacocca, M., Huelsenbeck-Dill, L., Potapova, C. O., Voronina, O., Liu, O., Fulidou, V., Cates, C., Sharp, A., Behera, M., Force, S., Khuri, F., Owonikoko, T., Pickens, A., Ramalingam, S., Sica, G., Dinjens, W., van Nistelrooij, A., Wijnhoven, B., Sandusky, G., Stepa, S., Crain, D., Paulauskis, J., Penny, R., Gardner, J., Mallery, D., Morris, S., Shelton, T., Shelton, C., Curley, E., Juhl, I. H., Zornig, C., Kwon, S. Y., Kelsen, D., Kim, G. H., Bartlett, J., Parfitt, J., Chetty, R., Darling, G., Knox, J., Wong, R., El-Zimaity, H., Liu, G., Boussioutas, A., Park, D. Y., Kemp, R., Carlotti, C. G., da Cunha Tirapelli, D. P., Saggioro, F. P., Sankarankutty, A. K., Noushmehr, H., dos Santos, J. S., Trevisan, F. A., Eschbacher, J., Eschbacher, J., Dubina, M., Mozgovoy, E., Carey, F., Chalmers, S., Forgie, I., Godwin, A., Reilly, C., Madan, R., Naima, Z., Ferrer-Torres, D., Rathmell, W. K., Dhir, R., Luketich, J., Pennathur, A., Ajani, J. A., McCall, S. J., Janjigian, Y., Kelsen, D., Ladanyi, M., Tang, L., Camargo, M. C., Ajani, J. A., Cheong, J., Chudamani, S., Liu, J., Lolla, L., Naresh, R., Pihl, T., Sun, Q., Wan, Y., Wu, Y., Demchok, J. A., Felau, I., Ferguson, M. L., Shaw, K. R., Sheth, M., Tarnuzzer, R., Wang, Z., Yang, L., Zenklusen, J. C., Hutter, C. M., Sofia, H. J., Zhang, J. 2017; 541 (7636): 169-?

    Abstract

    Oesophageal cancers are prominent worldwide; however, there are few targeted therapies and survival rates for these cancers remain dismal. Here we performed a comprehensive molecular analysis of 164 carcinomas of the oesophagus derived from Western and Eastern populations. Beyond known histopathological and epidemiologic distinctions, molecular features differentiated oesophageal squamous cell carcinomas from oesophageal adenocarcinomas. Oesophageal squamous cell carcinomas resembled squamous carcinomas of other organs more than they did oesophageal adenocarcinomas. Our analyses identified three molecular subclasses of oesophageal squamous cell carcinomas, but none showed evidence for an aetiological role of human papillomavirus. Squamous cell carcinomas showed frequent genomic amplifications of CCND1 and SOX2 and/or TP63, whereas ERBB2, VEGFA and GATA4 and GATA6 were more commonly amplified in adenocarcinomas. Oesophageal adenocarcinomas strongly resembled the chromosomally unstable variant of gastric adenocarcinoma, suggesting that these cancers could be considered a single disease entity. However, some molecular features, including DNA hypermethylation, occurred disproportionally in oesophageal adenocarcinomas. These data provide a framework to facilitate more rational categorization of these tumours and a foundation for new therapies.

    View details for DOI 10.1038/nature20805

    View details for Web of Science ID 000396125500030

    View details for PubMedID 28052061

  • Integrated genomic characterization of oesophageal carcinoma NATURE Kim, J., Bowlby, R., Mungall, A. J., Robertson, A. G., Odze, R. D., Cherniack, A. D., Shih, J., Pedamallu, C. S., Cibulskis, C., Dunford, A., Meier, S. R., Kim, J., Raphael, B. J., Wu, H., Wong, A. M., Willis, J. E., Bass, A. J., Derks, S., Garman, K., McCall, S. J., Wiznerowicz, M., Pantazi, A., Parfenov, M., Thorsson, V., Shmulevich, I., Dhankani, V., Miller, M., Sakai, R., Wang, K., Schultz, N., Shen, R., Arora, A., Weinhold, N., Sanchez-Vega, F., Kelsen, D. P., Zhang, J., Felau, I., Demchok, J., Rabkin, C. S., Camargo, M. C., Zenklusen, J. C., Bowen, J., Leraas, K., Lichtenberg, T. M., Curtis, C., Seoane, J. A., Ojesina, A. I., Beer, D. G., Gulley, M. L., Pennathur, A., Luketich, J. D., Zhou, Z., Weisenberger, D. J., Akbani, R., Lee, J., Liu, W., Mills, G. B., Zhang, W., Reid, B. J., Hinoue, T., Laird, P. W., Shen, H., Piazuelo, M. B., Schneider, B. G., McLellan, M., Taylor-Weiner, A., Cibulskis, C., Lawrence, M., Cibulskis, K., Stewart, C., Getz, G., Lander, E., Gabriel, S. B., Ding, L., McLellan, M. D., Miller, C. A., Appelbaum, E. L., Cordes, M. G., Fronick, C. C., Fulton, L. A., Mardis, E. R., Wilson, R. K., Schmidt, H. K., Fulton, R. S., Ally, A., Balasundaram, M., Bowlby, R., Carlsen, R., Chuah, E., Dhalla, N., Holt, R. A., Jones, S. J., Kasaian, K., Brooks, D., Li, H. I., Ma, Y., Marra, M. A., Mayo, M., Moore, R. A., Mungall, A. J., Mungall, K. L., Robertson, A. G., Schein, J. E., Sipahimalani, P., Tam, A., Thiessen, N., Wong, T., Cherniack, A. D., Shih, J., Pedamallu, C. S., Beroukhim, R., Bullman, S., Cibulskis, C., Murray, B. A., Saksena, G., Schumacher, S. E., Gabriel, S., Meyerson, M., Hadjipanayis, A., Kucherlapati, R., Pantazi, A., Parfenov, M., Ren, X., Park, P. J., Lee, S., Kucherlapati, M., Yang, L., Baylin, S. B., Hoadley, K. A., Weisenberger, D. J., Bootwalla, M. S., Lai, P. H., Van den Berg, D. J., Berrios, M., Holbrook, A., Akbani, R., Hwang, J., Jang, H., Liu, W., Weinstein, J. N., Lee, J., Lu, Y., Sohn, B. H., Mills, G., Seth, S., Protopopov, A., Bristow, C. A., Mahadeshwar, H. S., Tang, J., Song, X., Zhang, J., Laird, P. W., Hinoue, T., Shen, H., Cho, J., Defrietas, T., Frazer, S., Gehlenborg, N., Heiman, D. I., Lawrence, M. S., Lin, P., Meier, S. R., Noble, M. S., Doug Voet, D., Zhang, H., Kim, J., Polak, P., Saksena, G., Chin, L., Getz, G., Wong, A. M., Raphael, B. J., Wu, H., Lee, S., Park, P. J., Yang, L., Thorsson, V., Bernard, B., Iype, L., Miller, M., Reynolds, S. M., Shmulevich, I., Dhankani, V., Abeshouse, A., Arora, A., Armenia, J., Kundra, R., Ladanyi, M., Kjong-Van Lehmann, Gao, J., Sander, C., Schultz, N., Sanchez-Vega, F., Shen, R., Weinhold, N., Chakravarty, D., Zhang, H., Radenbaugh, A., Hegde, A., Akbani, R., Liu, W., Weinstein, J. N., Chin, L., Bristow, C. A., Lu, Y., Penny, R., Crain, D., Gardner, J., Curley, E., Mallery, D., Morris, S., Paulauskis, J., Shelton, T., Shelton, C., Bowen, J., Frick, J., Gastier-Foster, J. M., Gerken, M., Leraas, K. M., Lichtenberg, T. M., Ramirez, N. C., Wise, L., Zmuda, E., Tarvin, K., Saller, C., Park, Y. S., Button, M., Carvalho, A. L., Reis, R. M., Matsushita, M. M., Lucchesi, F., de Oliveira, A. T., Le, X., Paklina, O., Setdikova, G., Lee, J., Bennett, J., Iacocca, M., Huelsenbeck-Dill, L., Potapova, C. O., Voronina, O., Liu, O., Fulidou, V., Cates, C., Sharp, A., Behera, M., Force, S., Khuri, F., Owonikoko, T., Pickens, A., Ramalingam, S., Sica, G., Dinjens, W., van Nistelrooij, A., Wijnhoven, B., Sandusky, G., Stepa, S., Crain, D., Paulauskis, J., Penny, R., Gardner, J., Mallery, D., Morris, S., Shelton, T., Shelton, C., Curley, E., Juhl, I. H., Zornig, C., Kwon, S. Y., Kelsen, D., Kim, G. H., Bartlett, J., Parfitt, J., Chetty, R., Darling, G., Knox, J., Wong, R., El-Zimaity, H., Liu, G., Boussioutas, A., Park, D. Y., Kemp, R., Carlotti, C. G., da Cunha Tirapelli, D. P., Saggioro, F. P., Sankarankutty, A. K., Noushmehr, H., dos Santos, J. S., Trevisan, F. A., Eschbacher, J., Eschbacher, J., Dubina, M., Mozgovoy, E., Carey, F., Chalmers, S., Forgie, I., Godwin, A., Reilly, C., Madan, R., Naima, Z., Ferrer-Torres, D., Rathmell, W. K., Dhir, R., Luketich, J., Pennathur, A., Ajani, J. A., McCall, S. J., Janjigian, Y., Kelsen, D., Ladanyi, M., Tang, L., Camargo, M. C., Ajani, J. A., Cheong, J., Chudamani, S., Liu, J., Lolla, L., Naresh, R., Pihl, T., Sun, Q., Wan, Y., Wu, Y., Demchok, J. A., Felau, I., Ferguson, M. L., Shaw, K. R., Sheth, M., Tarnuzzer, R., Wang, Z., Yang, L., Zenklusen, J. C., Hutter, C. M., Sofia, H. J., Zhang, J. 2017; 541 (7636): 169-?

    Abstract

    Oesophageal cancers are prominent worldwide; however, there are few targeted therapies and survival rates for these cancers remain dismal. Here we performed a comprehensive molecular analysis of 164 carcinomas of the oesophagus derived from Western and Eastern populations. Beyond known histopathological and epidemiologic distinctions, molecular features differentiated oesophageal squamous cell carcinomas from oesophageal adenocarcinomas. Oesophageal squamous cell carcinomas resembled squamous carcinomas of other organs more than they did oesophageal adenocarcinomas. Our analyses identified three molecular subclasses of oesophageal squamous cell carcinomas, but none showed evidence for an aetiological role of human papillomavirus. Squamous cell carcinomas showed frequent genomic amplifications of CCND1 and SOX2 and/or TP63, whereas ERBB2, VEGFA and GATA4 and GATA6 were more commonly amplified in adenocarcinomas. Oesophageal adenocarcinomas strongly resembled the chromosomally unstable variant of gastric adenocarcinoma, suggesting that these cancers could be considered a single disease entity. However, some molecular features, including DNA hypermethylation, occurred disproportionally in oesophageal adenocarcinomas. These data provide a framework to facilitate more rational categorization of these tumours and a foundation for new therapies.

    View details for DOI 10.1038/nature20805

    View details for Web of Science ID 000396125500030

    View details for PubMedID 28052061

  • A p53 Super-tumor Suppressor Reveals a Tumor Suppressive p53-Ptpn14-Yap Axis in Pancreatic Cancer. Cancer cell Mello, S. S., Valente, L. J., Raj, N. n., Seoane, J. A., Flowers, B. M., McClendon, J. n., Bieging-Rolett, K. T., Lee, J. n., Ivanochko, D. n., Kozak, M. M., Chang, D. T., Longacre, T. A., Koong, A. C., Arrowsmith, C. H., Kim, S. K., Vogel, H. n., Wood, L. D., Hruban, R. H., Curtis, C. n., Attardi, L. D. 2017; 32 (4): 460–73.e6

    Abstract

    The p53 transcription factor is a critical barrier to pancreatic cancer progression. To unravel mechanisms of p53-mediated tumor suppression, which have remained elusive, we analyzed pancreatic cancer development in mice expressing p53 transcriptional activation domain (TAD) mutants. Surprisingly, the p5353,54 TAD2 mutant behaves as a "super-tumor suppressor," with an enhanced capacity to both suppress pancreatic cancer and transactivate select p53 target genes, including Ptpn14. Ptpn14 encodes a negative regulator of the Yap oncoprotein and is necessary and sufficient for pancreatic cancer suppression, like p53. We show that p53 deficiency promotes Yap signaling and that PTPN14 and TP53 mutations are mutually exclusive in human cancers. These studies uncover a p53-Ptpn14-Yap pathway that is integral to p53-mediated tumor suppression.

    View details for PubMedID 29017057

  • Early mutation bursts in colorectal tumors. PloS one Zhao, J., Salomon, M. P., Shibata, D., Curtis, C., Siegmund, K., Marjoram, P. 2017; 12 (3)

    Abstract

    Tumor growth is an evolutionary process involving accumulation of mutations, copy number alterations, and cancer stem cell (CSC) division and differentiation. As direct observation of this process is impossible, inference regarding when mutations occur and how stem cells divide is difficult. However, this ancestral information is encoded within the tumor itself, in the form of intratumoral heterogeneity of the tumor cell genomes. Here we present a framework that allows simulation of these processes and estimation of mutation rates at the various stages of tumor development and CSC division patterns for single-gland sequencing data from colorectal tumors. We parameterize the mutation rate and the CSC division pattern, and successfully retrieve their posterior distributions based on DNA sequence level data. Our approach exploits Approximate Bayesian Computation (ABC), a method that is becoming widely-used for problems of ancestral inference.

    View details for DOI 10.1371/journal.pone.0172516

    View details for PubMedID 28257429

    View details for PubMedCentralID PMC5336211

  • Intestinal Enteroendocrine Lineage Cells Possess Homeostatic and Injury-Inducible Stem Cell Activity Cell Stem Cell Yan, K., Gevaert, O., Zheng, G., Anchang, B., Probert, C., et al 2017; 21 (1): 78 - 90.e6

    Abstract

    Several cell populations have been reported to possess intestinal stem cell (ISC) activity during homeostasis and injury-induced regeneration. Here, we explored inter-relationships between putative mouse ISC populations by comparative RNA-sequencing (RNA-seq). The transcriptomes of multiple cycling ISC populations closely resembled Lgr5+ISCs, the most well-defined ISC pool, but Bmi1-GFP+cells were distinct and enriched for enteroendocrine (EE) markers, including Prox1. Prox1-GFP+cells exhibited sustained clonogenic growth in vitro, and lineage-tracing of Prox1+cells revealed long-lived clones during homeostasis and after radiation-induced injury in vivo. Single-cell mRNA-seq revealed two subsets of Prox1-GFP+cells, one of which resembled mature EE cells while the other displayed low-level EE gene expression but co-expressed tuft cell markers, Lgr5 and Ascl2, reminiscent of label-retaining secretory progenitors. Our data suggest that the EE lineage, including mature EE cells, comprises a reservoir of homeostatic and injury-inducible ISCs, extending our understanding of cellular plasticity and stemness.

    View details for DOI 10.1016/j.stem.2017.06.014

    View details for PubMedCentralID PMC5642297

  • Inferring Tumor Phylogenies from Multi-region Sequencing. Cell systems Hu, Z., Curtis, C. 2016; 3 (1): 12-14

    Abstract

    A new computational method illuminates the heterogeneity and evolutionary histories of cells within a tumor.

    View details for DOI 10.1016/j.cels.2016.07.007

    View details for PubMedID 27467243

  • Genome co-amplification upregulates a mitotic gene network activity that predicts outcome and response to mitotic protein inhibitors in breast cancer BREAST CANCER RESEARCH Hu, Z., Mao, J., Curtis, C., Huang, G., Gu, S., Heiser, L., Lenburg, M. E., Korkola, J. E., Bayani, N., Samarajiwa, S., Seoane, J. A., Dane, M. A., Esch, A., Feiler, H. S., Wang, N. J., Hardwicke, M. A., Laquerre, S., Jackson, J., Wood, K. W., Weber, B., Spellman, P. T., Aparicio, S., Wooster, R., Caldas, C., Gray, J. W. 2016; 18

    Abstract

    High mitotic activity is associated with the genesis and progression of many cancers. Small molecule inhibitors of mitotic apparatus proteins are now being developed and evaluated clinically as anticancer agents. With clinical trials of several of these experimental compounds underway, it is important to understand the molecular mechanisms that determine high mitotic activity, identify tumor subtypes that carry molecular aberrations that confer high mitotic activity, and to develop molecular markers that distinguish which tumors will be most responsive to mitotic apparatus inhibitors.We identified a coordinately regulated mitotic apparatus network by analyzing gene expression profiles for 53 malignant and non-malignant human breast cancer cell lines and two separate primary breast tumor datasets. We defined the mitotic network activity index (MNAI) as the sum of the transcriptional levels of the 54 coordinately regulated mitotic apparatus genes. The effect of those genes on cell growth was evaluated by small interfering RNA (siRNA).High MNAI was enriched in basal-like breast tumors and was associated with reduced survival duration and preferential sensitivity to inhibitors of the mitotic apparatus proteins, polo-like kinase, centromere associated protein E and aurora kinase designated GSK462364, GSK923295 and GSK1070916, respectively. Co-amplification of regions of chromosomes 8q24, 10p15-p12, 12p13, and 17q24-q25 was associated with the transcriptional upregulation of this network of 54 mitotic apparatus genes, and we identify transcription factors that localize to these regions and putatively regulate mitotic activity. Knockdown of the mitotic network by siRNA identified 22 genes that might be considered as additional therapeutic targets for this clinically relevant patient subgroup.We define a molecular signature which may guide therapeutic approaches for tumors with high mitotic network activity.

    View details for DOI 10.1186/s13058-016-0728-y

    View details for Web of Science ID 000378898900001

    View details for PubMedCentralID PMC4930593

  • Higher peripheral lymphocyte count to predict survival in triple-negative breast cancer (TNBC). Afghahi, A., Rigdon, J., Purington, N., Desal, M., Pierson, E., Mathur, M., Thompson, C. A., Curtis, C., West, R. B., Horst, K. C., Gomez, S., Ford, J. M., Sledge, G. W., Kurian, A. W. AMER SOC CLINICAL ONCOLOGY. 2016
  • Genome co-amplification upregulates a mitotic gene network activity that predicts outcome and response to mitotic protein inhibitors in breast cancer. Breast cancer research Hu, Z., Mao, J., Curtis, C., Huang, G., Gu, S., Heiser, L., Lenburg, M. E., Korkola, J. E., Bayani, N., Samarajiwa, S., Seoane, J. A., A Dane, M., Esch, A., Feiler, H. S., Wang, N. J., Hardwicke, M. A., Laquerre, S., Jackson, J., W Wood, K., Weber, B., Spellman, P. T., Aparicio, S., Wooster, R., Caldas, C., Gray, J. W. 2016; 18 (1): 70-?

    Abstract

    High mitotic activity is associated with the genesis and progression of many cancers. Small molecule inhibitors of mitotic apparatus proteins are now being developed and evaluated clinically as anticancer agents. With clinical trials of several of these experimental compounds underway, it is important to understand the molecular mechanisms that determine high mitotic activity, identify tumor subtypes that carry molecular aberrations that confer high mitotic activity, and to develop molecular markers that distinguish which tumors will be most responsive to mitotic apparatus inhibitors.We identified a coordinately regulated mitotic apparatus network by analyzing gene expression profiles for 53 malignant and non-malignant human breast cancer cell lines and two separate primary breast tumor datasets. We defined the mitotic network activity index (MNAI) as the sum of the transcriptional levels of the 54 coordinately regulated mitotic apparatus genes. The effect of those genes on cell growth was evaluated by small interfering RNA (siRNA).High MNAI was enriched in basal-like breast tumors and was associated with reduced survival duration and preferential sensitivity to inhibitors of the mitotic apparatus proteins, polo-like kinase, centromere associated protein E and aurora kinase designated GSK462364, GSK923295 and GSK1070916, respectively. Co-amplification of regions of chromosomes 8q24, 10p15-p12, 12p13, and 17q24-q25 was associated with the transcriptional upregulation of this network of 54 mitotic apparatus genes, and we identify transcription factors that localize to these regions and putatively regulate mitotic activity. Knockdown of the mitotic network by siRNA identified 22 genes that might be considered as additional therapeutic targets for this clinically relevant patient subgroup.We define a molecular signature which may guide therapeutic approaches for tumors with high mitotic network activity.

    View details for DOI 10.1186/s13058-016-0728-y

    View details for PubMedID 27368372

    View details for PubMedCentralID PMC4930593

  • Inferring Tumor Phylogenies from Multi-region Sequencing Cell Systems Hu, Z., Curtis, C. 2016; 3 (1): 12-14

    Abstract

    A new computational method illuminates the heterogeneity and evolutionary histories of cells within a tumor.

    View details for DOI 10.1016/j.cels.2016.07.007

  • Understanding tumor heterogeneity in glioblastoma Tavare, S., Sottoriva, A., Piccirillo, S., Spiteri, I., Touloumis, A., Marioni, J. C., Curtis, C. N., Watts, C. AMER ASSOC CANCER RESEARCH. 2015
  • A Big Bang model of human colorectal tumor growth Sottoriva, A., Kang, H., Ma, Z., Graham, T. A., Salomon, M., Zhao, J., Marjoram, P., Siegmund, K., Press, M. F., Shibata, D., Curtis, C. AMER ASSOC CANCER RESEARCH. 2015
  • Many private mutations originate from the first few divisions of a human colorectal adenoma JOURNAL OF PATHOLOGY Kang, H., Salomon, M. P., Sottoriva, A., Zhao, J., Toy, M., Press, M. F., Curtis, C., Marjoram, P., Siegmund, K., Shibata, D. 2015; 237 (3): 355-362

    Abstract

    Intratumoural mutational heterogeneity (ITH) or the presence of different private mutations in different parts of the same tumour is commonly observed in human tumours. The mechanisms generating such ITH are uncertain. Here we find that ITH can be remarkably well structured by measuring point mutations, chromosome copy numbers, and DNA passenger methylation from opposite sides and individual glands of a 6 cm human colorectal adenoma. ITH was present between tumour sides and individual glands, but the private mutations were side-specific and subdivided the adenoma into two major subclones. Furthermore, ITH disappeared within individual glands because the glands were clonal populations composed of cells with identical mutant genotypes. Despite mutation clonality, the glands were relatively old, diverse populations when their individual cells were compared for passenger methylation and by FISH. These observations can be organized into an expanding star-like ancestral tree with co-clonal expansion, where many private mutations and multiple related clones arise during the first few divisions. As a consequence, most detectable mutational ITH in the final tumour originates from the first few divisions. Much of the early history of a tumour, especially the first few divisions, may be embedded within the detectable ITH of tumour genomes.

    View details for DOI 10.1002/path.4581

    View details for PubMedID 26119426

    View details for PubMedCentralID PMC4607608

  • Genomic profiling of breast cancers. Current opinion in obstetrics & gynecology Curtis, C. 2015; 27 (1): 34-39

    Abstract

    To describe recent advances in the application of advanced genomic technologies towards the identification of biomarkers of prognosis and treatment response in breast cancer.Advances in high-throughput genomic profiling such as massively parallel sequencing have enabled researchers to catalogue the spectrum of somatic alterations in breast cancers. These tools also hold promise for precision medicine through accurate patient prognostication, stratification, and the dynamic monitoring of treatment response. For example, recent efforts have defined robust molecular subgroups of breast cancer and novel subtype-specific oncogenes. In addition, previously unappreciated activating mutations in human epidermal growth factor receptor 2 have been reported, suggesting new therapeutic opportunities. Genomic profiling of cell-free tumor DNA and circulating tumor cells has been used to monitor disease burden and the emergence of resistance, and such 'liquid biopsy' approaches may facilitate the early, noninvasive detection of aggressive disease. Finally, single-cell genomics is coming of age and will contribute to an understanding of breast cancer evolutionary dynamics.Here, we highlight recent studies that employ high-throughput genomic technologies in an effort to elucidate breast cancer biology, discover new therapeutic targets, improve prognostication and stratification, and discuss the implications for precision cancer medicine.

    View details for DOI 10.1097/GCO.0000000000000145

    View details for PubMedID 25502431

  • Contributions to Drug Resistance in Glioblastoma Derived from Malignant Cells in the Sub-Ependymal Zone CANCER RESEARCH Piccirillo, S. G., Spiteri, I., Sottoriva, A., Touloumis, A., Ber, S., Price, S. J., Heywood, R., Francis, N., Howarth, K. D., Collins, V. P., Venkitaraman, A. R., Curtis, C., Marioni, J. C., Tavare, S., Watts, C. 2015; 75 (1): 194-202

    Abstract

    Glioblastoma, the most common and aggressive adult brain tumor, is characterized by extreme phenotypic diversity and treatment failure. Through fluorescence-guided resection, we identified fluorescent tissue in the sub-ependymal zone (SEZ) of patients with glioblastoma. Histologic analysis and genomic characterization revealed that the SEZ harbors malignant cells with tumor-initiating capacity, analogous to cells isolated from the fluorescent tumor mass (T). We observed resistance to supramaximal chemotherapy doses along with differential patterns of drug response between T and SEZ in the same tumor. Our results reveal novel insights into glioblastoma growth dynamics, with implications for understanding and limiting treatment resistance. Cancer Res; 75(1); 194-202. ©2014 AACR.

    View details for DOI 10.1158/0008-5472.CAN-13-3131

    View details for Web of Science ID 000347383000020

    View details for PubMedID 25406193

    View details for PubMedCentralID PMC4286248

  • Comprehensive molecular characterization of gastric adenocarcinoma NATURE Bass, A. J., Thorsson, V., Shmulevich, I., Reynolds, S. M., Miller, M., Bernard, B., Hinoue, T., Laird, P. W., Curtis, C., Shen, H., Weisenberger, D. J., Schultz, N., Shen, R., Weinhold, N., Keiser, D. P., Bowlby, R., Sipahimalani, P., Cherniack, A. D., Getz, G., Liu, Y., Noble, M. S., Pedamallu, C., Sougnez, C., Taylor-Weiner, A., Akbani, R., Lee, J., Liu, W., Mills, G. B., Yang, D., Zhang, W., Pantazi, A., Parfenov, M., Gulley, M., Piazuelo, M. B., Schneider, B. G., Kim, J., Boussioutas, A., Sheth, M., Demchok, J. A., Rabkin, C. S., Willis, J. E., Ng, S., Garman, K., Beer, D. G., Pennathur, A., Raphael, B. J., Wu, H., Odze, R., Kim, H. K., Bowen, J., Leraas, K. M., Lichtenberg, T. M., Weaver, L., McLellan, M., Wiznerowicz, M., Sakai, R., Getz, G., Sougnez, C., Lawrence, M. S., Cibulskis, K., Lichtenstein, L., Fisher, S., Gabriel, S. B., Lander, E. S., Ding, L., Niu, B., Ally, A., Balasundaram, M., Birol, I., Bowlby, R., Brooks, D., Butterfield, Y. S., Carlsen, R., Chu, A., Chu, J., Chuah, E., Chun, H. E., Clarke, A., Dhalla, N., Guin, R., Holt, R. A., Jones, S. J., Kasaian, K., Lee, D., Li, H. A., Lim, E., Ma, Y., Marra, M. A., Mayo, M., Moore, R. A., Mungall, A. J., Mungall, K. L., Nip, K. M., Robertson, A. G., Schein, J. E., Sipahimalani, P., Tam, A., Thiessen, N., Beroukhim, R., Carter, S. L., Cherniack, A. D., Cho, J., Cibulskis, K., DiCara, D., Frazer, S., Fisher, S., Gabriel, S. B., Gehlenborg, N., Heiman, D. I., Jung, J., Kim, J., Lander, E. S., Lawrence, M. S., Lichtenstein, L., Lin, P., Meyerson, M., Ojesina, A. I., Pedamallu, C. S., Saksena, G., Schumacher, S. E., Sougnez, C., Stojanov, P., Tabak, B., Taylor-Weiner, A., Voet, D., Rosenberg, M., Zack, T. I., Zhang, H., Zou, L., Protopopov, A., Santoso, N., Parfenov, M., Lee, S., Zhang, J., Mahadeshwar, H. S., Tang, J., Ren, X., Seth, S., Yang, L., Xu, A. W., Song, X., Pantazi, A., Xi, R., Bristow, C. A., Hadjipanayis, A., Seidman, J., Chin, L., Park, P. J., Kucherlapati, R., Akbani, R., Ling, S., Liu, W., Rao, A., Weinstein, J. N., Kim, S., Lee, J., Lu, Y., Mills, G., Hinoue, T., Weisenberger, D. J., Bootwalla, M. S., Lai, P. H., Shen, H., Triche, T., Van den Berg, D. J., Baylin, S. B., Herman, J. G., Getz, G., Chin, L., Liu, Y., Murray, B. A., Noble, M. S., Askoy, B. A., Ciriello, G., Dresdner, G., Gao, J., Gross, B., Jacobsen, A., Lee, W., Ramirez, R., Sander, C., Schultz, N., Senbabaoglu, Y., Sinha, R., Sumer, S. O., Sun, Y., Weinhold, N., Thorsson, V., Bernard, B., Iype, L., Kramer, R. W., Kreisberg, R., Miller, M., Reynolds, S. M., Rovira, H., Tasman, N., Shmulevich, I., Ng, S., Haussler, D., Stuart, J. M., Akbani, R., Ling, S., Liu, W., Rao, A., Weinstein, J. N., Verhaak, R. G., Mills, G. B., Leiserson, M. D., Raphael, B. J., Wu, H., Taylor, B. S., Black, A. D., Bowen, J., Carney, J. A., Gastier-Foster, J. M., Helsel, C., Leraas, K. M., Lichtenberg, T. M., McAllister, C., Ramirez, N. C., Tabler, T. R., Wise, L., Zmuda, E., Penny, R., Crain, D., Gardner, J., Lau, K., Curely, E., Mallery, D., Morris, S., Paulauskis, J., Shelton, T., Shelton, C., Sherman, M., Benz, C., Lee, J., Fedosenko, K., Manikhas, G., Voronina, O., Belyaev, D., Dolzhansky, O., Rathmell, W. K., Brzezinski, J., Ibbs, M., Korski, K., Kycler, W., Lazniak, R., Leporowska, E., Mackiewicz, A., Murawa, D., Murawa, P., Spychala, A., Suchorska, W. M., Tatka, H., Teresiak, M., Wiznerowicz, M., Abdel-Misih, R., Bennett, J., Brown, J., Iacocca, M., Rabeno, B., Kwon, S., Penny, R., Gardner, J., Kemkes, A., Mallery, D., Morris, S., Shelton, T., Shelton, C., Curley, E., Alexopoulou, I., Engel, J., Bartlett, J., Albert, M., Park, D., Dhir, R., Luketich, J., Landreneau, R., Janjigian, Y. Y., Kelsen, D. P., Cho, E., Ladanyi, M., Tang, L., McCall, S. J., Park, Y. S., Cheong, J., Ajani, J., Camargo, M. C., Alonso, S., Ayala, B., Jensen, M. A., Pihl, T., Raman, R., Walton, J., Wan, Y., Demchok, J. A., Eley, G., Shaw, K. R., Sheth, M., Tarnuzzer, R., Wang, Z., Yang, L., Zenklusen, J. C., Davidsen, T., Hutter, C. M., Sofia, H. J., Burton, R., Chudamani, S., Liu, J. 2014; 513 (7517): 202-209

    Abstract

    Gastric cancer is a leading cause of cancer deaths, but analysis of its molecular and clinical characteristics has been complicated by histological and aetiological heterogeneity. Here we describe a comprehensive molecular evaluation of 295 primary gastric adenocarcinomas as part of The Cancer Genome Atlas (TCGA) project. We propose a molecular classification dividing gastric cancer into four subtypes: tumours positive for Epstein-Barr virus, which display recurrent PIK3CA mutations, extreme DNA hypermethylation, and amplification of JAK2, CD274 (also known as PD-L1) and PDCD1LG2 (also known as PD-L2); microsatellite unstable tumours, which show elevated mutation rates, including mutations of genes encoding targetable oncogenic signalling proteins; genomically stable tumours, which are enriched for the diffuse histological variant and mutations of RHOA or fusions involving RHO-family GTPase-activating proteins; and tumours with chromosomal instability, which show marked aneuploidy and focal amplification of receptor tyrosine kinases. Identification of these subtypes provides a roadmap for patient stratification and trials of targeted therapies.

    View details for DOI 10.1038/nature13480

    View details for Web of Science ID 000341362800044

    View details for PubMedID 25079317

  • A tumor DNA complex aberration index is an independent predictor of survival in breast and ovarian cancer. Molecular oncology Vollan, H. K., Rueda, O. M., Chin, S. F., Curtis, C., Turashvili, G., Shah, S., Lingjærde, O. C., Yuan, Y., Ng, C. K., Dunning, M. J., Dicks, E., Provenzano, E., Sammut, S., McKinney, S., Ellis, I. O., Pinder, S., Purushotham, A., Murphy, L. C., Kristensen, V. N., Brenton, J. D., Pharoah, P. D., Børresen-Dale, A. L., Aparicio, S., Caldas, C. 2014

    Abstract

    Complex focal chromosomal rearrangements in cancer genomes, also called "firestorms", can be scored from DNA copy number data. The complex arm-wise aberration index (CAAI) is a score that captures DNA copy number alterations that appear as focal complex events in tumors, and has potential prognostic value in breast cancer. This study aimed to validate this DNA-based prognostic index in breast cancer and test for the first time its potential prognostic value in ovarian cancer. Copy number alteration (CNA) data from 1950 breast carcinomas (METABRIC cohort) and 508 high-grade serous ovarian carcinomas (TCGA dataset) were analyzed. Cases were classified as CAAI positive if at least one complex focal event was scored. Complex alterations were frequently localized on chromosome 8p (n = 159), 17q (n = 176) and 11q (n = 251). CAAI events on 11q were most frequent in estrogen receptor positive (ER+) cases and on 17q in estrogen receptor negative (ER-) cases. We found only a modest correlation between CAAI and the overall rate of genomic instability (GII) and number of breakpoints (r = 0.27 and r = 0.42, p < 0.001). Breast cancer specific survival (BCSS), overall survival (OS) and ovarian cancer progression free survival (PFS) were used as clinical end points in Cox proportional hazard model survival analyses. CAAI positive breast cancers (43%) had higher mortality: hazard ratio (HR) of 1.94 (95%CI, 1.62-2.32) for BCSS, and of 1.49 (95%CI, 1.30-1.71) for OS. Representations of the 70-gene and the 21-gene predictors were compared with CAAI in multivariable models and CAAI was independently significant with a Cox adjusted HR of 1.56 (95%CI, 1.23-1.99) for ER+ and 1.55 (95%CI, 1.11-2.18) for ER- disease. None of the expression-based predictors were prognostic in the ER- subset. We found that a model including CAAI and the two expression-based prognostic signatures outperformed a model including the 21-gene and 70-gene signatures but excluding CAAI. Inclusion of CAAI in the clinical prognostication tool PREDICT significantly improved its performance. CAAI positive ovarian cancers (52%) also had worse prognosis: HRs of 1.3 (95%CI, 1.1-1.7) for PFS and 1.3 (95%CI, 1.1-1.6) for OS. This study validates CAAI as an independent predictor of survival in both ER+ and ER- breast cancer and reveals a significant prognostic value for CAAI in high-grade serous ovarian cancer.

    View details for DOI 10.1016/j.molonc.2014.07.019

    View details for PubMedID 25169931

  • The Breast Cancer Oncogene EMSY Represses Transcription of Antimetastatic microRNA miR-31 (vol 53, pg 806, 2014) MOLECULAR CELL Vire, E., Curtis, C., Davalos, V., Git, A., Robson, S., Villanueva, A., Vidal, A., Barbieri, I., Aparicio, S., Esteller, M., Caldas, C., Kouzarides, T. 2014; 54 (1): 203-203
  • Genome-driven integrated classification of breast cancer validated in over 7,500 samples Genome Biology Ali, R., Rueda, O. M., Chin, S., Curtis, C., Dunning, M. J., Aparicio, S., Caldas, C. 2014; 15 (8): 431
  • Precise inference of copy number alterations in tumor samples from SNP arrays BIOINFORMATICS Chen, G. K., Chang, X., Curtis, C., Wang, K. 2013; 29 (23): 2964-2970

    Abstract

    The accurate detection of copy number alterations (CNAs) in human genomes is important for understanding susceptibility to cancer and mechanisms of tumor progression. CNA detection in tumors from single nucleotide polymorphism (SNP) genotyping arrays is a challenging problem due to phenomena such as aneuploidy, stromal contamination, genomic waves and intra-tumor heterogeneity, issues that leading methods do not optimally address.Here we introduce methods and software (PennCNV-tumor) for fast and accurate CNA detection using signal intensity data from SNP genotyping arrays. We estimate stromal contamination by applying a maximum likelihood approach over multiple discrete genomic intervals. By conditioning on signal intensity across the genome, our method accounts for both aneuploidy and genomic waves. Finally, our method uses a hidden Markov model to integrate multiple sources of information, including total and allele-specific signal intensity at each SNP, as well as physical maps to make posterior inferences of CNAs. Using real data from cancer cell-lines and patient tumors, we demonstrate substantial improvements in accuracy and computational efficiency compared with existing methods.

    View details for DOI 10.1093/bioinformatics/btt521

    View details for Web of Science ID 000327508300002

    View details for PubMedID 24021380

  • The shaping and functional consequences of the microRNA landscape in breast cancer NATURE Dvinge, H., Git, A., Graef, S., Salmon-Divon, M., Curtis, C., Sottoriva, A., Zhao, Y., Hirst, M., Armisen, J., Miska, E. A., Chin, S., Provenzano, E., Turashvili, G., Green, A., Ellis, I., Aparicio, S., Caldas, C. 2013; 497 (7449): 378-382

    Abstract

    MicroRNAs (miRNAs) show differential expression across breast cancer subtypes, and have both oncogenic and tumour-suppressive roles. Here we report the miRNA expression profiles of 1,302 breast tumours with matching detailed clinical annotation, long-term follow-up and genomic and messenger RNA expression data. This provides a comprehensive overview of the quantity, distribution and variation of the miRNA population and provides information on the extent to which genomic, transcriptional and post-transcriptional events contribute to miRNA expression architecture, suggesting an important role for post-transcriptional regulation. The key clinical parameters and cellular pathways related to the miRNA landscape are characterized, revealing context-dependent interactions, for example with regards to cell adhesion and Wnt signalling. Notably, only prognostic miRNA signatures derived from breast tumours devoid of somatic copy-number aberrations (CNA-devoid) are consistently prognostic across several other subtypes and can be validated in external cohorts. We then use a data-driven approach to seek the effects of miRNAs associated with differential co-expression of mRNAs, and find that miRNAs act as modulators of mRNA-mRNA interactions rather than as on-off molecular switches. We demonstrate such an important modulatory role for miRNAs in the biology of CNA-devoid breast cancers, a common subtype in which the immune response is prominent. These findings represent a new framework for studying the biology of miRNAs in human breast cancer.

    View details for DOI 10.1038/nature12108

    View details for Web of Science ID 000318952000040

    View details for PubMedID 23644459

  • Improving Breast Cancer Survival Analysis through Competition-Based Multidimensional Modeling PLOS COMPUTATIONAL BIOLOGY Bilal, E., Dutkowski, J., Guinney, J., Jang, I. S., Logsdon, B. A., Pandey, G., Sauerwine, B. A., Shimoni, Y., Vollan, H. K., Mecham, B. H., Rueda, O. M., Tost, J., Curtis, C., Alvarez, M. J., Kristensen, V. N., Aparicio, S., Borresen-Dale, A., Caldas, C., Califano, A., Friend, S. H., Ideker, T., Schadt, E. E., Stolovitzky, G. A., Margolin, A. A. 2013; 9 (5)

    Abstract

    Breast cancer is the most common malignancy in women and is responsible for hundreds of thousands of deaths annually. As with most cancers, it is a heterogeneous disease and different breast cancer subtypes are treated differently. Understanding the difference in prognosis for breast cancer based on its molecular and phenotypic features is one avenue for improving treatment by matching the proper treatment with molecular subtypes of the disease. In this work, we employed a competition-based approach to modeling breast cancer prognosis using large datasets containing genomic and clinical information and an online real-time leaderboard program used to speed feedback to the modeling team and to encourage each modeler to work towards achieving a higher ranked submission. We find that machine learning methods combined with molecular features selected based on expert prior knowledge can improve survival predictions compared to current best-in-class methodologies and that ensemble models trained across multiple user submissions systematically outperform individual models within the ensemble. We also find that model scores are highly consistent across multiple independent evaluations. This study serves as the pilot phase of a much larger competition open to the whole research community, with the goal of understanding general strategies for model optimization using clinical and molecular profiling data and providing an objective, transparent system for assessing prognostic models.

    View details for DOI 10.1371/journal.pcbi.1003047

    View details for Web of Science ID 000320032100009

    View details for PubMedID 23671412

  • Systematic Analysis of Challenge-Driven Improvements in Molecular Prognostic Models for Breast Cancer SCIENCE TRANSLATIONAL MEDICINE Margolin, A. A., Bilal, E., Huang, E., Norman, T. C., Ottestad, L., Mecham, B. H., Sauerwine, B., Kellen, M. R., Mangravite, L. M., Furia, M. D., Vollan, H. K., Rueda, O. M., Guinney, J., Deflaux, N. A., Hoff, B., Schildwachter, X., Russnes, H. G., Park, D., Vang, V. O., Pirtle, T., Youseff, L., Citro, C., Curtis, C., Kristensen, V. N., Hellerstein, J., Friend, S. H., Stolovitzky, G., Aparicio, S., Caldas, C., Borresen-Dale, A. 2013; 5 (181)

    Abstract

    Although molecular prognostics in breast cancer are among the most successful examples of translating genomic analysis to clinical applications, optimal approaches to breast cancer clinical risk prediction remain controversial. The Sage Bionetworks-DREAM Breast Cancer Prognosis Challenge (BCC) is a crowdsourced research study for breast cancer prognostic modeling using genome-scale data. The BCC provided a community of data analysts with a common platform for data access and blinded evaluation of model accuracy in predicting breast cancer survival on the basis of gene expression data, copy number data, and clinical covariates. This approach offered the opportunity to assess whether a crowdsourced community Challenge would generate models of breast cancer prognosis commensurate with or exceeding current best-in-class approaches. The BCC comprised multiple rounds of blinded evaluations on held-out portions of data on 1981 patients, resulting in more than 1400 models submitted as open source code. Participants then retrained their models on the full data set of 1981 samples and submitted up to five models for validation in a newly generated data set of 184 breast cancer patients. Analysis of the BCC results suggests that the best-performing modeling strategy outperformed previously reported methods in blinded evaluations; model performance was consistent across several independent evaluations; and aggregating community-developed models achieved performance on par with the best-performing individual models.

    View details for DOI 10.1126/scitranslmed.3006112

    View details for Web of Science ID 000317720300005

    View details for PubMedID 23596205

  • Intratumor heterogeneity in human glioblastoma reflects cancer evolutionary dynamics PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA Sottoriva, A., Spiteri, I., Piccirillo, S. G., Touloumis, A., Collins, V. P., Marioni, J. C., Curtis, C., Watts, C., Tavare, S. 2013; 110 (10): 4009-4014

    Abstract

    Glioblastoma (GB) is the most common and aggressive primary brain malignancy, with poor prognosis and a lack of effective therapeutic options. Accumulating evidence suggests that intratumor heterogeneity likely is the key to understanding treatment failure. However, the extent of intratumor heterogeneity as a result of tumor evolution is still poorly understood. To address this, we developed a unique surgical multisampling scheme to collect spatially distinct tumor fragments from 11 GB patients. We present an integrated genomic analysis that uncovers extensive intratumor heterogeneity, with most patients displaying different GB subtypes within the same tumor. Moreover, we reconstructed the phylogeny of the fragments for each patient, identifying copy number alterations in EGFR and CDKN2A/B/p14ARF as early events, and aberrations in PDGFRA and PTEN as later events during cancer progression. We also characterized the clonal organization of each tumor fragment at the single-molecule level, detecting multiple coexisting cell lineages. Our results reveal the genome-wide architecture of intratumor variability in GB across multiple spatial scales and patient-specific patterns of cancer evolution, with consequences for treatment design.

    View details for DOI 10.1073/pnas.1219747110

    View details for Web of Science ID 000316377400072

    View details for PubMedID 23412337

    View details for PubMedCentralID PMC3593922

  • Single-Molecule Genomic Data Delineate Patient-Specific Tumor Profiles and Cancer Stem Cell Organization CANCER RESEARCH Sottoriva, A., Spiteri, I., Shibata, D., Curtis, C., Tavare, S. 2013; 73 (1): 41-49

    Abstract

    Substantial evidence supports the concept that cancers are organized in a cellular hierarchy with cancer stem cells (CSC) at the apex. To date, the primary evidence for CSCs derives from transplantation assays, which have known limitations. In particular, they are unable to report on the fate of cells within the original human tumor. Because of the difficulty in measuring tumor characteristics in patients, cellular organization and other aspects of cancer dynamics have not been quantified directly, although they likely play a fundamental role in tumor progression and therapy response. As such, new approaches to study CSCs in patient-derived tumor specimens are needed. In this study, we exploited ultradeep single-molecule genomic data derived from multiple microdissected colorectal cancer glands per tumor, along with a novel quantitative approach to measure tumor characteristics, define patient-specific tumor profiles, and infer tumor ancestral trees. We show that each cancer is unique in terms of its cellular organization, molecular heterogeneity, time from malignant transformation, and rate of mutation and apoptosis. Importantly, we estimate CSC fractions between 0.5% and 4%, indicative of a hierarchical organization responsible for long-lived CSC lineages, with variable rates of symmetric cell division. We also observed extensive molecular heterogeneity, both between and within individual cancer glands, suggesting a complex hierarchy of mitotic clones. Our framework enables the measurement of clinically relevant patient-specific characteristics in vivo, providing insight into the cellular organization and dynamics of tumor growth, with implications for personalized patient care.

    View details for DOI 10.1158/0008-5472.CAN-12-2273

    View details for Web of Science ID 000313019800006

    View details for PubMedID 23090114

    View details for PubMedCentralID PMC3544316

  • Quantitative Image Analysis of Cellular Heterogeneity in Breast Tumors Complements Genomic Profiling (vol 4, 161er6, 2012) SCIENCE TRANSLATIONAL MEDICINE Yuan, Y., Failmezger, H., Rueda, O. M., Ali, H. R., Graef, S., Chin, S., SCHWARZ, R. F., Curtis, C., DUNNING, M. J., Bardwell, H., Johnson, N., Doyle, S., Turashvili, G., Provenzano, E., Aparicio, S., Caldas, C., Markowetz, F. 2012; 4 (161)
  • Calling Sample Mix-Ups in Cancer Population Studies PLOS ONE Lynch, A. G., Chin, S., Dunning, M. J., Caldas, C., Tavare, S., Curtis, C. 2012; 7 (8)

    Abstract

    Sample tracking errors have been and always will be a part of the practical implementation of large experiments. It has recently been proposed that expression quantitative trait loci (eQTLs) and their associated effects could be used to identify sample mix-ups and this approach has been applied to a number of large population genomics studies to illustrate the prevalence of the problem. We had adopted a similar approach, termed 'BADGER', in the METABRIC project. METABRIC is a large breast cancer study that may have been the first in which eQTL-based detection of mismatches was used during the study, rather than after the event, to aid quality assurance. We report here on the particular issues associated with large cancer studies performed using historical samples, which complicate the interpretation of such approaches. In particular we identify the complications of using tumour samples, of considering cellularity and RNA quality, of distinct subgroups existing in the study population (including family structures), and of choosing eQTLs to use. We also present some results regarding the design of experiments given consideration of these matters. The eQTL-based approach to identifying sample tracking errors is seen to be of value to these studies, but requiring care in its implementation.

    View details for DOI 10.1371/journal.pone.0041815

    View details for Web of Science ID 000307378500009

    View details for PubMedID 22912679

    View details for PubMedCentralID PMC3415393

  • A Sparse Regulatory Network of Copy-Number Driven Gene Expression Reveals Putative Breast Cancer Oncogenes IEEE-ACM TRANSACTIONS ON COMPUTATIONAL BIOLOGY AND BIOINFORMATICS Yuan, Y., Curtis, C., Caldas, C., Markowetz, F. 2012; 9 (4): 947-954

    Abstract

    Copy number aberrations are recognized to be important in cancer as they may localize to regions harboring oncogenes or tumor suppressors. Such genomic alterations mediate phenotypic changes through their impact on expression. Both cis- and transacting alterations are important since they may help to elucidate putative cancer genes. However, amidst numerous passenger genes, trans-effects are less well studied due to the computational difficulty in detecting weak and sparse signals in the data, and yet may influence multiple genes on a global scale. We propose an integrative approach to learn a sparse interaction network of DNA copy-number regions with their downstream transcriptional targets in breast cancer. With respect to goodness of fit on both simulated and real data, the performance of sparse network inference is no worse than other state-of-the-art models but with the advantage of simultaneous feature selection and efficiency. The DNA-RNA interaction network helps to distinguish copy-number driven expression alterations from those that are copy-number independent. Further, our approach yields a quantitative copy-number dependency score, which distinguishes cis- versus trans-effects. When applied to a breast cancer data set, numerous expression profiles were impacted by cis-acting copy-number alterations, including several known oncogenes such as GRB7, ERBB2, and LSM1. Several trans-acting alterations were also identified, impacting genes such as ADAM2 and BAGE, which warrant further investigation.An R package named lol is available from www.markowetzlab.org/software/lol.html.

    View details for DOI 10.1109/TCBB.2011.105

    View details for Web of Science ID 000304147000002

    View details for PubMedID 21788678

  • The genomic and transcriptomic architecture of 2,000 breast tumours reveals novel subgroups NATURE Curtis, C., Shah, S. P., Chin, S., Turashvili, G., Rueda, O. M., Dunning, M. J., Speed, D., Lynch, A. G., Samarajiwa, S., Yuan, Y., Graef, S., Ha, G., Haffari, G., Bashashati, A., Russell, R., McKinney, S., Langerod, A., Green, A., Provenzano, E., Wishart, G., Pinder, S., Watson, P., Markowetz, F., Murphy, L., Ellis, I., Purushotham, A., Borresen-Dale, A., Brenton, J. D., Tavare, S., Caldas, C., Aparicio, S. 2012; 486 (7403): 346-352

    Abstract

    The elucidation of breast cancer subgroups and their molecular drivers requires integrated views of the genome and transcriptome from representative numbers of patients. We present an integrated analysis of copy number and gene expression in a discovery and validation set of 997 and 995 primary breast tumours, respectively, with long-term clinical follow-up. Inherited variants (copy number variants and single nucleotide polymorphisms) and acquired somatic copy number aberrations (CNAs) were associated with expression in ~40% of genes, with the landscape dominated by cis- and trans-acting CNAs. By delineating expression outlier genes driven in cis by CNAs, we identified putative cancer genes, including deletions in PPP2R2A, MTAP and MAP2K4. Unsupervised analysis of paired DNA–RNA profiles revealed novel subgroups with distinct clinical outcomes, which reproduced in the validation cohort. These include a high-risk, oestrogen-receptor-positive 11q13/14 cis-acting subgroup and a favourable prognosis subgroup devoid of CNAs. Trans-acting aberration hotspots were found to modulate subgroup-specific gene networks, including a TCR deletion-mediated adaptive immune response in the ‘CNA-devoid’ subgroup and a basal-specific chromosome 5 deletion-associated mitotic network. Our results provide a novel molecular stratification of the breast cancer population, derived from the impact of somatic CNAs on the transcriptome.

    View details for DOI 10.1038/nature10983

    View details for Web of Science ID 000305466800033

    View details for PubMedID 22522925

    View details for PubMedCentralID PMC3440846

  • The clonal and mutational evolution spectrum of primary triple-negative breast cancers NATURE Shah, S. P., Roth, A., Goya, R., Oloumi, A., Ha, G., Zhao, Y., Turashvili, G., Ding, J., Tse, K., Haffari, G., Bashashati, A., Prentice, L. M., Khattra, J., Burleigh, A., Yap, D., Bernard, V., McPherson, A., Shumansky, K., Crisan, A., Giuliany, R., Heravi-Moussavi, A., Rosner, J., Lai, D., Birol, I., Varhol, R., Tam, A., Dhalla, N., Zeng, T., Ma, K., Chan, S. K., Griffith, M., Moradian, A., Cheng, S. G., Morin, G. B., Watson, P., Gelmon, K., Chia, S., Chin, S., Curtis, C., Rueda, O. M., Pharoah, P. D., Damaraju, S., Mackey, J., Hoon, K., Harkins, T., Tadigotla, V., Sigaroudinia, M., Gascard, P., Tlsty, T., Costello, J. F., Meyer, I. M., Eaves, C. J., Wasserman, W. W., Jones, S., Huntsman, D., Hirst, M., Caldas, C., Marra, M. A., Aparicio, S. 2012; 486 (7403): 395-399

    Abstract

    Primary triple-negative breast cancers (TNBCs), a tumour type defined by lack of oestrogen receptor, progesterone receptor and ERBB2 gene amplification, represent approximately 16% of all breast cancers. Here we show in 104 TNBC cases that at the time of diagnosis these cancers exhibit a wide and continuous spectrum of genomic evolution, with some having only a handful of coding somatic aberrations in a few pathways, whereas others contain hundreds of coding somatic mutations. High-throughput RNA sequencing (RNA-seq) revealed that only approximately 36% of mutations are expressed. Using deep re-sequencing measurements of allelic abundance for 2,414 somatic mutations, we determine for the first time-to our knowledge-in an epithelial tumour subtype, the relative abundance of clonal frequencies among cases representative of the population. We show that TNBCs vary widely in their clonal frequencies at the time of diagnosis, with the basal subtype of TNBC showing more variation than non-basal TNBC. Although p53 (also known as TP53), PIK3CA and PTEN somatic mutations seem to be clonally dominant compared to other genes, in some tumours their clonal frequencies are incompatible with founder status. Mutations in cytoskeletal, cell shape and motility proteins occurred at lower clonal frequencies, suggesting that they occurred later during tumour progression. Taken together, our results show that understanding the biology and therapeutic responses of patients with TNBC will require the determination of individual tumour clonal genotypes.

    View details for DOI 10.1038/nature10933

    View details for Web of Science ID 000305466800042

    View details for PubMedID 22495314

  • Effects of BRCA2 cis-regulation in normal breast and cancer risk amongst BRCA2 mutation carriers BREAST CANCER RESEARCH Maia, A., Antoniou, A. C., O'Reilly, M., Samarajiwa, S., Dunning, M., Kartsonaki, C., Chin, S., Curtis, C. N., McGuffog, L., Domchek, S. M., Easton, D. F., Peock, S., Frost, D., Evans, D. G., Eeles, R., Izatt, L., Adlard, J., Eccles, D., Sinilnikova, O. M., Mazoyer, S., Stoppa-Lyonnet, D., Gauthier-Villars, M., Faivre, L., Venat-Bouvet, L., Delnatte, C., Nevanlinna, H., Couch, F. J., Godwin, A. K., Caligo, M. A., Barkardottir, R. B., Chen, X., Beesley, J., Healey, S., Caldas, C., Chenevix-Trench, G., Ponder, B. A. 2012; 14 (2)

    Abstract

    Cis-acting regulatory single nucleotide polymorphisms (SNPs) at specific loci may modulate penetrance of germline mutations at the same loci by introducing different levels of expression of the wild-type allele. We have previously reported that BRCA2 shows differential allelic expression and we hypothesize that the known variable penetrance of BRCA2 mutations might be associated with this mechanism.We combined haplotype analysis and differential allelic expression of BRCA2 in breast tissue to identify expression haplotypes and candidate cis-regulatory variants. These candidate variants underwent selection based on in silico predictions for regulatory potential and disruption of transcription factor binding, and were functionally analyzed in vitro and in vivo in normal and breast cancer cell lines. SNPs tagging the expression haplotypes were correlated with the total expression of several genes in breast tissue measured by Taqman and microarray technologies. The effect of the expression haplotypes on breast cancer risk in BRCA2 mutation carriers was investigated in 2,754 carriers.We identified common haplotypes associated with differences in the levels of BRCA2 expression in human breast cells. We characterized three cis-regulatory SNPs located at the promoter and two intronic regulatory elements which affect the binding of the transcription factors C/EBPα, HMGA1, D-binding protein (DBP) and ZF5. We showed that the expression haplotypes also correlated with changes in the expression of other genes in normal breast. Furthermore, there was suggestive evidence that the minor allele of SNP rs4942440, which is associated with higher BRCA2 expression, is also associated with a reduced risk of breast cancer (per-allele hazard ratio (HR) = 0.85, 95% confidence interval (CI) = 0.72 to 1.00, P-trend = 0.048).Our work provides further insights into the role of cis-regulatory variation in the penetrance of disease-causing mutations. We identified small-effect genetic variants associated with allelic expression differences in BRCA2 which could possibly affect the risk in mutation carriers through altering expression levels of the wild-type allele.

    View details for DOI 10.1186/bcr3169

    View details for Web of Science ID 000304771800038

    View details for PubMedID 22513257

  • Penalized regression elucidates aberration hotspots mediating subtype-specific transcriptional responses in breast cancer BIOINFORMATICS Yuan, Y., Rueda, O. M., Curtis, C., Markowetz, F. 2011; 27 (19): 2679-2685

    Abstract

    Copy number alterations (CNAs) associated with cancer are known to contribute to genomic instability and gene deregulation. Integrating CNAs with gene expression helps to elucidate the mechanisms by which CNAs act and to identify the transcriptional downstream targets of CNAs. Such analyses can help to sort functional driver events from the many accompanying passenger alterations. However, the way CNAs affect gene expression can vary in different cellular contexts, for example between different subtypes of the same cancer. Thus, it is important to develop computational approaches capable of inferring differential connectivity of regulatory networks in different cellular contexts.We propose a statistical deregulation model that integrates copy number and expression data of different disease subtypes to jointly model common and differential regulatory relationships. Our model not only identifies CNAs driving gene expression changes, but at the same time also predicts differences in regulation that distinguish one cancer subtype from the other. We implement our model in a penalized regression framework and demonstrate in a simulation study the feasibility and accuracy of our approach. Subsequently, we show that this model can identify both known and novel aspects of cross-talk between the ER and NOTCH pathways in ER-negative-specific deregulations, when compared with ER-positive breast cancer. This flexible model can be applied on other modalities such as methylation or microRNA and expression to disentangle cancer signaling pathways.The Bioconductor-compliant R package DANCE is available from www.markowetzlab.org/software/yinyin.yuan@cancer.org.uk; florian.markowetz@cancer.org.uk.

    View details for DOI 10.1093/bioinformatics/btr450

    View details for Web of Science ID 000295412200009

    View details for PubMedID 21804112

  • ZNF703 is a common Luminal B breast cancer oncogene that differentially regulates luminal and basal progenitors in human mammary epithelium EMBO MOLECULAR MEDICINE Holland, D. G., Burleigh, A., Git, A., Goldgraben, M. A., Perez-Mancera, P. A., Chin, S., Hurtado, A., Bruna, A., Ali, H. R., Greenwood, W., Dunning, M. J., Samarajiwa, S., Menon, S., Rueda, O. M., Lynch, A. G., McKinney, S., Ellis, I. O., Eaves, C. J., Carroll, J. S., Curtis, C., Aparicio, S., Caldas, C. 2011; 3 (3): 167-180

    Abstract

    The telomeric amplicon at 8p12 is common in oestrogen receptor-positive (ER+) breast cancers. Array-CGH and expression analyses of 1172 primary breast tumours revealed that ZNF703 was the single gene within the minimal amplicon and was amplified predominantly in the Luminal B subtype. Amplification was shown to correlate with increased gene and protein expression and was associated with a distinct expression signature and poor clinical outcome. ZNF703 transformed NIH 3T3 fibroblasts, behaving as a classical oncogene, and regulated proliferation in human luminal breast cancer cell lines and immortalized human mammary epithelial cells. Manipulation of ZNF703 expression in the luminal MCF7 cell line modified the effects of TGFβ on proliferation. Overexpression of ZNF703 in normal human breast epithelial cells enhanced the frequency of in vitro colony-forming cells from luminal progenitors. Taken together, these data strongly point to ZNF703 as a novel oncogene in Luminal B breast cancer.

    View details for DOI 10.1002/emmm.201100122

    View details for Web of Science ID 000288727200006

    View details for PubMedID 21337521

  • The importance of platform annotation in interpreting microarray data LANCET ONCOLOGY Dunning, M. J., Curtis, C., Barbosa-Morais, N. L., Caldas, C., Tavare, S., Lynch, A. G. 2010; 11 (8): 717-717

    View details for Web of Science ID 000281009500013

    View details for PubMedID 20688273

  • The pitfalls of platform comparison: DNA copy number array technologies assessed BMC GENOMICS Curtis, C., Lynch, A. G., Dunning, M. J., Spiteri, I., Marioni, J. C., Hadfield, J., Chin, S., Brenton, J. D., Tavare, S., Caldas, C. 2009; 10

    Abstract

    The accurate and high resolution mapping of DNA copy number aberrations has become an important tool by which to gain insight into the mechanisms of tumourigenesis. There are various commercially available platforms for such studies, but there remains no general consensus as to the optimal platform. There have been several previous platform comparison studies, but they have either described older technologies, used less-complex samples, or have not addressed the issue of the inherent biases in such comparisons. Here we describe a systematic comparison of data from four leading microarray technologies (the Affymetrix Genome-wide SNP 5.0 array, Agilent High-Density CGH Human 244A array, Illumina HumanCNV370-Duo DNA Analysis BeadChip, and the Nimblegen 385 K oligonucleotide array). We compare samples derived from primary breast tumours and their corresponding matched normals, well-established cancer cell lines, and HapMap individuals. By careful consideration and avoidance of potential sources of bias, we aim to provide a fair assessment of platform performance.By performing a theoretical assessment of the reproducibility, noise, and sensitivity of each platform, notable differences were revealed. Nimblegen exhibited between-replicate array variances an order of magnitude greater than the other three platforms, with Agilent slightly outperforming the others, and a comparison of self-self hybridizations revealed similar patterns. An assessment of the single probe power revealed that Agilent exhibits the highest sensitivity. Additionally, we performed an in-depth visual assessment of the ability of each platform to detect aberrations of varying sizes. As expected, all platforms were able to identify large aberrations in a robust manner. However, some focal amplifications and deletions were only detected in a subset of the platforms.Although there are substantial differences in the design, density, and number of replicate probes, the comparison indicates a generally high level of concordance between platforms, despite differences in the reproducibility, noise, and sensitivity. In general, Agilent tended to be the best aCGH platform and Affymetrix, the superior SNP-CGH platform, but for specific decisions the results described herein provide a guide for platform selection and study design, and the dataset a resource for more tailored comparisons.

    View details for DOI 10.1186/1471-2164-10-588

    View details for Web of Science ID 000273075400002

    View details for PubMedID 19995423

  • Drosophila melanogaster p53 has developmental stage-specific and sex-specific effects on adult life span indicative of sexual antagonistic pleiotropy AGING-US Waskar, M., Landis, G. N., Shen, J., Curtis, C., Tozer, K., Abdueva, D., Skvortsov, D., Tavare, S., Tower, J. 2009; 1 (11): 903-936

    Abstract

    Truncated and mutant forms ofp53 affect life span in Drosophila, nematodes and mice, however the role of wild-type p53 in aging remains unclear. Here conditional over-expression of both wild-type and mutant p53 transgenes indicated that, in adult flies, p53 limits life span in females but favors life span in males. In contrast, during larval development, moderate over-expression of p53 produced both male and female adults with increased life span. Mutations of the endogenous p53 gene also had sex-specific effects on life span under control and stress conditions: null mutation of p53 increased life span in females, and had smaller, more variable effects in males. These developmental stage-specific and sex-specific effects of p53 on adult life span are consistent with a sexual antagonistic pleiotropy model.

    View details for Web of Science ID 000276402700004

    View details for PubMedID 20157574

  • Swift: primary data analysis for the Illumina Solexa sequencing platform BIOINFORMATICS Whiteford, N., Skelly, T., Curtis, C., Ritchie, M. E., Loehr, A., Zaranek, A. W., Abnizova, I., Brown, C. 2009; 25 (17): 2194-2199

    Abstract

    Primary data analysis methods are of critical importance in second generation DNA sequencing. Improved methods have the potential to increase yield and reduce the error rates. Openly documented analysis tools enable the user to understand the primary data, this is important for the optimization and validity of their scientific work.In this article, we describe Swift, a new tool for performing primary data analysis on the Illumina Solexa Sequencing Platform. Swift is the first tool, outside of the vendors own software, which completes the full analysis process, from raw images through to base calls. As such it provides an alternative to, and independent validation of, the vendor supplied tool. Our results show that Swift is able to increase yield by 13.8%, at comparable error rate.

    View details for DOI 10.1093/bioinformatics/btp383

    View details for Web of Science ID 000269196000008

    View details for PubMedID 19549630

  • Product Length, Dye Choice, and Detection Chemistry in the Bead-Emulsion Amplification of Millions of Single DNA Molecules in Parallel ANALYTICAL CHEMISTRY Tiemann-Boege, I., Curtis, C., Shinde, D. N., Goodman, D. B., Tavare, S., Arnheim, N. 2009; 81 (14): 5770-5776

    Abstract

    The amplification of millions of single molecules in parallel can be performed on microscopic magnetic beads that are contained in aqueous compartments of an oil-buffer emulsion. These bead-emulsion amplification (BEA) reactions result in beads that are covered by almost-identical copies derived from a single template. The post-amplification analysis is performed using different fluorophore-labeled probes. We have identified BEA reaction conditions that efficiently produce longer amplicons of up to 450 base pairs. These conditions include the use of a Titanium Taq amplification system. Second, we explored alternate fluorophores coupled to probes for post-PCR DNA analysis. We demonstrate that four different Alexa fluorophores can be used simultaneously with extremely low crosstalk. Finally, we developed an allele-specific extension chemistry that is based on Alexa dyes to query individual nucleotides of the amplified material that is both highly efficient and specific.

    View details for DOI 10.1021/ac900633y

    View details for Web of Science ID 000268135000025

    View details for PubMedID 19601653

  • A screen of apoptosis and senescence regulatory genes for life span effects when over-expressed in Drosophila AGING-US Shen, J., Curtis, C., Tavare, S., Tower, J. 2009; 1 (2): 191-211

    Abstract

    Conditional expression of transgenes in Drosophila was produced using the Geneswitch system, wherein feeding the drug RU486/Mifepristone activates the artificial transcription factor Geneswitch. Geneswitch was expressed using the Actin5C promoter and this was found to yield conditional, tissue-general expression of a target transgene (UAS-GFP) in both larvae and adult flies. Nervous system-specific (Elav-GS) and fat body-specific Geneswitch drivers were also characterized using UAS-GFP. Fourteen genes implicated in growth, apoptosis and senescence regulatory pathways were over-expressed in adult flies or during larval development, and assayed for effects on adult fly life span. Over-expression of a dominant p53 allele (p53-259H) in adult flies using the ubiquitous driver produced increased life span in females but not males, consistent with previous studies. Both wingless and Ras activated form transgenes were lethal when expressed in larvae, and reduced life span when expressed in adults, consistent with results from other model systems indicating that the wingless and Ras pathways can promote senescence. Over-expression of the caspase inhibitor baculovirus p35 during larval development reduced the mean life span of male and female adults, and also produced a subset of females with increased life span. These experiments suggest that baculovirus p35 and the wingless and Ras pathways can have sex-specific and developmental stage-specific effects on adult Drosophila life span, and these reagents should be useful for the further analysis of the role of these conserved pathways in aging.

    View details for Web of Science ID 000276400900005

    View details for PubMedID 20157509

  • Explaining differences in saturation levels for Affymetrix GeneChip (R) arrays NUCLEIC ACIDS RESEARCH Skvortsov, D., Abdueva, D., Curtis, C., Schaub, B., Tavare, S. 2007; 35 (12): 4154-4163

    Abstract

    The experimental spike-in studies of microarray hybridization conducted by Affymetrix demonstrate a nonlinear response of fluorescence intensity signal to target concentration. Several theoretical models have been put forward to explain these data. It was shown that the Langmuir adsorption isotherm recapitulates a general trend of signal response to concentration. However, this model fails to explain some key properties of the observed signal. In particular, according to the simple Langmuir isotherm, all probes should saturate at the same intensity level. However, this effect was not observed in the publicly available Affymetrix spike-in data sets. On the contrary, it was found that the saturation intensities vary greatly and can be predicted based on the probe sequence composition. In our experimental study, we attempt to account for the unexplained variation in the observed probe intensities using customized fluidics scripts. We explore experimentally the effect of the stringent wash, target concentration and hybridization time on the final microarray signal. The washing effect is assessed by scanning chips both prior to and after the stringent wash. Selective labeling of both specific and non-specific targets allows the visualization and investigation of the washing effect for both specific and non-specific signal components. We propose a new qualitative model of the probe-target hybridization mechanism that is in agreement with observed hybridization and washing properties of short oligonucleotide microarrays. This study demonstrates that desorption of incompletely bound targets during the washing cycle contributes to the observed difference in saturation levels.

    View details for DOI 10.1093/nar/gkm348

    View details for Web of Science ID 000247817700026

    View details for PubMedID 17567617

  • Transcriptional profiling of MnSOD-mediated lifespan extension in Drosophila reveals a species-general network of aging and metabolic genes GENOME BIOLOGY Curtis, C., Landis, G. N., Folk, D., Wehr, N. B., Hoe, N., Waskar, M., Abdueva, D., Skvortsov, D., Ford, D., Luu, A., Badrinath, A., Levine, R. L., Bradley, T. J., Tavare, S., Tower, J. 2007; 8 (12)

    Abstract

    Several interventions increase lifespan in model organisms, including reduced insulin/insulin-like growth factor-like signaling (IIS), FOXO transcription factor activation, dietary restriction, and superoxide dismutase (SOD) over-expression. One question is whether these manipulations function through different mechanisms, or whether they intersect on common processes affecting aging.A doxycycline-regulated system was used to over-express manganese-SOD (MnSOD) in adult Drosophila, yielding increases in mean and maximal lifespan of 20%. Increased lifespan resulted from lowered initial mortality rate and required MnSOD over-expression in the adult. Transcriptional profiling indicated that the expression of specific genes was altered by MnSOD in a manner opposite to their pattern during normal aging, revealing a set of candidate biomarkers of aging enriched for carbohydrate metabolism and electron transport genes and suggesting a true delay in physiological aging, rather than a novel phenotype. Strikingly, cross-dataset comparisons indicated that the pattern of gene expression caused by MnSOD was similar to that observed in long-lived Caenorhabditis elegans insulin-like signaling mutants and to the xenobiotic stress response, thus exposing potential conserved longevity promoting genes and implicating detoxification in Drosophila longevity.The data suggest that MnSOD up-regulation and a retrograde signal of reactive oxygen species from the mitochondria normally function as an intermediate step in the extension of lifespan caused by reduced insulin-like signaling in various species. The results implicate a species-conserved net of coordinated genes that affect the rate of senescence by modulating energetic efficiency, purine biosynthesis, apoptotic pathways, endocrine signals, and the detoxification and excretion of metabolites.

    View details for DOI 10.1186/gb-2007-8-12-r262

    View details for Web of Science ID 000253451800010

    View details for PubMedID 18067683

  • Scambio, a novel guanine nucleotide exchange factor for Rho MOLECULAR CANCER Curtis, C., Hemmeryckx, B., Haataja, L., Senadheera, D., Groffen, J., Heisterkamp, N. 2004; 3