Andrew Gentles
Associate Professor (Research) of Pathology, of Medicine (BMIR) and, by courtesy, of Biomedical Data Science
Bio
BSc (Hons) Physics, University of Manchester, UK
PhD Theoretical particle physics, University of Southampton, UK
Academic Appointments
-
Associate Professor (Research), Pathology
-
Associate Professor (Research), Medicine - Biomedical Informatics Research
-
Associate Professor (Research) (By courtesy), Department of Biomedical Data Science
-
Member, Bio-X
-
Member, Cardiovascular Institute
-
Member, Stanford Cancer Institute
-
Member, Wu Tsai Neurosciences Institute
Current Research and Scholarly Interests
Computational systems biology
2024-25 Courses
- Machine Learning Approaches for Data Fusion in Biomedicine
BIODS 221, BIOMEDIN 221 (Aut) -
Independent Studies (3)
- Directed Reading and Research
BIOMEDIN 299 (Aut, Win, Spr, Sum) - Graduate Research
CBIO 399 (Aut, Win, Spr, Sum) - Graduate Research
IMMUNOL 399 (Aut, Win, Spr, Sum)
- Directed Reading and Research
-
Prior Year Courses
2023-24 Courses
- Machine Learning Approaches for Data Fusion in Biomedicine
BIODS 221, BIOMEDIN 221 (Aut)
2022-23 Courses
- Machine Learning Approaches for Data Fusion in Biomedicine
BIODS 221, BIOMEDIN 221 (Aut)
2021-22 Courses
- Essential Methods in Computational and Systems Immunology
IMMUNOL 207 (Spr) - Machine Learning Approaches for Data Fusion in Biomedicine
BIODS 221, BIOMEDIN 221 (Aut)
- Machine Learning Approaches for Data Fusion in Biomedicine
Stanford Advisees
-
Doctoral Dissertation Reader (AC)
Diego Almanza, Vandon Duong, Rachel Gleyzer, Kevin Liu, Warren Reynolds -
Postdoctoral Faculty Sponsor
Ruohan Wang -
Doctoral Dissertation Co-Advisor (AC)
Emma Heaton, Ilayda Ilerten
Graduate and Fellowship Programs
-
Biomedical Data Science (Masters Program)
-
Biomedical Data Science (Phd Program)
All Publications
-
Ten challenges and opportunities in computational immuno-oncology.
Journal for immunotherapy of cancer
2024; 12 (10)
Abstract
Immuno-oncology has transformed the treatment of cancer, with several immunotherapies becoming the standard treatment across histologies. Despite these advancements, the majority of patients do not experience durable clinical benefits, highlighting the imperative for ongoing advancement in immuno-oncology. Computational immuno-oncology emerges as a forefront discipline that draws on biomedical data science and intersects with oncology, immunology, and clinical research, with the overarching goal to accelerate the development of effective and safe immuno-oncology treatments from the laboratory to the clinic. In this review, we outline 10 critical challenges and opportunities in computational immuno-oncology, emphasizing the importance of robust computational strategies and interdisciplinary collaborations amid the constantly evolving interplay between clinical needs and technological innovation.
View details for DOI 10.1136/jitc-2024-009721
View details for PubMedID 39461879
-
Community assessment of methods to deconvolve cellular composition from bulk gene expression.
Nature communications
2024; 15 (1): 7362
Abstract
We evaluate deconvolution methods, which infer levels of immune infiltration from bulk expression of tumor samples, through a community-wide DREAM Challenge. We assess six published and 22 community-contributed methods using in vitro and in silico transcriptional profiles of admixed cancer and healthy immune cells. Several published methods predict most cell types well, though they either were not trained to evaluate all functional CD8+ T cell states or do so with low accuracy. Several community-contributed methods address this gap, including a deep learning-based approach, whose strong performance establishes the applicability of this paradigm to deconvolution. Despite being developed largely using immune cells from healthy tissues, deconvolution methods predict levels of tumor-derived immune cells well. Our admixed and purified transcriptional profiles will be a valuable resource for developing deconvolution methods, including in response to common challenges we observe across methods, such as sensitive identification of functional CD4+ T cell states.
View details for DOI 10.1038/s41467-024-50618-0
View details for PubMedID 39191725
View details for PubMedCentralID 6167550
-
IDENTIFICATION AND CHARACTERIZATION OF NEW MULTIPOTENT PROGENITORS IN ADULT HUMAN HEMATOPOIESIS
ELSEVIER SCIENCE INC. 2024
View details for Web of Science ID 001325038400119
-
AML/T cell interactomics uncover correlates of patient outcomes and the key role of ICAM1 in T cell killing of AML.
Leukemia
2024
Abstract
T cells are important for the control of acute myeloid leukemia (AML), a common and often deadly malignancy. We observed that some AML patient samples are resistant to killing by human-engineered cytotoxic CD4+ T cells. Single-cell RNA-seq of primary AML samples and CD4+ T cells before and after their interaction uncovered transcriptional programs that correlate with AML sensitivity or resistance to CD4+ T cell killing. Resistance-associated AML programs were enriched in AML patients with poor survival, and killing-resistant AML cells did not engage T cells in vitro. Killing-sensitive AML potently activated T cells before being killed, and upregulated ICAM1, a key component of the immune synapse with T cells. Without ICAM1, killing-sensitive AML became resistant to killing by primary ex vivo-isolated CD8+ T cells in vitro, and engineered CD4+ T cells in vitro and in vivo. While AML heterogeneity implies that multiple factors may determine their sensitivity to T cell killing, these data show that ICAM1 acts as an immune trigger, allowing T cell killing, and could play a role in AML patient survival in vivo.
View details for DOI 10.1038/s41375-024-02255-1
View details for PubMedID 38724673
View details for PubMedCentralID 6239928
-
Endometrioid Endometrial RNA Index Predicts Recurrence in Stage I Patients.
Clinical cancer research : an official journal of the American Association for Cancer Research
2024
Abstract
PURPOSE: Risk prediction with genomic and transcriptomic data has the potential to improve patient outcomes by enabling clinicians to identify patients requiring adjuvant treatment approaches, while sparing low-risk patients from unnecessary interventions. Endometrioid endometrial carcinoma (EEC) is the most common cancer in women in developed countries, and rates of endometrial cancer are increasing.EXPERIMENTAL DESIGN: We collected a 105-patient case-control cohort of stage I EEC comprised of 45 patients who experienced recurrence less than 6 years after excision, and 60 FIGO grade matched controls without recurrence. We first utilized two RNA based, previously validated machine learning approaches, namely EcoTyper and Complexity Index in Sarcoma (CINSARC). We developed Endometrioid Endometrial RNA Index (EERI) which uses RNA expression data from 46 genes to generate a personalized risk score for each patient. EERI was trained on our 105-patient cohort and tested on a publicly available cohort of 263 stage I EEC patients.RESULTS: EERI was able to predict recurrences with 94% accuracy in the training set and 81% accuracy in the test set. In the test set, patients assigned as EERI high-risk were significantly more likely to experience recurrence (30%) than the EERI low-risk group (1%) with a hazard ratio of 9.9 (95% CI 4.1-23.8, P <0.001).CONCLUSIONS: Tumors with high-risk genetic features may require additional treatment or closer monitoring and are not readily identified using traditional clinicopathologic and molecular features. EERI performs with high sensitivity and modest specificity, which may benefit from further optimization and validation in larger independent cohorts.
View details for DOI 10.1158/1078-0432.CCR-23-3158
View details for PubMedID 38669067
-
Mutation order in acute myeloid leukemia identifies uncommon patterns of evolution and illuminates phenotypic heterogeneity.
Leukemia
2024
Abstract
Acute myeloid leukemia (AML) has a poor prognosis and a heterogeneous mutation landscape. Although common mutations are well-studied, little research has characterized how the sequence of mutations relates to clinical features. Using published, single-cell DNA sequencing data from three institutions, we compared clonal evolution patterns in AML to patient characteristics, disease phenotype, and outcomes. Mutation trees, which represent the order of select mutations, were created for 207 patients from targeted panel sequencing data using 1 639 162 cells, 823 mutations, and 275 samples. In 224 distinct orderings of mutated genes, mutations related to DNA methylation typically preceded those related to cell signaling, but signaling-first cases did occur, and had higher peripheral cell counts, increased signaling mutation homozygosity, and younger patient age. Serial sample analysis suggested that NPM1 and DNA methylation mutations provide an advantage to signaling mutations in AML. Interestingly, WT1 mutation evolution shared features with signaling mutations, such as WT1-early being proliferative and occurring in younger individuals, trends that remained in multivariable regression. Some mutation orderings had a worse prognosis, but this was mediated by unfavorable mutations, not mutation order. These findings add a dimension to the mutation landscape of AML, identifying uncommon patterns of leukemogenesis and shedding light on heterogeneous phenotypes.
View details for DOI 10.1038/s41375-024-02211-z
View details for PubMedID 38467769
View details for PubMedCentralID 3983786
-
Single Cell Spatial Biology for Precision Cancer Medicine.
Pacific Symposium on Biocomputing. Pacific Symposium on Biocomputing
2023; 28: 549-553
Abstract
In cancer, complex ecosystems of interacting cell types play fundamental roles in tumor development, progression, and response to therapy. However, the cellular organization, community structure, and spatially defined microenvironments of human tumors remain poorly understood. With the emergence of new technologies for high-throughput spatial profiling of complex tissue specimens, it is now possible to identify clinically significant spatial features with high granularity. In this PSB workshop, we will highlight recent advances in this area and explore how single cell spatial profiling can advance precision cancer medicine.
View details for PubMedID 36541010
-
Loss of p53-DREAM-mediated repression of cell cycle genes as a driver of lymph node metastasis in head and neck cancer.
Genome medicine
2023; 15 (1): 98
Abstract
BACKGROUND: The prognosis for patients with head and neck cancer (HNC) is poor and has improved little in recent decades, partially due to lack of therapeutic options. To identify effective therapeutic targets, we sought to identify molecular pathways that drive metastasis and HNC progression, through large-scale systematic analyses of transcriptomic data.METHODS: We performed meta-analysis across 29 gene expression studies including 2074 primary HNC biopsies to identify genes and transcriptional pathways associated with survival and lymph node metastasis (LNM). To understand the biological roles of these genes in HNC, we identified their associated cancer pathways, as well as the cell types that express them within HNC tumor microenvironments, by integrating single-cell RNA-seq and bulk RNA-seq from sorted cell populations.RESULTS: Patient survival-associated genes were heterogenous and included drivers of diverse tumor biological processes: these included tumor-intrinsicprocesses such as epithelial dedifferentiation and epithelial to mesenchymal transition, as well as tumor microenvironmental factors such as T cell-mediated immunity and cancer-associated fibroblast activity. Unexpectedly, LNM-associated genes were almost universally associated with epithelial dedifferentiation within malignant cells. Genes negatively associated with LNM consisted of regulators of squamous epithelial differentiation that are expressed within well-differentiated malignant cells, while those positively associated with LNM represented cell cycle regulators thatare normally repressedby the p53-DREAM pathway. These pro-LNM genes are overexpressed in proliferating malignant cells of TP53 mutated and HPV+ve HNCs and are strongly associated with stemness, suggesting that they represent markers of pre-metastatic cancer stem-like cells. LNM-associated genes are deregulated in high-grade oral precancerous lesions, and deregulated further in primary HNCs with advancing tumor grade and deregulated further still in lymph node metastases.CONCLUSIONS: In HNC, patient survival is affected by multiple biological processes and is strongly influenced by the tumor immune and stromal microenvironments. In contrast, LNM appears to be driven primarily by malignant cell plasticity, characterized by epithelial dedifferentiation coupled with EMT-independent proliferation and stemness. Our findings postulate that LNM is initially caused by loss of p53-DREAM-mediated repression of cell cycle genes during early tumorigenesis.
View details for DOI 10.1186/s13073-023-01236-w
View details for PubMedID 37978395
-
Translatome analysis reveals microglia and astrocytes to be distinct regulators of inflammation in the hyperacute and acute phases after stroke.
Glia
2023
Abstract
Neuroinflammation is a hallmark of ischemic stroke, which is a leading cause of death and long-term disability. Understanding the exact cellular signaling pathways that initiate and propagate neuroinflammation after stroke will be critical for developing immunomodulatory stroke therapies. In particular, the precise mechanisms of inflammatory signaling in the clinically relevant hyperacute period, hours after stroke, have not been elucidated. We used the RiboTag technique to obtain microglia and astrocyte-derived mRNA transcripts in a hyperacute (4 h) and acute (3 days) period after stroke, as these two cell types are key modulators of acute neuroinflammation. Microglia initiated a rapid response to stroke at 4 h by adopting an inflammatory profile associated with the recruitment of immune cells. The hyperacute astrocyte profile was marked by stress response genes and transcription factors, such as Fos and Jun, involved in pro-inflammatory pathways such as TNF-α. By 3 days, microglia shift to a proliferative state and astrocytes strengthen their inflammatory response. The astrocyte pro-inflammatory response at 3 days is partially driven by the upregulation of the transcription factors C/EBPβ, Spi1, and Rel, which comprise 25% of upregulated transcription factor-target interactions. Surprisingly, few sex differences across all groups were observed. Expression and log2 fold data for all sequenced genes are available on a user-friendly website for researchers to examine gene changes and generate hypotheses for stroke targets. Taken together, our data comprehensively describe the microglia and astrocyte-specific translatome response in the hyperacute and acute period after stroke and identify pathways critical for initiating neuroinflammation.
View details for DOI 10.1002/glia.24377
View details for PubMedID 37067534
-
Multimodal data fusion for cancer biomarker discovery with deep learning.
Nature machine intelligence
2023; 5 (4): 351-362
Abstract
Technological advances now make it possible to study a patient from multiple angles with high-dimensional, high-throughput multi-scale biomedical data. In oncology, massive amounts of data are being generated ranging from molecular, histopathology, radiology to clinical records. The introduction of deep learning has significantly advanced the analysis of biomedical data. However, most approaches focus on single data modalities leading to slow progress in methods to integrate complementary data types. Development of effective multimodal fusion approaches is becoming increasingly important as a single modality might not be consistent and sufficient to capture the heterogeneity of complex diseases to tailor medical care and improve personalised medicine. Many initiatives now focus on integrating these disparate modalities to unravel the biological processes involved in multifactorial diseases such as cancer. However, many obstacles remain, including lack of usable data as well as methods for clinical validation and interpretation. Here, we cover these current challenges and reflect on opportunities through deep learning to tackle data sparsity and scarcity, multimodal interpretability, and standardisation of datasets.
View details for DOI 10.1038/s42256-023-00633-5
View details for PubMedID 37693852
View details for PubMedCentralID PMC10484010
-
Profiling Cellular Ecosystems at Single-Cell Resolution and at Scale with EcoTyper.
Methods in molecular biology (Clifton, N.J.)
2023; 2629: 43-71
Abstract
Tissues are composed of diverse cell types and cellular states that organize into distinct ecosystems with specialized functions. EcoTyper is a collection of machine learning tools for the large-scale delineation of cellular ecosystems and their constituent cell states from bulk, single-cell, and spatially resolved gene expression data. In this chapter, we provide a primer on EcoTyper and demonstrate its use for the discovery and recovery of cell states and ecosystems from healthy and diseased tissue specimens.
View details for DOI 10.1007/978-1-0716-2986-4_4
View details for PubMedID 36929073
View details for PubMedCentralID 9067608
-
High-resolution alignment of single-cell and spatial transcriptomes with CytoSPACE.
Nature biotechnology
2023
Abstract
Recent studies have emphasized the importance of single-cell spatial biology, yet available assays for spatial transcriptomics have limited gene recovery or low spatial resolution. Here we introduce CytoSPACE, an optimization method for mapping individual cells from a single-cell RNA sequencing atlas to spatial expression profiles. Across diverse platforms and tissue types, we show that CytoSPACE outperforms previous methods with respect to noise tolerance and accuracy, enabling tissue cartography at single-cell resolution.
View details for DOI 10.1038/s41587-023-01697-9
View details for PubMedID 36879008
View details for PubMedCentralID 6132072
-
Single cell genomics in AML: extending the frontiers of AML research.
Blood
2022
Abstract
The era of genomic medicine has allowed AML researchers to improve disease characterization, optimize risk stratification systems, and develop new treatments. While there has been significant progress, AML remains a lethal cancer due to its remarkably complex and plastic cellular architecture. This degree of heterogeneity continues to pose a major challenge as it limits the ability to identify and therefore eradicate the cells responsible for leukemogenesis and treatment failures. In recent years, the field of single cell genomics has led to unprecedented strides in the ability to characterize cellular heterogeneity and holds promise for the study of AML. In this review, we will highlight advancements in single cell technologies, outline important shortcomings in our understanding of AML biology and clinical management, and discuss how single cell genomics can not only address these shortcomings, but also provide unique opportunities in basic and translational AML research.
View details for DOI 10.1182/blood.2021014670
View details for PubMedID 35926108
-
Peripheral blood DNA methylation profiles predict future development of B-cell Non-Hodgkin Lymphoma.
NPJ precision oncology
2022; 6 (1): 53
Abstract
Lack of accurate methods for early lymphoma detection limits the ability to cure patients. Since patients with Non-Hodgkin lymphomas (NHL) who present with advanced disease have worse outcomes, accurate and sensitive methods for early detection are needed to improve patient care. We developed a DNA methylation-based prediction tool for NHL, based on blood samples collected prospectively from 278 apparently healthy patients who were followed for up to 16 years to monitor for NHL development. A predictive score was developed using machine learning methods in a robust training/validation framework. Our predictive score incorporates CpG DNA methylation at 135 genomic positions, with higher scores predicting higher risk. It was 85% and 78% accurate for identifying patients at risk of developing future NHL, in patients with high or low epigenetic mitotic clock respectively, in a validation cohort. It was also sensitive at detecting active NHL (96.3% accuracy) and healthy status (95.6% accuracy) in additional independent cohorts. Scores optimized for specific NHL subtypes showed significant but lower accuracy for predicting other subtypes. Our score incorporates hyper-methylation of Polycomb and HOX genes, which have roles in NHL development, as well as PAX5 - a master transcriptional regulator of B-cell fate. Subjects with higher risk scores showed higher regulatory T-cells, memory B-cells, but lower naive T helper lymphocytes fractions in the blood. Future prospective studies will be required to confirm the utility of our signature for managing patients who are at high risk for developing future NHL.
View details for DOI 10.1038/s41698-022-00295-3
View details for PubMedID 35864305
-
Identification of cell types in multiplexed in situ images by combining protein expression and spatial information using CELESTA.
Nature methods
2022
Abstract
Advances in multiplexed in situ imaging are revealing important insights in spatial biology. However, cell type identification remains a major challenge in imaging analysis, with most existing methods involving substantial manual assessment and subjective decisions for thousands of cells. We developed an unsupervised machine learning algorithm, CELESTA, which identifies the cell type of each cell, individually, using the cell's marker expression profile and, when needed, its spatial information. We demonstrate the performance of CELESTA on multiplexed immunofluorescence images of colorectal cancer and head and neck squamous cell carcinoma (HNSCC). Using the cell types identified by CELESTA, we identify tissue architecture associated with lymph node metastasis in HNSCC, and validate our findings in an independent cohort. By coupling our spatial analysis with single-cell RNA-sequencing data on proximal sections of the same specimens, we identify cell-cell crosstalk associated with lymph node metastasis, demonstrating the power of CELESTA to facilitate identification of clinically relevant interactions.
View details for DOI 10.1038/s41592-022-01498-z
View details for PubMedID 35654951
-
Lymph node colonization induces tumor-immune tolerance to promote distant metastasis.
Cell
2022
Abstract
For many solid malignancies, lymph node (LN) involvement represents a harbinger of distant metastatic disease and, therefore, an important prognostic factor. Beyond its utility as a biomarker, whether and how LN metastasis plays an active role in shaping distant metastasis remains an open question. Here, we develop a syngeneic melanoma mouse model of LN metastasis to investigate how tumors spread to LNs and whether LN colonization influences metastasis to distant tissues. We show that an epigenetically instilled tumor-intrinsic interferon response program confers enhanced LN metastatic potential by enabling the evasion of NK cells and promoting LN colonization. LN metastases resist T cell-mediated cytotoxicity, induce antigen-specific regulatory T cells, and generate tumor-specific immune tolerance that subsequently facilitates distant tumor colonization. These effects extend to human cancers and other murine cancer models, implicating a conserved systemic mechanism by which malignancies spread to distant organs.
View details for DOI 10.1016/j.cell.2022.04.019
View details for PubMedID 35525247
-
NSD1 mutations deregulate transcription and DNA methylation of bivalent developmental genes in Sotos syndrome.
Human molecular genetics
2022
Abstract
Sotos syndrome (SS), the most common overgrowth with intellectual disability (OGID) disorder, is caused by inactivating germline mutations of NSD1, which encodes a histone H3 lysine 36 methyltransferase. To understand how NSD1 inactivation deregulates transcription and DNA methylation (DNAm), and to explore how these abnormalities affect human development, we profiled transcription and DNAm in SS patients and healthy control individuals. We identified a transcriptional signature that distinguishes individuals with SS from controls and was also deregulated in NSD1 mutated cancers. Most abnormally expressed genes displayed reduced expression in SS; these downregulated genes consisted mostly of bivalent genes and were enriched for regulators of development and neural synapse function. DNA hypomethylation was strongly enriched within promoters of transcriptionally deregulated genes: Overexpressed genes displayed hypomethylation at their transcription start sites (TSSs) while underexpressed genes featured hypomethylation at polycomb binding sites within their promoter CpG island shores. SS patients featured accelerated molecular aging at the levels of both transcription and DNAm. Overall, these findings indicate that NSD1-deposited H3K36 methylation regulates transcription by directing promoter DNA methylation, partially by repressing polycomb repressive complex 2 (PRC2) activity. These findings could explain the phenotypic similarity of SS to OGID disorders that are caused by mutations in PRC2 complex-encoding genes.
View details for DOI 10.1093/hmg/ddac026
View details for PubMedID 35094088
-
Clonal architecture predicts clinical outcomes and drug sensitivity in acute myeloid leukemia.
Nature communications
1800; 12 (1): 7244
Abstract
The impact of clonal heterogeneity on disease behavior or drug response in acute myeloid leukemia remains poorly understood. Using a cohort of 2,829 patients, we identify features of clonality associated with clinical features and drug sensitivities. High variant allele frequency for 7 mutations (including NRAS and TET2) associate with dismal prognosis; elevated GATA2 variant allele frequency correlates with better outcomes. Clinical features such as white blood cell count and blast percentage correlate with the subclonal abundance of mutations such as TP53 and IDH1. Furthermore, patients with cohesin mutations occurring before NPM1, or transcription factor mutations occurring before splicing factor mutations, show shorter survival. Surprisingly, a branched pattern of clonal evolution is associated with superior clinical outcomes. Finally, several mutations (including NRAS and IDH1) predict drug sensitivity based on their subclonal abundance. Together, these results demonstrate the importance of assessing clonal heterogeneity with implications for prognosis and actionable biomarkers for therapy.
View details for DOI 10.1038/s41467-021-27472-5
View details for PubMedID 34903734
-
High-grade serous ovarian tumor cells modulate NK cell function to create an immune-tolerant microenvironment.
Cell reports
2021; 36 (9): 109632
Abstract
Tubo-ovarian high-grade serous carcinoma (HGSC) is unresponsive to immune checkpoint blockade despite significant frequencies of exhausted Tcells. Here we apply mass cytometry and uncover decidual-like natural killer (dl-NK) cell subpopulations (CD56+CD9+CXCR3+KIR+CD3-CD16-) in newly diagnosed HGSC samples that correlate with both tumor and transitioning epithelial-mesenchymal cell abundance. We show different combinatorial expression patterns of ligands for activating and inhibitory NK receptors within three HGSC tumor compartments: epithelial (E), transitioning epithelial-mesenchymal (EV), and mesenchymal (vimentin expressing [V]), with a more inhibitory ligand phenotype in V cells. In cocultures, NK-92 natural killer cells acquire CD9 from HGSC tumor cells by trogocytosis, resulting in reduced anti-tumor cytokine production and cytotoxicity. Cytotoxicity in these cocultures is restored with a CD9-blocking antibody or CD9 CRISPR knockout, thereby identifying mechanisms of immune suppression in HGSC. CD9 is widely expressed in HGSC tumors and so represents an important new therapeutic target with immediate relevance for NK immunotherapy.
View details for DOI 10.1016/j.celrep.2021.109632
View details for PubMedID 34469729
-
Landscape of innate lymphoid cells in human head and neck cancer reveals divergent NK cell states in the tumor microenvironment.
Proceedings of the National Academy of Sciences of the United States of America
2021; 118 (28)
Abstract
Natural killer (NK) cells comprise one subset of the innate lymphoid cell (ILC) family. Despite reported antitumor functions of NK cells, their tangible contribution to tumor control in humans remains controversial. This is due to incomplete understanding of the NK cell states within the tumor microenvironment (TME). Here, we demonstrate that peripheral circulating NK cells differentiate down two divergent pathways within the TME, resulting in different end states. One resembles intraepithelial ILC1s (ieILC1) and possesses potent in vivo antitumor activity. The other expresses genes associated with immune hyporesponsiveness and has poor antitumor functional capacity. Interleukin-15 (IL-15) and direct contact between the tumor cells and NK cells are required for the differentiation into CD49a+CD103+ cells, resembling ieILC1s. These data explain the similarity between ieILC1s and tissue-resident NK cells, provide insight into the origin of ieILC1s, and identify the ieILC1-like cell state within the TME to be the NK cell phenotype with the greatest antitumor activity. Because the proportions of the different ILC states vary between tumors, these findings provide a resource for the clinical study of innate immune responses against tumors and the design of novel therapy.
View details for DOI 10.1073/pnas.2101169118
View details for PubMedID 34244432
-
Transient rest restores functionality in exhausted CAR-T cells through epigenetic remodeling.
Science (New York, N.Y.)
2021; 372 (6537)
Abstract
T cell exhaustion limits immune responses against cancer and is a major cause of resistance to chimeric antigen receptor (CAR)-T cell therapeutics. Using murine xenograft models and an in vitro model wherein tonic CAR signaling induces hallmark features of exhaustion, we tested the effect of transient cessation of receptor signaling, or rest, on the development and maintenance of exhaustion. Induction of rest through enforced down-regulation of the CAR protein using a drug-regulatable system or treatment with the multikinase inhibitor dasatinib resulted in the acquisition of a memory-like phenotype, global transcriptional and epigenetic reprogramming, and restored antitumor functionality in exhausted CAR-T cells. This work demonstrates that rest can enhance CAR-T cell efficacy by preventing or reversing exhaustion, and it challenges the notion that exhaustion is an epigenetically fixed state.
View details for DOI 10.1126/science.aba1786
View details for PubMedID 33795428
-
Prognostic Gene Expression, Stemness and Immune Microenvironment in Pediatric Tumors.
Cancers
2021; 13 (4)
Abstract
Pediatric tumors frequently arise from embryonal cells, often displaying a stem cell-like ("small round blue") morphology in tissue sections. Because recently "stemness" has been associated with a poor immune response in tumors, we investigated the association of prognostic gene expression, stemness and the immune microenvironment systematically using transcriptomes of 4068 tumors occurring mostly at the pediatric and young adult age. While the prognostic landscape of gene expression (PRECOG) and infiltrating immune cell types (CIBERSORT) is similar to that of tumor entities occurring mainly in adults, the patterns are distinct for each diagnostic entity. A high stemness score (mRNAsi) correlates with clinical and morphologic subtype in Wilms tumors, neuroblastomas, synovial sarcomas, atypical teratoid rhabdoid tumors and germ cell tumors. In neuroblastomas, a high mRNAsi is associated with shortened overall survival. In Wilms tumors a high mRNAsi correlates with blastemal morphology, whereas tumors with predominant epithelial or stromal differentiation have a low mRNAsi and a high percentage of M2 type macrophages. This could be validated in Wilms tumor tissue (n = 78). Here, blastemal areas are low in M2 macrophage infiltrates, while nearby stromal differentiated areas contain abundant M2 macrophages, suggesting local microanatomic regulation of the immune response.
View details for DOI 10.3390/cancers13040854
View details for PubMedID 33670534
-
Atlas of clinically distinct cell states and ecosystems across human solid tumors.
Cell
2021
Abstract
Determining how cells vary with their local signaling environment and organize into distinct cellular communities is critical for understanding processes as diverse as development, aging, and cancer. Here we introduce EcoTyper, a machine learning framework for large-scale identification and validation of cell states and multicellular communities from bulk, single-cell, and spatially resolved gene expression data. When applied to 12 major cell lineages across 16 types of human carcinoma, EcoTyper identified 69 transcriptionally defined cell states. Most states were specific to neoplastic tissue, ubiquitous across tumor types, and significantly prognostic. By analyzing cell-state co-occurrence patterns, we discovered ten clinically distinct multicellular communities with unexpectedly strong conservation, including three with myeloid and stromal elements linked to adverse survival, one enriched in normal tissue, and two associated with early cancer development. This study elucidates fundamental units of cellular organization in human carcinoma and provides a framework for large-scale profiling of cellular ecosystems in any tissue.
View details for DOI 10.1016/j.cell.2021.09.014
View details for PubMedID 34597583
-
HGAL inhibits lymphoma dissemination by interacting with multiple Cytoskeletal proteins.
Blood advances
2021
Abstract
Human Germinal Center Associated Lymphoma (HGAL) is an adaptor protein specifically expressed in germinal center lymphocytes. High expression of HGAL is a predictor of prolonged survival of Diffuse Large B-Cell (DLBCL) and classical Hodgkin lymphomas. Furthermore, HGAL expression is associated with early stage DLBCL, thus potentially limiting lymphoma dissemination. In our previous studies, we demonstrated that HGAL regulates B-cell receptor signaling and cell motility in vitro and deciphered some molecular mechanisms underlying these effects. Herein, by using novel animal models for in vivo DLBCL dispersion, we demonstrate that HGAL decreases lymphoma dissemination and prolongs survival. Further, by using an unbiased proteomic approach we demonstrate that HGAL may interact with multiple cytoskeletal proteins whereby implicating a multiplicity of effects in regulating lymphoma motility and spread. Specifically, we show that HGAL interacts with tubulin and this interaction may also contribute to HGAL effects on cell motility. These findings recapitulate previous observations in humans, establish the role of HGAL in lymphoma in vivo dissemination, and explain improved survival of patients with HGAL expressing lymphomas.
View details for DOI 10.1182/bloodadvances.2021004304
View details for PubMedID 34543391
-
The landscape of tumor cell states and ecosystems in diffuse large B cell lymphoma.
Cancer cell
2021
Abstract
Biological heterogeneity in diffuse large B cell lymphoma (DLBCL) is partly driven by cell-of-origin subtypes and associated genomic lesions, but also by diverse cell types and cell states in the tumor microenvironment (TME). However, dissecting these cell states and their clinical relevance at scale remains challenging. Here, we implemented EcoTyper, a machine-learning framework integrating transcriptome deconvolution and single-cell RNA sequencing, to characterize clinically relevant DLBCL cell states and ecosystems. Using this approach, we identified five cell states of malignant B cells that vary in prognostic associations and differentiation status. We also identified striking variation in cell states for 12 other lineages comprising the TME and forming cell state interactions in stereotyped ecosystems. While cell-of-origin subtypes have distinct TME composition, DLBCL ecosystems capture clinical heterogeneity within existing subtypes and extend beyond cell-of-origin and genotypic classes. These results resolve the DLBCL microenvironment at systems-level resolution and identify opportunities for therapeutic targeting (https://ecotyper.stanford.edu/lymphoma).
View details for DOI 10.1016/j.ccell.2021.08.011
View details for PubMedID 34597589
-
Conditional expression of HGAL leads to the development of diffuse large B-cell lymphoma in mice.
Blood
2020
Abstract
Diffuse large B cell lymphomas (DLBCLs) are clinically and genetically heterogeneous tumors. Deregulation of diverse biological processes specific to B-cells, such as B cell receptor (BCR) signaling and motility regulation contribute to lymphomagenesis. HGAL is a B-cell specific adaptor protein controlling BCR signaling and B lymphocyte motility. In normal B-cells it is expressed in Germinal Center (GC) B lymphocytes and promptly downregulated upon further differentiation. Majority of DLBCL tumors, mainly GC B-cell but also activated types, express HGAL. To investigate the consequences of constitutive expression of HGAL in vivo, we generated mice that conditionally express the human HGAL at different stages of hematopoietic development using three different restricted Cre-mediated approaches to initiate expression of HGAL in hematopoietic stem cells (HSC), pro-B cells or GC B-cells, respectively. Following immune stimulation, we observed larger GCs in mice where HGAL expression was initiated in GC B-cells. All three mouse strains developed DLBCL at a frequency of 12-30% starting at age 13 months, leading to shorter survival. Immunohistochemical studies showed that all analyzed tumors were of the GC B-cell type. Exon sequencing demonstrated mutations reported in human DLBCL. Our data demonstrate that constitutive enforced expression of HGAL leads to DLBCL development.
View details for DOI 10.1182/blood.2020004996
View details for PubMedID 33024996
-
Maternal Anti-Dengue IgG Fucosylation Predicts Susceptibility to Dengue Disease in Infants.
Cell reports
2020; 31 (6): 107642
Abstract
Infant mortality from dengue disease is a devastating global health burden that could be minimized with the ability to identify susceptibility for severe disease prior to infection. Although most primary infant dengue infections are asymptomatic, maternally derived anti-dengue immunoglobulin G (IgGs) present during infection can trigger progression to severe disease through antibody-dependent enhancement mechanisms. Importantly, specific characteristics of maternal IgGs that herald progression to severe infant dengue are unknown. Here, we define ≥10% afucosylation of maternal anti-dengue IgGs as a risk factor for susceptibility of infants to symptomatic dengue infections. Mechanistic experiments show that afucosylation of anti-dengue IgGs promotes FcgammaRIIIa signaling during infection, in turn enhancing dengue virus replication in FcgammaRIIIa+ monocytes. These studies identify a post-translational modification of anti-dengue IgGs that correlates with risk for symptomatic infant dengue infections and define a mechanism by which afucosylated antibodies and FcgammaRIIIa enhance dengue infections.
View details for DOI 10.1016/j.celrep.2020.107642
View details for PubMedID 32402275
-
CRISPR screens in cancer spheroids identify 3D growth-specific vulnerabilities.
Nature
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
-
MYC and Twist1 cooperate to drive metastasis by eliciting crosstalk between cancer and innate immunity.
eLife
2020; 9
Abstract
Metastasis is a major cause of cancer mortality. We generated an autochthonous transgenic mouse model whereby conditional expression of MYC and Twist1 enables hepatocellular carcinoma (HCC) to metastasize in >90% of mice. MYC and Twist1 cooperate and their sustained expression is required to elicit a transcriptional program associated with the activation of innate immunity, through secretion of a cytokinome that elicits recruitment and polarization of tumor associated macrophages (TAMs). Systemic treatment with Ccl2 and Il13 induced MYC-HCCs to metastasize; whereas, blockade of Ccl2 and Il13 abrogated MYC/Twist1-HCC metastasis. Further, in 33 human cancers (n = 9502) MYC and TWIST1 predict poor survival (p=4.3*10-10), CCL2/IL13 expression (p<10-109) and TAM infiltration (p<10-96). Finally, in the plasma of patients with HCC (n = 25) but not cirrhosis (n = 10), CCL2 and IL13 were increased and IL13 predicted invasive tumors. Therefore, MYC and TWIST1 generally appear to cooperate in human cancer to elicit a cytokinome that enables metastasis through crosstalk between cancer and immune microenvironment.
View details for DOI 10.7554/eLife.50731
View details for PubMedID 31933479
-
Multiomic single cell analysis of normal human bone marrow identifies a unique stem and progenitor population that expands in AML
Proceedings of the Annual Meeting of the American Association for Cancer Research 2020
2020
View details for DOI 10.1158/1538-7445.AM2020-3779
-
A human lung tumor microenvironment interactome identifies clinically relevant cell-type cross-talk.
Genome biology
2020; 21 (1): 107
Abstract
Tumors comprise a complex microenvironment of interacting malignant and stromal cell types. Much of our understanding of the tumor microenvironment comes from in vitro studies isolating the interactions between malignant cells and a single stromal cell type, often along a single pathway.To develop a deeper understanding of the interactions between cells within human lung tumors, we perform RNA-seq profiling of flow-sorted malignant cells, endothelial cells, immune cells, fibroblasts, and bulk cells from freshly resected human primary non-small-cell lung tumors. We map the cell-specific differential expression of prognostically associated secreted factors and cell surface genes, and computationally reconstruct cross-talk between these cell types to generate a novel resource called the Lung Tumor Microenvironment Interactome (LTMI). Using this resource, we identify and validate a prognostically unfavorable influence of Gremlin-1 production by fibroblasts on proliferation of malignant lung adenocarcinoma cells. We also find a prognostically favorable association between infiltration of mast cells and less aggressive tumor cell behavior.These results illustrate the utility of the LTMI as a resource for generating hypotheses concerning tumor-microenvironment interactions that may have prognostic and therapeutic relevance.
View details for DOI 10.1186/s13059-020-02019-x
View details for PubMedID 32381040
-
The Immune Landscape of Cancer.
Immunity
2019; 51 (2): 411–12
View details for DOI 10.1016/j.immuni.2019.08.004
View details for PubMedID 31433971
-
LMO2 Confers Synthetic Lethality to PARP Inhibition in DLBCL.
Cancer cell
2019
Abstract
Deficiency in DNA double-strand break (DSB) repair mechanisms has been widely exploited for the treatment of different malignances, including homologous recombination (HR)-deficient breast and ovarian cancers. Here we demonstrate that diffuse large B cell lymphomas (DLBCLs) expressing LMO2 protein are functionally deficient in HR-mediated DSB repair. Mechanistically, LMO2 inhibits BRCA1 recruitment to DSBs by interacting with 53BP1 during repair. Similar to BRCA1-deficient cells, LMO2-positive DLBCLs and Tcell acute lymphoblastic leukemia (T-ALL) cells exhibit a high sensitivity to poly(ADP-ribose) polymerase (PARP) inhibitors. Furthermore, chemotherapy and PARP inhibitors synergize to inhibit the growth of LMO2-positive tumors. Together, our results reveal that LMO2 expression predicts HR deficiency and the potential therapeutic use of PARP inhibitors in DLBCL and T-ALL.
View details for DOI 10.1016/j.ccell.2019.07.007
View details for PubMedID 31447348
-
Determining cell type abundance and expression from bulk tissues with digital cytometry
NATURE BIOTECHNOLOGY
2019; 37 (7): 773-+
View details for DOI 10.1038/s41587-019-0114-2
View details for Web of Science ID 000478028700023
-
Targetable genetic alterations of TCF4 (E2-2) drive immunoglobulin expression in diffuse large B cell lymphoma.
Science translational medicine
2019; 11 (497)
Abstract
The activated B cell (ABC-like) subtype of diffuse large B cell lymphoma (DLBCL) is characterized by chronic activation of signaling initiated by immunoglobulin mu (IgM). By analyzing the DNA copy number profiles of 1000 DLBCL tumors, we identified gains of 18q21.2 as the most frequent genetic alteration in ABC-like DLBCL. Using integrative analysis of matched gene expression profiling data, we found that the TCF4 (E2-2) transcription factor gene was the target of these alterations. Overexpression of TCF4 in ABC-like DLBCL cell lines led to its occupancy on immunoglobulin (IGHM) and MYC gene enhancers and increased expression of these genes at the transcript and protein levels. Inhibition of TCF4 activity with dominant-negative constructs was synthetically lethal to ABC-like DLBCL cell lines harboring TCF4 DNA copy gains, highlighting these gains as an attractive potential therapeutic target. Furthermore, the TCF4 gene was one of the top BRD4-regulated genes in DLBCL cell lines. BET proteolysis-targeting chimera (PROTAC) ARV771 extinguished TCF4, MYC, and IgM expression and killed ABC-like DLBCL cells in vitro. In DLBCL xenograft models, ARV771 treatment reduced tumor growth and prolonged survival. This work highlights a genetic mechanism for promoting immunoglobulin signaling in ABC-like DLBCL and provides a functional rationale for the use of BET inhibitors in this disease.
View details for DOI 10.1126/scitranslmed.aav5599
View details for PubMedID 31217338
-
Data mining for mutation-specific targets in acute myeloid leukemia
LEUKEMIA
2019; 33 (4): 826–43
View details for DOI 10.1038/s41375-019-0387-y
View details for Web of Science ID 000463162400002
-
Determining cell type abundance and expression from bulk tissues with digital cytometry.
Nature biotechnology
2019
Abstract
Single-cell RNA-sequencing has emerged as a powerful technique for characterizing cellular heterogeneity, but it is currently impractical on large sample cohorts and cannot be applied to fixed specimens collected as part of routine clinical care. We previously developed an approach for digital cytometry, called CIBERSORT, that enables estimation of cell type abundances from bulk tissue transcriptomes. We now introduce CIBERSORTx, a machine learning method that extends this framework to infer cell-type-specific gene expression profiles without physical cell isolation. By minimizing platform-specific variation, CIBERSORTx also allows the use of single-cell RNA-sequencing data for large-scale tissue dissection. We evaluated the utility of CIBERSORTx in multiple tumor types, including melanoma, where single-cell reference profiles were used to dissect bulk clinical specimens, revealing cell-type-specific phenotypic states linked to distinct driver mutations and response to immune checkpoint blockade. We anticipate that digital cytometry will augment single-cell profiling efforts, enabling cost-effective, high-throughput tissue characterization without the need for antibodies, disaggregation or viable cells.
View details for PubMedID 31061481
-
Prognostic profiling of the immune cell microenvironment in Ewings Sarcoma Family of Tumors.
Oncoimmunology
2019; 8 (12): e1674113
Abstract
Ewings Sarcoma Family of Tumors (ESFT) are clinically aggressive bone and soft tissue tumors in children and young adults. Analysis of the immune tumor microenvironment (TME) provides insight into tumor evolution and novel treatment options. So far, the scarcity of immune cells in ESFT has hindered a comprehensive analysis of rare subtypes. We determined the relative fraction of 22 immune cell types using 197 microarray gene expression datasets of primary ESFT tumor samples by using CIBERSORT, a deconvolution algorithm enumerating infiltrating leucocytes in bulk tumor tissue. The most abundant cells were macrophages (mean 43% of total tumor-infiltrating leukocytes, TILs), predominantly immunosuppressive M2 type macrophages, followed by T cells (mean 23% of TILs). Increased neutrophils, albeit at low number, were associated with a poor overall survival (OS) (p = .038) and increased M2 macrophages predicted a shorter event-free survival (EFS) (p = .033). High frequency of T cells and activated NK cells correlated with prolonged OS (p = .044 and p = .007, respectively). A small patient population (9/32) with combined low infiltrating M2 macrophages, low neutrophils, and high total T cells was identified with favorable outcome. This finding was confirmed in a validation cohort of patients with follow up (11/38). When comparing the immune TME with expression of known stemness genes, hypoxia-inducible factor 1 alpha (HIF1alpha) correlated with high abundance of macrophages and neutrophils and decreased T cell levels. The immune TME in ESFTs shows a distinct composition including rare immune cell subsets that in part may be due to expression of HIF1alpha.
View details for DOI 10.1080/2162402X.2019.1674113
View details for PubMedID 31741777
-
Comprehensive analysis of cancer stemness
AMER ASSOC CANCER RESEARCH. 2018
View details for DOI 10.1158/1538-7445.AM2018-LB-373
View details for Web of Science ID 000468818900505
-
GFPT2-expressing cancer-associated fibroblasts mediate metabolic reprogramming in human lung adenocarcinoma.
Cancer research
2018
Abstract
Metabolic reprogramming of the tumor microenvironment is recognized as a cancer hallmark. To identify new molecular processes associated with tumor metabolism, we analyzed the transcriptome of bulk and flow-sorted human primary non-small cell lung cancer (NSCLC) together with 18FDG-positron emission tomography scans, which provide a clinical measure of glucose uptake. Tumors with higher glucose uptake were functionally enriched for molecular processes associated with invasion in adenocarcinoma (AD) and cell growth in squamous cell carcinoma (SCC). Next, we identified genes correlated to glucose uptake that were predominately overexpressed in a single cell-type comprising the tumor microenvironment. For SCC, most of these genes were expressed by malignant cells, whereas in AD they were predominately expressed by stromal cells, particularly cancer-associated fibroblasts (CAFs). Among these AD genes correlated to glucose uptake, we focused on Glutamine-Fructose-6-Phosphate Transaminase 2 (GFPT2), which codes for the Glutamine-Fructose-6-Phosphate Aminotransferase 2 (GFAT2), a rate-limiting enzyme of the hexosamine biosynthesis pathway (HBP), which is responsible for glycosylation. GFPT2 was predictive of glucose uptake independent of GLUT1, the primary glucose transporter, and was prognostically significant at both gene and protein level. We confirmed that normal fibroblasts transformed to CAF-like cells, following TGF-beta treatment, upregulated HBP genes, including GFPT2, with less change in genes driving glycolysis, pentose phosphate pathway and TCA cycle. Our work provides new evidence of histology-specific tumor-stromal properties associated with glucose uptake in NSCLC and identifies GFPT2 as a critical regulator of tumor metabolic reprogramming in AD.
View details for PubMedID 29760045
-
The Immune Landscape of Cancer
IMMUNITY
2018; 48 (4): 812-+
Abstract
We performed an extensive immunogenomic analysis of more than 10,000 tumors comprising 33 diverse cancer types by utilizing data compiled by TCGA. Across cancer types, we identified six immune subtypes-wound healing, IFN-γ dominant, inflammatory, lymphocyte depleted, immunologically quiet, and TGF-β dominant-characterized by differences in macrophage or lymphocyte signatures, Th1:Th2 cell ratio, extent of intratumoral heterogeneity, aneuploidy, extent of neoantigen load, overall cell proliferation, expression of immunomodulatory genes, and prognosis. Specific driver mutations correlated with lower (CTNNB1, NRAS, or IDH1) or higher (BRAF, TP53, or CASP8) leukocyte levels across all cancers. Multiple control modalities of the intracellular and extracellular networks (transcription, microRNAs, copy number, and epigenetic processes) were involved in tumor-immune cell interactions, both across and within immune subtypes. Our immunogenomics pipeline to characterize these heterogeneous tumors and the resulting data are intended to serve as a resource for future targeted studies to further advance the field.
View details for PubMedID 29628290
-
Machine Learning Identifies Stemness Features Associated with Oncogenic Dedifferentiation
CELL
2018; 173 (2): 338-+
Abstract
Cancer progression involves the gradual loss of a differentiated phenotype and acquisition of progenitor and stem-cell-like features. Here, we provide novel stemness indices for assessing the degree of oncogenic dedifferentiation. We used an innovative one-class logistic regression (OCLR) machine-learning algorithm to extract transcriptomic and epigenetic feature sets derived from non-transformed pluripotent stem cells and their differentiated progeny. Using OCLR, we were able to identify previously undiscovered biological mechanisms associated with the dedifferentiated oncogenic state. Analyses of the tumor microenvironment revealed unanticipated correlation of cancer stemness with immune checkpoint expression and infiltrating immune cells. We found that the dedifferentiated oncogenic phenotype was generally most prominent in metastatic tumors. Application of our stemness indices to single-cell data revealed patterns of intra-tumor molecular heterogeneity. Finally, the indices allowed for the identification of novel targets and possible targeted therapies aimed at tumor differentiation.
View details for PubMedID 29625051
-
Subtype assignment of CLL based on B-cell subset associated gene signatures from normal bone marrow - A proof of concept study
PLOS ONE
2018; 13 (3): e0193249
Abstract
Diagnostic and prognostic evaluation of chronic lymphocytic leukemia (CLL) involves blood cell counts, immunophenotyping, IgVH mutation status, and cytogenetic analyses. We generated B-cell associated gene-signatures (BAGS) based on six naturally occurring B-cell subsets within normal bone marrow. Our hypothesis is that by segregating CLL according to BAGS, we can identify subtypes with prognostic implications in support of pathogenetic value of BAGS. Microarray-based gene-expression samples from eight independent CLL cohorts (1,024 untreated patients) were BAGS-stratified into pre-BI, pre-BII, immature, naïve, memory, or plasma cell subtypes; the majority falling within the memory (24.5-45.8%) or naïve (14.5-32.3%) categories. For a subset of CLL patients (n = 296), time to treatment (TTT) was shorter amongst early differentiation subtypes (pre-BI/pre-BII/immature) compared to late subtypes (memory/plasma cell, HR: 0.53 [0.35-0.78]). Particularly, pre-BII subtype patients had the shortest TTT among all subtypes. Correlates derived for BAGS subtype and IgVH mutation (n = 405) revealed an elevated mutation frequency in late vs. early subtypes (71% vs. 45%, P < .001). Predictions for BAGS subtype resistance towards rituximab and cyclophosphamide varied for rituximab, whereas all subtypes were sensitive to cyclophosphamide. This study supports our hypothesis that BAGS-subtyping may be of tangible prognostic and pathogenetic value for CLL patients.
View details for DOI 10.1371/journal.pone.0193249
View details for Web of Science ID 000426896800048
View details for PubMedID 29513759
View details for PubMedCentralID PMC5841735
-
Brd4 regulates the expression of essential autophagy genes and Keap1 in AML cells.
Oncotarget
2018; 9 (14): 11665–76
Abstract
We have recently reported that activation of Brd4 is associated with the presence of autophagy in NPMc+ and MLL AML cells. In order to determine the mechanisms underlying this relationship, we have examined the role of Brd4 in regulating the expression of several genes that are central to the process of autophagy. We found that Brd4 binds to the promoters of ATG 3, 7 and CEBPbeta, and expression of these genes is markedly reduced by inhibitors of Brd4, as well as by Brd4-shRNA and depletion of CEBPbeta. Inhibitors of Brd4 also dramatically suppress the transcription of Keap1, thereby increasing the expression of anti-oxidant genes through the Nrf2 pathway and reducing the cytotoxicity induced by Brd4 inhibitors. Elimination of ATG3 or KEAP1 expression using CRISPR-cas9 mediated genomic editing markedly reduced autophagy. We conclude that Brd4 plays a significant role in autophagy activation through the direct transcriptional regulation of genes essential for it, as well as through the Keap1-Nrf2 axis in NPMc+ and MLL-fusion AML cells.
View details for PubMedID 29545928
-
Module Analysis Captures Pancancer Genetically and Epigenetically Deregulated Cancer Driver Genes for Smoking and Antiviral Response.
EBioMedicine
2018; 27: 156–66
Abstract
The availability of increasing volumes of multi-omics profiles across many cancers promises to improve our understanding of the regulatory mechanisms underlying cancer. The main challenge is to integrate these multiple levels of omics profiles and especially to analyze them across many cancers. Here we present AMARETTO, an algorithm that addresses both challenges in three steps. First, AMARETTO identifies potential cancer driver genes through integration of copy number, DNA methylation and gene expression data. Then AMARETTO connects these driver genes with co-expressed target genes that they control, defined as regulatory modules. Thirdly, we connect AMARETTO modules identified from different cancer sites into a pancancer network to identify cancer driver genes. Here we applied AMARETTO in a pancancer study comprising eleven cancer sites and confirmed that AMARETTO captures hallmarks of cancer. We also demonstrated that AMARETTO enables the identification of novel pancancer driver genes. In particular, our analysis led to the identification of pancancer driver genes of smoking-induced cancers and 'antiviral' interferon-modulated innate immune response.AMARETTO is available as an R package at https://bitbucket.org/gevaertlab/pancanceramaretto.
View details for PubMedID 29331675
-
Quantification of Macrophages in High-Grade Gliomas by Using Ferumoxytol-enhanced MRI: A Pilot Study.
Radiology
2018: 181204
Abstract
Purpose To investigate ferumoxytol-enhanced MRI as a noninvasive imaging biomarker of macrophages in adults with high-grade gliomas. Materials and Methods In this prospective study, adults with high-grade gliomas were enrolled between July 2015 and July 2017. Each participant was administered intravenous ferumoxytol (5 mg/kg) and underwent 3.0-T MRI 24 hours later. Two sites in each tumor were selected for intraoperative sampling on the basis of the degree of ferumoxytol-induced signal change. Susceptibility and the relaxation rates R2* (1/T2*) and R2 (1/T2) were obtained by region-of-interest analysis by using the respective postprocessed maps. Each sample was stained with Prussian blue, CD68, CD163, and glial fibrillary acidic protein. Pearson correlation and linear mixed models were performed to assess the relationship between imaging measurements and number of 400× magnification high-power fields with iron-containing macrophages. Results Ten adults (four male participants [mean age, 65 years ± 9 {standard deviation}; age range, 57-74 years] and six female participants [mean age, 53 years ± 12 years; age range, 32-65 years]; mean age of all participants, 58 years ± 12 [age range, 32-74 years]) with high-grade gliomas were included. Significant positive correlations were found between susceptibility, R2*, and R2' and the number of high-power fields with CD163-positive (r range, 0.64-0.71; P < .01) and CD68-positive (r range, 0.55-0.57; P value range, .01-.02) iron-containing macrophages. No significant correlation was found between R2 and CD163-positive (r = 0.33; P = .16) and CD68-positive (r = 0.24; P = .32) iron-containing macrophages. Similar significance results were obtained with linear mixed models. At histopathologic analysis, iron particles were found only in macrophages; none was found in glial fibrillary acidic protein-positive tumor cells. Conclusion MRI measurements of susceptibility, R2*, and R2' (R2* - R2) obtained after ferumoxytol administration correlate with iron-containing macrophage concentration, and this shows their potential as quantitative imaging markers of macrophages in malignant gliomas. © RSNA, 2018 Online supplemental material is available for this article.
View details for PubMedID 30398435
-
Non-Small Cell Lung Cancer Radiogenomics Map Identifies Relationships between Molecular and Imaging Phenotypes with Prognostic Implications.
Radiology
2018; 286 (1): 307–15
Abstract
Purpose To create a radiogenomic map linking computed tomographic (CT) image features and gene expression profiles generated by RNA sequencing for patients with non-small cell lung cancer (NSCLC). Materials and Methods A cohort of 113 patients with NSCLC diagnosed between April 2008 and September 2014 who had preoperative CT data and tumor tissue available was studied. For each tumor, a thoracic radiologist recorded 87 semantic image features, selected to reflect radiologic characteristics of nodule shape, margin, texture, tumor environment, and overall lung characteristics. Next, total RNA was extracted from the tissue and analyzed with RNA sequencing technology. Ten highly coexpressed gene clusters, termed metagenes, were identified, validated in publicly available gene-expression cohorts, and correlated with prognosis. Next, a radiogenomics map was built that linked semantic image features to metagenes by using the t statistic and the Spearman correlation metric with multiple testing correction. Results RNA sequencing analysis resulted in 10 metagenes that capture a variety of molecular pathways, including the epidermal growth factor (EGF) pathway. A radiogenomic map was created with 32 statistically significant correlations between semantic image features and metagenes. For example, nodule attenuation and margins are associated with the late cell-cycle genes, and a metagene that represents the EGF pathway was significantly correlated with the presence of ground-glass opacity and irregular nodules or nodules with poorly defined margins. Conclusion Radiogenomic analysis of NSCLC showed multiple associations between semantic image features and metagenes that represented canonical molecular pathways, and it can result in noninvasive identification of molecular properties of NSCLC. Online supplemental material is available for this article.
View details for PubMedID 28727543
-
Human AML-iPSCs Reacquire Leukemic Properties after Differentiation and Model Clonal Variation of Disease.
Cell stem cell
2017; 20 (3): 329-344 e7
Abstract
Understanding the relative contributions of genetic and epigenetic abnormalities to acute myeloid leukemia (AML) should assist integrated design of targeted therapies. In this study, we generated induced pluripotent stem cells (iPSCs) from AML patient samples harboring MLL rearrangements and found that they retained leukemic mutations but reset leukemic DNA methylation/gene expression patterns. AML-iPSCs lacked leukemic potential, but when differentiated into hematopoietic cells, they reacquired the ability to give rise to leukemia in vivo and reestablished leukemic DNA methylation/gene expression patterns, including an aberrant MLL signature. Epigenetic reprogramming was therefore not sufficient to eliminate leukemic behavior. This approach also allowed us to study the properties of distinct AML subclones, including differential drug susceptibilities of KRAS mutant and wild-type cells, and predict relapse based on increased cytarabine resistance of a KRAS wild-type subclone. Overall, our findings illustrate the value of AML-iPSCs for investigating the mechanistic basis and clonal properties of human AML.
View details for DOI 10.1016/j.stem.2016.11.018
View details for PubMedID 28089908
-
Identification of an atypical etiological head and neck squamous carcinoma subtype featuring the CpG island methylator phenotype.
EBioMedicine
2017; 17: 223-236
Abstract
Head and neck squamous cell carcinoma (HNSCC) is broadly classified into HNSCC associated with human papilloma virus (HPV) infection, and HPV negative HNSCC, which is typically smoking-related. A subset of HPV negative HNSCCs occur in patients without smoking history, however, and these etiologically 'atypical' HNSCCs disproportionately occur in the oral cavity, and in female patients, suggesting a distinct etiology. To investigate the determinants of clinical and molecular heterogeneity, we performed unsupervised clustering to classify 528 HNSCC patients from The Cancer Genome Atlas (TCGA) into putative intrinsic subtypes based on their profiles of epigenetically (DNA methylation) deregulated genes. HNSCCs clustered into five subtypes, including one HPV positive subtype, two smoking-related subtypes, and two atypical subtypes. One atypical subtype was particularly genomically stable, but featured widespread gene silencing associated with the 'CpG island methylator phenotype' (CIMP). Further distinguishing features of this 'CIMP-Atypical' subtype include an antiviral gene expression profile associated with pro-inflammatory M1 macrophages and CD8+ T cell infiltration, CASP8 mutations, and a well-differentiated state corresponding to normal SOX2 copy number and SOX2OT hypermethylation. We developed a gene expression classifier for the CIMP-Atypical subtype that could classify atypical disease features in two independent patient cohorts, demonstrating the reproducibility of this subtype. Taken together, these findings provide unprecedented evidence that atypical HNSCC is molecularly distinct, and postulates the CIMP-Atypical subtype as a distinct clinical entity that may be caused by chronic inflammation.
View details for DOI 10.1016/j.ebiom.2017.02.025
View details for PubMedID 28314692
-
Low BUB1 expression is an adverse prognostic marker in gastric adenocarcinoma.
Oncotarget
2017; 8 (44): 76329–39
Abstract
Gastric adenocarcinomas are associated with a poor prognosis due to the fact that the tumor has often metastasized by the time of diagnosis and prognostic markers are urgently needed to tailor treatment. We examined the expression of the mitotic spindle checkpoint protein BUB1 (budding uninhibited by benzimidazoles 1) and Ki-67 protein expression by immunohistochemistry in 218 patients with primary gastric adenocarcinomas. Tumors with low frequency of BUB1 expression were associated with larger tumor size (pT) (p < 0.001), higher incidence of lymph node metastases (pN) (p = 0.027), distant metastases (pM) (p = 0.006) and higher UICC stage (p < 0.001). Furthermore, BUB1 expression was inversely correlated with residual tumor stage (p = 0.038). Abundant BUB1 protein expression correlated with frequent Ki-67 protein expression (p < 0.001) and low BUB1 expression was associated with shorter survival (p < 0.001). Univariate and multivariate analyses confirmed BUB1 to be an independent prognostic marker in gastric cancer (p = 0.021).
View details for PubMedID 29100315
View details for PubMedCentralID PMC5652709
-
NSD1 inactivation defines an immune cold, DNA hypomethylated subtype in squamous cell carcinoma.
Scientific reports
2017; 7 (1): 17064
Abstract
Chromatin modifying enzymes are frequently mutated in cancer, resulting in widespread epigenetic deregulation. Recent reports indicate that inactivating mutations in the histone methyltransferase NSD1 define an intrinsic subtype of head and neck squamous cell carcinoma (HNSC) that features pronounced DNA hypomethylation. Here, we describe a similar hypomethylated subtype of lung squamous cell carcinoma (LUSC) that is enriched for both inactivating mutations and deletions in NSD1. The 'NSD1 subtypes' of HNSC and LUSC are highly correlated at the DNA methylation and gene expression levels, featuring ectopic expression of developmental transcription factors and genes that are also hypomethylated in Sotos syndrome, a congenital disorder caused by germline NSD1 mutations. Further, the NSD1 subtype of HNSC displays an 'immune cold' phenotype characterized by low infiltration of tumor-associated leukocytes, particularly macrophages and CD8+ T cells, as well as low expression of genes encoding the immunotherapy target PD-1 immune checkpoint receptor and its ligands. Using an in vivo model, we demonstrate that NSD1 inactivation results in reduced T cell infiltration into the tumor microenvironment, implicating NSD1 as a tumor cell-intrinsic driver of an immune cold phenotype. NSD1 inactivation therefore causes epigenetic deregulation across cancer sites, and has implications for immunotherapy.
View details for PubMedID 29213088
-
Data normalization considerations for digital tumor dissection.
Genome biology
2017; 18 (1): 128
Abstract
In a recently published article in Genome Biology, Li and colleagues introduced TIMER, a gene expression deconvolution approach for studying tumor-infiltrating leukocytes (TILs) in 23 cancer types profiled by The Cancer Genome Atlas. Methods to characterize TIL biology are increasingly important, and the authors offer several arguments in favor of their strategy. Several of these claims warrant further discussion and highlight the critical importance of data normalization in gene expression deconvolution applications.Please see related Li et al correspondence: www.dx.doi.org/10.1186/s13059-017-1256-5 and Zheng correspondence: www.dx.doi.org/10.1186/s13059-017-1258-3.
View details for PubMedID 28679399
-
Role of KEAP1/NRF2 and TP53 Mutations in Lung Squamous Cell Carcinoma Development and Radiation Resistance.
Cancer discovery
2016
Abstract
Lung squamous cell carcinoma (LSCC) pathogenesis remains incompletely understood, and biomarkers predicting treatment response remain lacking. Here, we describe novel murine LSCC models driven by loss of Trp53 and Keap1, both of which are frequently mutated in human LSCCs. Homozygous inactivation of Keap1 or Trp53 promoted airway basal stem cell (ABSC) self-renewal, suggesting that mutations in these genes lead to expansion of mutant stem cell clones. Deletion of Trp53 and Keap1 in ABSCs, but not more differentiated tracheal cells, produced tumors recapitulating histologic and molecular features of human LSCCs, indicating that they represent the likely cell of origin in this model. Deletion of Keap1 promoted tumor aggressiveness, metastasis, and resistance to oxidative stress and radiotherapy (RT). KEAP1/NRF2 mutation status predicted risk of local recurrence after RT in patients with non-small lung cancer (NSCLC) and could be noninvasively identified in circulating tumor DNA. Thus, KEAP1/NRF2 mutations could serve as predictive biomarkers for personalization of therapeutic strategies for NSCLCs.We developed an LSCC mouse model involving Trp53 and Keap1, which are frequently mutated in human LSCCs. In this model, ABSCs are the cell of origin of these tumors. KEAP1/NRF2 mutations increase radioresistance and predict local tumor recurrence in radiotherapy patients. Our findings are of potential clinical relevance and could lead to personalized treatment strategies for tumors with KEAP1/NRF2 mutations. Cancer Discov; 7(1); 86-101. ©2016 AACR.This article is highlighted in the In This Issue feature, p. 1.
View details for PubMedID 27663899
-
Pathophysiological significance and therapeutic targeting of germinal center kinase in diffuse large B-cell lymphoma.
Blood
2016; 128 (2): 239-248
Abstract
Diffuse large B-cell lymphoma (DLBCL) is the most common subtype of non-Hodgkin lymphoma (NHL), yet 40-50% of patients will eventually succumb to their disease demonstrating a pressing need for novel therapeutic options. Gene expression profiling has identified messenger RNA's that lead to transformation, but critical events transforming cells are normally executed by kinases. Therefore, we hypothesized that previously unrecognized kinases may contribute to DLBCL pathogenesis. We performed the first comprehensive analysis of global kinase activity in DLBCL, to identify novel therapeutic targets, and discovered that Germinal Center Kinase (GCK) was extensively activated. GCK RNA interference and small molecule inhibition induced cell cycle arrest and apoptosis in DLBCL cell lines and primary tumors in vitro and decreased the tumor growth rate in vivo, resulting in a significantly extended lifespan of mice bearing DLBCL xenografts. GCK expression was also linked to adverse clinical outcome in a cohort of 151 primary DLBCL patients. These studies demonstrate, for the first time, that GCK is a molecular therapeutic target in DLBCL tumors and that inhibiting GCK may significantly extend DLBCL patient survival. Since the majority of DLBCL tumors (~80%) exhibit activation of GCK, this therapy may be applicable to most patients.
View details for DOI 10.1182/blood-2016-02-696856
View details for PubMedID 27151888
-
Identifying Network Perturbation in Cancer
PLOS COMPUTATIONAL BIOLOGY
2016; 12 (5)
Abstract
We present a computational framework, called DISCERN (DIfferential SparsE Regulatory Network), to identify informative topological changes in gene-regulator dependence networks inferred on the basis of mRNA expression datasets within distinct biological states. DISCERN takes two expression datasets as input: an expression dataset of diseased tissues from patients with a disease of interest and another expression dataset from matching normal tissues. DISCERN estimates the extent to which each gene is perturbed-having distinct regulator connectivity in the inferred gene-regulator dependencies between the disease and normal conditions. This approach has distinct advantages over existing methods. First, DISCERN infers conditional dependencies between candidate regulators and genes, where conditional dependence relationships discriminate the evidence for direct interactions from indirect interactions more precisely than pairwise correlation. Second, DISCERN uses a new likelihood-based scoring function to alleviate concerns about accuracy of the specific edges inferred in a particular network. DISCERN identifies perturbed genes more accurately in synthetic data than existing methods to identify perturbed genes between distinct states. In expression datasets from patients with acute myeloid leukemia (AML), breast cancer and lung cancer, genes with high DISCERN scores in each cancer are enriched for known tumor drivers, genes associated with the biological processes known to be important in the disease, and genes associated with patient prognosis, in the respective cancer. Finally, we show that DISCERN can uncover potential mechanisms underlying network perturbation by explaining observed epigenomic activity patterns in cancer and normal tissue types more accurately than alternative methods, based on the available epigenomic data from the ENCODE project.
View details for DOI 10.1371/journal.pcbi.1004888
View details for Web of Science ID 000379348100011
View details for PubMedID 27145341
View details for PubMedCentralID PMC4856318
-
Gene expression analysis of plasmablastic lymphoma identifies downregulation of B-cell receptor signaling and additional unique transcriptional programs
LEUKEMIA
2015; 29 (11): 2270-2273
View details for DOI 10.1038/leu.2015.109
View details for Web of Science ID 000364527400020
View details for PubMedID 25921246
-
Integrating Tumor and Stromal Gene Expression Signatures With Clinical Indices for Survival Stratification of Early-Stage Non-Small Cell Lung Cancer.
Journal of the National Cancer Institute
2015; 107 (10)
Abstract
Accurate survival stratification in early-stage non-small cell lung cancer (NSCLC) could inform the use of adjuvant therapy. We developed a clinically implementable mortality risk score incorporating distinct tumor microenvironmental gene expression signatures and clinical variables.Gene expression profiles from 1106 nonsquamous NSCLCs were used for generation and internal validation of a nine-gene molecular prognostic index (MPI). A quantitative polymerase chain reaction (qPCR) assay was developed and validated on an independent cohort of formalin-fixed paraffin-embedded (FFPE) tissues (n = 98). A prognostic score using clinical variables was generated using Surveillance, Epidemiology, and End Results data and combined with the MPI. All statistical tests for survival were two-sided.The MPI stratified stage I patients into prognostic categories in three microarray and one FFPE qPCR validation cohorts (HR = 2.99, 95% CI = 1.55 to 5.76, P < .001 in stage IA patients of the largest microarray validation cohort; HR = 3.95, 95% CI = 1.24 to 12.64, P = .01 in stage IA of the qPCR cohort). Prognostic genes were expressed in distinct tumor cell subpopulations, and genes implicated in proliferation and stem cells portended poor outcomes, while genes involved in normal lung differentiation and immune infiltration were associated with superior survival. Integrating the MPI with clinical variables conferred greatest prognostic power (HR = 3.43, 95% CI = 2.18 to 5.39, P < .001 in stage I patients of the largest microarray cohort; HR = 3.99, 95% CI = 1.67 to 9.56, P < .001 in stage I patients of the qPCR cohort). Finally, the MPI was prognostic irrespective of somatic alterations in EGFR, KRAS, TP53, and ALK.The MPI incorporates genes expressed in the tumor and its microenvironment and can be implemented clinically using qPCR assays on FFPE tissues. A composite model integrating the MPI with clinical variables provides the most accurate risk stratification.
View details for DOI 10.1093/jnci/djv211
View details for PubMedID 26286589
-
CD93 Marks a Non-Quiescent Human Leukemia Stem Cell Population and Is Required for Development of MLL-Rearranged Acute Myeloid Leukemia.
Cell stem cell
2015; 17 (4): 412-421
Abstract
Leukemia stem cells (LSCs) are thought to share several properties with hematopoietic stem cells (HSCs), including cell-cycle quiescence and a capacity for self-renewal. These features are hypothesized to underlie leukemic initiation, progression, and relapse, and they also complicate efforts to eradicate leukemia through therapeutic targeting of LSCs without adverse effects on HSCs. Here, we show that acute myeloid leukemias (AMLs) with genomic rearrangements of the MLL gene contain a non-quiescent LSC population. Although human CD34(+)CD38(-) LSCs are generally highly quiescent, the C-type lectin CD93 is expressed on a subset of actively cycling, non-quiescent AML cells enriched for LSC activity. CD93 expression is functionally required for engraftment of primary human AML LSCs and leukemogenesis, and it regulates LSC self-renewal predominantly by silencing CDKN2B, a major tumor suppressor in AML. Thus, CD93 expression identifies a predominantly cycling, non-quiescent leukemia-initiating cell population in MLL-rearranged AML, providing opportunities for selective targeting and eradication of LSCs.
View details for DOI 10.1016/j.stem.2015.08.008
View details for PubMedID 26387756
View details for PubMedCentralID PMC4592469
-
An LSC epigenetic signature is largely mutation independent and implicates the HOXA cluster in AML pathogenesis
NATURE COMMUNICATIONS
2015; 6
Abstract
Acute myeloid leukaemia (AML) is characterized by subpopulations of leukaemia stem cells (LSCs) that are defined by their ability to engraft in immunodeficient mice. Here we show an LSC DNA methylation signature, derived from xenografts and integration with gene expression that is comprised of 71 genes and identifies a key role for the HOXA cluster. Most of the genes are epigenetically regulated independently of underlying mutations, although several are downstream targets of epigenetic modifier genes mutated in AML. The LSC epigenetic signature is associated with poor prognosis independent of known risk factors such as age and cytogenetics. Analysis of early haematopoietic progenitors from normal individuals reveals two distinct clusters of AML LSC resembling either lymphoid-primed multipotent progenitors or granulocyte/macrophage progenitors. These results provide evidence for DNA methylation variation between AML LSCs and their blast progeny, and identify epigenetically distinct subgroups of AML likely reflecting the cell of origin.
View details for DOI 10.1038/ncomms9489
View details for Web of Science ID 000364941300001
View details for PubMedID 26444494
View details for PubMedCentralID PMC4633733
-
The prognostic landscape of genes and infiltrating immune cells across human cancers
NATURE MEDICINE
2015; 21 (8): 938-945
Abstract
Molecular profiles of tumors and tumor-associated cells hold great promise as biomarkers of clinical outcomes. However, existing data sets are fragmented and difficult to analyze systematically. Here we present a pan-cancer resource and meta-analysis of expression signatures from ∼18,000 human tumors with overall survival outcomes across 39 malignancies. By using this resource, we identified a forkhead box MI (FOXM1) regulatory network as a major predictor of adverse outcomes, and we found that expression of favorably prognostic genes, including KLRB1 (encoding CD161), largely reflect tumor-associated leukocytes. By applying CIBERSORT, a computational approach for inferring leukocyte representation in bulk tumor transcriptomes, we identified complex associations between 22 distinct leukocyte subsets and cancer survival. For example, tumor-associated neutrophil and plasma cell signatures emerged as significant but opposite predictors of survival for diverse solid tumors, including breast and lung adenocarcinomas. This resource and associated analytical tools (http://precog.stanford.edu) may help delineate prognostic genes and leukocyte subsets within and across cancers, shed light on the impact of tumor heterogeneity on cancer outcomes, and facilitate the discovery of biomarkers and therapeutic targets.
View details for DOI 10.1038/nm.3909
View details for PubMedID 26193342
-
Robust enumeration of cell subsets from tissue expression profiles.
Nature methods
2015; 12 (5): 453-457
Abstract
We introduce CIBERSORT, a method for characterizing cell composition of complex tissues from their gene expression profiles. When applied to enumeration of hematopoietic subsets in RNA mixtures from fresh, frozen and fixed tissues, including solid tumors, CIBERSORT outperformed other methods with respect to noise, unknown mixture content and closely related cell types. CIBERSORT should enable large-scale analysis of RNA mixtures for cellular biomarkers and therapeutic targets (http://cibersort.stanford.edu/).
View details for DOI 10.1038/nmeth.3337
View details for PubMedID 25822800
-
Reprogramming of primary human Philadelphia chromosome-positive B cell acute lymphoblastic leukemia cells into nonleukemic macrophages
PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA
2015; 112 (13): 4074-4079
Abstract
BCR-ABL1(+) precursor B-cell acute lymphoblastic leukemia (BCR-ABL1(+) B-ALL) is an aggressive hematopoietic neoplasm characterized by a block in differentiation due in part to the somatic loss of transcription factors required for B-cell development. We hypothesized that overcoming this differentiation block by forcing cells to reprogram to the myeloid lineage would reduce the leukemogenicity of these cells. We found that primary human BCR-ABL1(+) B-ALL cells could be induced to reprogram into macrophage-like cells by exposure to myeloid differentiation-promoting cytokines in vitro or by transient expression of the myeloid transcription factor C/EBPα or PU.1. The resultant cells were clonally related to the primary leukemic blasts but resembled normal macrophages in appearance, immunophenotype, gene expression, and function. Most importantly, these macrophage-like cells were unable to establish disease in xenograft hosts, indicating that lineage reprogramming eliminates the leukemogenicity of BCR-ABL1(+) B-ALL cells, and suggesting a previously unidentified therapeutic strategy for this disease. Finally, we determined that myeloid reprogramming may occur to some degree in human patients by identifying primary CD14(+) monocytes/macrophages in BCR-ABL1(+) B-ALL patient samples that possess the BCR-ABL1(+) translocation and clonally recombined VDJ regions.
View details for DOI 10.1073/pnas.1413383112
View details for Web of Science ID 000351914500070
View details for PubMedID 25775523
View details for PubMedCentralID PMC4386392
-
Mutations in early follicular lymphoma progenitors are associated with suppressed antigen presentation.
Proceedings of the National Academy of Sciences of the United States of America
2015; 112 (10): E1116-25
Abstract
Follicular lymphoma (FL) is incurable with conventional therapies and has a clinical course typified by multiple relapses after therapy. These tumors are genetically characterized by B-cell leukemia/lymphoma 2 (BCL2) translocation and mutation of genes involved in chromatin modification. By analyzing purified tumor cells, we identified additional novel recurrently mutated genes and confirmed mutations of one or more chromatin modifier genes within 96% of FL tumors and two or more in 76% of tumors. We defined the hierarchy of somatic mutations arising during tumor evolution by analyzing the phylogenetic relationship of somatic mutations across the coding genomes of 59 sequentially acquired biopsies from 22 patients. Among all somatically mutated genes, CREBBP mutations were most significantly enriched within the earliest inferable progenitor. These mutations were associated with a signature of decreased antigen presentation characterized by reduced transcript and protein abundance of MHC class II on tumor B cells, in line with the role of CREBBP in promoting class II transactivator (CIITA)-dependent transcriptional activation of these genes. CREBBP mutant B cells stimulated less proliferation of T cells in vitro compared with wild-type B cells from the same tumor. Transcriptional signatures of tumor-infiltrating T cells were indicative of reduced proliferation, and this corresponded to decreased frequencies of tumor-infiltrating CD4 helper T cells and CD8 memory cytotoxic T cells. These observations therefore implicate CREBBP mutation as an early event in FL evolution that contributes to immune evasion via decreased antigen presentation.
View details for DOI 10.1073/pnas.1501199112
View details for PubMedID 25713363
-
Sparse expression bases in cancer reveal tumor drivers.
Nucleic acids research
2015; 43 (3): 1332-1344
Abstract
We define a new category of candidate tumor drivers in cancer genome evolution: 'selected expression regulators' (SERs)-genes driving dysregulated transcriptional programs in cancer evolution. The SERs are identified from genome-wide tumor expression data with a novel method, namely SPARROW ( SPAR: se selected exp R: essi O: n regulators identified W: ith penalized regression). SPARROW uncovers a previously unknown connection between cancer expression variation and driver events, by using a novel sparse regression technique. Our results indicate that SPARROW is a powerful complementary approach to identify candidate genes containing driver events that are hard to detect from sequence data, due to a large number of passenger mutations and lack of comprehensive sequence information from a sufficiently large number of samples. SERs identified by SPARROW reveal known driver mutations in multiple human cancers, along with known cancer-associated processes and survival-associated genes, better than popular methods for inferring gene expression networks. We demonstrate that when applied to acute myeloid leukemia expression data, SPARROW identifies an apoptotic biomarker (PYCARD) for an investigational drug obatoclax. The PYCARD and obatoclax association is validated in 30 AML patient samples.
View details for DOI 10.1093/nar/gku1290
View details for PubMedID 25583238
View details for PubMedCentralID PMC4330344
-
Mutant WT1 is associated with DNA hypermethylation of PRC2 targets in AML and responds to EZH2 inhibition.
Blood
2015; 125 (2): 316-326
Abstract
Acute myeloid leukemia (AML) is associated with deregulation of DNA methylation; however, many cases do not bear mutations in known regulators of CpG methylation. We found that mutations in WT1, IDH2, and CEBPA were strongly linked to DNA hypermethylation in AML using a novel integrative analysis of TCGA data based on Boolean implications, if-then rules that identify all individual CpG sites that are hypermethylated in the presence of a mutation. Introduction of mutant WT1 (WT1mut) into wildtype AML cells induced DNA hypermethylation, confirming mutant WT1 to be causally associated with DNA hypermethylation. Methylated genes in WT1mut primary patient samples were highly enriched for polycomb repressor complex 2 (PRC2) targets, implicating PRC2 dysregulation in WT1mut leukemogenesis. We found that PRC2 target genes were aberrantly repressed in WT1mut AML, and that expression of mutant WT1 in CD34+ cord blood cells induced myeloid differentiation block. Treatment of WT1mut AML cells with shRNA or pharmacologic PRC2/EZH2 inhibitors promoted myeloid differentiation, suggesting EZH2 inhibitors may be active in this AML subtype. Our results highlight a strong association between mutant WT1 and DNA hypermethylation in AML, and demonstrate that Boolean implications can be used to decipher mutation-specific methylation patterns that may lead to therapeutic insights.
View details for DOI 10.1182/blood-2014-03-566018
View details for PubMedID 25398938
-
A Simple Method for Estimating Interactions Between a Treatment and a Large Number of Covariates
JOURNAL OF THE AMERICAN STATISTICAL ASSOCIATION
2014; 109 (508): 1517-1532
Abstract
We consider a setting in which we have a treatment and a potentially large number of covariates for a set of observations, and wish to model their relationship with an outcome of interest. We propose a simple method for modeling interactions between the treatment and covariates. The idea is to modify the covariate in a simple way, and then fit a standard model using the modified covariates and no main effects. We show that coupled with an efficiency augmentation procedure, this method produces clinically meaningful estimators in a variety of settings. It can be useful for practicing personalized medicine: determining from a large set of biomarkers the subset of patients that can potentially benefit from a treatment. We apply the method to both simulated datasets and real trial data. The modified covariates idea can be used for other purposes, for example, large scale hypothesis testing for determining which of a set of covariates interact with a treatment variable.
View details for DOI 10.1080/01621459.2014.951443
View details for Web of Science ID 000346797000016
View details for PubMedCentralID PMC4338439
-
A Simple Method for Estimating Interactions between a Treatment and a Large Number of Covariates.
Journal of the American Statistical Association
2014; 109 (508): 1517-1532
Abstract
We consider a setting in which we have a treatment and a potentially large number of covariates for a set of observations, and wish to model their relationship with an outcome of interest. We propose a simple method for modeling interactions between the treatment and covariates. The idea is to modify the covariate in a simple way, and then fit a standard model using the modified covariates and no main effects. We show that coupled with an efficiency augmentation procedure, this method produces clinically meaningful estimators in a variety of settings. It can be useful for practicing personalized medicine: determining from a large set of biomarkers the subset of patients that can potentially benefit from a treatment. We apply the method to both simulated datasets and real trial data. The modified covariates idea can be used for other purposes, for example, large scale hypothesis testing for determining which of a set of covariates interact with a treatment variable.
View details for DOI 10.1080/01621459.2014.951443
View details for PubMedID 25729117
View details for PubMedCentralID PMC4338439
-
Targeting Unique Metabolic Properties of Breast Tumor Initiating Cells
STEM CELLS
2014; 32 (7): 1734-1745
Abstract
Normal stem cells from a variety of tissues display unique metabolic properties compared to their more differentiated progeny. However, relatively little is known about metabolic properties of cancer stem cells, also called tumor initiating cells (TICs). In this study we show that, analogous to some normal stem cells, breast TICs have distinct metabolic properties compared to nontumorigenic cancer cells (NTCs). Transcriptome profiling using RNA-Seq revealed TICs underexpress genes involved in mitochondrial biology and mitochondrial oxidative phosphorylation, and metabolic analyses revealed TICs preferentially perform glycolysis over oxidative phosphorylation compared to NTCs. Mechanistic analyses demonstrated that decreased expression and activity of pyruvate dehydrogenase (Pdh), a key regulator of oxidative phosphorylation, plays a critical role in promoting the proglycolytic phenotype of TICs. Metabolic reprogramming via forced activation of Pdh preferentially eliminated TICs both in vitro and in vivo. Our findings reveal unique metabolic properties of TICs and demonstrate that metabolic reprogramming represents a potential therapeutic strategy for targeting these cells.
View details for DOI 10.1002/stem.1662
View details for Web of Science ID 000337785200005
View details for PubMedCentralID PMC4144791
-
Active idiotypic vaccination versus control immunotherapy for follicular lymphoma.
Journal of clinical oncology
2014; 32 (17): 1797-1803
Abstract
Idiotypes (Ids), the unique portions of tumor immunoglobulins, can serve as targets for passive and active immunotherapies for lymphoma. We performed a multicenter, randomized trial comparing a specific vaccine (MyVax), comprising Id chemically coupled to keyhole limpet hemocyanin (KLH) plus granulocyte macrophage colony-stimulating factor (GM-CSF) to a control immunotherapy with KLH plus GM-CSF.Patients with previously untreated advanced-stage follicular lymphoma (FL) received eight cycles of chemotherapy with cyclophosphamide, vincristine, and prednisone. Those achieving sustained partial or complete remission (n=287 [44%]) were randomly assigned at a ratio of 2:1 to receive one injection per month for 7 months of MyVax or control immunotherapy. Anti-Id antibody responses (humoral immune responses [IRs]) were measured before each immunization. The primary end point was progression-free survival (PFS). Secondary end points included IR and time to subsequent antilymphoma therapy.At a median follow-up of 58 months, no significant difference was observed in either PFS or time to next therapy between the two arms. In the MyVax group (n=195), anti-Id IRs were observed in 41% of patients, with a median PFS of 40 months, significantly exceeding the median PFS observed in patients without such Id-induced IRs and in those receiving control immunotherapy.This trial failed to demonstrate clinical benefit of specific immunotherapy. The subset of vaccinated patients mounting specific anti-Id responses had superior outcomes. Whether this reflects a therapeutic benefit or is a marker for more favorable underlying prognosis requires further study.
View details for DOI 10.1200/JCO.2012.43.9273
View details for PubMedID 24799467
-
Utility in prognostic value added by molecular profiles for diffuse large B-cell lymphoma.
Blood
2013; 121 (15): 3052-3054
View details for DOI 10.1182/blood-2013-01-477521
View details for PubMedID 23580636
-
Hierarchy in somatic mutations arising during genomic evolution and progression of follicular lymphoma.
Blood
2013; 121 (9): 1604-1611
Abstract
Follicular lymphoma (FL) is currently incurable using conventional chemotherapy or immunotherapy regimes, compelling new strategies. Advances in high-throughput sequencing technologies that can reveal oncogenic pathways have stimulated interest in tailoring therapies toward actionable somatic mutations. However, for mutation-directed therapies to be most effective, the mutations must be uniformly present in evolved tumor cells as well as in the self-renewing tumor-cell precursors. Here, we show striking intratumoral clonal diversity within FL tumors in the representation of mutations in the majority of genes as revealed by whole exome sequencing of subpopulations. This diversity captures a clonal hierarchy, resolved using immunoglobulin somatic mutations and IGH-BCL2 translocations as a frame of reference and by comparing diagnosis and relapse tumor pairs, allowing us to distinguish early versus late genetic eventsduring lymphomagenesis. We provide evidence that IGH-BCL2 translocations and CREBBP mutations are early events, whereas MLL2 and TNFRSF14 mutations probably represent late events during disease evolution. These observations provide insight into which of the genetic lesions represent suitable candidates for targeted therapies.
View details for DOI 10.1182/blood-2012-09-457283
View details for PubMedID 23297126
-
Systematic Deconvolution of Hematolymphoid Tumor Transcriptomes Reveals Infiltrating Immune Cell Signatures Related to Survival
54th Annual Meeting and Exposition of the American-Society-of-Hematology (ASH)
AMER SOC HEMATOLOGY. 2012
View details for Web of Science ID 000314049601071
-
Hierarchy in Somatic Mutations Arising During Genomic Evolution and Progression of Follicular Lymphoma
54th Annual Meeting and Exposition of the American-Society-of-Hematology (ASH)
AMER SOC HEMATOLOGY. 2012
View details for Web of Science ID 000313838900311
-
The chemoattractant chemerin suppresses melanoma by recruiting natural killer cell antitumor defenses
JOURNAL OF EXPERIMENTAL MEDICINE
2012; 209 (8): 1427-1435
Abstract
Infiltration of specialized immune cells regulates the growth and survival of neoplasia. Here, in a survey of public whole genome expression datasets we found that the gene for chemerin, a widely expressed endogenous chemoattractant protein, is down-regulated in melanoma as well as other human tumors. Moreover, high chemerin messenger RNA expression in tumors correlated with improved outcome in human melanoma. In experiments using the B16 transplantable mouse melanoma, tumor-expressed chemerin inhibited in vivo tumor growth without altering in vitro proliferation. Growth inhibition was associated with an altered profile of tumor-infiltrating cells with an increase in natural killer (NK) cells and a relative reduction in myeloid-derived suppressor cells and putative immune inhibitory plasmacytoid dendritic cells. Tumor inhibition required host expression of CMKLR1 (chemokine-like receptor 1), the chemoattractant receptor for chemerin, and was abrogated by NK cell depletion. Intratumoral injection of chemerin also inhibited tumor growth, suggesting the potential for therapeutic application. These results show that chemerin, whether expressed by tumor cells or within the tumor environment, can recruit host immune defenses that inhibit tumorigenesis and suggest that down-regulation of chemerin may be an important mechanism of tumor immune evasion.
View details for DOI 10.1084/jem.20112124
View details for Web of Science ID 000307016500006
View details for PubMedID 22753924
View details for PubMedCentralID PMC3409495
-
Identification of LMO2 transcriptome and interactome in diffuse large B-cell lymphoma
BLOOD
2012; 119 (23): 5478-5491
Abstract
LMO2 regulates gene expression by facilitating the formation of multipartite DNA-binding complexes. In B cells, LMO2 is specifically up-regulated in the germinal center (GC) and is expressed in GC-derived non-Hodgkin lymphomas. LMO2 is one of the most powerful prognostic indicators in diffuse large B-cell (DLBCL) patients. However, its function in GC B cells and DLBCL is currently unknown. In this study, we characterized the LMO2 transcriptome and transcriptional complex in DLBCL cells. LMO2 regulates genes implicated in kinetochore function, chromosome assembly, and mitosis. Overexpression of LMO2 in DLBCL cell lines results in centrosome amplification. In DLBCL, the LMO2 complex contains some of the traditional partners, such as LDB1, E2A, HEB, Lyl1, ETO2, and SP1, but not TAL1 or GATA proteins. Furthermore, we identified novel LMO2 interacting partners: ELK1, nuclear factor of activated T-cells (NFATc1), and lymphoid enhancer-binding factor1 (LEF1) proteins. Reporter assays revealed that LMO2 increases transcriptional activity of NFATc1 and decreases transcriptional activity of LEF1 proteins. Overall, our studies identified a novel LMO2 transcriptome and interactome in DLBCL and provides a platform for future elucidation of LMO2 function in GC B cells and DLBCL pathogenesis.
View details for DOI 10.1182/blood-2012-01-403154
View details for Web of Science ID 000307391400022
View details for PubMedID 22517897
View details for PubMedCentralID PMC3369683
-
The chemoattractant chemerin as a natural tumor suppressive cytokine.
48th Annual Meeting of the American-Society-of-Clinical-Oncology (ASCO)
AMER SOC CLINICAL ONCOLOGY. 2012
View details for Web of Science ID 000318009803142
-
The CD47-signal regulatory protein alpha (SIRPa) interaction is a therapeutic target for human solid tumors
PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA
2012; 109 (17): 6662-6667
Abstract
CD47, a "don't eat me" signal for phagocytic cells, is expressed on the surface of all human solid tumor cells. Analysis of patient tumor and matched adjacent normal (nontumor) tissue revealed that CD47 is overexpressed on cancer cells. CD47 mRNA expression levels correlated with a decreased probability of survival for multiple types of cancer. CD47 is a ligand for SIRPα, a protein expressed on macrophages and dendritic cells. In vitro, blockade of CD47 signaling using targeted monoclonal antibodies enabled macrophage phagocytosis of tumor cells that were otherwise protected. Administration of anti-CD47 antibodies inhibited tumor growth in orthotopic immunodeficient mouse xenotransplantation models established with patient tumor cells and increased the survival of the mice over time. Anti-CD47 antibody therapy initiated on larger tumors inhibited tumor growth and prevented or treated metastasis, but initiation of the therapy on smaller tumors was potentially curative. The safety and efficacy of targeting CD47 was further tested and validated in immune competent hosts using an orthotopic mouse breast cancer model. These results suggest all human solid tumor cells require CD47 expression to suppress phagocytic innate immune surveillance and elimination. These data, taken together with similar findings with other human neoplasms, show that CD47 is a commonly expressed molecule on all cancers, its function to block phagocytosis is known, and blockade of its function leads to tumor cell phagocytosis and elimination. CD47 is therefore a validated target for cancer therapies.
View details for DOI 10.1073/pnas.1121623109
View details for PubMedID 22451913
-
Identification of LMO2 Transcriptome and Interactome in Diffuse Large B-Cell Lymphoma by Integrated Experimental and Computational Approach
53rd Annual Meeting and Exposition of the American-Society-of-Hematology (ASH)
AMER SOC HEMATOLOGY. 2011: 201–2
View details for Web of Science ID 000299597100439
-
A few good genes Simple, biologically motivated signatures for cancer prognosis
CELL CYCLE
2011; 10 (21): 3615-3616
View details for DOI 10.4161/cc.10.21.17835
View details for Web of Science ID 000296572100003
View details for PubMedID 22037208
View details for PubMedCentralID PMC3266003
-
Lymphomas that recur after MYC suppression continue to exhibit oncogene addiction
PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA
2011; 108 (42): 17432-17437
Abstract
The suppression of oncogenic levels of MYC is sufficient to induce sustained tumor regression associated with proliferative arrest, differentiation, cellular senescence, and/or apoptosis, a phenomenon known as oncogene addiction. However, after prolonged inactivation of MYC in a conditional transgenic mouse model of Eμ-tTA/tetO-MYC T-cell acute lymphoblastic leukemia, some of the tumors recur, recapitulating what is frequently observed in human tumors in response to targeted therapies. Here we report that these recurring lymphomas express either transgenic or endogenous Myc, albeit in many cases at levels below those in the original tumor, suggesting that tumors continue to be addicted to MYC. Many of the recurring lymphomas (76%) harbored mutations in the tetracycline transactivator, resulting in expression of the MYC transgene even in the presence of doxycycline. Some of the remaining recurring tumors expressed high levels of endogenous Myc, which was associated with a genomic rearrangement of the endogenous Myc locus or activation of Notch1. By gene expression profiling, we confirmed that the primary and recurring tumors have highly similar transcriptomes. Importantly, shRNA-mediated suppression of the high levels of MYC in recurring tumors elicited both suppression of proliferation and increased apoptosis, confirming that these tumors remain oncogene addicted. These results suggest that tumors induced by MYC remain addicted to overexpression of this oncogene.
View details for DOI 10.1073/pnas.1107303108
View details for PubMedID 21969595
-
Systems Biology: Confronting the Complexity of Cancer
CANCER RESEARCH
2011; 71 (18): 5961-5964
Abstract
The AACR-NCI Conference "Systems Biology: Confronting the Complexity of Cancer" took place from February 27 to March 2, 2011, in San Diego, CA. Several themes resonated during the meeting, notably (i) the need for better methods to distill insights from large-scale networks, (ii) the importance of integrating multiple data types in constructing more realistic models, (iii) challenges in translating insights about tumorigenic mechanisms into therapeutic interventions, and (iv) the role of the tumor microenvironment, at the physical, cellular, and molecular levels. The meeting highlighted concrete applications of systems biology to cancer, and the value of collaboration between interdisciplinary researchers in attacking formidable problems.
View details for DOI 10.1158/0008-5472.CAN-11-1569
View details for Web of Science ID 000294843600019
View details for PubMedID 21896642
View details for PubMedCentralID PMC3174325
-
Prediction of survival in diffuse large B-cell lymphoma based on the expression of 2 genes reflecting tumor and microenvironment
BLOOD
2011; 118 (5): 1350-1358
Abstract
Several gene-expression signatures predict survival in diffuse large B-cell lymphoma (DLBCL), but the lack of practical methods for genome-scale analysis has limited translation to clinical practice. We built and validated a simple model using one gene expressed by tumor cells and another expressed by host immune cells, assessing added prognostic value to the clinical International Prognostic Index (IPI). LIM domain only 2 (LMO2) was validated as an independent predictor of survival and the "germinal center B cell-like" subtype. Expression of tumor necrosis factor receptor superfamily member 9 (TNFRSF9) from the DLBCL microenvironment was the best gene in bivariate combination with LMO2. Study of TNFRSF9 tissue expression in 95 patients with DLBCL showed expression limited to infiltrating T cells. A model integrating these 2 genes was independent of "cell-of-origin" classification, "stromal signatures," IPI, and added to the predictive power of the IPI. A composite score integrating these genes with IPI performed well in 3 independent cohorts of 545 DLBCL patients, as well as in a simple assay of routine formalin-fixed specimens from a new validation cohort of 147 patients with DLBCL. We conclude that the measurement of a single gene expressed by tumor cells (LMO2) and a single gene expressed by the immune microenvironment (TNFRSF9) powerfully predicts overall survival in patients with DLBCL.
View details for DOI 10.1182/blood-2011-03-345272
View details for PubMedID 21670469
-
Clinical Application of Readout-Segmented-Echo-Planar Imaging for Diffusion-Weighted Imaging in Pediatric Brain
AMERICAN JOURNAL OF NEURORADIOLOGY
2011; 32 (7): 1274-1279
Abstract
RS-EPI has been suggested as an alternative approach to EPI for high-resolution DWI with reduced distortions. To determine whether RS-EPI is a useful approach for routine clinical use, we implemented GRAPPA-accelerated RS-EPI DWI at our pediatric hospital and graded the images alongside standard accelerated (ASSET) EPI DWI used routinely for clinical studies.GRAPPA-accelerated RS-EPI DWIs and ASSET EPI DWIs were acquired on 35 pediatric patients using a 3T system in 35 pediatric patients. The images were graded alongside each other by using a 7-point Likert scale as follows: 1, nondiagnostic; 2, poor; 3, acceptable; 4, standard; 5, above average; 6, good; and 7, outstanding.The following were the average scores for EPI and RS-EPI, respectively: resolution, 3.5/5.2; distortion level, 2.9/6.0; SNR, 3.4/4.1; lesion conspicuity, 3.3/5.9; and diagnostic confidence, 3.2/6.0. Overall, the RS-EPI had significantly improved diagnostic confidence and more reliably defined the extent and structure of several lesions. Although ASSET EPI scans had better SNR per scanning time, the higher spatial resolution as well as reduced blurring and distortions on RS-EPI scans helped to better reveal important anatomic details at the cortical-subcortical levels, brain stem, temporal and inferior frontal lobes, skull base, sinonasal cavity, cranial nerves, and orbits.This work shows the importance of both resolution and decreased distortions in the clinics, which can be accomplished by a combination of parallel imaging and alternative k-space trajectories such as RS-EPI.
View details for DOI 10.3174/ajnr.A2481
View details for Web of Science ID 000294275100023
View details for PubMedID 21596809
-
Discovering Biological Progression Underlying Microarray Samples
PLOS COMPUTATIONAL BIOLOGY
2011; 7 (4)
Abstract
In biological systems that undergo processes such as differentiation, a clear concept of progression exists. We present a novel computational approach, called Sample Progression Discovery (SPD), to discover patterns of biological progression underlying microarray gene expression data. SPD assumes that individual samples of a microarray dataset are related by an unknown biological process (i.e., differentiation, development, cell cycle, disease progression), and that each sample represents one unknown point along the progression of that process. SPD aims to organize the samples in a manner that reveals the underlying progression and to simultaneously identify subsets of genes that are responsible for that progression. We demonstrate the performance of SPD on a variety of microarray datasets that were generated by sampling a biological process at different points along its progression, without providing SPD any information of the underlying process. When applied to a cell cycle time series microarray dataset, SPD was not provided any prior knowledge of samples' time order or of which genes are cell-cycle regulated, yet SPD recovered the correct time order and identified many genes that have been associated with the cell cycle. When applied to B-cell differentiation data, SPD recovered the correct order of stages of normal B-cell differentiation and the linkage between preB-ALL tumor cells with their cell origin preB. When applied to mouse embryonic stem cell differentiation data, SPD uncovered a landscape of ESC differentiation into various lineages and genes that represent both generic and lineage specific processes. When applied to a prostate cancer microarray dataset, SPD identified gene modules that reflect a progression consistent with disease stages. SPD may be best viewed as a novel tool for synthesizing biological hypotheses because it provides a likely biological progression underlying a microarray dataset and, perhaps more importantly, the candidate genes that regulate that progression.
View details for DOI 10.1371/journal.pcbi.1001123
View details for PubMedID 21533210
-
Prospective separation of normal and leukemic stem cells based on differential expression of TIM3, a human acute myeloid leukemia stem cell marker
PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA
2011; 108 (12): 5009-5014
Abstract
Hematopoietic tissues in acute myeloid leukemia (AML) patients contain both leukemia stem cells (LSC) and residual normal hematopoietic stem cells (HSC). The ability to prospectively separate residual HSC from LSC would enable important scientific and clinical investigation including the possibility of purged autologous hematopoietic cell transplants. We report here the identification of TIM3 as an AML stem cell surface marker more highly expressed on multiple specimens of AML LSC than on normal bone marrow HSC. TIM3 expression was detected in all cytogenetic subgroups of AML, but was significantly higher in AML-associated with core binding factor translocations or mutations in CEBPA. By assessing engraftment in NOD/SCID/IL2Rγ-null mice, we determined that HSC function resides predominantly in the TIM3-negative fraction of normal bone marrow, whereas LSC function from multiple AML specimens resides predominantly in the TIM3-positive compartment. Significantly, differential TIM3 expression enabled the prospective separation of HSC from LSC in the majority of AML specimens with detectable residual HSC function.
View details for DOI 10.1073/pnas.1100551108
View details for Web of Science ID 000288712200061
View details for PubMedID 21383193
View details for PubMedCentralID PMC3064328
-
Association of a Leukemic Stem Cell Gene Expression Signature With Clinical Outcomes in Acute Myeloid Leukemia
JAMA-JOURNAL OF THE AMERICAN MEDICAL ASSOCIATION
2010; 304 (24): 2706-2715
Abstract
In many cancers, specific subpopulations of cells appear to be uniquely capable of initiating and maintaining tumors. The strongest support for this cancer stem cell model comes from transplantation assays in immunodeficient mice, which indicate that human acute myeloid leukemia (AML) is driven by self-renewing leukemic stem cells (LSCs). This model has significant implications for the development of novel therapies, but its clinical relevance has yet to be determined.To identify an LSC gene expression signature and test its association with clinical outcomes in AML.Retrospective study of global gene expression (microarray) profiles of LSC-enriched subpopulations from primary AML and normal patient samples, which were obtained at a US medical center between April 2005 and July 2007, and validation data sets of global transcriptional profiles of AML tumors from 4 independent cohorts (n = 1047).Identification of genes discriminating LSC-enriched populations from other subpopulations in AML tumors; and association of LSC-specific genes with overall, event-free, and relapse-free survival and with therapeutic response.Expression levels of 52 genes distinguished LSC-enriched populations from other subpopulations in cell-sorted AML samples. An LSC score summarizing expression of these genes in bulk primary AML tumor samples was associated with clinical outcomes in the 4 independent patient cohorts. High LSC scores were associated with worse overall, event-free, and relapse-free survival among patients with either normal karyotypes or chromosomal abnormalities. For the largest cohort of patients with normal karyotypes (n = 163), the LSC score was significantly associated with overall survival as a continuous variable (hazard ratio [HR], 1.15; 95% confidence interval [CI], 1.08-1.22; log-likelihood P <.001). The absolute risk of death by 3 years was 57% (95% CI, 43%-67%) for the low LSC score group compared with 78% (95% CI, 66%-86%) for the high LSC score group (HR, 1.9 [95% CI, 1.3-2.7]; log-rank P = .002). In another cohort with available data on event-free survival for 70 patients with normal karyotypes, the risk of an event by 3 years was 48% (95% CI, 27%-63%) in the low LSC score group vs 81% (95% CI, 60%-91%) in the high LSC score group (HR, 2.4 [95% CI, 1.3-4.5]; log-rank P = .006). In multivariate Cox regression including age, mutations in FLT3 and NPM1, and cytogenetic abnormalities, the HRs for LSC score in the 3 cohorts with data on all variables were 1.07 (95% CI, 1.01-1.13; P = .02), 1.10 (95% CI, 1.03-1.17; P = .005), and 1.17 (95% CI, 1.05-1.30; P = .005).High expression of an LSC gene signature is independently associated with adverse outcomes in patients with AML.
View details for PubMedID 21177505
-
Calreticulin Is the Dominant Pro-Phagocytic Signal on Multiple Human Cancers and Is Counterbalanced by CD47
SCIENCE TRANSLATIONAL MEDICINE
2010; 2 (63)
Abstract
Under normal physiological conditions, cellular homeostasis is partly regulated by a balance of pro- and anti-phagocytic signals. CD47, which prevents cancer cell phagocytosis by the innate immune system, is highly expressed on several human cancers including acute myeloid leukemia, non-Hodgkin's lymphoma, and bladder cancer. Blocking CD47 with a monoclonal antibody results in phagocytosis of cancer cells and leads to in vivo tumor elimination, yet normal cells remain mostly unaffected. Thus, we postulated that cancer cells must also display a potent pro-phagocytic signal. Here, we identified calreticulin as a pro-phagocytic signal that was highly expressed on the surface of several human cancers, but was minimally expressed on most normal cells. Increased CD47 expression correlated with high amounts of calreticulin on cancer cells and was necessary for protection from calreticulin-mediated phagocytosis. Blocking the interaction of target cell calreticulin with its receptor, low-density lipoprotein receptor-related protein, on phagocytic cells prevented anti-CD47 antibody-mediated phagocytosis. Furthermore, increased calreticulin expression was an adverse prognostic factor in diverse tumors including neuroblastoma, bladder cancer, and non-Hodgkin's lymphoma. These findings identify calreticulin as the dominant pro-phagocytic signal on several human cancers, provide an explanation for the selective targeting of tumor cells by anti-CD47 antibody, and highlight the balance between pro- and anti-phagocytic signals in the immune evasion of cancer.
View details for DOI 10.1126/scitranslmed.3001375
View details for Web of Science ID 000288444900003
View details for PubMedID 21178137
-
Recurrent Interstitial 1p36 Deletions: Evidence for Germline Mosaicism and Complex Rearrangement Breakpoints
AMERICAN JOURNAL OF MEDICAL GENETICS PART A
2010; 152A (12): 3074-3083
Abstract
Deletions of chromosome 1p36 are one of the most frequently encountered subtelomeric alterations. Clinical features of monosomy 1p36 include neurocognitive impairment, hearing loss, seizures, cardiac defects, and characteristic facial features. The majority of cases have occurred sporadically, implying that genomic instability plays a role in the prevalence of the syndrome. Here, we report two siblings with mild phenotypic features of the deletion syndrome, including developmental delay, hearing loss, and left ventricular non-compaction (LVNC). Microarray analysis using bacterial artificial chromosome and oligonucleotide microarrays indicated the deletions were identical, suggesting germline mosaicism. Parental phenotypes were normal, and analysis by fluorescence in situ hybridization (FISH) did not show mosaicism. These small interstitial deletions were not detectable by conventional subtelomeric FISH analysis. To investigate the mechanism of deletion further, the breakpoints were cloned and sequenced, demonstrating the presence of a complex rearrangement. Sequence analysis of genes in the deletion interval did not reveal any mutations on the intact homologue that may have contributed to the LVNC seen in both children. This is the first report of apparent germline mosaicism for this disorder. Thus, our findings have important implications for diagnostic approaches and for recurrence risk counseling in families with a child with monosomy 1p36. In addition, our results further refine the minimal critical region for LVNC and hearing loss.
View details for DOI 10.1002/ajmg.a.33733
View details for Web of Science ID 000285251800019
View details for PubMedID 21108392
View details for PubMedCentralID PMC3058890
-
Prediction of Survival In Diffuse Large B-Cell Lymphoma Based On the Expression of Two Genes Reflecting Tumor and Microenvironment
52nd Annual Meeting and Exposition of the American-Society-of-Hematology (ASH)
AMER SOC HEMATOLOGY. 2010: 836–37
View details for Web of Science ID 000289662202229
-
Efficacy of bortezomib in a direct xenograft model of primary effusion lymphoma
PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA
2010; 107 (29): 13069-13074
Abstract
Primary effusion lymphoma (PEL) is an aggressive B-cell lymphoma most commonly diagnosed in HIV-positive patients and universally associated with Kaposi's sarcoma-associated herpesvirus (KSHV). Chemotherapy treatment of PEL yields only short-term remissions in the vast majority of patients, but efforts to develop superior therapeutic approaches have been impeded by lack of animal models that accurately mimic human disease. To address this issue, we developed a direct xenograft model, UM-PEL-1, by transferring freshly isolated human PEL cells into the peritoneal cavities of NOD/SCID mice without in vitro cell growth to avoid the changes in KSHV gene expression evident in cultured cells. We used this model to show that bortezomib induces PEL remission and extends overall survival of mice bearing lymphomatous effusions. The proapoptotic effects of bortezomib are not mediated by inhibition of the prosurvival NF-kappaB pathway or by induction of a terminal unfolded protein response. Transcriptome analysis by genomic arrays revealed that bortezomib down-regulated cell-cycle progression, DNA replication, and Myc-target genes. Furthermore, we demonstrate that in vivo treatment with either bortezomib or doxorubicin induces KSHV lytic reactivation. These reactivations were temporally distinct, and this difference may help elucidate the therapeutic window for use of antivirals concurrently with chemotherapy. Our findings show that this direct xenograft model can be used for testing novel PEL therapeutic strategies and also can provide a rational basis for evaluation of bortezomib in clinical trials.
View details for DOI 10.1073/pnas.1002985107
View details for Web of Science ID 000280144500066
View details for PubMedID 20615981
View details for PubMedCentralID PMC2919898
-
Reducing the Computational Complexity of Information Theoretic Approaches for Reconstructing Gene Regulatory Networks
JOURNAL OF COMPUTATIONAL BIOLOGY
2010; 17 (2): 169-176
Abstract
Information theoretic approaches are increasingly being used for reconstructing regulatory networks from microarray data. These approaches start by computing the pairwise mutual information (MI) between all gene pairs. The resulting MI matrix is then manipulated to identify regulatory relationships. A barrier to these approaches is the time-consuming step of computing the MI matrix. We present a method to reduce this computation time. We apply spectral analysis to re-order the genes, so that genes that share regulatory relationships are more likely to be placed close to each other. Then, using a "sliding window" approach with appropriate window size and step size, we compute the MI for the genes within the sliding window, and the remainder is assumed to be zero. Using both simulated data and microarray data, we demonstrate that our method does not incur performance loss in regions of high-precision and low-recall, while the computational time is significantly lowered. The proposed method can be used with any method that relies on the mutual information to reconstruct networks.
View details for DOI 10.1089/cmb.2009.0052
View details for PubMedID 20078227
-
Novel IL-21 signaling pathway up-regulates c-Myc and induces apoptosis of diffuse large B-cell lymphomas
BLOOD
2010; 115 (3): 570-580
Abstract
Interleukin-21 (IL-21), a member of the IL-2 cytokine family, has diverse regulatory effects on natural killer (NK), T, and B cells. In contrast to other cytokines that are usually immunostimulatory, IL-21 can induce apoptosis of murine B cells at specific activation-differentiation stages. This effect may be used for treatment of B-cell malignancies. Herein we report that diffuse large B-cell lymphoma (DLBCL) cell lines exhibit widespread expression of the IL-21 receptor (IL-21R) and that IL-21 stimulation leads to cell-cycle arrest and caspase-dependent apoptosis. IL-21 also induces apoptosis in de novo DLBCL primary tumors but does not affect viability of human healthy B cells. Furthermore, IL-21 promotes tumor regression and prolongs survival of mice harboring xenograft DLBCL tumors. The antilymphoma effects of this cytokine are dependent on a mechanism involving IL-21-activated signal transducer and activator of transcription 3 (STAT3) up-regulating expression of c-Myc. This up-regulation promotes a decrease in expression of antiapoptotic Bcl-2 and Bcl-X(L) proteins triggering cell death. Our results represent one of the first examples in which the STAT3-c-Myc signaling pathway, which can promote survival and oncogenesis, can induce apoptosis in neoplastic cells. Moreover, based on IL-21's potency in vitro and in animal models, our findings indicate that this cytokine should be examined in clinical studies of DLBCL.
View details for DOI 10.1182/blood-2009-08-239996
View details for Web of Science ID 000273820600018
View details for PubMedID 19965678
View details for PubMedCentralID PMC2810990
-
Prediction of Survival in Diffuse Large B-Cell Lymphoma Based On the Expression of Two Genes: Integration of Tumor and Microenvironment Contributions
51st Annual Meeting and Exposition of the American-Society-of-Hematology
AMER SOC HEMATOLOGY. 2009: 258–58
View details for Web of Science ID 000272725800623
-
Gene Expression Signature of Host Immune Response Is Predictive of Follicular Lymphoma Patient Survival in Independent Cohorts, and Correlates with Transformation to Diffuse Large B-Cell Lymphoma.
51st Annual Meeting and Exposition of the American-Society-of-Hematology
AMER SOC HEMATOLOGY. 2009: 1153–53
View details for Web of Science ID 000272725803506
-
A pluripotency signature predicts histologic transformation and influences survival in follicular lymphoma patients
BLOOD
2009; 114 (15): 3158-3166
Abstract
Histologic transformation (HT) of follicular lymphoma to diffuse large B-cell lymphoma (DLBCL-t) is associated with accelerated disease course and drastically worse outcome, yet the underlying mechanisms are poorly understood. We show that a network of gene transcriptional modules underlies HT. Central to the network hierarchy is a signature strikingly enriched for pluripotency-related genes. These genes are typically expressed in embryonic stem cells (ESCs), including MYC and its direct targets. This core ESC-like program was independent of proliferation/cell-cycle and overlapped but was distinct from normal B-cell transcriptional programs. Furthermore, we show that the ESC program is correlated with transcriptional programs maintaining tumor phenotype in transgenic MYC-driven mouse models of lymphoma. Although our approach was to identify HT mechanisms rather than to derive an optimal survival predictor, a model based on ESC/differentiation programs stratified patient outcomes in 2 independent patient cohorts and was predictive of propensity of follicular lymphoma tumors to transform. Transformation was associated with an expression signature combining high expression of ESC transcriptional programs with reduced expression of stromal programs. Together, these findings suggest a central role for an ESC-like signature in the mechanism of HT and provide new clues for potential therapeutic targets.
View details for DOI 10.1182/blood-2009-02-202465
View details for PubMedID 19636063
-
Molecular Outcome Prediction in Diffuse Large-B-Cell Lymphoma
NEW ENGLAND JOURNAL OF MEDICINE
2009; 360 (26): 2794-2795
View details for Web of Science ID 000267286600032
View details for PubMedID 19553658
-
Further delineation of nonhomologous-based recombination and evidence for subtelomeric segmental duplications in 1p36 rearrangements
HUMAN GENETICS
2009; 125 (5-6): 551-563
Abstract
The mechanisms involved in the formation of subtelomeric rearrangements are now beginning to be elucidated. Breakpoint sequencing analysis of 1p36 rearrangements has made important contributions to this line of inquiry. Despite the unique architecture of segmental duplications inherent to human subtelomeres, no common mechanism has been identified thus far and different nonexclusive recombination-repair mechanisms seem to predominate. In order to gain further insights into the mechanisms of chromosome breakage, repair, and stabilization mediating subtelomeric rearrangements in humans, we investigated the constitutional rearrangements of 1p36. Cloning of the breakpoint junctions in a complex rearrangement and three non-reciprocal translocations revealed similarities at the junctions, such as microhomology of up to three nucleotides, along with no significant sequence identity in close proximity to the breakpoint regions. All the breakpoints appeared to be unique and their occurrence was limited to non-repetitive, unique DNA sequences. Several recombination- or cleavage-associated motifs that may promote non-homologous recombination were observed in close proximity to the junctions. We conclude that NHEJ is likely the mechanism of DNA repair that generates these rearrangements. Additionally, two apparently pure terminal deletions were also investigated, and the refinement of the breakpoint regions identified two distinct genomic intervals ~25-kb apart, each containing a series of 1p36 specific segmental duplications with 90-98% identity. Segmental duplications can serve as substrates for ectopic homologous recombination or stimulate genomic rearrangements.
View details for DOI 10.1007/s00439-009-0650-9
View details for Web of Science ID 000266261600006
View details for PubMedID 19271239
-
Fast calculation of pairwise mutual information for gene regulatory network reconstruction
COMPUTER METHODS AND PROGRAMS IN BIOMEDICINE
2009; 94 (2): 177-180
Abstract
We present a new software implementation to more efficiently compute the mutual information for all pairs of genes from gene expression microarrays. Computation of the mutual information is a necessary first step in various information theoretic approaches for reconstructing gene regulatory networks from microarray data. When the mutual information is estimated by kernel methods, computing the pairwise mutual information is quite time-consuming. Our implementation significantly reduces the computation time. For an example data set of 336 samples consisting of normal and malignant B-cells, with 9563 genes measured per sample, the current available software for ARACNE requires 142 hours to compute the mutual information for all gene pairs, whereas our algorithm requires 1.6 hours. The increased efficiency of our algorithm improves the feasibility of applying mutual information based approaches for reconstructing large regulatory networks.
View details for DOI 10.1016/j.cmpb.2008.11.003
View details for PubMedID 19167129
-
Characterization of Patient Specific Signaling via Augmentation of Bayesian Networks with Disease and Patient State Nodes
Annual International Conference of the IEEE-Engineering-in-Medicine-and-Biology-Society
IEEE. 2009: 6624–6627
Abstract
Characterization of patient-specific disease features at a molecular level is an important emerging field. Patients may be characterized by differences in the level and activity of relevant biomolecules in diseased cells. When high throughput, high dimensional data is available, it becomes possible to characterize differences not only in the level of the biomolecules, but also in the molecular interactions among them. We propose here a novel approach to characterize patient specific signaling, which augments high throughput single cell data with state nodes corresponding to patient and disease states, and learns a Bayesian network based on this data. Features distinguishing individual patients emerge as downstream nodes in the network. We illustrate this approach with a six phospho-protein, 30,000 cell-per-patient dataset characterizing three comparably diagnosed follicular lymphoma, and show that our approach elucidates signaling differences among them.
View details for Web of Science ID 000280543605113
View details for PubMedID 19963681
View details for PubMedCentralID PMC3124088
-
A Bayesian nonparametric method for model evaluation: application to genetic studies
JOURNAL OF NONPARAMETRIC STATISTICS
2009; 21 (3): 379-396
View details for DOI 10.1080/10485250802613558
View details for Web of Science ID 000263651100007
-
Unexpected complexity at breakpoint junctions in phenotypically normal individuals and mechanisms involved in generating balanced translocations t(1;22)(p36;q13)
GENOME RESEARCH
2008; 18 (11): 1733-1742
Abstract
Approximately one in 500 individuals carries a reciprocal translocation. Balanced translocations are usually associated with a normal phenotype unless the translocation breakpoints disrupt a gene(s) or cause a position effect. We investigated breakpoint junctions at the sequence level in phenotypically normal balanced translocation carriers. Eight breakpoint junctions derived from four nonrelated subjects with apparently balanced translocation t(1;22)(p36;q13) were examined. Additions of nucleotides, deletions, duplications, and a triplication identified at the breakpoints demonstrate high complexity at the breakpoint junctions and indicate involvement of multiple mechanisms in the DNA breakage and repair process during translocation formation. Possible detailed nonhomologous end-joining scenarios for t(1;22) cases are presented. We propose that cryptic imbalances in phenotypically normal, balanced translocation carriers may be more common than currently appreciated.
View details for DOI 10.1101/gr.077453.108
View details for Web of Science ID 000260536100006
View details for PubMedID 18765821
View details for PubMedCentralID PMC2577863
-
Genomic and proteomic analysis reveals a threshold level of MYC required for tumor maintenance
CANCER RESEARCH
2008; 68 (13): 5132-5142
Abstract
MYC overexpression has been implicated in the pathogenesis of most types of human cancers. MYC is likely to contribute to tumorigenesis by its effects on global gene expression. Previously, we have shown that the loss of MYC overexpression is sufficient to reverse tumorigenesis. Here, we show that there is a precise threshold level of MYC expression required for maintaining the tumor phenotype, whereupon there is a switch from a gene expression program of proliferation to a state of proliferative arrest and apoptosis. Oligonucleotide microarray analysis and quantitative PCR were used to identify changes in expression in 3,921 genes, of which 2,348 were down-regulated and 1,573 were up-regulated. Critical changes in gene expression occurred at or near the MYC threshold, including genes implicated in the regulation of the G(1)-S and G(2)-M cell cycle checkpoints and death receptor/apoptosis signaling. Using two-dimensional protein analysis followed by mass spectrometry, phospho-flow fluorescence-activated cell sorting, and antibody arrays, we also identified changes at the protein level that contributed to MYC-dependent tumor regression. Proteins involved in mRNA translation decreased below threshold levels of MYC. Thus, at the MYC threshold, there is a loss of its ability to maintain tumorigenesis, with associated shifts in gene and protein expression that reestablish cell cycle checkpoints, halt protein translation, and promote apoptosis.
View details for DOI 10.1158/0008-5472.CAN-07-6192
View details for PubMedID 18593912
-
Boolean implication networks derived from large scale, whole genome microarray datasets
GENOME BIOLOGY
2008; 9 (10)
Abstract
We describe a method for extracting Boolean implications (if-then relationships) in very large amounts of gene expression microarray data. A meta-analysis of data from thousands of microarrays for humans, mice, and fruit flies finds millions of implication relationships between genes that would be missed by other methods. These relationships capture gender differences, tissue differences, development, and differentiation. New relationships are discovered that are preserved across all three species.
View details for PubMedID 18973690
-
SINEs, evolution and genome structure in the opossum
GENE
2007; 396 (1): 46-58
Abstract
Short INterspersed Elements (SINEs) are non-autonomous retrotransposons, usually between 100 and 500 base pairs (bp) in length, which are ubiquitous components of eukaryotic genomes. Their activity, distribution, and evolution can be highly informative on genomic structure and evolutionary processes. To determine recent activity, we amplified more than one hundred SINE1 loci in a panel of 43 M. domestica individuals derived from five diverse geographic locations. The SINE1 family has expanded recently enough that many loci were polymorphic, and the SINE1 insertion-based genetic distances among populations reflected geographic distance. Genome-wide comparisons of SINE1 densities and GC content revealed that high SINE1 density is associated with high GC content in a few long and many short spans. Young SINE1s, whether fixed or polymorphic, showed an unbiased GC content preference for insertion, indicating that the GC preference accumulates over long time periods, possibly in periodic bursts. SINE1 evolution is thus broadly similar to human Alu evolution, although it has an independent origin. High GC content adjacent to SINE1s is strongly correlated with bias towards higher AT to GC substitutions and lower GC to AT substitutions. This is consistent with biased gene conversion, and also indicates that like chickens, but unlike eutherian mammals, GC content heterogeneity (isochore structure) is reinforced by substitution processes in the M. domestica genome. Nevertheless, both high and low GC content regions are apparently headed towards lower GC content equilibria, possibly due to a relative shift to lower recombination rates in the recent Monodelphis ancestral lineage. Like eutherians, metatherian (marsupial) mammals have evolved high CpG substitution rates, but this is apparently a convergence in process rather than a shared ancestral state.
View details for DOI 10.1016/j.gene.2007.02.028
View details for Web of Science ID 000247479000005
View details for PubMedID 17442506
-
Evolutionary dynamics of transposable elements in the short-tailed opossum Monodelphis domestica
GENOME RESEARCH
2007; 17 (7): 992-1004
Abstract
The genome of the gray short-tailed opossum Monodelphis domestica is notable for its large size ( approximately 3.6 Gb). We characterized nearly 500 families of interspersed repeats from the Monodelphis. They cover approximately 52% of the genome, higher than in any other amniotic lineage studied to date, and may account for the unusually large genome size. In comparison to other mammals, Monodelphis is significantly rich in non-LTR retrotransposons from the LINE-1, CR1, and RTE families, with >29% of the genome sequence comprised of copies of these elements. Monodelphis has at least four families of RTE, and we report support for horizontal transfer of this non-LTR retrotransposon. In addition to short interspersed elements (SINEs) mobilized by L1, we found several families of SINEs that appear to use RTE elements for mobilization. In contrast to L1-mobilized SINEs, the RTE-mobilized SINEs in Monodelphis appear to shift from G+C-rich to G+C-low regions with time. Endogenous retroviruses have colonized approximately 10% of the opossum genome. We found that their density is enhanced in centromeric and/or telomeric regions of most Monodelphis chromosomes. We identified 83 new families of ancient repeats that are highly conserved across amniotic lineages, including 14 LINE-derived repeats; and a novel SINE element, MER131, that may have been exapted as a highly conserved functional noncoding RNA, and whose emergence dates back to approximately 300 million years ago. Many of these conserved repeats are also present in human, and are highly over-represented in predicted cis-regulatory modules. Seventy-six of the 83 families are present in chicken in addition to mammals.
View details for DOI 10.1101/gr.6070707
View details for Web of Science ID 000247701600004
View details for PubMedID 17495012
View details for PubMedCentralID PMC1899126
-
Genome of the marsupial Monodelphis domestica reveals innovation in non-coding sequences
NATURE
2007; 447 (7141): 167-U1
Abstract
We report a high-quality draft of the genome sequence of the grey, short-tailed opossum (Monodelphis domestica). As the first metatherian ('marsupial') species to be sequenced, the opossum provides a unique perspective on the organization and evolution of mammalian genomes. Distinctive features of the opossum chromosomes provide support for recent theories about genome evolution and function, including a strong influence of biased gene conversion on nucleotide sequence composition, and a relationship between chromosomal characteristics and X chromosome inactivation. Comparison of opossum and eutherian genomes also reveals a sharp difference in evolutionary innovation between protein-coding and non-coding functional elements. True innovation in protein-coding genes seems to be relatively rare, with lineage-specific differences being largely due to diversification and rapid turnover in gene families involved in environmental interactions. In contrast, about 20% of eutherian conserved non-coding elements (CNEs) are recent inventions that postdate the divergence of Eutheria and Metatheria. A substantial proportion of these eutherian-specific CNEs arose from sequence inserted by transposable elements, pointing to transposons as a major creative force in the evolution of mammalian gene regulation.
View details for DOI 10.1038/nature05805
View details for Web of Science ID 000246338700035
View details for PubMedID 17495919
-
Annotation, submission and screening of repetitive elements in Repbase: RepbaseSubmitter and Censor
BMC BIOINFORMATICS
2006; 7
Abstract
Repbase is a reference database of eukaryotic repetitive DNA, which includes prototypic sequences of repeats and basic information described in annotations. Updating and maintenance of the database requires specialized tools, which we have created and made available for use with Repbase, and which may be useful as a template for other curated databases.We describe the software tools RepbaseSubmitter and Censor, which are designed to facilitate updating and screening the content of Repbase. RepbaseSubmitter is a java-based interface for formatting and annotating Repbase entries. It eliminates many common formatting errors, and automates actions such as calculation of sequence lengths and composition, thus facilitating curation of Repbase sequences. In addition, it has several features for predicting protein coding regions in sequences; searching and including Pubmed references in Repbase entries; and searching the NCBI taxonomy database for correct inclusion of species information and taxonomic position. Censor is a tool to rapidly identify repetitive elements by comparison to known repeats. It uses WU-BLAST for speed and sensitivity, and can conduct DNA-DNA, DNA-protein, or translated DNA-translated DNA searches of genomic sequence. Defragmented output includes a map of repeats present in the query sequence, with the options to report masked query sequence(s), repeat sequences found in the query, and alignments.Censor and RepbaseSubmitter are available as both web-based services and downloadable versions. They can be found at http://www.girinst.org/repbase/submission.html (RepbaseSubmitter) and http://www.girinst.org/censor/index.php (Censor).
View details for DOI 10.1186/1471-2105-7-474
View details for Web of Science ID 000241763200001
View details for PubMedID 17064419
View details for PubMedCentralID PMC1634758
-
Retroposition of processed pseudogenes: the impact of RNA stability and translational control
TRENDS IN GENETICS
2006; 22 (2): 69-73
Abstract
Human processed pseudogenes are copies of cellular RNAs reverse transcribed and inserted into the nuclear genome by the enzymatic machinery of L1 (LINE1) non-LTR retrotransposons. Although it is generally accepted that germline expression is crucial for the heritable retroposition of cellular mRNAs, little is known about the influences of RNA stability, mRNA quality control and compartmentalization of translation on the retroposition of processed pseudogenes. We found that frequently retroposed human mRNAs are derived from stable transcripts with translation-competent functional reading frames that are resistant to nonsense-mediated RNA decay. They are preferentially translated on free cytoplasmic ribosomes and encode soluble proteins. Our results indicate that interactions between mRNAs and L1 proteins seem to occur at free cytoplasmic ribosomes.
View details for DOI 10.1016/j.tig.2005.11.005
View details for Web of Science ID 000235576900003
View details for PubMedID 16356584
View details for PubMedCentralID PMC1379630
-
Origin and diversification of minisatellites derived from human Alu sequences
GENE
2006; 365: 21-26
Abstract
We analyze minisatellites derived from Alu fragments corresponding approximately to the first 44 bases of human Alu consensus sequences from different subfamilies. The origin of Alu-derived minisatellites appears to have been mediated by short flanking repeats, as first proposed by Haber and Louis [Haber, J.E., Louis, E.J., 1998. Minisatellite origins in yeast and humans. Genomics 48, 132-135.]. We also present evidence for base substitutions and deletions introduced to minisatellites by gene conversion with partially similar but unrelated flanking regions. Segments flanked by short direct repeats are relatively common in different regions of Alu and other repetitive sequences. Our analysis shows that they can be effectively used in comparative studies of the overall sequence context which may contribute to instability of DNA segments flanked by short direct repeats.
View details for DOI 10.1016/j.gene.2005.09.029
View details for Web of Science ID 000236312100004
View details for PubMedID 16343813
-
Traffic of genetic information between segmental duplications flanking the typical 22q-11.2 deletion in velo-cardio-facial syndrome/DiGeorge syndrome
GENOME RESEARCH
2005; 15 (11): 1487-1495
Abstract
Velo-cardio-facial syndrome/DiGeorge syndrome results from unequal crossing-over events between two 240-kb low-copy repeats termed LCR22 (LCR22-2 and LCR22-4) on Chromosome 22q11.2, comprised of modules, each of which are >99% identical in sequence. To delineate regions in the LCR22s that might contain hotspots for 22q11.2 rearrangements, we scanned the interval for increased rates of recombination with the hypothesis that these regions might be more prone to breakage. We generated an algorithm to detect sites of altered recombination by searching for single nucleotide polymorphic positions in BAC clones from different libraries mapped to LCR22-2 and LCR22-4. This method distinguishes single nucleotide polymorphisms from paralogous sequence variants and complex polymorphic positions. Sites of shared polymorphism are considered potential sites of gene conversion or double cross-over between the two LCR22s. We found an inverse correlation between regions of paralogous sequence variants that are unique to a given position within one LCR22 and clusters of shared polymorphic sites, suggesting that these clusters depict altered recombination and not remnants of ancestral single nucleotide polymorphisms. We postulate that most shared polymorphic sites are products of past transfers of DNA information between the LCR22s, suggesting that frequent traffic of genetic material may induce genomic instability in the two LCR22s. We also found that gaps up to 1.5 kb long can be transferred between LCR22s.
View details for DOI 10.1101/gr.4281205
View details for Web of Science ID 000232889400004
View details for PubMedID 16251458
View details for PubMedCentralID PMC1310636
-
Evolutionary diversity and potential recombinogenic role of integration targets of non-LTR retrotransposons
MOLECULAR BIOLOGY AND EVOLUTION
2005; 22 (10): 1983-1991
Abstract
Short interspersed elements (SINEs) make up a significant fraction of total DNA in mammalian genomes, providing a rich substrate for chromosomal rearrangements by SINE-SINE recombinations. Proliferation of mammalian SINEs is mediated primarily by long interspersed element 1 (L1) non-long terminal repeat retrotransposons that preferentially integrate at DNA sequence targets with an average length of approximately 15 bp and containing conserved endonucleolytic nicking signals at both ends. We report that sequence variations in the first of the two nicking signals, represented by a 5'-TT-AAAA consensus sequence, affect the position of the second signal thus leading to target site duplications (TSDs) of different lengths. The length distribution of TSDs appears to be affected also by L1-encoded enzyme variants because targets with the same 5' nicking site can be of different average lengths in different mammalian species. Taking this into account, we reanalyzed the second nicking site and found that it is larger and includes more conserved sites than previously appreciated, with a consensus of 5'-ANTNTN-AA. We also studied potential involvement of the nicking sites in stimulating recombinations between SINEs. We determined that SINEs retaining TSDs with perfect 5'-TT-AAAA nicking sites appear to be lost relatively rapidly from the human and rat genomes and less rapidly from dog. We speculate that the introduction of DNA breaks induced by recurring endonucleolytic attacks at these sites, combined with the ubiquitousness of SINEs, may significantly promote recombination between repetitive elements, leading to the observed losses. At the same time, new L1 subfamilies may be selected for "incompatibility" with preexisting targets. This provides a possible driving force for the continual emergence of new L1 subfamilies which, in turn, may affect selection of L1-dependent SINE subfamilies.
View details for DOI 10.1093/molbev/msi188
View details for Web of Science ID 000231826500005
View details for PubMedID 15944437
View details for PubMedCentralID PMC1400617
-
Genome comparisons and analysis
CURRENT OPINION IN STRUCTURAL BIOLOGY
2003; 13 (3): 344-352
Abstract
As we enter the post-genomic era, with the accelerating availability of complete genome sequences, new theoretical approaches and new experimental techniques, our ability to dissect cellular processes at the molecular level continues to expand. Recent advances include the application of RNA interference methods to characterize loss-of-function phenotype genes in higher eukaryotes, comparative analysis of the human and mouse genome sequences, and methods for reconciling contradictory phylogenetic reconstructions. New developments feed into the increasingly rich content of databases such as the COG database. The next phase of research will be increasingly dominated by efforts to integrate the deluge of data into our understanding of biological systems.
View details for DOI 10.1016/S0959-440X(03)00073-3
View details for Web of Science ID 000184112300011
View details for PubMedID 12831886
-
Associations between human disease genes and overlapping gene groups and multiple amino acid runs
PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA
2002; 99 (26): 17008-17013
Abstract
Overlapping gene groups (OGGs) arise when exons of one gene are contained within the introns of another. Typically, the two overlapping genes are encoded on opposite DNA strands. OGGs are often associated with specific disease phenotypes. In this report, we identify genes with OGG architecture and genes encoding multiple long amino acid runs and examine their relations to diseases. OGGs appear to be susceptible to genomic rearrangements as happens commonly with the loci of the DiGeorge syndrome on human chromosome 22. We also examine the degree of conservation of OGGs between human and mouse. Our analyses suggest that (i) a high proportion of genes in OGG regions are disease-associated, (ii) genomic rearrangements are likely to occur within OGGs, possibly as a consequence of anomalous sequence features prevalent in these regions, and (iii) multiple amino acid runs are also frequently associated with pathologies.
View details for DOI 10.1073/pnas.262658799
View details for Web of Science ID 000180101600090
View details for PubMedID 12473749
View details for PubMedCentralID PMC139260
-
Genes, pseudogenes, and Alu sequence organization across human chromosomes 21 and 22
PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA
2002; 99 (5): 2930-2935
Abstract
Human chromosomes 21 and 22 (mainly the q-arms) were the first complete parts of the human genome released. Our analysis of genes, pseudogenes (Psig), and Alu repeats across these chromosomes include the following findings: The number of gene structures containing untranslated exons exceeds 25%; the terminal exon tends to be the largest among exons, whereas, the initial intron tends to be the largest among introns; single-exon gene length is approximately the mean gene exon number times the mean internal exon length; processed Psig lengths are on average approximately the same as single-exon gene length; and the G+C content and length of genes are uncorrelated. The counts and distribution of genes, Psig, and Alu sequences and G+C variation are evaluated with respect to clusters and overdispersions. Other assessments concern comparisons of intergenic lengths, properties of Psig sequences, and correlations between Alu and Psig sequences.
View details for DOI 10.1073/pnas.052692099
View details for Web of Science ID 000174284600062
View details for PubMedID 11867739
View details for PubMedCentralID PMC122450
-
Amino acid runs in eukaryotic proteomes and disease associations
PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA
2002; 99 (1): 333-338
Abstract
We present a comparative proteome analysis of the five complete eukaryotic genomes (human, Drosophila melanogaster, Caenorhabditis elegans, Saccharomyces cerevisiae, Arabidopsis thaliana), focusing on individual and multiple amino acid runs, charge and hydrophobic runs. We found that human proteins with multiple long runs are often associated with diseases; these include long glutamine runs that induce neurological disorders, various cancers, categories of leukemias (mostly involving chromosomal translocations), and an abundance of Ca(2 +) and K(+) channel proteins. Many human proteins with multiple runs function in development and/or transcription regulation and are Drosophila homeotic homologs. A large number of these proteins are expressed in the nervous system. More than 80% of Drosophila proteins with multiple runs seem to function in transcription regulation. The most frequent amino acid runs in Drosophila sequences occur for glutamine, alanine, and serine, whereas human sequences highlight glutamate, proline, and leucine. The most frequent runs in yeast are of serine, glutamine, and acidic residues. Compared with the other eukaryotic proteomes, amino acid runs are significantly more abundant in the fly. This finding might be interpreted in terms of innate differences in DNA-replication processes, repair mechanisms, DNA-modification systems, and mutational biases. There are striking differences in amino acid runs for glutamine, asparagine, and leucine among the five proteomes.
View details for Web of Science ID 000173233300061
View details for PubMedID 11782551
-
Genomics - Annotation of the Drosophila genome
NATURE
2001; 411 (6835): 259-260
View details for Web of Science ID 000168710000034
View details for PubMedID 11357119
-
Genome-scale compositional comparisons in eukaryotes
GENOME RESEARCH
2001; 11 (4): 540-546
Abstract
We examined dinucleotide relative abundances and their biases in recent sequences of eukaryotic genomes and chromosomes, including human chromosomes 21 and 22, Saccharomyces cerevisiae, Arabidopsis thaliana, and Drosophila melanogaster. We found that dinucleotide relative abundances are remarkably constant across human chromosomes and within the DNA of a particular species. The dinucleotide biases differ between species, providing a genome signature that is characteristic of the bulk properties of an organism's DNA. We detail the relations between species genome signatures and suggest possible mechanisms for their origin and maintenance.
View details for Web of Science ID 000167885400005
View details for PubMedID 11282969
View details for PubMedCentralID PMC311039
-
Why are human G-protein-coupled receptors predominantly intronless?
TRENDS IN GENETICS
1999; 15 (2): 47-49
View details for Web of Science ID 000079419400002
View details for PubMedID 10098406