Honors & Awards
Fellowship for Ph.D. research studies abroad, German academic exchange program (DAAD) (11/2011-10/2012)
Fellowship for Diploma thesis research, DAAD (08/2010-11/2010)
Diploma fellowship, PROSA LMU (06/2010-07/2010)
Core Exploratory Award, UC San Francisco (05/2012-04/2013)
Woman in Cancer Research Award, WICR (04/2015)
Current Research and Scholarly Interests
My research focuses on understanding the evolution of tumor cell populations, on how selective pressures, such as those imposed by chemo- and radiotherapies, favor the survival of one tumor cell population over another. Towards this goal I develop algorithms that measure intra-tumor heterogeneity from next-generation sequencing data or from more traditional diagnostic procedures, such as H&E stainings.
My long-term goal is to develop an adaptable therapeutic strategy that vastly increases the number of alternative therapy options and that rationalizes therapy choice.
Single-cell RNA-Seq of lymphoma cancers reveals malignant B cell types and co-expression of T cell immune checkpoints.
Follicular lymphoma (FL) is a low-grade B cell malignancy that transforms into a highly aggressive and lethal disease at a rate of 2% per year. Perfect isolation of the malignant B cell population from a surgical biopsy is a significant challenge, masking important FL biology, such as immune checkpoint co-expression patterns. To resolve the underlying transcriptional networks of follicular B cell lymphomas we analyzed the transcriptomes of 34,188 cells derived from six primary FL tumors. For each tumor, we identified normal immune subpopulations and malignant B cells based on gene expression. We used multicolor flow cytometry analysis of the same tumors to confirm our assignments of cellular lineages and validate our predictions of expressed proteins. Comparison of gene expression between matched malignant and normal B cells from the same patient revealed tumor-specific features. Malignant B cells exhibited restricted immunoglobulin light chain expression (either Ig Kappa or Ig Lambda), as well the expected upregulation of the BCL2 gene, but also down-regulation of the FCER2, CD52 and MHC class II genes. By analyzing thousands of individual cells per patient tumor, we identified the mosaic of malignant B cell subclones that coexist within a FL and examined the characteristics of tumor-infiltrating T cells. We identified genes co-expressed with immune checkpoint molecules, such as CEBPA and B2M in Tregs, providing a better understanding of the gene networks involved in immune regulation. In summary, parallel measurement of single-cell expression in thousands of tumor cells and tumor-infiltrating lymphocytes can be used to obtain a systems-level view of the tumor microenvironment and identify new avenues for therapeutic development.
View details for DOI 10.1182/blood-2018-08-862292
View details for PubMedID 30591526
Pan-cancer analysis of the extent and consequences of intratumor heterogeneity
2016; 22 (1): 105-?
Intratumor heterogeneity (ITH) drives neoplastic progression and therapeutic resistance. We used the bioinformatics tools 'expanding ploidy and allele frequency on nested subpopulations' (EXPANDS) and PyClone to detect clones that are present at a ≥10% frequency in 1,165 exome sequences from tumors in The Cancer Genome Atlas. 86% of tumors across 12 cancer types had at least two clones. ITH in the morphology of nuclei was associated with genetic ITH (Spearman's correlation coefficient, ρ = 0.24-0.41; P < 0.001). Mutation of a driver gene that typically appears in smaller clones was a survival risk factor (hazard ratio (HR) = 2.15, 95% confidence interval (CI): 1.71-2.69). The risk of mortality also increased when >2 clones coexisted in the same tumor sample (HR = 1.49, 95% CI: 1.20-1.87). In two independent data sets, copy-number alterations affecting either <25% or >75% of a tumor's genome predicted reduced risk (HR = 0.15, 95% CI: 0.08-0.29). Mortality risk also declined when >4 clones coexisted in the sample, suggesting a trade-off between the costs and benefits of genomic instability. ITH and genomic instability thus have the potential to be useful measures that can universally be applied to all cancers.
View details for DOI 10.1038/nm.3984
View details for Web of Science ID 000367590700022
EXPANDS: expanding ploidy and allele frequency on nested subpopulations
2014; 30 (1): 50-60
Several cancer types consist of multiple genetically and phenotypically distinct subpopulations. The underlying mechanism for this intra-tumoral heterogeneity can be explained by the clonal evolution model, whereby growth advantageous mutations cause the expansion of cancer cell subclones. The recurrent phenotype of many cancers may be a consequence of these coexisting subpopulations responding unequally to therapies. Methods to computationally infer tumor evolution and subpopulation diversity are emerging and they hold the promise to improve the understanding of genetic and molecular determinants of recurrence.To address cellular subpopulation dynamics within human tumors, we developed a bioinformatic method, EXPANDS. It estimates the proportion of cells harboring specific mutations in a tumor. By modeling cellular frequencies as probability distributions, EXPANDS predicts mutations that accumulate in a cell before its clonal expansion. We assessed the performance of EXPANDS on one whole genome sequenced breast cancer and performed SP analyses on 118 glioblastoma multiforme samples obtained from TCGA. Our results inform about the extent of subclonal diversity in primary glioblastoma, subpopulation dynamics during recurrence and provide a set of candidate genes mutated in the most well-adapted subpopulations. In summary, EXPANDS predicts tumor purity and subclonal composition from sequencing data.EXPANDS is available for download at http://code.google.com/p/expands (matlab version--used in this manuscript) and http://cran.r-project.org/web/packages/expands (R version).
View details for DOI 10.1093/bioinformatics/btt622
View details for Web of Science ID 000329059700008
View details for PubMedID 24177718
Exploring the spatiotemporal genetic heterogeneity in metastatic lung adenocarcinoma using a nuclei flow-sorting approach.
The Journal of pathology
Variable tumor cellularity can limit sensitivity and precision in comparative genomics, because differences in tumor content can result in misclassifying truncal mutations as region-specific private mutations in stroma-rich regions, especially when studying tissue specimens of mediocre tumor cellularity such as lung adenocarcinomas (LUADs). To address this issue, we refined a nuclei flow-sorting approach by sorting nuclei based on ploidy and the LUAD lineage marker thyroid transcription factor 1 and applied this method to investigated genome-wide somatic copy number aberrations (SCNA) and mutations of 409 cancer genes in 39 tumor populations obtained from 16 primary tumors and 21 matched metastases. This approach increased the mean tumor purity from 54% (range: 7-89%) of unsorted material to 92% (range: 79-99%) after sorting. Despite this rise in tumor purity, we detected limited genetic heterogeneity between primary tumors and their metastases. In fact, 88% of SCNAs and 80% of mutations were propagated from primary tumors to metastases and low allele frequency mutations accounted for much of the mutational heterogeneity. Even though the presence of SCNAs indicated a history of chromosomal instability (CIN) in all tumors, metastases did not have more SCNAs than primary tumors. Moreover, tumors with biallelic TP53 or ATM mutations had high numbers of SCNAs, yet they were associated with a low interlesional genetic heterogeneity. The results of our study thus provide evidence that most macroevolutionary events occur in primary tumors before metastatic dissemination and advocate for a limited degree of CIN over time and space in this cohort of LUADs. Sampling of primary tumors thus may suffice to detect most mutations and SCNAs. In addition, metastases but not primary tumors had seeded additional metastases in three of four patients; this provides a genomic rational for surgical treatment of such oligometastatic LUADs.
View details for DOI 10.1002/path.5183
View details for PubMedID 30350422
Lgl1 controls NG2 endocytic pathway to regulate oligodendrocyte differentiation and asymmetric cell division and gliomagenesis
2018; 9: 2862
Oligodendrocyte progenitor cells (OPC) undergo asymmetric cell division (ACD) to generate one OPC and one differentiating oligodendrocyte (OL) progeny. Loss of pro-mitotic proteoglycan and OPC marker NG2 in the OL progeny is the earliest immunophenotypic change of unknown mechanism that indicates differentiation commitment. Here, we report that expression of the mouse homolog of Drosophila tumor suppressor Lethal giant larvae 1 (Lgl1) is induced during OL differentiation. Lgl1 conditional knockout OPC progeny retain NG2 and show reduced OL differentiation, while undergoing more symmetric self-renewing divisions at the expense of asymmetric divisions. Moreover, Lgl1 and hemizygous Ink4a/Arf knockouts in OPC synergistically induce gliomagenesis. Time lapse and total internal reflection microscopy reveals a critical role for Lgl1 in NG2 endocytic routing and links aberrant NG2 recycling to failed differentiation. These data establish Lgl1 as a suppressor of gliomagenesis and positive regulator of asymmetric division and differentiation in the healthy and demyelinated murine brain.
View details for DOI 10.1038/s41467-018-05099-3
View details for Web of Science ID 000442268000001
View details for PubMedID 30131568
View details for PubMedCentralID PMC6104045
SVEngine: an efficient and versatile simulator of genome structural variations with features of cancer clonal evolution.
Background: Simulating genome sequence data with variant features facilitates the development and benchmarking of structural variant analysis programs. However, there are only a few data simulators that provide structural variants in silico and even fewer that provide variants with different allelic fraction and haplotypes.Findings: We developed SVEngine, an open source tool to address this need. SVEngine simulates next generation sequencing data with embedded structural variations. As input, SVEngine takes template haploid sequences (FASTA) and an external variant file, a variant distribution file and/or a clonal phylogeny tree file (NEWICK) as input. Subsequently, it simulates and outputs sequence contigs (FASTAs), sequence reads (FASTQs) and/or post-alignment files (BAMs). All of the files contain the desired variants, along with BED files containing the ground truth. SVEngine's flexible design process enables one to specify size, position, and allelic fraction for deletions, insertions, duplications, inversions and translocations. Finally, SVEngine simulates sequence data that replicates the characteristics of a sequencing library with mixed sizes of DNA insert molecules. To improve the compute speed, SVEngine is highly parallelized to reduce the simulation time.Conclusions: We demonstrated the versatile features of SVEngine and its improved runtime comparisons with other available simulators. SVEngine's features include the simulation of locus-specific variant frequency designed to mimic the phylogeny of cancer clonal evolution. We validated SVEngine's accuracy by simulating genome-wide structural variants of NA12878 and a heterogenous cancer genome. Our evaluation included checking various sequencing mapping features such as coverage change, read clipping, insert size shift and neighbouring hanging read pairs for representative variant types. Structural variant callers Lumpy and Manta and tumor heterogeneity estimator THetA2 were able to perform realistically on the simulated data. SVEngine is implemented as a standard Python package and is freely available for academic use at: https://bitbucket.org/charade/svengine.
View details for DOI 10.1093/gigascience/giy081
View details for PubMedID 29982625
Genomic Instability in Cancer: Teetering on the Limit of Tolerance
2017; 77 (9): 2179-2185
Cancer genomic instability contributes to the phenomenon of intratumoral genetic heterogeneity, provides the genetic diversity required for natural selection, and enables the extensive phenotypic diversity that is frequently observed among patients. Genomic instability has previously been associated with poor prognosis. However, we have evidence that for solid tumors of epithelial origin, extreme levels of genomic instability, where more than 75% of the genome is subject to somatic copy number alterations, are associated with a potentially better prognosis compared with intermediate levels under this threshold. This has been observed in clonal subpopulations of larger size, especially when genomic instability is shared among a limited number of clones. We hypothesize that cancers with extreme levels of genomic instability may be teetering on the brink of a threshold where so much of their genome is adversely altered that cells rarely replicate successfully. Another possibility is that tumors with high levels of genomic instability are more immunogenic than other cancers with a less extensive burden of genetic aberrations. Regardless of the exact mechanism, but hinging on our ability to quantify how a tumor's burden of genetic aberrations is distributed among coexisting clones, genomic instability has important therapeutic implications. Herein, we explore the possibility that a high genomic instability could be the basis for a tumor's sensitivity to DNA-damaging therapies. We primarily focus on studies of epithelial-derived solid tumors. Cancer Res; 77(9); 2179-85. ©2017 AACR.
View details for DOI 10.1158/0008-5472.CAN-16-1553
View details for Web of Science ID 000400270100001
View details for PubMedID 28432052
View details for PubMedCentralID PMC5413432
Pharmacologic inhibition of histone demethylation as a therapy for pediatric brainstem glioma
2014; 20 (12): 1394-1396
Pediatric brainstem gliomas often harbor oncogenic K27M mutation of histone H3.3. Here we show that GSKJ4 pharmacologic inhibition of K27 demethylase JMJD3 increases cellular H3K27 methylation in K27M tumor cells and demonstrate potent antitumor activity both in vitro against K27M cells and in vivo against K27M xenografts. Our results demonstrate that increasing H3K27 methylation by inhibiting K27 demethylase is a valid therapeutic strategy for treating K27M-expressing brainstem glioma.
View details for DOI 10.1038/nm.3716
View details for Web of Science ID 000345817900013
View details for PubMedID 25401693
- BIOLOGICALLY-BASED THERAPEUTICS FOR THE TREATMENT OF DIFFUSE INTRINSIC PONTINE GLIOMAS 20th International Conference on Brain Tumor Research and Therapy OXFORD UNIV PRESS INC. 2014
- STEM- AND PROGENITOR-LIKE CELL CONTRIBUTION TO MALIGNANT ASTROCYTOMA HETEROGENEITY 20th International Conference on Brain Tumor Research and Therapy OXFORD UNIV PRESS INC. 2014
Asymmetry-Defective Oligodendrocyte Progenitors Are Glioma Precursors
2011; 20 (3): 328-340
Postnatal oligodendrocyte progenitor cells (OPC) self-renew, generate mature oligodendrocytes, and are a cellular origin of oligodendrogliomas. We show that the proteoglycan NG2 segregates asymmetrically during mitosis to generate OPC cells of distinct fate. NG2 is required for asymmetric segregation of EGFR to the NG2(+) progeny, which consequently activates EGFR and undergoes EGF-dependent proliferation and self-renewal. In contrast, the NG2(-) progeny differentiates. In a mouse model, decreased NG2 asymmetry coincides with premalignant, abnormal self-renewal rather than differentiation and with tumor-initiating potential. Asymmetric division of human NG2(+) cells is prevalent in non-neoplastic tissue but is decreased in oligodendrogliomas. Regulators of asymmetric cell division are misexpressed in low-grade oligodendrogliomas. Our results identify loss of asymmetric division associated with the neoplastic transformation of OPC.
View details for DOI 10.1016/j.ccr.2011.08.011
View details for Web of Science ID 000295205700009
View details for PubMedID 21907924