Systematic Assessment of Tumor Purity and Its Clinical Implications

PURPOSE

The tumor microenvironment is complex, comprising heterogeneous cellular populations. As molecular profiles are frequently generated using bulk tissue sections, they represent an admixture of multiple cell types (including immune, stromal, and cancer cells) interacting with each other. Therefore, these molecular profiles are confounded by signals emanating from many cell types. Accurate assessment of residual cancer cell fraction is crucial for parameterization and interpretation of genomic analyses, as well as for accurately interpreting the clinical properties of the tumor.

MATERIALS AND METHODS

To benchmark cancer cell fraction estimation methods, 10 estimators were applied to a clinical cohort of 333 patients with prostate cancer. These methods include gold-standard multiobserver pathology estimates, as well as estimates inferred from genome, epigenome, and transcriptome data. In addition, two methods based on genomic and transcriptomic profiles were used to quantify tumor purity in 4,497 tumors across 12 cancer types. Bulk mRNA and microRNA profiles were subject to in silico deconvolution to estimate cancer cell-specific mRNA and microRNA profiles.

RESULTS

We present a systematic comparison of 10 tumor purity estimation methods on a cohort of 333 prostate tumors. We quantify variation among purity estimation methods and demonstrate how this influences interpretation of clinico-genomic analyses. Our data show poor concordance between pathologic and molecular purity estimates, necessitating caution when interpreting molecular results. Limited concordance between DNA- and mRNA-derived purity estimates remained a general pan-cancer phenomenon when tested in an additional 4,497 tumors spanning 12 cancer types.

CONCLUSION

The choice of tumor purity estimation method may have a profound impact on the interpretation of genomic assays. Taken together, these data highlight the need for improved assessment of tumor purity and quantitation of its influences on the molecular hallmarks of cancers.

Abstract 3302: The molecular landscape of oncogenic signaling pathways in The Cancer Genome Atlas

Over the past decade, The Cancer Genome Atlas (TCGA) has profiled more than 11,000 tumors spanning 33 distinct cancer types. The TCGA PanCanAtlas is a collaborative project by the TCGA Research Network that aims to address relevant overarching questions in oncology based on a cross-cancer analysis of the full, uniformly reprocessed TCGA data set. Here, we present results from our analysis of genetic alterations in mitogenic signaling pathways across cancer.

Genetic alterations in signaling pathways that control cell cycle progression, apoptosis, and cell growth are common hallmarks of cancer, but the extent, mechanisms, and co-occurrence of alterations in these pathways differ between individual tumors and tumor types. Using mutations and copy-number changes in 9,125 tumor samples profiled by TCGA, we analyzed the mechanisms and patterns of alterations in 10 canonical pathways: cell cycle, Hippo, Myc, Notch, beta-catenin / WNT, PI-3-Kinase / Akt, receptor-tyrosine kinase / RAS / MAP-kinase signaling, TP53, and TGF-beta signaling, as well as oxidative stress response. For each of these pathways, we propose an expert-curated description (or “template”) that includes the relevant (altered) genes and the connections between them, as well as a detailed catalogue of the driver mutations and copy number changes with known oncogenic relevance. We provide a high-level map of pathway alteration frequencies across tissues and relevant cancer subtypes as well as detailed frequencies of alteration at the gene level for each individual pathway. We also investigate relationships of co-occurrence and mutual exclusivity across pathways and evaluate therapeutic implications, including drug combinations. Forty-nine percent of tumors had at least one potentially targetable alteration in the evaluated pathways, and 31% of tumors had multiple targetable alterations, making them candidates for combination therapy.

Our work delineates the full landscape of oncogenic alterations in mitogenic signaling pathways across cancer, and the pathway templates as well as the richly annotated data set that we provide will constitute an invaluable public resource for future use by the cancer genomics and precision oncology communities.

Citation Format: Francisco Sanchez-Vega, Marco Mina, Joshua Armenia, Walid K. Chatila, Augustin Luna, Konnor La, Sofia Dimitriadoy, David L. Liu, Havish S. Kantheti, Zachary Heins, Angelica Ochoa, Benjamin Gross, Jianjiong Gao, Hongxin Zhang, Ritika Kundra, Cyriac Kandoth, Istemi Bahceci, Leonard Dervishi, Ugur Dogrusoz, Wanding Zhou, Hui Shen, Peter W. Laird, Alice H. Berger, Trever G. Bivona, Alexander J. Lazar, Gary Hammer, Thomas Giordano, Lawrence Kwong, Grant McArthur, Chenfei Huang, Mitchell J. Frederick, Frank McCormick, Matthew Meyerson, The Cancer Genome Atlas Research Network, Eliezer Van Allen, Andrew D. Cherniack, Giovanni Ciriello, Chris Sander, Nikolaus Schultz. The molecular landscape of oncogenic signaling pathways in The Cancer Genome Atlas [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2018; 2018 Apr 14-18; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2018;78(13 Suppl):Abstract nr 3302.

Abstract LB-373: Comprehensive analysis of cancer stemness

Cancer progression involves the gradual loss of a differentiated phenotype and acquisition of progenitor and stem cell-like features. Here, we provide new stemness indices for assessing the degree of oncogenic dedifferentiation. We took advantage of an innovative one-class logistic regression machine learning algorithm (OCLR) to extract transcriptomic and epigenetic feature sets derived from non-transformed pluripotent stem cells and their differentiated progenies. Using OCLR, we were able to sort TCGA tumor samples by stemness phenotype and identify previously undiscovered biological mechanisms associated with the dedifferentiated oncogenic state. Analyses of tumor microenvironment revealed the correlation of cancer stemness with immune checkpoint expression and infiltrating immune system cells not previously anticipated. We have shown the de-differentiated oncogenic phenotype increased in the metastatic tumor that further justify their more aggressive phenotype. Application of our stemness indices reveals features of intra-tumor heterogeneity in molecular profiles obtained from the single-cell analyses. Finally, the machine learning-based indices allowed for the identification of chemical compounds and novel targets for the cancer therapies aiming at tumor differentiation. Our findings provide new prognostic signatures that enable cancer biologists and oncologists to quantify the impact of tumor stemness on outcome across cancer types and may help to pave the way for progress in treatment strategies for cancer patients.

Citation Format: Tathiane M. Malta, Artem Sokolov, Andrew J. Gentles, Tomasz Burzykowski, Laila Poisson, John Weinstein, Bożena Kamińska, Joerg Huelsken, Larsson Omberg, Olivier Gevaert, Antonio Colaprico, Patrycja Czerwińska, Sylwia Mazurek, Lopa Mishra, Holger Heyn, Alex Krasnitz, Andrew K. Godwin, Alexander J. Lazar, The Cancer Genome Atlas Research Network, Joshua M. Stuart, Katherine Hoadley, Peter W. Laird, Houtan Noushmehr, Maciej Wiznerowicz. Comprehensive analysis of cancer stemness [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2018; 2018 Apr 14-18; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2018;78(13 Suppl):Abstract nr LB-373.

Abstract 3413: A pan-cancer atlas of genomic, epigenomic and transcriptomic alterations in the TGF-β pathway

The TGF-β pathway is a multifunctional signaling cascade with context-dependent roles in diverse biologic processes, including tumor promotion or suppression, metastasis, stem cell homeostasis, and immune suppression. Due to its highly context-dependent nature, decoding functional outcomes of the TGF-β pathway in specific tissues is highly challenging. Here, we present comprehensive genomic, transcriptomic and epigenomic analyses of the TGF-β pathway identified by 44 core pathway genes across 33 TCGA tumor types and 9125 samples. The core pathway genes involve TGF-β like ligands, receptors, intracellular SMAD molecules and adaptors. Although individual core pathway genes were rarely mutated or copy number altered in different cancer types, 41% of all samples have at least one genomic alteration in the TGF-β pathway, predominantly in the form of mutations. We identified a highly conserved TGF-β downstream gene expression signature associated with alterations in core pathway genes, suggesting that the alterations in the pathway have shared functional consequences. We observed a significant enrichment of the genomic alterations in gastrointestinal cancers (GI) with a distinct gene expression signature. The newly identified gene expression signature (over- or downregulation of key TGF-β downstream genes) in pan-cancer cohort was associated with significantly poor prognosis, particularly when it co-occurred with genomic alterations in the core pathway. Analysis of mutational hotspot sites revealed 6 genes with hotspots recurring in at least 9 (up to 78) mutational incidences. The hotspot mutations were also highly enriched in GI cancers. We identified previously characterized cancer mutation sites on SMAD4 and SMAD2 as hotspots mainly in GI cancers. We hypothesized novel functions to two of the newly identified hotpot sites through structural and trancriptomic analyses, and two other novel hotspot sites in the pathway await functional characterization. miRNA and epigenomic analyses revealed that TGF-β pathway activity is limited by epigenetic silencing or miRNA expression, especially in cancers with very low pathway gene expression levels. This multidimensional study provides the multifacefed landscape of TGF-β signaling in both individual disease and pan-cancer settings to guide future functional and therapeutic studies of this key cancer pathway.

Citation Format: Anil Korkut, Sobia Zaidi, Rupa Kanchi, Ashton C. Berger, Gordon Robertson, Lawrence N. Kwong, Mike Datto, Jason Roszik, Shiyun Ling, Andre Schultz, Visweswaran Ravikumar, Ganiraju Manyam, Arvind Rao, Simon Shelley, Yuexin Liu, Zhenlin Ju, Donna Hansel, Guillermo de Velasco, Arjun Pennathur, Jesper B. Andersen, Colm J. O'Rourke, Kazufumi Ohshiro, Wilma Jogunoori, Nancy Gough, Shulin Li, Hatice Osmanbeyoglu, Andres Houseman, Shuyun Rao, Maciej Wiznerowicz, Jian Chen, Shoujun Gu, Wencai Ma, Jiexin Zhang, Pan Tong, Andrew D. Cherniack, Chuxia Deng, Linda Resar-Smith, Jaffer Ajani, The Cancer Genome Atlas Research Network, John N. Weinstein, Lopa Mishra, Rehan Akbani. A pan-cancer atlas of genomic, epigenomic and transcriptomic alterations in the TGF-β pathway [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2018; 2018 Apr 14-18; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2018;78(13 Suppl):Abstract nr 3413.

Abstract 133: Integrated molecular characterization of uterine carcinosarcoma in The Cancer Genome Atlas (TCGA) project

We used array- and sequencing-based technologies to perform an integrated genomic, epigenomic, transcriptomic, and proteomic characterization of the rare tumor type uterine carcinosarcoma (UCS) within the context of The Cancer Genome Atlas (TCGA) project using 57 cases that had stringent histopathologic review. Cohort samples had extensive copy number alterations and highly recurrent somatic mutations. Nearly all (91%) cases had TP53 mutations, similar to ovarian and serous uterine carcinomas, and frequent mutations were also found in PTEN, PIK3CA, PPP2R1A, FBXW7, and KRAS, similar to endometrioid and serous uterine carcinomas. Transcriptome sequencing identified a strong EMT gene signature in a subset of 17 (30%) cases, and cases with EMT signatures had decreased expression of mir-200 family members that was attributable to epigenetic alterations at miRNA promoters. The range of EMT signatures scores in UCS was the largest among all the TCGA tumor types studied. UCS shared proteomic features with both gynecologic carcinomas and non-gynecologic mesenchymal-like tumors. Our results indicate that UCS tumors share many features with serous-like endometrial carcinomas, including frequent TP53 mutations and extensive somatic copy number alterations, though with greater EMT features. Multiple somatic mutations and copy number alterations in genes that are therapeutic targets were identified. There was a high degree of mutational clonality, consistent with tumors being derived from a single cell of origin. Taken together, these data suggest that while some UCS tumors develop from an endometrioid lineage, the majority likely de-differentiate from a serous precursor, potentially accounting for their clinical aggressiveness and poor response to treatment.

Citation Format: Rehan Akbani, The Cancer Genome Atlas Research Network, Douglas A. Levine. Integrated molecular characterization of uterine carcinosarcoma in The Cancer Genome Atlas (TCGA) project. [abstract]. In: Proceedings of the 107th Annual Meeting of the American Association for Cancer Research; 2016 Apr 16-20; New Orleans, LA. Philadelphia (PA): AACR; Cancer Res 2016;76(14 Suppl):Abstract nr 133.

Abstract 2976: Comprehensive Pan-Genomic characterization of adrenocortical carcinoma

Adrenocortical carcinoma (ACC) is a rare neoplasm with a heterogeneous outcome and limited treatment options. To understand its molecular and genomic landscape as a part of The Cancer Genome Atlas (TCGA) project, we performed the genomic, transcriptomic, epigenomic and proteomic profiling of 91 ACCs.

We identified potential driving alterations including amplifications (TERT, TERF2 and CDK4), deletions (ZNRF3, CDKN2A and RB1) and point mutations in genes unknown to participate in adrenal disease (RPL22) and genes known to initiate familial syndromes that occasionally include adrenocortical neoplasms (TP53, CTNNB1, PRKAR1A, MEN1). The finding of PRKAR1A expands the catalogue of pathogenic pathways underlying ACC, suggesting of the protein kinase alpha signaling pathway as a potential target for molecular interventions. Novel transcript fusions potentially leading to overactive kinases included EXOSC10-MTOR and PPP1CB-BRE.

DNA copy number analysis unveiled prevalent DNA losses leading to hypodiploidy as well as whole genome doubling (WGD) in 51% of ACC. The similar penetrance of loss of heterozygosity before and after WGD suggests a sequential development from hypodiploidy to polyploidy along the doubling in a subset of ACCs, which was endorsed by the worse outcome for WGD samples relative to nonWGD ACCs. An association between TERT expression and WGD was observed, suggesting a role for telomere regulation. These findings present ACC as a model disease for studies of WGD which is a frequent event in many tumor types.

Unsupervised clustering of DNA methylation, copy number, gene expression, miRNA expression and protein abundance converged into three classes with specific biological characteristics and a respective median event free survival of 8, 38 and >100 months (p-value 1.7e-13). Comparison of the subtypes suggested additional drivers such as protein kinase C (PKC) phosphorylation and upregulation of a miRNA cluster at chromosome Xq27.3, which complemented the genomic alterations identified in these subtypes.

To gain more insights into this rare cancer type, we placed ACC in a broader context of cancer genomic profiles including an array of other cancer types. These analyses revealed interesting shared features, including beta-catenin activation with a subset of endometroid cancer, DNA mismatch repair gene mutational signature with gastrointestinal cancers and a smoking signature with lung cancer. These findings highlight the commonalities between ACC and other lineages of cancer.

Taken together, we found Wnt signaling pathway and p53/Rb signaling pathway were the most frequently altered pathways in ACC. Meanwhile, new players surfaced from our analyses including the PKA and PKC pathways. Our results present a comprehensive genomic landscape and refined molecular classification of ACC improve our understanding of its pathogenesis, and will ultimately improve the care of patients.

Citation Format: Siyuan Zheng, Andrew D. Cherniack, Ninad Dewal, Richard A. Moffitt, Ludmila Danilova, Bradley A. Murray, Antonio M. Lerario, Tobias Else, Theo A. Knijnenburg, Giovanni Ciriello, Seungchan Kim, Guillaume Assie, Olena Morozova, Rehan Akbani, Juliann Shih, Katherine A. Hoadley, Toni K. Choueiri, Jens Waldmann, Ozgur Mete, Gordon A. Robertson, Matthew Meyerson, Michael J. Demeure, Felix Beuschlein, Anthony Gill, Ana C. Latronico, Maria C. Fragosa, Leslie Cope, Electron Kebebew, Mouhammed A. Habra, Timothy G. Whitsett, Kimberly J. Bussey, William E. Rainey, Sylvia Asa, Jérôme Bertherat, Martin Fassnacht, David A. Wheeler, The Cancer Genome Atlas Research Network, Gary D. Hammer, Thomas J. Giordano, Roel Verhaak. Comprehensive Pan-Genomic characterization of adrenocortical carcinoma. [abstract]. In: Proceedings of the 106th Annual Meeting of the American Association for Cancer Research; 2015 Apr 18-22; Philadelphia, PA. Philadelphia (PA): AACR; Cancer Res 2015;75(15 Suppl):Abstract nr 2976. doi:10.1158/1538-7445.AM2015-2976

Comprehensive molecular characterization of gastric adenocarcinoma

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

Comprehensive molecular characterization of urothelial bladder carcinoma

Urothelial carcinoma of the bladder is a common malignancy that causes approximately 150,000 deaths per year worldwide. So far, no molecularly targeted agents have been approved for treatment of the disease. As part of The Cancer Genome Atlas project, we report here an integrated analysis of 131 urothelial carcinomas to provide a comprehensive landscape of molecular alterations. There were statistically significant recurrent mutations in 32 genes, including multiple genes involved in cell-cycle regulation, chromatin regulation, and kinase signalling pathways, as well as 9 genes not previously reported as significantly mutated in any cancer. RNA sequencing revealed four expression subtypes, two of which (papillary-like and basal/squamous-like) were also evident in microRNA sequencing and protein data. Whole-genome and RNA sequencing identified recurrent in-frame activating FGFR3-TACC3 fusions and expression or integration of several viruses (including HPV16) that are associated with gene inactivation. Our analyses identified potential therapeutic targets in 69% of the tumours, including 42% with targets in the phosphatidylinositol-3-OH kinase/AKT/mTOR pathway and 45% with targets (including ERBB2) in the RTK/MAPK pathway. Chromatin regulatory genes were more frequently mutated in urothelial carcinoma than in any other common cancer studied so far, indicating the future possibility of targeted therapy for chromatin abnormalities.

Abstract 1112: Whole exome and whole genome sequence analysis of lung adenocarcinoma

Lung adenocarcinoma is the leading cause of cancer-related death worldwide. Recent molecular characterization of this disease through large-scale sequencing efforts has identified distinct subsets driven by mutant oncogenes or kinase fusion proteins, many of which can be inhibited with targeted therapies. Despite these advances, almost half of all lung cancers still lack an identifiable driver. Here, we describe the genomic profiling of 230 normal-paired lung adenocarcinoma samples included as part of The Cancer Genome Atlas (TCGA) effort. All samples were subjected to whole exome analysis, copy number profiling and a subset were also subjected to whole genome sequencing. Mutation calling was performed with the MuTect algorithm. To identify significantly mutated genes, we used the MutSig CV algorithm, a statistically rigorous analysis that takes into account nucleotide context, gene-expression, replication time, and somatic background mutation rate. Mutation rate in lung adenocarcinoma was quite high with an average of 242 mutations/tumor observed (median: 161, range: 11-1328). In total, we identified mutations in over 13,500 genes of which 10 genes reached statistical significance (q<0.1). One significant gene was excluded from further analyses as it was not expressed in RNA-seq data. In addition to mutant genes with established roles in lung adenocarcinoma (e.g. TP53, KRAS, STK11, EGFR, RB1, KEAP1, and BRAF), we also identified other statistically significant mutant genes whose role in lung tumorigenesis is presently unclear. These included mutations in the RNA-binding protein RBM10, and the integrin protein ITGAL. Although statistically insignificant by a small degree, we also identified mutations in the splicing factor U2AF1, and the SWI/SNF complex proteins SMARCA4 and ARID1A. We are currently analyzing whole genome sequences to confirm these events, and identify known and novel fusion events that may be contributing to tumorigenesis. In conclusion, we have analyzed the exomes of 230 lung adenocarcinoma samples and identified known and unknown mutations in this disease. Ultimately, these data will be integrated with ongoing expression, methylation, pathway, miRNA, and proteomic analyses. At its conclusion, this effort will represent the most comprehensive profiling of lung adenocarcinoma samples to date, and will provide a detailed integrative picture of the molecular mechanisms contributing to this disease.

Citation Format: Juliann Chmielecki, Mara Rosenberg, Marcin Imielinski, Bryan Hernandez, Michael Lawrence, Andrey Sivachenko, Kristian Cibulskis, Douglas Voet, Carrie Sougnez, Stacey Gabriel, Gad Getz, Matthew Meyerson, The Cancer Genome Atlas Research Network. Whole exome and whole genome sequence analysis of lung adenocarcinoma. [abstract]. In: Proceedings of the 104th Annual Meeting of the American Association for Cancer Research; 2013 Apr 6-10; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2013;73(8 Suppl):Abstract nr 1112. doi:10.1158/1538-7445.AM2013-1112

Spectrum of somatic mitochondrial mutations in five cancers

Somatic mtDNA mutations have been reported in some human tumors, but their spectrum in different malignancies and their role in cancer development remain incompletely understood. Here, we describe the breadth of somatic and inherited mutations across the mitochondrial genome by sequence analyses of paired tumor and normal tissue samples from 226 individuals with five types of cancer using whole-genome data generated by The Cancer Genome Atlas Research Network. The frequencies of deleterious tumor-specific somatic mutations found in mtDNA varied across tumor types, ranging from 13% of glioblastomas to 63% of rectal adenocarcinomas. Compared with inherited mtDNA variants, somatic mtDNA mutations were enriched for nonsynonymous vs. synonymous changes (93 vs. 15; P < 2.2E-16) and were predicted to functionally impact the encoded protein. Somatic missense mutations in tumors were distributed uniformly among the mitochondrial protein genes, but 65% of somatic truncating mutations occurred in NADH dehydrogenase 5. Analysis of staging data in colon and rectal cancers revealed that the frequency of damaging mitochondrial mutations is the same in stages I and IV tumors. In summary, these data suggest that damaging somatic mtDNA mutations occur frequently (13-63%) in these five tumor types and likely confer a selective advantage in oncogenesis.

Landscape of somatic retrotransposition in human cancers

Transposable elements (TEs) are abundant in the human genome, and some are capable of generating new insertions through RNA intermediates. In cancer, the disruption of cellular mechanisms that normally suppress TE activity may facilitate mutagenic retrotranspositions. We performed single-nucleotide resolution analysis of TE insertions in 43 high-coverage whole-genome sequencing data sets from five cancer types. We identified 194 high-confidence somatic TE insertions, as well as thousands of polymorphic TE insertions in matched normal genomes. Somatic insertions were present in epithelial tumors but not in blood or brain cancers. Somatic L1 insertions tend to occur in genes that are commonly mutated in cancer, disrupt the expression of the target genes, and are biased toward regions of cancer-specific DNA hypomethylation, highlighting their potential impact in tumorigenesis.

Integrated analyses of microRNAs demonstrate their widespread influence on gene expression in high-grade serous ovarian carcinoma

BACKGROUND

The Cancer Genome Atlas (TCGA) Network recently comprehensively catalogued the molecular aberrations in 487 high-grade serous ovarian cancers, with much remaining to be elucidated regarding the microRNAs (miRNAs). Here, using TCGA ovarian data, we surveyed the miRNAs, in the context of their predicted gene targets.

METHODS AND RESULTS

Integration of miRNA and gene patterns yielded evidence that proximal pairs of miRNAs are processed from polycistronic primary transcripts, and that intronic miRNAs and their host gene mRNAs derive from common transcripts. Patterns of miRNA expression revealed multiple tumor subtypes and a set of 34 miRNAs predictive of overall patient survival. In a global analysis, miRNA:mRNA pairs anti-correlated in expression across tumors showed a higher frequency of in silico predicted target sites in the mRNA 3'-untranslated region (with less frequency observed for coding sequence and 5'-untranslated regions). The miR-29 family and predicted target genes were among the most strongly anti-correlated miRNA:mRNA pairs; over-expression of miR-29a in vitro repressed several anti-correlated genes (including DNMT3A and DNMT3B) and substantially decreased ovarian cancer cell viability.

CONCLUSIONS

This study establishes miRNAs as having a widespread impact on gene expression programs in ovarian cancer, further strengthening our understanding of miRNA biology as it applies to human cancer. As with gene transcripts, miRNAs exhibit high diversity reflecting the genomic heterogeneity within a clinically homogeneous disease population. Putative miRNA:mRNA interactions, as identified using integrative analysis, can be validated. TCGA data are a valuable resource for the identification of novel tumor suppressive miRNAs in ovarian as well as other cancers.

Identification of a CpG island methylator phenotype that defines a distinct subgroup of glioma

We have profiled promoter DNA methylation alterations in 272 glioblastoma tumors in the context of The Cancer Genome Atlas (TCGA). We found that a distinct subset of samples displays concerted hypermethylation at a large number of loci, indicating the existence of a glioma-CpG island methylator phenotype (G-CIMP). We validated G-CIMP in a set of non-TCGA glioblastomas and low-grade gliomas. G-CIMP tumors belong to the proneural subgroup, are more prevalent among lower-grade gliomas, display distinct copy-number alterations, and are tightly associated with IDH1 somatic mutations. Patients with G-CIMP tumors are younger at the time of diagnosis and experience significantly improved outcome. These findings identify G-CIMP as a distinct subset of human gliomas on molecular and clinical grounds.