Showing papers by "Chris Sander published in 2012"

The cBio Cancer Genomics Portal: An Open Platform for Exploring Multidimensional Cancer Genomics Data

Abstract: The cBio Cancer Genomics Portal (http://cbioportal.org) is an open-access resource for interactive exploration of multidimensional cancer genomics data sets, currently providing access to data from more than 5,000 tumor samples from 20 cancer studies. The cBio Cancer Genomics Portal significantly lowers the barriers between complex genomic data and cancer researchers who want rapid, intuitive, and high-quality access to molecular profiles and clinical attributes from large-scale cancer genomics projects and empowers researchers to translate these rich data sets into biologic insights and clinical applications.

Comprehensive molecular portraits of human breast tumours

Abstract: We analysed primary breast cancers by genomic DNA copy number arrays, DNA methylation, exome sequencing, messenger RNA arrays, microRNA sequencing and reverse-phase protein arrays. Our ability to integrate information across platforms provided key insights into previously defined gene expression subtypes and demonstrated the existence of four main breast cancer classes when combining data from five platforms, each of which shows significant molecular heterogeneity. Somatic mutations in only three genes (TP53, PIK3CA and GATA3) occurred at >10% incidence across all breast cancers; however, there were numerous subtype-associated and novel gene mutations including the enrichment of specific mutations in GATA3, PIK3CA and MAP3K1 with the luminal A subtype. We identified two novel protein-expression-defined subgroups, possibly produced by stromal/microenvironmental elements, and integrated analyses identified specific signalling pathways dominant in each molecular subtype including a HER2/phosphorylated HER2/EGFR/phosphorylated EGFR signature within the HER2-enriched expression subtype. Comparison of basal-like breast tumours with high-grade serous ovarian tumours showed many molecular commonalities, indicating a related aetiology and similar therapeutic opportunities. The biological finding of the four main breast cancer subtypes caused by different subsets of genetic and epigenetic abnormalities raises the hypothesis that much of the clinically observable plasticity and heterogeneity occurs within, and not across, these major biological subtypes of breast cancer.

Comprehensive molecular characterization of human colon and rectal cancer

Abstract: To characterize somatic alterations in colorectal carcinoma, we conducted a genome-scale analysis of 276 samples, analysing exome sequence, DNA copy number, promoter methylation and messenger RNA and microRNA expression. A subset of these samples (97) underwent low-depth-of-coverage whole-genome sequencing. In total, 16% of colorectal carcinomas were found to be hypermutated: three-quarters of these had the expected high microsatellite instability, usually with hypermethylation and MLH1 silencing, and one-quarter had somatic mismatch-repair gene and polymerase e (POLE) mutations. Excluding the hypermutated cancers, colon and rectum cancers were found to have considerably similar patterns of genomic alteration. Twenty-four genes were significantly mutated, and in addition to the expected APC, TP53, SMAD4, PIK3CA and KRAS mutations, we found frequent mutations in ARID1A, SOX9 and FAM123B. Recurrent copy-number alterations include potentially drug-targetable amplifications of ERBB2 and newly discovered amplification of IGF2. Recurrent chromosomal translocations include the fusion of NAV2 and WNT pathway member TCF7L1. Integrative analyses suggest new markers for aggressive colorectal carcinoma and an important role for MYC-directed transcriptional activation and repression.

Comprehensive genomic characterization of squamous cell lung cancers

Abstract: Lung squamous cell carcinoma is a common type of lung cancer, causing approximately 400,000 deaths per year worldwide. Genomic alterations in squamous cell lung cancers have not been comprehensively characterized, and no molecularly targeted agents have been specifically developed for its treatment. As part of The Cancer Genome Atlas, here we profile 178 lung squamous cell carcinomas to provide a comprehensive landscape of genomic and epigenomic alterations. We show that the tumour type is characterized by complex genomic alterations, with a mean of 360 exonic mutations, 165 genomic rearrangements, and 323 segments of copy number alteration per tumour. We find statistically recurrent mutations in 11 genes, including mutation of TP53 in nearly all specimens. Previously unreported loss-of-function mutations are seen in the HLA-A class I major histocompatibility gene. Significantly altered pathways included NFE2L2 and KEAP1 in 34%, squamous differentiation genes in 44%, phosphatidylinositol-3-OH kinase pathway genes in 47%, and CDKN2A and RB1 in 72% of tumours. We identified a potential therapeutic target in most tumours, offering new avenues of investigation for the treatment of squamous cell lung cancers.

Mutual exclusivity analysis identifies oncogenic network modules

Abstract: Although individual tumors of the same clinical type have surprisingly diverse genomic alterations, these events tend to occur in a limited number of pathways, and alterations that affect the same pathway tend to not co-occur in the same patient. While pathway analysis has been a powerful tool in cancer genomics, our knowledge of oncogenic pathway modules is incomplete. To systematically identify such modules, we have developed a novel method, Mutual Exclusivity Modules in cancer (MEMo). The method uses correlation analysis and statistical tests to identify network modules by three criteria: (1) Member genes are recurrently altered across a set of tumor samples; (2) member genes are known to or are likely to participate in the same biological process; and (3) alteration events within the modules are mutually exclusive. Applied to data from the Cancer Genome Atlas (TCGA), the method identifies the principal known altered modules in glioblastoma (GBM) and highlights the striking mutual exclusivity of genomic alterations in the PI(3)K, p53, and Rb pathways. In serous ovarian cancer, we make the novel observation that inactivation of BRCA1 and BRCA2 is mutually exclusive of amplification of CCNE1 and inactivation of RB1, suggesting distinct alternative causes of genomic instability in this cancer type; and, we identify RBBP8 as a candidate oncogene involved in Rb-mediated cell cycle control. When applied to any cancer genomics data set, the algorithm can nominate oncogenic alterations that have a particularly strong selective effect and may also be useful in the design of therapeutic combinations in cases where mutual exclusivity reflects synthetic lethality.

Genome Sequencing Identifies a Basis for Everolimus Sensitivity

Abstract: Cancer drugs often induce dramatic responses in a small minority of patients. We used whole-genome sequencing to investigate the genetic basis of a durable remission of metastatic bladder cancer in a patient treated with everolimus, a drug that inhibits the mTOR (mammalian target of rapamycin) signaling pathway. Among the somatic mutations was a loss-of-function mutation in TSC1 (tuberous sclerosis complex 1), a regulator of mTOR pathway activation. Targeted sequencing revealed TSC1 mutations in about 8% of 109 additional bladder cancers examined, and TSC1 mutation correlated with everolimus sensitivity. These results demonstrate the feasibility of using whole-genome sequencing in the clinical setting to identify previously occult biomarkers of drug sensitivity that can aid in the identification of patients most likely to respond to targeted anticancer drugs.

Protein structure prediction from sequence variation

Abstract: Genomic sequences contain rich evolutionary information about functional constraints on macromolecules such as proteins. This information can be efficiently mined to detect evolutionary couplings between residues in proteins and address the long-standing challenge to compute protein three-dimensional structures from amino acid sequences. Substantial progress has recently been made on this problem owing to the explosive growth in available sequences and the application of global statistical methods. In addition to three-dimensional structure, the improved understanding of covariation may help identify functional residues involved in ligand binding, protein-complex formation and conformational changes. We expect computation of covariation patterns to complement experimental structural biology in elucidating the full spectrum of protein structures, their functional interactions and evolutionary dynamics.

Integrative subtype discovery in glioblastoma using iCluster.

Abstract: Large-scale cancer genome projects, such as the Cancer Genome Atlas (TCGA) project, are comprehensive molecular characterization efforts to accelerate our understanding of cancer biology and the discovery of new therapeutic targets. The accumulating wealth of multidimensional data provides a new paradigm for important research problems including cancer subtype discovery. The current standard approach relies on separate clustering analyses followed by manual integration. Results can be highly data type dependent, restricting the ability to discover new insights from multidimensional data. In this study, we present an integrative subtype analysis of the TCGA glioblastoma (GBM) data set. Our analysis revealed new insights through integrated subtype characterization. We found three distinct integrated tumor subtypes. Subtype 1 lacks the classical GBM events of chr 7 gain and chr 10 loss. This subclass is enriched for the G-CIMP phenotype and shows hypermethylation of genes involved in brain development and neuronal differentiation. The tumors in this subclass display a Proneural expression profile. Subtype 2 is characterized by a near complete association with EGFR amplification, overrepresentation of promoter methylation of homeobox and G-protein signaling genes, and a Classical expression profile. Subtype 3 is characterized by NF1 and PTEN alterations and exhibits a Mesenchymal-like expression profile. The data analysis workflow we propose provides a unified and computationally scalable framework to harness the full potential of large-scale integrated cancer genomic data for integrative subtype discovery.

Distinct Patterns of Dysregulated Expression of Enzymes Involved in Androgen Synthesis and Metabolism in Metastatic Prostate Cancer Tumors

Abstract: Androgen receptor (AR) signaling persists in castration-resistant prostate carcinomas (CRPCs), due to several mechanisms that include increased AR expression and intratumoral androgen metabolism. We investigated the mechanisms underlying aberrant expression of transcripts involved in androgen metabolism in CRPC. We compared gene expression profiles and DNA copy number alteration (CNA) data from 29 normal prostate tissue samples, 127 primary prostate carcinomas (PCas) and 19 metastatic PCas. Steroidogenic enzyme transcripts were evaluated by qRT-PCR in PCa cell lines and circulating tumor cells (CTCs) from CRPC patients. Metastatic PCas expressed higher transcript levels for AR and several steroidogenic enzymes, including SRD5A1, SRD5A3, and AKR1C3, while expression of SRD5A2, CYP3A4, CYP3A5 and CYP3A7 was decreased. This aberrant expression was rarely associated with CNAs. Instead, our data suggest distinct patterns of coordinated aberrant enzyme expression. Inhibition of AR activity by itself stimulated AKR1C3 expression. The aberrant expression of the steroidogenic enzyme transcripts were detected in CTCs from CRPC patients. In conclusion, our findings identify substantial interpatient heterogeneity and distinct patterns of dysregulated expression of enzymes involved in intratumoral androgen metabolism in PCa. These steroidogenic enzymes represent targets for complete suppression of systemic and intratumoral androgen levels, an objective that is supported by the clinical efficacy of the CYP17 inhibitor abiraterone. A comprehensive AR axis targeting approach via simultaneous, frontline enzymatic blockade and/or transcriptional repression of several steroidogenic enzymes, in combination with GnRH analogs and potent anti-androgens, would represent a powerful future strategy for PCa management.

miR-34a repression in proneural malignant gliomas upregulates expression of its target PDGFRA and promotes tumorigenesis.

Abstract: Glioblastoma (GBM) and other malignant gliomas are aggressive primary neoplasms of the brain that exhibit notable refractivity to standard treatment regimens. Recent large-scale molecular profiling has revealed distinct disease subclasses within malignant gliomas whose defining genomic features highlight dysregulated molecular networks as potential targets for therapeutic development. The “proneural” designation represents the largest and most heterogeneous of these subclasses, and includes both a large fraction of GBMs along with most of their lower-grade astrocytic and oligodendroglial counterparts. The pathogenesis of proneural gliomas has been repeatedly associated with dysregulated PDGF signaling. Nevertheless, genomic amplification or activating mutations involving the PDGF receptor (PDGFRA) characterize only a subset of proneural GBMs, while the mechanisms driving dysregulated PDGF signaling and downstream oncogenic networks in remaining tumors are unclear. MicroRNAs (miRNAs) are a class of small, noncoding RNAs that regulate gene expression by binding loosely complimentary sequences in target mRNAs. The role of miRNA biology in numerous cancer variants is well established. In an analysis of miRNA involvement in the phenotypic expression and regulation of oncogenic PDGF signaling, we found that miR-34a is downregulated by PDGF pathway activation in vitro. Similarly, analysis of data from the Cancer Genome Atlas (TCGA) revealed that miR-34a expression is significantly lower in proneural gliomas compared to other tumor subtypes. Using primary GBM cells maintained under neurosphere conditions, we then demonstrated that miR-34a specifically affects growth of proneural glioma cells in vitro and in vivo. Further bioinformatic analysis identified PDGFRA as a direct target of miR-34a and this interaction was experimentally validated. Finally, we found that PDGF-driven miR-34a repression is unlikely to operate solely through a p53-dependent mechanism. Taken together, our data support the existence of reciprocal negative feedback regulation involving miR-34 and PDGFRA expression in proneural gliomas and, as such, identify a subtype specific therapeutic potential for miR-34a.

Integrated Analyses of microRNAs Demonstrate Their Widespread Influence on Gene Expression in High-Grade Serous Ovarian Carcinoma

Abstract: 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 39-untranslated region (with less frequency observed for coding sequence and 59-untranslated regions). The miR-29 family and predicted target genes were among the most strongly anticorrelated 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.

Genomic Complexity and AKT Dependence in Serous Ovarian Cancer

Abstract: Effective oncoprotein-targeted therapies have not yet been developed for ovarian cancer. To explore the role of phosphatidylinositol 3-kinase (PI3K)/AKT signaling in this disease, we performed a genetic and functional analysis of ovarian cancer cell lines and tumors. PI3K pathway alterations were common in both, but the spectrum of mutational changes differed. Genetic activation of the pathway was necessary, but not sufficient, to confer sensitivity to selective inhibition of AKT and cells with RAS pathway alterations or RB1 loss were resistant to AKT inhibition, whether or not they had coexistent PI3K/AKT pathway activation. Inhibition of AKT1 caused growth arrest in a subset of ovarian cell lines, but not in those with AKT3 expression, which required pan-AKT inhibition. Thus, a subset of ovarian tumors is sensitive to AKT inhibition, but the genetic heterogeneity of the disease suggests that effective treatment with AKT pathway inhibitors will require a detailed molecular analysis of each patient's tumor. Significance: A subset of ovarian cancers exhibits AKT pathway activation and is sensitive to selective AKT inhibition. Ovarian tumors exhibit significant genetic heterogeneity and thus an individualized approach based on real-time, detailed genomic and proteomic characterization of individual tumors will be required for the successful application of PI3K/AKT pathway inhibitors in this disease. Cancer Discovery; 2(1) ; 56–67. ©2011 AACR . Read the Commentary on this article by Bast and Mills, [p. 16][1] This article is highlighted in the In This Issue feature, [p. 1][2] [1]: /lookup/volpage/2/16?iss=1 [2]: /lookup/volpage/2/1?iss=1

Search for heavy neutrinos and WR bosons with right-handed couplings in a left-right symmetric model in pp collisions at √s=7 TeV

Abstract: Results are presented from a search for heavy, right-handed muon neutrinos, Nμ, and right-handed WR bosons, which arise in the left-right symmetric extensions of the standard model. The analysis is based on a 5.0 fb-1 sample of proton-proton collisions at a center-of-mass energy of 7 TeV, collected by the CMS detector at the Large Hadron Collider. No evidence is observed for an excess of events over the standard model expectation. For models with exact left-right symmetry, heavy right-handed neutrinos are excluded at 95% confidence level for a range of neutrino masses below the WR mass, dependent on the value of MWR. The excluded region in the two-dimensional (MWR, MNμ) mass plane extends to MWR=2.5 TeV.

Primary cutaneous B-cell lymphomas.

Abstract: Cutaneous B-cell lymphomas (CBCL) are the second most common form of primary cutaneous lymphomas. The cutaneous follicle center lymphoma and the cutaneous marginal zone lymphoma (extranodal MALT type lymphoma) account for the vast majority of CBCL and manifest with nodules. These two lymphoma entities have an indolent, slowly progressive course and an excellent prognosis despite a high rate of recurrences. In contrast, cutaneous diffuse large B-cell lymphoma, leg type, and other rare forms of CBCL display an impaired prognosis and therefore require to be treated with multiagent chemotherapy and anti-CD20 monoclonal antibodies in most cases. Clinico-pathologic correlation, histology with immunohistochemical profile and genotyping as well as staging examinations are crucial diagnostic elements in the work-up of CBCL.

Defining the genetic basis of everolimus sensitivity in metastatic bladder cancer (MBC) by whole-genome sequencing (WGS).

Abstract: 4527 Background: MBC is rarely cured with standard chemotherapy and novel agents are clearly needed. A phase II trial of everolimus in MBC resulted in 1 near-complete response (CR), 1 partial respo...

Abstract B15: Repression of PDGFRA-targeting miR-34a promotes tumorigenesis in proneural malignant gliomas

Abstract: Malignant gliomas - particularly glioblastoma (GBM) - continue to cause a disproportionate degree of morbidity and mortality within human oncology. Recent integrated genomics has demonstrated biologically distinct subclasses within malignant glioma that transcend conventional histopathological boundaries. Perhaps the broadest of these subclassess has been termed “proneural” and includes both a large fraction of GBMs along with most of their lower-grade astrocytic and oligodendroglial counterparts. The pathogenesis of proneural gliomas has been strongly linked to dysregulated PDGF signaling; but although genomic amplification or activating mutations involving the PDGF receptor (PDGFRA) characterize a significant subset of proneural GBMs, the mechanisms driving dysregulated PDGF signaling and downstream oncogenic networks in non-amplified/mutated tumors remain unclear. MicroRNAs (miRNAs) are a class of small, noncoding RNAs that regulate gene expression on a pre-translational level by binding loosely to complimentary sequences in target mRNAs. The role of miRNA biology in numerous cancer variants is well established. In an analysis of miRNA involvement in the phenotypic expression and regulation of oncogenic PDGF signaling, we found that expression of miR-34a is responsive to PDGF pathway activation in vitro. Similarly, analysis of data from the Cancer Genome Atlas (TCGA) revealed that expression of miR-34a is highly negatively correlated in proneural gliomas and in gliomas harboring amplified PDGFRA compared to other tumor subtypes. Using primary GBM cells maintained under neurosphere conditions, we then demonstrated that miR-34a specifically affects growth of proneural GBM cells in vitro and in vivo. Using data from TCGA, we identified PDGFRA as a direct target of miR-34a and validated this interaction experimentally. Finally, we provided evidence for a p53-independent mechanism mediated by PDGF signaling for negative regulation of miR-34a in proneural tumors. Taken together, our data suggest reciprocal negative feedback regulation of miR-34 and PDGFRA expression in proneural gliomas and, as such, identify a subtype specific therapeutic potential for miR-34a. Citation Format: Joachim Silber, Anders Jacobsen, Tatsuya Ozawa, Girish Harinath, Eric C. Holland, Chris Sander, Jason T. Huse. Repression of PDGFRA-targeting miR-34a promotes tumorigenesis in proneural malignant gliomas [abstract]. In: Proceedings of the AACR Special Conference on Noncoding RNAs and Cancer; 2012 Jan 8-11; Miami Beach, FL. Philadelphia (PA): AACR; Cancer Res 2012;72(2 Suppl):Abstract nr B15.