Cancer therapy is challenged by the diversity of molecular implementations of oncogenic processes and by the resulting variation in therapeutic responses. Projects such as The Cancer Genome Atlas ...(TCGA) provide molecular tumor maps in unprecedented detail. The interpretation of these maps remains a major challenge. Here we distilled thousands of genetic and epigenetic features altered in cancers to ∼500 selected functional events (SFEs). Using this simplified description, we derived a hierarchical classification of 3,299 TCGA tumors from 12 cancer types. The top classes are dominated by either mutations (M class) or copy number changes (C class). This distinction is clearest at the extremes of genomic instability, indicating the presence of different oncogenic processes. The full hierarchy shows functional event patterns characteristic of multiple cross-tissue groups of tumors, termed oncogenic signature classes. Targetable functional events in a tumor class are suggestive of class-specific combination therapy. These results may assist in the definition of clinical trials to match actionable oncogenic signatures with personalized therapies.
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DOBA, IJS, IZUM, KILJ, NUK, PILJ, PNG, SAZU, UILJ, UKNU, UL, UM, UPUK
We present a novel method for the identification of sets of mutually exclusive gene alterations in a given set of genomic profiles. We scan the groups of genes with a common downstream effect on the ...signaling network, using a mutual exclusivity criterion that ensures that each gene in the group significantly contributes to the mutual exclusivity pattern. We test the method on all available TCGA cancer genomics datasets, and detect multiple previously unreported alterations that show significant mutual exclusivity and are likely to be driver events.
The cBioPortal for Cancer Genomics (http://cbioportal.org) provides a Web resource for exploring, visualizing, and analyzing multidimensional cancer genomics data. The portal reduces molecular ...profiling data from cancer tissues and cell lines into readily understandable genetic, epigenetic, gene expression, and proteomic events. The query interface combined with customized data storage enables researchers to interactively explore genetic alterations across samples, genes, and pathways and, when available in the underlying data, to link these to clinical outcomes. The portal provides graphical summaries of gene-level data from multiple platforms, network visualization and analysis, survival analysis, patient-centric queries, and software programmatic access. The intuitive Web interface of the portal makes complex cancer genomics profiles accessible to researchers and clinicians without requiring bioinformatics expertise, thus facilitating biological discoveries. Here, we provide a practical guide to the analysis and visualization features of the cBioPortal for Cancer Genomics.
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.
Somatic mutations in the RNase IIIb domain of DICER1 arise in cancer and disrupt the cleavage of 5' pre-miRNA arms. Here, we characterize an unstudied, recurrent, mutation (S1344L) in the DICER1 ...RNase IIIa domain in tumors from The Cancer Genome Atlas (TCGA) project and MSK-IMPACT profiling. RNase IIIa/b hotspots are absent from most cancers, but are notably enriched in uterine cancers. Systematic analysis of TCGA small RNA datasets show that DICER1 RNase IIIa-S1344L tumors deplete 5p-miRNAs, analogous to RNase IIIb hotspot samples. Structural and evolutionary coupling analyses reveal constrained proximity of RNase IIIa-S1344 to the RNase IIIb catalytic site, rationalizing why mutation of this site phenocopies known hotspot alterations. Finally, examination of DICER1 hotspot endometrial tumors reveals derepression of specific miRNA target signatures. In summary, comprehensive analyses of DICER1 somatic mutations and small RNA data reveal a mechanistic aspect of pre-miRNA processing that manifests in specific cancer settings.
In cancer genomics, recurrence of mutations in independent tumor samples is a strong indicator of functional impact. However, rare functional mutations can escape detection by recurrence analysis ...owing to lack of statistical power. We enhance statistical power by extending the notion of recurrence of mutations from single genes to gene families that share homologous protein domains. Domain mutation analysis also sharpens the functional interpretation of the impact of mutations, as domains more succinctly embody function than entire genes. By mapping mutations in 22 different tumor types to equivalent positions in multiple sequence alignments of domains, we confirm well-known functional mutation hotspots, identify uncharacterized rare variants in one gene that are equivalent to well-characterized mutations in another gene, detect previously unknown mutation hotspots, and provide hypotheses about molecular mechanisms and downstream effects of domain mutations. With the rapid expansion of cancer genomics projects, protein domain hotspot analysis will likely provide many more leads linking mutations in proteins to the cancer phenotype.
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•Comprehensive analysis of cancer mutations in protein domains (http://www.mutationaligner.org)•Identification of new mutation hotspots across homologous domains•Functional coupling of rare, uncharacterized mutations and known oncogenic mutations•Mechanistic clues about downstream effects of mutations in signaling domains
Using cancer genomics datasets from thousands of tumor samples in 22 tumor types, Miller et al. analyze somatic missense mutations in protein domains and discover new domain mutation hotspots. By associating mutations in infrequently altered genes with mutations in frequently altered paralogous genes that are known to contribute to cancer, this study provides many new clues to the functional role of rare mutations in cancer.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UILJ, UL, UM, UPCLJ, UPUK, ZAGLJ, ZRSKP
The Lauren diffuse type of gastric adenocarcinoma (DGA), as opposed to the intestinal type (IGA), often harbors mutations in RHOA, but little is known about the role of RhoA in DGA.
We examined RhoA ...activity and RhoA pathway inhibition in DGA cell lines and in two mouse xenograft models. RhoA activity was also assessed in patient tumor samples.
RhoA activity was higher in DGA compared with IGA cell lines and was further increased when grown as spheroids to enrich for cancer stem-like cells (CSCs) or when sorted using the gastric CSC marker CD44. RhoA shRNA or the RhoA inhibitor Rhosin decreased expression of the stem cell transcription factor, Sox2, and decreased spheroid formation by 78% to 81%. DGA spheroid cells had 3- to 5-fold greater migration and invasion than monolayer cells, and this activity was Rho-dependent. Diffuse GA spheroid cells were resistant in a cytotoxicity assay to 5-fluorouracil and cisplatin chemotherapy, and this resistance could be reversed with RhoA pathway inhibition. In two xenograft models, cisplatin inhibited tumor growth by 40% to 50%, RhoA inhibition by 32% to 60%, and the combination by 77% to 83%. In 288 patient tumors, increased RhoA activity correlated with worse overall survival in DGA patients (P = 0.017) but not in IGA patients (P = 0.612).
RhoA signaling promotes CSC phenotypes in DGA cells. Increased RhoA activity is correlated with worse overall survival in DGA patients, and RhoA inhibition can reverse chemotherapy resistance in DGA CSC and in tumor xenografts. Thus, the RhoA pathway is a promising new target in DGA patients.
Tumor metabolism is reorganized to support proliferation in the face of growth-related stress. Unlike the widespread profiling of changes to metabolic enzyme levels in cancer, comparatively less ...attention has been paid to the substrates/products of enzyme-catalyzed reactions, small-molecule metabolites. We developed an informatic pipeline to concurrently analyze metabolomics data from over 900 tissue samples spanning seven cancer types, revealing extensive heterogeneity in metabolic changes relative to normal tissue across cancers of different tissues of origin. Despite this heterogeneity, a number of metabolites were recurrently differentially abundant across many cancers, such as lactate and acyl-carnitine species. Through joint analysis of metabolomic data alongside clinical features of patient samples, we also identified a small number of metabolites, including several polyamines and kynurenine, which were associated with aggressive tumors across several tumor types. Our findings offer a glimpse onto common patterns of metabolic reprogramming across cancers, and the work serves as a large-scale resource accessible via a web application (http://www.sanderlab.org/pancanmet).
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•Computational pipeline to integrate cancer metabolomics data across studies•Free, open-source pipeline, data, and online visualization portal available•Recurrent patterns of differentially abundant metabolites across cancer types•Discovery of metabolites associated with aggressive disease across cancer types
Reznik et al. develop a computational approach for integrative analysis of metabolomics data and apply it to data from 900 tissue samples spanning seven different cancer types. They identify recurrent metabolic changes associated with tumor initiation and progression to aggressive disease.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UILJ, UL, UM, UPCLJ, UPUK, ZAGLJ, ZRSKP
PaxtoolsR package enables access to pathway data represented in the BioPAX format and made available through the Pathway Commons webservice for users of the R language to aid in advanced pathway ...analyses. Features include the extraction, merging and validation of pathway data represented in the BioPAX format. This package also provides novel pathway datasets and advanced querying features for R users through the Pathway Commons webservice allowing users to query, extract and retrieve data and integrate these data with local BioPAX datasets.
The PaxtoolsR package is compatible with versions of R 3.1.1 (and higher) on Windows, Mac OS X and Linux using Bioconductor 3.0 and is available through the Bioconductor R package repository along with source code and a tutorial vignette describing common tasks, such as data visualization and gene set enrichment analysis. Source code and documentation are at http://www.bioconductor.org/packages/paxtoolsr This plugin is free, open-source and licensed under the LGPL-3.
paxtools@cbio.mskcc.org or lunaa@cbio.mskcc.org.
Lauren diffuse-type gastric adenocarcinomas (DGAs) are generally genomically stable. We identified lysine (K)-specific methyltransferase 2C (
) as a frequently mutated gene and examined its role in ...DGA progression.
We performed whole exome sequencing on tumor samples of 27 patients with DGA who underwent gastrectomy. Lysine (K)-specific methyltransferase 2C (
) was analyzed in DGA cell lines and in patient tumors.
was the most frequently mutated gene (11 of 27 tumors 41%). KMT2C expression by immunohistochemistry in tumors from 135 patients with DGA undergoing gastrectomy inversely correlated with more advanced tumor stage (
= 0.023) and worse overall survival (
= 0.017). KMT2C shRNA knockdown in non-transformed HFE-145 gastric epithelial cells promoted epithelial-to-mesenchymal transition (EMT) as demonstrated by increased expression of EMT-related proteins N-cadherin and Slug. Migration and invasion in gastric epithelial cells following KMT2C knockdown increased by 47- to 88-fold. In the DGA cell lines MKN-45 and SNU-668, which have lost KMT2C expression, KMT2C re-expression decreased expression of EMT-related proteins, reduced cell migration by 52% to 60%, and reduced cell invasion by 50% to 74%. Flank xenografts derived from KMT2C-expressing DGA organoids, compared with wild-type organoids, grew more slowly and lost their infiltrative leading edge. EMT can lead to the acquisition of cancer stem cell (CSC) phenotypes. KMT2C re-expression in DGA cell lines reduced spheroid formation by 77% to 78% and reversed CSC resistance to chemotherapy via promotion of DNA damage and apoptosis.
is frequently mutated in certain populations with DGA. KMT2C loss in DGA promotes EMT and is associated with worse overall survival.
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