A multi-gene signature predicts outcome in patients with pancreatic ductal adenocarcinoma.

© 2014 Haider et al.; licensee BioMed Central. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly credited. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.Improved usage of the repertoires of pancreatic ductal adenocarcinoma (PDAC) profiles is crucially needed to guide the development of predictive and prognostic tools that could inform the selection of treatment options

Deconstruction of a Metastatic Tumor Microenvironment Reveals a Common Matrix Response in Human Cancers.

We have profiled, for the first time, an evolving human metastatic microenvironment by measuring gene expression, matrisome proteomics, cytokine and chemokine levels, cellularity, extracellular matrix organization, and biomechanical properties, all on the same sample. Using biopsies of high-grade serous ovarian cancer metastases that ranged from minimal to extensive disease, we show how nonmalignant cell densities and cytokine networks evolve with disease progression. Multivariate integration of the different components allowed us to define, for the first time, gene and protein profiles that predict extent of disease and tissue stiffness, while also revealing the complexity and dynamic nature of matrisome remodeling during development of metastases. Although we studied a single metastatic site from one human malignancy, a pattern of expression of 22 matrisome genes distinguished patients with a shorter overall survival in ovarian and 12 other primary solid cancers, suggesting that there may be a common matrix response to human cancer.Significance: Conducting multilevel analysis with data integration on biopsies with a range of disease involvement identifies important features of the evolving tumor microenvironment. The data suggest that despite the large spectrum of genomic alterations, some human malignancies may have a common and potentially targetable matrix response that influences the course of disease. Cancer Discov; 8(3); 304-19. ©2017 AACR.This article is highlighted in the In This Issue feature, p. 253

Exploring genetic associations with ceRNA regulation in the human genome

Abstract Competing endogenous RNAs (ceRNAs) are RNA molecules that sequester shared microRNAs (miRNAs) thereby affecting the expression of other targets of the miRNAs. Whether genetic variants in ceRNA can affect its biological function and disease development is still an open question. Here we identified a large number of genetic variants that are associated with ceRNA's function using Geuvaids RNA-seq data for 462 individuals from the 1000 Genomes Project. We call these loci competing endogenous RNA expression quantitative trait loci or ‘cerQTL’, and found that a large number of them were unexplored in conventional eQTL mapping. We identified many cerQTLs that have undergone recent positive selection in different human populations, and showed that single nucleotide polymorphisms in gene 3΄UTRs at the miRNA seed binding regions can simultaneously regulate gene expression changes in both cis and trans by the ceRNA mechanism. We also discovered that cerQTLs are significantly enriched in traits/diseases associated variants reported from genome-wide association studies in the miRNA binding sites, suggesting that disease susceptibilities could be attributed to ceRNA regulation. Further in vitro functional experiments demonstrated that a cerQTL rs11540855 can regulate ceRNA function. These results provide a comprehensive catalog of functional non-coding regulatory variants that may be responsible for ceRNA crosstalk at the post-transcriptional level

An Integrated TCGA Pan-Cancer Clinical Data Resource to Drive High-Quality Survival Outcome Analytics

For a decade, The Cancer Genome Atlas (TCGA) program collected clinicopathologic annotation data along with multi-platform molecular profiles of more than 11,000 human tumors across 33 different cancer types. TCGA clinical data contain key features representing the democratized nature of the data collection process. To ensure proper use of this large clinical dataset associated with genomic features, we developed a standardized dataset named the TCGA Pan-Cancer Clinical Data Resource (TCGA-CDR), which includes four major clinical outcome endpoints. In addition to detailing major challenges and statistical limitations encountered during the effort of integrating the acquired clinical data, we present a summary that includes endpoint usage recommendations for each cancer type. These TCGA-CDR findings appear to be consistent with cancer genomics studies independent of the TCGA effort and provide opportunities for investigating cancer biology using clinical correlates at an unprecedented scale. Analysis of clinicopathologic annotations for over 11,000 cancer patients in the TCGA program leads to the generation of TCGA Clinical Data Resource, which provides recommendations of clinical outcome endpoint usage for 33 cancer types

Pan-Cancer Analysis of lncRNA Regulation Supports Their Targeting of Cancer Genes in Each Tumor Context

Long noncoding RNAs (lncRNAs) are commonly dys-regulated in tumors, but only a handful are known toplay pathophysiological roles in cancer. We inferredlncRNAs that dysregulate cancer pathways, onco-genes, and tumor suppressors (cancer genes) bymodeling their effects on the activity of transcriptionfactors, RNA-binding proteins, and microRNAs in5,185 TCGA tumors and 1,019 ENCODE assays.Our predictions included hundreds of candidateonco- and tumor-suppressor lncRNAs (cancerlncRNAs) whose somatic alterations account for thedysregulation of dozens of cancer genes and path-ways in each of 14 tumor contexts. To demonstrateproof of concept, we showed that perturbations tar-geting OIP5-AS1 (an inferred tumor suppressor) andTUG1 and WT1-AS (inferred onco-lncRNAs) dysre-gulated cancer genes and altered proliferation ofbreast and gynecologic cancer cells. Our analysis in-dicates that, although most lncRNAs are dysregu-lated in a tumor-specific manner, some, includingOIP5-AS1, TUG1, NEAT1, MEG3, and TSIX, synergis-tically dysregulate cancer pathways in multiple tumorcontexts

Pan-cancer Alterations of the MYC Oncogene and Its Proximal Network across the Cancer Genome Atlas

Although theMYConcogene has been implicated incancer, a systematic assessment of alterations ofMYC, related transcription factors, and co-regulatoryproteins, forming the proximal MYC network (PMN),across human cancers is lacking. Using computa-tional approaches, we define genomic and proteo-mic features associated with MYC and the PMNacross the 33 cancers of The Cancer Genome Atlas.Pan-cancer, 28% of all samples had at least one ofthe MYC paralogs amplified. In contrast, the MYCantagonists MGA and MNT were the most frequentlymutated or deleted members, proposing a roleas tumor suppressors.MYCalterations were mutu-ally exclusive withPIK3CA,PTEN,APC,orBRAFalterations, suggesting that MYC is a distinct onco-genic driver. Expression analysis revealed MYC-associated pathways in tumor subtypes, such asimmune response and growth factor signaling; chro-matin, translation, and DNA replication/repair wereconserved pan-cancer. This analysis reveals insightsinto MYC biology and is a reference for biomarkersand therapeutics for cancers with alterations ofMYC or the PMN

Genomic, Pathway Network, and Immunologic Features Distinguishing Squamous Carcinomas

This integrated, multiplatform PanCancer Atlas study co-mapped and identified distinguishing molecular features of squamous cell carcinomas (SCCs) from five sites associated with smokin

Spatial Organization and Molecular Correlation of Tumor-Infiltrating Lymphocytes Using Deep Learning on Pathology Images

Beyond sample curation and basic pathologic characterization, the digitized H&E-stained images of TCGA samples remain underutilized. To highlight this resource, we present mappings of tumorinfiltrating lymphocytes (TILs) based on H&E images from 13 TCGA tumor types. These TIL maps are derived through computational staining using a convolutional neural network trained to classify patches of images. Affinity propagation revealed local spatial structure in TIL patterns and correlation with overall survival. TIL map structural patterns were grouped using standard histopathological parameters. These patterns are enriched in particular T cell subpopulations derived from molecular measures. TIL densities and spatial structure were differentially enriched among tumor types, immune subtypes, and tumor molecular subtypes, implying that spatial infiltrate state could reflect particular tumor cell aberration states. Obtaining spatial lymphocytic patterns linked to the rich genomic characterization of TCGA samples demonstrates one use for the TCGA image archives with insights into the tumor-immune microenvironment

Fatty acid synthase mediates EGFR palmitoylation in EGFR mutated non‐small cell lung cancer

Abstract Metabolic reprogramming is widely known as a hallmark of cancer cells to allow adaptation of cells to sustain survival signals. In this report, we describe a novel oncogenic signaling pathway exclusively acting in mutated epidermal growth factor receptor (EGFR) non‐small cell lung cancer (NSCLC) with acquired tyrosine kinase inhibitor (TKI) resistance. Mutated EGFR mediates TKI resistance through regulation of the fatty acid synthase (FASN), which produces 16‐C saturated fatty acid palmitate. Our work shows that the persistent signaling by mutated EGFR in TKI‐resistant tumor cells relies on EGFR palmitoylation and can be targeted by Orlistat, an FDA‐approved anti‐obesity drug. Inhibition of FASN with Orlistat induces EGFR ubiquitination and abrogates EGFR mutant signaling, and reduces tumor growths both in culture systems and in vivo. Together, our data provide compelling evidence on the functional interrelationship between mutated EGFR and FASN and that the fatty acid metabolism pathway is a candidate target for acquired TKI‐resistant EGFR mutant NSCLC patients

A role for a neo-sex chromosome in stickleback speciation.

Sexual antagonism, or conflict between the sexes, has been proposed as a driving force in both sex-chromosome turnover and speciation. Although closely related species often have different sex-chromosome systems, it is unknown whether sex-chromosome turnover contributes to the evolution of reproductive isolation between species. Here we show that a newly evolved sex chromosome contains genes that contribute to speciation in threespine stickleback fish (Gasterosteus aculeatus). We first identified a neo-sex chromosome system found only in one member of a sympatric species pair in Japan. We then performed genetic linkage mapping of male-specific traits important for reproductive isolation between the Japanese species pair. The neo-X chromosome contains loci for male courtship display traits that contribute to behavioural isolation, whereas the ancestral X chromosome contains loci for both behavioural isolation and hybrid male sterility. Our work not only provides strong evidence for a large X-effect on reproductive isolation in a vertebrate system, but also provides direct evidence that a young neo-X chromosome contributes to reproductive isolation between closely related species. Our data indicate that sex-chromosome turnover might have a greater role in speciation than was previously appreciated