G(alpha)11 signaling through ARF6 regulates F-actin mobilization and GLUT4 glucose transporter translocation to the plasma membrane

The action of insulin to recruit the intracellular GLUT4 glucose transporter to the plasma membrane of 3T3-L1 adipocytes is mimicked by endothelin 1, which signals through trimeric G(alpha)q or G(alpha)11 proteins. Here we report that murine G(alpha)11 is most abundant in fat and that expression of the constitutively active form of G(alpha)11 [G(alpha)11(Q209L)] in 3T3-L1 adipocytes causes recruitment of GLUT4 to the plasma membrane and stimulation of 2-deoxyglucose uptake. In contrast to the action of insulin on GLUT4, the effects of endothelin 1 and G(alpha)11 were not inhibited by the phosphatidylinositol 3-kinase inhibitor wortmannin at 100 nM. Signaling by insulin, endothelin 1, or G(alpha)11(Q209L) also mobilized cortical F-actin in cultured adipocytes. Importantly, GLUT4 translocation caused by all three agents was blocked upon disassembly of F-actin by latrunculin B, suggesting that the F-actin polymerization caused by these agents may be required for their effects on GLUT4. Remarkably, expression of a dominant inhibitory form of the actin-regulatory GTPase ARF6 [ARF6(T27N)] in cultured adipocytes selectively inhibited both F-actin formation and GLUT4 translocation in response to endothelin 1 but not insulin. These data indicate that ARF6 is a required downstream element in endothelin 1 signaling through G(alpha)11 to regulate cortical actin and GLUT4 translocation in cultured adipocytes, while insulin action involves different signaling pathways

Genome-scale analysis identifies paralog lethality as a vulnerability of chromosome 1p loss in cancer.

Functional redundancy shared by paralog genes may afford protection against genetic perturbations, but it can also result in genetic vulnerabilities due to mutual interdependency1-5. Here, we surveyed genome-scale short hairpin RNA and CRISPR screening data on hundreds of cancer cell lines and identified MAGOH and MAGOHB, core members of the splicing-dependent exon junction complex, as top-ranked paralog dependencies6-8. MAGOHB is the top gene dependency in cells with hemizygous MAGOH deletion, a pervasive genetic event that frequently occurs due to chromosome 1p loss. Inhibition of MAGOHB in a MAGOH-deleted context compromises viability by globally perturbing alternative splicing and RNA surveillance. Dependency on IPO13, an importin-β receptor that mediates nuclear import of the MAGOH/B-Y14 heterodimer9, is highly correlated with dependency on both MAGOH and MAGOHB. Both MAGOHB and IPO13 represent dependencies in murine xenografts with hemizygous MAGOH deletion. Our results identify MAGOH and MAGOHB as reciprocal paralog dependencies across cancer types and suggest a rationale for targeting the MAGOHB-IPO13 axis in cancers with chromosome 1p deletion

Identification of focally amplified lineage-specific super-enhancers in human epithelial cancers

Whole genome analysis approaches are revealing recurrent cancer-associated somatic alterations in non-coding DNA regions. We combined somatic copy number analysis of 12 tumor types with tissue-specific epigenetic profiling to identify significant regions of focal amplification harboring super-enhancers. Copy-number gains of non-coding regions harboring super-enhancers near KLF5, USP12, PARD6B and MYC are associated with over-expression of these cancer-related genes. We show that two distinct focal amplifications of super-enhancers 3′ to MYC in lung adenocarcinoma (MYC-LASE) and endometrial carcinoma (MYC-ECSE), are physically associated with the MYC promoter and correlate with MYC over-expression. CRISPR/Cas9-mediated repression or deletion of a constituent enhancer within the MYC-LASE region led to significant reductions in the expression of MYC and its target genes, and to the impairment of anchorage-independent and clonogenic growth, consistent with an oncogenic function. Our results demonstrate that genomic amplification of super-enhancers represents a common mechanism to activate cancer driver genes in multiple cancer types

The Integrated Genomic Landscape of Thymic Epithelial Tumors

Thymic epithelial tumors (TETs) are one of the rarest adult malignancies. Among TETs, thymoma is the most predominant, characterized by a unique association with autoimmune diseases, followed by thymic carcinoma, which is less common but more clinically aggressive. Using multi-platform omics analyses on 117 TETs, we define four subtypes of these tumors defined by genomic hallmarks and an association with survival and World Health Organization histological subtype. We further demonstrate a marked prevalence of a thymoma-specific mutated oncogene, GTF2I, and explore its biological effects on multi-platform analysis. We further observe enrichment of mutations in HRAS, NRAS, and TP53. Last, we identify a molecular link between thymoma and the autoimmune disease myasthenia gravis, characterized by tumoral overexpression of muscle autoantigens, and increased aneuploidy

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

Machine Learning Detects Pan-cancer Ras Pathway Activation in The Cancer Genome Atlas.

Precision oncology uses genomic evidence to match patients with treatment but often fails to identify all patients who may respond. The transcriptome of these "hidden responders" may reveal responsive molecular states. We describe and evaluate a machine-learning approach to classify aberrant pathway activity in tumors, which may aid in hidden responder identification. The algorithm integrates RNA-seq, copy number, and mutations from 33 different cancer types across The Cancer Genome Atlas (TCGA) PanCanAtlas project to predict aberrant molecular states in tumors. Applied to the Ras pathway, the method detects Ras activation across cancer types and identifies phenocopying variants. The model, trained on human tumors, can predict response to MEK inhibitors in wild-type Ras cell lines. We also present data that suggest that multiple hits in the Ras pathway confer increased Ras activity. The transcriptome is underused in precision oncology and, combined with machine learning, can aid in the identification of hidden responders

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