The molecular mechanisms underlying angioimmunoblastic T cell lymphoma (AITL), a common type of mature T cell lymphoma of poor prognosis, are largely unknown. Here we report a frequent somatic mutation in RHOA (encoding p.Gly17Val) using exome and transcriptome sequencing of samples from individuals with AITL. Further examination of the RHOA mutation encoding p.Gly17Val in 239 lymphoma samples showed that the mutation was specific to T cell lymphoma and was absent from B cell lymphoma. We demonstrate that the RHOA mutation encoding p.Gly17Val, which was found in 53.3% (24 of 45) of the AITL cases examined, is oncogenic in nature using multiple molecular assays. Molecular modeling and docking simulations provided a structural basis for the loss of GTPase activity in the RHOA Gly17Val mutant. Our experimental data and modeling results suggest that the RHOA mutation encoding p.Gly17Val is a driver mutation in AITL. On the basis of these data and through integrated pathway analysis, we build a comprehensive signaling network for AITL oncogenesis.

MicroRNAs (miRNAs) regulate cardiovascular biology and disease, but the role of flow-sensitive microRNAs in atherosclerosis is still unclear. Here we identify miRNA-712 (miR-712) as a mechanosensitive miRNA upregulated by disturbed flow (d-flow) in endothelial cells, in vitro and in vivo. We also show that miR-712 is derived from an unexpected source, pre-ribosomal RNA, in an exoribonuclease-dependent but DiGeorge Syndrome Critical Region-8 (DGCR8)-independent manner, suggesting that it is an atypical miRNA. Mechanistically, d-flow-induced miR-712 downregulates tissue inhibitor of metalloproteinase-3 (TIMP3) expression, which in turn activates the downstream matrix metalloproteinases (MMPs) and a disintegrin and metalloproteases (ADAMs) and stimulate pro-atherogenic responses, endothelial inflammation and permeability. Furthermore, silencing miR-712 by anti-miR-712 rescues TIMP3 expression and prevents atherosclerosis in murine models of atherosclerosis. Finally, we report that human miR-205 shares the same “seed sequence” as murine-specific miR-712, and also targets TIMP3 in a flow-dependent manner. Targeting these mechanosensitive “athero-miRs” may provide a new treatment paradigm in atherosclerosis.

Graphical AbstractHighlights d Mutation-phosphorylation correlation suggests possible signaling interplays in EOGCs d mRNA-protein correlation suggests genes with high association with patient survival d Integrated analysis of mRNA and protein data identified four subtypes d Phosphorylation data provide cellular signaling pathways underlying the subtypes SUMMARYWe report proteogenomic analysis of diffuse gastric cancers (GCs) in young populations. Phosphoproteome data elucidated signaling pathways associated with somatic mutations based on mutation-phosphorylation correlations. Moreover, correlations between mRNA and protein abundances provided potential oncogenes and tumor suppressors associated with patient survival. Furthermore, integrated clustering of mRNA, protein, phosphorylation, and N-glycosylation data identified four subtypes of diffuse GCs. Distinguishing these subtypes was possible by proteomic data. Four subtypes were associated with proliferation, immune response, metabolism, and invasion, respectively; and associations of the subtypes with immune-and invasion-related pathways were identified mainly by phosphorylation and N-glycosylation data. Therefore, our proteogenomic analysis provides additional information beyond genomic analyses, which can improve understanding of cancer biology and patient stratification in diffuse GCs.

Fusion genes represent an important class of biomarkers and therapeutic targets in cancer. ChimerDB is a comprehensive database of fusion genes encompassing analysis of deep sequencing data (ChimerSeq) and text mining of publications (ChimerPub) with extensive manual annotations (ChimerKB). In this update, we present all three modules substantially enhanced by incorporating the recent flood of deep sequencing data and related publications. ChimerSeq now covers all 10 565 patients in the TCGA project, with compilation of computational results from two reliable programs of STAR-Fusion and FusionScan with several public resources. In sum, ChimerSeq includes 65 945 fusion candidates, 21 106 of which were predicted by multiple programs (ChimerSeq-Plus). ChimerPub has been upgraded by applying a deep learning method for text mining followed by extensive manual curation, which yielded 1257 fusion genes including 777 cases with experimental supports (ChimerPub-Plus). ChimerKB includes 1597 fusion genes with publication support, experimental evidences and breakpoint information. Importantly, we implemented several new features to aid estimation of functional significance, including the fusion structure viewer with domain information, gene expression plot of fusion positive versus negative patients and a STRING network viewer. The user interface also was greatly enhanced by applying responsive web design. ChimerDB 4.0 is available at http://www.kobic.re.kr/chimerdb/.

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