Comprehensive molecular characterization of gastric adenocarcinoma

Gastric cancer is a leading cause of cancer deaths, but analysis of its molecular and clinical characteristics has been complicated by histological and aetiological heterogeneity. Here we describe a comprehensive molecular evaluation of 295 primary gastric adenocarcinomas as part of The Cancer Genome Atlas (TCGA) project. We propose a molecular classification dividing gastric cancer into four subtypes: tumours positive for Epstein–Barr virus, which display recurrent PIK3CA mutations, extreme DNA hypermethylation, and amplification of JAK2, CD274 (also known as PD-L1) and PDCD1LG2 (also knownasPD-L2); microsatellite unstable tumours, which show elevated mutation rates, including mutations of genes encoding targetable oncogenic signalling proteins; genomically stable tumours, which are enriched for the diffuse histological variant and mutations of RHOA or fusions involving RHO-family GTPase-activating proteins; and tumours with chromosomal instability, which show marked aneuploidy and focal amplification of receptor tyrosine kinases. Identification of these subtypes provides a roadmap for patient stratification and trials of targeted therapies

The Somatic Genomic Landscape of Glioblastoma

We describe the landscape of somatic genomic alterations based on multi-dimensional and comprehensive characterization of more than 500 glioblastoma tumors (GBMs). We identify several novel mutated genes as well as complex rearrangements of signature receptors including EGFR and PDGFRA. TERT promoter mutations are shown to correlate with elevated mRNA expression, supporting a role in telomerase reactivation. Correlative analyses confirm that the survival advantage of the proneural subtype is conferred by the G-CIMP phenotype, and MGMT DNA methylation may be a predictive biomarker for treatment response only in classical subtype GBM. Integrative analysis of genomic and proteomic profiles challenges the notion of therapeutic inhibition of a pathway as an alternative to inhibition of the target itself. These data will facilitate the discovery of therapeutic and diagnostic target candidates, the validation of research and clinical observations and the generation of unanticipated hypotheses that can advance our molecular understanding of this lethal cancer

Orca Reduction and ContrAction Graph Clustering

During the last years, a wide range of huge networks has been made available to researchers. The discovery of natural groups, a task called graph clustering, in such datasets is a challenge arising in many applications such as the analysis of neural, social, and communication networks. We here present Orca, a new graph clustering algorithm, which operates locally and hierarchically contracts the input. In contrast to most existing graph clustering algorithms, which operate globally, Orca is able to cluster inputs with hundreds of millions of edges in less than 2.5 hours, identifying clusterings with measurably high quality. Our approach explicitly avoids maximizing any single index value such as modularity, but instead relies on simple and sound structural operations. We present and discuss the Orca algorithm and evaluate its performance with respect to both clustering quality and running time, compared to other graph clustering algorithms

Transcatheter Aortic Heart Valves Histological Analysis Providing Insight to Leaflet Thickening and Structural Valve Degeneration

OBJECTIVES This study investigated processes causing leaflet thickening and structural valve degeneration (SVD).BACKGROUND Although transcatheter aortic valve replacement (TAVR) has changed the treatment of aortic stenosis, concerns remain regarding SVD, potentially related to valve thrombosis and thickening, based on studies using computed tomography (CT). Detailed histological analyses are provided to help attain insights into these processes.METHODS Explanted transcatheter heart valves (THVs) were evaluated for thrombosis, fibrosis, and calcification for quantification of leaflet thickness. Immunohistochemical and microscopy approaches were used to investigate SVD-associated mechanisms.RESULTS THVs (n=23) were obtained from 22 patients (median 81 years of age; 50% male) from 0 to 2,583 days post TAVR. Maximal leaflet thickness increased relative to implant duration (p = 0.427; p = 0.027). THVs explanted after >2 years were thicker than those explanted after <2 years (p = 0.007). All THVs had adherent thrombus on both aortic and ventricular sides, which beyond 60 days was seen in combination with fibrosis and beyond 4 years had calcification. Early thrombus formation (<60 days) occurred despite rapid endothetialization with an abnormal hyperplastic phenotype. Fibrosis was observed in 6 patients on both the aortic and the ventricular THV surfaces, remodeled over time, and was associated with matrix metalloproteinase-1 expression. Five THVs showed overt calcification associated with adherent thrombus and fibrosis.CONCLUSIONS There is a time-dependent degeneration of THVs consisting of thrombus formation, endothelial hyperplasia, fibrosis, tissue remodeling, proteinase expression, and calcification. Future investigation is needed to further understand these mechanisms contributing to leaflet thickening and SVD. (C) 2019 by the American College of Cardiology Foundation.Cardiolog