Volume 47 Issue 9, September 2015

The identification of gene-regulatory polymorphisms that influence cancer susceptibility can identify key oncogenic pathways. A new study links a germline variant to Ewing sarcoma disease susceptibility and EWSR1-FLI1–mediated gene activation.

High-throughput analysis of the phenotypes of mouse genetic knockouts presents several challenges, such as systematic measurement biases that can vary with time. A report from the EUMODIC consortium presents data from 320 genetic knockouts generated using standardized phenotyping pipelines and new statistical analyses aimed at increasing reproducibility across centers.

A new study has conducted a comprehensive exome and transcriptome analysis of a large number of intrahepatic, perihilar and distal cholangiocarcinomas and gallbladder cancers in Japanese patients. This study identifies many new alterations, confirms genetic differences in these distinct subtypes of biliary tract cancer and demonstrates that approximately 40% of described genetic aberrations are potentially targetable.

Steve Brown and colleagues report an analysis of 20 phenotyping tests, including 413 data parameters, across 449 mutant mouse alleles. They identify widespread pleiotropy and assign putative functions to genes that lacked previous phenotypic annotation.

Rinse Weersma, Carl Anderson and colleagues report the results of a trans-ancestry association study of inflammatory bowel disease. They implicate 38 new susceptibility loci, and show that the variance explained by each IBD risk locus is consistent across diverse ancestries, with a few notable exceptions.

Matthew Law, Mark Iles and colleagues report the results of a large-scale genome-wide meta-analysis of cutaneous malignant melanoma. They confirm previously reported association signals and identify five new susceptibility loci, with associated variants mapping within putative melanocyte regulatory elements.

Ruth Halaban, Michael Krauthammer and colleagues report exome sequencing of 213 melanomas and identify a distinct co-mutation pattern of NF1 with known RASopathy genes. They identify novel melanoma mutations in several RASopathy genes and suggest that mutations in these genes may enhance the pathogenicity of NF1 mutation.

Tatsuhiro Shibata and colleagues molecularly characterize 260 biliary tract cancer samples by a combination of exome and transcriptome sequencing. They find genomic alterations that could potentially be therapeutic targets.

Richard Lifton and colleagues report a genomic analysis of cutaneous T cell lymphoma (CTCL). Their results implicate several pathways in CTCL pathogenesis, including genes involved in T cell activation and apoptosis, NF-κB signaling, chromatin remodeling and DNA damage response.

Jean-Pierre Bourquin, Martin Stanulla and colleagues report whole genome, whole exome and transcriptome sequencing of TCF3-HLF fusion–positive acute lymphoblastic leukemia. Drug response profiling in patient-derived xenografts identified sensitivity to the BCL2-specific inhibitor ABT-199 (venetoclax) as a new option for treating this fatal disease.

Guy Sauvageau, Josée Hébert and colleagues analyze exomes and transcriptomes in MLL-rearranged acute myeloid leukemias. They find frequent RAS pathway mutations, which sensitize leukemias to MEK and receptor tyrosine kinase inhibitors.

Rebecca Fitzgerald and colleagues report whole-genome sequence analyses of 23 paired samples of Barrett's esophagus and esophageal adenocarcinoma. Their analyses of the clonal architecture of these lesions shows that copy number increases and heterogeneity persists during development of esophageal adenocarcinoma.

Adam Bass, Gad Getz, Scott Carter and colleagues report the whole-exome sequences of 25 pairs of esophageal adenocarcinoma and Barrett's esophagus. They identify two pathways by which Barrett's esophagus can develop into esophageal adenocarcinoma.

Paul Khavari and colleagues report genomic analyses of cutaneous T cell lymphomas. They identify recurrent point mutations and genomic gains of TNFRSF1B, encoding the tumor necrosis factor receptor TNFR2, in 18% of tumors and show that expression of a recurrent TNFR2 mutant in T cells leads to enhanced non-canonical NF-κB signaling that is sensitive to the proteasome inhibitor bortezomib.

Zhu Chen, Sai-Juan Chen, Wei-Li Zhao and colleagues identify recurrent loss-of-function mutations in the RNA helicase gene DDX3X in 20% of subjects with natural killer/T-cell lymphoma (NKTCL) in their study. The results suggest that DDX3X acts as a tumor suppressor and that its inactivation leads to poor clinical outcome.

Dmitry Gordenin and colleagues use a yeast reporter strain to identify distinct mutagenic signatures for the cytosine deaminases APOBEC3A and APOBEC3B. They find that cancer samples with APOBEC3A-like mutation signatures have greater than tenfold more APOBEC signature mutations than those with APOBEC3B-like signatures.

Olivier Delattre and colleagues show that a Ewing sarcoma susceptibility variant at 10q21.3 influences EGR2 expression by altering the activity of an enhancer bound by EWSR1-FLI1. They further show that EGR2 knockdown inhibits growth of Ewing sarcoma cells in vitro and induces complete regression of xenografts in vivo, establishing a critical role for EGR2 in Ewing sarcomagenesis.

Colin Ross and colleagues report the results of a genome-wide association study of anthracycline-induced cardiotoxicity in children treated for cancer. They identify a nonsynonymous coding variant in RARG associated with roughly fivefold higher risk of developing this severe adverse drug reaction.

Soumya Raychaudhuri, Paul de Bakker and colleagues test the non-additive disease contributions of classical HLA alleles to five common autoimmune diseases. In four of the five diseases, they observe highly significant non-additive dominance and interaction effects.

Hae Kyung Im and colleagues report a method for predicting gene expression perturbations from genotype data after training on reference transcriptome data sets. Association of predicted gene expression with disease traits identifies known and new candidate disease genes.