Somatic mutations of GNA11 and GNAQ in CTNNB1-mutant aldosterone-producing adenomas presenting in puberty, pregnancy or menopause.

Most aldosterone-producing adenomas (APAs) have gain-of-function somatic mutations of ion channels or transporters. However, their frequency in aldosterone-producing cell clusters of normal adrenal gland suggests a requirement for codriver mutations in APAs. Here we identified gain-of-function mutations in both CTNNB1 and GNA11 by whole-exome sequencing of 3/41 APAs. Further sequencing of known CTNNB1-mutant APAs led to a total of 16 of 27 (59%) with a somatic p.Gln209His, p.Gln209Pro or p.Gln209Leu mutation of GNA11 or GNAQ. Solitary GNA11 mutations were found in hyperplastic zona glomerulosa adjacent to double-mutant APAs. Nine of ten patients in our UK/Irish cohort presented in puberty, pregnancy or menopause. Among multiple transcripts upregulated more than tenfold in double-mutant APAs was LHCGR, the receptor for luteinizing or pregnancy hormone (human chorionic gonadotropin). Transfections of adrenocortical cells demonstrated additive effects of GNA11 and CTNNB1 mutations on aldosterone secretion and expression of genes upregulated in double-mutant APAs. In adrenal cortex, GNA11/Q mutations appear clinically silent without a codriver mutation of CTNNB1

Sequencing of prostate cancers identifies new cancer genes, routes of progression and drug targets

Prostate cancer represents a substantial clinical challenge because it is difficult to predict outcome and advanced disease is often fatal. We sequenced the whole genomes of 112 primary and metastatic prostate cancer samples. From joint analysis of these cancers with those from previous studies (930 cancers in total), we found evidence for 22 previously unidentified putative driver genes harboring coding mutations, as well as evidence for NEAT1 and FOXA1 acting as drivers through noncoding mutations. Through the temporal dissection of aberrations, we identified driver mutations specifically associated with steps in the progression of prostate cancer, establishing, for example, loss of CHD1 and BRCA2 as early events in cancer development of ETS fusion-negative cancers. Computational chemogenomic (canSAR) analysis of prostate cancer mutations identified 11 targets of approved drugs, 7 targets of investigational drugs, and 62 targets of compounds that may be active and should be considered candidates for future clinical trials

Pan-cancer analysis of whole genomes

Cancer is driven by genetic change, and the advent of massively parallel sequencing has enabled systematic documentation of this variation at the whole-genome scale(1-3). Here we report the integrative analysis of 2,658 whole-cancer genomes and their matching normal tissues across 38 tumour types from the Pan-Cancer Analysis of Whole Genomes (PCAWG) Consortium of the International Cancer Genome Consortium (ICGC) and The Cancer Genome Atlas (TCGA). We describe the generation of the PCAWG resource, facilitated by international data sharing using compute clouds. On average, cancer genomes contained 4-5 driver mutations when combining coding and non-coding genomic elements; however, in around 5% of cases no drivers were identified, suggesting that cancer driver discovery is not yet complete. Chromothripsis, in which many clustered structural variants arise in a single catastrophic event, is frequently an early event in tumour evolution; in acral melanoma, for example, these events precede most somatic point mutations and affect several cancer-associated genes simultaneously. Cancers with abnormal telomere maintenance often originate from tissues with low replicative activity and show several mechanisms of preventing telomere attrition to critical levels. Common and rare germline variants affect patterns of somatic mutation, including point mutations, structural variants and somatic retrotransposition. A collection of papers from the PCAWG Consortium describes non-coding mutations that drive cancer beyond those in the TERT promoter(4); identifies new signatures of mutational processes that cause base substitutions, small insertions and deletions and structural variation(5,6); analyses timings and patterns of tumour evolution(7); describes the diverse transcriptional consequences of somatic mutation on splicing, expression levels, fusion genes and promoter activity(8,9); and evaluates a range of more-specialized features of cancer genomes(8,10-18).Peer reviewe