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

Electroweak parameters of the z0 resonance and the standard model

Contains fulltext : 124399.pdf (publisher's version ) (Open Access

Analysis of heritability and shared heritability based on Genome-Wide Association Studies for 13 Cancer Types

Background: Studies of related individuals have consistently demonstrated notable familial aggregation of cancer. We aim to estimate the heritability and genetic correlation attributable to the additive effects of common SNPs for cancer at 13 anatomical sites. Methods: Between 2007 and 2014, the US National Cancer Institute has generated data from genome-wide association studies (GWAS) for 49,492 cancer cases and 34,131 controls. We apply novel mixed model methodology (GCTA) to this GWAS data to estimate the heritability of individual cancers, as well as the proportion of heritability attributable to cigarette smoking in smoking-related cancers, and the genetic correlation between pairs of cancers. Results: GWAS heritability was statistically significant at nearly all sites, with the estimates of array-based heritability, hl2, on the liability threshold (LT) scale ranging from 0.05 to 0.38. Estimating the combined heritability of multiple smoking characteristics, we calculate that at least 24% (95% CI = 14% - 37%) and 7% (4% - 11%) of the heritability for lung and bladder cancer, respectively, can be attributed to genetic determinants of smoking. Most pairs of cancers studied did not show evidence of strong genetic correlation. We found only four pairs of cancers with marginally statistically significant correlations, specifically kidney and testes (ρ=0.73, SE=0.28), Diffuse Large B-Cell Lymphoma (DLBCL) and pediatric osteosarcoma (ρ=0.53, SE=0.21), DLBCL and Chronic Lymphocytic Leukemia (CLL) (ρ=0.51, SE=0.18), and bladder and lung (ρ=0.35, SE=0.14). Correlation analysis also indicates that the genetic architecture of lung cancer differs between a smoking population of European ancestry and a non-smoking Asian population, allowing for the possibility that the genetic etiology for the same disease can vary by population and environmental exposures. Conclusion: Our results provide important insights into the genetic architecture of cancers and suggest new avenues for investigation

Two years after pandemic influenza A/2009/H1N1: What have we learned?

The world had been anticipating another influenza pandemic since the last one in 1968. The pandemic influenza A H1N1 2009 virus (A/2009/H1N1) finally arrived, causing the first pandemic influenza of the new millennium, which has affected over 214 countries and caused over 18,449 deaths. Because of the persistent threat from the A/H5N1 virus since 1997 and the outbreak of the severe acute respiratory syndrome (SARS) coronavirus in 2003, medical and scientific communities have been more prepared in mindset and infrastructure. This preparedness has allowed for rapid and effective research on the epidemiological, clinical, pathological, immunological, virological, and other basic scientific aspects of the disease, with impacts on its control. A PubMed search using the keywords "pandemic influenza virus H1N1 2009" yielded over 2,500 publications, which markedly exceeded the number published on previous pandemics. Only representative works with relevance to clinical microbiology and infectious diseases are reviewed in this article. A significant increase in the understanding of this virus and the disease within such a short amount of time has allowed for the timely development of diagnostic tests, treatments, and preventive measures. These findings could prove useful for future randomized controlled clinical trials and the epidemiological control of future pandemics. © 2012, American Society for Microbiology. All Rights Reserved.link_to_subscribed_fulltex