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

Students’ self-worth protection and approaches to learning in higher education: predictors and consequences

© 2017, Springer Science+Business Media B.V., part of Springer Nature. The aim of this study was to test a process model of students’ learning in higher education, linking anxiety, course experience (positive and negative), self-worth protection (SWP) (self-handicapping, defensive expectations, reflectivity), student approach to learning (SAL) (deep/surface), and achievement. Path and bootstrap analyses of data from 899 first-year university students showed that anxiety significantly predicted all SWP strategies and that positive course experience negatively predicted defensive expectations, whereas negative course experience was linked to higher levels of self-handicapping and reflectivity. Deep approach was linked negatively to self-handicapping and positively to reflectivity, whereas surface approach was associated positively with both self-handicapping and defensive expectations. Finally, deep approach positively predicted achievement and partially mediated the effect of self-handicapping on achievement. These findings support the validity of linking SWP with SAL and demonstrate meaningful connections between these and the anxiety and course experience of students. Implications for theory and practice are discussed