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- Campbell, PJ, et al.
(author)
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Pan-cancer analysis of whole genomes
- 2020
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In: Nature. - : Springer Science and Business Media LLC. - 1476-4687 .- 0028-0836. ; 578:7793, s. 82-
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Journal article (peer-reviewed)abstract
- Cancer is driven by genetic change, and the advent of massively parallel sequencing has enabled systematic documentation of this variation at the whole-genome scale1–3. 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 promoter4; identifies new signatures of mutational processes that cause base substitutions, small insertions and deletions and structural variation5,6; analyses timings and patterns of tumour evolution7; describes the diverse transcriptional consequences of somatic mutation on splicing, expression levels, fusion genes and promoter activity8,9; and evaluates a range of more-specialized features of cancer genomes8,10–18.
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- Adcox, K, et al.
(author)
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PHENIX detector overview
- 2003
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In: Nuclear Instruments & Methods in Physics Research. Section A: Accelerators, Spectrometers, Detectors, and Associated Equipment. - 0167-5087. ; 499:2-3, s. 469-479
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Journal article (peer-reviewed)abstract
- The PHENIX detector is designed to perform a broad study of A-A, p-A, and p-p collisions to investigate nuclear matter under extreme conditions. A wide variety of probes, sensitive to all timescales, are used to study systematic variations with species and energy as well as to measure the spin structure of the nucleon. Designing for the needs of the heavy-ion and polarized-proton programs has produced a detector with unparalleled capabilities. PHENIX measures electron and muon pairs, photons, and hadrons with excellent energy and momentum resolution. The detector consists of a large number of subsystems that are discussed in other papers in this volume. The overall design parameters of the detector are presented. (C) 2002 Elsevier Science B.V. All rights reserved.
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- de Jong, S, et al.
(author)
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Applying polygenic risk scoring for psychiatric disorders to a large family with bipolar disorder and major depressive disorder
- 2018
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In: Communications biology. - : Springer Science and Business Media LLC. - 2399-3642. ; 1, s. 163-
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Journal article (peer-reviewed)abstract
- Psychiatric disorders are thought to have a complex genetic pathology consisting of interplay of common and rare variation. Traditionally, pedigrees are used to shed light on the latter only, while here we discuss the application of polygenic risk scores to also highlight patterns of common genetic risk. We analyze polygenic risk scores for psychiatric disorders in a large pedigree (n ~ 260) in which 30% of family members suffer from major depressive disorder or bipolar disorder. Studying patterns of assortative mating and anticipation, it appears increased polygenic risk is contributed by affected individuals who married into the family, resulting in an increasing genetic risk over generations. This may explain the observation of anticipation in mood disorders, whereby onset is earlier and the severity increases over the generations of a family. Joint analyses of rare and common variation may be a powerful way to understand the familial genetics of psychiatric disorders.
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