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Initial studies using massively parallel sequencing demonstrated the feasibility of identifying every somatic point mutation, copy-number change and structural variant (SV) in a given cancer 1, 2, 3.
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Mutations that provide a selective advantage to the clone are termed driver mutations, as opposed to selectively neutral passenger mutations. A subset of these mutations alter the cellular phenotype, and a small subset of those variants confer an advantage on clones during the competition to escape the tight physiological controls wired into somatic cells. In the context of somatic cells, heritable variation arises from mutations acquired stochastically throughout life, notwithstanding additional contributions from germline and epigenetic variation. There are three preconditions for Darwinian evolution: characteristics must vary within a population this variation must be heritable from parent to offspring and there must be competition for survival within the population. This heterogeneity arises from the stochastic nature of Darwinian evolution. Rather, there is a large pool of potential pathogenic abnormalities from which individual cancers draw their own combinations: the commonalities of macroscopic features across tumours belie a vastly heterogeneous landscape of cellular abnormalities. No single cellular program directs these behaviours. To achieve this behaviour, the cancer clone must co-opt multiple cellular pathways that enable it to disregard the normal constraints on cell growth, modify the local microenvironment to favour its own proliferation, invade through tissue barriers, spread to other organs and evade immune surveillance 21. ‘Cancer’ is a catch-all term used to denote a set of diseases characterized by autonomous expansion and spread of a somatic clone. 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, 11, 12, 13, 14, 15, 16, 17, 18.Ĭancer is the second most-frequent cause of death worldwide, killing more than 8 million people every year the incidence of cancer is expected to increase by more than 50% over the coming decades 19, 20. Common and rare germline variants affect patterns of somatic mutation, including point mutations, structural variants and somatic retrotransposition. Cancers with abnormal telomere maintenance often originate from tissues with low replicative activity and show several mechanisms of preventing telomere attrition to critical levels. 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.
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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. We describe the generation of the PCAWG resource, facilitated by international data sharing using compute clouds. 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). 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, 2, 3.