Pan-cancer analysis of whole genomes
By Peter J. Campbell, Gad Getz, Joshua M. Stuart, Jan O. Korbel, Lincoln D. Stein, Icgc. 2020
2,501 citations recorded by the source corpus.
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. The flagship paper of the ICGC/TCGA Pan-Cancer Analysis of Whole Genomes Consortium describes the generation of the integrative analyses of 2,658 cancer whole genomes and their matching normal tissues across 38 tumour types, the structures for international data sharing and standardized analyses, and the main scientific findings from across the consortium studies.
Subfields: Cancer Research, Oncology, Pathology and Forensic Medicine
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
In Cancer Research
In Oncology
Citations in the corpus
- Scalable Open Science Approach for Mutation Calling of Tumor Exomes Using Multiple Genomic Pipelines (2018, neutral): “There are a number of cancer genomics projects working to do analysis on increasingly large datasets (Table 1) (Barretina et al., 2012; Brunner and Graubert, 2018; Campbell et al., 2017; Hart-maier et al., 2017; Turnbull, 2018; Project GENIE, 2017).”
- The frequency of Ras mutations in cancer (2020, neutral): “6 coding driver mutations per tumor (46).”
- Protein design and variant prediction using autoregressive generative models (2021, background): “…up 15 – 21% of human polymorphisms 41 – 43 , 44% of human proteins contain disordered regions longer than 30 amino acids 40,44 , and both are enriched in association with human diseases such as cystic fi brosis, many cancers 45,46 , cardiovascular and neurodegenerative diseases, and diabetes 47,48 .”
- SvABA: genome-wide detection of structural variants and indels by local assembly (2018, background): “For instance,SvABAhasbeenrecentlyusedtogen-erate somatic variant calls from 2961 cancer whole genomes as part of the International Cancer Genome Consortium (Campbell et al. 2017).”