The pan-cancer analysis of whole genomes The expansion of whole-genome sequencing studies from individual ICGC and TCGA working groups presented the opportunity to undertake a meta-analysis of genomic features across tumour types. To achieve this, the PCAWG Consortium was established. A Technical Working Group implemented the informatics analyses by aggregating the raw sequencing data from different working groups that studied individual tumour types, aligning the sequences to the human genome and delivering a set of high-quality somatic mutation calls for downstream analysis (Extended Data Fig. 1). Given the recent meta-analysis

Cancers require telomere maintenance mechanisms for unlimited replicative potential. They achieve this through TERT activation or alternative telomere lengthening associated with ATRX or DAXX loss. Here, as part of the ICGC/TCGA Pan-Cancer Analysis of Whole Genomes (PCAWG) Consortium, we dissect whole-genome sequencing data of over 2500 matched tumor-control samples from 36 different tumor types aggregated within the ICGC/TCGA Pan-Cancer Analysis of Whole Genomes (PCAWG) Consortium to characterize the genomic footprints of these mechanisms. While the telomere content of tumors with ATRX or DAXX mutations (ATRX/DAXX trunc) is increased, tumors with TERT modifications show a moderate decrease of telomere content. One quarter of all tumor samples contain somatic integrations of telomeric sequences into non-telomeric DNA. This fraction is increased to 80% prevalence in ATRX/DAXX trunc tumors, which carry an aberrant telomere variant repeat (TVR) distribution as another genomic marker. The latter feature includes enrichment or depletion of the previously undescribed singleton TVRs TTCGGG and TTTGGG, respectively. Our systematic analysis provides new insight into the recurrent genomic alterations associated with telomere maintenance mechanisms in cancer.

Discovery of cancer drivers has traditionally focused on the identification of proteincoding genes. Here we present a comprehensive analysis of putative cancer driver mutations in both protein-coding and non-coding genomic regions across >2,500 whole cancer genomes from the Pan-Cancer Analysis of Whole Genomes (PCAWG) Consortium. We developed a statistically rigorous strategy for combining significance levels from multiple driver discovery methods and demonstrate that the integrated results overcome limitations of individual methods. We combined this strategy with careful filtering and applied it to protein-coding genes, promoters, untranslated regions (UTRs), distal enhancers and non-coding RNAs. These analyses redefine the . CC-BY-NC-ND4.0 International license not peer-reviewed) is the author/funder. It is made available under a The copyright holder for this preprint (which was . http:

Many primary tumours have low levels of molecular oxygen (hypoxia), and hypoxic tumours respond poorly to therapy. Pan-cancer molecular hallmarks of tumour hypoxia remain poorly understood, with limited comprehension of its associations with specific mutational processes, non-coding driver genes and evolutionary features. Here, as part of the ICGC/TCGA Pan-Cancer Analysis of Whole Genomes (PCAWG) Consortium, which aggregated whole genome sequencing data from 2658 cancers across 38 tumour types, we quantify hypoxia in 1188 tumours spanning 27 cancer types. Elevated hypoxia associates with increased mutational load across cancer types, irrespective of underlying mutational class. The proportion of mutations attributed to several mutational signatures of unknown aetiology directly associates with the level of hypoxia, suggesting underlying mutational processes for these signatures. At the gene level, driver mutations in TP53, MYC and PTEN are enriched in hypoxic tumours, and mutations in PTEN interact with hypoxia to direct tumour evolutionary trajectories. Overall, hypoxia plays a critical role in shaping the genomic and evolutionary landscapes of cancer.

1 SUMMARYThe advance of personalized cancer medicine requires the accurate identification of the mutations driving each patient's tumor. However, to date, we have only been able to obtain partial insights into the contribution of genomic events to tumor development. Here, we design a comprehensive approach to identify the driver mutations in each patient's tumor and obtain a whole-genome panorama of driver events across more than 2,500 tumors from 37 types of cancer. This panorama includes coding and non-coding point mutations, copy number alterations and other genomic rearrangements of somatic origin, and potentially predisposing germline variants. We demonstrate that genomic events are at the root of virtually all tumors, with each carrying on average 4.6 driver events. Most individual tumors harbor a unique combination of drivers, and we uncover the most frequent co-occurring driver events. Half of all cancer genes are affected by several types of driver mutations. In summary, the panorama described here provides answers to fundamental questions in cancer genomics and bridges the gap between cancer genomics and personalized cancer medicine.Tumors arise from genomic mutations, often referred to as 'drivers', that confer proliferative advantage to a The characterization of more than 2,500 tumors by the International Cancer Genomics Consortium (ICGC) and The Cancer Genome Atlas (TCGA) under the Pan-Cancer Analysis of Whole Genomes 2 (PCAWG) 16 initiative provides an unprecedented opportunity to obtain a comprehensive whole-genome view of driver events in cancer. Here, we set the goal of identifying all driver events (somatic point mutations, SCNAs, SGRs, and potentially predisposing germline variants) across the whole genome of each tumor in the PCAWG cohort. We call this list of driver events the per-patient panorama of driver mutations (or simply panorama). To obtain it, we designed an incremental approach ( Fig. 1a; Methods and Suppl. Notes 1 and 2)that exploits the power of this cohort to discover novel drivers, both coding and non-coding, and the knowledge accumulated through decades of cancer genetics research 2 . We found driver mutations in virtually all tumors, thereby providing definitive evidence of the oft-quoted maxim that cancer is fundamentally a genomics disease. We also demonstrated the presence of a small number of driver mutations in each tumor -4.6 on average, a number that is relatively stable regardless of of the variability in mutational burden. While the contribution of somatic point mutations and SVs to tumorigenesis across cancer types differs, their relative proportions across the entire cohort are very similar. We found that most individual tumors harbor a unique combination of driver mutations, and we uncovered the most frequently co-occurring driver events.Some of these combinations may have a synergistic effect in the emergence of cancer, as in the cases of somatic point mutations of KRAS and SMAD4 in pancreatic adenocarcinomas (Panc-AdenoCA) and DAXX and MEN1 across pancreatic ...