The evolutionary history of 2,658 cancers

Abstract

Cancer develops through a process of somatic evolution 1,2. Sequencing data from a single biopsy represent a snapshot of this process that can reveal the timing of specific genomic aberrations and the changing influence of mutational processes 3. Here, by whole-genome sequencing analysis of 2,658 cancers as part of the Pan-Cancer Analysis of Whole Genomes (PCAWG) Consortium of the International Cancer Genome Consortium (ICGC) and The Cancer Genome Atlas (TCGA) 4 , we reconstruct the life history and evolution of mutational processes and driver mutation sequences of 38 types of cancer. Early oncogenesis is characterized by mutations in a constrained set of driver genes, and specific copy number gains, such as trisomy 7 in glioblastoma and isochromosome 17q in medulloblastoma. The mutational spectrum changes significantly throughout tumour evolution in 40% of samples. A nearly fourfold diversification of driver genes and increased genomic instability are features of later stages. Copy number alterations often occur in mitotic crises, and lead to simultaneous gains of chromosomal segments. Timing analyses suggest that driver mutations often precede diagnosis by many years, if not decades. Together, these results determine the evolutionary trajectories of cancer, and highlight opportunities for early cancer detection. Similar to the evolution in species, the approximately 10 14 cells in the human body are subject to the forces of mutation and selection 1. This process of somatic evolution begins in the zygote and only comes to rest at death, as cells are constantly exposed to mutagenic stresses, introducing 1-10 mutations per cell division 2. These mutagenic forces lead to a gradual accumulation of point mutations throughout life, observed in a range of healthy tissues 5-11 and cancers 12. Although these mutations are predominantly selectively neutral passenger mutations, some are proliferatively advantageous driver mutations 13. The types of mutation in cancer genomes are well studied, but little is known about the times when these lesions arise during somatic evolution and where the boundary between normal evolution and cancer progression should be drawn. Sequencing of bulk tumour samples enables partial reconstruction of the evolutionary history of individual tumours, based on the catalogue of somatic mutations they have accumulated 3,14,15. These inferences include timing of chromosomal gains during early somatic evolution 16 , phylogenetic analysis of late cancer evolution using matched primary and metastatic tumour samples from individual patients 17-20 , and temporal ordering of driver mutations across many samples 21,22 .

Next-Generation Sequencing (NGS) in the Prediction of Pancreatic Malignancy: Does Cell Free Mean Error Free?

“…Efficient amplification of the targets from cfDNA templates is expected with an amplicon size of ~ 150 bp, corresponding to the median size of the cfDNA [5], a finding supported by an earlier study that reported an increase (5-20-fold) in the percentage of mutant molecules of the adenomatous polyposis coli (APC) gene when the template size was decreased from 1296 to 100 bp [6]. Furthermore, a recent study identified that apart from variants (KRAS and TP53), copy number alterations (CNAs-17p, 9p, ARID1A, 18q, 9p213, SMAD4) are preferentially altered early in the tumorigenesis process [7]. This suggests that for effective identification of early tumorigenesis, it is not only the variants that have to genotyped but CNAs also have to be assessed.…”

Pan-cancer analysis of whole genomes identifies driver rearrangements promoted by LINE-1 retrotransposition

“…46 Copy-number dataset. We analyzed copy-number profiles obtained by the PCAWG Evolution and Heterogeneity Working Group, using a consensus approach that combines six different state-of-the-art copy-number calling methods 49 . GC content corrected logR values were extracted using the Battenberg algorithm 50 , smoothed using a running median and transformed into copy-number space according to n = [(2(1 − ρ) + ψρ)2 logR − 2(1 − ρ)]/ρ where ρ and ψ are consensus tumor purity and ploidy, respectively.…”

The repertoire of mutational signatures in human cancer

“…Therefore, the uniformly processed and highly curated sets of all classes of somatic mutations from the 2,780 cancer genomes of the PCAWG project 2 , combined with most other suitable cancer genomes (accession code syn11801889, available at https://www.synapse.org/#!Synapse:syn11801889), present a notable opportunity to establish the repertoire of mutational signatures and determine their activities across different types of cancer. The timing of these signatures during the evolution of individual cancers and the repertoire of signatures of structural variation have been explored in other PCAWG analyses 30,34 .…”