Mutations that occur in somatic cells are a driving force behind the development of cancers. Cells are constantly exposed to mutagenic stress, with one to 10 mutations occurring per cell division. Although most mutations are passive, some lead to the proliferation of cancers. While many studies have been conducted to understand the types of mutations that occur in cancer genomes, little is understood about their evolution and progression.

Researchers from the Pan-Cancer Analysis of Whole Genomes (PCAWG) Consortium gathered whole-genome sequencing data from 2,658 cancers across 38 tumor types. After standardizing against the human genome, they analyzed the patterns and signatures of structural variants across the data. By observing replication-based rearrangement processes that result in clusters of structural variants over time, the researchers were able to determine the order in which mutations occurred and the relative timing between them.

"We've developed the first timelines of genetic mutations across the spectrum of cancer types," said co-lead study author Peter Van Loo, PhD, group leader in the Cancer Genomics Laboratory at the Francis Crick Institute, in a statement released by the institute. "For more than 30 cancers, we now know what specific genetic changes are likely to happen, and when these are likely to take place. Unlocking these patterns means it should now be possible to develop new diagnostic tests that pick up signs of cancer much earlier."

The collaboration included Wellcome Sanger Institute, Broad Institute of MIT and Harvard, Big Data Institute at the University of Oxford, and Oregon Health and Science University.

The researchers were able to reconstruct the life history and evolution of mutational drivers of the 38 types of cancer by cataloging the somatic mutations that accumulated. By measuring the number of allelic copies in cancer cells, categories of early and late clonal variants were defined. They found that early oncogenesis is characterized by mutations in a constrained set of driver genes and specific chromosomal copy number gains.

Chromosomal gains occur across a wide range of molecular times, with systematic differences between tumor types. For example, in glioblastoma and medulloblastoma, the chromosomal gains occur early in molecular time, whereas in lung cancers, melanomas, and papillary kidney cancers, the gains arise toward the end of the molecular timescale. Alternatively, some cancers, including breast, ovarian, and colorectal cancers, have broad periods of chromosomal instability indicating variable timing.

In certain tumor types there are consistently early or late gains of specific chromosomal regions. For example, across cancer types, deletion of TP53 is one of the most frequent initiating mutations, including in ovarian cancer. And single copy gains of chromosome 7 occur in 90% of glioblastoma tumors, generally early in molecular time.

Out of nearly 47 million point mutations analyzed, 22% were early clonal and 7% were late clonal. Specifically, of the 5,913 oncogenic point mutations identifying cancer driver genes, 29% were early clonal and 5% were late clonal. This association indicates mutations are preferential to early timing. It also suggests that over time, as tumors evolve, they follow increasingly diverse paths driven by individually rare driver mutations and by copy number alterations.

Timing analyses suggest that driver mutations often precede diagnosis by many years, if not decades. For example, ovarian adenocarcinoma can be latent for up to 10 years.

"We have learned that cancer is the endpoint of a lifelong evolutionary process that drives our cells. This process is fueled by mutations in the cells' genomes," said co-lead author Moritz Gerstung, PhD, group leader at European Molecular Biology Laboratory's European Bioinformatics Institute (EMBL-EBI), in the statement. "These mutations occur as we age. Usually, there are no consequences to these mutations, but sometimes, the consequences can be dramatic. This process usually culminates within the decades prior to cancer diagnosis, but in some cases, we have been able to identify alterations as old as the patient."

This study is presented as part of a special collection of papers published by Nature on Pan-Cancer Analysis of Whole Genomes performed by the International Cancer Genome Consortium (ICGC) and the Cancer Genome Atlas (TCGA), Pan-Cancer Analysis of Whole Genomes (PCAWG) Project. To view more papers or learn more about the special, visit Nature.

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