Pan-cancer inference of intra-tumor heterogeneity reveals associations with different forms of genomic instability

PLoS Genet. 2018 Sep 13;14(9):e1007669. doi: 10.1371/journal.pgen.1007669. eCollection 2018 Sep.

Abstract

Genomic instability is a major driver of intra-tumor heterogeneity. However, unstable genomes often exhibit different molecular and clinical phenotypes, which are associated with distinct mutational processes. Here, we algorithmically inferred the clonal phylogenies of ~6,000 human tumors from 32 tumor types to explore how intra-tumor heterogeneity depends on different implementations of genomic instability. We found that extremely unstable tumors associated with DNA repair deficiencies or high chromosomal instability are not the most intrinsically heterogeneous. Conversely, intra-tumor heterogeneity is greatest in tumors exhibiting relatively high numbers of both mutations and copy number alterations, a feature often observed in cancers associated with exogenous mutagens. Independently of the type of instability, tumors with high number of clones invariably evolved through branching phylogenies that could be stratified based on the extent of clonal (early) and subclonal (late) instability. Interestingly, tumors with high number of subclonal mutations frequently exhibited chromosomal instability, TP53 mutations, and APOBEC-related mutational signatures. Vice versa, mutations of chromatin remodeling genes often characterized tumors with few subclonal but multiple clonal mutations. Understanding how intra-tumor heterogeneity depends on genomic instability is critical to identify markers predictive of the tumor complexity and envision therapeutic strategies able to exploit this association.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • APOBEC Deaminases / genetics
  • Algorithms
  • Chromatin Assembly and Disassembly
  • DNA Copy Number Variations
  • DNA Repair / genetics*
  • Datasets as Topic
  • Genome, Human / genetics
  • Genomic Instability*
  • Humans
  • Models, Genetic*
  • Mutation Rate
  • Neoplasms / genetics*
  • Phylogeny
  • Software
  • Tumor Suppressor Protein p53 / genetics

Substances

  • TP53 protein, human
  • Tumor Suppressor Protein p53
  • APOBEC Deaminases

Grants and funding

The project was supported by the Giorgi-Cavaglieri Foundation. MM and DT are also supported by the Swiss National Science Foundation (SNSF, grant 310030_169519). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.