Identification of a signature of evolutionarily conserved stress-induced mutagenesis in cancer

Luis H Cisneros1,2, Charles Vaske1, Kimberly J Bussey1,2,3

  • 1NantOmics, LLC, Santa Cruz, CA, United States.

Frontiers in Genetics
|September 23, 2022
PubMed

Insights

Cancer mutations resemble bacterial stress-induced mutagenesis (SIM). This ancient adaptive mutation response drives genomic instability in cancer, potentially explaining tumor evolution and treatment resistance.

Area of Science:

  • Genetics
  • Evolutionary Biology
  • Cancer Biology

Background:

  • Clustering of mutations in cancer mirrors bacterial stress-induced mutagenesis (SIM).
  • SIM in bacteria involves DNA double-strand breaks and the SOS response, utilizing DinB, a precursor to human trans-lesion synthesis (TLS) polymerases.
  • SIM results in mutations concentrated near DNA breaks, decreasing with distance.

Purpose of the Study:

  • To quantitatively investigate mutational clustering in human cancer and normal samples.
  • To identify statistical methods for detecting and characterizing mutational clusters.
  • To explore the mechanistic origins and evolutionary implications of these mutational patterns in cancer.

Main Methods:

  • Analysis of whole-genome sequencing data from 1950 tumors and 129 normal samples.
  • Development of statistical approaches to identify, quantify, and determine the shape of mutational clusters.
  • Examination of 3 cell line models for stress-induced adaptive mutation.

Main Results:

  • Mutations in both normal and cancer samples exhibit clustering patterns consistent with SIM.
  • Normal samples show more consistent cluster locations across individuals than cancer samples, suggesting regulatory loss in cancer.
  • Trans-lesion synthesis (TLS) signatures are the primary drivers of mutational cluster formation.
  • Mutational cluster shape heterogeneity correlates with reduced cancer patient survival (HR=5.744).

Conclusions:

  • The ancient, conserved bacterial SIM response is a source of genomic instability in human cancer.
  • SIM-driven biological adaptation may enable tumor evolution under selective pressures like therapy.
  • Aggressive cancer treatment strategies might be counterproductive due to promoting adaptive evolution via SIM.

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