Abstract
Loss of genes that guard against endogenous DNA damage generates distinct mutational signatures.
Major Finding: Loss of genes that guard against endogenous DNA damage generates distinct mutational signatures.
Approach: An algorithm informed by MMR gene-specific mutational signatures classifies MMR-deficient tumors.
Impact: Pinpointing mutational signature origins can improve understanding of tumor etiology and guide tumor classification.
Endogenous and exogenous sources of DNA damage create distinct patterns of somatic mutations referred to as mutational signatures. Dozens of mutational signatures have been identified to date in human tumors, but the etiologies and underlying mechanisms of many remain undefined. To systematically analyze the mutational consequences of endogenous DNA damage, Zou and colleagues used CRISPR–Cas9-mediated genome editing to generate isogenic biallelic knockouts of 42 DNA replication or repair pathway genes in human induced pluripotent stem cells and performed whole-genome sequencing after cells were cultured for 15 days. The majority of genes tested did not show mutational signatures, which could be due to the cellular model used, the timeframe of the screen, or a requirement for exogenous DNA damage for a mutational signature to manifest. However, knockout of nine genes (OGG1, UNG, EXO1, RNF168, MLH1, MSH2, MSH6, PMS1, and PMS2) induced mutational signatures, suggesting that these genes are critical for guarding the genome against endogenous DNA damage. Comparison of gene-specific signatures to those of tumors suggested potential origins for several tumor-derived mutational signatures, and detailed analyses of the substitution or indel patterns indicated that elimination of certain types of DNA damage is sequence context-specific in some cases but sequence context-independent in others. Comparison of signatures also revealed distinct mutational patterns caused by knocking out genes in the same DNA repair pathway, as knockout of the mismatch repair (MMR) pathway gene PMS2 led to a different substitution and indel profile than knockout of MLH1, MSH2, and MSH6, which had similar consequences. Building on the insights gained from MMR gene-specific mutational signatures, an algorithm to classify MMR-deficient tumors based on sequencing data was developed that was found to have improved sensitivity relative to existing methods, which could have potential implications for predicting response to immunotherapy. This experimental approach provides a framework for further annotation and attribution of mutational signatures that could provide insights into tumorigenesis and ultimately improve tumor classification and patient stratification.
Note: Research Watch is written by Cancer Discovery editorial staff. Readers are encouraged to consult the original articles for full details. For more Research Watch, visit Cancer Discovery online at http://cancerdiscovery.aacrjournals.org/CDNews.
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