Cancer researchers explored unique mutational patterns of DNA mismatch repair machinery through genome editing and developed an algorithm to predict tumor responsiveness to immunotherapy.
Somatic mutations in cancer genomes can be caused by many different mutational processes, each of which produce distinctive patterns termed mutational signatures. Although cancer researchers can now recognize a large number of mutational signatures, exactly how these patterns arise remains unknown. Nik-Zainal and colleagues tackled this problem using a CRISPR-Cas9 genome editing screen to knock out components of the DNA mismatch repair machinery and learn their unique mutational patterns. Based on their data, the authors developed MMRDetect, a computational algorithm to classify the different DNA repair deficiencies and predict tumour responsiveness to immunotherapy.
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