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Identifying colorectal cancer caused by biallelic MUTYH pathogenic variants using tumor mutational signatures.

Peter GeorgesonTabitha A HarrisonBernard J PopeSyed H ZaidiConghui QuRobert S SteinfelderYi LinJihoon E JooKhalid MahmoodMark ClendenningRomy WalkerEfrat L AmitaySonja I BerndtHermann BrennerPeter T CampbellYin CaoAndrew T ChanJenny Chang-ClaudeKimberly F DohenyDavid A DrewJane C FigueiredoAmy J FrenchSteven GallingerMarios GiannakisGraham G GilesAndrea GsurMarc J GunterMichael HoffmeisterLi HsuWen-Yi HuangPaul LimburgJoAnn E MansonVictor MorenoRami NassirJonathan A NowakMireia Obón-SantacanaShuji OginoAmanda I PhippsJohn D PotterRobert E SchoenWei SunAmanda Ewart TolandQuang M TrinhTomotaka UgaiFinlay A MacraeChristophe RostyThomas J HudsonMark E JenkinsStephen N ThibodeauIngrid M WinshipUlrike PetersDaniel D Buchanan
Published in: Nature communications (2022)
Carriers of germline biallelic pathogenic variants in the MUTYH gene have a high risk of colorectal cancer. We test 5649 colorectal cancers to evaluate the discriminatory potential of a tumor mutational signature specific to MUTYH for identifying biallelic carriers and classifying variants of uncertain clinical significance (VUS). Using a tumor and matched germline targeted multi-gene panel approach, our classifier identifies all biallelic MUTYH carriers and all known non-carriers in an independent test set of 3019 colorectal cancers (accuracy = 100% (95% confidence interval 99.87-100%)). All monoallelic MUTYH carriers are classified with the non-MUTYH carriers. The classifier provides evidence for a pathogenic classification for two VUS and a benign classification for five VUS. Somatic hotspot mutations KRAS p.G12C and PIK3CA p.Q546K are associated with colorectal cancers from biallelic MUTYH carriers compared with non-carriers (p = 2 × 10 -23 and p = 6 × 10 -11 , respectively). Here, we demonstrate the potential application of mutational signatures to tumor sequencing workflows to improve the identification of biallelic MUTYH carriers.
Keyphrases
  • copy number
  • intellectual disability
  • genome wide
  • machine learning
  • deep learning
  • gene expression
  • dna methylation
  • drug delivery
  • climate change
  • wild type