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NTHL1 and MUTYH polyposis syndromes: two sides of the same coin?

Robbert DA WerenMarjolijn Jl LigtenbergAd Geurts van KesselRicharda M De VoerNicoline HoogerbruggeRoland P Kuiper
Published in: The Journal of pathology (2017)
It is now well established that germline genomic aberrations can underlie high-penetrant familial polyposis and colorectal cancer syndromes, but a genetic cause has not yet been found for the major proportion of patients with polyposis. Since next-generation sequencing has become widely accessible, several novel, but rare, high-penetrant risk factors for adenomatous polyposis have been identified, all operating in pathways responsible for genomic maintenance and DNA repair. One of these is the base excision repair pathway. In addition to the well-established role of the DNA glycosylase gene MUTYH, biallelic mutations in which predispose to MUTYH-associated polyposis, a second DNA glycosylase gene, NTHL1, has recently been associated with adenomatous polyposis and a high colorectal cancer risk. Both recessive polyposis syndromes are associated with increased risks for several other cancer types as well, but the spectrum of benign and malignant tumours in individuals with biallelic NTHL1 mutations was shown to be broader; hence the name NTHL1-associated tumour syndrome. Colorectal tumours encountered in patients with these syndromes show unique, clearly distinct mutational signatures that may facilitate the identification of these syndromes. On the basis of the prevalence of pathogenic MUTYH and NTHL1 variants in the normal population, we estimate that the frequency of the novel NTHL1-associated tumour syndrome is five times lower than that of MUTYH-associated polyposis. Copyright © 2017 Pathological Society of Great Britain and Ireland. Published by John Wiley & Sons, Ltd.
Keyphrases
  • copy number
  • dna repair
  • chronic rhinosinusitis
  • genome wide
  • dna damage
  • circulating tumor
  • intellectual disability
  • dna methylation
  • risk factors
  • single molecule
  • transcription factor
  • bioinformatics analysis