Cancer risks by gene, age, and gender in 6350 carriers of pathogenic mismatch repair variants: findings from the Prospective Lynch Syndrome Database

Abstract

Lynch syndrome (LS) results from pathogenic variants in the mismatch repair (MMR) genes and is the most common hereditary cancer syndrome, affecting an estimated 1 in 300 individuals. Pathogenic variants in each of the MMR genes path_MLH1, path_MSH2, path_MSH6, and path_PMS2 result in different risks for cancers in organs including the colorectum, endometrium, ovaries, stomach, small bowel, bile duct, pancreas, and upper urinary tract. Accurate estimates of these risks are essential for planning appropriate approaches to the prevention or early diagnosis of cancers but the robustness of previous studies has been limited by factors including retrospective design,1,2 lack of validation in independent cohorts,3-5 and inconsistent classification of genetic variants. Unexpected findings from previous studies have included path_MLH1 and path_MSH2 carriers appearing to have a lifetime risk of colorectal cancer (CRC) of approximately 50%, despite surveillance colonoscopy,6-8 and that shorter intervals between colonoscopies do not seem to reduce the incidence of CRC in LS.9,10 These findings challenge the assumptions that CRC in LS usually develops from a noninfiltrative adenoma precursor and that CRC can be prevented by colonoscopic detection and removal of adenomas in the colon and rectum. Additionally, previous studies in the Prospective Lynch Syndrome Database (PLSD) have shown no increase in cancer risk in path_PMS2 carriers before 40 years of age and, although observation years were limited in older path_PMS2 carriers, LS-associated cancers other than endometrial and prostate were not observed.6-8 In this study we collected prospective data from a new large cohort of path_MMR carriers to validate previous findings from PLSD. We also updated information on the original cohort to ensure consistent classification of pathogenicity of MMR gene variants. We then combined both data sets, providing larger numbers that allowed us to derive more precise risk estimates for cancers in LS categorized by gene and gender.