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      Explaining the familial colorectal cancer risk associated with mismatch repair (MMR)-deficient and MMR-stable tumors.

      Clinical cancer research : an official journal of the American Association for Cancer Research
      Adenomatous Polyposis Coli, genetics, Adolescent, Adult, Aged, Aged, 80 and over, Base Pair Mismatch, Child, Colorectal Neoplasms, pathology, DNA Repair, Family Health, Female, Genetic Predisposition to Disease, Germ-Line Mutation, Humans, Male, Microsatellite Instability, Middle Aged, Phenotype, Risk

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          Abstract

          There is a paucity of data quantifying the familial risk of colorectal cancer associated with mismatch repair (MMR)-deficient and MMR-stable tumors. To address this, we analyzed a population-based series of 1,042 colorectal cancer probands with verified family histories. Constitutional DNA from probands was systematically screened for MYH variants and those with cancers displaying microsatellite instability (MSI) for germ-line MMR mutations; diagnoses of familial adenomatous polyposis and juvenile polyposis were established based on clinical phenotype and mutational analysis. Familial colorectal cancer risks were enumerated from age-, sex-, and calendar-specific population incidence rates. Segregation analysis was conducted to derive a model of the residual familial aggregation of colorectal cancer. Germ-line predisposition to colorectal cancer was identified in 37 probands [3.4%; 95% confidence interval (95% CI), 2.4-4.6]: 29 with MLH1/MSH2 mutations, 2 with familial adenomatous polyposis, 1 with juvenile polyposis, and 5 with biallelic MYH variants. The risk of colorectal cancer in first-degree relatives of probands with MSI and MMR-stable cancers was increased 5.01-fold (95% CI, 3.73-6.59) and 1.31-fold (95% CI, 1.07-1.59), respectively. MSH2/MLH1 mutations were responsible for 50% of the overall excess familial risk and 80% of the risk associated with MSI cancers but 32% of the familial risk was unaccounted for by known loci. Genetic models based on major gene loci did not provide a better explanation of the residual familial aggregation than a simple polygenic model. The information from our analyses should be useful in quantifying familial risks in clinical practice and in the design of studies to identify novel disease alleles.

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