Explaining the familial colorectal cancer risk associated with mismatch repair (MMR)-deficient and MMR-stable tumors
Explaining the familial colorectal cancer risk associated with mismatch repair (MMR)-deficient and MMR-stable tumors
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DOI:
10.1158/1078-0432.ccr-06-1256
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发表时间:
2007-01-01
影响因子:
11.5
通讯作者:
Houlston, Richard
中科院分区:
文献类型:
--
作者:
Aaltonen, Lauri;Johns, Louise;Houlston, Richard
Purpose: There is a paucity of data quantifying the familial risk of colorectal cancer associatedwith 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.Experimental Design: 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.Results: 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.Conclusions: 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.