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Oncotarget ; 6(38): 41108-22, 2015 Dec 01.
Article in English | MEDLINE | ID: mdl-26517685

ABSTRACT

BACKGROUND: The risk to develop colorectal and endometrial cancers among subjects testing positive for a pathogenic Lynch syndrome mutation varies, making the risk prediction difficult. Genetic risk modifiers alter the risk conferred by inherited Lynch syndrome mutations, and their identification can improve genetic counseling. We aimed at identifying rare genetic modifiers of the risk of Lynch syndrome endometrial cancer. METHODS: A family based approach was used to assess the presence of genetic risk modifiers among 35 Lynch syndrome mutation carriers having either a poor clinical phenotype (early age of endometrial cancer diagnosis or multiple cancers) or a neutral clinical phenotype. Putative genetic risk modifiers were identified by Next Generation Sequencing among a panel of 154 genes involved in endometrial physiology and carcinogenesis. RESULTS: A simple pipeline, based on an allele frequency lower than 0.001 and on predicted non-conservative amino-acid substitutions returned 54 variants that were considered putative risk modifiers. The presence of two or more risk modifying variants in women carrying a pathogenic Lynch syndrome mutation was associated with a poor clinical phenotype. CONCLUSION: A gene-panel is proposed that comprehends genes that can carry variants with putative modifying effects on the risk of Lynch syndrome endometrial cancer. Validation in further studies is warranted before considering the possible use of this tool in genetic counseling.


Subject(s)
Colorectal Neoplasms, Hereditary Nonpolyposis/genetics , Endometrial Neoplasms/genetics , Estrogens/metabolism , Germ-Line Mutation , High-Throughput Nucleotide Sequencing/methods , Adult , Aged , Aged, 80 and over , Colorectal Neoplasms, Hereditary Nonpolyposis/metabolism , Endometrial Neoplasms/metabolism , Female , Gene Frequency , Genetic Predisposition to Disease/genetics , Genotype , Humans , Immunohistochemistry/statistics & numerical data , Kaplan-Meier Estimate , Middle Aged , Phenotype , Polymorphism, Single Nucleotide , Prognosis , Proportional Hazards Models , Risk Factors
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