Modeling of Susceptibility Genes for Cancer Risk Estimation in Family Studies

Abstract

Numerous family studies have been performed to assess the associations between cancer incidence and genetic and non-genetic risk factors and to quantitatively evaluate the cancer risk attributable to these factors. As more and more mutated genes and risk alleles have been discovered or identified over the past few decades, such as mutations in BRCA1/2 for breast/ovarian cancer, in hMSH2/hMLH1 for colorectal cancer, and in TP53 for many different cancer types, it becomes increasingly important to incorporate information on known susceptibility genotypes into cancer risk analyses. However, mathematical models that account for measured (known) susceptibility genes have not been explored in family studies. We developed methods to precisely model measured susceptibility genes accounting for intra-familial correlation in hereditary mutation distribution and simultaneously determine the combined effects of individual risk factors and their interactions. The methods that we developed (1) account for measured hereditary susceptibility genotypes of each relative in a family, (2) assign to relatives with missing genotypes possible genotypes conditional on the known genotypes of others, (3) enable the measured susceptibility genotypes to follow Mendelian transmission patterns among relatives, and (4) account for genetic heterogeneity in known mutation carrier status. Our approaches are structured for age-specific risk models and can be implemented using existing program packages based on Cox proportional hazards regression and logistic regression methods. We exemplified these methods by analyzing various data sets, including 159 families with childhood soft-tissue sarcoma, 6 extended pedigrees of Li-Fraumeni syndrome with TP53 germ-line mutations, and 19 extended pedigrees of Li-Fraumeni syndrome with TP53 germ-line mutations and genetic modifier of MDM2 SNP309. Our analyses showed that TP53 germ-line mutations and their interaction with gender were strongly associated with familial cancer incidence and that SNP309 G-alleles were associated with accelerated tumor formation in both carriers and non-carriers of TP53 germ-line mutations. However, the marginal effect of SNP309 on cancer risk for those who had no known germ-line TP53 mutations was not as strong in this family study as that reported in case-series analyses.