Identification of novel sarcoma risk genes using a two-stage genome wide DNA sequencing strategy in cancer cluster families and population case and control cohorts

Background: Although familial clustering of cancers is relatively common, only a small proportion of familial cancerrisk can be explained by known cancer predisposition genes.Methods: In this study we employed a two-stage approach to identify candidate sarcoma risk genes. First, weconducted whole exome sequencing in three multigenerational cancer families ascertained through a sarcoma proband(n = 19) in order to prioritize candidate genes for validation in an independent case-control cohort of sarcoma patientsusing family-based association and segregation analysis. The second stage employed a burden analysis of rare variantswithin prioritized candidate genes identified from stage one in 560 sarcoma cases and 1144 healthy ageing controls, forwhich whole genome sequence was available.Results: Variants from eight genes were identified in stage one. Following gene-based burden testing and aftercorrection for multiple testing, two of these genes, ABCB5 and C16orf96, were determined to show statistically significantassociation with cancer. The ABCB5 gene was found to have a higher burden of putative regulatory variants (OR = 4.9, pvalue = 0.007, q-value = 0.04) based on allele counts in sarcoma cases compared to controls. C16orf96, was found to havea significantly lower burden (OR = 0.58, p-value = 0.0004, q-value = 0.003) of regulatory variants in controls compared tosarcoma cases.Conclusions: Based on these genetic association data we propose that ABCB5 and C16orf96 are novel candidate riskgenes for sarcoma. Although neither of these two genes have been previously associated with sarcoma, ABCB5 has beenshown to share clinical drug resistance associations with melanoma and leukaemia and C16orf96 shares regulatoryelements with genes that are involved with TNF-alpha mediated apoptosis in a p53/TP53-dependent manner. Futuregenetic studies in other family and population cohorts will be required for further validation of these novel findings