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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
Journal article   Open access   Peer reviewed

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

R.M. Jones, P.E. Melton, M. Pinese, A.J. Rea, E. Ingley, M.L. Ballinger, D.J. Wood, D.M. Thomas and E.K. Moses
BMC Medical Genetics, Vol.20(1), Article number 69
2019
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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.pdfDownloadView
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Abstract

Background Although familial clustering of cancers is relatively common, only a small proportion of familial cancer risk 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, we conducted 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 patients using family-based association and segregation analysis. The second stage employed a burden analysis of rare variants within prioritized candidate genes identified from stage one in 560 sarcoma cases and 1144 healthy ageing controls, for which whole genome sequence was available. Results Variants from eight genes were identified in stage one. Following gene-based burden testing and after correction for multiple testing, two of these genes, ABCB5 and C16orf96, were determined to show statistically significant association with cancer. The ABCB5 gene was found to have a higher burden of putative regulatory variants (OR = 4.9, p-value = 0.007, q-value = 0.04) based on allele counts in sarcoma cases compared to controls. C16orf96, was found to have a significantly lower burden (OR = 0.58, p-value = 0.0004, q-value = 0.003) of regulatory variants in controls compared to sarcoma cases. Conclusions Based on these genetic association data we propose that ABCB5 and C16orf96 are novel candidate risk genes for sarcoma. Although neither of these two genes have been previously associated with sarcoma, ABCB5 has been shown to share clinical drug resistance associations with melanoma and leukaemia and C16orf96 shares regulatory elements with genes that are involved with TNF-alpha mediated apoptosis in a p53/TP53-dependent manner. Future genetic studies in other family and population cohorts will be required for further validation of these novel findings.

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Collaboration types
Domestic collaboration
Citation topics
1 Clinical & Life Sciences
1.189 Genome Studies
1.189.455 Genome-Wide Association Studies
Web Of Science research areas
Genetics & Heredity
ESI research areas
Molecular Biology & Genetics
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