| Literature DB >> 35181301 |
Sally Yepes1, Margaret A Tucker2, Hela Koka2, Yanzi Xiao2, Tongwu Zhang2, Kristine Jones3, Aurelie Vogt3, Laurie Burdette3, Wen Luo3, Bin Zhu3, Amy Hutchinson3, Meredith Yeager3, Belynda Hicks3, Kevin M Brown2, Neal D Freedman2, Stephen J Chanock2, Alisa M Goldstein2, Xiaohong R Yang2.
Abstract
The application of whole-exome sequencing has led to the identification of high- and moderate-risk variants that contribute to cutaneous melanoma susceptibility. However, confirming disease-causing variants remains challenging. We applied a gene coexpression network analysis to prioritize the candidate genes identified from whole-exome sequencing of 34 melanoma-prone families, with at least three affected members sequenced per family (N = 119 cases). A coexpression network was constructed from genotype-tissue expression project, skin melanoma from the cancer genome atlas, and primary melanocyte cultures. We performed module-specific enrichment and focused on modules associated with pigmentation processes because they are the best-studied and most well-known risk factors for melanoma susceptibility. We found that pigmentation-associated modules across the four expression datasets examined were enriched for well-known melanoma susceptibility genes plus genes associated with pigmentation. We also used network properties to prioritize genes within pigmentation modules as candidate susceptibility genes. Integrating information from coexpression network analysis and variant prioritization, we identified 36 genes (such as DCT, TPCN2, TRPM1, ATP10A, and EPHA5) as potential melanoma risk genes in the families. Our approach also allowed us to link families with private gene mutations on the basis of gene coexpression patterns and thereby may provide an innovative perspective in gene identification in high-risk families.Entities:
Mesh:
Year: 2022 PMID: 35181301 PMCID: PMC9378750 DOI: 10.1016/j.jid.2022.01.029
Source DB: PubMed Journal: J Invest Dermatol ISSN: 0022-202X Impact factor: 7.590