title: A meta-analysis of somatic mutations from next generation sequencing of 241 melanomas: a road map for the study of genes with potential clinical relevance.
abstract: Next generation sequencing (NGS) has been used to characterize the overall genomic landscape of melanomas. Here, we systematically examined mutations from recently published melanoma NGS data involving 241 paired tumor-normal samples to identify potentially clinically relevant mutations. Melanomas were characterized according to an in-house clinical assay that identifies well-known specific recurrent mutations in five driver genes: BRAF (affecting V600), NRAS (G12, G13, and Q61), KIT (W557, V559, L576, K642, and D816), GNAQ (Q209), and GNA11 (Q209). Tumors with none of these mutations are termed "pan negative." We then mined the driver mutation-positive and pan-negative melanoma NGS data for mutations in 632 cancer genes that could influence existing or emerging targeted therapies. First, we uncovered several genes whose mutations were more likely associated with BRAF- or NRAS-driven melanomas, including TP53 and COL1A1 with BRAF, and PPP6C, KALRN, PIK3R4, TRPM6, GUCY2C, and PRKAA2 with NRAS. Second, we found that the 69 "pan-negative" melanoma genomes harbored alternate infrequent mutations in the five known driver genes along with many mutations in genes encoding guanine nucleotide binding protein α-subunits. Third, we identified 12 significantly mutated genes in "pan-negative" samples (ALK, STK31, DGKI, RAC1, EPHA4, ADAMTS18, EPHA7, ERBB4, TAF1L, NF1, SYK, and KDR), including five genes (RAC1, ADAMTS18, EPHA7, TAF1L, and NF1) with a recurrent mutation in at least two "pan-negative" tumor samples. This meta-analysis provides a road map for the study of additional potentially actionable genes in both driver mutation-positive and pan-negative melanomas.
authors.affiliation: Authors' Affiliations: Department of Biomedical Informatics;
authors.forename: Junfeng
authors.initials: J
authors.lastname: Xia
authors.affiliation: Authors' Affiliations: Department of Biomedical Informatics; Center for Quantitative Sciences;
authors.forename: Peilin
authors.initials: P
authors.lastname: Jia
authors.affiliation: Department of Cancer Biology;
authors.forename: Katherine E
authors.initials: KE
authors.lastname: Hutchinson
authors.affiliation: Department of Cancer Biology; Vanderbilt-Ingram Cancer Center; and.
authors.forename: Kimberly B
authors.initials: KB
authors.lastname: Dahlman
authors.affiliation: Department of Medicine/Division of Hematology-Oncology, Vanderbilt University School of Medicine, Nashville, Tennessee.
authors.forename: Douglas
authors.initials: D
authors.lastname: Johnson
authors.affiliation: Vanderbilt-Ingram Cancer Center; and Department of Medicine/Division of Hematology-Oncology, Vanderbilt University School of Medicine, Nashville, Tennessee.
authors.forename: Jeffrey
authors.initials: J
authors.lastname: Sosman
authors.affiliation: Vanderbilt-Ingram Cancer Center; and Department of Medicine/Division of Hematology-Oncology, Vanderbilt University School of Medicine, Nashville, Tennessee zhongming.zhao@vanderbilt.edu william.pao@vanderbilt.edu.
authors.forename: William
authors.initials: W
authors.lastname: Pao
authors.affiliation: Authors' Affiliations: Department of Biomedical Informatics; Center for Quantitative Sciences; Department of Cancer Biology; Vanderbilt-Ingram Cancer Center; and zhongming.zhao@vanderbilt.edu william.pao@vanderbilt.edu.
authors.forename: Zhongming
authors.initials: Z
authors.lastname: Zhao
mesh_terms: D059014:High-Throughput Nucleotide Sequencing; D006801:Humans; D008545:Melanoma / Q000235:genetics*; D009154:Mutation; D012878:Skin Neoplasms / Q000235:genetics*
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