Integrated Analysis of Coexpression and Exome Sequencing to Prioritize Susceptibility Genes for Familial Cutaneous Melanoma.


Journal

The Journal of investigative dermatology
ISSN: 1523-1747
Titre abrégé: J Invest Dermatol
Pays: United States
ID NLM: 0426720

Informations de publication

Date de publication:
09 2022
Historique:
received: 02 08 2021
revised: 05 01 2022
accepted: 05 01 2022
pubmed: 20 2 2022
medline: 24 8 2022
entrez: 19 2 2022
Statut: ppublish

Résumé

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.

Identifiants

pubmed: 35181301
pii: S0022-202X(22)00118-X
doi: 10.1016/j.jid.2022.01.029
pmc: PMC9378750
mid: NIHMS1781264
pii:
doi:

Types de publication

Journal Article Research Support, N.I.H., Intramural

Langues

eng

Sous-ensembles de citation

IM

Pagination

2464-2475.e5

Subventions

Organisme : Intramural NIH HHS
ID : Z99 CA999999
Pays : United States

Informations de copyright

Copyright © 2022 The Authors. Published by Elsevier Inc. All rights reserved.

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Auteurs

Sally Yepes (S)

Division of Cancer Epidemiology & Genetics, National Cancer Institute, National Institutes of Health, Bethesda, Maryland, USA. Electronic address: sally.yepestorres@nih.gov.

Margaret A Tucker (MA)

Division of Cancer Epidemiology & Genetics, National Cancer Institute, National Institutes of Health, Bethesda, Maryland, USA.

Hela Koka (H)

Division of Cancer Epidemiology & Genetics, National Cancer Institute, National Institutes of Health, Bethesda, Maryland, USA.

Yanzi Xiao (Y)

Division of Cancer Epidemiology & Genetics, National Cancer Institute, National Institutes of Health, Bethesda, Maryland, USA.

Tongwu Zhang (T)

Division of Cancer Epidemiology & Genetics, National Cancer Institute, National Institutes of Health, Bethesda, Maryland, USA.

Kristine Jones (K)

Division of Cancer Epidemiology & Genetics, National Cancer Institute, National Institutes of Health, Bethesda, Maryland, USA; Cancer Genomics Research Laboratory, Frederick National Laboratory for Cancer Research, Leidos Biomedical Research Inc, Frederick, Maryland, USA.

Aurelie Vogt (A)

Division of Cancer Epidemiology & Genetics, National Cancer Institute, National Institutes of Health, Bethesda, Maryland, USA; Cancer Genomics Research Laboratory, Frederick National Laboratory for Cancer Research, Leidos Biomedical Research Inc, Frederick, Maryland, USA.

Laurie Burdette (L)

Division of Cancer Epidemiology & Genetics, National Cancer Institute, National Institutes of Health, Bethesda, Maryland, USA; Cancer Genomics Research Laboratory, Frederick National Laboratory for Cancer Research, Leidos Biomedical Research Inc, Frederick, Maryland, USA.

Wen Luo (W)

Division of Cancer Epidemiology & Genetics, National Cancer Institute, National Institutes of Health, Bethesda, Maryland, USA; Cancer Genomics Research Laboratory, Frederick National Laboratory for Cancer Research, Leidos Biomedical Research Inc, Frederick, Maryland, USA.

Bin Zhu (B)

Division of Cancer Epidemiology & Genetics, National Cancer Institute, National Institutes of Health, Bethesda, Maryland, USA; Cancer Genomics Research Laboratory, Frederick National Laboratory for Cancer Research, Leidos Biomedical Research Inc, Frederick, Maryland, USA.

Amy Hutchinson (A)

Division of Cancer Epidemiology & Genetics, National Cancer Institute, National Institutes of Health, Bethesda, Maryland, USA; Cancer Genomics Research Laboratory, Frederick National Laboratory for Cancer Research, Leidos Biomedical Research Inc, Frederick, Maryland, USA.

Meredith Yeager (M)

Division of Cancer Epidemiology & Genetics, National Cancer Institute, National Institutes of Health, Bethesda, Maryland, USA; Cancer Genomics Research Laboratory, Frederick National Laboratory for Cancer Research, Leidos Biomedical Research Inc, Frederick, Maryland, USA.

Belynda Hicks (B)

Division of Cancer Epidemiology & Genetics, National Cancer Institute, National Institutes of Health, Bethesda, Maryland, USA; Cancer Genomics Research Laboratory, Frederick National Laboratory for Cancer Research, Leidos Biomedical Research Inc, Frederick, Maryland, USA.

Kevin M Brown (KM)

Division of Cancer Epidemiology & Genetics, National Cancer Institute, National Institutes of Health, Bethesda, Maryland, USA.

Neal D Freedman (ND)

Division of Cancer Epidemiology & Genetics, National Cancer Institute, National Institutes of Health, Bethesda, Maryland, USA.

Stephen J Chanock (SJ)

Division of Cancer Epidemiology & Genetics, National Cancer Institute, National Institutes of Health, Bethesda, Maryland, USA.

Alisa M Goldstein (AM)

Division of Cancer Epidemiology & Genetics, National Cancer Institute, National Institutes of Health, Bethesda, Maryland, USA.

Xiaohong R Yang (XR)

Division of Cancer Epidemiology & Genetics, National Cancer Institute, National Institutes of Health, Bethesda, Maryland, USA.

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Classifications MeSH