Melanoma Genetics

A special issue of Genes (ISSN 2073-4425). This special issue belongs to the section "Human Genomics and Genetic Diseases".

Deadline for manuscript submissions: closed (29 February 2020) | Viewed by 8086

Special Issue Editor

Cancer Programme, QIMR Berghofer Medical Research Institute, 300 Herston Rd, Herston, Brisbane, QLD 4029, Australia
Interests: melanoma; genetics; genomics; families; genome-wide association studies; phenotypes

Special Issue Information

Dear Colleagues,

Cutaneous melanoma is one of the most common cancers in fair-skinned populations. At the population level, risk of developing the disease is largely attributed to solar ultraviolet radiation exposure. Populations with pale skin, or living at low latitudes, have a higher incidence of melanoma than those with dark skin or who live at high latitudes. Natural variation in skin pigmentation is genetically controlled; thus, genes regulating pigment (melanin) production were among the first risk loci for melanoma identified through genome-wide association studies (GWAS). Likewise, genes influencing melanocytic naevus development, a well-characterized phenotypic risk factor for melanoma, were also found through GWAS to be strongly associated with melanoma susceptibility. Dozens of melanoma risk loci have now been identified through GWAS, and while many of these have pleiotropic effects on pigmentation or naevus development, others mediate their effects through such pathways as cell cycle control and telomere maintenance. Indeed, rare high penetrance mutations in genes related to these, and various other, cellular functions have been shown to cause ‘familial’ melanoma, or underlie more general cancer predisposition syndromes. Multiple melanoma susceptibility loci collectively contribute to an individual’s risk of melanoma, and polygenic risk scores can be estimated to predict lifetime probabilities of developing the disease. How much additional information such scores provide on top of routine phenotypic risk factor assessment is still to be determined. This is a critical point in relation to the clinical utility of implementing population-based genetic screening programmes for melanoma risk.

For this Special Issue, we solicit review articles, primary research papers, and methodological reports addressing all aspects of melanoma genetics, including, though not limited to: family and twin studies, population-based studies, associated phenotypic risk features, polygenic risk assessment, and cancer predisposition syndromes. We look forward to your contributions.

Prof. Nicholas K. Hayward
Guest Editor

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Keywords

  • familial
  • genetics
  • genome-wide association study
  • high pentrance
  • low penetrance
  • melanoma
  • naevi
  • phenotype
  • pigmentation
  • polygenic risk score
  • population-based

Published Papers (2 papers)

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Research

22 pages, 5170 KiB  
Article
Identification of Potential Biomarkers for Anti-PD-1 Therapy in Melanoma by Weighted Correlation Network Analysis
by Xuanyi Wang, Zixuan Chai, Yinghong Li, Fei Long, Youjin Hao, Guizhi Pan, Mingwei Liu and Bo Li
Genes 2020, 11(4), 435; https://doi.org/10.3390/genes11040435 - 17 Apr 2020
Cited by 14 | Viewed by 4841
Abstract
Melanoma is the most malignant form of skin cancer, which seriously threatens human life and health. Anti-PD-1 immunotherapy has shown clinical benefits in improving patients’ overall survival, but some melanoma patients failed to respond. Effective therapeutic biomarkers are vital to evaluate and optimize [...] Read more.
Melanoma is the most malignant form of skin cancer, which seriously threatens human life and health. Anti-PD-1 immunotherapy has shown clinical benefits in improving patients’ overall survival, but some melanoma patients failed to respond. Effective therapeutic biomarkers are vital to evaluate and optimize benefits from anti-PD-1 treatment. Although the establishment of immunotherapy biomarkers is well underway, studies that identify predictors by gene network-based approaches are lacking. Here, we retrieved the existing datasets (GSE91061, GSE78220 and GSE93157, 79 samples in total) on anti-PD-1 therapy to explore potential therapeutic biomarkers in melanoma using weighted correlation network analysis (WGCNA), function validation and clinical corroboration. As a result, 13 hub genes as critical nodes were traced from the key module associated with clinical features. After receiver operating characteristic (ROC) curve validation by an independent dataset (GSE78220), six hub genes with diagnostic significance were further recovered. Moreover, these six genes were revealed to be closely associated not only with the immune system regulation, immune infiltration, and validated immunotherapy biomarkers, but also with excellent prognostic value and significant expression level in melanoma. The random forest prediction model constructed using these six genes presented a great diagnostic ability for anti-PD-1 immunotherapy response. Taken together, IRF1, JAK2, CD8A, IRF8, STAT5B, and SELL may serve as predictive therapeutic biomarkers for melanoma and could facilitate future anti-PD-1 therapy. Full article
(This article belongs to the Special Issue Melanoma Genetics)
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15 pages, 6186 KiB  
Article
Alternative Splicing Events as Indicators for the Prognosis of Uveal Melanoma
by Qi Wan, Xuan Sang, Lin Jin and Zhichong Wang
Genes 2020, 11(2), 227; https://doi.org/10.3390/genes11020227 - 21 Feb 2020
Cited by 17 | Viewed by 2974
Abstract
Growing evidence has revealed that abnormal alternative splicing (AS) events are closely related to carcinogenic processes. However, the comprehensive study on the prognostic value of splicing events involved in uveal melanoma (UM) is still lacking. Therefore, splicing data of 80 UM patients were [...] Read more.
Growing evidence has revealed that abnormal alternative splicing (AS) events are closely related to carcinogenic processes. However, the comprehensive study on the prognostic value of splicing events involved in uveal melanoma (UM) is still lacking. Therefore, splicing data of 80 UM patients were obtained from the Cancer Genome Atlas (TCGA) SpliceSeq and RNA sequence data of UM and patient clinical features were downloaded from the Cancer Genome Atlas (TCGA) database to identify survival related splicing events in UM. As a result, a total of 37996 AS events of 17911 genes in UM were detected, among which 5299 AS events of 3529 genes were significantly associated with UM patients’ survival. Functional enrichment analysis revealed that this survival related splicing genes are corelated with mRNA catabolic process and ribosome pathway. Based on survival related splicing events, seven types of prognostic markers and the final overall prognostic signature could independently predict the overall survival of UM patients. Finally, an 11 spliced gene was identified in the final signature. On the basis of these 11 genes, we constructed a Support Vector Machine (SVM) classifier and evaluated it with leave-one-out cross-validation. The results showed that the 11 genes could determine short- and long-term survival with a predicted accuracy of 97.5%. Besides, the splicing factors and alternative splicing events correlation network was constructed to serve as therapeutic targets for UM treatment. Thus, our study depicts a comprehensive landscape of alternative splicing events in the prognosis of UM. The correlation network and associated pathways would provide additional potential targets for therapy and prognosis. Full article
(This article belongs to the Special Issue Melanoma Genetics)
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