Identification of Gene Expression Signatures as Potential Novel Biomarkers in Malignant Melanoma

Author Type(s)

Faculty

Document Type

Abstract

Publication Date

7-1-2021

Journal Title

Cancer Research

Department

Pathology, Microbiology and Immunology

Abstract

Melanoma accounts for the vast majority of skin cancer-related deaths due to its ability to metastasize and therapeutic resistance. We aimed to identify expression-based signatures associated with melanoma patient survival by analyzing The Cancer Genome Atlas (TCGA) database to identify potential, prognostic biomarkers of cutaneous melanoma. Genes overexpressed in melanoma, compared with normal skin, as well as genes associated with the survival of melanoma patients were found using the online bioinformatics platform GEPIA2 (Gene Expression Profiling Interactive Analysis). The Metascape bioinformatics tool was then used for clustering of the genes based on processes and Protein-Protein Interaction (PPI) Enrichment Analysis. The genes from the 6 most significantly enriched pathways were selected to create gene signatures, which were then subjected to Kaplan-Meier survival analysis. Melanoma patients from the TCGA database (458) were placed into two groups (229 patients each): a high and a low expression group. There were 139 statistically significantly upregulated genes in melanoma (p<0.01), while 500 genes had expression levels that were significantly associated with the survival of melanoma patients. Overexpressed genes were found to belong to pigment-related pathways (pigmentation, cellular pigmentation, and pigment cell differentiation), while survival-associated genes were found to function in immune system-related pathways (adaptive immune response, lymphocyte activation, and immune response-regulating signaling pathways). Kaplan-Meier survival analysis showed that the most overexpressed genes in melanoma correlated with poorer survival, while higher expression of the most-significantly survival associated gene signatures correlated with better survival. Together, these gene signatures may serve as predictors of survival in melanoma patients.

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