Beschreibung:
<jats:title>Abstract</jats:title>
<jats:p>Melanoma is one of the most aggressive forms of cancer with a meager 5-year survival rate of 25%, for metastatic melanoma. These necessitates new efforts to fully understand the pathogenesis of melanoma metastasis and identify new targets. In recent years, researchers have been taking advantage of TCGA and other publicly available databases to perform high-throughput data-mining aimed at identifying mechanisms and potential biomarkers of progression of different cancers, including melanoma. Although a limited number of bioinformatics studies have attempted to predict the genes that may be involved in the pathogenesis of metastatic melanoma, these are yet to be rigorously validated by other computational methodologies or databases. The purpose of this study was to identify key genes in the pathogenesis of metastatic melanoma by a comprehensive analysis of TCGA and other available databases. We first downloaded 470 TCGA melanoma patient's data, including clinical information and mRNA expression. Employing survival analysis within a multiple comparison correction of FDR&lt;=0.05, we identified 1355 genes that have a significant effect on the overall survival (OS) of melanoma patients. Using “TCGAbiolinks” package in R, we further classified 1317 genes that are differentially expressed between primary and metastatic melanoma (FDR&lt;=0.05, |log2 fold change|&gt;=1). By taking the intersection, we narrowed down to 236 genes that i) have significant effects on patient OS and ii) differentially expressed between primary and metastatic melanoma. To study the functionalities of these 236 genes, we performed Gene Ontology (GO) analysis with FDR&lt;=0.05 using the ClueGO application in Cytoscape. Interestingly, the most significantly deregulated GO term was the regulation of immune system process (GO:0002682, FDR=1.1e-39) that contained 62 out of the 236 genes, suggesting the significance of immune pathways in melanoma metastasis. To further cross-validate these 62 immune-related genes, we assessed whether these genes were differentially expressed between primary and metastatic melanoma using an external GEO database (GSE46517, 31 primary melanoma and 73 metastatic melanoma). Finally, we narrowed down to 21 candidate genes, including KLK8, SERPINB4, AQP3, S100A9, S100A8, S100A7, S100A7A, CLEC10A, FCGR3A, CD8B, CD84, CXCL13, MZB1, KIT, CD4, EBI3, NCKAP1L, SAMSN1, CD80, SIT1, and CCR2. In summary, we have identified 21 genes that i) regulate immune process, ii) have significant effects on melanoma patient survival, and iii) are differentially expressed between primary and metastatic melanoma. Further studies are required to validate our findings in metastatic melanoma cells and tissues.</jats:p>
<jats:p>Citation Format: Shengqin Su, Gagan Chhabra, Ting Ye, Nihal Ahmad. Identification of key immune-related genes in the pathogenesis of metastatic melanoma via bioinformatic approaches [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2021; 2021 Apr 10-15 and May 17-21. Philadelphia (PA): AACR; Cancer Res 2021;81(13_Suppl):Abstract nr 873.</jats:p>