Egyptian Journal of Medical Human GeneticsBioinformaticsPeer-reviewed journal article
A Bioinformatics Approach To Reveal Common Genes And Molecular Pathways Shared By Cutaneous Melanoma and Uveal Melanoma.
Perumal JayarajiD, Tanisha BhimwaliD, Khushneet KauriD, Kritika GuptaiD, Shreya TalujaiD, Anjali PriyadarshaniiD
Abstract
BackgroundMelanomas are highly aggressive in nature and are known for metastasis and death. Melanocytes that give rise to melanomas are neural crest progenitor-cells. Our research is primarily concerned with Uveal Melanoma (UM) and Cutaneous Melanoma (CM). Although they both share same melanocytic origin, but the biology of their respective is different. AimThe aim of our study is to recognize the common differentially expressed genes (DEGs) between UM and CM. MethodologyThe gene expression profile was downloaded from the GEO and analyzed by GEO2R for identification of DEGs. By applying DAVID, GO and KEGG, pathway enrichment analysis was performed. PPI of these DEGs was analyzed using STRING and visualized through Cytoscape and MCODE. Further, we utilized HPA and GEPIA to obtain Kaplan-Meier Graph for survival analysis in order to assess the prognostic value of hub genes. ResultsWe examined the UM and CM datasets and discovered three common upregulated and eight common downregulated DEGs for both the melanomas based on computational analysis. HMGCS1 and ELOVL5 were shown to be enriched in a variety of altered molecular pathways and pathways in cancer. Overexpression of HMGCS1 and ELOVL5 were linked to poor prognosis in CM. ConclusionOn computational evaluation, we found that HMGCS1 and ELOVL5 were upregulated in both of these melanomas. Enrichment analysis showed that these genes are involved in cancer metabolism pathway and associated with poor prognosis in CM. However, the molecular study of these genes in UM is limited. Therefore, a better understanding of the cancer metabolism pathways should be carried to pave the way for clinical benefits.
- organism: human
- assay: bulk RNA-seq
- research focus: differential expression
- approach: statistical model
- Citations
- 1
- FWCI
- 0.14
- Field percentile
- 36th percentile
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