In silico Evaluation of WWC1 in Melanoma Using Bioinformatic Analyses

Year 2022, , 257 - 266, 29.12.2022

Dilara Kamer Çolak , Ufuk Ünal , Sema Bolkent

https://doi.org/10.26650/EurJBiol.2022.1168881

Abstract

Objective: It is suggested that WWC1 has an active role in melanoma progression. Therefore, it was aimed to evaluate the WWC1 gene expression profiles in melanoma, an aggressive malignant skin tumor. Materials and Methods: Quantitative data from melanoma samples (n=592) were clinically evaluated using cBioPortal. Gene expression (GSE65904 and GSE22155) and gene methylation datasets (GSE120878) were retrieved from the Gene Expression Omnibus (GEO) database. Using the GeneMANIA database, the functions of given genes and pathways were evaluated. The STRING database achieved a protein-protein interaction (PPI) network was used to visualize it. Results: Mutations in the WWC1 were found in 6.7% of all melanoma samples, 8% of skin cutaneous melanoma, and 2.8% of metastatic melanoma. When the GeneMANIA platform was used to analyze gene interactions, it was determined that the WWC1 gene shared common protein domains with three genes, was co-expressed with five genes, and interacted with 17 other genes. According to the function analysis results, the most effective of the ten functions of WWC1 was Hippo signaling, with a coverage value of 0.16 (p=0.009). In addition, it then played a role in Notch signaling and organ growth. When the protein-protein interactions were examined, it was determined that it interacted with ten proteins and was co-expressed with nine. Conclusion: The findings demonstrated the potential of WWC1 to be effective in the progression of melanoma. Further research is needed to provide a more accurate analysis of WWC1 expression and methylation.

Keywords

Melanoma, WWC1, KIBRA, Bioinformatic mining, GEO

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