In-silico analysis of highly pathogenic variants of RET gene associated with thyroid cancer
DOI:
https://doi.org/10.48047/HM.10.2.2024.1490-1501Keywords:
Bioinformatics Tools, Thyroid Cancer, RET gene, Precision Medicine, Pathogenic VariantsAbstract
The proto-oncogene RET is composed of 21 exons located on chromosome 10 (10q11.2) and encodes for a transmembrane receptor tyrosine kinase for members of the glial cell line–derived neurotrophic factor family (GDNF) and associated ligands, and mutations in this gene can cause Thyroid cancer in humans. Therefore, we anticipated studying the consequences of RET non-synonymous variations using advanced bioinformatics tools. Analysis of the genetic mutations in the gene, accomplished using computational methods. The functional and pathogenic effect of missense variations and the deleterious tendency of amino acid substitutions of a gene was investigated using the gnomAD database, SIFT, MutPred, MAESTRO, UCSF Chimera, and cBioportal and survival analysis of a gene was investigated by GEPHA database. This study revealed that “C609Y”,"C618R", “C634R”,"C634F","C634W","L790F, "V804L" and "R813W" variants were predicted to be the most harmful/damaging mutations in RET gene and the survival of patients with thyroid cancer was strongly impacted by the downregulated RET (low expression). This research renders the next generation of precision medicine approaches possible and provides simple but precious tools for use in clinical settings.
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