In-silico analysis of highly pathogenic variants of RET gene associated with thyroid cancer

Authors

  • Hamid Khan Department of Biochemistry, Faculty of Biological Sciences, Quaid-e-Azam University, Islamabad Author
  • Asma Kiran Pervez National University of Modern Languages, Lahore Author
  • Nida Matloob Department of Biomedicine, University of Triestle, Italy Author
  • Ali Raza Nawab Dr. Ikram-ul-Haq Institute of Industrial Biotechnology, Government College University, Lahore Author
  • Fayez Ali Siddiqui Department of Biotechnology, University of Karachi Author
  • Saba Iqbal School of Biochemistry and Biotechnology, University of the Punjab, Lahore Author
  • Amna Waseem Dr. Ikram-ul-Haq Institute of Industrial Biotechnology, Government College University, Lahore Author
  • Saba Abbas School of Medical Laboratory Technology, Minhaj University Lahore Author

DOI:

https://doi.org/10.48047/HM.10.2.2024.1490-1501

Keywords:

Bioinformatics Tools, Thyroid Cancer, RET gene, Precision Medicine, Pathogenic Variants

Abstract

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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Published

2024-04-30

How to Cite

Khan, H., Kiran Pervez, A., Matloob, N., Raza Nawab, A., Ali Siddiqui, F., Iqbal, S., Waseem, A., & Abbas, S. (2024). In-silico analysis of highly pathogenic variants of RET gene associated with thyroid cancer. History of Medicine, 10(2), 1490-1501. https://doi.org/10.48047/HM.10.2.2024.1490-1501