Genetic Insights into Cervical Cancer: In silico approach
DOI:
https://doi.org/10.22399/ijcesen.969Keywords:
bioinformatics, in silico, cervix cancer, TP53, MDM2Abstract
Cervical cancer is a major global health burden, particularly in developing regions where it remains a leading cause of cancer-related deaths among women. While high-risk human papillomavirus (HPV) types are the primary etiological agents, host genetic factors and their interplay with viral mechanisms significantly influence cervical cancer susceptibility and progression. This study focuses on the genetic contributions of RPL11, TP63, and CDKN2A, key genes involved in cell cycle regulation, apoptosis, and DNA repair.We performed an in silico analysis using advanced computational tools to identify and characterize missense single nucleotide polymorphisms (SNPs) in these genes. Protein-protein interaction networks were constructed using STRING and GeneMANIA databases, and disease associations were evaluated using the DISEASES and KEGG pathway databases. Our findings identified significant polymorphisms, such as rs1042522 in TP53, encoding the P72R variant, and rs769412 in CDKN2A, which may modulate cellular responses to HPV oncoproteins, contributing to tumorigenesis. RPL11 was shown to stabilize TP53 through MDM2 inhibition, underscoring its role in tumor suppression, while TP63 was associated with epithelial differentiation and HPV-related infections.These genetic variations may also play a role in HPV-negative cervical cancers, which exhibit distinct molecular profiles. The study highlights the importance of exploring genetic predispositions in cervical cancer to better understand its pathogenesis. These findings provide a foundation for future research into personalized therapeutic strategies targeting genetic and molecular pathways, particularly for cases with unique etiological mechanisms.
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