Promising candidate drug target genes for repurposing in cervical cancer: A bioinformatics-based approach
DOI:
https://doi.org/10.52225/narra.v4i3.938Keywords:
Cervical cancer, drug target genes, bioinformatic, drug candidate, PARP inhibitorAbstract
Cervical cancer is the fourth most common cancer among women globally, and studies have shown that genetic variants play a significant role in its development. A variety of germline and somatic mutations are associated with cervical cancer. However, genomic data derived from these mutations have not been extensively utilized for the development of repurposed drugs for cervical cancer. The objective of this study was to identify novel potential drugs that could be repurposed for cervical cancer treatment through a bioinformatics approach. A comprehensive genomic and bioinformatics database integration strategy was employed to identify potential drug target genes for cervical cancer. Using the GWAS and PheWAS databases, a total of 232 genes associated with cervical cancer were identified. These pharmacological target genes were further refined by applying a biological threshold of six functional annotations. The drug target genes were then cross-referenced with cancer treatment candidates using the DrugBank database. Among the identified genes, LTA, TNFRSF1A, PRKCZ, PDE4B, and PARP were highlighted as promising targets for repurposed drugs. Notably, these five target genes overlapped with 12 drugs that could potentially be repurposed for cervical cancer treatment. Among these, talazoparib, a potent PARP inhibitor, emerged as a particularly promising candidate. Talazoparib is currently being investigated for safety and tolerability in other cancers but has not yet been studied in the context of cervical cancer. Further clinical trials are necessary to validate this finding and explore its potential as a repurposed drug for cervical cancer.
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Copyright (c) 2024 Nurfi Pratiwi, Aida J. Ulfah, Rachmadina Rachmadina, Lalu M. Irham, Arief R. Afief, Wirawan Adikusuma, Darmawi Darmawi, Rahmat A. Kemal, Ina F. Rangkuti, Maya Savira
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.