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Promising candidate drug target genes for repurposing in cervical cancer: A bioinformatics-based approach Pratiwi, Nurfi; Ulfah, Aida J.; Rachmadina, Rachmadina; Irham, Lalu M.; Afief, Arief R.; Adikusuma, Wirawan; Darmawi, Darmawi; Kemal, Rahmat A.; Rangkuti, Ina F.; Savira, Maya
Narra J Vol. 4 No. 3 (2024): December 2024
Publisher : Narra Sains Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52225/narra.v4i3.938

Abstract

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.
Unveiling the impacts of metformin on hepatocellular carcinoma: A bioinformatic exploration in cell lines Soraya, Soraya; Arfianti, Arfianti; Adikusuma, Wirawan; Irham, Lalu M.; Hamidy, Muhammad Y.; Winarto, Winarto; Rangkuti, Ina F.; Darmawi, Darmawi
Narra J Vol. 4 No. 3 (2024): December 2024
Publisher : Narra Sains Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52225/narra.v4i3.968

Abstract

The most common type of liver cancer is hepatocellular carcinoma (HCC), accounting for 75–85% of cases. Despite its associated side effects, sorafenib remains the standard treatment for HCC. Given the critical need to improve therapeutic efficacy while minimizing adverse effects, alternative drugs must be thoroughly investigated. Numerous studies indicate that combining sorafenib with metformin results in a more favorable treatment profile. The aim of this study was to employ bioinformatics methodologies to elucidate the molecular pathways and genetic underpinnings of metformin's efficacy in HCC treatment. Genes associated with metformin and its action against HCC (Huh-7 and HepG2 cells) were acquired from the NCBI-GEO data collection by utilizing pre-determined keywords. Subsequently, pathways implicated in metformin-mediated HCC treatment were analyzed through the Kyoto Encyclopedia of Genes and Genomes (KEGG). Our analysis revealed the involvement of multiple pathways, with metabolic pathways implicated in 80% of the total cases. Neurodegenerative pathways were involved in only around 60% of the total cases. These findings align with the multifaceted mechanisms of metformin’s action, encompassing adenosine monophosphate-activated protein kinase activation, apoptosis induction, insulin regulation, anti-inflammatory responses, and modulation of cell proliferation. This comprehensive investigation sheds light on the intricate molecular landscape underpinning metformin's therapeutic efficacy in HCC, thereby informing potential avenues for optimizing treatment strategies.