Network pharmacology and bioinformatics illuminates punicalagin's pharmacological mechanisms countering drug resistance in hepatocellular carcinoma

Abstract

Background: Hepatocellular carcinoma (HCC) poses a formidable global health challenge, exhibiting significant prevalence variations across diverse regions. This study delves into the potential therapeutic implications of punicalagin, a polyphenol abundant in pomegranates, for HCC. The primary objectives encompass the identification of potent molecular targets and enriched pathways influenced by punicalagin using integrated bioinformatic analysis. Materials and methods: Employing Gene Set Enrichment Analysis (GSEA), the study discerned potential differentially expressed genes (DEGs) in liver cancer. Collating information from diverse databases, including GEO2R, CTD database, and Gene Cards, revealed a set of 20 potential targets. A pharmacological network analysis was subsequently conducted using STITCH, with Cytoscape software pinpointing five highly upregulated genes within the punicalagin network such as SRC, CASP3, AKT1, IL6, and NOS3 via the cytohubba plugin. Furthermore, Gene Ontology (GO) analysis was employed to predict functional categories, unveiling key insights into the potential biological impact of punicalagin.

Results: KEGG pathway analysis demonstrated enrichment in crucial pathways such as AMPK signaling, HIF1a, and mTOR signaling, shedding light on the molecular mechanisms influenced by punicalagin. Diagnostic assessments were performed by analyzing mRNA expression levels and overall survival for the identified targets, utilizing datasets from UALCAN and GEPIA databases. Structural confirmation of punicalagin interactions with its targets was accomplished through molecular docking studies, revealing robust binding associations with biomolecules such as SRC, CASP3, AKT1, IL6, and NOS3. Experimental validation involved RT-PCR, showcasing reduced expression levels of target biomolecules such as SRC, CASP3, AKT1, IL6, and NOS3 in HepG2 cells treated with punicalagin. Conclusion: These findings underscore the potential of punicalagin as a promising therapeutic avenue for liver cancer treatment, presenting a comprehensive approach that integrates computational insights with experimental evidence.