Comprehensive Analysis of Apigetrin's Effects on Liver Cancer Cells: Insights from Bioinformatics, In Vitro Studies, and Next-Generation Transcriptome Sequencing.
Pritam Bhagwan Bhosale, Abuyaseer Abusaliya, Hun Hwan Kim, Vetrivel Preethi, Se Hyo Jeong, Min Yeong Park, Chung Kil Won, Jeong Doo Heo, Meejung Ahn, Je Kyung Seong, Gon Sup Kim
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引用次数: 0
Abstract
Despite numerous attempts to understand the molecular mechanisms behind the development of liver cancer, it continues to pose a significant worldwide health challenge. Transcriptome sequencing, a powerful tool in molecular biology, has played a pivotal role in uncovering the intricate gene expression profiles underlying hepatocellular carcinoma (HCC). In the present study, we identified a total of 808 differentially expressed genes (DEGs), with 584 exhibiting downregulation, and 224 showing upregulation following apigetrin treatment. We utilized a combination of bioinformatics tools and platforms, including Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment and mapping, Protein-Protein Interaction (PPI), and GEPIA. We found that DEGs were related to the apoptotic cell death process and identified hub genes, namely CASP8, RB1, and TGFBR2. These genes were further validated through both GEPIA analysis and western blot experiments. Our findings collectively demonstrate that apigetrin has the potential to modulate genes related to liver cancer and trigger molecular pathways that lead to apoptotic cell death in liver cancer cells. This study underscores the potential of apigetrin as an innovative treatment strategy for HCC, emphasizing the need for additional research to elucidate its mechanisms of action and evaluate its clinical efficacy.
期刊介绍:
MCP - Advancing biology through–omics and bioinformatic technologies wants to capture outcomes from the current revolution in molecular technologies and sciences. The journal has broadened its scope and embraces any high quality research papers, reviews and opinions in areas including, but not limited to, molecular biology, cell biology, biochemistry, immunology, physiology, epidemiology, ecology, virology, microbiology, parasitology, genetics, evolutionary biology, genomics (including metagenomics), bioinformatics, proteomics, metabolomics, glycomics, and lipidomics. Submissions with a technology-driven focus on understanding normal biological or disease processes as well as conceptual advances and paradigm shifts are particularly encouraged. The Editors welcome fundamental or applied research areas; pre-submission enquiries about advanced draft manuscripts are welcomed. Top quality research and manuscripts will be fast-tracked.