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Author Spotlight: Investigating Liver Cancer Pathogenesis Using Patient-Derived Organoids
Published on: August 18, 2023
Bioinformatics analysis of molecular genetic targets and key pathways for hepatocellular carcinoma
Junxue Tu1, Jingjing Chen2, Meimei He1
1Department of Pharmacy, The Second Affiliated Hospital and Yuying Children's Hospital of Wenzhou Medical University, Wenzhou, Zhejiang 325000, People's Republic of China.
Background:
Hepatocellular carcinoma (HCC) is the second leading cause of death among cancers worldwide. In this study, we aimed to identify the molecular target genes and detect the key mechanisms of HCC. Three gene expression profiles (GSE84006, GSE14323, GSE14811) and two miRNA expression profiles (GSE40744, GSE36915) were analyzed to determine the molecular target genes, microRNAs (miRNAs) and the potential molecular mechanisms in HCC.
Methods:
All profiles were extracted from the Gene Expression Omnibus database. The identification of the differentially expressed genes (DEGs) was analyzed by the GEO2R method. Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway and gene ontology (GO) enrichment analysis performed database for Integrated Discovery, Visualization and Annotation. The miRNA-gene network and protein-protein interaction (PPI) network were correlated by the Cytoscape software. The key target genes were identified by the CytoHubba plugin, Molecular Complex Detection (MCODE) plugin and miRNA-gene network. The identified hub genes were testified for survival curve using the Kaplan-Meier plotter database.
Results:
Expression profiles had 592 overlapped DEGs. The majority of the DEGs were enriched in membrane-bounded organelles and intracellular membrane-bounded organelles. These DEGs were significantly enriched in metabolic, protein processing in the endoplasmic reticulum and thyroid cancer pathways. PPI network analysis showed these genes were mostly involved in the pathogenic Escherichia coli infection and the regulation of actin cytoskeleton pathways. Combining these results, we identified 10 key genes involving in the progression of HCC. Finally, PLK1, PRCC, PRPF4 and PSMA7 exhibited higher expression levels in HCC patients with poor prognosis than those for lower expression via Kaplan-Meier plotter database.
Conclusion:
PLK1, PRCC, PRPF4 and PSMA7 could be potential biomarkers or therapeutic targets for HCC. Meanwhile, the metabolic pathway, protein processing in the endoplasmic reticulum and the thyroid cancer pathway may play vital roles in the progression of HCC.
Insights
Hepatocellular carcinoma (HCC) is a major cancer. This study identified key genes like PLK1, PRCC, PRPF4, and PSMA7, and pathways involved in HCC progression, offering potential therapeutic targets.
Area of Science:
- Oncology
- Molecular Biology
- Bioinformatics
Background:
- Hepatocellular carcinoma (HCC) is a significant global health concern, ranking as the second leading cause of cancer-related mortality worldwide.
- Identifying molecular targets and understanding the underlying mechanisms of HCC are crucial for developing effective treatment strategies.
Purpose of the Study:
- To identify key molecular target genes and elucidate the underlying mechanisms driving Hepatocellular Carcinoma (HCC) progression.
- To analyze gene and microRNA (miRNA) expression profiles to uncover novel insights into HCC pathogenesis.
Main Methods:
- Utilized gene expression profiles (GSE84006, GSE14323, GSE14811) and miRNA expression profiles (GSE40744, GSE36915) from the Gene Expression Omnibus database.
- Employed GEO2R for differentially expressed gene (DEG) analysis, KEGG pathway and GO enrichment analysis, and Cytoscape for miRNA-gene and protein-protein interaction (PPI) network construction.
- Identified key target genes using CytoHubba, MCODE, and miRNA-gene networks, and validated hub gene survival using the Kaplan-Meier plotter database.
Main Results:
- Identified 592 overlapping DEGs, enriched in membrane-bounded organelles and significantly associated with metabolic, protein processing in the endoplasmic reticulum, and thyroid cancer pathways.
- PPI network analysis highlighted involvement in pathogenic *Escherichia coli* infection and actin cytoskeleton regulation.
- Pinpointed 10 key genes in HCC progression, with *PLK1*, *PRCC*, *PRPF4*, and *PSMA7* showing higher expression in HCC patients with poor prognosis.
Conclusions:
- *PLK1*, *PRCC*, *PRPF4*, and *PSMA7* demonstrate potential as biomarkers or therapeutic targets for Hepatocellular Carcinoma (HCC).
- The metabolic pathway, protein processing in the endoplasmic reticulum, and the thyroid cancer pathway are implicated as critical players in HCC progression.
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