The identification of key genes and pathways in hepatocellular carcinoma by bioinformatics analysis of high-throughput dataReport as inadecuate




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Medical Oncology

, 34:101

First Online: 21 April 2017Received: 12 April 2017Accepted: 18 April 2017DOI: 10.1007-s12032-017-0963-9

Cite this article as: Zhang, C., Peng, L., Zhang, Y. et al. Med Oncol 2017 34: 101. doi:10.1007-s12032-017-0963-9

Abstract

Liver cancer is a serious threat to public health and has fairly complicated pathogenesis. Therefore, the identification of key genes and pathways is of much importance for clarifying molecular mechanism of hepatocellular carcinoma HCC initiation and progression. HCC-associated gene expression dataset was downloaded from Gene Expression Omnibus database. Statistical software R was used for significance analysis of differentially expressed genes DEGs between liver cancer samples and normal samples. Gene Ontology GO term enrichment analysis and Kyoto Encyclopedia of Genes and Genomes KEGG pathway analysis, based on R software, were applied for the identification of pathways in which DEGs significantly enriched. Cytoscape software was for the construction of protein–protein interaction PPI network and module analysis to find the hub genes and key pathways. Finally, weighted correlation network analysis WGCNA was conducted to further screen critical gene modules with similar expression pattern and explore their biological significance. Significance analysis identified 1230 DEGs with fold change >2, including 632 significantly down-regulated DEGs and 598 significantly up-regulated DEGs. GO term enrichment analysis suggested that up-regulated DEG significantly enriched in immune response, cell adhesion, cell migration, type I interferon signaling pathway, and cell proliferation, and the down-regulated DEG mainly enriched in response to endoplasmic reticulum stress and endoplasmic reticulum unfolded protein response. KEGG pathway analysis found DEGs significantly enriched in five pathways including complement and coagulation cascades, focal adhesion, ECM–receptor interaction, antigen processing and presentation, and protein processing in endoplasmic reticulum. The top 10 hub genes in HCC were separately GMPS, ACACA, ALB, TGFB1, KRAS, ERBB2, BCL2, EGFR, STAT3, and CD8A, which resulted from PPI network. The top 3 gene interaction modules in PPI network enriched in immune response, organ development, and response to other organism, respectively. WGCNA revealed that the confirmed eight gene modules significantly enriched in monooxygenase and oxidoreductase activity, response to endoplasmic reticulum stress, type I interferon signaling pathway, processing, presentation and binding of peptide antigen, cellular response to cadmium and zinc ion, cell locomotion and differentiation, ribonucleoprotein complex and RNA processing, and immune system process, respectively. In conclusion, we identified some key genes and pathways closely related with HCC initiation and progression by a series of bioinformatics analysis on DEGs. These screened genes and pathways provided for a more detailed molecular mechanism underlying HCC occurrence and progression, holding promise for acting as biomarkers and potential therapeutic targets.

KeywordsHepatocellular carcinoma Bioinformatics analysis Microarray Differentially expressed gene 



Author: Chaoyang Zhang - Li Peng - Yaqin Zhang - Zhaoyang Liu - Wenling Li - Shilian Chen - Guancheng Li

Source: https://link.springer.com/



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