ArticleOncotarget2017
Identification of hub genes involved in the development of hepatocellular carcinoma by transcriptome sequencing.
Article in Oncotarget, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
What it found
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Who cites it
7 citing papers in PubMed.
- Design and Validation of a Predictive Model for Hepatocellular Carcinoma Based on Genes With Differential Expression Driven by DNA Methylation.International journal of genomics · 2026Article
- A novel focal adhesion related gene signature for prognostic prediction in hepatocellular carcinoma.Aging · 2021Article
- System-Wide Pollution of Biomedical Data: Consequence of the Search for Hub Genes of Hepatocellular Carcinoma Without Spatiotemporal Consideration.Molecular diagnosis & therapy · 2021Review
- Transcriptomic analysis and identification of prognostic biomarkers in cholangiocarcinoma.Oncology reports · 2019Article
- Identification of cancer/testis antigen 2 gene as a potential hepatocellular carcinoma therapeutic target by hub gene screening with topological analysis.Oncology letters · 2019Article
- DNA methylation-driven genes for constructing diagnostic, prognostic, and recurrence models for hepatocellular carcinoma.Theranostics · 2019Article
- Bioinformatics analysis of aberrantly methylated-differentially expressed genes and pathways in hepatocellular carcinoma.World journal of gastroenterology · 2018Article
Corrections and comments
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Authors and funding
13 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Hepatocellular carcinoma (HCC) is a leading cause of cancer-related death. The aim of this study was to identify underlying hub genes and dysregulated pathways associated with the development of HCC using bioinformatics analysis. Differentially expressed protein-coding genes were subjected to transcriptome sequencing in 11 pairs of liver cancer tissue and matched adjacent non-cancerous tissue. Gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses were performed, followed by protein-protein interaction (PPI) network construction. Hub genes were identified via centralities analysis and verified using published datasets. In total, 720 significantly differentially expressed protein-coding genes were identified in the samples, including 335 upregulated genes and 385 downregulated genes. The upregulated genes were significantly enriched in cell adhesion, biological adhesion and cell-cell adhesion GO terms under biological process (BP). Conversely, the downregulated genes were significantly enriched in embryonic organ morphogenesis, embryonic organ development and embryonic morphogenesis. The KEGG pathway analysis showed that the upregulated genes were enriched in ECM-receptor interaction and focal adhesion pathways. Furthermore, the downregulated genes were enriched in the ErbB, VEGF and MAPK signaling pathways. The PPI network and centralities analysis suggested that ITGA2 and 12 alternate genes were significant hub genes. These findings improve current understanding of the molecular mechanisms underlying HCC development and may be helpful in identifying candidate molecular biomarkers for use in diagnosing, treating and monitoring the prognosis of HCC.
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