ArticleBioMed research international2021
Identification and Validation of Key Genes in Hepatocellular Carcinoma by Bioinformatics Analysis.
Article in BioMed research international, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It has been retracted, and should not be counted. Cited by 12 papers.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
12 citing papers in PubMed, 19 citations in OpenAlex.
- Mitochondrial fission regulator 2 promotes cell proliferation, migration and invasion in hepatocellular carcinoma through regulating PI3K/AKT signaling pathway.Cell division · 2025Article
- Statistical and machine learning based platform-independent key genes identification for hepatocellular carcinoma.PloS one · 2025Article
- Identification of Potential Hub Proteins as Theragnostic Targets in Hepatocellular Carcinoma through Comprehensive Quantitative Tissue Proteomics Analysis.Cancer informatics · 2025Article
- The role of Cyclin Dependent Kinase Inhibitor 3 (Heliyon · 2024Review
- Retracted: Identification and Validation of Key Genes in Hepatocellular Carcinoma by Bioinformatics Analysis.BioMed research international · 2024Article
- Detection of reproducible liver cancer specific ligand-receptor signaling in blood.Frontiers in bioinformatics · 2024Article
- Identification of key genes and signalling pathways in clear cell renal cell carcinoma: An integrated bioinformatics approach.Cancer biomarkers : section A of Disease markers · 2024Article
- Bioinformatics prediction and experimental verification identify cuproptosis-related lncRNA as prognosis biomarkers of hepatocellular carcinoma.Biochemistry and biophysics reports · 2023Article
- Differentially expressed discriminative genes and significant meta-hub genes based key genes identification for hepatocellular carcinoma using statistical machine learning.Scientific reports · 2023Article
- TRIM55 Promotes Proliferation of Hepatocellular Carcinoma Through Stabilizing TRIP6 to Activate Wnt/β-Catenin Signaling.Journal of hepatocellular carcinoma · 2023Article
- Pituitary Tumor-Transforming Gene 1/Delta like Non-Canonical Notch Ligand 1 Signaling in Chronic Liver Diseases.International journal of molecular sciences · 2022Review
- Identification of the biological function of miR-9 in spinal cord ischemia-reperfusion injury in rats.PeerJ · 2021Article
Corrections and comments
- Retraction · 2024-01-09Compromised Peer Review · Investigation by Journal/Publisher · Investigation by Third Party · Paper Mill · Unreliable Results and/or Conclusions ·
- Retracted
Authors and funding
6 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Hepatocellular carcinoma (HCC) is the most frequent primary liver cancer and has poor outcomes. However, the potential molecular biological process underpinning the occurrence and development of HCC is still largely unknown. The purpose of this study was to identify the core genes related to HCC and explore their potential molecular events using bioinformatics methods. HCC-related expression profiles GSE25097 and GSE84005 were selected from the Gene Expression Omnibus (GEO) database, and the differentially expressed genes (DEGs) between 306 HCC tissues and 281 corresponding noncancerous tissues were identified using GEO2R online tools. The protein-protein interaction network (PPIN) was constructed and visualized using the STRING database. Gene Ontology (GO) and KEGG pathway enrichment analyses of the DEGs were carried out using DAVID 6.8 and KOBAS 3.0. Additionally, module analysis and centrality parameter analysis were performed by Cytoscape. The expression differences of key genes in normal hepatocyte cells and HCC cells were verified by quantitative real-time fluorescence polymerase chain reaction (qRT-PCR). Additionally, survival analysis of key genes was performed by GEPIA. Our results showed that a total of 291 DEGs were identified including 99 upregulated genes and 192 downregulated genes. Our results showed that the PPIN of HCC was made up of 287 nodes and 2527 edges. GO analysis showed that these genes were mainly enriched in the molecular function of protein binding. Additionally, KEGG pathway analysis also revealed that DEGs were mainly involved in the metabolic, cell cycle, and chemical carcinogenesis pathways. Interestingly, a significant module with high centrality features including 10 key genes was found. Among these, CDK1, NDC80, HMMR, CDKN3, and PTTG1, which were only upregulated in HCC patients, have attracted much attention. Furthermore, qRT-PCR also confirmed the upregulation of these five key genes in the normal human hepatocyte cell line (HL-7702) and HCC cell lines (SMMC-7721, MHCC-97L, and MHCC-97H); patients with upregulated expression of these five key genes had significantly poorer survival and prognosis. CDK1, NDC80, HMMR, CDKN3, and PTTG1 can be used as molecular markers for HCC. This finding provides potential strategies for clinical diagnosis, accurate treatment, and prognosis analysis of liver cancer.
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