Evidence map›Paper›PMID 28432618›Full record

ArticleMedical oncology (Northwood, London, England)2017

The identification of key genes and pathways in hepatocellular carcinoma by bioinformatics analysis of high-throughput data.

Chaoyang Zhang, Li Peng, Yaqin Zhang, Zhaoyang Liu, Wenling Li, Shilian Chen, Guancheng Li

Open access · hybridAbstract read
In one paragraph

Article in Medical oncology (Northwood, London, England), 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 102 papers.

0numbers the graph read from it
0cells of the map it votes in
102citing papers in PubMed
9.6field-weighted citation impact, top 1% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

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.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

102 citing papers in PubMed, 176 citations in OpenAlex.

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  13. Gene targets with therapeutic potential in hepatocellular carcinoma.World journal of gastrointestinal oncology · 2024
    Article
  14. Article
  15. Review
  16. Analysis of the Upregulated Expression Mechanism of Apoptotic Chromatin Condensation Inducer 1 in Hepatocellular Carcinoma Based on Bioinformatics.The Turkish journal of gastroenterology : the official journal of Turkish Society of Gastroenterology · 2024
    Article
  17. Article
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  19. CENPA-driven STMN1 Transcription Inhibits Ferroptosis in Hepatocellular Carcinoma.Journal of clinical and translational hepatology · 2023
    Article
  20. Article

42 more citing papers are in PubMed but not listed here.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

7 authors at 2 institutions in 1 country.

Chaoyang ZhangKey Laboratory of Carcinogenesis of the Chinese Ministry of Health, Xiangya Hospital, Central South University, Changsha, People's Republic of China.
Li PengKey Laboratory of Carcinogenesis of the Chinese Ministry of Health, Xiangya Hospital, Central South University, Changsha, People's Republic of China.
Yaqin ZhangKey Laboratory of Carcinogenesis of the Chinese Ministry of Health, Xiangya Hospital, Central South University, Changsha, People's Republic of China.
Zhaoyang LiuKey Laboratory of Carcinogenesis of the Chinese Ministry of Health, Xiangya Hospital, Central South University, Changsha, People's Republic of China.
Wenling LiKey Laboratory of Carcinogenesis of the Chinese Ministry of Health, Xiangya Hospital, Central South University, Changsha, People's Republic of China.
Shilian ChenKey Laboratory of Carcinogenesis of the Chinese Ministry of Health, Xiangya Hospital, Central South University, Changsha, People's Republic of China.
Guancheng LiKey Laboratory of Carcinogenesis of the Chinese Ministry of Health, Xiangya Hospital, Central South University, Changsha, People's Republic of China. ligc61@csu.edu.cn.
Xiangya Hospital Central South University · CNCentral South University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

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.

Indexed as

Biomarkers, TumorCarcinoma, HepatocellularCluster AnalysisComputational BiologyGene Expression ProfilingGene Expression Regulation, NeoplasticHigh-Throughput Nucleotide SequencingHumansLiver NeoplasmsSoftwareBiomarkers, TumorBioinformatics analysisDifferentially expressed geneHepatocellular carcinomaMicroarray

Identifiers

PMID28432618
PMCPMC5400790
OpenAlexW2607237735

What OpenQuestion holds

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LicenceCC BY
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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.