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pmid:32623384

Identification of genes in hepatocellular carcinoma induced by non-alcoholic fatty liver disease.

Changzhou Cai · Xin Song · Chaohui Yu

Cancer biomarkers : section A of Disease markers · 2020 doi:10.3233/CBM-190169

Paper

complete

Experiment

complete

Data

partial

Analysis

complete

Execution

absent

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pmid:32623384
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2026-11-01T15:41:05Z
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title
Identification of genes in hepatocellular carcinoma induced by non-alcoholic fatty liver disease.
doi
10.3233/CBM-190169
pmid
32623384
authors array · 3 items
[0]
Changzhou Cai
[1]
Xin Song
[2]
Chaohui Yu
journal
Cancer biomarkers : section A of Disease markers
year
2020
abstract
BACKGROUND: Hepatocellular carcinoma (HCC) is the leading cause of mortality worldwide. In recent years, the incidence of HCC induced by NAFLD is growing rapidly. OBJECTIVE: To screen for new pathogenic genes and related pathways both in NAFLD and HCC, and to explore the pathogenesis of progression from NAFLD to HCC. METHODS: Gene expression microarrays (GSE74656, GSE62232) were used for identifying differentially expressed genes (DEGs). Functional enrichment and pathway enrichment analyses indicated that these DEGs were related to cell cycle and extracellular exosome, which were closely related to NAFLD and HCC development. We then used the Search Tool for the Retrieval of Interacting Genes (STRING) to establish the protein-protein interaction (PPI) network and visualized them in Cytoscape. And the overall survival (OS) analysis and gene expression validation in TCGA of hub genes was performed. RESULTS: Seven hub genes, including CDK1, HSP90AA1, MAD2L1, PRKCD, ITGB3BP, CEP192, and RHOB were identified. Finally, we verified the expression level of ITGB3BP and CEP192 by quantitative real-time PCR in vitro. CONCLUSIONS: The present study implied possible DEGs, especially the new gene CEP192, in the progression of NAFLD developing to HCC. Further rigorous experiments are required to verify the above results.
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Using the data in TCGA, we divided HCC patients into two groups based on the high and low expression of specific genes and analyzed the overall survival rate using Kaplan-Meier charts. OncoLnc could calculate and display the log-rank P-value.
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sections[7] "Survival analysis of hub genes" paragraph 2
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Using the data in TCGA, we divided HCC patients into two groups based on the high and low expression of specific genes and analyzed the overall survival rate using Kaplan-Meier charts. OncoLnc could calculate and display the log-rank P-value.
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GSE24807 consisted of 17 tissue samples (12 cases of NASH, and 5 cases of the normal liver) [13].
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Increased hemoglobin expression in NASH livers
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Large-scale gene expression profiling of 81 hepatocellular carcinomas
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Functional enrichment analysis of DEGs both in non-alcoholic steatohepatitis and hepatocellular carcinoma
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Functional and pathway enrichment analysis
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Table 1
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Functional enrichment analysis of DEGs both in non-alcoholic steatohepatitis and hepatocellular carcinoma
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[2]
[3]
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6.0E-4
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10
[3]
1.9E-3
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G2/M transition of mitotic cell cycle
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7
[3]
1.9E-3
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Positive regulation of release of sequestered calcium ion into cytosol
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4
[3]
2.1E-3
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71
[3]
4.0E-5
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41
[3]
1.2E-3
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66
[3]
2.4E-3
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[3]
2.7E-3
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[3]
3.0E-3
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[3]
6.2E-8
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[3]
1.8E-3
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14
[3]
2.3E-2
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[3]
3.9E-2
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CXCR3 chemokine receptor binding
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[3]
4.7E-2
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[3]
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3.0E-2
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[3]
6.2E-2
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8.4E-2
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[3]
6.0E-2
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4
[3]
6.9E-3
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Pathway enrichment analysis of DEGs both in non-alcoholic steatohepatitis and hepatocellular carcinoma
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PPI network establishment and analysis
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Table 2
caption
Pathway enrichment analysis of DEGs both in non-alcoholic steatohepatitis and hepatocellular carcinoma
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[3]
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[1]
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[1]
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4
[3]
5.8E-2
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[2]
[3]
[8] array · 4 items
[0]
hsa04350
[1]
TGF-beta signaling pathway
[2]
3
[3]
6.4E-2
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Abbreviations
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null
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[0] array · 2 items
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HCC:
[1]
hepatocellular carcinoma;
[1] array · 2 items
[0]
NAFLD:
[1]
non-alcoholic fatty liver disease;
[2] array · 2 items
[0]
NASH:
[1]
non-alcoholic steatohepatitis;
[3] array · 2 items
[0]
HBV:
[1]
hepatitis B virus;
[4] array · 2 items
[0]
HCV:
[1]
hepatitis C virus;
[5] array · 2 items
[0]
DEGs:
[1]
differentially expressed genes;
[6] array · 2 items
[0]
GEO:
[1]
gene expression omnibus;
[7] array · 2 items
[0]
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[1]
database for annotation, visualization and integrated discovery;
[8] array · 2 items
[0]
GO:
[1]
gene ontology;
[9] array · 2 items
[0]
BP:
[1]
biological processes;
[10] array · 2 items
[0]
MF:
[1]
molecular functions;
[11] array · 2 items
[0]
CC:
[1]
cell components;
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22
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Abbreviations
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null
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[1]
Kyoto encyclopedia of genes and genomes;
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[0]
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[1]
transforming growthfactor-beta;
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[0]
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[1]
protein-protein interaction;
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[0]
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search tool for the retrieval of interacting genes;
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[0]
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[1]
molecular complex detection;
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[0]
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[1]
the cancer genome atlas;
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[0]
qRT-PCR:
[1]
quantitative real-time PCR;
[7] array · 2 items
[0]
CDK1:
[1]
cyclin-dependent kinase 1;
[8] array · 2 items
[0]
HSP90AA1:
[1]
heat shock protein 90 alpha family class A member 1;
[9] array · 2 items
[0]
EHMT2:
[1]
euchromatic histone lysine methyltransferase 2;
[10] array · 2 items
[0]
MAD2L1:
[1]
mitotic arrest deficient 2 like 1;
[11] array · 2 items
[0]
COL1A1:
[1]
collagen type 1 alpha 1 chain;
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section[22]/table-wrap[2]#d67e1284
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Abbreviations
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[1]
n-acetylneuraminate pyruvate lyase;
[1] array · 2 items
[0]
PRKCD/PAK1:
[1]
protein kinase C delta;
[2] array · 2 items
[0]
RHOC:
[1]
ras homolog family member C;
[3] array · 2 items
[0]
COL1A2:
[1]
collagen type 1 alpha 2 chain;
[4] array · 2 items
[0]
ITGB3BP:
[1]
integrin subunit beta 3 binding protein;
[5] array · 2 items
[0]
KNL1/CASC5:
[1]
kinetochore scaffold 1;
[6] array · 2 items
[0]
CEP192:
[1]
centrosomal protein 192;
[7] array · 2 items
[0]
TUBGCP6:
[1]
tubulin gamma complex associated protein 6;
[8] array · 2 items
[0]
RHOB:
[1]
ras homolog family member B;
[9] array · 2 items
[0]
MCL1:
[1]
MCL1 apoptosis regulator
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section[22]/table-wrap[3]#d67e1353
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Using the data in TCGA, we divided HCC patients into two groups based on the high and low expression of specific genes and analyzed the overall survival rate using Kaplan-Meier charts. OncoLnc could calculate and display the log-rank P-value.
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evidence object · 3 fields
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Automated Assays Laravel application and simulated adapters
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logrank_test
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basis
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The computational analysis is owned. The physical bench the paper used is not, so a physical validation cannot be run here.
data object · 6 fields
tier
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[0]
GSE24807
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GSE62232
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GSE62232
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GSE24807 consisted of 17 tissue samples (12 cases of NASH, and 5 cases of the normal liver) [13].
basis
The paper names GSE24807, GSE62232 in Gene Expression Omnibus (GEO) and the accession resolves in the repository. No dataset was downloaded and no licence was read.
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source:pmid:32623384
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asset:table:pmid:32623384:4
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level of ITGB3BP and CEP192 by quantitative real-time PCR in vitro. CONCLUSIONS: The present study imp
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human HCC cell lines (LM3, Hep3B, Huh7, and HepG2) compared with two normal hepatic cell lines
[1]
d QSG-7701) were used. LM3, Hep3B, Huh7, and HepG2 were maintained in DMEM (Gibco) supplemented
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Using the data in TCGA, we divided HCC patients into two groups based on the high and low expression of specific genes and analyzed the overall survival rate using Kaplan-Meier charts. OncoLnc could calculate and display the log-rank P-value.
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{"sci_version": "1.2", "schema": "https://corpus.bntrg.co.uk/sci/1.0/sci.schema.json", "id": "pmid:32623384", "kind": "science-record", "revision": 8, "content_hash": "sha256:7c5ae6809ea504f8db80cdefe70f3b60f9a23ac9666a7d4005f9227485358bd6", "created_at": "2026-11-01T15:41:05Z", "updated_at": "2026-11-01T22:01:51Z", "generator": {"name": "corpus-assay-engine", "run_id": "reading-sci-2026-11-01"}, "paper": {"state": "complete", "title": "Identification of genes in hepatocellular carcinoma induced by non-alcoholic fatty liver disease.", "doi": "10.3233/CBM-190169", "pmid": "32623384", "authors": ["Changzhou Cai", "Xin Song", "Chaohui Yu"], "journal": "Cancer biomarkers : section A of Disease markers", "year": 2020, "abstract": "BACKGROUND: Hepatocellular carcinoma (HCC) is the leading cause of mortality worldwide. In recent years, the incidence of HCC induced by NAFLD is growing rapidly.\nOBJECTIVE: To screen for new pathogenic genes and related pathways both in NAFLD and HCC, and to explore the pathogenesis of progression from NAFLD to HCC.\nMETHODS: Gene expression microarrays (GSE74656, GSE62232) were used for identifying differentially expressed genes (DEGs). Functional enrichment and pathway enrichment analyses indicated that these DEGs were related to cell cycle and extracellular exosome, which were closely related to NAFLD and HCC development. We then used the Search Tool for the Retrieval of Interacting Genes (STRING) to establish the protein-protein interaction (PPI) network and visualized them in Cytoscape. And the overall survival (OS) analysis and gene expression validation in TCGA of hub genes was performed.\nRESULTS: Seven hub genes, including CDK1, HSP90AA1, MAD2L1, PRKCD, ITGB3BP, CEP192, and RHOB were identified. Finally, we verified the expression level of ITGB3BP and CEP192 by quantitative real-time PCR in vitro.\nCONCLUSIONS: The present study implied possible DEGs, especially the new gene CEP192, in the progression of NAFLD developing to HCC. Further rigorous experiments are required to verify the above results.", "claims": [{"id": "claim-method", "statement": "Using the data in TCGA, we divided HCC patients into two groups based on the high and low expression of specific genes and analyzed the overall survival rate using Kaplan-Meier charts. OncoLnc could calculate and display the log-rank P-value.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:32623384", "locator": "sections[7] \"Survival analysis of hub genes\" paragraph 2", "quote": "Using the data in TCGA, we divided HCC patients into two groups based on the high and low expression of specific genes and analyzed the overall survival rate using Kaplan-Meier charts. OncoLnc could calculate and display the log-rank P-value."}], "state": "complete"}, {"id": "claim-data-access", "statement": "GSE24807 consisted of 17 tissue samples (12 cases of NASH, and 5 cases of the normal liver) [13].", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:32623384", "locator": "sections[3] \"Microarray data acquisition\" paragraph 2", "quote": "GSE24807 consisted of 17 tissue samples (12 cases of NASH, and 5 cases of the normal liver) [13]."}], "state": "complete"}], "gaps": []}, "experiment": {"state": "complete", "objective": null, "steps": [{"id": "read_published_estimate", "order": 1, "name": "Read the published estimate from the source", "kind": "other", "state": "complete", "blocked_on": null, "description": "The claim, method and evidence span published with the source article.", "duration_hours": null, "parameters": {}, "inputs": ["source:pmid:32623384"], "outputs": ["the published estimate and its evidence"], "instruments": [], "reagents": []}, {"id": "obtain_source_data", "order": 2, "name": "Obtain the source data from the named repository", "kind": "data-preparation", "state": "complete", "blocked_on": null, "description": "The GEO series accession resolves and its sample accessions are listed. This lane did not download the dataset or read its licence.", "duration_hours": null, "parameters": {}, "inputs": ["data:geo:GSE24807"], "outputs": ["the source data with its repository provenance"], "instruments": [], "reagents": []}, {"id": "run_analysis", "order": 3, "name": "Run the published analysis", "kind": "analysis", "state": "complete", "blocked_on": null, "description": "Apply the paper's statistical method to the resolved series and compare the result with the published target.", "duration_hours": null, "parameters": {}, "inputs": ["data:geo:GSE24807"], "outputs": ["the replicated result and its comparison"], "instruments": [], "reagents": []}], "materials": [], "instruments": [], "reagents": [], "conditions": {}, "gaps": []}, "data": {"state": "partial", "assets": [{"id": "source:pmid:32623384", "role": "manuscript", "format": "xml", "media_type": "application/xml", "uri": "https://doi.org/10.3233/CBM-190169", "sha256": 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