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pmid:29879025

Systems analysis of key genes and pathways in the progression of hepatocellular carcinoma.

Yu-Kui Shang · Fanni Li · Yi Zhang · Ze-Kun Liu · Zi-Ling Wang · Huijie Bian · Zhi-Nan Chen

Medicine · 2018 doi:10.1097/MD.0000000000010892

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Experiment

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Data

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Analysis

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pmid:29879025
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title
Systems analysis of key genes and pathways in the progression of hepatocellular carcinoma.
doi
10.1097/MD.0000000000010892
pmid
29879025
authors array · 7 items
[0]
Yu-Kui Shang
[1]
Fanni Li
[2]
Yi Zhang
[3]
Ze-Kun Liu
[4]
Zi-Ling Wang
[5]
Huijie Bian
[6]
Zhi-Nan Chen
journal
Medicine
year
2018
abstract
The carcinogenesis of hepatocellular carcinoma (HCC) is a complex process, starting from a chronically altered hepatic microenvironment due to liver cirrhosis and ultimately progressing to HCC. However, the sequential molecular alterations driving the malignant transformation in liver cirrhosis are not clearly defined.In this study, we obtained gene expression profiles of HCC, including 268 tumor tissues, 243 adjacent tumor tissues, and 40 cirrhotic tissues (GSE25097) from Gene Expression Omnibus (GEO), to comprehensively define changes in the transcriptome of HCC during the sequential evolution of liver cirrhosis into HCC.We showed that changes in the molecular profiles of cirrhotic and adjacent tumor samples were small and quite uniform, whereas there was a striking increase in the heterogeneity of tumors in HCC tissues at the mRNA level. A massive deregulation of key oncogenic molecules and pathways was observed from cirrhosis to HCC tumors. In addition, we focused on FOXO1 and DCN, 2 critical tumor suppressor genes that play an important role in liver cirrhosis and HCC development. FOXO1 and DCN expression levels were significantly reduced in tumor tissues compared with adjacent tumor tissues in HCC. Kaplan-Meier analysis revealed that FOXO1 and DCN expression was positively correlated with overall survival, defining FOXO1 and DCN as adverse prognostic biomarkers for HCC.This system-level research provided new insights into the molecular mechanisms of HCC carcinogenesis. FOXO1 and DCN may be applied as potential targets for HCC treatment in the future.
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Survival analysis was performed with the Kaplan–Meier method, and the log-rank test was used to evaluate the statistical significance of the differences.
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The discovery dataset GSE25097 was obtained from Gene Expression Omnibus (GEO, https://www.ncbi.nlm.nih.gov/geo/)[8].
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The discovery dataset GSE25097 was obtained from Gene Expression Omnibus (GEO, https://www.ncbi.nlm.nih.gov/geo/)[8].
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title
miR-122 as a Regulator of Mitochondrial Metabolic Gene Network in Hepatocellular Carcinoma
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[404]
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[414]
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[418]
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[421]
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[422]
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[423]
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[424]
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[425]
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[428]
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[429]
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[431]
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[432]
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[433]
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[434]
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[435]
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[436]
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[437]
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[438]
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[439]
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[440]
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[442]
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[443]
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[447]
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[450]
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[452]
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[457]
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[464]
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[465]
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[466]
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[467]
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[468]
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[469]
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[470]
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[471]
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[472]
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[473]
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[474]
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[475]
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[476]
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[477]
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[478]
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[479]
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[481]
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[482]
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[483]
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[497]
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GSM617571
sample_count
557
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null
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null
platform
10687
taxon
Homo sapiens
title
Study of gene expression of human liver Hepatocellular carcinoma
resolution_checked_at
2026-11-01T15:39:54Z
resolution_check
identifier_resolution_only_no_download_no_licence_read
downloaded
false
licence_read
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read_table
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section[9]/table-wrap[1]#T1
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null
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Significantly impacted pathways between cirrhotic and adjacent nontumor as determined by SPIA.
structure object · 5 fields
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PMC5999467
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9
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Pathway enrichment analysis of DEGs among cirrhotic, adjacent nontumor, and tumor samples of HCC
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0
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0
table object · 8 fields
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Table 1
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Significantly impacted pathways between cirrhotic and adjacent nontumor as determined by SPIA.
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section[9]/table-wrap[1]#T1
[4] object · 16 fields
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read_table
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section[9]/table-wrap[2]#T2
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Significantly impacted pathways between adjacent nontumor and tumor as determined by SPIA.
structure object · 5 fields
pmcid
PMC5999467
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9
section_title
Pathway enrichment analysis of DEGs among cirrhotic, adjacent nontumor, and tumor samples of HCC
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0
column_count
0
table object · 8 fields
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Table 2
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Significantly impacted pathways between adjacent nontumor and tumor as determined by SPIA.
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section[9]/table-wrap[2]#T2
[5] object · 16 fields
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read_table
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available
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section[11]/table-wrap[1]#T3
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null
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Clinical characteristics and correlations with the expression of FOXO1 and DCN.
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PMC5999467
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11
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FOXO1 and DCN expression were prognostic indicators for patients with HCC
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0
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0
table object · 8 fields
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Table 3
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Clinical characteristics and correlations with the expression of FOXO1 and DCN.
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section[11]/table-wrap[1]#T3
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[0]
asset:data:geo:GSE22058 not downloaded
[1]
asset:data:geo:GSE22058 licence not read
[2]
asset:data:geo:GSE25097 not downloaded
[3]
asset:data:geo:GSE25097 licence not read
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partial
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[0] object · 10 fields
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method-1
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survival_analysis
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log_rank_test
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Survival analysis
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[0]
logrank_test
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parameters object · 0 fields
data_shapes array · 1 item
[0]
time_to_event_with_censoring
evidence object · 3 fields
score
1
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verbatim
quote
Survival analysis was performed with the Kaplan–Meier method, and the log-rank test was used to evaluate the statistical significance of the differences.
[1] object · 10 fields
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method-2
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group_comparison
specific
student_t_test
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Group comparison
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missing_operations array · 1 item
[0]
student_t
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false
parameters object · 0 fields
data_shapes array · 1 item
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two_or_more_groups_continuous
evidence object · 3 fields
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0.8
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Student t test
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method-3
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survival_analysis
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Survival analysis
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[0]
survival_km
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parameters object · 0 fields
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time_to_event_with_censoring
evidence object · 3 fields
score
0.7
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medium
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Kaplan-Meier
[3] object · 10 fields
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method-4
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network_analysis
specific
pathway_enrichment
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Network / pathway analysis
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[0]
pathway_enrich
missing_operations array · 0 items
parameters object · 0 fields
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[0]
edge_list
evidence object · 3 fields
score
0.8
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high
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Pathway enrichment
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[0]
method.reader_differs_from_extractor
capability object · 3 fields
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complete
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[0] object · 6 fields
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gwas
candidate
Automated Assays Laravel application and simulated adapters
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readiness object · 8 fields
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complete
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R1
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nothing:replicable_now
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method object · 5 fields
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R1
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true
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[0]
logrank_test
missing_operations array · 0 items
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The paper names the method it used and the corpus's method extractor maps it onto the DSL catalogue: log_rank_test.
capability object · 4 fields
tier
R1
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capability:computational_analysis
availability_state
owned
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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
R1
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GSE25097
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GSE22058
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GSE25097
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GSE22058
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The discovery dataset GSE25097 was obtained from Gene Expression Omnibus (GEO, https://www.ncbi.nlm.nih.gov/geo/)[8].
basis
The paper names GSE25097, GSE22058 in Gene Expression Omnibus (GEO) and the accession resolves in the repository. No dataset was downloaded and no licence was read.
can_run object · 3 fields
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logrank_test
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[0]
source:pmid:29879025
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data:geo:GSE22058
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asset:table:pmid:29879025:1
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asset:table:pmid:29879025:2
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asset:table:pmid:29879025:3
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[0]
run_analysis
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data:geo:GSE22058
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partial
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extraction_review
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minimax
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minimax
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2026-10-31T18:11:44Z
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same_provider
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verbatim
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null
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3
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extraction
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agent:corpus-assay-engine
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agent:corpus-assay-engine
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gaps array · 9 items
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asset:data:geo:GSE22058 licence not read
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asset:data:geo:GSE25097 licence not read
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Survival analysis was performed with the Kaplan–Meier method, and the log-rank test was used to evaluate the statistical significance of the differences.
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Complete file
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However, the sequential molecular alterations driving the malignant transformation in liver cirrhosis are not clearly defined.In this study, we obtained gene expression profiles of HCC, including 268 tumor tissues, 243 adjacent tumor tissues, and 40 cirrhotic tissues (GSE25097) from Gene Expression Omnibus (GEO), to comprehensively define changes in the transcriptome of HCC during the sequential evolution of liver cirrhosis into HCC.We showed that changes in the molecular profiles of cirrhotic and adjacent tumor samples were small and quite uniform, whereas there was a striking increase in the heterogeneity of tumors in HCC tissues at the mRNA level. A massive deregulation of key oncogenic molecules and pathways was observed from cirrhosis to HCC tumors. In addition, we focused on FOXO1 and DCN, 2 critical tumor suppressor genes that play an important role in liver cirrhosis and HCC development. FOXO1 and DCN expression levels were significantly reduced in tumor tissues compared with adjacent tumor tissues in HCC. Kaplan-Meier analysis revealed that FOXO1 and DCN expression was positively correlated with overall survival, defining FOXO1 and DCN as adverse prognostic biomarkers for HCC.This system-level research provided new insights into the molecular mechanisms of HCC carcinogenesis. 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This lane did not download the dataset or read its licence.", "duration_hours": null, "parameters": {}, "inputs": ["data:geo:GSE22058"], "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:GSE22058"], "outputs": ["the replicated result and its comparison"], "instruments": [], "reagents": []}], "materials": [], "instruments": [], "reagents": [], "conditions": {}, "gaps": []}, "data": {"state": "partial", "assets": [{"id": "source:pmid:29879025", "role": "manuscript", "format": "xml", "media_type": "application/xml", "uri": "https://doi.org/10.1097/MD.0000000000010892", "sha256": 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