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pmid:39874008

Biomarker Panels Associated with Diagnosis and Overall Survival in Hepatocellular Carcinoma Revealed from Protein-Protein and mRNA-miRNA Interaction Networks.

Reyhaneh Farrokhi Yekta · Mostafa Rezaei Tavirani · Afsaneh Arefi Oskouie · Nasrin Amiri-Dashatan

Asian Pacific journal of cancer prevention : APJCP · 2025 doi:10.31557/APJCP.2025.26.1.249

Paper

complete

Experiment

complete

Data

partial

Analysis

complete

Execution

absent

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Record details sci_version · id · kind · revision · content_hash · schema · created_at · updated_at · generator
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pmid:39874008
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science-record
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2026-11-01T20:30:09Z
updated_at
2026-11-01T22:56:03Z
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paper object · 10 fields
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title
Biomarker Panels Associated with Diagnosis and Overall Survival in Hepatocellular Carcinoma Revealed from Protein-Protein and mRNA-miRNA Interaction Networks.
doi
10.31557/APJCP.2025.26.1.249
pmid
39874008
authors array · 4 items
[0]
Reyhaneh Farrokhi Yekta
[1]
Mostafa Rezaei Tavirani
[2]
Afsaneh Arefi Oskouie
[3]
Nasrin Amiri-Dashatan
journal
Asian Pacific journal of cancer prevention : APJCP
year
2025
abstract
BACKGROUND: Hepatocellular carcinoma (HCC), the most common form of liver cancer, has a significant mortality rate, largely due to late diagnosis. Recent advances in medical research have demonstrated the potential of biomarkers for early detection. Moreover, the discovery and use of prognostic biomarkers offer a ray of hope in the fight against liver cancer. METHODS: Three gene transcript collections (GSE57957, GSE76427, and GSE84402) were retrieved from the GEO database, and significantly expressed genes were identified through a comprehensive screening process. Subsequently, key potential biomarkers were identified using various methods, including functional pathway enrichment, protein-protein interaction network analysis, mRNA-miR interaction study, and ROC curve and survival analysis. RESULTS: After analyzing the expression of hub proteins and miRs, 12 proteins were found to have AUC values greater than 0.9 and log-rank KM-plot p values less than 0.05. Therefore, these proteins can be considered as potential diagnostic and prognostic biomarkers. Among these proteins, the top 5 were CDC6, PTTG1, CDCA5, RACGAP1, and RAD51AP1. The microRNAs with the highest diagnostic significance (AUC≥0.8) were hsa-mir-101-3p, hsa-mir-195-5p, hsa-mir-130a-3p, hsa-mir-26b-5p, hsa-mir-29c-3p, hsa-mir-26a-5p, and hsa-mir-34a-5p. Notably, hsa-mir-34a-5p, hsa-mir-195-5p, and hsa-mir-130a-3p also showed prognostic potential as predictors of overall survival in HCC patients. CONCLUSION: Harnessing the potential of these biomarkers will enable healthcare professionals to make informed decisions, leading to improved care and more favorable outcomes in the fight against HCC. However, the next step is to thoroughly validate these potential markers in large cohorts.
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Proteins showing significant correlation with overall survival were identified using Kaplan-Meier survival curves.
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sections[9] "Survival analysis" paragraph 2
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Proteins showing significant correlation with overall survival were identified using Kaplan-Meier survival curves.
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The three gene transcriptome datasets used in this study were GSE57957, GSE76427, and GSE84402 [17-19].
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sections[3] "Microarray datasets and data analysis" paragraph 2
quote
The three gene transcriptome datasets used in this study were GSE57957, GSE76427, and GSE84402 [17-19].
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After analyzing the expression of hub proteins and miRs, 12 proteins were found to have AUC values greater than 0.9 and log-rank KM-plot p values less than 0.05.
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qualitative
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null
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sections[0] "Abstract" paragraph 3
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After analyzing the expression of hub proteins and miRs, 12 proteins were found to have AUC values greater than 0.9 and log-rank KM-plot p values less than 0.05.
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After analyzing the expression of hub proteins and miRs, 12 proteins were found to have AUC values greater than 0.9 and log-rank KM-plot p values less than 0.05.
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Expression profile of Hepatocellular Carcinoma
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title
Microarray expression data for tumor and adjacent non-tumor tissues from hepatocellular carcinoma patients
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Proteins showing significant correlation with overall survival were identified using Kaplan-Meier survival curves.
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pmid:39874008
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source:pmid:39874008
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manuscript
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PMID 39874008 full text
[2] object · 3 fields
id
data:geo:GSE57957
type
dataset
label
GEO GSE57957
agent
agent:corpus-assay-engine
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activity-read-39874008
type
extraction
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source:pmid:39874008
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agent:minimax-reader
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activity-resolve-GSE57957
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accession_resolution
used array · 1 item
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data:geo:GSE57957
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agent:corpus-assay-engine
agents array · 2 items
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agent:corpus-assay-engine
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agent:minimax-reader
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software
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capability_table_fingerprint
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lineage object · 4 fields
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null
gaps array · 8 items
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[2]
asset:data:geo:GSE76427 licence not read
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review.human_critique
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review.independent_reader
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assays array · 1 item
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dsl_catalogue
f2132e96ae6c7a4e
evidence array · 1 item
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Proteins showing significant correlation with overall survival were identified using Kaplan-Meier survival curves.
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Complete file
{"sci_version": "1.2", "schema": "https://corpus.bntrg.co.uk/sci/1.0/sci.schema.json", "id": "pmid:39874008", "kind": "science-record", "revision": 4, "content_hash": "sha256:ccd50d2751cc657d20a10e0f3dd3317a929ca29b49bc3a73382ff246b0e41890", "created_at": "2026-11-01T20:30:09Z", "updated_at": "2026-11-01T22:56:03Z", "generator": {"name": "corpus-assay-engine", "run_id": "reading-sci-2026-11-01"}, "paper": {"state": "complete", "title": "Biomarker Panels Associated with Diagnosis and Overall Survival in Hepatocellular Carcinoma Revealed from Protein-Protein and mRNA-miRNA Interaction Networks.", "doi": "10.31557/APJCP.2025.26.1.249", "pmid": "39874008", "authors": ["Reyhaneh Farrokhi Yekta", "Mostafa Rezaei Tavirani", "Afsaneh Arefi Oskouie", "Nasrin Amiri-Dashatan"], "journal": "Asian Pacific journal of cancer prevention : APJCP", "year": 2025, "abstract": "BACKGROUND: Hepatocellular carcinoma (HCC), the most common form of liver cancer, has a significant mortality rate, largely due to late diagnosis. Recent advances in medical research have demonstrated the potential of biomarkers for early detection. Moreover, the discovery and use of prognostic biomarkers offer a ray of hope in the fight against liver cancer.\nMETHODS: Three gene transcript collections (GSE57957, GSE76427, and GSE84402) were retrieved from the GEO database, and significantly expressed genes were identified through a comprehensive screening process. Subsequently, key potential biomarkers were identified using various methods, including functional pathway enrichment, protein-protein interaction network analysis, mRNA-miR interaction study, and ROC curve and survival analysis.\nRESULTS: After analyzing the expression of hub proteins and miRs, 12 proteins were found to have AUC values greater than 0.9 and log-rank KM-plot p values less than 0.05. Therefore, these proteins can be considered as potential diagnostic and prognostic biomarkers. Among these proteins, the top 5 were CDC6, PTTG1, CDCA5, RACGAP1, and RAD51AP1. The microRNAs with the highest diagnostic significance (AUC≥0.8) were hsa-mir-101-3p, hsa-mir-195-5p, hsa-mir-130a-3p, hsa-mir-26b-5p, hsa-mir-29c-3p, hsa-mir-26a-5p, and hsa-mir-34a-5p. Notably, hsa-mir-34a-5p, hsa-mir-195-5p, and hsa-mir-130a-3p also showed prognostic potential as predictors of overall survival in HCC patients.\nCONCLUSION: Harnessing the potential of these biomarkers will enable healthcare professionals to make informed decisions, leading to improved care and more favorable outcomes in the fight against HCC. However, the next step is to thoroughly validate these potential markers in large cohorts.", "claims": [{"id": "claim-method", "statement": "Proteins showing significant correlation with overall survival were identified using Kaplan-Meier survival curves.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:39874008", "locator": "sections[9] \"Survival analysis\" paragraph 2", "quote": "Proteins showing significant correlation with overall survival were identified using Kaplan-Meier survival curves."}], "state": "complete"}, {"id": "claim-data-access", "statement": "The three gene transcriptome datasets used in this study were GSE57957, GSE76427, and GSE84402 [17-19].", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:39874008", "locator": "sections[3] \"Microarray datasets and data analysis\" paragraph 2", "quote": "The three gene transcriptome datasets used in this study were GSE57957, GSE76427, and GSE84402 [17-19]."}], "state": "complete"}, {"id": "claim-target-result", "statement": "After analyzing the expression of hub proteins and miRs, 12 proteins were found to have AUC values greater than 0.9 and log-rank KM-plot p values less than 0.05.", "kind": "qualitative", "target": null, "evidence": [{"asset": "source:pmid:39874008", "locator": "sections[0] \"Abstract\" paragraph 3", "quote": "After analyzing the expression of hub proteins and miRs, 12 proteins were found to have AUC values greater than 0.9 and log-rank KM-plot p values less than 0.05."}], "state": "complete"}], "gaps": []}, "experiment": {"state": "complete", "objective": "After analyzing the expression of hub proteins and miRs, 12 proteins were found to have AUC values greater than 0.9 and log-rank KM-plot p values less than 0.05.", "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:39874008"], "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:GSE57957"], "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:GSE57957"], "outputs": ["the replicated result and its comparison"], "instruments": [], "reagents": []}], "materials": [], "instruments": [], "reagents": [], "conditions": {}, "gaps": []}, "data": {"state": "partial", "assets": [{"id": "source:pmid:39874008", "role": "manuscript", "format": "xml", "media_type": "application/xml", "uri": "https://doi.org/10.31557/APJCP.2025.26.1.249", "sha256": 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