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pmid:33447084

Identification of Hub Genes as Potential Prognostic Biomarkers in Cervical Cancer Using Comprehensive Bioinformatics Analysis and Validation Studies.

Han Xue · Zhaojun Sun · Weiqing Wu · Dong Du · Shuping Liao

Cancer management and research · 2021 doi:10.2147/CMAR.S282989

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Experiment

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Data

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2026-11-01T15:41:22Z
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title
Identification of Hub Genes as Potential Prognostic Biomarkers in Cervical Cancer Using Comprehensive Bioinformatics Analysis and Validation Studies.
doi
10.2147/CMAR.S282989
pmid
33447084
authors array · 5 items
[0]
Han Xue
[1]
Zhaojun Sun
[2]
Weiqing Wu
[3]
Dong Du
[4]
Shuping Liao
journal
Cancer management and research
year
2021
abstract
BACKGROUND: Cervical cancer belongs to one of the most common female cancers; yet, the exact underlying mechanisms are still elusive. Recently, microarray and sequencing technologies have been widely used for screening biomarkers and molecular mechanism discovery in cancer studies. In this study, we aimed to analyse the microarray datasets using comprehensive bioinformatics tools and identified novel biomarkers associated with the prognosis of patients with cervical cancer. METHODS: The differentially expressed genes (DEGs) from Gene Expression Omnibus (GEO) datasets including GSE138080, GSE113942 and GSE63514 were analysed using GEO2R tool. The functional enrichment analysis was performed using g:Profiler tool. The protein-protein interaction (PPI) network construction and hub genes identification were performed using the STRING database and Cytoscape software, respectively. The hub genes were subjected to expression and survival analysis in the cervical cancer. The EdU incorporation and Cell Counting Kit-8 assays were performed to evaluate the effects of hub gene knockdown on the proliferation of cervical cancer cells. RESULTS: A total of 89 overlapping DEGs (63 up-regulated and 26 down-regulated genes) were identified in the microarray datasets. The functional enrichment analysis indicated that the overlapping DEGs were mainly associated with "DNA replication" and "cell cycle". Furthermore, the PPI network analysis revealed that the network contains 87 nodes and 309 edges. Sub-module analysis using the Molecular Complex Detection tool identified 21 hub genes from the PPI network. The expression levels of the 21 hub genes were all up-regulated in the cervical cancer tissues when compared to normal cervical tissues as analysed by GEPIA tool. The survival analysis showed that the low expression of cell division cycle 45 (CDC45), GINS complex subunit 2 (GINS2), minichromosome maintenance complex component 2 (MCM2) and proliferating cell nuclear antigen (PCNA) was significantly correlated with the shorter overall survival of patients with cervical cancer. Moreover, the protein expression levels of GINS2, MCM2 and PCNA, but not CDC45, were significantly up-regulated in the cervical cancer tissues when compared to normal cervical tissues. Finally, knockdown of MCM2 significantly suppressed the proliferation of HeLa and SiHa cells. CONCLUSION: In conclusion, we screened a total of 89 overlapping DEGs from the GEO datasets, and further analysis identified four hub genes (CDC45, GINS2, MCM2 and PCNA) that were likely associated with the prognosis of patients with cervical cancer. MCM2 knockdown repressed the cervical cancer cell proliferation. The current findings may provide novel insights into understanding the pathophysiology of cervical cancer and develop therapeutic targets for patients with cervical cancer.
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sections[8] "Survival Analysis of Hub Genes in Cervical Cancer" paragraph 2
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Log rank P < 0.05 was considered to be statistically significant.
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By searching the GEO database using “cervical cancer” as the keywords, three microarray datasets including GSE138080, GSE113942 and GSE63514 were downloaded for analysis in this study. The platform for GSE138080 is GPL4133, Agilent-014850 Whole Human Genome Microarray 4x44K G4112F (Feature Number version), which contains 10 normal cervical samples and 10 cervical cancer specimens
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ying mechanisms are still elusive. Recently, microarray and sequencing technologies have been widely
[1]
dies. In this study, we aimed to analyse the microarray datasets using comprehensive bioinformatics
[2]
down-regulated genes) were identified in the microarray datasets. The functional enrichment analysis
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erformed to evaluate the effects of hub gene knockdown on the proliferation of cervical cancer cell
[1]
ompared to normal cervical tissues. Finally, knockdown of MCM2 significantly suppressed the prolife
[2]
nosis of patients with cervical cancer. MCM2 knockdown repressed the cervical cancer cell prolifera
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ignificantly suppressed the proliferation of HeLa and SiHa cells. CONCLUSION: In conclusion, w
[1]
m ATCC (ATCC, USA). HeLa and SiHa cells were cultured in DMEM medium supplemented with 10% fetal bovi
[2]
ulture Two human cervical cancer cell lines (HeLa and SiHa) were obtained from ATCC (ATCC, USA
[3]
d SiHa) were obtained from ATCC (ATCC, USA). HeLa and SiHa cells were cultured in DMEM medium
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and normal cervical tissues was evaluated by immunohistochemistry using the Human Protein Atlas database; as s
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Complete file
{"sci_version": "1.2", "schema": "https://corpus.bntrg.co.uk/sci/1.0/sci.schema.json", "id": "pmid:33447084", "kind": "science-record", "revision": 8, "content_hash": "sha256:ffd38f6a7ddfe2cda04583e5cb037ebb228c1d4be0ff6dfb262a028afdc10311", "created_at": "2026-11-01T15:41:22Z", "updated_at": "2026-11-01T22:02:57Z", "generator": {"name": "corpus-assay-engine", "run_id": "reading-sci-2026-11-01"}, "paper": {"state": "complete", "title": "Identification of Hub Genes as Potential Prognostic Biomarkers in Cervical Cancer Using Comprehensive Bioinformatics Analysis and Validation Studies.", "doi": "10.2147/CMAR.S282989", "pmid": "33447084", "authors": ["Han Xue", "Zhaojun Sun", "Weiqing Wu", "Dong Du", "Shuping Liao"], "journal": "Cancer management and research", "year": 2021, "abstract": "BACKGROUND: Cervical cancer belongs to one of the most common female cancers; yet, the exact underlying mechanisms are still elusive. Recently, microarray and sequencing technologies have been widely used for screening biomarkers and molecular mechanism discovery in cancer studies. In this study, we aimed to analyse the microarray datasets using comprehensive bioinformatics tools and identified novel biomarkers associated with the prognosis of patients with cervical cancer.\nMETHODS: The differentially expressed genes (DEGs) from Gene Expression Omnibus (GEO) datasets including GSE138080, GSE113942 and GSE63514 were analysed using GEO2R tool. The functional enrichment analysis was performed using g:Profiler tool. The protein-protein interaction (PPI) network construction and hub genes identification were performed using the STRING database and Cytoscape software, respectively. The hub genes were subjected to expression and survival analysis in the cervical cancer. The EdU incorporation and Cell Counting Kit-8 assays were performed to evaluate the effects of hub gene knockdown on the proliferation of cervical cancer cells.\nRESULTS: A total of 89 overlapping DEGs (63 up-regulated and 26 down-regulated genes) were identified in the microarray datasets. The functional enrichment analysis indicated that the overlapping DEGs were mainly associated with \"DNA replication\" and \"cell cycle\". Furthermore, the PPI network analysis revealed that the network contains 87 nodes and 309 edges. Sub-module analysis using the Molecular Complex Detection tool identified 21 hub genes from the PPI network. The expression levels of the 21 hub genes were all up-regulated in the cervical cancer tissues when compared to normal cervical tissues as analysed by GEPIA tool. The survival analysis showed that the low expression of cell division cycle 45 (CDC45), GINS complex subunit 2 (GINS2), minichromosome maintenance complex component 2 (MCM2) and proliferating cell nuclear antigen (PCNA) was significantly correlated with the shorter overall survival of patients with cervical cancer. Moreover, the protein expression levels of GINS2, MCM2 and PCNA, but not CDC45, were significantly up-regulated in the cervical cancer tissues when compared to normal cervical tissues. Finally, knockdown of MCM2 significantly suppressed the proliferation of HeLa and SiHa cells.\nCONCLUSION: In conclusion, we screened a total of 89 overlapping DEGs from the GEO datasets, and further analysis identified four hub genes (CDC45, GINS2, MCM2 and PCNA) that were likely associated with the prognosis of patients with cervical cancer. MCM2 knockdown repressed the cervical cancer cell proliferation. 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No dataset was downloaded and no licence was read."}}, "can_run": {"dsl_operations": ["logrank_test"], "assets": ["source:pmid:33447084", "data:geo:GSE113942"], "steps": ["run_analysis"]}, "must_build": {"dsl_operations": [], "converters": [], "readers": [], "capabilities": [], "data_gaps": ["data:geo:GSE113942"]}, "gaps": []}, "review": {"state": "partial", "machine_critique": {"kind": "extraction_review", "reader": {"model": "MiniMax-M3.1-Flash", "provider": "minimax", "provider_family": "minimax", "read_at": "2026-10-31T18:26:12Z", "independence": "single_reader"}, "evidence_check": {"method": "verbatim", "availability": null}, "calls": 3, "usage": {"prompt_tokens": 32800, "completion_tokens": 2694, "cached_tokens": 11016}}, "human_critique": null, "stages": [{"id": "extraction", "state": "complete", "reader": "MiniMax-M3.1-Flash", "provider": "minimax"}], "gaps": ["review.independent_reader", "review.machine_critique", "review.human_critique"]}, "execution": {"state": "absent", "status": "not_run", "mode": null, "runs": [], "gaps": ["execution.not_run"]}, "provenance": {"entities": [{"id": "pmid:33447084", "type": "paper", "label": "pmid:33447084"}, {"id": "source:pmid:33447084", "type": "manuscript", "label": "PMID 33447084 full text"}, {"id": "data:geo:GSE113942", "type": "dataset", "label": "GEO GSE113942"}], "activities": [{"id": "activity-reading-sci-2026-11-01", "type": "classification", "used": [{"id": "pmid:33447084", "type": "paper", "label": "pmid:33447084"}, {"id": "source:pmid:33447084", "type": "manuscript", "label": "PMID 33447084 full text"}, {"id": "data:geo:GSE113942", "type": "dataset", "label": "GEO GSE113942"}], "agent": "agent:corpus-assay-engine"}, {"id": "activity-read-33447084", "type": "extraction", "used": ["source:pmid:33447084"], "agent": "agent:minimax-reader"}, {"id": "activity-resolve-GSE113942", "type": "accession_resolution", "used": ["data:geo:GSE113942"], "agent": "agent:corpus-assay-engine"}], "agents": [{"id": "agent:corpus-assay-engine", "type": "software", "label": "Corpus assay engine"}, {"id": "agent:minimax-reader", "type": "software", "label": "MiniMax literature reader"}], "source_run_id": "reading-sci-2026-11-01", "dsl_catalogue_fingerprint": "343fb30756ba6ec3", "capability_table_fingerprint": "2cb3e42f047d2ecf", "snapshot_id": "ba34b49490d9bfaf"}, "lineage": {"parent_id": "pmid:33447084", "parent_hash": "sha256:1e297e88b7010975bf7a7587d56a30adb040a299f8e07dccedd24952fa6560ca", "fork_of": null, "generation": 7}, "gaps": ["asset:data:geo:GSE113942 licence not read", "asset:data:geo:GSE113942 not downloaded", "asset:data:geo:GSE138080 licence not read", "asset:data:geo:GSE138080 not downloaded", "asset:data:geo:GSE63514 licence not read", "asset:data:geo:GSE63514 not downloaded", "execution.not_run", "method.reader_differs_from_extractor", "review.human_critique", "review.independent_reader", "review.machine_critique"], "assays": [{"role": "data_generation", "definition_id": "microarray", "definition_version": "99e1195c7d6f", "definition_digest": null, "required_operations": [], "support_state": "partial", "source_hashes": {"assay_lexicon": "99e1195c7d6f"}, "confidence": 0.99, "evidence": ["ying mechanisms are still elusive. Recently, microarray and sequencing technologies have been widely", "dies. In this study, we aimed to analyse the microarray datasets using comprehensive bioinformatics", "down-regulated genes) were identified in the microarray datasets. The functional enrichment analysis"], "order_basis": "paper_text_order:249", "id": "assay:1"}, {"role": "data_generation", "definition_id": "transfection", "definition_version": "99e1195c7d6f", "definition_digest": null, "required_operations": [], "support_state": "partial", "source_hashes": {"assay_lexicon": "99e1195c7d6f"}, "confidence": 0.99, "evidence": ["erformed to evaluate the effects of hub gene knockdown on the proliferation of cervical cancer cell", "ompared to normal cervical tissues. Finally, knockdown of MCM2 significantly suppressed the prolife", "nosis of patients with cervical cancer. MCM2 knockdown repressed the cervical cancer cell prolifera"], "order_basis": "paper_text_order:1187", "id": "assay:2"}, {"role": "data_generation", "definition_id": "cell_culture", "definition_version": "99e1195c7d6f", "definition_digest": null, "required_operations": [], "support_state": "partial", "source_hashes": {"assay_lexicon": "99e1195c7d6f"}, "confidence": 0.99, "evidence": ["ignificantly suppressed the proliferation of HeLa and SiHa cells. CONCLUSION: In conclusion, w", "m ATCC (ATCC, USA). HeLa and SiHa cells were cultured in DMEM medium supplemented with 10% fetal bovi", "ulture Two human cervical cancer cell lines (HeLa and SiHa) were obtained from ATCC (ATCC, USA", "d SiHa) were obtained from ATCC (ATCC, USA). HeLa and SiHa cells were cultured in DMEM medium"], "order_basis": "paper_text_order:2453", "id": "assay:3"}, {"role": "data_generation", "definition_id": "ihc", "definition_version": "99e1195c7d6f", "definition_digest": null, "required_operations": [], "support_state": "partial", "source_hashes": {"assay_lexicon": "99e1195c7d6f"}, "confidence": 0.93, "evidence": ["and normal cervical tissues was evaluated by immunohistochemistry using the Human Protein Atlas database; as s"], "order_basis": "paper_text_order:8340", "id": "assay:4"}, {"role": "analysis", "definition_id": "survival_analysis", "definition_version": "f2132e96ae6c7a4e", "definition_digest": null, "required_operations": ["logrank_test"], "support_state": "supported", "source_hashes": {"dsl_catalogue": "f2132e96ae6c7a4e"}, "confidence": 1.0, "evidence": ["Log rank P < 0.05 was considered to be statistically significant."], "order_basis": "consumes_earlier_output", "id": "assay:5"}]}