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pmid:37313154

Key genes involved with prognosis were identified in lung adenocarcinoma by integrated bioinformatics analysis.

Hao Song · Junfeng Wu · Wang Liu · Kaier Cai · Zhilong Xie · Yingao Liu · Jiandi Huang · Siyuan Gan · Yinghuan Xiong · Yanqin Sun

Heliyon · 2023 doi:10.1016/j.heliyon.2023.e16789

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Experiment

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Data

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pmid:37313154
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title
Key genes involved with prognosis were identified in lung adenocarcinoma by integrated bioinformatics analysis.
doi
10.1016/j.heliyon.2023.e16789
pmid
37313154
authors array · 10 items
[0]
Hao Song
[1]
Junfeng Wu
[2]
Wang Liu
[3]
Kaier Cai
[4]
Zhilong Xie
[5]
Yingao Liu
[6]
Jiandi Huang
[7]
Siyuan Gan
[8]
Yinghuan Xiong
[9]
Yanqin Sun
journal
Heliyon
year
2023
abstract
Objective: By screening the core genes in lung adenocarcinoma (LUAD) with bioinformatics, our study evaluated its prognosis value and role in infiltration process of immune cells. Methods: Using GEO database, we screened 5 gene chips, including GSE11072, GSE32863, GSE43458, GSE115002, and GSE116959. Then, we obtained the corresponding differentially expressed genes by analyzed 5 gene chips online by GEO2R (P < 0.05, |logFC| > 1). Then, through DAVID online platform, Cytoscape 3.6.1 software and PPI network analysis, the network was visualized and obtain the final core genes. Next, we plan to use the GEPIA, UALCAN, Kaplan-Meier plotter and Time 2.0 database for corresponding analysis. The GEPIA database was used to verify the expression of core genes in LUAD and normal lung tissues, and survival analysis was used to evaluate the value of core genes in the prognosis of LUAD patients. UALCAN was used to verify the expression of the LUAD core gene and promoter methylation status, and the predictive value of core genes was evaluated in LUAD patients by the Kaplan-Meier plotter online tool. Then, we used the Time 2.0 database to identify the relationship to immune infiltration in LUAD. Finally, we used the human protein atlas (HPA) database for online immunohistochemical analysis of the expressed proteins. Results: The expression of CCNB2 and CDC20 in LUAD were higher than those in normal lung tissues, their increased expression was negatively correlated with the overall survival rate of LUAD, and they were involved in cell cycle signal transduction, oocyte meiosis signal transduction as well as the infiltration process of immune cells in LUAD. The expression proteins of CCNB2 and CDC20 were also different in lung cancer tissue and normal lung tissue. Therefore, CCNB2 and CDC20 were identified as the vital core genes. Conclusion: CCNB2 and CDC20 are essential genes that may constitute prognostic biomarkers in LUAD, they also participate the immune infiltration process and protein expression process of LUAD, and might provides basis for clinical anti-tumor drug research.
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Five data groups were analyzed online by GEO2R, and through screening, P < 0.05 and |logFC| > 1, and the corresponding differentially expressed genes (DEGs) of the 5 datasets were obtained.
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sections[5] "Data processing" paragraph 2
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Five data groups were analyzed online by GEO2R, and through screening, P < 0.05 and |logFC| > 1, and the corresponding differentially expressed genes (DEGs) of the 5 datasets were obtained.
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sections[31] "References" paragraph 1
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All databases (GEO, DAVID, Venn diagram, STRING, GEPIA database, TIMER 2.0 database, the HPA database) are freely available on the web.
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The five microarray datasets yielded 188 intersecting differentially expressed genes, including 39 upregulated genes and 149 downregulated genes.
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sections[12] "Data identification of LUAD differentially expressed genes" paragraph 2
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A Venn diagram was drawn to obtain the intersection of the five datasets, and we obtained 188 differentially expressed genes (see Table 1), including 39 upregulated genes and 149 downregulated genes (see Fig. 1A and B).
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The five microarray datasets yielded 188 intersecting differentially expressed genes, including 39 upregulated genes and 149 downregulated genes.
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116
group_sizes
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platform
6884
taxon
Homo sapiens
title
Gene expression analysis of lung adenocarcinoma and matched adjacent non-tumor lung tissue
resolution_checked_at
2026-11-01T15:39:54Z
resolution_check
identifier_resolution_only_no_download_no_licence_read
downloaded
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licence_read
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data:geo:GSE43458
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All databases (GEO, DAVID, Venn diagram, STRING, GEPIA database, TIMER 2.0 database, the HPA database) are freely available on the web.
structure object · 15 fields
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GEO
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GEO accession URL
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All databases (GEO, DAVID, Venn diagram, STRING, GEPIA database, TIMER 2.0 database, the HPA database) are freely available on the web.
access_statement_kind
data_availability_statement
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sample_count
110
group_sizes
null
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null
platform
6244
taxon
Homo sapiens
title
Gene expression profiling of lung adenocarcinomas and normal lung tissue
resolution_checked_at
2026-11-01T15:39:54Z
resolution_check
identifier_resolution_only_no_download_no_licence_read
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false
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analysis object · 4 fields
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survival_km
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time_to_event_with_censoring
evidence object · 3 fields
score
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Kaplan-Meier
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network_analysis
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null
specific
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GEO2R differential-expression screening with P < 0.05 and |logFC| > 1
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score
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Five data groups were analyzed online by GEO2R, and through screening, P < 0.05 and |logFC| > 1, and the corresponding differentially expressed genes (DEGs) of the 5 datasets were obtained.
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gaps array · 1 item
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method.reader_named_unmapped
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complete
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gwas
candidate
Automated Assays Laravel application and simulated adapters
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tier
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tier
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statements array · 1 item
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All databases (GEO, DAVID, Venn diagram, STRING, GEPIA database, TIMER 2.0 database, the HPA database) are freely available on the web.
basis
The paper names GSE10072, GSE32863, GSE43458, GSE115002, GSE116959 in GEO and the accession resolves in the repository. No dataset was downloaded and no licence was read.
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survival_km
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minimax
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minimax
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Complete file
{"sci_version": "1.2", "schema": "https://corpus.bntrg.co.uk/sci/1.0/sci.schema.json", "id": "pmid:37313154", "kind": "science-record", "revision": 3, "content_hash": "sha256:0c7a652a3c85fef009ece311cba318a3b57ffc81f9ed8197228149a5a8e3f2f8", "created_at": "2026-11-01T19:02:03Z", "updated_at": "2026-11-01T22:09:41Z", "generator": {"name": "corpus-assay-engine", "run_id": "reading-sci-2026-11-01"}, "paper": {"state": "complete", "title": "Key genes involved with prognosis were identified in lung adenocarcinoma by integrated bioinformatics analysis.", "doi": "10.1016/j.heliyon.2023.e16789", "pmid": "37313154", "authors": ["Hao Song", "Junfeng Wu", "Wang Liu", "Kaier Cai", "Zhilong Xie", "Yingao Liu", "Jiandi Huang", "Siyuan Gan", "Yinghuan Xiong", "Yanqin Sun"], "journal": "Heliyon", "year": 2023, "abstract": "Objective: By screening the core genes in lung adenocarcinoma (LUAD) with bioinformatics, our study evaluated its prognosis value and role in infiltration process of immune cells.\nMethods: Using GEO database, we screened 5 gene chips, including GSE11072, GSE32863, GSE43458, GSE115002, and GSE116959. Then, we obtained the corresponding differentially expressed genes by analyzed 5 gene chips online by GEO2R (P < 0.05, |logFC| > 1). Then, through DAVID online platform, Cytoscape 3.6.1 software and PPI network analysis, the network was visualized and obtain the final core genes. Next, we plan to use the GEPIA, UALCAN, Kaplan-Meier plotter and Time 2.0 database for corresponding analysis. The GEPIA database was used to verify the expression of core genes in LUAD and normal lung tissues, and survival analysis was used to evaluate the value of core genes in the prognosis of LUAD patients. UALCAN was used to verify the expression of the LUAD core gene and promoter methylation status, and the predictive value of core genes was evaluated in LUAD patients by the Kaplan-Meier plotter online tool. Then, we used the Time 2.0 database to identify the relationship to immune infiltration in LUAD. Finally, we used the human protein atlas (HPA) database for online immunohistochemical analysis of the expressed proteins.\nResults: The expression of CCNB2 and CDC20 in LUAD were higher than those in normal lung tissues, their increased expression was negatively correlated with the overall survival rate of LUAD, and they were involved in cell cycle signal transduction, oocyte meiosis signal transduction as well as the infiltration process of immune cells in LUAD. The expression proteins of CCNB2 and CDC20 were also different in lung cancer tissue and normal lung tissue. Therefore, CCNB2 and CDC20 were identified as the vital core genes.\nConclusion: CCNB2 and CDC20 are essential genes that may constitute prognostic biomarkers in LUAD, they also participate the immune infiltration process and protein expression process of LUAD, and might provides basis for clinical anti-tumor drug research.", "claims": [{"id": "claim-method", "statement": "Five data groups were analyzed online by GEO2R, and through screening, P < 0.05 and |logFC| > 1, and the corresponding differentially expressed genes (DEGs) of the 5 datasets were obtained.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:37313154", "locator": "sections[5] \"Data processing\" paragraph 2", "quote": "Five data groups were analyzed online by GEO2R, and through screening, P < 0.05 and |logFC| > 1, and the corresponding differentially expressed genes (DEGs) of the 5 datasets were obtained."}], "state": "complete"}, {"id": "claim-data-access", "statement": "All databases (GEO, DAVID, Venn diagram, STRING, GEPIA database, TIMER 2.0 database, the HPA database) are freely available on the web.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:37313154", "locator": "sections[31] \"References\" paragraph 1", "quote": "All databases (GEO, DAVID, Venn diagram, STRING, GEPIA database, TIMER 2.0 database, the HPA database) are freely available on the web."}], "state": "complete"}, {"id": "claim-target-result", "statement": "The five microarray datasets yielded 188 intersecting differentially expressed genes, including 39 upregulated genes and 149 downregulated genes.", "kind": "qualitative", "target": null, "evidence": [{"asset": "source:pmid:37313154", "locator": "sections[12] \"Data identification of LUAD differentially expressed genes\" paragraph 2", "quote": "A Venn diagram was drawn to obtain the intersection of the five datasets, and we obtained 188 differentially expressed genes (see Table 1), including 39 upregulated genes and 149 downregulated genes (see Fig. 1A and B)."}], "state": "complete"}], "gaps": []}, "experiment": {"state": "complete", "objective": "The five microarray datasets yielded 188 intersecting differentially expressed genes, including 39 upregulated genes and 149 downregulated genes.", "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:37313154"], "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:GSE10072"], "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:GSE10072"], "outputs": ["the replicated result and its comparison"], "instruments": [], "reagents": []}], "materials": [], "instruments": [], "reagents": [], "conditions": {}, "gaps": []}, "data": {"state": "partial", "assets": [{"id": "source:pmid:37313154", "role": "manuscript", "format": "xml", "media_type": "application/xml", "uri": "https://doi.org/10.1016/j.heliyon.2023.e16789", "sha256": 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