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pmid:35600043

NUF2 Is a Potential Immunological and Prognostic Marker for Non-Small-Cell Lung Cancer.

Xia Li · Lianlian Zhang · Zhongquan Yi · Jing Zhou · Wenchun Song · Panwen Zhao · Jixiang Wu · Jianxiang Song · Qinggan Ni

Journal of immunology research · 2022 doi:10.1155/2022/1161931

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Experiment

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Data

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Record details sci_version · id · kind · revision · content_hash · schema · created_at · updated_at · generator
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pmid:35600043
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2026-11-01T18:14:29Z
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2026-11-01T22:49:06Z
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title
NUF2 Is a Potential Immunological and Prognostic Marker for Non-Small-Cell Lung Cancer.
doi
10.1155/2022/1161931
pmid
35600043
authors array · 9 items
[0]
Xia Li
[1]
Lianlian Zhang
[2]
Zhongquan Yi
[3]
Jing Zhou
[4]
Wenchun Song
[5]
Panwen Zhao
[6]
Jixiang Wu
[7]
Jianxiang Song
[8]
Qinggan Ni
journal
Journal of immunology research
year
2022
abstract
Background: Globally, non-small-cell lung cancer (NSCLC) is one of the most prevalent tumors. Various studies have investigated its etiology, but the molecular mechanism of NSCLC has not been elucidated. Methods: The GSE19804, GSE118370, GSE19188, GSE27262, and GSE33532 microarray datasets were obtained from the Gene Expression Omnibus (GEO) database for the identification of genes involved in NSCLC development as well as progression. Then, the identified differentially expressed genes (DEGs) were subjected to functional enrichment analyses. The protein-protein interaction (PPI) network was built after which module analysis was conducted via the Search Tool for Retrieval of Interacting Genes/Proteins (STRING) and Cytoscape. There were 562 DEGs: 98 downregulated genes and 464 upregulated. These DEGs were established to be enriched in p53 signaling pathway, transendothelial leukocyte migration, cell adhesion molecules, contractions of vascular smooth muscles, coagulation and complement cascades, and axon guidance. Assessment of tumor immunity was performed to determine the roles of hub genes. Results: There were 562 dysregulated genes, while 12 genes were hub genes. NUF2 was established to be a candidate immunotherapeutic target with potential clinical implications. The 12 hub genes were highly enriched in the p53 signaling pathway, the cell cycle, progesterone-associated oocyte maturation, cellular senescence, and oocyte meiosis. Survival analysis showed that NUF2 is associated with NSCLC occurrence, invasion, and recurrence. Conclusion: The NUF2 gene discovered in this study helps us clarify the pathomechanisms of NSCLC occurrence as well as progression and provides a potential diagnostic and therapeutic target for NSCLC.
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GEO2R (http://www.ncbi.nlm.nih.gov/geo/geo2r) was used for screening DEGs between NSCLC samples and noncancer samples. Overall survival and disease-free survival analyses of hub genes were performed using the Kaplan-Meier curves in cBioPortal. Between-group differences were evaluated by the two-tailed Student's t-test.
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sections[11] "4.2. Identification DEGS" paragraph 2
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GEO2R (http://www.ncbi.nlm.nih.gov/geo/geo2r) was used for screening DEGs between NSCLC samples and noncancer samples.
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sections[14] "4.5. Hub Gene Selection and Analysis" paragraph 2
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Overall survival and disease-free survival analyses of hub genes were performed using the Kaplan-Meier curves in cBioPortal.
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sections[18] "4.9. Statistical Analysis" paragraph 2
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Between-group differences were evaluated by the two-tailed Student's t-test.
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sections[20] "Data Availability" paragraph 2
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The data sets used and/or analyzed during the current study are available from the corresponding author on reasonable request.
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NSCLC patients with NUF2 genome changes showed the highest hazard ratio and significantly decreased overall survival (HR = 2.01, CI 1.7-2.39, P = 2.4e − 16).
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sections[6] "2.4. Hub Gene Identification and Analysis" paragraph 2
quote
We noticed that NSCLC patients with changes of NUF2-related genes showed decreased overall survival, while NSCLC patients with NUF2 genome changes showed the highest hazard ratio.
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NSCLC patients with NUF2 genome changes showed the highest hazard ratio and significantly decreased overall survival (HR = 2.01, CI 1.7-2.39, P = 2.4e − 16).
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title
Intratumor heterogeneity of gene expression profiles in early stage non-small cell lung cancer (NSCLC)
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GEO2R (http://www.ncbi.nlm.nih.gov/geo/geo2r) was used for screening DEGs between NSCLC samples and noncancer samples. Overall survival and disease-free survival analyses of hub genes were performed using the Kaplan-Meier curves in cBioPortal. Between-group differences were evaluated by the two-tailed Student's t-test.
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[0]
GEO2R (http://www.ncbi.nlm.nih.gov/geo/geo2r) was used for screening DEGs between NSCLC samples and noncancer samples. Overall survival and disease-free survival analyses of hub genes were performed using the Kaplan-Meier curves in cBioPortal. Between-group differences were evaluated by the two-tailed Student's t-test.
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{"sci_version": "1.2", "schema": "https://corpus.bntrg.co.uk/sci/1.0/sci.schema.json", "id": "pmid:35600043", "kind": "science-record", "revision": 5, "content_hash": "sha256:4a612c70565817b3166c9501d97fdc8b81b521d8c813d0c2ed000feeb1c59a8d", "created_at": "2026-11-01T18:14:29Z", "updated_at": "2026-11-01T22:49:06Z", "generator": {"name": "corpus-assay-engine", "run_id": "reading-sci-2026-11-01"}, "paper": {"state": "complete", "title": "NUF2 Is a Potential Immunological and Prognostic Marker for Non-Small-Cell Lung Cancer.", "doi": "10.1155/2022/1161931", "pmid": "35600043", "authors": ["Xia Li", "Lianlian Zhang", "Zhongquan Yi", "Jing Zhou", "Wenchun Song", "Panwen Zhao", "Jixiang Wu", "Jianxiang Song", "Qinggan Ni"], "journal": "Journal of immunology research", "year": 2022, "abstract": "Background: Globally, non-small-cell lung cancer (NSCLC) is one of the most prevalent tumors. Various studies have investigated its etiology, but the molecular mechanism of NSCLC has not been elucidated.\nMethods: The GSE19804, GSE118370, GSE19188, GSE27262, and GSE33532 microarray datasets were obtained from the Gene Expression Omnibus (GEO) database for the identification of genes involved in NSCLC development as well as progression. Then, the identified differentially expressed genes (DEGs) were subjected to functional enrichment analyses. The protein-protein interaction (PPI) network was built after which module analysis was conducted via the Search Tool for Retrieval of Interacting Genes/Proteins (STRING) and Cytoscape. There were 562 DEGs: 98 downregulated genes and 464 upregulated. These DEGs were established to be enriched in p53 signaling pathway, transendothelial leukocyte migration, cell adhesion molecules, contractions of vascular smooth muscles, coagulation and complement cascades, and axon guidance. Assessment of tumor immunity was performed to determine the roles of hub genes.\nResults: There were 562 dysregulated genes, while 12 genes were hub genes. NUF2 was established to be a candidate immunotherapeutic target with potential clinical implications. The 12 hub genes were highly enriched in the p53 signaling pathway, the cell cycle, progesterone-associated oocyte maturation, cellular senescence, and oocyte meiosis. Survival analysis showed that NUF2 is associated with NSCLC occurrence, invasion, and recurrence.\nConclusion: The NUF2 gene discovered in this study helps us clarify the pathomechanisms of NSCLC occurrence as well as progression and provides a potential diagnostic and therapeutic target for NSCLC.", "claims": [{"id": "claim-method", "statement": "GEO2R (http://www.ncbi.nlm.nih.gov/geo/geo2r) was used for screening DEGs between NSCLC samples and noncancer samples. Overall survival and disease-free survival analyses of hub genes were performed using the Kaplan-Meier curves in cBioPortal. Between-group differences were evaluated by the two-tailed Student's t-test.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:35600043", "locator": "sections[11] \"4.2. Identification DEGS\" paragraph 2", "quote": "GEO2R (http://www.ncbi.nlm.nih.gov/geo/geo2r) was used for screening DEGs between NSCLC samples and noncancer samples."}, {"asset": "source:pmid:35600043", "locator": "sections[14] \"4.5. Hub Gene Selection and Analysis\" paragraph 2", "quote": "Overall survival and disease-free survival analyses of hub genes were performed using the Kaplan-Meier curves in cBioPortal."}, {"asset": "source:pmid:35600043", "locator": "sections[18] \"4.9. Statistical Analysis\" paragraph 2", "quote": "Between-group differences were evaluated by the two-tailed Student's t-test."}], "state": "complete"}, {"id": "claim-data-access", "statement": "The data sets used and/or analyzed during the current study are available from the corresponding author on reasonable request.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:35600043", "locator": "sections[20] \"Data Availability\" paragraph 2", "quote": "The data sets used and/or analyzed during the current study are available from the corresponding author on reasonable request."}], "state": "complete"}, {"id": "claim-target-result", "statement": "NSCLC patients with NUF2 genome changes showed the highest hazard ratio and significantly decreased overall survival (HR = 2.01, CI 1.7-2.39, P = 2.4e − 16).", "kind": "qualitative", "target": null, "evidence": [{"asset": "source:pmid:35600043", "locator": "sections[6] \"2.4. Hub Gene Identification and Analysis\" paragraph 2", "quote": "We noticed that NSCLC patients with changes of NUF2-related genes showed decreased overall survival, while NSCLC patients with NUF2 genome changes showed the highest hazard ratio."}], "state": "complete"}], "gaps": []}, "experiment": {"state": "partial", "objective": "NSCLC patients with NUF2 genome changes showed the highest hazard ratio and significantly decreased overall survival (HR = 2.01, CI 1.7-2.39, P = 2.4e − 16).", "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:35600043"], "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:GSE118370"], "outputs": ["the source data with its repository provenance"], "instruments": [], "reagents": []}, {"id": "run_analysis", "order": 3, "name": "Run the published analysis", "kind": "analysis", "state": "blocked", "blocked_on": "method:student_t", "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:GSE118370"], "outputs": ["the replicated result and its comparison"], "instruments": [], "reagents": []}], "materials": [], "instruments": [], "reagents": [], "conditions": {}, "gaps": ["step:run_analysis blocked on method:student_t"]}, "data": {"state": "partial", "assets": [{"id": "source:pmid:35600043", "role": "manuscript", "format": "xml", "media_type": "application/xml", "uri": 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