The identification of hub biomarkers and pathways in lung cancer and prognostic evaluation.

{"sci_version": "1.2", "schema": "https://corpus.bntrg.co.uk/sci/1.0/sci.schema.json", "id": "pmid:36093542", "kind": "science-record", "revision": 4, "content_hash": "sha256:209775ac6816ca2b12b47a08fa6dbbfd9f62303957f068d499491a13683cb677", "created_at": "2026-11-01T18:15:20Z", "updated_at": "2026-11-01T22:07:32Z", "generator": {"name": "corpus-assay-engine", "run_id": "reading-sci-2026-11-01"}, "paper": {"state": "complete", "title": "The identification of hub biomarkers and pathways in lung cancer and prognostic evaluation.", "doi": "10.21037/tcr-22-245", "pmid": "36093542", "authors": ["Yi Yin", "Dong Li", "Muqun He", "Jianfeng Wang"], "journal": "Translational cancer research", "year": 2022, "abstract": "Background: Lung cancer is the most frequently diagnosed malignant tumor and the highest mortality worldwide, and can be divided into two differential histologic subtypes, non-small cell lung cancer (NSCLC) and small cell lung cancer (SCLC). However, there are significant differences in diagnosis and prognosis between NSCLC and SCLC. We aimed to identify hub differentially expressed genes (DEGs) and pathways for diagnostic and prognostic prediction in NSCLC and SCLC.\nMethods: Three expression profiles (GSE43346, GSE40275 and GSE18842) were obtained through GEO2R tools from Gene Expression Omnibus (GEO) database. The Database for Annotation, Visualization, and Integrated Discovery (DAVID) was used to investigate functional enrichment of the DEGs. The protein-protein interaction network was constructed by the Search Tool for the Retrieval of Interacting Genes (STRING) and Cytoscape. Kaplan-Meier analysis was performed using Kaplan-Meier plotter and Gene Expression Profiling Interactive Analysis (GEPIA).\nResults: We have identified 84 overlap DEGs that may play an important role in SCLC & NSCLC. However, we also found some genes were only significantly differential expressed in SCLC or NSCLC. There were 87 DEGs unique to SCLC tissues and 28 DEGs unique to NSCLC ones. Functional analysis results indicated that these DEGs had different biological functions and were significantly enriched in different pathways. Hub DEGs were identified via protein-protein interaction network and cross-validated using Kaplan-Meier plotter and GEPIA. The 14 hub DEGs were highly correlated with the overall survival of NSCLC. Kyoto Encyclopedia of Genes and Genome (KEGG) re-analysis of 14 hub DEGs showed that RRM2, CHEK1 and SERPINB5 enriched in the p53 signaling pathway, RRM2 and TYMS enriched in pyrimidine metabolism pathway maybe play a key role in SCLC&NSCLC and were significantly related to overall survival in patients with NSCLC.\nConclusions: RRM2, CHEK1, TYMS and SERPINB5, which are mainly enriched in the p53 signaling pathway and pyrimidine metabolism pathway, were significantly associated with the overall survival of NSCLC patients. These genes could serve as potential prognostic markers in NSCLC and therapeutic target in lung cancer for personalized oncology.", "claims": [{"id": "claim-method", "statement": "Kaplan-Meier analysis was performed using Kaplan-Meier plotter and Gene Expression Profiling Interactive Analysis (GEPIA).", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:36093542", "locator": "sections[0] \"Abstract\" paragraph 2", "quote": "Kaplan-Meier analysis was performed using Kaplan-Meier plotter and Gene Expression Profiling Interactive Analysis (GEPIA)."}], "state": "complete"}, {"id": "claim-data-access", "statement": "GSE43346 contains 42 normal tissue samples and 23 SCLC samples.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:36093542", "locator": "sections[3] \"Microarray data and identification of DEGs\" paragraph 2", "quote": "GSE43346 contains 42 normal tissue samples and 23 SCLC samples."}], "state": "complete"}, {"id": "claim-target-result", "statement": "RRM2, CHEK1, TYMS and SERPINB5, which are mainly enriched in the p53 signaling pathway and pyrimidine metabolism pathway, were significantly associated with the overall survival of NSCLC patients.", "kind": "qualitative", "target": null, "evidence": [{"asset": "source:pmid:36093542", "locator": "sections[0] \"Abstract\" paragraph 4", "quote": "RRM2, CHEK1, TYMS and SERPINB5, which are mainly enriched in the p53 signaling pathway and pyrimidine metabolism pathway, were significantly associated with the overall survival of NSCLC patients."}], "state": "complete"}], "gaps": []}, "experiment": {"state": "complete", "objective": "RRM2, CHEK1, TYMS and SERPINB5, which are mainly enriched in the p53 signaling pathway and pyrimidine metabolism pathway, were significantly associated with the overall survival of NSCLC patients.", "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:36093542"], "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:GSE18842"], "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:GSE18842"], "outputs": ["the replicated result and its comparison"], "instruments": [], "reagents": []}], "materials": [], "instruments": [], "reagents": [], "conditions": {}, "gaps": []}, "data": {"state": "partial", "assets": [{"id": "source:pmid:36093542", "role": "manuscript", "format": "xml", "media_type": "application/xml", "uri": "https://doi.org/10.21037/tcr-22-245", "sha256": 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