Identification of a novel 10 immune-related genes signature as a prognostic biomarker panel for gastric cancer.

{"sci_version": "1.2", "schema": "https://corpus.bntrg.co.uk/sci/1.0/sci.schema.json", "id": "pmid:34382341", "kind": "science-record", "revision": 4, "content_hash": "sha256:577355727bf230c66a6396e4594ee3c724cfa2bb116d16fe1f5d12371c136c90", "created_at": "2026-11-01T15:41:47Z", "updated_at": "2026-11-01T21:26:00Z", "generator": {"name": "corpus-assay-engine", "run_id": "reading-sci-2026-11-01"}, "paper": {"state": "complete", "title": "Identification of a novel 10 immune-related genes signature as a prognostic biomarker panel for gastric cancer.", "doi": "10.1002/cam4.4180", "pmid": "34382341", "authors": ["Tingna Chen", "Chaogang Yang", "Rongzhang Dou", "Bin Xiong"], "journal": "Cancer medicine", "year": 2021, "abstract": "BACKGROUND: Emerging evidence indicates that immune infiltrating cells in tumor microenvironment (TME) correlates with the development and progression of gastric cancer (GC). This study aimed to systematically investigate the immune-related genes (IRGs) to develop a prognostic signature to predict the overall survival (OS) in GC.\nMETHOD: The gene expression profiles of training dataset (GSE62254), validation dataset I (GSE15459), and validation dataset II (GSE84437) were retrieved from GEO and TCGA databases. In the present study, we developed a 10 IRGs prognostic signature with the combination of weighted gene co-expression network analysis (WGCNA) and least absolute shrinkage and selection operator method (LASSO) COX model.\nRESULTS: In the training dataset, the accuracy of the signature was 0.681, 0.741, and 0.72 in predicting 1, 3, and 5-year OS separately. The signature also had good performance in validation dataset Ⅰ with the accuracy of 0.57, 0.619, and 0.694, and in validation dataset Ⅱ with the accuracy of 0.559, 0.624, and 0.585. Then, we constructed a nomogram using the signature and clinical information which had strong discrimination ability with the c-index of 0.756. In the immune infiltration analysis, the signature was correlated with multiple immune infiltrating cells such as CD8 T cells, CD4 memory T cells, NK cells, and macrophages. Furthermore, several significant pathways were enriched in gene set enrichment analysis (GSEA) analysis, including TGF-beta signaling pathway and Wnt signaling pathway.\nCONCLUSION: The signature of 10 IRGs we identified can effectively predict the prognosis of GC and provides new insight into discovering candidate prognostic biomarkers of GC.", "claims": [{"id": "claim-data-access", "statement": "The data that support the findings of this study are openly available in ImmPort database (https://immport.niaid.nih.gov/ ), Gene Expression Omnibus (GEO) database (GSE62254, GSE15459, GSE84437), and The Cancer Genome Atlas (TCGA) database (https://genomecancer.ucsc.edu/).", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:34382341", "locator": "sections[22] \"DATA AVAILABILITY STATEMENT\" paragraph 2", "quote": "The data that support the findings of this study are openly available in ImmPort database (https://immport.niaid.nih.gov/ ), Gene Expression Omnibus (GEO) database (GSE62254, GSE15459, GSE84437), and The Cancer Genome Atlas (TCGA) database (https://genomecancer.ucsc.edu/)."}], "state": "complete"}], "gaps": []}, "experiment": {"state": "complete", "objective": null, "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:34382341"], "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:GSE15459"], "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:GSE15459"], "outputs": ["the replicated result and its comparison"], "instruments": [], "reagents": []}], "materials": [], "instruments": [], "reagents": [], "conditions": {}, "gaps": []}, "data": {"state": "partial", "assets": [{"id": "source:pmid:34382341", "role": "manuscript", "format": "xml", "media_type": "application/xml", "uri": "https://doi.org/10.1002/cam4.4180", "sha256": 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