A 5-Gene Prognostic Combination for Predicting Survival of Patients with Gastric Cancer.

{"sci_version": "1.2", "schema": "https://corpus.bntrg.co.uk/sci/1.0/sci.schema.json", "id": "pmid:31422414", "kind": "science-record", "revision": 7, "content_hash": "sha256:474239b7af565bf8bd29b9fe2f5aed2e22daf4e975b59d2ea410016d865a45e6", "created_at": "2026-11-01T15:40:48Z", "updated_at": "2026-11-01T21:22:25Z", "generator": {"name": "corpus-assay-engine", "run_id": "reading-sci-2026-11-01"}, "paper": {"state": "complete", "title": "A 5-Gene Prognostic Combination for Predicting Survival of Patients with Gastric Cancer.", "doi": "10.12659/MSM.914815", "pmid": "31422414", "authors": ["Liang Song", "Xiao-Yan Wang", "Xiao-Feng He"], "journal": "Medical science monitor : international medical journal of experimental and clinical research", "year": 2019, "abstract": "BACKGROUND The aim of the study was to identify a multigene prognostic factor in patients with gastric cancer (GC). MATERIAL AND METHODS Random survival forest (RSF) was performed to screen survival-related genes and develop a multigene combination based on the cumulative hazard function of each GC patient in TCGA-STAD and GSE15459. Kaplan-Meier curve and univariate and multivariable Cox proportional hazards regression model were applied to evaluate the prognostic performance of the 5-gene combination. C-index was used to compare the prognostic performance of the 5-gene combination and another 9-gene signature in GC. Gene set enrichment analysis (GSEA) was conducted. RESULTS We obtained 19 survival-related genes through univariate Cox proportional hazards analysis in the training set, 5 of which were identified and were used to develop a 5-gene combination through RSF. Patients in the 5-gene combination low-risk group had better overall survival (OS) than those in the 5-gene combination high-risk group, and the 5-gene combination was demonstrated to be an independent prognostic factor in patients with GC. The 5-gene combination outperformed the 9-gene signature in predicting the OS of GC patients, and it might affect the prognosis of GC patients through E2F signaling, MYC signaling, and G2M checkpoint. CONCLUSIONS We introduce a 5-gene combination that can predict the survival of GC patients and might be an independent prognostic factor in GC.", "claims": [{"id": "claim-data-access", "statement": "The GC gene expression study TCGA-STAD (level 3 data) [13], measured by using the Illumina HiSeq 2000 RNA Sequencing platform by the University of North Carolina TCGA genome characterization center, was shown as in log2(x+1) transformed RSEM normalized count and downloaded from UCSC Xena (https://xenabrowser.net/datapages/). The related clinical information (including age, gender, pathological stage, survival information, and relapse information) of samples in TCGA-STAD was also downloaded.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:31422414", "locator": "sections[3] \"GC gene expression study\" paragraph 2", "quote": "The GC gene expression study TCGA-STAD (level 3 data) [13], measured by using the Illumina HiSeq 2000 RNA Sequencing platform by the University of North Carolina TCGA genome characterization center, was shown as in log2(x+1) transformed RSEM normalized count and downloaded from UCSC Xena (https://xenabrowser.net/datapages/). The related clinical information (including age, gender, pathological stage, survival information, and relapse information) of samples in TCGA-STAD was also downloaded."}], "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:31422414"], "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:31422414", "role": "manuscript", "format": "xml", "media_type": "application/xml", "uri": "https://doi.org/10.12659/MSM.914815", "sha256": "sha256:87a296873a48c859caf992054d306cb8c5df8f1aa6ccec5a954d6de2c92b79bb", "bytes": 20626, "access": "open", "state": "resolved", "reader": null, "reader_status": "reader_required", "identifier": "10.12659/MSM.914815", "version": null, "note": "Full article fetched from PMC; the checksum covers the rendered section body, not the original XML bytes.", "structure": {"pmcid": "PMC6713029", "source": "europe_pmc_fulltext", "coverage": "whole_body_without_references", "text_hash_scope": "rendered_section_body"}}, {"id": "data:geo:GSE15459", "role": "raw", "format": "geo-series", "media_type": "application/vnd.ncbi.geo-series+json", "uri": "https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE15459", "sha256": null, "bytes": null, "access": "open", "state": "resolved", "reader": null, "reader_status": "reader_required", "identifier": "GSE15459", "version": null, "note": "The GC gene expression study TCGA-STAD (level 3 data) [13], measured by using the Illumina HiSeq 2000 RNA Sequencing platform by the University of North Carolina TCGA genome characterization center, was shown as in log2(x+1) transformed RSEM normalized count and downloaded from UCSC Xena (https://xenabrowser.net/datapages/). 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The physical bench the paper used is not, so a physical validation cannot be run here."}, "data": {"tier": "R1", "reachable": true, "accessions": ["GSE15459"], "resolved_accessions": ["GSE15459"], "statements": ["The GC gene expression study TCGA-STAD (level 3 data) [13], measured by using the Illumina HiSeq 2000 RNA Sequencing platform by the University of North Carolina TCGA genome characterization center, was shown as in log2(x+1) transformed RSEM normalized count and downloaded from UCSC Xena (https://xenabrowser.net/datapages/). The related clinical information (including age, gender, pathological stage, survival information, and relapse information) of samples in TCGA-STAD was also downloaded."], "basis": "The paper names GSE15459 in Gene Expression Omnibus (GEO) and the accession resolves in the repository. 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