Identification of a chemotherapy-associated gene signature for a risk model of prognosis in gastric adenocarcinoma through bioinformatics analysis.

{"sci_version": "1.2", "schema": "https://corpus.bntrg.co.uk/sci/1.0/sci.schema.json", "id": "pmid:36388651", "kind": "science-record", "revision": 3, "content_hash": "sha256:fa9a2c8b0c6009195cb1d8e56ae3c0d14116acf9a8913d78c0454e13751a1beb", "created_at": "2026-11-01T18:15:49Z", "updated_at": "2026-11-01T21:29:27Z", "generator": {"name": "corpus-assay-engine", "run_id": "reading-sci-2026-11-01"}, "paper": {"state": "complete", "title": "Identification of a chemotherapy-associated gene signature for a risk model of prognosis in gastric adenocarcinoma through bioinformatics analysis.", "doi": "10.21037/jgo-22-872", "pmid": "36388651", "authors": ["Yanping Shen", "Ke Chen", "Chijiang Gu"], "journal": "Journal of gastrointestinal oncology", "year": 2022, "abstract": "Background: Over the past few years, the overall survival rate of patients with gastric adenocarcinoma who have received different chemotherapy regimens has increased. However, not all gastric cancer patients who receive chemotherapy have a longer survival. We need better predictive biomarkers. This study is to construct a new risk model of chemotherapy-associated genes in gastric adenocarcinoma (GA) for prognostication.\nMethods: RNA-seq data and clinical information of GSE26901 (containing 44 chemotherapy samples and 65 patients without chemotherapy) in Gene Expression Omnibus (GEO) and stomach adenocarcinoma (STAD, containing 360 cancer tissue samples and 50 paired normal tissue samples) in The Cancer Genome Atlas (TCGA) were selected for screening differentially expressed genes (DEGs). Multivariate Cox regression was conducted to screen prognosis-associated genes and its link to patients' prognosis were screened by least absolute shrinkage and selection operator (LASSO) regression analysis. Based on the key genes, a risk scoring equation for the prognosis model was established, and constructed survival prognosis model. The model was tested for predictive ability through training set (TCGA datasets) and validation set (GSE84437). The correlations of the risk score with clinical pathological features, immune score and drug sensitivity score were evaluated.\nResults: In total, 179 overlapping genes were obtained by screening DEGs. Univariate Cox analysis revealed 36 prognosis-related genes, and LASSO regression analysis revealed 8 key genes (KCNJ2, GATA5, CLDN1, SERPINE1, FCER2, PMEPA1, TMEM37 and CRTAC1). Kaplan-Meier (K-M) analysis uncovered a relatively short overall survival time in the high-risk group. The model was verified to possess favourable predictive ability. In addition, the nomogram model were demonstrated good predictability with area under the curve (AUC) for 1-5 years in training set were 0.78, 0.78, 0.76, 0.79 and 0.81. The high-risk group was less likely to get benefits from immunotherapy and less sensitive to cisplatin.\nConclusions: According to the results of our training set and validation set, the risk model based on the eight chemotherapy-related gene signatures predicting prognosis has certain predictive accuracy in predicting the survival of GA patients which can be a promising prognostic parameter for GA. However, its efficacy remains to be proved in clinical practice.", "claims": [{"id": "claim-method", "statement": "The least absolute shrinkage and selection operator (LASSO) regression algorithm was used to select the characteristics of key genes, and 10-fold cross-validation for determining the parameters.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:36388651", "locator": "sections[5] \"Key genes screening and prognosis model construction\" paragraph 2", "quote": "The least absolute shrinkage and selection operator (LASSO) regression algorithm was used to select the characteristics of key genes, and 10-fold cross-validation for determining the parameters."}], "state": "complete"}, {"id": "claim-data-access", "statement": "From TCGA (https://portal.gdc.cancer.gov/), the clinicopathological parameters of stomach adenocarcinoma (STAD) samples and the RNA-seq of tumour tissue samples were downloaded.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:36388651", "locator": "sections[3] \"Data source\" paragraph 2", "quote": "From TCGA (https://portal.gdc.cancer.gov/), the clinicopathological parameters of stomach adenocarcinoma (STAD) samples and the RNA-seq of tumour tissue samples were downloaded."}], "state": "complete"}, {"id": "claim-target-result", "statement": "In addition, the nomogram model were demonstrated good predictability with area under the curve (AUC) for 1–5 years in training set were 0.78, 0.78, 0.76, 0.79 and 0.81.", "kind": "qualitative", "target": null, "evidence": [{"asset": "source:pmid:36388651", "locator": "sections[0] \"Abstract\" paragraph 3", "quote": "In addition, the nomogram model were demonstrated good predictability with area under the curve (AUC) for 1–5 years in training set were 0.78, 0.78, 0.76, 0.79 and 0.81."}], "state": "complete"}], "gaps": []}, "experiment": {"state": "complete", "objective": "In addition, the nomogram model were demonstrated good predictability with area under the curve (AUC) for 1–5 years in training set were 0.78, 0.78, 0.76, 0.79 and 0.81.", "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:36388651"], "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. 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No dataset was downloaded and no licence was read."}}, "can_run": {"dsl_operations": ["survival_km"], "assets": ["source:pmid:36388651", "data:geo:GSE26901"], "steps": ["run_analysis"]}, "must_build": {"dsl_operations": [], "converters": [], "readers": [], "capabilities": [], "data_gaps": ["data:geo:GSE26901"]}, "gaps": []}, "review": {"state": "partial", "machine_critique": {"kind": "extraction_review", "reader": {"model": "MiniMax-M3.1-Flash", "provider": "minimax", "provider_family": "minimax", "read_at": "2026-11-01T18:15:33Z", "independence": "single_reader"}, "evidence_check": {"method": "verbatim", "availability": null}, "calls": 5, "usage": {"prompt_tokens": 8209, "completion_tokens": 2031, "cached_tokens": 256}}, "human_critique": null, "stages": [{"id": "extraction", "state": "complete", "reader": "MiniMax-M3.1-Flash", "provider": "minimax"}], "gaps": ["review.independent_reader", "review.machine_critique", "review.human_critique"]}, "execution": {"state": "absent", "status": "not_run", "mode": null, "runs": [], "gaps": ["execution.not_run"]}, "provenance": {"entities": [{"id": "pmid:36388651", "type": "paper", "label": "pmid:36388651"}, {"id": "source:pmid:36388651", "type": "manuscript", "label": "PMID 36388651 full text"}, {"id": "data:geo:GSE26901", "type": "dataset", "label": "GEO GSE26901"}], "activities": [{"id": "activity-reading-sci-2026-11-01", "type": "classification", "used": [{"id": "pmid:36388651", "type": "paper", "label": "pmid:36388651"}, {"id": "source:pmid:36388651", "type": "manuscript", "label": "PMID 36388651 full text"}, {"id": "data:geo:GSE26901", "type": "dataset", "label": "GEO GSE26901"}], "agent": "agent:corpus-assay-engine"}, {"id": "activity-read-36388651", "type": "extraction", "used": ["source:pmid:36388651"], "agent": "agent:minimax-reader"}, {"id": "activity-resolve-GSE26901", "type": "accession_resolution", "used": ["data:geo:GSE26901"], "agent": "agent:corpus-assay-engine"}], "agents": [{"id": "agent:corpus-assay-engine", "type": "software", "label": "Corpus assay engine"}, {"id": "agent:minimax-reader", "type": "software", "label": "MiniMax literature reader"}], "source_run_id": "reading-sci-2026-11-01", "dsl_catalogue_fingerprint": "343fb30756ba6ec3", "capability_table_fingerprint": "2cb3e42f047d2ecf", "snapshot_id": "ba34b49490d9bfaf"}, "lineage": {"parent_id": "pmid:36388651", "parent_hash": "sha256:e012ed9645fb667d2f036055aaab7fe968a8b7a841867168835cfd43cd70ea8f", "fork_of": null, "generation": 2}, "gaps": ["asset:data:geo:GSE26901 licence not read", "asset:data:geo:GSE26901 not downloaded", "asset:data:geo:GSE84437 licence not read", "asset:data:geo:GSE84437 not downloaded", "execution.not_run", "method.reader_named_unmapped", "review.human_critique", "review.independent_reader", "review.machine_critique"], "assays": [{"role": "data_generation", "definition_id": "rna_seq", "definition_version": "99e1195c7d6f", "definition_digest": null, "required_operations": [], "support_state": "partial", "source_hashes": {"assay_lexicon": "99e1195c7d6f"}, "confidence": 0.93, "evidence": ["carcinoma (GA) for prognostication. Methods: RNA-seq data and clinical information of GSE26901 (c"], "order_basis": "paper_text_order:537", "id": "assay:1"}, {"role": "analysis", "definition_id": "survival_analysis", "definition_version": "f2132e96ae6c7a4e", "definition_digest": null, "required_operations": ["survival_km"], "support_state": "supported", "source_hashes": {"dsl_catalogue": "f2132e96ae6c7a4e"}, "confidence": 0.7, "evidence": ["Kaplan-Meier"], "order_basis": "consumes_earlier_output", "id": "assay:2"}]}