Identification and validation of an epithelial-mesenchymal transition-related lncRNA pairs prognostic model for gastric cancer.

{"sci_version": "1.2", "schema": "https://corpus.bntrg.co.uk/sci/1.0/sci.schema.json", "id": "pmid:37304549", "kind": "science-record", "revision": 3, "content_hash": "sha256:83371cb96786eb5f5107a3035dd24e3f0e62c1b043a0ad074bd5029424e8a9f6", "created_at": "2026-11-01T19:02:02Z", "updated_at": "2026-11-01T22:52:06Z", "generator": {"name": "corpus-assay-engine", "run_id": "reading-sci-2026-11-01"}, "paper": {"state": "complete", "title": "Identification and validation of an epithelial-mesenchymal transition-related lncRNA pairs prognostic model for gastric cancer.", "doi": "10.21037/tcr-22-2751", "pmid": "37304549", "authors": ["Wanting Song", "Jialin Zhu", "Chenyan Li", "Shiqiao Peng", "Mingjun Sun", "Yiling Li", "Xuren Sun"], "journal": "Translational cancer research", "year": 2023, "abstract": "Background: Gastric cancer (GC) is a common malignancy. A mounting body of evidence has demonstrated the correlation between GC prognosis and epithelial-mesenchymal transition (EMT)-related biomarkers. This research constructed an available model using EMT-related long noncoding RNA (lncRNA) pairs to predict the survival for GC patients.\nMethods: The transcriptome data along with clinical information on GC samples were derived from The Cancer Genome Atlas (TCGA). Differentially expressed EMT-related lncRNAs were acquired and paired. Univariate and least absolute shrinkage and selection operator (LASSO) Cox regression analyses were applied to filter lncRNA pairs, and the risk model was built to investigate its effect on the prognosis of GC patients. Then, the areas under the receiver operating characteristic curves (AUCs) were calculated and the cutoff point for distinguishing low- or high-risk GC patients was identified. And the predictive ability of this model was tested in the GSE62254. Furthermore, the model was evaluated from the perspectives of survival time, clinicopathological parameters, infiltration of immunocytes, and functional enrichment analysis.\nResults: The risk model was built by using the identified twenty EMT-related lncRNA pairs, and it was not necessary to know the specific expression level of each lncRNA. Survival analysis pointed out that GC patients with high risk had poorer outcomes. Additionally, this model could be an independent prognostic variable for GC patients. The accuracy of the model was also verified in the testing set.\nConclusions: The new predictive model constructed here is composed of EMT-related lncRNA pairs, with reliable prognostic values, and can be utilized to predict the survival of GC.", "claims": [{"id": "claim-method", "statement": "The survival data analyses were carried out by Kaplan-Meier survival curves with log-rank test.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:37304549", "locator": "sections[11] \"Statistical analysis\" paragraph 2", "quote": "The survival data analyses were carried out by Kaplan-Meier survival curves with log-rank test."}], "state": "complete"}, {"id": "claim-data-access", "statement": "The RNA-sequencing profiles together with corresponding clinical data for GC patients from The Cancer Genome Atlas (TCGA) dataset (https://portal.gdc.cancer.gov/) were obtained and used as the training set.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:37304549", "locator": "sections[4] \"Data acquisition\" paragraph 2", "quote": "The RNA-sequencing profiles together with corresponding clinical data for GC patients from The Cancer Genome Atlas (TCGA) dataset (https://portal.gdc.cancer.gov/) were obtained and used as the training set."}], "state": "complete"}, {"id": "claim-target-result", "statement": "A risk model based on 20 EMT-related lncRNA pairs identified high-risk gastric cancer patients with poorer outcomes.", "kind": "qualitative", "target": null, "evidence": [{"asset": "source:pmid:37304549", "locator": "sections[0] \"Abstract\" paragraph 3", "quote": "The risk model was built by using the identified twenty EMT-related lncRNA pairs, and it was not necessary to know the specific expression level of each lncRNA."}, {"asset": "source:pmid:37304549", "locator": "sections[0] \"Abstract\" paragraph 3", "quote": "Survival analysis pointed out that GC patients with high risk had poorer outcomes."}], "state": "complete"}], "gaps": []}, "experiment": {"state": "complete", "objective": "A risk model based on 20 EMT-related lncRNA pairs identified high-risk gastric cancer patients with poorer outcomes.", "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:37304549"], "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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