Three Immune-Related Prognostic mRNAs as Therapeutic Targets for Pancreatic Cancer.

{"sci_version": "1.2", "schema": "https://corpus.bntrg.co.uk/sci/1.0/sci.schema.json", "id": "pmid:33869254", "kind": "science-record", "revision": 8, "content_hash": "sha256:1fb3a4b1181d79390289ef5cff1c2d702d12c5c20b3a5bd41c4a7964e48d2556", "created_at": "2026-11-01T15:41:32Z", "updated_at": "2026-11-01T22:46:32Z", "generator": {"name": "corpus-assay-engine", "run_id": "reading-sci-2026-11-01"}, "paper": {"state": "complete", "title": "Three Immune-Related Prognostic mRNAs as Therapeutic Targets for Pancreatic Cancer.", "doi": "10.3389/fmed.2021.649326", "pmid": "33869254", "authors": ["Cangang Zhang", "Yueji Zou", "Yanan Zhu", "Yi Liu", "Hui Feng", "Fan Niu", "Pengcheng He", "Haibo Liu"], "journal": "Frontiers in medicine", "year": 2021, "abstract": "Objective: Pancreatic cancer is a highly lethal malignancy globally. This study aimed to probe and validate immune-related prognostic mRNAs as therapeutic targets for pancreatic cancer. Methods: Gene transcriptome data of pancreatic cancer and normal pancreas were retrieved from TCGA-GTEx projects. Two thousand four hundred and ninety-eight immune-related genes were obtained from the IMMUPORT database. Abnormally expressed immune-related genes were then identified. Under univariate and multivariate cox models, a gene signature was constructed. Its predictive efficacy was assessed via ROCs. The interactions between the 21 genes were analyzed by Spearson analysis and PPI network. Using the GEPIA and The Human Protein Atlas databases, their expression and prognostic value were evaluated. The TIMER database was utilized to determine the relationships between MET, OAS1, and OASL mRNAs and immune infiltrates. Finally, their mRNA expression was externally verified in the GSE15471 and GSE62452 datasets. Results: An immune-related 21-gene signature was developed for predicting patients' prognosis. Following verification, this signature exhibited the well predictive performance. There were physical and functional interactions between them. MET, OAS1, and OASL mRNAs were all up-regulated in pancreatic cancer and associated with unfavorable prognosis. They showed strong correlations with tumor progression. Furthermore, the three mRNAs were distinctly associated with immune infiltrates. Their up-regulation was confirmed in the two external datasets. Conclusion: These findings identified three immune-related prognostic mRNAs MET, OAS1, and OASL, which may assist clinicians to choose targets for immunotherapy and make personalized treatment strategy for pancreatic cancer patients.", "claims": [{"id": "claim-method", "statement": "Gene transcriptome data of 165 normal pancreas samples from the Genotype-Tissue Expression (GTEx) project and 178 pancreatic cancer samples from The Cancer Genome Atlas (TCGA) database were downloaded based on the UCSC Xena browser (https://xenabrowser.net/datapages/). After merging gene matrix of GTEx and TCGA datasets based on the Ensembl IDs, differentially expressed genes (DEGs) between pancreatic cancer and normal pancreas specimens were screened via the Linear Models for Microarray Data (limma) package in R (13).", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:33869254", "locator": "sections[3] \"Downloaded Datasets\" paragraph 2", "quote": "Gene transcriptome data of 165 normal pancreas samples from the Genotype-Tissue Expression (GTEx) project and 178 pancreatic cancer samples from The Cancer Genome Atlas (TCGA) database were downloaded based on the UCSC Xena browser (https://xenabrowser.net/datapages/)."}, {"asset": "source:pmid:33869254", "locator": "sections[4] \"Screening for Abnormally Expressed Immune-Related Genes\" paragraph 2", "quote": "After merging gene matrix of GTEx and TCGA datasets based on the Ensembl IDs, differentially expressed genes (DEGs) between pancreatic cancer and normal pancreas specimens were screened via the Linear Models for Microarray Data (limma) package in R (13)."}], "state": "complete"}, {"id": "claim-data-access", "statement": "The datasets generated for this study can be found in online repositories. 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"4.91E−05"], ["OASL", "0.511952", "1.668545", "1.105363", "2.518668", "0.014819"], ["PTGS2", "0.242464", "1.274385", "1.025728", "1.583322", "0.028572"], ["OAS1", "0.411634", "1.509282", "0.980257", "2.323809", "0.061566"], ["LTBP1", "0.566777", "1.762578", "1.172497", "2.649628", "0.006428"], ["PLAUR", "−1.28398", "0.276934", "0.146236", "0.524442", "8.11E−05"], ["AGT", "−0.36056", "0.697283", "0.545836", "0.890749", "0.003902"], ["AREG", "0.340822", "1.406103", "1.086432", "1.819832", "0.0096"], ["CMTM6", "−0.64978", "0.522162", "0.291347", "0.935836", "0.029056"], ["HBEGF", "0.51271", "1.669811", "1.177601", "2.367752", "0.004009"], ["SPP1", "0.21316", "1.237583", "1.050946", "1.457366", "0.010596"], ["IL22RA1", "0.170068", "1.185385", "0.937948", "1.498097", "0.154535"], ["MET", "0.82481", "2.281447", "1.443826", "3.605005", "0.00041"], ["NRP2", "−0.59908", "0.549317", "0.341531", "0.88352", "0.013485"], ["SDC4", "−0.62306", "0.536299", "0.36083", "0.797097", "0.002059"], ["PAK3", 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