Identification and Validation of Constructing the Prognostic Model With Four DNA Methylation-Driven Genes in Pancreatic Cancer.

{"sci_version": "1.2", "schema": "https://corpus.bntrg.co.uk/sci/1.0/sci.schema.json", "id": "pmid:35087823", "kind": "science-record", "revision": 5, "content_hash": "sha256:9e9e58010b906adc1d95a70a70a7b8d808ada2da1897d6c81501625b5a345fe0", "created_at": "2026-11-01T17:36:49Z", "updated_at": "2026-11-01T22:48:19Z", "generator": {"name": "corpus-assay-engine", "run_id": "reading-sci-2026-11-01"}, "paper": {"state": "complete", "title": "Identification and Validation of Constructing the Prognostic Model With Four DNA Methylation-Driven Genes in Pancreatic Cancer.", "doi": "10.3389/fcell.2021.709669", "pmid": "35087823", "authors": ["Guangyu Chen", "Junyu Long", "Ruizhe Zhu", "Gang Yang", "Jiangdong Qiu", "Fangyu Zhao", "Yuezhe Liu", "Jinxin Tao", "Taiping Zhang", "Yupei Zhao"], "journal": "Frontiers in cell and developmental biology", "year": 2021, "abstract": "Background: Pancreatic cancer (PC) is a highly aggressive gastrointestinal tumor and has a poor prognosis. Evaluating the prognosis validly is urgent for PC patients. In this study, we utilized the RNA-sequencing (RNA-seq) profiles and DNA methylation expression data comprehensively to develop and validate a prognostic signature in patients with PC. Methods: The integrated analysis of RNA-seq, DNA methylation expression profiles, and relevant clinical information was performed to select four DNA methylation-driven genes. Then, a prognostic signature was established by the univariate, multivariate Cox, and least absolute shrinkage and selection operator (LASSO) regression analyses in The Cancer Genome Atlas (TCGA) dataset. GSE62452 cohort was utilized for external validation. Finally, a nomogram model was set up and evaluated by calibration curves. Results: Nine DNA methylation-driven genes that were related to overall survival (OS) were identified. After multivariate Cox and LASSO regression analyses, four of these genes (RIC3, MBOAT2, SEZ6L, and OAS2) were selected to establish the predictive signature. The PC patients were stratified into two groups according to the median risk score, of which the low-risk group displayed a prominently favorable OS compared with the high-risk group, whether in the training (p < 0.001) or validation (p < 0.01) cohort. Then, the univariate and multivariate Cox regression analyses showed that age, grade, risk score, and the number of positive lymph nodes were significantly associated with OS in PC patients. Therefore, we used these clinical variables to construct a nomogram; and its performance in predicting the 1-, 2-, and 3-year OS of patients with PC was assessed via calibration curves. Conclusion: A prognostic risk score signature was built with the four alternative DNA methylation-driven genes. Furthermore, in combination with the risk score, age, grade, and the number of positive lymph nodes, a nomogram was established for conveniently predicting the individualized prognosis of PC patients.", "claims": [{"id": "claim-method", "statement": "We identified the DNA methylation-driven genes of which mRNA expression levels are a negative relationship with the DNA methylation levels via linear regression analysis.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:35087823", "locator": "sections[5] \"Identification of DNA Methylation-Driven Denes\" paragraph 2", "quote": "We identified the DNA methylation-driven genes of which mRNA expression levels are a negative relationship with the DNA methylation levels via linear regression analysis."}], "state": "complete"}, {"id": "claim-data-access", "statement": "The datasets presented in this study can be found in online repositories. The names of the repository/repositories and accession number(s) can be found below: https://www.ncbi.nlm.nih.gov/geo/, GSE62452.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:35087823", "locator": "sections[20] \"Data Availability Statement\" paragraph 2", "quote": "The datasets presented in this study can be found in online repositories. The names of the repository/repositories and accession number(s) can be found below: https://www.ncbi.nlm.nih.gov/geo/, GSE62452."}], "state": "complete"}, {"id": "claim-target-result", "statement": "A four-gene prognostic risk score signature was built, and a nomogram combining the risk score with age, grade, and the number of positive lymph nodes was established to predict individualized overall survival in pancreatic cancer.", "kind": "qualitative", "target": null, "evidence": [{"asset": "source:pmid:35087823", "locator": "sections[0] \"Abstract\" paragraph 4", "quote": "A prognostic risk score signature was built with the four alternative DNA methylation-driven genes."}, {"asset": "source:pmid:35087823", "locator": "sections[0] \"Abstract\" paragraph 4", "quote": "Furthermore, in combination with the risk score, age, grade, and the number of positive lymph nodes, a nomogram was established for conveniently predicting the individualized prognosis of PC patients."}], "state": "complete"}], "gaps": []}, "experiment": {"state": "partial", "objective": "A four-gene prognostic risk score signature was built, and a nomogram combining the risk score with age, grade, and the number of positive lymph nodes was established to predict individualized overall survival in pancreatic cancer.", "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:35087823"], "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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In this study, we utilized the RNA-sequencing (RNA-seq) profiles and DNA methylation expre", "this study, we utilized the RNA-sequencing (RNA-seq) profiles and DNA methylation expression dat", "with PC. Methods: The integrated analysis of RNA-seq, DNA methylation expression profiles, and re", "and Methods Sample Datasets With the use of RNA-seq data, 430 DNA methylation expression profile"], "order_basis": "paper_text_order:282", "id": "assay:1"}, {"role": "analysis", "definition_id": "group_comparison", "definition_version": "f2132e96ae6c7a4e", "definition_digest": null, "required_operations": [], "support_state": "partial", "source_hashes": {"dsl_catalogue": "f2132e96ae6c7a4e"}, "confidence": 1.0, "evidence": ["We identified the DNA methylation-driven genes of which mRNA expression levels are a negative relationship with the DNA methylation levels via linear regression analysis."], "order_basis": "consumes_earlier_output", "id": "assay:2"}]}