Construction and integrated analysis of a lncRNA-associated competing endogenous RNA network reveal functional lncRNAs in pancreatic cancer.

{"sci_version": "1.2", "schema": "https://corpus.bntrg.co.uk/sci/1.0/sci.schema.json", "id": "pmid:35117727", "kind": "science-record", "revision": 5, "content_hash": "sha256:0f58791f5d27080568ac273074feff0e286cdf683ad084d8617227692cec1888", "created_at": "2026-11-01T17:36:51Z", "updated_at": "2026-11-01T22:48:24Z", "generator": {"name": "corpus-assay-engine", "run_id": "reading-sci-2026-11-01"}, "paper": {"state": "complete", "title": "Construction and integrated analysis of a lncRNA-associated competing endogenous RNA network reveal functional lncRNAs in pancreatic cancer.", "doi": "10.21037/tcr.2020.04.03", "pmid": "35117727", "authors": ["Yuanbin Liu", "Zhen Huo", "Weishen Wang", "Shuyu Zhai", "Yue Wang", "Yuanchi Weng", "Xiaxing Deng", "Xiongxiong Lu"], "journal": "Translational cancer research", "year": 2020, "abstract": "BACKGROUND: Long noncoding RNAs (lncRNAs) can serve as a competing endogenous RNA (ceRNA) in regulating gene expression in multiple cancers by sponging miRNA. However, this mechanism is poorly studied in pancreatic cancer. This study aims to identify functional lncRNAs and their potential regulatory mechanisms in pancreatic cancer.\nMETHODS: Differentially expressed lncRNA (DE-lncRNA), miRNA (DE-miRNA) and mRNA (DE-mRNA) were analyzed using data from three datasets (GSE89139, GSE24279 and GSE62452) from the Gene Expression Omnibus (GEO). The lncRNA-miRNA-mRNA interactions were predicted using miRcode and Targetscan. Gene ontology (GO) and pathway analysis of DE-mRNAs were performed using clusterProfiler. Survival analysis was conducted using data from The Cancer Genome Atlas (TCGA) database.\nRESULTS: Three hundred sixty-six DE-lncRNAs, 28 DE-miRNAs and 330 DE-mRNAs from pancreatic cancer and adjacent tissue were identified. A ceRNA network including 75 DE-lncRNAs, 18 DE-miRNAs and 85 DE-mRNAs was constructed, among which 16 DE-lncRNAs were associated with overall survival and 13 DE-lncRNAs were correlated with tumor progression. Three functional lncRNAs, GABPB1-AS1, ST7-AS1 and PSMG3-AS1, were identified as key functional lncRNAs, and their differential expression and potential ceRNA regulatory mechanism were validated by qPCR using pancreatic cancer cell lines and tissues.\nCONCLUSIONS: Our study identifies novel lncRNAs associated with progression and prognosis of pancreatic cancer and contributes to better understanding of lncRNA-associated ceRNA regulatory mechanisms in pancreatic cancer.", "claims": [{"id": "claim-method", "statement": "Kaplan-Meier curves were plotted to analyze overall survival using data from 178 patients from the TCGA database, and differences in survival between groups were assessed by log-rank test. Univariate and multivariate Cox regression analysis was used to evaluate the hazard ratio (HR) and 95% confidence intervals (CI).", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:35117727", "locator": "sections[10] \"Statistical analysis\" paragraph 2", "quote": "Kaplan-Meier curves were plotted to analyze overall survival using data from 178 patients from the TCGA database, and differences in survival between groups were assessed by log-rank test. Univariate and multivariate Cox regression analysis was used to evaluate the hazard ratio (HR) and 95% confidence intervals (CI)."}], "state": "complete"}, {"id": "claim-data-access", "statement": "LncRNA expression data were derived from GSE89139, which contains 3 pancreatic cancer samples and 3 normal samples.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:35117727", "locator": "sections[3] \"Microarray data processing\" paragraph 2", "quote": "LncRNA expression data were derived from GSE89139, which contains 3 pancreatic cancer samples and 3 normal samples."}], "state": "complete"}, {"id": "claim-target-result", "statement": "In addition, using data from 178 patients from the TCGA database, we found that 16 DE-lncRNAs in the network were correlated with OS.", "kind": "qualitative", "target": null, "evidence": [{"asset": "source:pmid:35117727", "locator": "sections[13] \"Construction of the ceRNA network and prognostic analysis\" paragraph 2", "quote": "In addition, using data from 178 patients from the TCGA database, we found that 16 DE-lncRNAs in the network were correlated with OS."}], "state": "complete"}], "gaps": []}, "experiment": {"state": "complete", "objective": "In addition, using data from 178 patients from the TCGA database, we found that 16 DE-lncRNAs in the network were correlated with OS.", "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:35117727"], "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:GSE24279"], "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:GSE24279"], "outputs": ["the replicated result and its comparison"], "instruments": [], "reagents": []}], "materials": [], "instruments": [], "reagents": [], "conditions": {}, "gaps": []}, "data": {"state": "partial", "assets": [{"id": "source:pmid:35117727", "role": "manuscript", "format": "xml", "media_type": "application/xml", "uri": "https://doi.org/10.21037/tcr.2020.04.03", "sha256": 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