A 10‑microRNA prognosis scoring system in esophageal squamous cell carcinoma constructed using bioinformatic methods.

{"sci_version": "1.2", "schema": "https://corpus.bntrg.co.uk/sci/1.0/sci.schema.json", "id": "pmid:29393486", "kind": "science-record", "revision": 8, "content_hash": "sha256:781d4dc2fd024005733529002f12ff861a17c1fbef06bbacee1bacc60551addc", "created_at": "2026-11-01T15:40:31Z", "updated_at": "2026-11-01T21:59:42Z", "generator": {"name": "corpus-assay-engine", "run_id": "reading-sci-2026-11-01"}, "paper": {"state": "complete", "title": "A 10‑microRNA prognosis scoring system in esophageal squamous cell carcinoma constructed using bioinformatic methods.", "doi": "10.3892/mmr.2018.8550", "pmid": "29393486", "authors": ["Qingchao Sun", "Liang Zong", "Haiping Zhang", "Yanchao Deng", "Changming Zhang", "Liwei Zhang"], "journal": "Molecular medicine reports", "year": 2018, "abstract": "MicroRNA (miR) signatures may aid the diagnosis and prediction of cancer; therefore, miRs associated with the prognosis of esophageal squamous cell carcinoma (ESCC) were screened. miR‑sequencing (seq) and mRNA‑seq data from early‑stage ESCC samples were downloaded from The Cancer Genome Atlas (TCGA) database, and samples from subjects with a >6‑month survival time were assessed with Cox regression analysis for prognosis‑associated miRs. A further two miR expression datasets of ESCC samples, GSE43732 and GSE13937, were downloaded from the Gene Expression Omnibus database. Common miRs between prognosis‑associated miRs, and miRs in the GSE43732 and GSE13937, datasets were used for risk score calculations for each sample, and median risk scores were applied for the stratification of low‑ and high‑risk samples. A prognostic scoring system of signature miRs was subsequently constructed and used for survival analysis for low‑ and high‑risk samples. Differentially‑expressed genes (DEGs) corresponding to all miRs were screened and functional annotation was performed. A total of 34 prognostic miRs were screened and a scoring system was created using 10 signature miRs (hsa‑miR‑140, ‑33b, ‑34b, ‑144, ‑486, ‑214, ‑129‑2, ‑374a and ‑412). Using this system, low‑risk samples were identified to be associated with longer survival compared with high‑risk samples in the TCGA and GSE43732 datasets. Age, alcohol and tobacco use, and radiotherapy were prognostic factors for samples with different risk scores and the same clinical features. There were 168 DEGs, and the top 20 risk scores positively‑correlated and the top 20 risk scores negatively‑correlated DEGs were significantly enriched for six and 10 functional terms, respectively. 'Tight junction' and 'melanogenesis' were two significantly enriched pathways of DEGs. miR‑214, miR‑129‑2, miR‑37a and miR‑486 may predict ESCC patient survival, although further studies to validate this hypothesis are required.", "claims": [{"id": "claim-method", "statement": "Therefore, miR-seq data samples from TCGA with a survival time of <6 months were removed to avoid introducing more mixed factors, and the remaining 77 samples assessed with Cox regression analysis using the survival package in R (17) to identify prognostic miRs (threshold of P<0.01 for the log rank test).", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:29393486", "locator": "sections[5] \"Prognostic miRs\" paragraph 2", "quote": "Therefore, miR-seq data samples from TCGA with a survival time of <6 months were removed to avoid introducing more mixed factors, and the remaining 77 samples assessed with Cox regression analysis using the survival package in R (17) to identify prognostic miRs (threshold of P<0.01 for the log rank test)."}], "state": "complete"}, {"id": "claim-data-access", "statement": "miR-seq and mRNA-seq data from early stage ESCC samples were downloaded from TCGA on March 18, 2017 and 89 samples with miR and mRNA expression data were obtained by matching barcodes. These were early stage (stage I and II) cancer samples. This dataset was used as a test dataset.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:29393486", "locator": "sections[4] \"Microarray data\" paragraph 2", "quote": "miR-seq and mRNA-seq data from early stage ESCC samples were downloaded from TCGA on March 18, 2017 and 89 samples with miR and mRNA expression data were obtained by matching barcodes. These were early stage (stage I and II) cancer samples. This dataset was used as a test dataset."}], "state": "complete"}, {"id": "claim-target-result", "statement": "The paper used Cox regression analysis to screen 34 prognostic miRNAs from TCGA miR-seq data and validated the resulting prognostic scoring system using GEO datasets GSE43732 and GSE13937.", "kind": "qualitative", "target": null, "evidence": [{"asset": "source:pmid:29393486", "locator": "sections[10] \"Prognostic miRs\" paragraph 2", "quote": "Using Cox regression analysis on samples that indicated a survival time of >6 months, 34 prognostic miRs from the miR-seq dataset were screened and 16 common miRs were identified between the GSE43732 and GSE13937 datasets (Table II)."}], "state": "complete"}], "gaps": []}, "experiment": {"state": "complete", "objective": "The paper used Cox regression analysis to screen 34 prognostic miRNAs from TCGA miR-seq data and validated the resulting prognostic scoring system using GEO datasets GSE43732 and GSE13937.", "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:29393486"], "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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