Prognostic model construction and immune microenvironment analysis of esophageal cancer based on gene expression data and microRNA target genes.

{"sci_version": "1.2", "schema": "https://corpus.bntrg.co.uk/sci/1.0/sci.schema.json", "id": "pmid:37304542", "kind": "science-record", "revision": 3, "content_hash": "sha256:880f78a79520f9e957968f22b00ea72167ca47c5960264cdf31f0f05b28eb0f4", "created_at": "2026-11-01T19:02:02Z", "updated_at": "2026-11-01T22:09:40Z", "generator": {"name": "corpus-assay-engine", "run_id": "reading-sci-2026-11-01"}, "paper": {"state": "complete", "title": "Prognostic model construction and immune microenvironment analysis of esophageal cancer based on gene expression data and microRNA target genes.", "doi": "10.21037/tcr-22-2588", "pmid": "37304542", "authors": ["Bingbing Gu", "Shuai Zhang", "Zhe Fan", "Jiajing Che", "Shuting Li", "Yunfei Li", "Keyu Pan", "Jiali Lv", "Cheng Wang", "Tao Zhang", "Jialin Wang"], "journal": "Translational cancer research", "year": 2023, "abstract": "Background: Accumulating evidence suggests that microRNA-target genes are closely related to tumorigenesis and progression. This study aims to screen the intersection of differentially expressed mRNAs (DEmRNAs) and the target genes of differentially expressed microRNAs (DEmiRNAs), and to construct a prognostic gene model of esophageal cancer (EC).\nMethods: Gene expression, microRNA expression, somatic mutation, and clinical information data of EC from The Cancer Genome Atlas (TCGA) database were used. The intersection of DEmRNAs and the target genes of DEmiRNAs predicted by the Targetscan database and microRNA Data Integration Portal (mirDIP) database were screened. The screened genes were used to construct a prognostic model of EC. Then, the molecular and immune signatures of these genes were explored. Finally, the GSE53625 dataset from the Gene Expression Omnibus (GEO) database was further used as a validation cohort to confirm the prognostic value of the genes.\nResults: Six genes on the grounds of the intersection of DEmiRNAs target genes and DEmRNAs were identified as prognostic genes, including ARHGAP11A, H1.4, HMGB3, LRIG1, PRR11, and COL4A1. Based on the median risk score calculated for these genes, EC patients were divided into a high-risk group (n=72) and a low-risk group (n=72). Survival analysis showed that the high-risk group had a significantly shorter survival time than the low-risk group (TCGA and GEO, P<0.001). The nomogram evaluation showed high reliability in predicting the 1-year, 2-year, and 3-year survival probability of EC patients. Compared to low-risk group, higher expression level of M2 macrophages was found in high-risk group of EC patient (P<0.05), while STAT3 checkpoints showed attenuated expression level in high-risk group.\nConclusions: A panel of differential genes was identified as potential EC prognostic biomarkers and showed great clinical significance in EC prognosis.", "claims": [{"id": "claim-method", "statement": "Least absolute shrinkage and selection operator (LASSO) Cox regression analysis was used to select differential genes to construct final prognostic model using the R package “glmnet” (13). Then, Cox regression analysis was performed to construct the best prognostic model and make proportional hazards assumption with R package “survival” and “MASS”.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:37304542", "locator": "sections[5] \"Construction and validation of a prognostic model\" paragraph 2", "quote": "Least absolute shrinkage and selection operator (LASSO) Cox regression analysis was used to select differential genes to construct final prognostic model using the R package “glmnet” (13). Then, Cox regression analysis was performed to construct the best prognostic model and make proportional hazards assumption with R package “survival” and “MASS”."}], "state": "complete"}, {"id": "claim-data-access", "statement": "Gene expression, microRNA expression, somatic mutation, and clinical information data of EC from The Cancer Genome Atlas (TCGA) database were used.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:37304542", "locator": "sections[0] \"Abstract\" paragraph 2", "quote": "Gene expression, microRNA expression, somatic mutation, and clinical information data of EC from The Cancer Genome Atlas (TCGA) database were used."}], "state": "complete"}, {"id": "claim-target-result", "statement": "Survival analysis showed that the high-risk group had a significantly shorter survival time than the low-risk group (TCGA and GEO, P<0.001).", "kind": "quantitative", "target": {"value": 0.001, "unit": "p-value", "tolerance": null, "source": "Survival analysis showed that the high-risk group had a significantly shorter survival time than the low-risk group (TCGA and GEO, P<0.001)."}, "evidence": [{"asset": "source:pmid:37304542", "locator": "sections[0] \"Abstract\" paragraph 3", "quote": "Survival analysis showed that the high-risk group had a significantly shorter survival time than the low-risk group (TCGA and GEO, P<0.001)."}], "state": "complete"}], "gaps": []}, "experiment": {"state": "complete", "objective": "Survival analysis showed that the high-risk group had a significantly shorter survival time than the low-risk group (TCGA and GEO, P<0.001).", "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:37304542"], "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:GSE53625"], "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:GSE53625"], "outputs": ["the replicated result and its comparison"], "instruments": [], "reagents": []}], "materials": [], "instruments": [], "reagents": [], "conditions": {}, "gaps": []}, "data": {"state": "partial", "assets": [{"id": "source:pmid:37304542", "role": "manuscript", "format": "xml", "media_type": "application/xml", "uri": "https://doi.org/10.21037/tcr-22-2588", "sha256": 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