Immune cell related signature predicts prognosis in esophageal squamous cell carcinoma based on single-cell and bulk-RNA sequencing.

{"sci_version": "1.2", "schema": "https://corpus.bntrg.co.uk/sci/1.0/sci.schema.json", "id": "pmid:38903709", "kind": "science-record", "revision": 2, "content_hash": "sha256:df766070b048b77796285c5ff8cab624672e6f417e2f63061092dc30737a907f", "created_at": "2026-11-01T20:28:58Z", "updated_at": "2026-11-01T21:33:19Z", "generator": {"name": "corpus-assay-engine", "run_id": "reading-sci-2026-11-01"}, "paper": {"state": "complete", "title": "Immune cell related signature predicts prognosis in esophageal squamous cell carcinoma based on single-cell and bulk-RNA sequencing.", "doi": "10.3389/fonc.2024.1370801", "pmid": "38903709", "authors": ["Xian Wang", "Wei Peng", "Yali Zhao", "Jiming Sha", "Na Li", "Shan Huang", "Hua Wang"], "journal": "Frontiers in oncology", "year": 2024, "abstract": "Background: It has been reported that tumor immune microenvironment performs a vital role in tumor progress. However, acting mechanism of immune cell related genes (IRGs) in esophageal squamous cell carcinoma (ESCC) is uncertain.\nMethods: TCGA-ESCC, GSE23400, GSE26886, GSE75241, and GSE196756 datasets were gained via public databases. First, differentially expressed genes (DEGs) between ESCC and control samples from GSE23400, GSE26886, and GSE75241 were screened out by differential expression analysis, and overlapping DEGs were identified. Single-cell transcriptome data of GSE196756 were applied to explore immune cells that might be involved in regulation of ESCC. Then, weighted gene co-expression network analysis was applied to screen IRGs. Next, differentially expressed IRGs (DE-IRGs) were identified by overlapping IRGs and DEGs, and were incorporated into univariate Cox, least absolute shrinkage and selection operator, and multivariate Cox to acquire prognosis-related genes, and ESCC samples were grouped into high-/low-risk groups on the basis of median risk score. Finally, the role of prognosis model in immunotherapy was analyzed.\nResults: Totally 248 DEGs were yielded by overlapping 3,915 DEGs in GSE26886, 459 DEGs in GSE23400, and 1,641 DEGs in GSE75241. Single-cell analysis found that B cells, dendritic cells, monocytes, neutrophils, natural killer cells, and T cells were involved in ESCC development. Besides, MEred, MEblack, MEpink, MEblue and MEbrown modules were considered as key modules because of their highest correlations with immune cell subtypes. A total of 154 DE-IRGs were yielded by taking intersection of DEGs and genes in key modules. Moreover, CTSC, ALOX12, and RMND5B were identified as prognosis-related genes in ESCC. Obviously, Exclusion and TIDE scores were notably lower in high-risk group than in the other one, indicating that high-risk group was more responsive to immunotherapy.\nConclusions: Through bioinformatic analysis, we identified a prognosis model consisting of IRGs (CTSC, ALOX12, and RMND5B) in ESCC, providing new ideas for studies related to treatment and prognosis of ESCC.", "claims": [{"id": "claim-method", "statement": "According to the survival information of 81 ESCC samples in TCGA-ESCC dataset, univariate Cox was implemented on DE-IRGs to sift out genes that related to the survival of ESCC. After that, the least absolute shrinkage and selection operator (LASSO) analysis of genes acquired in the previous step was applied to yield genes corresponding to lambda min for proportional hazards (PH) hypothesis test. Subsequently, genes satisfying the PH hypothesis test were incorporated into multivariate Cox analysis to acquire prognosis-related genes.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:38903709", "locator": "sections[7] \"Creation of a prognosis model\" paragraph 2", "quote": "According to the survival information of 81 ESCC samples in TCGA-ESCC dataset, univariate Cox was implemented on DE-IRGs to sift out genes that related to the survival of ESCC. After that, the least absolute shrinkage and selection operator (LASSO) analysis of genes acquired in the previous step was applied to yield genes corresponding to lambda min for proportional hazards (PH) hypothesis test. 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This lane did not download the dataset or read its licence.", "duration_hours": null, "parameters": {}, "inputs": ["data:geo:GSE196756"], "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:GSE196756"], "outputs": ["the replicated result and its comparison"], "instruments": [], "reagents": []}], "materials": [], "instruments": [], "reagents": [], "conditions": {}, "gaps": []}, "data": {"state": "partial", "assets": [{"id": "source:pmid:38903709", "role": "manuscript", "format": "xml", "media_type": "application/xml", "uri": "https://doi.org/10.3389/fonc.2024.1370801", "sha256": "sha256:61f31f893927af6aa33222da8dd1a6e0ad87502184eec5f1ebb670da68d633e2", "bytes": 44280, "access": "open", "state": "resolved", "reader": null, "reader_status": "reader_required", "identifier": "10.3389/fonc.2024.1370801", "version": null, "note": "Full article fetched from PMC; the checksum covers the rendered section body, not the original XML bytes.", "structure": {"pmcid": "PMC11187079", "source": "europe_pmc_fulltext", "coverage": "whole_body_without_references", "text_hash_scope": "rendered_section_body"}}, {"id": "data:geo:GSE196756", "role": "raw", "format": "geo-series", "media_type": "application/vnd.ncbi.geo-series+json", "uri": "https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE196756", "sha256": null, "bytes": null, "access": "open", "state": "resolved", "reader": null, "reader_status": "reader_required", "identifier": "GSE196756", "version": null, "note": "The original contributions presented in the study are included in the article/ Supplementary Material . 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