A prognostic gene model of immune cell infiltration in diffuse large B-cell lymphoma.

{"sci_version": "1.2", "schema": "https://corpus.bntrg.co.uk/sci/1.0/sci.schema.json", "id": "pmid:32844062", "kind": "science-record", "revision": 4, "content_hash": "sha256:ca4e4b2f13695418f9dc745f3cb7de1376081238af31ec59640aaef3a34bb495", "created_at": "2026-11-01T15:41:08Z", "updated_at": "2026-11-01T21:23:41Z", "generator": {"name": "corpus-assay-engine", "run_id": "reading-sci-2026-11-01"}, "paper": {"state": "complete", "title": "A prognostic gene model of immune cell infiltration in diffuse large B-cell lymphoma.", "doi": "10.7717/peerj.9658", "pmid": "32844062", "authors": ["Hao Zhou", "Chang Zheng", "De-Sheng Huang"], "journal": "PeerJ", "year": 2020, "abstract": "BACKGROUND: Immune cells in the tumor microenvironment are an important prognostic indicator in diffuse large B-cell lymphoma (DLBCL). However, information on the heterogeneity and risk stratification of these cells is limited. We sought to develop a novel immune model to evaluate the prognostic intra-tumoral immune landscape of patients with DLBCL.\nMETHODS: The ESTIMATE and CIBERSORT algorithms were used to estimate the numbers of 22 infiltrating immune cells based on the gene expression profiles of 229 patients with DLBCL who were recruited from a public database. The least absolute shrinkage and selection operator (Lasso) penalized regression analyses and nomogram model were used to construct and evaluate the prognostic immunoscore (PIS) model for overall survival prediction. An immune gene prognostic score (IGPS) was generated by Gene Set Enrichment Analysis (GSEA) and Cox regression analysis was and validated in an independent NCBI GEO dataset (GSE10846).\nRESULTS: A higher proportion of activated natural killer cells was associated with a poor outcome. A total of five immune cells were selected in the Lasso model and DLBCL patients with high PIS showed a poor prognosis (hazard ratio (HR) 2.16; 95% CI [1.33-3.50]; P = 0.002). Differences in immunoscores and their related outcomes were attributed to eight specific immune genes involved in the cytokine-cytokine receptor interaction and chemokine signaling pathways. The IGPS based on a weighted formula of eight genes is an independent prognostic factor (HR: 2.14, 95% CI [1.40-3.28]), with high specificity and sensitivity in the validation dataset.\nCONCLUSIONS: Our findings showed that a PIS model based on immune cells is associated with the prognosis of DLBCL. We developed a novel immune-related gene-signature model associated with the PIS model and enhanced the prognostic functionality for the prediction of overall survival in patients with DLBCL.", "claims": [{"id": "claim-method", "statement": "A hazard ratio (HR) with a 95% confidence interval (95% CI) was calculated by multivariate Cox proportional hazard models to quantify the strength of the association between relevant parameters and overall survival.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:32844062", "locator": "sections[7] \"Prognostic analysis\" paragraph 2", "quote": "A hazard ratio (HR) with a 95% confidence interval (95% CI) was calculated by multivariate Cox proportional hazard models to quantify the strength of the association between relevant parameters and overall survival."}], "state": "complete"}, {"id": "claim-data-access", "statement": "The following information was supplied regarding data availability:The data that support the findings of this study are publicly available at The Cancer Genome Atlas (search terms: CTSP-DLBCL1, NCICCR-DLBCL) and the NCBI Gene Expression Omnibus (GSE10846). The R codes are available in the Supplemental Files.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:32844062", "locator": "sections[19] \"Additional Information and Declarations\" paragraph 4", "quote": "The following information was supplied regarding data availability:The data that support the findings of this study are publicly available at The Cancer Genome Atlas (search terms: CTSP-DLBCL1, NCICCR-DLBCL) and the NCBI Gene Expression Omnibus (GSE10846). 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This lane did not download the dataset or read its licence.", "duration_hours": null, "parameters": {}, "inputs": ["data:geo:GSE10846"], "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:GSE10846"], "outputs": ["the replicated result and its comparison"], "instruments": [], "reagents": []}], "materials": [], "instruments": [], "reagents": [], "conditions": {}, "gaps": []}, "data": {"state": "partial", "assets": [{"id": "source:pmid:32844062", "role": "manuscript", "format": "xml", "media_type": "application/xml", "uri": "https://doi.org/10.7717/peerj.9658", "sha256": "sha256:4c17b636af022082dc0e0285e4021bb06283e75d0db437bc219d54c93194f374", "bytes": 33478, "access": "open", "state": "resolved", "reader": null, "reader_status": "reader_required", "identifier": "10.7717/peerj.9658", "version": null, "note": "Full article fetched from PMC; the checksum covers the rendered section body, not the original XML bytes.", "structure": {"pmcid": "PMC7414766", "source": "europe_pmc_fulltext", "coverage": "whole_body_without_references", "text_hash_scope": "rendered_section_body"}}, {"id": "data:geo:GSE10846", "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=GSE10846", "sha256": null, "bytes": null, "access": "open", "state": "resolved", "reader": null, "reader_status": "reader_required", "identifier": "GSE10846", "version": null, "note": "The following information was supplied regarding data availability:The data that support the findings of this study are publicly available at The Cancer Genome Atlas (search terms: CTSP-DLBCL1, NCICCR-DLBCL) and the NCBI Gene Expression Omnibus (GSE10846). 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