Integration of Transcriptome Profiling and Single-Cell Sequencing Analysis to Establish a CD8+ T Cell-Related Prognostic Model for Patients With NSCLC: From Assessment to Therapy.

{"sci_version": "1.2", "schema": "https://corpus.bntrg.co.uk/sci/1.0/sci.schema.json", "id": "pmid:41223031", "kind": "science-record", "revision": 3, "content_hash": "sha256:fe619bce540298c6742781ee801411360d591acc6c6d823ac836f0e6431ec7a0", "created_at": "2026-11-01T20:31:15Z", "updated_at": "2026-11-01T22:14:58Z", "generator": {"name": "corpus-assay-engine", "run_id": "reading-sci-2026-11-01"}, "paper": {"state": "complete", "title": "Integration of Transcriptome Profiling and Single-Cell Sequencing Analysis to Establish a CD8+ T Cell-Related Prognostic Model for Patients With NSCLC: From Assessment to Therapy.", "doi": "10.1002/cam4.71337", "pmid": "41223031", "authors": ["Yi-Yang Jiang", "Min-Min Yu", "Xia Cui", "Xue Li", "Bin-Bin Li", "Jing-Tao Zhang", "Fei Xu"], "journal": "Cancer medicine", "year": 2025, "abstract": "BACKGROUND: Non-small cell lung cancer (NSCLC) is the leading cause of cancer-related mortality, characterized by a poor prognosis. The advent of immunotherapy has significantly altered the treatment landscape for NSCLC. CD8+ T cells, key mediators of immune responses, play a pivotal role in the prognosis and progression of the disease. This study aims to develop a CD8+ T-cell-related prognostic model to enable more precise prognostic evaluations and enhance clinical decision-making in immunotherapy for patients with NSCLC.\nMETHODS: Three datasets (TCGA-NSCLC, GSE183219, and GSE42127) were analyzed using Weighted Gene Co-expression Network Analysis and single-cell analysis. A risk model was constructed through least absolute shrinkage and selection operator, univariate Cox regression, and multivariate Cox regression analyses. A prognostic nomogram was subsequently developed, integrating the risk model and clinical characteristics of patients with NSCLC, and validated using multiple methods. Additionally, Gene Set Enrichment Analysis, immune-related analyses, and drug susceptibility assays were performed to assess responses to immunotherapy and chemotherapy.\nRESULTS: CD52, CD69, and PLIN2 were identified as biomarkers and used to construct a risk model with high accuracy. Based on the risk model, patients were classified into high- and low-risk subgroups. The model demonstrated strong predictive performance in both the training and validation cohorts. When combined with pathologic N and T stages, a clinical prognostic nomogram was developed, outperforming individual indicators in prognostic prediction. Immune landscape analyses revealed a robust immune system in the low-risk group, whereas immune dysfunction was observed in the high-risk group, suggesting differential immunotherapy efficacy between the cohorts. Additionally, paclitaxel showed significantly greater effectiveness in the high-risk group.\nCONCLUSION: This study constructed an innovative CD8+ T cell-related risk model, advancing clinical diagnosis and offering valuable therapeutic strategies for patients with NSCLC.", "claims": [{"id": "claim-method", "statement": "Univariate and multivariate Cox regression analyses were performed using the “survival” R package to identify independent prognostic factors.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:41223031", "locator": "sections[9] \"Establishing and Estimating a Clinical Prognostic Model\" paragraph 2", "quote": "Univariate and multivariate Cox regression analyses were performed using the “survival” R package to identify independent prognostic factors."}], "state": "complete"}, {"id": "claim-data-access", "statement": "Data will be made available on request.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:41223031", "locator": "sections[29] \"Data Availability Statement\" paragraph 2", "quote": "Data will be made available on request."}], "state": "complete"}], "gaps": []}, "experiment": {"state": "complete", "objective": null, "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:41223031"], "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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