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Integration of Transcriptome Profiling and Single-Cell Sequencing Analysis to Establish a CD8+ T Cell-Related
Yi-Yang Jiang1, Min-Min Yu2, Xia Cui3
1The First School of Clinical Medicine, Shandong University of Traditional Chinese Medicine, Jinan, China.
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.
Methods:
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.
Results:
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.
Conclusion:
This study constructed an innovative CD8+ T cell-related risk model, advancing clinical diagnosis and offering valuable therapeutic strategies for patients with NSCLC.
