Integrating pleural PD-1+CD8+ T cell as a complement variable into LENT score to assess patients with lung adenocarcinoma complicated with MPE.

Malignant pleural effusion (MPE) is a common complication of advanced non-small cell lung cancer (NSCLC), particularly in lung adenocarcinoma, and is associated with poor prognosis. A better understanding of the role of PD-1+CD8+ T cells in the pleural environment and their relevance to patient survival could facilitate better clinical decision-making.

We performed a cohort study involving NSCLC patients with MPE. The abundance of pleural PD-1+CD8+ T cells was measured using flow cytometry. We also assessed the presence of epidermal growth factor receptor (EGFR) mutations and programmed death-ligand 1 (PD-L1) expression in the pleural fluid. The LENT score, a known prognostic tool, was combined with pleural PD-1+CD8+ T cell abundance to develop a novel scoring system, the Immuno-LENT score. The model's performance was validated using the bootstrap method and concordance index (C-index) calculation.

We found that PD-1+CD8+ T cells were present in the pleural fluid of all patients with MPE. Notably, the abundance of these cells was influenced by EGFR mutations, while PD-L1 expression had little effect. Patients with a higher abundance of pleural PD-1+CD8+ T cells also exhibited higher LENT scores, correlating with poorer survival. The Immuno-LENT score, incorporating both the LENT score and pleural PD-1+CD8+ T cell abundance, was found to be an independent prognostic factor. The model showed strong statistical robustness with a high C-index.

The combination of pleural PD-1+CD8+ T cells with the LENT score offers a more accurate prognostic tool for survival prediction in NSCLC patients with MPE. Our findings suggest that the Immuno-LENT score could guide clinical management and inform therapeutic decisions for these patients, improving patient outcomes by tailoring interventions based on a more comprehensive biomarker profile.
Cancer
Chronic respiratory disease
Care/Management

Authors

Jiang Jiang, Lv Lv, Zhang Zhang, Qu Qu, Chen Chen
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