1. Tumor-infiltrating lymphocytes predict efficacy of immunotherapy in advanced non-small cell lung cancer: a single-center retrospective cohort study.
- Author
-
Zhang, Wenjie, Li, Sumei, Zhang, Chufeng, Mu, Zhengshuai, Chen, Kaili, and Xu, Zhenshu
- Subjects
LUNG cancer ,STATISTICS ,IMMUNE checkpoint inhibitors ,STAINS & staining (Microscopy) ,IMMUNOHISTOCHEMISTRY ,MULTIVARIATE analysis ,RETROSPECTIVE studies ,LYMPHOCYTES ,TREATMENT effectiveness ,CANCER patients ,RESEARCH funding ,HISTOLOGICAL techniques ,KAPLAN-Meier estimator ,SURVIVAL analysis (Biometry) ,DESCRIPTIVE statistics ,PREDICTION models ,PROGRESSION-free survival ,IMMUNOTHERAPY ,LONGITUDINAL method ,PROPORTIONAL hazards models ,OVERALL survival - Abstract
The current study aimed to investigate the correlation between tumor-infiltrating lymphocytes (TILs) and immunotherapy efficacy in patients with advanced non-small cell lung cancer (NSCLC). Eighty-nine patients with advanced NSCLC who received immune checkpoint inhibitors (ICIs) monotherapy were retrospectively enrolled in this study. The density of TILs in paraffin-embedded pathological tissues taken before receiving ICIs was quantitatively analyzed by immunohistochemical staining. The density of TILs was treated as a dichotomous variable using the median as the cutoff value. The Kaplan–Meier analysis was used to assess survival differences between groups. Univariate and multivariate Cox analyses were applied to screen out independent prognostic factors and further construct a nomogram prediction model to predict survival. Survival analysis showed that CD8
+ TILs, CD4+ TILs, and IFN-γ+ Th1 were significant positive indicators for predicting progression-free survival (PFS) and overall survival (OS) (p < 0.05), whereas Foxp3+ Treg were a significant negative predictor (p < 0.05). The predictive role of IL-4+ Th2 was not apparent in this study and requires further investigation and exploration (p > 0.05). The nomogram prediction model exhibited good discriminative ability, with C-index values of 0.723 (95% CI 0.682-0.764) and 0.793 (95% CI, 0.738-0.848) in the training cohort and validation cohort, respectively. The AUC values indicated that the nomogram prediction model had high predictive value and the calibration curve presented good prediction accuracy. TILs could predict the efficacy of immunotherapy and may become a promising predictor. [ABSTRACT FROM AUTHOR]- Published
- 2023
- Full Text
- View/download PDF