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• W4387030269 abstract "I read the recently published article by Sun et al.1Sun D. Liu J. Zhou H. et al.Classification of Tumor Immune Microenvironment According to Programmed Death-Ligand 1 Expression and Immune Infiltration Predicts Response to Immunotherapy Plus Chemotherapy in Advanced Patients With NSCLC.J Thorac Oncol. 2023; 18: 869-881https://doi.org/10.1016/j.jtho.2023.03.012Google Scholar with great interest. The authors evaluated the tumor immune microenvironment (TIME) to predict survival outcomes in patients with advanced NSCLC receiving programmed cell death protein-1 (PD-1) (PDCD1) blockade plus chemotherapy or chemotherapy alone. Their model revealed that only patients with high programmed death-ligand 1 (PD-L1) (CD274) expression and high immune filtration benefited from immunotherapy plus chemotherapy. Although efficiently identifying patients likely to benefit from immunotherapy, their model might overlook a subset of patients who would benefit from immunotherapy. It might be possible to develop a more accurate prediction model using the available data. Among the variables reflecting tumor-infiltrating immune cells, the immune score determined by the Estimation of STromal and Immune cells in MAlignant Tumors using Expression data (ESTIMATE) method2Yoshihara K. Shahmoradgoli M. Martínez E. et al.Inferring tumour purity and stromal and immune cell admixture from expression data.Nat Commun. 2013; 4: 2612Google Scholar revealed the best performance in predicting the effectiveness of immunotherapy plus chemotherapy.1Sun D. Liu J. Zhou H. et al.Classification of Tumor Immune Microenvironment According to Programmed Death-Ligand 1 Expression and Immune Infiltration Predicts Response to Immunotherapy Plus Chemotherapy in Advanced Patients With NSCLC.J Thorac Oncol. 2023; 18: 869-881https://doi.org/10.1016/j.jtho.2023.03.012Google Scholar Reflecting a variety of immune and stromal cells, the ESTIMATE immune score provides a comprehensive assessment of the TIME.2Yoshihara K. Shahmoradgoli M. Martínez E. et al.Inferring tumour purity and stromal and immune cell admixture from expression data.Nat Commun. 2013; 4: 2612Google Scholar Among the PD-L1 expression variables, PD-L1 mRNA expression was the most accurate predictor.1Sun D. Liu J. Zhou H. et al.Classification of Tumor Immune Microenvironment According to Programmed Death-Ligand 1 Expression and Immune Infiltration Predicts Response to Immunotherapy Plus Chemotherapy in Advanced Patients With NSCLC.J Thorac Oncol. 2023; 18: 869-881https://doi.org/10.1016/j.jtho.2023.03.012Google Scholar This observation aligns with a previous study3Kowanetz M. Zou W. Gettinger S.N. et al.Differential regulation of PD-L1 expression by immune and tumor cells in NSCLC and the response to treatment with atezolizumab (anti-PD-L1).Proc Natl Acad Sci U S A. 2018; 115: E10119-E10126Google Scholar which revealed that PD-L1 expressed by tumor cells and immune cells played distinct roles in attenuating antitumor immunity. Therefore, PD-L1 expression in both cell types could be important for predicting the effectiveness of immunotherapy. Accordingly, the authors used the ESTIMATE score and PD-L1 mRNA expression for their TIME classification model.1Sun D. Liu J. Zhou H. et al.Classification of Tumor Immune Microenvironment According to Programmed Death-Ligand 1 Expression and Immune Infiltration Predicts Response to Immunotherapy Plus Chemotherapy in Advanced Patients With NSCLC.J Thorac Oncol. 2023; 18: 869-881https://doi.org/10.1016/j.jtho.2023.03.012Google Scholar Nevertheless, the predictive performance of their model could potentially be affected by collinearity between the ESTIMATE immune score and PD-L1 mRNA expression. PD-L1 is expressed by tumor cells and immune cells, especially macrophages, whose activity is captured in the ESTIMATE score. Moreover, immune cells can influence PD-L1 expression in tumor cells. Indeed, a significant correlation was observed between PD-L1 mRNA expression and the ESTIMATE score (Rs = 0.53, p < 0.001),1Sun D. Liu J. Zhou H. et al.Classification of Tumor Immune Microenvironment According to Programmed Death-Ligand 1 Expression and Immune Infiltration Predicts Response to Immunotherapy Plus Chemotherapy in Advanced Patients With NSCLC.J Thorac Oncol. 2023; 18: 869-881https://doi.org/10.1016/j.jtho.2023.03.012Google Scholar suggesting that the association of PD-L1 mRNA expression with treatment outcomes might be influenced by its correlation with the ESTIMATE score. Therefore, the model combining the highest predictive immune score with the highest predictive PD-L1 expression variable might not reveal the highest predictive performance owing to residual confounding. PD-L1 immunohistochemical expression might be a better alternative to PD-L1 mRNA expression in the prediction model because it reflects PD-L1 expression in tumor cells and is thus less likely to be correlated with the ESTIMATE score. Therefore, I suggest that the authors confirm whether their model represents the most predictive combination. In their previous work,4Yang Y. Sun J. Wang Z. et al.Updated overall survival data and predictive biomarkers of sintilimab plus pemetrexed and platinum as first-line treatment for locally advanced or metastatic nonsquamous NSCLC in the phase 3 ORIENT-11 study.J Thorac Oncol. 2021; 16: 2109-2120Google Scholar the authors found that the MHC class II signature and the expression of CIITA, the master regulator of MHC class II genes, were both predictive of the effectiveness of immunotherapy plus chemotherapy. Given that IFN-γ is known to enhance the expression of PD-L1, CIITA, and MHC class II genes,5Ayers M. Lunceford J. Nebozhyn M. et al.IFN-γ-related mRNA profile predicts clinical response to PD-1 blockade.J Clin Invest. 2017; 127: 2930-2940Google Scholar confounding associations among their expressions would exist. Nonetheless, I suggest that the authors also investigate whether the inclusion of the MHC class II signature or CIITA expression in the model could improve its predictive accuracy. Some further exploratory analyses could refine the prediction model, thereby enabling improved treatment strategies for individual patients with NSCLC. Kentaro Inamura: Conceptualization, Writing—original draft, Writing—review and editing. Dr. Inamura was supported financially by JSPS KAKENHI Grant Number 22H02930, the Takeda Science Foundation, the Mochida Memorial Foundation for Medical and Pharmaceutical Research, the Ichiro Kanehara Foundation for the Promotion of Medical Sciences and Medical Care, Grant for Lung Cancer Research provided by the Japan Lung Cancer Society, Foundation for Promotion of Cancer Research in Japan, and the Yakult Bio-Science Foundation. Classification of Tumor Immune Microenvironment According to Programmed Death-Ligand 1 Expression and Immune Infiltration Predicts Response to Immunotherapy Plus Chemotherapy in Advanced Patients With NSCLCJournal of Thoracic OncologyVol. 18Issue 7PreviewAccording to mechanisms of adaptive immune resistance, tumor immune microenvironment (TIME) is classified into four types: (1) programmed death-ligand 1 (PD-L1)–negative and tumor-infiltrating lymphocyte (TIL)–negative (type I); (2) PD-L1–positive and TIL-positive (type II); (3) PD-L1–negative and TIL-positive (type III); and (4) PD-L1–positive and TIL-negative (type IV). However, the relationship between the TIME classification model and immunotherapy efficacy has not been validated by any large-scale randomized controlled clinical trial among patients with advanced NSCLC. Full-Text PDF Open Access" @default.
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• W4387030269 title "Exploiting Tumor Immune Microenvironment to Predict Response to Immunotherapy Plus Chemotherapy in NSCLC" @default.
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