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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.
Sun, Dongchen; Liu, Jiaqing; Zhou, Huaqiang; Shi, Mengting; Sun, Jiya; Zhao, Shen; Chen, Gang; Zhang, Yaxiong; Zhou, Ting; Ma, Yuxiang; Zhao, Yuanyuan; Fang, Wenfeng; Zhao, Hongyun; Huang, Yan; Yang, Yunpeng; Zhang, Li.
Afiliación
  • Sun D; Department of Medical Oncology, Sun Yat-sen University Cancer Center, Guangzhou, People's Republic of China; State Key Laboratory of Oncology in South China, Guangzhou, People's Republic of China; Collaborative Innovation Center for Cancer Medicine, Guangzhou, People's Republic of China; Zhongshan S
  • Liu J; State Key Laboratory of Oncology in South China, Guangzhou, People's Republic of China; Collaborative Innovation Center for Cancer Medicine, Guangzhou, People's Republic of China; Department of Intensive Care Unit, Sun Yat-sen University Cancer Center, Guangzhou, People's Republic of China.
  • Zhou H; Department of Medical Oncology, Sun Yat-sen University Cancer Center, Guangzhou, People's Republic of China; State Key Laboratory of Oncology in South China, Guangzhou, People's Republic of China; Collaborative Innovation Center for Cancer Medicine, Guangzhou, People's Republic of China.
  • Shi M; Department of Medical Oncology, Sun Yat-sen University Cancer Center, Guangzhou, People's Republic of China; State Key Laboratory of Oncology in South China, Guangzhou, People's Republic of China; Collaborative Innovation Center for Cancer Medicine, Guangzhou, People's Republic of China; Zhongshan S
  • Sun J; New Drug Biology and Translational Medicine, Innovent Biologics, Inc., Suzhou, People's Republic of China.
  • Zhao S; Department of Medical Oncology, Sun Yat-sen University Cancer Center, Guangzhou, People's Republic of China; State Key Laboratory of Oncology in South China, Guangzhou, People's Republic of China; Collaborative Innovation Center for Cancer Medicine, Guangzhou, People's Republic of China.
  • Chen G; Department of Medical Oncology, Sun Yat-sen University Cancer Center, Guangzhou, People's Republic of China; State Key Laboratory of Oncology in South China, Guangzhou, People's Republic of China; Collaborative Innovation Center for Cancer Medicine, Guangzhou, People's Republic of China.
  • Zhang Y; Department of Medical Oncology, Sun Yat-sen University Cancer Center, Guangzhou, People's Republic of China; State Key Laboratory of Oncology in South China, Guangzhou, People's Republic of China; Collaborative Innovation Center for Cancer Medicine, Guangzhou, People's Republic of China.
  • Zhou T; Department of Medical Oncology, Sun Yat-sen University Cancer Center, Guangzhou, People's Republic of China; State Key Laboratory of Oncology in South China, Guangzhou, People's Republic of China; Collaborative Innovation Center for Cancer Medicine, Guangzhou, People's Republic of China.
  • Ma Y; Department of Medical Oncology, Sun Yat-sen University Cancer Center, Guangzhou, People's Republic of China; State Key Laboratory of Oncology in South China, Guangzhou, People's Republic of China; Collaborative Innovation Center for Cancer Medicine, Guangzhou, People's Republic of China.
  • Zhao Y; Department of Medical Oncology, Sun Yat-sen University Cancer Center, Guangzhou, People's Republic of China; State Key Laboratory of Oncology in South China, Guangzhou, People's Republic of China; Collaborative Innovation Center for Cancer Medicine, Guangzhou, People's Republic of China.
  • Fang W; Department of Medical Oncology, Sun Yat-sen University Cancer Center, Guangzhou, People's Republic of China; State Key Laboratory of Oncology in South China, Guangzhou, People's Republic of China; Collaborative Innovation Center for Cancer Medicine, Guangzhou, People's Republic of China.
  • Zhao H; Department of Medical Oncology, Sun Yat-sen University Cancer Center, Guangzhou, People's Republic of China; State Key Laboratory of Oncology in South China, Guangzhou, People's Republic of China; Collaborative Innovation Center for Cancer Medicine, Guangzhou, People's Republic of China.
  • Huang Y; Department of Medical Oncology, Sun Yat-sen University Cancer Center, Guangzhou, People's Republic of China; State Key Laboratory of Oncology in South China, Guangzhou, People's Republic of China; Collaborative Innovation Center for Cancer Medicine, Guangzhou, People's Republic of China.
  • Yang Y; Department of Medical Oncology, Sun Yat-sen University Cancer Center, Guangzhou, People's Republic of China; State Key Laboratory of Oncology in South China, Guangzhou, People's Republic of China; Collaborative Innovation Center for Cancer Medicine, Guangzhou, People's Republic of China.
  • Zhang L; Department of Medical Oncology, Sun Yat-sen University Cancer Center, Guangzhou, People's Republic of China; State Key Laboratory of Oncology in South China, Guangzhou, People's Republic of China; Collaborative Innovation Center for Cancer Medicine, Guangzhou, People's Republic of China. Electronic
J Thorac Oncol ; 18(7): 869-881, 2023 07.
Article en En | MEDLINE | ID: mdl-36948245
ABSTRACT

INTRODUCTION:

According 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.

METHODS:

On the basis of RNA-sequencing and immunohistochemistry data from the ORIENT-11 study, we optimized the TIME classification model and evaluated its predictive value for the efficacy of immunotherapy plus chemotherapy.

RESULTS:

PD-L1 mRNA expression and immune score calculated by the ESTIMATE method were the strongest predictors for the efficacy of immunotherapy plus chemotherapy. Therefore, they were determined as the optimized definition of the TIME classification system. When compared between combination therapy and chemotherapy alone, only the type II subpopulation with high immune score and high PD-L1 mRNA expression was significantly associated with improved progression-free survival (PFS) (hazard ratio = 0.12, 95% confidence interval 0.06-0.25, p < 0.001) and overall survival (hazard ratio = 0.27, 95% confidence interval 0.13-0.55, p < 0.001). In the combination group, the type II subpopulation had a much longer survival time, not even reaching the median PFS or overall survival, but the other three subpopulations were susceptible to having similar PFS. In the chemotherapy group, there was no marked association between survival outcomes and TIME subtypes.

CONCLUSIONS:

Only patients with both high PD-L1 expression and high immune infiltration could benefit from chemotherapy plus immunotherapy in first-line treatment of advanced NSCLC. For patients lacking either PD-L1 expression or immune infiltration, chemotherapy alone might be a better treatment option to avoid unnecessary toxicities and financial burdens.
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Texto completo: 1 Base de datos: MEDLINE Asunto principal: Carcinoma de Pulmón de Células no Pequeñas / Neoplasias Pulmonares Tipo de estudio: Clinical_trials / Prognostic_studies / Risk_factors_studies Límite: Humans Idioma: En Revista: J Thorac Oncol Año: 2023 Tipo del documento: Article

Texto completo: 1 Base de datos: MEDLINE Asunto principal: Carcinoma de Pulmón de Células no Pequeñas / Neoplasias Pulmonares Tipo de estudio: Clinical_trials / Prognostic_studies / Risk_factors_studies Límite: Humans Idioma: En Revista: J Thorac Oncol Año: 2023 Tipo del documento: Article