Zhijie Wang1, Jianchun Duan1, Guoqiang Wang2, Jing Zhao2, Jiachen Xu1, Jiefei Han1, Zhengyi Zhao2, Jun Zhao3, Bo Zhu4, Minglei Zhuo3, Jianguo Sun4, Hua Bai1, Rui Wan1, Xin Wang1, Kailun Fei1, Shuhang Wang5, Xiaochen Zhao2, Yuzi Zhang2, Mengli Huang2, Depei Huang2, Chuang Qi2, Chan Gao2, Yuezong Bai2, Hua Dong6, Lei Xiong2, Yanhua Tian1, Di Wang1, Chunwei Xu7, Wenxian Wang8, Junling Li1, Xingsheng Hu1, Shangli Cai2, Jie Wang9. 1. State Key Laboratory of Molecular Oncology, Department of Medical Oncology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, P. R. China. 2. The Medical Department, 3D Medicines, Inc., Shanghai, P. R. China. 3. Department of Thoracic Medical Oncology, Peking University School of Oncology, Beijing Cancer Hospital & Institute, Beijing, P. R. China. 4. Cancer Institute, Xinqiao Hospital, Army Medical University, Chongqing, P. R. China. 5. GCP Center, National Cancer Center/Cancer Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, P. R. China. 6. The Bioinformatics Department, 3D Medicines, Inc., Shanghai, P. R. China. 7. Department of Pathology, Fujian Cancer Hospital, Fujian Medical University, Fujian, P. R. China. 8. Department of Chemotherapy, Zhejiang Cancer Hospital, Zhejiang, P. R. China. 9. State Key Laboratory of Molecular Oncology, Department of Medical Oncology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, P. R. China. Electronic address: zlhuxi@163.com.
Abstract
INTRODUCTION: Blood-based tumor mutational burden (bTMB) has been studied to identify patients with NSCLC who would benefit from anti-programmed cell death protein 1 (anti-PD-1) or anti-programmed death ligand 1 (anti-PD-L1) therapies. However, it failed to predict overall survival (OS) benefits, which warrants further exploration. METHODS: Three independent cohorts of patients with NSCLC treated with immunotherapy were used in this study. A new bTMB algorithm was first developed in the two independent cohorts (POPLAR, N = 211, and OAK, N = 462) and further validated in the third National Cancer Center (NCC) cohort (N = 64). RESULTS: bTMB-H (bTMB ≥ cutoff point) was not associated with favorable OS after immunotherapy regardless of the cutoff points in either the POPLAR and OAK or the NCC cohorts (p > 0.05) owing to its correlation with the amount of circulating tumor DNA, which was associated with poor OS. In the POPLAR and OAK cohorts, with allele frequency (AF) adjustment, a high AF bTMB (HAF-bTMB, mutation counts with an AF > 5%) was strongly correlated with the amount of circulating tumor DNA (Pearson r = 0.65), whereas a low AF bTMB (LAF-bTMB, mutation counts with an AF ≤ 5%) was not (Pearson r = 0.09). LAF-bTMB-H was associated with favorable OS (hazard ratio [HR] = 0.70, 95% confidence interval [CI]: 0.52-0.95, p = 0.02), progression-free survival (PFS; HR = 0.62, 95% CI: 0.47-0.80, p < 0.001), and objective response rate (ORR) (p < 0.001) after immunotherapy but not chemotherapy, with a cutoff point of 12 trained in the POPLAR cohort and validated in the OAK cohort. The LAF-bTMB algorithm was further validated in the NCC cohort in which LAF-bTMB-H was associated with OS (HR = 0.20, 95% CI: 0.05-0.84, p = 0.02), PFS (HR = 0.30, 95% CI: 0.13-0.70, p = 0.003), and ORR (p = 0.001). CONCLUSIONS: We developed and validated a new LAF-bTMB algorithm as a feasible predictor of OS, PFS, and ORR after anti-PD-(L)1 therapies in patients with NSCLC, which needs to be prospectively validated.
INTRODUCTION: Blood-based tumor mutational burden (bTMB) has been studied to identify patients with NSCLC who would benefit from anti-programmed cell death protein 1 (anti-PD-1) or anti-programmed death ligand 1 (anti-PD-L1) therapies. However, it failed to predict overall survival (OS) benefits, which warrants further exploration. METHODS: Three independent cohorts of patients with NSCLC treated with immunotherapy were used in this study. A new bTMB algorithm was first developed in the two independent cohorts (POPLAR, N = 211, and OAK, N = 462) and further validated in the third National Cancer Center (NCC) cohort (N = 64). RESULTS:bTMB-H (bTMB ≥ cutoff point) was not associated with favorable OS after immunotherapy regardless of the cutoff points in either the POPLAR and OAK or the NCC cohorts (p > 0.05) owing to its correlation with the amount of circulating tumor DNA, which was associated with poor OS. In the POPLAR and OAK cohorts, with allele frequency (AF) adjustment, a high AF bTMB (HAF-bTMB, mutation counts with an AF > 5%) was strongly correlated with the amount of circulating tumor DNA (Pearson r = 0.65), whereas a low AF bTMB (LAF-bTMB, mutation counts with an AF ≤ 5%) was not (Pearson r = 0.09). LAF-bTMB-H was associated with favorable OS (hazard ratio [HR] = 0.70, 95% confidence interval [CI]: 0.52-0.95, p = 0.02), progression-free survival (PFS; HR = 0.62, 95% CI: 0.47-0.80, p < 0.001), and objective response rate (ORR) (p < 0.001) after immunotherapy but not chemotherapy, with a cutoff point of 12 trained in the POPLAR cohort and validated in the OAK cohort. The LAF-bTMB algorithm was further validated in the NCC cohort in which LAF-bTMB-H was associated with OS (HR = 0.20, 95% CI: 0.05-0.84, p = 0.02), PFS (HR = 0.30, 95% CI: 0.13-0.70, p = 0.003), and ORR (p = 0.001). CONCLUSIONS: We developed and validated a new LAF-bTMB algorithm as a feasible predictor of OS, PFS, and ORR after anti-PD-(L)1 therapies in patients with NSCLC, which needs to be prospectively validated.