Publication-only abstracts (abstract number preceded by an "e"), published in conjunction with the 2019 ASCO Annual Meeting but not presented at the Meeting, can be found online only.
A novel algorithm to redefine blood-based tumor mutational burden for optimized prediction of clinical benefits from immunotherapy.
Metastatic Non-Small Cell Lung Cancer
Lung Cancer—Non-Small Cell Metastatic
2019 ASCO Annual Meeting
J Clin Oncol 37, 2019 (suppl; abstr e20514)
Author(s): Zhijie Wang, Guoqiang Wang, Jianchun Duan, Jing Zhao, Zhengyi Zhao, Hua Bai, Shuhang Wang, Shangli Cai, Jie Wang; State Key Laboratory of Molecular Oncology, Department of Medical Oncology, National Cancer Center/Cancer Hospital, Chinese Academy of Medical Sciences &Peking Union Medical College, Beijing, China; The Medical Department, 3D Medicines Inc., Shanghai, China; State Key Laboratory of Molecular Oncology, Department of Medical Oncology, National Cancer Center/Cancer Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, China; Cancer Hospital Chinese Academy of Medical Sciences, Beijing, China
Background: The previous reported predictive biomarker, blood-based tumor mutational burden (bTMB) can only predict progression-free survival (PFS) while failed to predict overall survival (OS) from atezolizumab over docetaxel, or to predict PFS or OS in the atezolizumab arm. Here we aimed to explore the underlying mechanism and develop an algorithm to redefine bTMB as a predictor of both PFS and OS from immunotherapy. Methods: Data from POPLAR (N = 211) and OAK (N = 642) trials was used for algorithm development in bTMB redefinition. The derived algorithm was validated in two independent NSCLC cohorts (cohort 1 N = 64; cohort 2 N = 184). Results: In POPLAR and OAK cohorts, bTMB-H was not associated with favorable OS (P = 0.68, HR 1.06; 95% CI, 0.81-1.38) from immunotherapy at the reported cut-point of 16, which was validated in our independent cohort 1 (P = 0.86, HR 0.39; 95% CI, 0.39-1.89). Further analysis showed that blood TMB was associated with maximum somatic allele frequency (Pearson r = 0.47 in POPLAR and OAK cohorts, Pearson r = 0.36 in the independent cohort 2), which was a negative prognostic factor and may impede the predictive value of bTMB. The bTMB was thus redefined (referred to as bTMB*) with mutations with allele frequency > 5% filtered out, when the correlation between bTMB and MSAF became less correlated (Pearson r = 0.09 and 0.07, respectively). Both better PFS and OS benefits from atezolizumab over docetaxel was observed in the redefined bTMB-H group as tested in POPLAR (PFS HR = 0.41, 95% CI, 0.21-0.80; OS HR = 0.34, 95% CI, 0.16-0.71) and validated in OAK (PFS HR = 0.49, 95% CI, 0.33-0.71; OS HR = 0.47, 95% CI, 0.29-0.77) with the cut-point of 12, while there was no significant association in redefined bTMB-L group (P interaction = 0.01 and 0.04 for PFS and OS in POPALR, < 0.001 and 0.06 for OAK PFS and OS in OAK). The results was further validated in our independent cohort 1 treated with anti-PD-1/PD-L1, where the redefined bTMB-H was also associated with favorable PFS compared with bTMB-L (Logrank P = 0.005, HR = 0.34, 95% CI, 0.26-0.75) and OS (Logrank P = 0.08, HR 0.35, 95% CI, 0.11-1.18). Conclusions: The allele frequency needs to be taken into consideration in the algorithm of bTMB. The redefined bTMB may serve as a predictor of both PFS and OS of immunotherapy.