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- Title
The Optimal Tumor Mutational Burden Cutoff Value as a Novel Marker for Predicting the Efficacy of Programmed Cell Death-1 Checkpoint Inhibitors in Advanced Gastric Cancer.
- Authors
Jae Yeon Jang; Youngkyung Jeon; Sun Young Jeong; Sung Hee Lim; Won Ki Kang; Jeeyun Lee; Seung Tae Kim
- Abstract
Purpose: The optimal tumor mutational burden (TMB) value for predicting treatment response to programmed cell death-1 (PD-1) checkpoint inhibitors in advanced gastric cancer (AGC) remains unclear. We aimed to investigate the optimal TMB cutoff value that could predict the efficacy of PD-1 checkpoint inhibitors in AGC. Materials and Methods: Patients with AGC who received pembrolizumab or nivolumab between October 1, 2020, and July 27, 2021, at Samsung Medical Center in Korea were retrospectively analyzed. The TMB levels were measured using a next-generation sequencing assay. Based on receiver operating characteristic curve analysis, the TMB cutoff value was determined. Results: A total 53 patients were analyzed. The TMB cutoff value for predicting the overall response rate (ORR) to PD-1 checkpoint inhibitors was defined as 13.31 mutations per megabase (mt/Mb) with 56% sensitivity and 95% specificity. Based on this definition, 7 (13.2%) patients were TMB-high (TMB-H). The ORR differed between the TMB-low (TMB-L) and TMB-H (8.7% vs. 71.4%, P=0.001). The progression-free survival and overall survival (OS) for 53 patients were 1.93 (95% confidence interval [CI], 1.600–2.268) and 4.26 months (95% CI, 2.992–5.532). The median OS was longer in the TMB-H (20.8 months; 95% CI, 2.292–39.281) than in the TMB-L (3.31 months; 95% CI, 1.604–5.019; P=0.049). Conclusions: The TMB cutoff value for predicting treatment response in AGC patients who received PD-1 checkpoint inhibitor monotherapy as salvage treatment was 13.31 mt/Mb. When applying the programmed death ligand-1 status to TMB-H, patients who would benefit from PD-1 checkpoint inhibitors can be selected.
- Subjects
SOUTH Korea; REFERENCE values; STOMACH cancer; RECEIVER operating characteristic curves
- Publication
Journal of Gastric Cancer, 2023, Vol 23, Issue 3, p476
- ISSN
2093-582X
- Publication type
Article
- DOI
10.5230/jgc.2023.23.e29