Tumor-Type-Specific TMB Cutoffs for Improved ICI Outcome Prediction: Large-Scale Analysis with Real-World Targeted NGS Data
Real-world TMB cutoffs derived from distribution-based methods offer improved predictive value for ICI outcomes. Integration of the PD-L1 expression and subclonality status further refines the predictive utility of TMB, improving precision in ICI treatment.
Authors
- Sung‐Min Chun (ORCID: https://orcid.org/0000-0002-3357-1382)
- C.C. Lee
- Ha Ra Jun
- Ji‐Young Lee (ORCID: https://orcid.org/0000-0002-7784-1401)
Institutions
- Ulsan College (KR)
- Asan Medical Center (KR)
- University of Ulsan (KR)
- ToolGen (South Korea) (KR)
Publication Details
- Journal
- Cancer Research and Treatment
- Published
- 2025-09-19
- DOI
- https://doi.org/10.4143/crt.2025.860
- Primary Topic
- Cancer Immunotherapy and Biomarkers
- Type
- article
- Field-Weighted Citation Impact
- 0.00