Tumor-Type-Specific TMB Cutoffs for Improved ICI Outcome Prediction: Large-Scale Analysis with Real-World Targeted...

Area of Science:

• Oncology
• Genomics
• Immunotherapy

Background:

• Tumor mutational burden (TMB) is a promising biomarker for predicting response to immune checkpoint inhibitors (ICIs).
• Clinical utility of TMB is currently limited by methodological inconsistencies in its determination.
• Standardized TMB assessment is crucial for optimizing immunotherapy efficacy.

Purpose of the Study:

• To evaluate the predictive value of TMB for immune checkpoint inhibitor (ICI) outcomes using next-generation sequencing (NGS) data.
• To compare different TMB cutoff methodologies for predicting patient response to ICIs.
• To explore the role of PD-L1 expression and subclonality in refining TMB's predictive power.

Main Methods:

• Retrospective analysis of 9,459 cancer patients undergoing tumor-only targeted NGS.
• TMB-high (TMB-H) cutoffs determined using an interquartile range (IQR)-based method.
• Validation against The Cancer Genome Atlas (TCGA) TMB and a universal 10 mut/Mb cutoff; assessment of PD-L1 expression and subclonality.

Main Results:

• IQR-based TMB-H significantly associated with longer progression-free survival (PFS) in ICI-treated cohorts (HR=0.85, p=0.02).
• Significant PFS benefit observed in bladder, bowel, and uterine cancers; lung cancer patients with high TMB and PD-L1 (≥90%) showed longest PFS (HR=0.64, p=0.021).
• The universal 10 mut/Mb cutoff lacked statistical significance; high subclonality in TMB-H non-hypermutated cases correlated with worse overall survival (OS) (p=0.032).

Conclusions:

• Real-world TMB cutoffs derived from distribution-based methods improve prediction of ICI outcomes.
• Integrating PD-L1 expression and subclonality status refines TMB's predictive utility.
• Enhanced TMB assessment improves precision in guiding ICI treatment decisions.