Revisiting Tumor Mutational Burden Cutoff: Multi-Study Replicability in Immunotherapy
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PURPOSE
Tumor Mutational Burden (TMB) is a crucial biomarker for predicting the effectiveness of cancer immunotherapy. However, ongoing debates about the optimal cutoff significantly impact the clinical application of immunotherapy. The purpose of our study is to comprehensively evaluate TMB cutoffs for predicting immunotherapy outcomes across multiple studies, considering both cancer type and outcome endpoint, using statistically principled approaches.
METHODS
We analyzed data from PredictIO, curated through a PubMed search for studies involving immune checkpoint blockade treatment in the adjuvant setting, excluding those involving combinations with chemotherapy, targeted treatment, or radiation. The included studies, published between January 2015 and June 2022, required tumor sequencing data from whole exomes or targeted gene panels for TMB assessment. Outcome endpoints included clinical benefit rate (CBR), progression-free survival (PFS), and overall survival (OS). CBR was defined as the rate of complete response, partial response, or stable disease lasting at least six months, according to RECIST 1.1 criteria. OS and PFS were defined as the interval from treatment initiation to death and disease progression, respectively. TMB was uniformly derived from tumor sequencing data, representing the count of nonsynonymous mutations relative to the target sequencing size. TMB cutoffs were evaluated for outcome associations using study replicability analysis, alongside individual-study analysis and random-effects meta-analysis for comparison.
RESULTS
The data provided sufficient evidence of replicable outcome associations for specific TMB cutoffs in melanoma, lung cancer, and bladder cancer. The FDA-recommended cutoff of 10 mutations per megabase showed replicable associations in melanoma for OS (p-value < 0.01) and CBR (p-value < 0.01), though more replicable cutoffs were identified for the latter. Lower cutoffs of 4 and 2 were found to be replicable in lung cancer for CBR (p-value = 0.04) and in bladder cancer for OS (p-value < 0.01), respectively. No cutoff was deemed replicable for the other cancer type and outcome combinations, due to no association, inadequate power, or insufficient data.
CONCLUSION
A pan-cancer cutoff of 10 mutations per megabase may not be optimal for predicting immunotherapy outcomes. Further studies are needed to determine appropriate cutoffs specific to cancer types and outcomes through statistically principled replicability analyses.
