TMBleR

TMBleR optimizes and compares tumor mutational burden (TMB) estimation from targeted gene panels and whole-exome sequencing (WES) to evaluate their predictive power for immunotherapy response.

Key Features:

• TMB estimation optimization: Compares and optimizes TMB estimation strategies across targeted gene panels and whole-exome sequencing (WES) to improve predictive performance.
• Panel variability analysis: Evaluates the effects of differing targeted panel genomic sizes and diverse TMB estimation strategies on measured TMB.
• Predictive biomarker assessment: Assesses TMB's association with neoantigen load and its predictive power for immunotherapy response.
• Comparative benchmarking: Enables comparative evaluation of multiple panel-based TMB measurement methodologies to determine clinical impact.
• Computational implementation: Implemented as an R package for reproducible computational analyses.

Scientific Applications:

• Benchmarking TMB assays: Compare panel-based TMB assays against WES to quantify concordance and biases in TMB estimates.
• Predictive biomarker development: Evaluate and validate TMB as a biomarker for predicting immunotherapy response.
• Panel design and optimization: Inform targeted gene panel design and selection of TMB estimation strategies to maximize clinical predictive accuracy.
• Translational oncology research: Bridge research-grade WES approaches and clinical panel-based measurements to support personalized cancer treatment strategies.

Methodology:

Implemented as an R package that compares panel-based TMB measurement strategies to WES-based TMB and assesses their predictive power and association with neoantigen load.