Panels and Models for Accurate Prediction of Tumor Mutation Burden in Tumor Samples

Overview

Journal NPJ Precis Oncol

Publisher Springer Nature

Specialty Oncology

Date 2021 Apr 14

PMID 33850256

Citations 6

Authors

Elizabeth Martinez-Perez

Miguel Angel Molina-Vila

Cristina Marino-Buslje

Affiliations

Soon will be listed here.

Abstract

Immune checkpoint blockade (ICB) is becoming standard-of-care in many types of human malignancies, but patient selection is still imperfect. Tumor mutation burden (TMB) is being evaluated as a biomarker for ICB in clinical trials, but most of the sequencing panels used to estimate it are inadequately designed. Here, we present a bioinformatics-based method to select panels and mathematical models for accurate TMB prediction. Our method is based on tumor-specific, forward-step selection of genes, generation of panels using a linear regression algorithm, and rigorous internal and external validation comparing predicted with experimental TMB. As a result, we propose cancer-specific panels for 14 malignancies which can offer reliable, clinically relevant estimates of TMBs. Our work facilitates a better prediction of TMB that can improve the selection of patients for ICB therapy.

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