Measuring Tumor Mutational Burden Using Whole-Exome Sequencing

  • Tomas VilimasEmail author
Part of the Methods in Molecular Biology book series (MIMB, volume 2055)


Cancer immunotherapy, particularly a class of antibodies targeting the CTLA4 and PD-1/PD-L1 negative regulators of immune response (collectively called the immune checkpoint), is one of the most promising approaches for cancer treatment and the use of immune checkpoint inhibitors (ICI) has demonstrated remarkable success in several types of cancer. In studies of unselected patient populations, it was shown that melanoma, non small cell lung cancer (NSCLC), renal cell carcinoma and urothelial carcinoma patients treated with CTLA-4, PD-1 or PD-L1 inhibitors had an improved objective response and overall survival relative to chemotherapy or historical trends, and several ICIs have been approved for the treatment of these and other indications.

More recently, several groups found that response to ICI therapy strongly correlates with a high burden of single nucleotide variant (SNV) mutations in the tumor genome, termed tumor mutational burden (TMB), usually expressed as the number of nonsynonymous single nucleotide variants per megabase of sequenced genome. These studies showed that TMB is a promising predictive biomarker for ICI response in melanoma, urothelial carcinoma and a subset of NSCLC patients. High TMB relates to ICI response via the production of increased numbers of novel, mutant peptide antigens (neoantigens), resulting in enhanced recognition and killing of neoantigen-presenting tumor cells by cytotoxic CD8+ T cells.

In this chapter I describe the current best-practice methods for measuring TMB in tumor specimens using whole-exome sequencing (WES).

Key words

Tumor mutational burden Next-generation sequencing Whole-exome sequencing Immune checkpoint inhibitor Cancer immunotherapy biomarker Nonsynonymous mutations Neoantigens 



I would like to express my deep gratitude to Chris Karlovich, Justine McCutcheon, Brandie Fullmer, Rajesh Patidar, Bishu Das, Li Chen, Mickey Williams, and Rasa Vilimas for their critical reviews, editorial assistance, and support with creating figures for the chapter.


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Copyright information

© Springer Science+Business Media, LLC, part of Springer Nature 2020

Authors and Affiliations

  1. 1.Molecular Characterization LaboratoryFrederick National Laboratory for Cancer Research, Leidos Biomedical Research, Inc.FrederickUSA

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