Publication date: Jul 01, 2019
Retrospective analyses show that a high tumor mutation burden (TMB) is associated with an improved response and prolonged survival with immune checkpoint inhibitor (ICI) treatment in several different malignancies, including melanoma.
TMB reflects the total number of somatic mutations in tumor DNA, and is used as a surrogate measure of tumor neoantigen load, which is the spectrum of tumor-specific antigens that can induce reactive T cells.
Despite this promise, expression of the checkpoint regulator programmed death-ligand 1 (PD-L1) – by immunohistochemical assessment – is the only marker that is currently used to select patients for treatment with ICI therapies. There are several challenges to the routine use of TMB to identify melanoma patients for ICI treatment.
To produce a more robust biomarker, assessments of PD-L1 and TMB could be integrated with other tumor alterations, such as indels or copy number changes, and other positive and negative predictors of response to ICIs, such as tumor neoantigen load, T cell infiltration, and inflammatory gene signatures.
Tumor mutational burden (TMB) has been shown to be a predictive biomarker of immune checkpoint inhibitor treatment outcome in several cancers.
TMB is the total of somatic mutations (synonymous and nonsynonymous) in the DNA of tumor cells and is quantified per coding area (megabase, Mb).
This hypothesis further says that tumors with a high neoantigen load have high recognition by antigen-reactive T cells, and thus are likely to respond to immune checkpoint inhibitors.
TMB is a surrogate for tumor neoantigen load, and is therefore a predictor of treatment outcome with immune checkpoint inhibition, Ugurel said.
Malignant melanoma exomes from 64 patients who were treated with CTLA-4 inhibition had their TMB quantified by whole exome sequencing.
Foundation Medicine and Memorial Sloan Kettering have panels that have been tested in translational studies in different cancer entities, showing a correlation between TMB and outcome with immune checkpoint inhibition.
“Quantification of TMB will soon be open for widespread clinical use supported by a switch from whole exome sequencing to targeted gene panel sequencing,” she said.
Although TMB identifies a population with melanoma that has greater benefit from CTLA-4 blockade, the degree of overlap in TMB between patients who derived clinical benefit from treatment and those who did not is very high.
A team of researchers led by Marta Luksza, PhD, of the Institute for Advanced Study in Princeton, New Jersey, constructed a mathematical model showing two determinants of a tumor neoantigen predict for responses to anti-CTA4 therapy in patients with melanoma: Renal cell carcinoma represents another cancer in which tumors with intermediate levels of TMB respond to immune checkpoint blockade.