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High Tumor Mutation Burden and Other Immunotherapy Response Predictors in Breast Cancers: Associations and Therapeutic Opportunities

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Abstract

Background

The recent development of effective immunotherapies with immune checkpoint inhibitors for the treatment of cancer has rekindled the interest for the immune system and its activation for an anti-cancer response. At the same time, it has become evident that not all types of cancers respond equally to these treatments, and even within the same tumor type only a subset of patients derive clinical benefit. Biomarkers predictive of response to immunotherapy have been sought and in certain occasions incorporated in the indication for treatment. These include expression of PD-L1 and defects in DNA mismatch repair (MMR).

Objective

Tumor mutation burden (TMB) has been associated with response to immune checkpoint inhibitors. The current investigation examines TMB as a biomarker of response to immunotherapy in breast cancer.

Patients and Methods

Publicly available data from the breast cancer study of The Cancer Genome Atlas (TCGA) and the METABRIC study were analyzed. Parameters examined included the TMB and specific mutations that may impact on TMB. In addition, correlations with breast cancer sub-types were investigated.

Results

The percentage of breast cancers with high TMB (more than 192 mutations per sample) was low (3.5–4.6%) in luminal and triple-negative cancers and higher (14.1%) in the HER2-positive subset. Almost all cancers with high TMB had defects in MMR proteins or the replicative polymerases POLE and POLD1.

Conclusions

Small sub-sets of breast cancers with high TMB exist and may present an opportunity for effective immunotherapeutic targeting.

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Correspondence to Ioannis A. Voutsadakis.

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No external funding was used in the preparation of this article.

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Ioannis A. Voutsadakis declares that he has no conflicts of interest that might be relevant to the contents of this article.

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Voutsadakis, I.A. High Tumor Mutation Burden and Other Immunotherapy Response Predictors in Breast Cancers: Associations and Therapeutic Opportunities. Targ Oncol 15, 127–138 (2020). https://doi.org/10.1007/s11523-019-00689-7

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