Towards predictive biomarkers for immunotherapy response in breast cancer patients


Abstract

Immunotherapy using anti-PD(L)1 has revolutionized treatment for various tumor types. Early data have shown durable responses in a small subgroup of breast cancer patients. So far, the response rates appear higher for breast tumors that are triple negative, PDL1-positive and/or harbor high levels of immune cells. Both comprehensive analyses of the breast tumor microenvironment and exploiting research on biomarkers in other cancer types, such as melanoma and lung cancer, may contribute to the discovery of accurate biomarkers to select breast cancer patients for immunotherapy. Here we summarize key features of the breast tumor microenvironment as well as putative predictive biomarkers established in other tumor types. Insights from both fields can guide future studies to enable personalized breast cancer immunotherapy.

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Practice points

  • Although response rates to anti-PD(L)1 are moderate in breast cancer, durable responses are seen.

  • No accurate biomarkers for the prediction of response to immunotherapy in breast cancer are available yet.

  • Response rates to anti-PD(L)1 appear higher in triple-negative breast cancer (TNBC) and PDL1-positive breast cancer.

  • Early data show that TNBC patients with a tumor harboring relatively high levels of tumor infiltrating lymphocytes have a better outcome after anti-PD(L)1.

  • As seen in melanoma patients, TNBC patients with high serum lactate dehydrogenase levels are less likely to respond to anti-PD(L)1 monotherapy.

  • Exploiting research on immune biomarkers in other cancer types can guide the analyses of samples of breast cancer patients treated with anti-PD(L)1 in order to find predictive biomarkers.

  • It needs to be determined whether potential biomarkers predicting response to anti-PD(L)1 have solely predictive value or capture information on prognosis as well.