Refining patient selection for breast cancer immunotherapy: beyond PD-L1

Therapies that modulate immune response to cancer, such as immune checkpoint inhibitors, began an intense development a few years ago; however, in breast cancer (BC), the results have been relatively disappointing so far. Finding biomarkers for better selection of BC patients for various immunotherapies remains a significant unmet medical need. At present, only tumour tissue programmed death-ligand 1 (PD-L1) and mismatch repair deficiency status are approved as theranostic biomarkers for programmed cell death-1 (PD-1)/PD-L1 inhibitors in BC. However, due to the complexity of tumour microenvironment (TME) and cancer response to immunomodulators, none of them is a perfect selector. Therefore, an intense quest is ongoing for complementary tumour- or host-related predictive biomarkers in breast immuno-oncology. Among the upcoming biomarkers, quantity, immunophenotype and spatial distribution of tumour-infiltrating lymphocytes and other TME cells as well as immune gene signatures emerge as most promising and are being increasingly tested in clinical trials. Biomarkers or strategies allowing dynamic assessment of BC response to immunotherapy, such as circulating/exosomal PD-L1, quantity of white/immune blood cell subpopulations and molecular imaging are particularly suitable for immunotreatment monitoring. Finally, host-related factors, such as microbiome and lifestyle, should also be taken into account when planning integration of immunomodulating therapies into BC management. As none of the biomarkers taken separately is accurate enough, the solution could come from composite biomarkers, which would combine clinical, molecular and immunological features of the disease, possibly powered by artificial intelligence.

Automated summary

Immunotherapy for breast cancer still faces challenges in patient selection and biomarker identification, with only PD-L1 expression and mismatch repair deficiency status approved for PD-1/PD-L1 inhibitors. Ongoing research is focusing on finding additional predictive biomarkers, including immune gene signatures and tumor-infiltrating lymphocytes, to improve treatment efficacy. Dynamic assessment of treatment response through biomarkers like circulating PD-L1 and immune cell quantity, as well as consideration of host factors like microbiome and lifestyle, are important for integrating immunomodulating therapies into breast cancer management.