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Tissue- and liquid biopsy-based biomarkers for immunotherapy in breast cancer
Luca Licata1, Marco Mariani1, Federico Rossari2
1Department of Medical Oncology, San Raffaele Hospital, Milan, Italy; School of Medicine and Surgery, Vita-Salute San Raffaele University, Milan, Italy.
Abstract:
Immune checkpoint inhibitors (ICIs) have revolutionized cancer therapy and now represent the mainstay of treatment for many tumor types, including triple-negative breast cancer and two agnostic registrations. However, despite impressive durable responses suggestive of an even curative potential in some cases, most patients receiving ICIs do not derive a substantial benefit, highlighting the need for more precise patient selection and stratification. The identification of predictive biomarkers of response to ICIs may play a pivotal role in optimizing the therapeutic use of such compounds. In this Review, we describe the current landscape of tissue and blood biomarkers that could serve as predictive factors for ICI treatment in breast cancer. The integration of these biomarkers in a "holistic" perspective aimed at developing comprehensive panels of multiple predictive factors will be a major step forward towards precision immune-oncology.
Insights
Immune checkpoint inhibitors (ICIs) offer cancer treatment breakthroughs but benefit only some patients. Identifying predictive biomarkers is crucial for selecting patients likely to respond to ICI therapy, advancing precision oncology.
Area of Science:
- Oncology
- Immunotherapy
Background:
- Immune checkpoint inhibitors (ICIs) have transformed cancer treatment, including for triple-negative breast cancer.
- Despite successes, many patients do not benefit from ICIs, necessitating better patient selection.
- Predictive biomarkers are essential for optimizing ICI therapy and improving patient outcomes.
Purpose of the Study:
- To review current tissue and blood biomarkers for predicting response to ICI treatment in breast cancer.
- To highlight the importance of a holistic approach integrating multiple predictive factors.
Main Methods:
- Literature review of existing biomarkers for ICI response.
- Analysis of current landscape of predictive biomarkers in breast cancer.
Main Results:
- Several tissue and blood biomarkers show potential for predicting ICI response.
- A comprehensive panel of biomarkers is needed for precise patient stratification.
- Integration of biomarkers is key to advancing precision immuno-oncology.
Conclusions:
- Biomarker discovery is critical for maximizing the efficacy of immune checkpoint inhibitors.
- A multi-biomarker strategy will enable personalized ICI treatment selection.
- This approach will drive progress in precision immuno-oncology for breast cancer and other malignancies.
