Updates on breast biomarkers

Recent advancements in breast cancer treatment have ushered in a new era of precision medicine. Novel trials have led to the approval of a growing list of personalized therapies and corresponding biomarkers. These advancements have shifted the pathologist's practice into a leading role in the management breast cancer. Understanding the complex algorithms and diagnostic modalities used to assess predictive and prognostic biomarkers is central for quality oncology care. ER and HER2 subcategorize breast cancers into treatment groups under which different biomarkers and therapies are indicated, while they also serve as predictive biomarkers for specific targeted treatments. This review will cover the evolution and latest updates of the CAP/ASCO guidelines relevant to these two important biomarkers in breast cancer. Still evolving concepts such as HER2 heterogeneity, HER2 low, and HER2-mutated cancers have the potential to continue to change HER2 testing in breast cancers. In addition to ER and HER2, biomarkers used in specific clinical scenarios will be covered. In early-stage ER-positive/HER2-negative disease, multi-gene expression panels (such as OncotypeDX) have emerged as the new standard biomarker when determining if chemotherapy should be added to endocrine therapy. In the more aggressive ER-negative/HER2-positive or triple negative early-stage breast cancers, response to neoadjuvant therapy has proved to be a useful biomarker to help determine if additional therapy should be added for patients with an incomplete response. Ki67 has also recently emerged as a marker that can be used to identify the highest risk ER-positive and HER2-negative cancers if considering adding a cell cycle inhibitor (abemaciclib) to endocrine therapy. Importantly, in the metastatic setting, numerous predictive biomarkers have emerged, including recommendations for germline BRCA mutation testing for all metastatic patients (to determine if PARP inhibitor therapy is an option) and other ER-/HER2-dependent biomarkers such as PD-L1 (for potential immunotherapy in triple negative patients) and PIK3CA mutation status (for potential PI3K inhibitor therapy in ER-positive metastatic patients). Other less common biomarkers of targeted therapy options (e.g., MSI/MMR, TMB, NTRK) as well as comprehensive genomic profiling to identify uncommon targets are also available in the metastatic setting to determine additional treatment options.

Automated summary

Recent advancements in breast cancer treatment have shifted the pathologist's practice into a leading role, as personalized therapies and corresponding biomarkers are approved. Understanding the algorithms and diagnostic modalities used to assess predictive and prognostic biomarkers is crucial for quality oncology care.