Breast Cancer Awareness Month is an opportunity to recognize the profound impact the disease has on patients, families and communities. About one in eight women in the United States are expected to develop breast cancer in their lifetime, making it one of the most common cancers.
Although the incidence of breast cancer continues to rise, death rates have decreased by 44% since 1989. This improvement can be attributed to a combination of early detection, increased awareness and improved treatment, particularly advances in precision oncology. By using molecular profiling, including genomic analysis, precision oncology enables physicians to choose treatments tailored to a patient’s specific disease.
As precision oncology has reshaped breast cancer care, it has also transformed the technologies and strategies used to guide clinical decisions. At HDMZ, we’ve watched these changes unfold through our work with clients who are developing the tools and therapies that advance the field.
In this blog, we’ll explore how molecular insights have changed the way breast cancer is approached, tracing the evolution of our understanding of the disease, the development of tools that enable more targeted treatment decisions and the opportunities that lie ahead.
From one diagnosis to distinct molecular diseases
Advances in molecular analysis have fundamentally changed how we understand breast cancer. What used to be regarded as a single disease, characterized primarily by its morphology and extent of spread, is now known to be a diverse group of diseases that originate in the same organ, but are distinct in their underlying biology.
The identification of estrogen receptor (ER) and progesterone receptor (PR) established an important distinction between tumors that may respond to endocrine therapy and those that do not. Tamoxifen, which blocks estrogen receptor signaling on cancer cells, demonstrated the clinical value of targeting tumor biology. Subsequently, the discovery of the HER2 gene, which is amplified or overexpressed in 20% to 25% of breast cancers, and the development of trastuzumab, a targeted monoclonal antibody for HER2-positive cancers, marked another major advance: the ability to identify HER2 overexpression or amplification and match patients to a therapy directed at that target.
Gene expression profiling extended this approach beyond individual receptors. Researchers identified intrinsic molecular subtypes based on patterns of gene activity, including Luminal A, Luminal B, HER2-enriched and Basal-like. These subtypes reflect differences in tumor behavior and clinical course, underscoring the limitations of classification based on clinical and pathologic factors alone. For instance, ER-positive/HER2-negative breast cancer encompasses diverse intrinsic subtypes with markedly different clinical trajectories. While many cases are indolent Luminal A tumors, a subset exhibits an aggressive, Basal-like biology.
These distinctions have implications for understanding recurrence risk and treatment response. They also raise questions about whether additional molecular information can help identify patients whose disease behaves differently from what clinical characteristics alone would suggest.
Translating molecular insights into clinical practice
Understanding the biological differences between breast cancers has changed how clinicians assess recurrence risk and select treatment. One of the best established applications is the use of multigene expression assays in early-stage disease. By measuring patterns of gene activity, these tests provide information about tumor biology that complements conventional clinicopathological factors and can help guide decisions about chemotherapy or endocrine therapy.
Major clinical trials, such as MINDACT, TAILORx and RxPONDER, have demonstrated how these assays can help identify patients who may benefit from chemotherapy and those who may be able to safely avoid it, sparing many patients unnecessary treatment. Large, prospective real-world studies, such as the FLEX Study, which links genomic test results with clinical outcomes, have taken this a step further to inform regimen selection itself.
For example, recent FLEX data show that genomic risk stratification using MammaPrint, a 70-gene recurrence risk assay, and BluePrint, an 80-gene molecular subtyping assay, can identify patients who may derive survival benefit from anthracycline-based chemotherapy. Because this treatment is aggressive and often causes significant side effects, the findings may help clinicians better identify which patients are most likely to derive meaningful benefit.
Molecular characterization through next-generation sequencing has also enabled treatments directed at specific biological targets. HER2 testing established a basis for selecting patients for HER2-directed therapies, while identification of germline BRCA1/2 mutations can inform the use of PARP inhibitors in eligible patients.
In ER-positive, HER2-negative advanced breast cancer, alterations in PIK3CA, AKT1 and PTEN can inform the use of therapies targeting the PI3K/AKT signaling pathway. Mutations in ESR1, which encodes the estrogen receptor, can emerge under the selective pressure of endocrine therapy and contribute to acquired resistance, helping inform subsequent treatment choices.
More recently, the recognition of HER2-low disease has expanded treatment options for patients with previously treated advanced breast cancer through certain HER2-directed antibody-drug conjugates. Together, these developments illustrate how identifying specific molecular features can reveal treatment options within established clinical disease categories.
Understanding the biological differences between breast cancers has changed how clinicians assess recurrence risk and select treatment.
Future directions of precision oncology in breast cancer
New technologies are continuously being developed to advance precision therapy capabilities in breast cancer. Liquid biopsies evaluating minimal residual disease offer the potential to detect recurrence months before it appears on imaging. However, moving this approach from a prognostic tool to standard practice hinges on ongoing clinical trials proving that preemptively changing therapy at the molecular stage improves overall survival.
Artificial intelligence (AI) has also become a major part of the discussion, with emerging digital pathology approaches designed to assess recurrence risk directly from standard pathology slides, a capability that could significantly expand patient access to rapid, cost-effective risk stratification. Multimodal, AI-based approaches that help integrate genomics, imaging and clinical data to further enhance precision medicine are under development.
Concurrently, a growing awareness of the importance of real-world evidence in bridging the gap between clinical research and daily practice has prompted large, observational studies that complement clinical trials. By capturing real-world outcomes from older, higher-risk and underrepresented patient groups typically excluded from randomized trials, these initiatives promise to make clinical research findings more generalizable to diverse, everyday patient populations.
Precision oncology has already made great strides in improving patient outcomes. In the coming years, with expanding capabilities, it will continue reshaping how we think about and treat breast cancer.
