Breast cancer is a leading cause of cancer death (PMID: 25651787). According to the WHO, breast cancer incidence rose 20% between 2008 and 2012, with 1.7M global diagnoses in 2012. More than 40,000 women died from breast cancer in the U.S. in 2016. Residual disease is important because breast cancer patients with positive margins have a high risk of recurrence and disease-specific mortality. Some studies indicate a surprisingly high risk from positive margins: patients with positive margins have a higher risk of recurrence than patients who have micrometastases to 10 lymph nodes. The elevated risk from positive margins continues to persist even in an era where lumpectomy patients are treated with radiotherapy and systemic therapies. In fact, the increased risk from positive margins is not reduced by additional chemo or a radiation boost. These findings underscore the continued importance of identifying positive margins, especially when clinical trial data will be used to evaluate emerging therapies or compare treatment efficacies. Improving the diagnosis and treatment of breast cancer depends on clinical trials, which must account for confounding clinical variables like residual disease. Evidence-based medicine depends on the quality of the underlying data that are used to evaluate therapeutic options and perform comparative efficacy studies. Unfortunately, existing tests are not reliable enough to accurately and reproducibly detect residual disease. Inaccurate tests contribute to confusion and conflicting trial results. This goal of this project is to establish an improved test for residual breast cancer. This work builds on extensive development and validation of a panel of biomarkers that distinguishes tumors from healthy samples. This project will continue our transition from discovery platforms to a technology that is already widely used in clinical labs. Improved testing would improve clinical trials by identifying high-risk patients, allow researchers to ask fundamental questions about breast cancer treatments, and compare treatment efficacies.
Detection of minimal residual disease for liquid tumors has undergone two revolutions: from microscopy to flow cytometry, and then from flow cytometry to nucleic acid tests. Each advance transformed clinical management. Meanwhile, detection of residual disease for solid tumors continues to rely on microscopic sectioning, which is not an ideal way to hunt for residual disease. This project will establish a research test that uses nucleic acids to detect residual tumor along the surface of surgical breast cancer specimens.
