Funding Progress

The most common metastasis of breast cancer is to the brain. Current therapies are not meaningfully improving survival. Tumor-associated macrophages (TAMs) in breast cancer usually display an alternatively activated (M2-like) phenotype, which suppresses antitumor immunity and aids in metastasis, including brain metastasis. Therefore, reprogramming TAMs from M2-to M1-like phenotype could be a promising therapeutic approach for metastatic breast cancer. However, the molecular basis governing macrophage reprogramming during breast cancer brain metastasis remains elusive and there is no effective approach to reprogram TAMs in the tumor microenvironment. We propose to employ integrated strategies to reveal whether and how TAM reprogramming contributes to breast cancer brain metastasis. We also plan to determine how TAM reprogramming can work with immune checkpoint inhibitors to suppress brain metastasis of breast cancer.

Approximately 70% of all breast cancers are due to hormone receptor (ER)-positive BCa. Currently, ER+ BCa diagnosed patients can be treated with hormone therapy via drugs, such as tamoxifen. However, this type of breast cancer can lead to reoccurrences many years after treatment. In this particular study, we have developed a new therapy by targeting metabolic signaling to overcome endocrine resistance in breast cancer.

Metastatic breast cancer (MBC) is an aggressive cancer for which there currently is no cure. However, there are many treatment options to help control the disease and allow patients to live longer. Despite available treatments, there is a limited understanding of how to select treatments for patients to better extend their survival. This study plans to look for changes in DNA which will help identify the treatment best suited to each patient. To achieve this, blood samples are collected from patients with MBC currently receiving treatment and changes in their DNA over time are studied to understand how these changes correlate with their response to treatment. The hope is to leverage this new dataset to develop a blood-based test which can help MBC patients select the most effective treatment.

A tool of ‘single-cell transcriptional profiling’ (scRNA seq)—gives the ability to measure how much any single human gene in the entire genome is turned ‘on’ or ‘off’ within a single cell. Utilizing scRNA seq on patient tissue samples offers the potential to identify cell populations and genes responsible for disease pathology in a highly precise manner. In diseases like TNBC where there are no treatment options outside of routine chemotherapy, scRNA seq holds the potential to make precision medicine a reality. Our laboratory has created a new method, SCALES (Spectral Correlation Analysis of Layered Evolutionary Signals), to precisely identify drivers of pathology. Preliminary results show substantial promise in precisely defining transcriptional signatures of TNBC. This study is centered around validating statistical predictions with the goal of establishing a framework to identify high-value targets for gene therapy. If successful, we believe we can develop new treatments for TNBC, reflecting a new paradigm for data-driven precision medicine.