Finding signals in the noise: Elucidating the many sources of heterogeneity in breast cancer metastasis using single-cell ‘omics

Despite improvement in screening and early detection, breast cancer remains the second leading cause of cancer related deaths among women according to the American Cancer Society. These deaths can be almost entirely attributed to metastatic disease, which is far more difficult to treat than local disease. It is therefore critical to gain a deeper understanding of what drives breast cancer metastasis and how the cells that surround metastatic tumors, known as the metastatic niche, respond to breast cancer cells to facilitate or inhibit their outgrowth. In this work, we use single-cell RNA-sequencing (scRNA-seq) and custom analytical pipelines to characterize breast cancer metastasis from multiple angles. We start by looking at pre-neoplastic breast epithelial cells and investigate the conserved lineage relationships between each epithelial cell state using a pseudotime analysis pipeline. We next look at matched primary tumor and metastatic cells from triple-negative breast cancer patient-derived xenograft models and identify biomarkers of micrometastasis (very small, early stage metastatic tumors) using generalized linear models which we validate are prognostically useful for relapse-free survival. And finally, we characterize the response heterogeneity of microglia, the brain resident macrophage, to breast cancer brain metastasis, demonstrate that these responses are conserved in human microglia, and show that microglia facilitate tumor regression using a genetic depletion model. In all of these projects, we find that our newly defined cell states and tissue heterogeneity can be generalized across patients and models, suggesting that much of the noise seemingly inherent to breast cancer metastasis can be understood by asking the right questions. Further, by observing these systems at the single-cell level, we demonstrate the plasticity of breast epithelial cells in homeostasis, identify novel biomarkers and patient stratification opportunities for early breast cancer metastasis detection, and suggest new therapeutic routes for breast cancer brain metastasis patients