Title: Identifying Genetic Patterns in Breast Cancer Metastasis with Single-Cell Sequencing
Abstract: The spread of breast cancer to organs such as lung, lymph, brain, and bone accounts for a vast number of cancer related deaths with a median survival of 3 years after metastatic disease diagnosis. It is therefore crucial to find ways to target not only tumor driver mutations but also any drivers of metastasis. To do this, we must first identify both the phenotypic and genotypic patterns in metastasis, a task that is complicated by intratumoral heterogeneity. The system our lab uses to study this phenomenon is a patient derived xenograft (PDX) model, which allows us to serially passage a human breast cancer tumor in immunocompromised NOD/SCID mice. We then apply single-cell whole exome sequencing of the tumor xenograft and associated metastases to give a direct readout of which mutations occur together in cells to find sets of mutations shared between individual metastatic cells and individual tumor cells. Further, our approach can better estimate tumor heterogeneity than standard bulk sequencing approaches, giving insight into whether metastatic disease arises from one or many tumor subclones. This presentation will show preliminary results from a shallowly sequenced dataset of 90 tumor cells and 6 lung metastatic cells and focus on experimental design for the project moving forward.