While the number of deaths from breast cancer is decreasing and the disease-free survival has been significantly prolonged; there is still a large number of patients with ER-positive (ER+) disease that do not respond to the therapy or relapse. Therefore, for many patients the chosen therapy is inadequate and ultimately leads to treatment failure. We hypothesize that this is associated with the cellular heterogeneity of the tumour microenvironment, such as the presence of a heterogeneous mix of neoplastic cells with distinct molecular subtypes.
Single cell technologies have provided powerful tools to address this issue, by allowing for better understanding of breast cancer heterogeneity at an unprecedented level and resolution. Previous studies using single-cell RNA-seq (scRNA-seq) have highlighted remarkable epithelial cell diversity and the presence of different transcriptional patterns across tumours. However, their association with outcome and survival is unclear. However, a focus on the luminal breast cancers, which constitute the majority of breast cancers, is lacking.
This work will comprehensively map the cellular heterogeneity of ER+ breast cancers by generating an integrated cellular atlas of ~200 treatment-naive primary tumours. These samples have been collected over 7 years from breast cancer biopsies and surgeries and have detailed clinical annotation. We have developed cryopreservation and tissue processing workflows to yield high-viability cell suspensions from primary clinical tissue. We have benchmarked and optimized computational processes for data demultiplexing, annotation and integration to permit processing of high-quality single-cell transcriptomes from ~ one million cells.
This is the first study of ER+ breast cancers, at this scale, at cellular resolution. We hypothesize it will unravel and define novel cellular subtypes and interactions that drive the adverse events in ER-positive breast cancer patients, leading to high translational impact.