Abstract 4342: Breast cancer multi-omic single cell profiling identifies key progressive disease markers

Abstract Breast cancer is one of the most diagnosed cancers and has a complex tumor microenvironment (TME). Breast tumors are subtyped by receptor expression, and all have a high degree of cellular heterogeneity. We analyzed tumors from 8 individuals with early-stage breast cancer. The patients had either triple negative breast (TNBC) or an estrogen receptor (ER) positive cancer. The tumors and normal adjacent tissue were profiled by single-nuclei gene expression (GEX) and ATAC data using the 10X multi-ome methodology. Gene set analysis identified specific epithelial clusters associated with the estrogen early/late response, epithelial mesenchymal transition, and several key cytokine pathways. From those epithelial cells, a subset highly proliferative in nature emerged. It consists of both ER positive and TNBC tumor types enriched for specific DNA transcriptional motifs including those for stem cell (Yamanaka) factors and other cellular proliferation motifs. GEX proliferation markers such as MKi-67 were also highly expressed. Overlaying GEX and ATAC data, it was possible to filter the numerous differentially expressed genes and peaks into a subset of genes specific to progressive breast cancer within the proliferative cluster. Those genes included ESRP1, POP4, CCNE1, and AAMDC all of which are associated with progressive breast cancer. To further elucidate the complexity of the TME, we examined clusters of fibroblasts from our dataset. A difference in cancer associated fibroblast marker gene expression was related to the level of ER expression expressed in the tumor epithelium. In general, ER-low tumor fibroblasts had higher expression of immune cancer associated fibroblasts (iCAFs) markers while ER-positive and TNBC tumors had greater expression of extracellular matrix associated markers (emCAFs). Specific clusters were enriched for emCAFs and iCAFs representing another critical part of the TME. In conclusion, using a multi-modal single-cell approach to the TME allowed the identification of an aggressive cluster of epithelial cells marked by genes for cellular proliferation and noted therapeutic targets while also characterizing other critical TME components especially, CAFs. Citation Format: Hugh Russell, Manisha Rao, Grant Duclos, Rogelio Aguilar, Nick Barkas, Megan Callahan, Ojasvi Chaudhary, Peter Gathungu, Chris Rands, Varsha Shankarappa, Daniel Stetson, Asaf Rotem, Maurizio Scaltriti, Brian Dougherty. Breast cancer multi-omic single cell profiling identifies key progressive disease markers abstract. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts) ; 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84 (6Suppl): Abstract nr 4342.