Abstract P2-21-08: Digital spatial profiling of RNA and protein in the invasive lobular breast cancer microenvironment

Abstract Invasive lobular breast cancer (ILC) is an understudied subtype of breast cancer with late recurrence, metastasis to serosal surfaces, such as the peritoneum, and dismal long-term outcome. We previously reported better patient outcome in ER+ breast cancers with high glucocorticoid receptor (GR) expression (Pan et al 2011). Preliminary data suggests more favorable patient outlook in the ILC subtype when tumors express higher levels of GR. The dynamic interaction between a tumor and its microenvironment leads to phenotypic changes in stromal cells and the extracellular matrix to promote growth or invasion of malignant cells. ILC is histologically distinct from invasive ductal carcinoma and is characterized by discohesive tumor cells that grow as “Indian files” due to lack of the cell adhesion molecule E-cadherin. Because of these differences we expect the tumor microenvironment (TME) to be quite unique in ILC compared to other breast cancer subtypes. We hypothesized that differing levels of expression of nuclear receptors by tumor cells would impact cells residing within the stroma, presumably through paracrine signaling. Immunohistochemistry for 25 ILC biopsies revealed a wide variation in GR expression, ranging from completely negative to strongly positive. Our goal was to gain insight into how GR presence or absence in ILC cells might impact gene and protein expression in malignant cells and their TME. We were inspired to examine how crosstalk between the GR-positive or GR-negative cancer cells and their respective tumor microenvironment (TME) differentially impact stromal cell gene expression as well as the immune cell milieu. Bulk expression profiling is inadequate to examine molecular profiles of the tumor and stroma separately. Therefore, we used nanoString GeoMx® high-plex digital spatial profiling of RNA and protein expression in GR-positive and GR-negative primary ILC. We first performed spatial gene expression using the Whole Transcriptome Atlas (WTA) for six primary ILC, two of which were strongly positive for GR, two GR-negative and 2 tumors harboring both GR-positive and GR-negative regions. To examine the tumor cells and the stroma independently we segmented regions into panCK-positive and panCK-negative segments and analyzed those separately. Intriguing differences were observed between GR-positive and negative ILC, for the tumor cells as well as for the TME. Implementation of the Spatial Deconvolution script embedded within the GeoMx® software revealed striking differences in the abundance of immune cells, endothelial cells and fibroblasts in the stroma of GR-positive vs GR-negative ILC. Macrophages and other myeloid subsets were present in significantly higher numbers in the TME of GR-positive compared to GR-negative ILC. The contribution of B- and T-cell subsets as well as endothelial cells and fibroblasts were also notably different. To more precisely define the spatial distribution and abundance of various cell subtypes and their association with tumor cells, we are including protein DSP as an added layer to complement the WTA. We are also performing RNA and protein DSP for an additional ten GR-positive and ten GR-negative ILC. Thus, we will test our initial observations and expand our investigation to generate comprehensive molecular profiles of ILC tumors and stromal cells and acquire a deeper understanding of how GR expression/activation influences the crosstalk between ILC cells and their TME. We anticipate that differences in gene and protein expression will provide clues as to how GR activation affects proliferative and adhesive properties of ILC through modification of the TME. Citation Format: Lynda B. Bennett, Candace Frerich, Sunati Sahoo, Cheryl Lewis, Indu Raman, Min Xu, Guanchun Chen, Suzanne D. Conzen. Digital spatial profiling of RNA and protein in the invasive lobular breast cancer microenvironment [abstract]. In: Proceedings of the 2022 San Antonio Breast Cancer Symposium; 2022 Dec 6-10; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2023;83(5 Suppl):Abstract nr P2-21-08.