Background Clinical trials have shown minimal activity of immune checkpoint blockade (ICB) in HR+ breast cancer. While this is, in part, attributable to low tumor-infiltrating lymphocyte (TIL) levels in HR+ breast cancer, a thorough investigation of the immunologic aspects of the tumor microenvironment (TME) is required to fully understand the limited efficacy of ICB in HR+ disease. We sought to characterize the TME of HR+ breast cancer at single cell resolution using single-cell RNA-seq (scRNA-seq), paired with tissue-based cyclic immunofluorescence (t-CyCIF), a multiplexed imaging technology for formalin-fixed paraffin-embedded (FFPE) tissue sections across up to 30 distinct antigen channels. We hypothesized that integrative analysis of clinical samples using these technologies would elucidate inter-patient heterogeneity of the TME of HR+ breast cancer. Methods Surgically excised primary tumor samples were obtained from five, treatment-naïve, HR+ breast cancer patients. Each tumor was divided with half preserved as a FFPE block for t-CyCIF and bulk RNA-seq, and half frozen and later dissociated into single cells for scRNA-seq. For each t-CyCIF cycle, slides were stained with 3 antibodies and a DNA dye. The resultant image was captured with a CyteFinder (RareCyte) slide scanning fluorescence microscope. Each slide was stained for 3-7 cycles (9-21 antibodies), depending on tissue stability. Acquired images were processed (illumination correction, alignment, stitching, and segmentation) using mcmicro (https://mcmicro.org/) and the fluorescence intensity per cell per antibody was determined. After identifying regions where cells were appropriately stained throughout the cycles, the tumor, stromal, and immune cell types were determined based on expressed antigens. Samples were further characterized based on the spatial distribution of T cells within the tumor and categorized into three classes: immunologically cold (lacking T cells), immune stromal-restricted (T cells located predominantly in the stromal) and highly inflamed (T cells located throughout entire tumor). CyCIF data was compared to bulk RNA-seq data for each sample. For scRNA-seq, two samples with high cellularity were identified. The single-cell barcoded library was constructed with 10X Chromium and sequenced with NextSeq (Illumina). The cell types were compared as were gene expressions of the corresponding T cell populations between the two samples. For all experiments, downstream analysis was performed in R. Results CyCIF analysis revealed diverse compositions of immune cell types. In particular, the spatial distributions of T cells revealed that the five samples were classified into the three TME classes: 2 immune cold, 1 immune stromal-restricted, and 2 highly inflamed. This trend was consistent in the corresponding bulk RNA-seq data, in which we found higher expression of an interferon-gamma signaling signature in the two highly-inflamed tumors. For the two scRNA-seq samples, one corresponds to the immunologically cold class in CyCIF and the other to the immune stromal-restricted class. Consistent with CyCIF analysis, scRNA-seq revealed that the immune stromal-restricted tumor had higher T cell infiltration than the immune cold tumor, particularly with a higher abundance of naïve T cells, Th17 cells, and helper T cells. Conclusions While HR+ breast cancer is generally considered immunologically cold, our pilot analysis integrating CyCIF, scRNA-seq, and bulk RNA-seq revealed considerable diversity between the five HR+ samples, including the distribution of T cells relative to tumor cells. Additional samples are being collected to allow for more detailed exploration of the TME heterogeneity of HR+ breast cancer. Citation Format: Kenichi Shimada, Yvonne X Cui, Jonathan S Goldberg, Ricardo Pastorello, Janae Davis, Tuulia Vallius, Lukas Kania, Ashka Patel, Mckenna Moore, Esther R Ogayo, Deborah Dillon, Peter K Sorger, Jennifer L Guerriero, Elizabeth A Mittendorf. Integrative analysis of single-cell transcriptomic and spatial profiles characterized distinct tumor microenvironment phenotypes in hormone receptor positive (HR+) breast cancer [abstract]. In: Proceedings of the 2021 San Antonio Breast Cancer Symposium; 2021 Dec 7-10; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2022;82(4 Suppl):Abstract nr P4-04-06.

Background: Tumor infiltrating lymphocytes (TILs) are observed in low numbers in HR+ breast cancer relative to other subtypes. For T cells (TC) to recognize and respond to a tumor, antigens must be presented on the tumor cell surface via human leukocyte antigen class one (HLA-I) molecules. Hence, the lack of immune infiltration into HR+ tumors could be explained by limited antigen or impaired antigen presentation. We hypothesized that ERS inversely correlates with antigen presentation and T cell infiltration in HR+ tumors. The objective of this study was to comprehensively examine the relationship between ERS, antigen presentation machinery (APM) and TC gene expression in HR+ breast cancer.Methods: Comprehensive gene panels for ERS, APM and TC expression were generated from literature review, GO terms, KEGG pathways, REACTOME, and computationally and manually curated gene lists. Genes expressed in both The Cancer Genome Atlas (TCGA) and Molecular Taxonomy of Breast Cancer International Consortium (METABRIC) were used for subsequent analyses. Tumors were classified into 4 major subtypes (HR+/HER2-, HR+/HER2+, HR-/HER2+, HR-/HER2-) based on estrogen receptor (ER), progesterone receptor and HER2 expression as defined by immunohistochemistry. To statistically refine each gene panel, the genes were hierarchically clustered based on their pairwise Spearman correlation coefficients among HR+/HER2- samples in TCGA (n = 441) and METABRIC (n = 1028). Specifically, clusters were identified by linkage with 2 hallmark genes for each panel: ESR1 and FOXA1 for the ERS panel, HLA-A and NLRC5 for the APM panel, and CD8A and CD8B for the TC panel. Due to overlapping genes in the APM and TC panels, these two panels were combined for subsequent analyses. Final gene panels for ERS and APM/TC were generated from overlapping genes identified in corresponding TCGA and METABRIC clusters. Internal validity of the final gene panels was assessed through pathway enrichment analysis. The panels were then validated through correlation analysis in an independent single institution cohort (HR+ = 25, HER2+ [regardless of HR] = 25, TNBC = 23). Finally, intra and inter-panel correlation analysis results were compared between breast cancer subtypes in both TCGA and METABRIC datasets. Results: Among the 988 genes identified in our manually curated panels, 788 genes were recognized in both TCGA and METABRIC datasets. Statistical refinement resulted in a final 28-gene ERS panel and a final 135-gene combined APM/TC panel. Early and late-estrogen response pathways were enriched in the ERS panel, whereas interferon-gamma response and other innate and acquired immune-related pathways were enriched in the APM/TC panel. Strong inverse correlations between ERS and APM/TC panels were identified in both TCGA and METABRIC datasets. These findings were validated in the single institution cohort where we noted the strength of the correlations varied with the subtype of disease and extent of HR expression. Further analyses in all 4 breast cancer subtypes, in both TCGA and METABRIC datasets, revealed consistent positive correlations within the APM/TC panel across all subtypes. However, positive correlations within the ERS panel corresponded to the subtypes’ dependency on ER pathway, with a strong correlation in HR+ breast cancer and limited correlation in HR- tumors. Conclusions: Using an unbiased data-driven approach, ERS and APM/TC gene panels were generated. Among HR+ tumors, high levels of ERS gene expression significantly correlated with lower levels of APM/TC gene expression providing one potential mechanism for low TC infiltration in HR+ breast cancer. The prognostic and predictive values of these panels are currently being investigated. Citation Format: Jonathan S Goldberg, Xiaoyong Cui, Kenichi Shimada, Sandra McAllister, Sara Tolaney, Adrienne Waks, Rinath Jeselsohn, Jennifer Guerriero, Judith Agudo, Elizabeth Mittendorf. Generation and validation of an estrogen receptor signaling (ERS) gene panel that inversely correlates with antigen presentation and T cell infiltration and activity in hormone receptor positive (HR+) breast cancer [abstract]. In: Proceedings of the 2021 San Antonio Breast Cancer Symposium; 2021 Dec 7-10; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2022;82(4 Suppl):Abstract nr P1-04-13.