Integrative spatial omics reveals distinct tumor-promoting multicellular niches and immunosuppressive mechanisms in African American and European American patients with TNBC (Spatial Transcriptomic 10X Visium portion)

Racial disparities in triple-negative breast cancer (TNBC) outcomes have been reported. However, the biological mechanisms underlying these disparities remain unclear. We integrated imaging mass cytometry and spatial transcriptomics, to characterize the tumor microenvironment (TME) of African American (AA) and European American (EA) patients with TNBC. The TME in AA patients was characterized by interactions between endothelial cells, macrophages, and mesenchymal-like cells, which were associated with poor patient survival. In contrast, the EA TNBC-associated niche is enriched in T-cells and neutrophils suggestive of an exhaustion and suppression of otherwise active T cell responses. Ligand-receptor and pathway analyses of race-associated niches found AA TNBC to be “immune cold” and hence immunotherapy resistant tumors, and EA TNBC as ‘inflamed’ tumors that evolved a distinctive immunosuppressive mechanism. Our study revealed the presence of racially distinct tumor-promoting and immunosuppressive microenvironments in AA and EA patients with TNBC, which may explain the poor clinical outcomes.   This dataset contains the 10X Visium Spatial Transcriptomic data of TNBC patients. There are two cohorts.   Baylor Scott and White (BSW) cohort: 10x.visium.tar.gz, containing 10 patients with TNBC from Baylor Scott and White affiliated Hospital.  Each sample is made of Space Ranger processed spot-separated gene expression data (processed to HDF5 AnnData file). There are also H&E images, and spot coordinate files available.    For Georgia validation cohort, 400 genes used for validation of ESG signatures (associated with BA-Community 1 and WA-Community-1) were obtained and provided by Ritu Aneja's lab. These 400 genes' spot-based expression data across Black and White TNBC patients are provided. See file georgia.validation.visium.tar.gz. Expression was normalized by total counts per spot, followed by log-normalization by Giotto.   As well in our paper, we integrated a published racial TNBC cohort for deriving some of initial results in the paper. This refers to the Bassiouni et al (Cancer Research) paper in Carpten's group. GSM_giotto_processed.tar.gz refers to this dataset, which we deposit here. The data were normalized by Giotto using standard procedure.