Spatial transcriptomics reveals the two cancer stem cell-like populations in triple-negative breast cancer

Abstract

AbstractGene expression analysis at the single-cell scale by next generation sequencing has revealed the existence of clonal dissemination in cancer metastasis. The current spatial analysis technologies elucidate the heterogeneity of cell-cell interactions in situ; however, further analysis is needed to elucidate the nature of tumor heterogeneity. To reveal the expressional heterogeneity and cell-cell interactions in primary tumors and metastases, we performed transcriptomic analysis of microtissues dissected from a triple-negative breast cancer (TNBC) cell line MDA-MB-231 xenograft model by our automated tissue microdissection punching technology. This multiple-microtissue transcriptome analysis revealed that there were existed three cell-type clusters in the primary tumor and axillary lymph node metastasis, two of which were cancer stem cell-like clusters (CD44/MYC-high, HMGA1-high). The CD44/MYC-high cluster showed aggressive proliferation with MYC expression. The HMGA1-high cluster exhibited HIF1A activation and upregulation of ribosomal processes. Furthermore, we developed a cell-cell Interaction (CCI) analysis to investigate the ligand-receptor interactions (cancer cell to stroma and stroma to cancer cell) in each spot. The CCI analysis revealed the interaction dynamics generated by the combination of cancer cells and stromal cells in primary tumors and metastases. Two cancer stem cell-like populations were also detected by the scRNA-seq analysis of TNBC patients. In addition, the gene signature of the HMGA1-high cancer stem cell-like cluster has the potential to serve as a novel biomarker for diagnosis. The mixture of these multiple cancer stem cell-like populations may cause differential anticancer drug resistance, increasing the difficulty of curing this cancer.