세미나

Tumor microenvironments exert a significant influence on changing the transcriptomic state of tumor cells. Single-cell RNA sequencing (scRNAseq) enables the identification of individual cell transcriptomes. However, cell dissociation process results in the loss of neighbor information. Addressing this challenge and aiming to comprehensively monitor gene activity within tissue samples, integrating scRNAseq with spatial transcriptomics (ST) data becomes imperative. In our previous study on Physically Interacting Cell sequencing (PIC-seq), we demonstrated that the gene expression of single cells can be influenced by neighboring cell information. Here, we propose a strategy for identifying niche-specific gene signatures by harmonizing scRNAseq and ST data. This approach was applied to paired scRNAseq and ST datasets of Visium platform across five cancer types (breast cancer, gastrointestinal stromal tumor, liver hepatocellular carcinoma, uterine corpus endometrial carcinoma, ovarian cancer), revealing distinct gene signatures specific to cellular niches and their neighboring counter parts. Remarkably, these niche-specific genes display considerable dissimilarity to cell type markers and exhibit unique functional attributes independent of cancer types. These results show the potential of this integrative approach to unveil novel marker genes and their spatial relationships

keywords: scRNAseq, Spatial transcriptomics, Tumor microenvironments Niche-specific genes