Spatial transcriptome sequencing revealed spatial trajectory in the Non-Small Cell Lung Carcinoma

Abstract

ABSTRACTDeepening understanding in the heterogeneity of tumors is critical for clinical treatment. Here we investigate tissue-wide gene expression heterogeneity throughout a multifocal lung cancer using the spatial transcriptomics (ST) technology. We identified gene expression gradients in stroma adjacent to tumor regions that allow for re-understanding of the tumor micro-environment. The establishment of these profiles was the first step towards an unbiased view of lung cancer and can serve as a dictionary for future studies. Tumor subclones were detected by ST technology in our research, while we contrast the EMT ability among in subclones which inferred the possible trajectory of tumor metastasis and invasion, which was confirmed by constructing the pseudo-time model of spatial transition within subclones. Together, these results uncovered lung cancer spatial heterogeneity, highlight potential tumor micro-environment differences and spatial evolution trajectory, and served as a resource for further investigation of tumor microenvironment.