A Spatially Resolved Transcriptome Landscape during Thyroid Cancer Progression
Thyroid cancer ranks as the ninth most common cancer type in terms of incidence worldwide. Furthermore, the global incidence of thyroid cancer has been on the rise over the past decades.Spatial transcriptomics technology systematically profiles gene expression across tissue space by combing high-throughput RNA sequencing and imaging techniques. The applications of ST have revealed high-resolution spatial architecture and cellular crosstalk in many tumor types, advancing the discovery of new targets for diagnosis and therapy. However, the spatial architecture in thyroid cancer and the structural differences in the TME among papillary thyroid cancer (PTC), locally advanced thyroid cancer (LPTC), and Anaplastic thyroid carcinoma (ATC) have been little investigated. Herein , we applied ST and scRNA-seq data to reveal the spatial difference of TME in PTC, LPTC, and ATC samples. Overall design: Specimens collected for single-cell transcriptomics and spatial transcriptomics were from twelves thyroid cancer patients undergoing surgery at Fudan University Shanghai Cancer Center. All the patients signed informed consent before sample collection. In total, 4 para-tumors (N), 4 early thyroid cancer (PTC), 4 locally advanced thyroid cancer (LPTC), and 4 anaplastic thyroid cancer (ATC) were used for spatial transcriptomics. Three out of 4 N, 3 out of 4 PTC, and 3 out of 4 LPTC samples were collected for single-cell transcriptomics. Two experienced pathologists confirmed the pathology of each sample.