Single‐cell transcriptomic landscape reveals the differences in cell differentiation and immune microenvironment of papillary thyroid carcinoma between genders

BACKGROUND: Papillary thyroid carcinoma (PTC) is the main pathological type of thyroid carcinoma (TC). Gender is a prominent background parameter for patients with PTC. Here, we aimed to delineate the differences in cell clusters and immune microenvironment in relation to gender in PTC. METHODS: We generated 6720, 14,666, and 33,373 single-cell transcriptomes that were pooled from the tissues of four male patients with PTC, seven female patients with PTC, and three patients with nodular goiter, respectively. We performed single-cell RNA-sequencing (scRNA-seq) based on BD Rhapsody and characterized the first single-cell transcriptomic landscape of PTC involving gender. The differential cell clusters and their gene profiles were identified and analyzed via a multi-resolution network in male and female patients. The interactions of fibroblasts and endothelial cells with malignant epithelial cells and the difference in the immune infiltration of B and T lymphocytes according to gender were assessed. RESULTS: Malignant epithelial cells were divided into two distinct subsets in male and female patients with PTC. Moreover, significant differences involving inferred copy-number variations (CNVs), gene profiles, and cell differentiation were detected between male and female patients. Regarding the interactions of fibroblasts and endothelial cells with malignant epithelial cells, members of the human leukocyte antigen (HLA) family and their receptors were considered as typical in female patients with PTC, while transforming growth factor beta 1 (TGFB1) and its receptors were typical of male patients with PTC. The characteristics of B cells, including cell clusters, cell differentiation, and dominant gene sets, were significantly different between genders. CONCLUSIONS: Our data revealed the detailed differences in cell clusters and immune microenvironment in PTC according to gender at the single-cell level, which provided new insights into the understanding of the impact of gender on PTC.