Construction of a Single-cell Atlas of Thyroid Cancer

Differentiated thyroid cancer generally has a favorable prognosis; however, the cure rate remains low for patients with metastatic or undifferentiated thyroid cancer. Moreover, this group of patients exhibits diverse responses to different treatments. To address this, single- cell RNA sequencing (scRNA-seq) offers an unbiased approach to reveal the heterogeneity within and between tumor cells. Using, scRNA-seq, we aimed to explore the intricate ecosystem of thyroid cancer, potentially providing novel insights into clinical cancer staging and treatment strategies. We conducted a thorough analysis by screening thyroid cancer and paraneoplastic tissues from 20 patients sourced from the Gene Expression Omnibus database. The dataset comprised 11 primary tumor tissues, 6 paraneoplastic tissues, 8 metastatic lymph nodes, and 2 distant metastases of papillary thyroid cancer. Through comprehensive bioinformatic analyses, we constructed a panoramic single-cell atlas of thyroid cancer (THCA). Our findings revealed significant heterogeneity in gene expression among tumor cells from different patients with THCA, contributing to the development of a comprehensive single-- cell landscape. Notably, the long noncoding RNA (lncRNA) gene XIST exhibited higher abundance in anaplastic thyroid cancer (ATC) tumor cells. Additionally, we identified an enriched m6A locus in lncRNA XIST and observed high expression of the m6A "reader" IGF2BP3, as well as low expression of the "encoder" VIRMA. Based on these observations, we hypothesized that IGF2BP3 and VIRMA could augment the expression of lncRNA XIST, thereby promoting the malignant proliferation and invasion of ATC. By leveraging scRNA-seq technology, our study sheds light on the intricate molecular characteristics of THCA lesions. These findings have the potential to revolutionize our understanding of thyroid cancer pathogenesis and pave the way for innovative therapeutic interventions.