Construction of a Single-cell Atlas of Thyroid Cancer.

Kaiyu Song, Yaqi Wang, Yuantao Wang, Jiahui Liu, Wenjie Yao, Yongli Chu, Yun Qu, Xicheng Song, Jin Zhou
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Abstract

Introduction: 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.

Methods: 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).

Results: 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.

Conclusion: 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.

甲状腺癌单细胞图谱的构建。
分化型甲状腺癌一般预后良好;然而,对于转移性或未分化的甲状腺癌患者,治愈率仍然很低。此外,这组患者对不同的治疗表现出不同的反应。为了解决这个问题,单细胞RNA测序(scRNA-seq)提供了一种公正的方法来揭示肿瘤细胞内和肿瘤细胞之间的异质性。使用scRNA-seq,我们旨在探索甲状腺癌复杂的生态系统,可能为临床癌症分期和治疗策略提供新的见解。方法:我们从基因表达综合数据库中筛选20例甲状腺癌和副肿瘤组织进行全面分析。该数据集包括11例原发性肿瘤组织、6例副肿瘤组织、8例转移性淋巴结和2例甲状腺乳头状癌的远处转移。通过全面的生物信息学分析,我们构建了甲状腺癌(THCA)的全景单细胞图谱。结果:我们的研究结果揭示了不同THCA患者肿瘤细胞中基因表达的显著异质性,有助于全面的单细胞景观的发展。值得注意的是,长链非编码RNA (lncRNA)基因XIST在间变性甲状腺癌(ATC)肿瘤细胞中表现出更高的丰度。此外,我们在lncRNA XIST中发现了一个富集的m6A位点,并观察到m6A“读取器”IGF2BP3的高表达,而“编码器”VIRMA的低表达。基于这些观察,我们假设IGF2BP3和VIRMA可以增强lncRNA XIST的表达,从而促进ATC的恶性增殖和侵袭。结论:利用scRNA-seq技术,我们的研究揭示了THCA病变复杂的分子特征。这些发现有可能彻底改变我们对甲状腺癌发病机制的理解,并为创新的治疗干预铺平道路。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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