转录组
甲状腺癌
计算生物学
癌症
生物
甲状腺
医学
遗传学
基因
基因表达
作者
Tian Liao,Yu Zeng,Weibo Xu,Xiao Shi,Cenkai Shen,Yuxin Du,Meng Zhang,Yan Zhang,Ling Li,Peipei Ding,Weiguo Hu,Zhiheng Huang,Matrix Man Him Fung,Qinghai Ji,Yu Wang,Shengli Li,Wenjun Wei
标识
DOI:10.1016/j.xcrm.2025.102043
摘要
Tumor microenvironment (TME) remodeling plays a pivotal role in thyroid cancer progression, yet its spatial dynamics remain unclear. In this study, we integrate spatial transcriptomics and single-cell RNA sequencing to map the TME architecture across para-tumor thyroid (PT) tissue, papillary thyroid cancer (PTC), locally advanced PTC (LPTC), and anaplastic thyroid carcinoma (ATC). Our integrative analysis reveals extensive molecular and cellular heterogeneity during thyroid cancer progression, enabling the identification of three distinct thyrocyte meta-clusters, including TG+IYG+ subpopulation in PT, HLA-DRB1+HLA-DRA+ subpopulation in early cancerous stages, and APOE+APOC1+ subpopulation in late-stage progression. We reveal stage-specific tumor leading edge remodeling and establish high-confidence cell-cell interactions, such as COL8A1-ITHB1 in PTC, LAMB2-ITGB4 in LPTC, and SERPINE1-PLAUR in ATC. Notably, both SERPINE1 expression level and SERPINE1+ fibroblast abundance correlate with malignant progression and prognosis. These findings provide a spatially resolved framework of TME remodeling, offering insights for thyroid cancer diagnosis and treatment.
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