使用单细胞RNA测序对肿瘤微环境进行表征已成为肿瘤诊断和治疗的一种有前景的策略。然而，很少有研究集中在通过该技术诊断乳头状甲状腺癌（PTC）。因此，我们的研究探索了肿瘤微环境（TME）特征，并确定了潜在的生物标志物，以建立乳头状甲状腺癌的诊断模型。细胞类型使用CellMarker数据库和已发表的研究的标记物进行鉴定。使用CellChat软件包分析细胞间相互作用。使用SCEVAN软件包鉴定恶性甲状腺细胞。使用SCP软件包进行多个单细胞下游分析，如GSEA分析、富集分析、伪时间轨迹分析和差异表达分析。通过校准曲线、接受者操作特征曲线和决策曲线分析评估了PTC的诊断模型。用RT-qPCR验证了候选基因在人类乳头状甲状腺样本中的表达。通过已发表的细胞标记物，在scRNA-seq数据集中确定了8种细胞类型。PTC组织中存在着FN1/ITGB1等广泛的细胞间相互作用。我们鉴定了与PTC进展相关的26个关键基因。此外，我们鉴定了8个PTC肿瘤细胞亚群，并显示出很高的异质性。MDK/LRP1、MDK/ALK、GAS6/MERTK和GAS6/AXL被鉴定为成纤维细胞/内皮细胞与肿瘤细胞之间相互作用的潜在配体-受体对。最后，由TRPC5、TENM1、NELL2、DMD、SLC35F3和AUTS2构建的诊断模型对区分PTC和正常组织显示出良好的效果。我们的研究对乳头状甲状腺癌中的肿瘤微环境进行了全面的表征。通过与批量RNA测序的联合分析，我们鉴定并验证了6个潜在的诊断生物标志物。我们构建的诊断模型是一种有前景的PTC诊断工具。我们的发现为了解甲状腺癌的异质性和诊断甲状腺癌的理论基础提供了新的见解。© 2023. The Author(s).

Characterizing tumor microenvironment using single-cell RNA sequencing has been a promising strategy for cancer diagnosis and treatment. However, a few studies have focused on diagnosing papillary thyroid cancer (PTC) through this technology. Therefore, our study explored tumor microenvironment (TME) features and identified potential biomarkers to establish a diagnostic model for papillary thyroid cancer.The cell types were identified using the markers from the CellMarker database and published research. The CellChat package was conducted to analyze the cell-cell interaction. The SCEVAN package was used to identify malignant thyroid cells. The SCP package was used to perform multiple single-cell downstream analyses, such as GSEA analysis, enrichment analysis, pseudotime trajectory analysis, and differential expression analysis. The diagnostic model of PTC was estimated using the calibration curves, receiver operating characteristic curves, and decision curve analysis. RT-qPCR was performed to validate the expression of candidate genes in human papillary thyroid samples.Eight cell types were identified in the scRNA-seq dataset by published cell markers. Extensive cell-cell interactions like FN1/ITGB1 existed in PTC tissues. We identified 26 critical genes related to PTC progression. Further, eight subgroups of PTC tumor cells were identified and exhibited high heterogeneity. The MDK/LRP1, MDK/ALK, GAS6/MERTK, and GAS6/AXL were identified as potential ligand-receptor pairs involved in the interactions between fibroblasts/endothelial cells and tumor cells. Eventually, the diagnostic model constructed by TRPC5, TENM1, NELL2, DMD, SLC35F3, and AUTS2 showed a good efficiency for distinguishing the PTC and normal tissues.Our study comprehensively characterized the tumor microenvironment in papillary thyroid cancer. Through combined analysis with bulk RNA-seq, six potential diagnostic biomarkers were identified and validated. The diagnostic model we constructed was a promising tool for PTC diagnosis. Our findings provide new insights into the heterogeneity of thyroid cancer and the theoretical basis for diagnosing thyroid cancer.© 2023. The Author(s).