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Integrated analysis of tumor microenvironment features to establish a diagnostic model for papillary thyroid cancer using bulk and single-cell RNA sequencing technology by Yizeng Wang; Wenbin Song; Yingxi Li; Zhaoyi Liu; Ke Zhao; Lanning Jia; Xiaoning Wang; Ruoyu Jiang; Yao Tian; Xianghui He is a Medicine article available to read on EtoBox.
What is Integrated analysis of tumor microenvironment features to establish a diagnostic model for papillary thyroid cancer using bulk and single-cell RNA sequencing technology about?
## Background 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. ## Methods 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. ## Results Eight cell types were identified in the scRNA-seq dataset by published cell
Who reads Integrated analysis of tumor microenvironment features to establish a diagnostic model for papillary thyroid cancer using bulk and single-cell RNA sequencing technology?
It is typically read by researchers, students, and practitioners in Medicine.
- Author
- Yizeng Wang; Wenbin Song; Yingxi Li; Zhaoyi Liu; Ke Zhao; Lanning Jia; Xiaoning Wang; Ruoyu Jiang; Yao Tian; Xianghui He
- Publisher
- Springer Science and Business Media LLC
- Published
- 2023
- Language
- EN
- Field
- Medicine (Health Sciences)