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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

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 microenvi...

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Autores principales: Wang, Yizeng, Song, Wenbin, Li, Yingxi, Liu, Zhaoyi, Zhao, Ke, Jia, Lanning, Wang, Xiaoning, Jiang, Ruoyu, Tian, Yao, He, Xianghui
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer Berlin Heidelberg 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10645658/
https://www.ncbi.nlm.nih.gov/pubmed/37733241
http://dx.doi.org/10.1007/s00432-023-05420-8
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author Wang, Yizeng
Song, Wenbin
Li, Yingxi
Liu, Zhaoyi
Zhao, Ke
Jia, Lanning
Wang, Xiaoning
Jiang, Ruoyu
Tian, Yao
He, Xianghui
author_facet Wang, Yizeng
Song, Wenbin
Li, Yingxi
Liu, Zhaoyi
Zhao, Ke
Jia, Lanning
Wang, Xiaoning
Jiang, Ruoyu
Tian, Yao
He, Xianghui
author_sort Wang, Yizeng
collection PubMed
description 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 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. CONCLUSIONS: 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. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1007/s00432-023-05420-8.
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spelling pubmed-106456582023-11-14 Integrated analysis of tumor microenvironment features to establish a diagnostic model for papillary thyroid cancer using bulk and single-cell RNA sequencing technology Wang, Yizeng Song, Wenbin Li, Yingxi Liu, Zhaoyi Zhao, Ke Jia, Lanning Wang, Xiaoning Jiang, Ruoyu Tian, Yao He, Xianghui J Cancer Res Clin Oncol Research 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 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. CONCLUSIONS: 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. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1007/s00432-023-05420-8. Springer Berlin Heidelberg 2023-09-21 2023 /pmc/articles/PMC10645658/ /pubmed/37733241 http://dx.doi.org/10.1007/s00432-023-05420-8 Text en © The Author(s) 2023 https://creativecommons.org/licenses/by/4.0/Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) .
spellingShingle Research
Wang, Yizeng
Song, Wenbin
Li, Yingxi
Liu, Zhaoyi
Zhao, Ke
Jia, Lanning
Wang, Xiaoning
Jiang, Ruoyu
Tian, Yao
He, Xianghui
Integrated analysis of tumor microenvironment features to establish a diagnostic model for papillary thyroid cancer using bulk and single-cell RNA sequencing technology
title Integrated analysis of tumor microenvironment features to establish a diagnostic model for papillary thyroid cancer using bulk and single-cell RNA sequencing technology
title_full Integrated analysis of tumor microenvironment features to establish a diagnostic model for papillary thyroid cancer using bulk and single-cell RNA sequencing technology
title_fullStr Integrated analysis of tumor microenvironment features to establish a diagnostic model for papillary thyroid cancer using bulk and single-cell RNA sequencing technology
title_full_unstemmed Integrated analysis of tumor microenvironment features to establish a diagnostic model for papillary thyroid cancer using bulk and single-cell RNA sequencing technology
title_short Integrated analysis of tumor microenvironment features to establish a diagnostic model for papillary thyroid cancer using bulk and single-cell RNA sequencing technology
title_sort integrated analysis of tumor microenvironment features to establish a diagnostic model for papillary thyroid cancer using bulk and single-cell rna sequencing technology
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10645658/
https://www.ncbi.nlm.nih.gov/pubmed/37733241
http://dx.doi.org/10.1007/s00432-023-05420-8
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