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Integrated analysis of fibroblasts molecular features in papillary thyroid cancer combining single-cell and bulk RNA sequencing technology
BACKGROUND: Papillary thyroid cancer (PTC) is the most common pathological type of thyroid cancer with a high incidence globally. Increasing evidence reported that fibroblasts infiltration in cancer was correlated with prognostic outcomes. However, fibroblasts related study in thyroid cancer remains...
Autores principales: | , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Frontiers Media S.A.
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9643292/ https://www.ncbi.nlm.nih.gov/pubmed/36387901 http://dx.doi.org/10.3389/fendo.2022.1019072 |
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author | Li, Wei Liu, Zhiyong Cen, Xiaoxia Xu, Jing Zhao, Suo Wang, Bin Zhang, Wei Qiu, Ming |
author_facet | Li, Wei Liu, Zhiyong Cen, Xiaoxia Xu, Jing Zhao, Suo Wang, Bin Zhang, Wei Qiu, Ming |
author_sort | Li, Wei |
collection | PubMed |
description | BACKGROUND: Papillary thyroid cancer (PTC) is the most common pathological type of thyroid cancer with a high incidence globally. Increasing evidence reported that fibroblasts infiltration in cancer was correlated with prognostic outcomes. However, fibroblasts related study in thyroid cancer remains deficient. METHODS: Single-cell sequencing data of PTC were analyzed by Seurat R package to explore the ecosystem in PTC and identify fibroblasts cluster. The expression profiles and prognostic values of fibroblast related genes were assessed in TCGA dataset. A fibrosis score model was established for prognosis prediction in thyroid cancer patients. Differentially expressed genes and functional enrichment between high and low fibrosis score groups in TCGA dataset were screened. The correlation of immune cells infiltration and fibrosis score in thyroid cancer patients was explored. Expression levels and prognostic values of key fibroblast related factor were validated in clinical tissues another PTC cohort. RESULTS: Fibroblasts were highly infiltrated in PTC and could interact with other type of cells by single-cell data analysis. 34 fibroblast related terms were differentially expressed in thyroid tumor tissues. COX regression analysis suggested that the constructed fibrosis score model was an independent prognostic predictor for thyroid cancer patients (HR = 5.17, 95%CI 2.31-11.56, P = 6.36E-05). Patients with low fibrosis scores were associated with a significantly better overall survival (OS) than those with high fibrosis scores in TCGA dataset (P = 7.659E-04). Specific immune cells infiltration levels were positively correlated with fibrosis score, including monocytes, M1 macrophages and eosinophils. CONCLUSION: Our research demonstrated a comprehensive horizon of fibroblasts features in thyroid cancer microenvironment, which may provide potential value for thyroid cancer treatment. |
format | Online Article Text |
id | pubmed-9643292 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Frontiers Media S.A. |
record_format | MEDLINE/PubMed |
spelling | pubmed-96432922022-11-15 Integrated analysis of fibroblasts molecular features in papillary thyroid cancer combining single-cell and bulk RNA sequencing technology Li, Wei Liu, Zhiyong Cen, Xiaoxia Xu, Jing Zhao, Suo Wang, Bin Zhang, Wei Qiu, Ming Front Endocrinol (Lausanne) Endocrinology BACKGROUND: Papillary thyroid cancer (PTC) is the most common pathological type of thyroid cancer with a high incidence globally. Increasing evidence reported that fibroblasts infiltration in cancer was correlated with prognostic outcomes. However, fibroblasts related study in thyroid cancer remains deficient. METHODS: Single-cell sequencing data of PTC were analyzed by Seurat R package to explore the ecosystem in PTC and identify fibroblasts cluster. The expression profiles and prognostic values of fibroblast related genes were assessed in TCGA dataset. A fibrosis score model was established for prognosis prediction in thyroid cancer patients. Differentially expressed genes and functional enrichment between high and low fibrosis score groups in TCGA dataset were screened. The correlation of immune cells infiltration and fibrosis score in thyroid cancer patients was explored. Expression levels and prognostic values of key fibroblast related factor were validated in clinical tissues another PTC cohort. RESULTS: Fibroblasts were highly infiltrated in PTC and could interact with other type of cells by single-cell data analysis. 34 fibroblast related terms were differentially expressed in thyroid tumor tissues. COX regression analysis suggested that the constructed fibrosis score model was an independent prognostic predictor for thyroid cancer patients (HR = 5.17, 95%CI 2.31-11.56, P = 6.36E-05). Patients with low fibrosis scores were associated with a significantly better overall survival (OS) than those with high fibrosis scores in TCGA dataset (P = 7.659E-04). Specific immune cells infiltration levels were positively correlated with fibrosis score, including monocytes, M1 macrophages and eosinophils. CONCLUSION: Our research demonstrated a comprehensive horizon of fibroblasts features in thyroid cancer microenvironment, which may provide potential value for thyroid cancer treatment. Frontiers Media S.A. 2022-10-26 /pmc/articles/PMC9643292/ /pubmed/36387901 http://dx.doi.org/10.3389/fendo.2022.1019072 Text en Copyright © 2022 Li, Liu, Cen, Xu, Zhao, Wang, Zhang and Qiu https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms. |
spellingShingle | Endocrinology Li, Wei Liu, Zhiyong Cen, Xiaoxia Xu, Jing Zhao, Suo Wang, Bin Zhang, Wei Qiu, Ming Integrated analysis of fibroblasts molecular features in papillary thyroid cancer combining single-cell and bulk RNA sequencing technology |
title | Integrated analysis of fibroblasts molecular features in papillary thyroid cancer combining single-cell and bulk RNA sequencing technology |
title_full | Integrated analysis of fibroblasts molecular features in papillary thyroid cancer combining single-cell and bulk RNA sequencing technology |
title_fullStr | Integrated analysis of fibroblasts molecular features in papillary thyroid cancer combining single-cell and bulk RNA sequencing technology |
title_full_unstemmed | Integrated analysis of fibroblasts molecular features in papillary thyroid cancer combining single-cell and bulk RNA sequencing technology |
title_short | Integrated analysis of fibroblasts molecular features in papillary thyroid cancer combining single-cell and bulk RNA sequencing technology |
title_sort | integrated analysis of fibroblasts molecular features in papillary thyroid cancer combining single-cell and bulk rna sequencing technology |
topic | Endocrinology |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9643292/ https://www.ncbi.nlm.nih.gov/pubmed/36387901 http://dx.doi.org/10.3389/fendo.2022.1019072 |
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