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TREM2 as a Prognostic Biomarker for Osteosarcoma Microenvironment Remodeling
The tumor microenvironment (TME) acts as a crucial role in the occurrence and development of osteosarcoma (OS). Despite this, the mechanism controlling the components of immunity and stroma in the tumor microenvironment remains a mystery. To conduct this study, we download and collate transcriptome...
Autores principales: | , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Hindawi
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9957636/ https://www.ncbi.nlm.nih.gov/pubmed/36844870 http://dx.doi.org/10.1155/2023/3677789 |
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author | Shen, Zhi-Long Chen, Zhao-Yu Ji, Yong Jiang, Hao Zhu, Zhi-Peng Yuan, Hao Li, Bo Xu, Wei Xiao, Jianru |
author_facet | Shen, Zhi-Long Chen, Zhao-Yu Ji, Yong Jiang, Hao Zhu, Zhi-Peng Yuan, Hao Li, Bo Xu, Wei Xiao, Jianru |
author_sort | Shen, Zhi-Long |
collection | PubMed |
description | The tumor microenvironment (TME) acts as a crucial role in the occurrence and development of osteosarcoma (OS). Despite this, the mechanism controlling the components of immunity and stroma in the tumor microenvironment remains a mystery. To conduct this study, we download and collate transcriptome data from the TARGET database, whose full name is Therapeutically Applicable Research to Generate Effective Treatments, as well as available clinical information of OS. The CIBERSORT and ESTIMATE methodology are used to acquire the proportions of components of immunity and stroma and tumor-infiltrating immune cells (TICs). Protein-protein interaction (PPI) networks and Cox regression analysis are used to select differentially expressed genes (DEGs). A prognostic biomarker is determined by intersecting univariate COX and PPI results, which lead to the finding of Triggering receptor expressed on myeloid cells-2 (TREM2). Based on the next analysis, TREM2 expression is positively correlated with OS survival time. Immune function-related genes have enrichment in the group with high expression of TREM2, according to gene set enrichment analysis (GSEA). The percentage of TICs by CIBERSORT methodology revealed that the expression of TREM2 is positively associated with follicular helper T cells, CD8-positive T cells, and M2 macrophages and negatively correlated with plasma cells, M0 macrophages, and naive CD4-positive T cells. All results suggest a possible integral role of TREM2 in the immune-related events of TME. Therefore, TREM2 may be a potential indicator of remodeling of TME in osteosarcoma, which is useful and helpful in predicting the clinical prognostic outcome of OS patients and provide a unique perspective for immunotherapy for OS. |
format | Online Article Text |
id | pubmed-9957636 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | Hindawi |
record_format | MEDLINE/PubMed |
spelling | pubmed-99576362023-02-25 TREM2 as a Prognostic Biomarker for Osteosarcoma Microenvironment Remodeling Shen, Zhi-Long Chen, Zhao-Yu Ji, Yong Jiang, Hao Zhu, Zhi-Peng Yuan, Hao Li, Bo Xu, Wei Xiao, Jianru J Oncol Research Article The tumor microenvironment (TME) acts as a crucial role in the occurrence and development of osteosarcoma (OS). Despite this, the mechanism controlling the components of immunity and stroma in the tumor microenvironment remains a mystery. To conduct this study, we download and collate transcriptome data from the TARGET database, whose full name is Therapeutically Applicable Research to Generate Effective Treatments, as well as available clinical information of OS. The CIBERSORT and ESTIMATE methodology are used to acquire the proportions of components of immunity and stroma and tumor-infiltrating immune cells (TICs). Protein-protein interaction (PPI) networks and Cox regression analysis are used to select differentially expressed genes (DEGs). A prognostic biomarker is determined by intersecting univariate COX and PPI results, which lead to the finding of Triggering receptor expressed on myeloid cells-2 (TREM2). Based on the next analysis, TREM2 expression is positively correlated with OS survival time. Immune function-related genes have enrichment in the group with high expression of TREM2, according to gene set enrichment analysis (GSEA). The percentage of TICs by CIBERSORT methodology revealed that the expression of TREM2 is positively associated with follicular helper T cells, CD8-positive T cells, and M2 macrophages and negatively correlated with plasma cells, M0 macrophages, and naive CD4-positive T cells. All results suggest a possible integral role of TREM2 in the immune-related events of TME. Therefore, TREM2 may be a potential indicator of remodeling of TME in osteosarcoma, which is useful and helpful in predicting the clinical prognostic outcome of OS patients and provide a unique perspective for immunotherapy for OS. Hindawi 2023-02-17 /pmc/articles/PMC9957636/ /pubmed/36844870 http://dx.doi.org/10.1155/2023/3677789 Text en Copyright © 2023 Zhi-Long Shen et al. https://creativecommons.org/licenses/by/4.0/This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Research Article Shen, Zhi-Long Chen, Zhao-Yu Ji, Yong Jiang, Hao Zhu, Zhi-Peng Yuan, Hao Li, Bo Xu, Wei Xiao, Jianru TREM2 as a Prognostic Biomarker for Osteosarcoma Microenvironment Remodeling |
title | TREM2 as a Prognostic Biomarker for Osteosarcoma Microenvironment Remodeling |
title_full | TREM2 as a Prognostic Biomarker for Osteosarcoma Microenvironment Remodeling |
title_fullStr | TREM2 as a Prognostic Biomarker for Osteosarcoma Microenvironment Remodeling |
title_full_unstemmed | TREM2 as a Prognostic Biomarker for Osteosarcoma Microenvironment Remodeling |
title_short | TREM2 as a Prognostic Biomarker for Osteosarcoma Microenvironment Remodeling |
title_sort | trem2 as a prognostic biomarker for osteosarcoma microenvironment remodeling |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9957636/ https://www.ncbi.nlm.nih.gov/pubmed/36844870 http://dx.doi.org/10.1155/2023/3677789 |
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