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Characterization of osteosarcoma subtypes mediated by macrophage-related genes and creation and validation of a risk score system to quantitatively assess the prognosis of osteosarcoma and reflect the tumor microenvironment

BACKGROUND: Macrophages are the main immune components in the microenvironment of osteosarcoma. The treatment strategy centered on macrophages has become a hot topic to improve cancer treatment. However, the research on the role of macrophages in the treatment of osteosarcoma is still in its infancy...

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Autores principales: Liu, Zhe, Zhang, Lei, Zhong, Yun
Formato: Online Artículo Texto
Lenguaje:English
Publicado: AME Publishing Company 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9843337/
https://www.ncbi.nlm.nih.gov/pubmed/36660647
http://dx.doi.org/10.21037/atm-22-5613
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author Liu, Zhe
Zhang, Lei
Zhong, Yun
author_facet Liu, Zhe
Zhang, Lei
Zhong, Yun
author_sort Liu, Zhe
collection PubMed
description BACKGROUND: Macrophages are the main immune components in the microenvironment of osteosarcoma. The treatment strategy centered on macrophages has become a hot topic to improve cancer treatment. However, the research on the role of macrophages in the treatment of osteosarcoma is still in its infancy. METHODS: The data of osteosarcoma samples were downloaded from the Therapeutically Applicable Research to Generate Effective Treatments (TARGET) and GSE21257 datasets, and the macrophage enrichment fraction of osteosarcoma samples in TARGET was calculated by single-sample gene set enrichment analysis (ssGSEA) method to screen macrophage-related genes for consensus clustering. Differential expression analysis, univariable Cox, and least absolute shrinkage and selection operator (LASSO) regression were conducted to select reliable predictors and create a risk score system. The GSE21257 dataset was used as a verification set to verify the accuracy of risk score system. RESULTS: We identified 2 osteosarcoma clusters mediated by 22 macrophage score-related genes, namely cluster 1 (C1) and cluster 2 (C2). Compared with C2, C1 had a significant advantage in prognosis, and the degree of immune cell infiltration in tumor microenvironment (TME) was significantly higher, the expression of immune checkpoint molecules was significantly enhanced, and the Tumor Immune Dysfunction and Exclusion (TIDE) score was also significantly down-regulated. A robust risk score system was presented and validated, which demonstrated accuracy and independence in assessing the risk of death of osteosarcoma. The risk score system could also monitor TME infiltration in osteosarcoma samples and showed a close relationship with osteosarcoma biology, including metastasis and immunity. CONCLUSIONS: We identified 2 types of clusters mediated by macrophage-related genes and helped to analyze the cluster suitable for immunotherapy. A new prognostic risk score system was created to quantitatively evaluate the prognosis and TME of osteosarcoma, and to provide a new entry point for the design of personalized treatment.
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spelling pubmed-98433372023-01-18 Characterization of osteosarcoma subtypes mediated by macrophage-related genes and creation and validation of a risk score system to quantitatively assess the prognosis of osteosarcoma and reflect the tumor microenvironment Liu, Zhe Zhang, Lei Zhong, Yun Ann Transl Med Original Article BACKGROUND: Macrophages are the main immune components in the microenvironment of osteosarcoma. The treatment strategy centered on macrophages has become a hot topic to improve cancer treatment. However, the research on the role of macrophages in the treatment of osteosarcoma is still in its infancy. METHODS: The data of osteosarcoma samples were downloaded from the Therapeutically Applicable Research to Generate Effective Treatments (TARGET) and GSE21257 datasets, and the macrophage enrichment fraction of osteosarcoma samples in TARGET was calculated by single-sample gene set enrichment analysis (ssGSEA) method to screen macrophage-related genes for consensus clustering. Differential expression analysis, univariable Cox, and least absolute shrinkage and selection operator (LASSO) regression were conducted to select reliable predictors and create a risk score system. The GSE21257 dataset was used as a verification set to verify the accuracy of risk score system. RESULTS: We identified 2 osteosarcoma clusters mediated by 22 macrophage score-related genes, namely cluster 1 (C1) and cluster 2 (C2). Compared with C2, C1 had a significant advantage in prognosis, and the degree of immune cell infiltration in tumor microenvironment (TME) was significantly higher, the expression of immune checkpoint molecules was significantly enhanced, and the Tumor Immune Dysfunction and Exclusion (TIDE) score was also significantly down-regulated. A robust risk score system was presented and validated, which demonstrated accuracy and independence in assessing the risk of death of osteosarcoma. The risk score system could also monitor TME infiltration in osteosarcoma samples and showed a close relationship with osteosarcoma biology, including metastasis and immunity. CONCLUSIONS: We identified 2 types of clusters mediated by macrophage-related genes and helped to analyze the cluster suitable for immunotherapy. A new prognostic risk score system was created to quantitatively evaluate the prognosis and TME of osteosarcoma, and to provide a new entry point for the design of personalized treatment. AME Publishing Company 2022-12 /pmc/articles/PMC9843337/ /pubmed/36660647 http://dx.doi.org/10.21037/atm-22-5613 Text en 2022 Annals of Translational Medicine. All rights reserved. https://creativecommons.org/licenses/by-nc-nd/4.0/Open Access Statement: This is an Open Access article distributed in accordance with the Creative Commons Attribution-NonCommercial-NoDerivs 4.0 International License (CC BY-NC-ND 4.0), which permits the non-commercial replication and distribution of the article with the strict proviso that no changes or edits are made and the original work is properly cited (including links to both the formal publication through the relevant DOI and the license). See: https://creativecommons.org/licenses/by-nc-nd/4.0 (https://creativecommons.org/licenses/by-nc-nd/4.0/) .
spellingShingle Original Article
Liu, Zhe
Zhang, Lei
Zhong, Yun
Characterization of osteosarcoma subtypes mediated by macrophage-related genes and creation and validation of a risk score system to quantitatively assess the prognosis of osteosarcoma and reflect the tumor microenvironment
title Characterization of osteosarcoma subtypes mediated by macrophage-related genes and creation and validation of a risk score system to quantitatively assess the prognosis of osteosarcoma and reflect the tumor microenvironment
title_full Characterization of osteosarcoma subtypes mediated by macrophage-related genes and creation and validation of a risk score system to quantitatively assess the prognosis of osteosarcoma and reflect the tumor microenvironment
title_fullStr Characterization of osteosarcoma subtypes mediated by macrophage-related genes and creation and validation of a risk score system to quantitatively assess the prognosis of osteosarcoma and reflect the tumor microenvironment
title_full_unstemmed Characterization of osteosarcoma subtypes mediated by macrophage-related genes and creation and validation of a risk score system to quantitatively assess the prognosis of osteosarcoma and reflect the tumor microenvironment
title_short Characterization of osteosarcoma subtypes mediated by macrophage-related genes and creation and validation of a risk score system to quantitatively assess the prognosis of osteosarcoma and reflect the tumor microenvironment
title_sort characterization of osteosarcoma subtypes mediated by macrophage-related genes and creation and validation of a risk score system to quantitatively assess the prognosis of osteosarcoma and reflect the tumor microenvironment
topic Original Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9843337/
https://www.ncbi.nlm.nih.gov/pubmed/36660647
http://dx.doi.org/10.21037/atm-22-5613
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