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Prognostic and immunological significance of an M1 macrophage-related gene signature in osteosarcoma

As the most abundant infiltrating immune cells in the tumor microenvironment (TME), tumor-associated macrophages (TAMs) are pivotal in tumor development and treatment. The present investigation endeavors to explore the potential of M1 macrophage-related genes (MRGs) as biomarkers for assessing risk...

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Autores principales: Mao, Xiaoyu, Song, Fanglong, Jin, Ju, Zou, Bin, Dai, Peijun, Sun, Mingjuan, Xu, Weicheng, Wang, Lianghua, Kang, Yifan
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10350629/
https://www.ncbi.nlm.nih.gov/pubmed/37465666
http://dx.doi.org/10.3389/fimmu.2023.1202725
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author Mao, Xiaoyu
Song, Fanglong
Jin, Ju
Zou, Bin
Dai, Peijun
Sun, Mingjuan
Xu, Weicheng
Wang, Lianghua
Kang, Yifan
author_facet Mao, Xiaoyu
Song, Fanglong
Jin, Ju
Zou, Bin
Dai, Peijun
Sun, Mingjuan
Xu, Weicheng
Wang, Lianghua
Kang, Yifan
author_sort Mao, Xiaoyu
collection PubMed
description As the most abundant infiltrating immune cells in the tumor microenvironment (TME), tumor-associated macrophages (TAMs) are pivotal in tumor development and treatment. The present investigation endeavors to explore the potential of M1 macrophage-related genes (MRGs) as biomarkers for assessing risk in individuals with osteosarcoma. RNA-sequence data and clinical data were derived from TCGA and GEO databases. The CIBERSORT method was utilized to discern subtypes of tumor-infiltrating immune cells. Identification of MRGs was achieved through Pearson correlation analysis. A prognostic risk model for MRGs was developed using Cox and LASSO regression analyses. A tripartite gene signature comprising CD37, GABRD, and ARHGAP25 was an independent prognostic indicator and was employed to develop a risk score model. The internal and external validation cohort confirmed the results. The area under the ROC curve (AUC) was determined for survival periods of 1 year, three years, and five years, yielding values of 0.746, 0.839, and 0.850, respectively. The C-index of the risk score was found to be superior to clinicopathological factors. GO/KEGG enrichment showed that the differences between high- and low-risk groups were predominantly associated with immune response pathways. Immune-related analysis related to proportions of immune cells, immune function, and expression levels of immune checkpoint genes all showed differences between the high- and low-risk groups. The qRT-PCR and Western blotting results indicate that CD37 expression was markedly higher in MG63 and U2OS cell lines when compared to normal osteoblast hFOB1.19. In U2OS cell line, GABRD expression levels were significantly upregulated. ARHGAP25 expression levels were elevated in both 143B and U2OS cell lines. In summary, utilizing a macrophage genes signature demonstrates efficacy in predicting both the prognosis and therapy response of OS. Additionally, immune analysis confirms a correlation between the risk score and the tumor microenvironment. Our findings, therefore, provide a cogent account for the disparate prognoses observed among patients and furnish a justification for further inquiry into biomarkers and anti-tumor treatment strategies.
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spelling pubmed-103506292023-07-18 Prognostic and immunological significance of an M1 macrophage-related gene signature in osteosarcoma Mao, Xiaoyu Song, Fanglong Jin, Ju Zou, Bin Dai, Peijun Sun, Mingjuan Xu, Weicheng Wang, Lianghua Kang, Yifan Front Immunol Immunology As the most abundant infiltrating immune cells in the tumor microenvironment (TME), tumor-associated macrophages (TAMs) are pivotal in tumor development and treatment. The present investigation endeavors to explore the potential of M1 macrophage-related genes (MRGs) as biomarkers for assessing risk in individuals with osteosarcoma. RNA-sequence data and clinical data were derived from TCGA and GEO databases. The CIBERSORT method was utilized to discern subtypes of tumor-infiltrating immune cells. Identification of MRGs was achieved through Pearson correlation analysis. A prognostic risk model for MRGs was developed using Cox and LASSO regression analyses. A tripartite gene signature comprising CD37, GABRD, and ARHGAP25 was an independent prognostic indicator and was employed to develop a risk score model. The internal and external validation cohort confirmed the results. The area under the ROC curve (AUC) was determined for survival periods of 1 year, three years, and five years, yielding values of 0.746, 0.839, and 0.850, respectively. The C-index of the risk score was found to be superior to clinicopathological factors. GO/KEGG enrichment showed that the differences between high- and low-risk groups were predominantly associated with immune response pathways. Immune-related analysis related to proportions of immune cells, immune function, and expression levels of immune checkpoint genes all showed differences between the high- and low-risk groups. The qRT-PCR and Western blotting results indicate that CD37 expression was markedly higher in MG63 and U2OS cell lines when compared to normal osteoblast hFOB1.19. In U2OS cell line, GABRD expression levels were significantly upregulated. ARHGAP25 expression levels were elevated in both 143B and U2OS cell lines. In summary, utilizing a macrophage genes signature demonstrates efficacy in predicting both the prognosis and therapy response of OS. Additionally, immune analysis confirms a correlation between the risk score and the tumor microenvironment. Our findings, therefore, provide a cogent account for the disparate prognoses observed among patients and furnish a justification for further inquiry into biomarkers and anti-tumor treatment strategies. Frontiers Media S.A. 2023-07-03 /pmc/articles/PMC10350629/ /pubmed/37465666 http://dx.doi.org/10.3389/fimmu.2023.1202725 Text en Copyright © 2023 Mao, Song, Jin, Zou, Dai, Sun, Xu, Wang and Kang 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 Immunology
Mao, Xiaoyu
Song, Fanglong
Jin, Ju
Zou, Bin
Dai, Peijun
Sun, Mingjuan
Xu, Weicheng
Wang, Lianghua
Kang, Yifan
Prognostic and immunological significance of an M1 macrophage-related gene signature in osteosarcoma
title Prognostic and immunological significance of an M1 macrophage-related gene signature in osteosarcoma
title_full Prognostic and immunological significance of an M1 macrophage-related gene signature in osteosarcoma
title_fullStr Prognostic and immunological significance of an M1 macrophage-related gene signature in osteosarcoma
title_full_unstemmed Prognostic and immunological significance of an M1 macrophage-related gene signature in osteosarcoma
title_short Prognostic and immunological significance of an M1 macrophage-related gene signature in osteosarcoma
title_sort prognostic and immunological significance of an m1 macrophage-related gene signature in osteosarcoma
topic Immunology
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10350629/
https://www.ncbi.nlm.nih.gov/pubmed/37465666
http://dx.doi.org/10.3389/fimmu.2023.1202725
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