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Profiles of immune cell infiltration and immune-related genes in the tumor microenvironment of osteosarcoma cancer

BACKGROUNDS: Osteosarcomas are one of the most common primary malignant tumors of bone. It primarily occurs in children and adolescents, with the second highest incidence among people over 50 years old. Although there were immense improvements in the survival of patients with osteosarcoma in the pas...

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Autores principales: Liu, Ruixuan, Hu, Yuhang, Liu, Tianyi, Wang, Yansong
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8684084/
https://www.ncbi.nlm.nih.gov/pubmed/34922489
http://dx.doi.org/10.1186/s12885-021-09042-6
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author Liu, Ruixuan
Hu, Yuhang
Liu, Tianyi
Wang, Yansong
author_facet Liu, Ruixuan
Hu, Yuhang
Liu, Tianyi
Wang, Yansong
author_sort Liu, Ruixuan
collection PubMed
description BACKGROUNDS: Osteosarcomas are one of the most common primary malignant tumors of bone. It primarily occurs in children and adolescents, with the second highest incidence among people over 50 years old. Although there were immense improvements in the survival of patients with osteosarcoma in the past 30 years, targetable mutations and agents of osteosarcomas still have been generally not satisfactory. Therefore, it is of great importance to further explore the highly specialized immune environment of bone, genes related to macrophage infiltration and potential therapeutic biomarkers and targets. METHODS: The 11 expression data sets of OS tissues and the 11 data sets of adjacent non-tumorous tissues available in the GEO database GSE126209 were used to conduct immune infiltration analysis. Then, through WGCNA analysis, we acquired the co-expression modules related to Mast cells activated and performed the GO and KEGG enrichment analysis. Next, we did the survival prognosis analysis and plotted a survival curve. Finally, we analyzed the COX multivariate regression of gene expression on clinical parameters and drew forest maps for visualization by the forest plot package. RESULTS: OS disease-related immune cell populations, mainly Mast cells activated, have higher cell content (p = 0.006) than the normal group. Then, we identified co-expression modules related to Mast cells activated. In sum, a total of 822 genes from the top three strongest positive correlation module MEbrown4, MEdarkslateblue and MEnavajowhite2 and the strongest negative correlation module MEdarkturquoise. From that, we identified nine genes with different levels in immune cell infiltration related to osteosarcoma, eight of which including SORBS2, BAIAP2L2, ATAD2, CYGB, PAMR1, PSIP1, SNAPC3 and ZDHHC21 in their low abundance have higher disease-free survival probability than the group in their high abundances. CONCLUSION: These results could assist clinicians to select targets for immunotherapies and individualize treatment strategies for patients with OS. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12885-021-09042-6.
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spelling pubmed-86840842021-12-20 Profiles of immune cell infiltration and immune-related genes in the tumor microenvironment of osteosarcoma cancer Liu, Ruixuan Hu, Yuhang Liu, Tianyi Wang, Yansong BMC Cancer Reserarch BACKGROUNDS: Osteosarcomas are one of the most common primary malignant tumors of bone. It primarily occurs in children and adolescents, with the second highest incidence among people over 50 years old. Although there were immense improvements in the survival of patients with osteosarcoma in the past 30 years, targetable mutations and agents of osteosarcomas still have been generally not satisfactory. Therefore, it is of great importance to further explore the highly specialized immune environment of bone, genes related to macrophage infiltration and potential therapeutic biomarkers and targets. METHODS: The 11 expression data sets of OS tissues and the 11 data sets of adjacent non-tumorous tissues available in the GEO database GSE126209 were used to conduct immune infiltration analysis. Then, through WGCNA analysis, we acquired the co-expression modules related to Mast cells activated and performed the GO and KEGG enrichment analysis. Next, we did the survival prognosis analysis and plotted a survival curve. Finally, we analyzed the COX multivariate regression of gene expression on clinical parameters and drew forest maps for visualization by the forest plot package. RESULTS: OS disease-related immune cell populations, mainly Mast cells activated, have higher cell content (p = 0.006) than the normal group. Then, we identified co-expression modules related to Mast cells activated. In sum, a total of 822 genes from the top three strongest positive correlation module MEbrown4, MEdarkslateblue and MEnavajowhite2 and the strongest negative correlation module MEdarkturquoise. From that, we identified nine genes with different levels in immune cell infiltration related to osteosarcoma, eight of which including SORBS2, BAIAP2L2, ATAD2, CYGB, PAMR1, PSIP1, SNAPC3 and ZDHHC21 in their low abundance have higher disease-free survival probability than the group in their high abundances. CONCLUSION: These results could assist clinicians to select targets for immunotherapies and individualize treatment strategies for patients with OS. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12885-021-09042-6. BioMed Central 2021-12-18 /pmc/articles/PMC8684084/ /pubmed/34922489 http://dx.doi.org/10.1186/s12885-021-09042-6 Text en © The Author(s) 2021 https://creativecommons.org/licenses/by/4.0/Open AccessThis 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/) . The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/ (https://creativecommons.org/publicdomain/zero/1.0/) ) applies to the data made available in this article, unless otherwise stated in a credit line to the data.
spellingShingle Reserarch
Liu, Ruixuan
Hu, Yuhang
Liu, Tianyi
Wang, Yansong
Profiles of immune cell infiltration and immune-related genes in the tumor microenvironment of osteosarcoma cancer
title Profiles of immune cell infiltration and immune-related genes in the tumor microenvironment of osteosarcoma cancer
title_full Profiles of immune cell infiltration and immune-related genes in the tumor microenvironment of osteosarcoma cancer
title_fullStr Profiles of immune cell infiltration and immune-related genes in the tumor microenvironment of osteosarcoma cancer
title_full_unstemmed Profiles of immune cell infiltration and immune-related genes in the tumor microenvironment of osteosarcoma cancer
title_short Profiles of immune cell infiltration and immune-related genes in the tumor microenvironment of osteosarcoma cancer
title_sort profiles of immune cell infiltration and immune-related genes in the tumor microenvironment of osteosarcoma cancer
topic Reserarch
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8684084/
https://www.ncbi.nlm.nih.gov/pubmed/34922489
http://dx.doi.org/10.1186/s12885-021-09042-6
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