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Osteosarcoma subtypes based on platelet-related genes and tumor microenvironment characteristics

BACKGROUND: Osteosarcoma is a common metastatic tumor in children and adolescents. Because of its easy metastasis, patients often show a poor prognosis. Recently, researchers have found that platelets are closely related to metastasis of a variety of malignant tumors, but the role of platelets relat...

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Autores principales: Shu, Yuan, Peng, Jie, Feng, Zuxi, Hu, Kaibo, Li, Ting, Zhu, Peijun, Cheng, Tao, Hao, Liang
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9539847/
https://www.ncbi.nlm.nih.gov/pubmed/36212395
http://dx.doi.org/10.3389/fonc.2022.941724
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author Shu, Yuan
Peng, Jie
Feng, Zuxi
Hu, Kaibo
Li, Ting
Zhu, Peijun
Cheng, Tao
Hao, Liang
author_facet Shu, Yuan
Peng, Jie
Feng, Zuxi
Hu, Kaibo
Li, Ting
Zhu, Peijun
Cheng, Tao
Hao, Liang
author_sort Shu, Yuan
collection PubMed
description BACKGROUND: Osteosarcoma is a common metastatic tumor in children and adolescents. Because of its easy metastasis, patients often show a poor prognosis. Recently, researchers have found that platelets are closely related to metastasis of a variety of malignant tumors, but the role of platelets related characteristics in osteosarcoma is still unknown. The purpose of this study is to explore the characteristics of platelet-related subtypes and cell infiltration in tumor microenvironment. METHODS: We collected osteosarcoma cohorts from TCGA and GEO databases, and explored the molecular subtypes mediated by platelet-related genes and the related TME cell infiltration according to the expression of platelet-related genes in osteosarcoma. In addition, we also explored the differentially expressed genes (DEGs) among different molecular subtypes and established a protein-protein interaction network (PPI). Then we constructed a platelet scoring model by Univariate cox regression and least absolute shrinkage and selection operator (Lasso) cox regression model to quantify the characteristics of platelet in a single tumor. RT-PCR was used to investigate the expression of six candidate genes in osteosarcoma cell lines and normal osteoblast lines. Finally, we also predicted potential drugs with therapeutic effects on platelet-related subtypes. RESULTS: We found that platelet-related genes (PRGs) can distinguish osteosarcoma into two different platelet-related subtypes, C1 and C2. And the prognosis of the C2 subtype was significantly worse than that of C1 subtype. The results of ESTIMATE analysis and GO/KEGG enrichment showed that the differences between different subtypes were mainly concentrated in immune response pathways, and the immune response of C2 was inhibited relative to C1. We further studied the relationship between platelet-related subtypes and immune cell infiltration. We found that the distribution of most immune cells in C1 subtype was higher than that in C2 subtype, and there was a correlation between C1 subtype and more immune cells. Finally, we screened the PRGs related to the prognosis of osteosarcoma through Univariate Cox regression, established independent prognostic platelet characteristics consisting of six genes to predict the prognosis of patients with OS, and predicted the drugs that may be used in the treatment of osteosarcoma. RT-PCR was used to verify the expression of candidate genes in osteosarcoma cells. CONCLUSION: Platelet scoring model is a significant biomarker, which is of great significance to determine the prognosis, molecular subtypes, characteristics of TME cell infiltration and therapy in patients with OS.
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spelling pubmed-95398472022-10-08 Osteosarcoma subtypes based on platelet-related genes and tumor microenvironment characteristics Shu, Yuan Peng, Jie Feng, Zuxi Hu, Kaibo Li, Ting Zhu, Peijun Cheng, Tao Hao, Liang Front Oncol Oncology BACKGROUND: Osteosarcoma is a common metastatic tumor in children and adolescents. Because of its easy metastasis, patients often show a poor prognosis. Recently, researchers have found that platelets are closely related to metastasis of a variety of malignant tumors, but the role of platelets related characteristics in osteosarcoma is still unknown. The purpose of this study is to explore the characteristics of platelet-related subtypes and cell infiltration in tumor microenvironment. METHODS: We collected osteosarcoma cohorts from TCGA and GEO databases, and explored the molecular subtypes mediated by platelet-related genes and the related TME cell infiltration according to the expression of platelet-related genes in osteosarcoma. In addition, we also explored the differentially expressed genes (DEGs) among different molecular subtypes and established a protein-protein interaction network (PPI). Then we constructed a platelet scoring model by Univariate cox regression and least absolute shrinkage and selection operator (Lasso) cox regression model to quantify the characteristics of platelet in a single tumor. RT-PCR was used to investigate the expression of six candidate genes in osteosarcoma cell lines and normal osteoblast lines. Finally, we also predicted potential drugs with therapeutic effects on platelet-related subtypes. RESULTS: We found that platelet-related genes (PRGs) can distinguish osteosarcoma into two different platelet-related subtypes, C1 and C2. And the prognosis of the C2 subtype was significantly worse than that of C1 subtype. The results of ESTIMATE analysis and GO/KEGG enrichment showed that the differences between different subtypes were mainly concentrated in immune response pathways, and the immune response of C2 was inhibited relative to C1. We further studied the relationship between platelet-related subtypes and immune cell infiltration. We found that the distribution of most immune cells in C1 subtype was higher than that in C2 subtype, and there was a correlation between C1 subtype and more immune cells. Finally, we screened the PRGs related to the prognosis of osteosarcoma through Univariate Cox regression, established independent prognostic platelet characteristics consisting of six genes to predict the prognosis of patients with OS, and predicted the drugs that may be used in the treatment of osteosarcoma. RT-PCR was used to verify the expression of candidate genes in osteosarcoma cells. CONCLUSION: Platelet scoring model is a significant biomarker, which is of great significance to determine the prognosis, molecular subtypes, characteristics of TME cell infiltration and therapy in patients with OS. Frontiers Media S.A. 2022-09-23 /pmc/articles/PMC9539847/ /pubmed/36212395 http://dx.doi.org/10.3389/fonc.2022.941724 Text en Copyright © 2022 Shu, Peng, Feng, Hu, Li, Zhu, Cheng and Hao 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 Oncology
Shu, Yuan
Peng, Jie
Feng, Zuxi
Hu, Kaibo
Li, Ting
Zhu, Peijun
Cheng, Tao
Hao, Liang
Osteosarcoma subtypes based on platelet-related genes and tumor microenvironment characteristics
title Osteosarcoma subtypes based on platelet-related genes and tumor microenvironment characteristics
title_full Osteosarcoma subtypes based on platelet-related genes and tumor microenvironment characteristics
title_fullStr Osteosarcoma subtypes based on platelet-related genes and tumor microenvironment characteristics
title_full_unstemmed Osteosarcoma subtypes based on platelet-related genes and tumor microenvironment characteristics
title_short Osteosarcoma subtypes based on platelet-related genes and tumor microenvironment characteristics
title_sort osteosarcoma subtypes based on platelet-related genes and tumor microenvironment characteristics
topic Oncology
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9539847/
https://www.ncbi.nlm.nih.gov/pubmed/36212395
http://dx.doi.org/10.3389/fonc.2022.941724
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