Cargando…

A glycometabolic gene signature associating with immune infiltration and chemosensitivity and predicting the prognosis of patients with osteosarcoma

BACKGROUND: Accumulating evidence has suggested that glycometabolism plays an important role in the pathogenesis of tumorigenesis. However, few studies have investigated the prognostic values of glycometabolic genes in patients with osteosarcoma (OS). This study aimed to recognize and establish a gl...

Descripción completa

Detalles Bibliográficos
Autores principales: Wang, Fengyan, Yang, Kun, Pan, Runsang, Xiang, Yang, Xiong, Zhilin, Li, Pinhao, Li, Ke, Sun, Hong
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10244582/
https://www.ncbi.nlm.nih.gov/pubmed/37293295
http://dx.doi.org/10.3389/fmed.2023.1115759
_version_ 1785054670731870208
author Wang, Fengyan
Yang, Kun
Pan, Runsang
Xiang, Yang
Xiong, Zhilin
Li, Pinhao
Li, Ke
Sun, Hong
author_facet Wang, Fengyan
Yang, Kun
Pan, Runsang
Xiang, Yang
Xiong, Zhilin
Li, Pinhao
Li, Ke
Sun, Hong
author_sort Wang, Fengyan
collection PubMed
description BACKGROUND: Accumulating evidence has suggested that glycometabolism plays an important role in the pathogenesis of tumorigenesis. However, few studies have investigated the prognostic values of glycometabolic genes in patients with osteosarcoma (OS). This study aimed to recognize and establish a glycometabolic gene signature to forecast the prognosis, and provide therapeutic options for patients with OS. METHODS: Univariate and multivariate Cox regression, LASSO Cox regression, overall survival analysis, receiver operating characteristic curve, and nomogram were adopted to develop the glycometabolic gene signature, and further evaluate the prognostic values of this signature. Functional analyses including Gene Ontology (GO), kyoto encyclopedia of genes and genomes analyses (KEGG), gene set enrichment analysis, single-sample gene set enrichment analysis (ssGSEA), and competing endogenous RNA (ceRNA) network, were used to explore the molecular mechanisms of OS and the correlation between immune infiltration and gene signature. Moreover, these prognostic genes were further validated by immunohistochemical staining. RESULTS: A total of four genes including PRKACB, SEPHS2, GPX7, and PFKFB3 were identified for constructing a glycometabolic gene signature which had a favorable performance in predicting the prognosis of patients with OS. Univariate and multivariate Cox regression analyses revealed that the risk score was an independent prognostic factor. Functional analyses indicated that multiple immune associated biological processes and pathways were enriched in the low-risk group, while 26 immunocytes were down-regulated in the high-risk group. The patients in high-risk group showed elevated sensitivity to doxorubicin. Furthermore, these prognostic genes could directly or indirectly interact with other 50 genes. A ceRNA regulatory network based on these prognostic genes was also constructed. The results of immunohistochemical staining showed that SEPHS2, GPX7, and PFKFB3 were differentially expressed between OS tissues and adjacent normal tissues. CONCLUSION: The preset study constructed and validated a novel glycometabolic gene signature which could predict the prognosis of patients with OS, identify the degree of immune infiltration in tumor microenvironment, and provide guidance for the selection of chemotherapeutic drugs. These findings may shed new light on the investigation of molecular mechanisms and comprehensive treatments for OS.
format Online
Article
Text
id pubmed-10244582
institution National Center for Biotechnology Information
language English
publishDate 2023
publisher Frontiers Media S.A.
record_format MEDLINE/PubMed
spelling pubmed-102445822023-06-08 A glycometabolic gene signature associating with immune infiltration and chemosensitivity and predicting the prognosis of patients with osteosarcoma Wang, Fengyan Yang, Kun Pan, Runsang Xiang, Yang Xiong, Zhilin Li, Pinhao Li, Ke Sun, Hong Front Med (Lausanne) Medicine BACKGROUND: Accumulating evidence has suggested that glycometabolism plays an important role in the pathogenesis of tumorigenesis. However, few studies have investigated the prognostic values of glycometabolic genes in patients with osteosarcoma (OS). This study aimed to recognize and establish a glycometabolic gene signature to forecast the prognosis, and provide therapeutic options for patients with OS. METHODS: Univariate and multivariate Cox regression, LASSO Cox regression, overall survival analysis, receiver operating characteristic curve, and nomogram were adopted to develop the glycometabolic gene signature, and further evaluate the prognostic values of this signature. Functional analyses including Gene Ontology (GO), kyoto encyclopedia of genes and genomes analyses (KEGG), gene set enrichment analysis, single-sample gene set enrichment analysis (ssGSEA), and competing endogenous RNA (ceRNA) network, were used to explore the molecular mechanisms of OS and the correlation between immune infiltration and gene signature. Moreover, these prognostic genes were further validated by immunohistochemical staining. RESULTS: A total of four genes including PRKACB, SEPHS2, GPX7, and PFKFB3 were identified for constructing a glycometabolic gene signature which had a favorable performance in predicting the prognosis of patients with OS. Univariate and multivariate Cox regression analyses revealed that the risk score was an independent prognostic factor. Functional analyses indicated that multiple immune associated biological processes and pathways were enriched in the low-risk group, while 26 immunocytes were down-regulated in the high-risk group. The patients in high-risk group showed elevated sensitivity to doxorubicin. Furthermore, these prognostic genes could directly or indirectly interact with other 50 genes. A ceRNA regulatory network based on these prognostic genes was also constructed. The results of immunohistochemical staining showed that SEPHS2, GPX7, and PFKFB3 were differentially expressed between OS tissues and adjacent normal tissues. CONCLUSION: The preset study constructed and validated a novel glycometabolic gene signature which could predict the prognosis of patients with OS, identify the degree of immune infiltration in tumor microenvironment, and provide guidance for the selection of chemotherapeutic drugs. These findings may shed new light on the investigation of molecular mechanisms and comprehensive treatments for OS. Frontiers Media S.A. 2023-05-24 /pmc/articles/PMC10244582/ /pubmed/37293295 http://dx.doi.org/10.3389/fmed.2023.1115759 Text en Copyright © 2023 Wang, Yang, Pan, Xiang, Xiong, Li, Li and Sun. 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 Medicine
Wang, Fengyan
Yang, Kun
Pan, Runsang
Xiang, Yang
Xiong, Zhilin
Li, Pinhao
Li, Ke
Sun, Hong
A glycometabolic gene signature associating with immune infiltration and chemosensitivity and predicting the prognosis of patients with osteosarcoma
title A glycometabolic gene signature associating with immune infiltration and chemosensitivity and predicting the prognosis of patients with osteosarcoma
title_full A glycometabolic gene signature associating with immune infiltration and chemosensitivity and predicting the prognosis of patients with osteosarcoma
title_fullStr A glycometabolic gene signature associating with immune infiltration and chemosensitivity and predicting the prognosis of patients with osteosarcoma
title_full_unstemmed A glycometabolic gene signature associating with immune infiltration and chemosensitivity and predicting the prognosis of patients with osteosarcoma
title_short A glycometabolic gene signature associating with immune infiltration and chemosensitivity and predicting the prognosis of patients with osteosarcoma
title_sort glycometabolic gene signature associating with immune infiltration and chemosensitivity and predicting the prognosis of patients with osteosarcoma
topic Medicine
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10244582/
https://www.ncbi.nlm.nih.gov/pubmed/37293295
http://dx.doi.org/10.3389/fmed.2023.1115759
work_keys_str_mv AT wangfengyan aglycometabolicgenesignatureassociatingwithimmuneinfiltrationandchemosensitivityandpredictingtheprognosisofpatientswithosteosarcoma
AT yangkun aglycometabolicgenesignatureassociatingwithimmuneinfiltrationandchemosensitivityandpredictingtheprognosisofpatientswithosteosarcoma
AT panrunsang aglycometabolicgenesignatureassociatingwithimmuneinfiltrationandchemosensitivityandpredictingtheprognosisofpatientswithosteosarcoma
AT xiangyang aglycometabolicgenesignatureassociatingwithimmuneinfiltrationandchemosensitivityandpredictingtheprognosisofpatientswithosteosarcoma
AT xiongzhilin aglycometabolicgenesignatureassociatingwithimmuneinfiltrationandchemosensitivityandpredictingtheprognosisofpatientswithosteosarcoma
AT lipinhao aglycometabolicgenesignatureassociatingwithimmuneinfiltrationandchemosensitivityandpredictingtheprognosisofpatientswithosteosarcoma
AT like aglycometabolicgenesignatureassociatingwithimmuneinfiltrationandchemosensitivityandpredictingtheprognosisofpatientswithosteosarcoma
AT sunhong aglycometabolicgenesignatureassociatingwithimmuneinfiltrationandchemosensitivityandpredictingtheprognosisofpatientswithosteosarcoma
AT wangfengyan glycometabolicgenesignatureassociatingwithimmuneinfiltrationandchemosensitivityandpredictingtheprognosisofpatientswithosteosarcoma
AT yangkun glycometabolicgenesignatureassociatingwithimmuneinfiltrationandchemosensitivityandpredictingtheprognosisofpatientswithosteosarcoma
AT panrunsang glycometabolicgenesignatureassociatingwithimmuneinfiltrationandchemosensitivityandpredictingtheprognosisofpatientswithosteosarcoma
AT xiangyang glycometabolicgenesignatureassociatingwithimmuneinfiltrationandchemosensitivityandpredictingtheprognosisofpatientswithosteosarcoma
AT xiongzhilin glycometabolicgenesignatureassociatingwithimmuneinfiltrationandchemosensitivityandpredictingtheprognosisofpatientswithosteosarcoma
AT lipinhao glycometabolicgenesignatureassociatingwithimmuneinfiltrationandchemosensitivityandpredictingtheprognosisofpatientswithosteosarcoma
AT like glycometabolicgenesignatureassociatingwithimmuneinfiltrationandchemosensitivityandpredictingtheprognosisofpatientswithosteosarcoma
AT sunhong glycometabolicgenesignatureassociatingwithimmuneinfiltrationandchemosensitivityandpredictingtheprognosisofpatientswithosteosarcoma