|Table of Contents|

The prognostic model of TGF-β pathway related genes in ependymoma constructed by bioinformatics

Journal Of Modern Oncology[ISSN:1672-4992/CN:61-1415/R]

Issue:
2024 06
Page:
1032-1037
Research Field:
Publishing date:

Info

Title:
The prognostic model of TGF-β pathway related genes in ependymoma constructed by bioinformatics
Author(s):
FAN Yandong1; ZHU Manli2; DENG Guoqi1; WANG Jiaming3; LUO Kun1
1.Neurosurgery Department，the Second Affiliated Hospital of Xinjiang Medical University，Xinjiang Urumqi 830054，China;2.Central Laboratory，Xinjiang Medical University，Xinjiang Urumqi 830054，China;3.Neurosurgery Department，the First Affiliated Hospital of Xinjiang Medical University,Xinjiang Urumqi 830054，China.
Keywords:
TGF-β signaling pathway; ependymoma; bioinformatics; prediction model
PACS:
R739.4
DOI:
10.3969/j.issn.1672-4992.2024.06.008
Abstract:
Objective:To establish a prognostic model of TGF-β signaling pathway related genes in ependymoma based on bioinformatics.Methods:Unsupervised clustering algorithm was used to distinguish the different molecular subtypes of ependymoma.Gene set variation analysis (GSVA) was used to calculate TGF-β signal pathway-related scores in different ependymoma subtypes.The survival rates of patients with different ependymoma subtypes were calculated by Kaplan-Meier analysis (KM).Linear models for microarray data (limma) were used to analyze the differential genes among different ependymoma subtypes.Least absolute shrinkage and selection operator (LASSO) and COX proportional hazards model were used to construct a prognostic model of TGF-β signaling pathway related genes in ependymoma.Receiver operating characteristic curve (ROC) was used to evaluate the performance of prognostic prediction model.Pearson correlation analysis was used to investigate the correlation of important genes.qRT-PCR and Western blot were used to investigate the expression of important genes in ependymoma tissues.Results:The unsupervised clustering algorithm showed that there were two different subtypes in ependymoma.GSVA and KM analysis showed that TGF-β signaling pathway scores and prognosis were significantly different in different subtypes of ependymomas.The results of gene differential expression analysis showed that TGF-β pathway related gene expression was significantly different in different subtypes of ependymomas.LASSO showed that BMP4,FBN1,CDC20 and TGFB1 were the important genes of prognosis prediction model.ROC analysis results showed that TGF-β signaling pathway related gene model had high predictive performance.The results of Pearson correlation analysis showed that BMP4,FBN1,CDC20,TGFB1 were significantly correlated with the downstream genes of TGF-β signaling pathway.qRT-PCR and western blot showed that the expressions of BMP4,FBN1,CDC20 and TGFB1 were significantly up-regulated in ependymal tissues.Conclusion:The prognosis prediction model based on TGF-β pathway related genes BMP4,FBN1,CDC20 and TGFB1 can effectively predict the survival of patients with ependymoma.

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省部共建中亚高发病成因与防治国家重点实验室开放课题项目（编号：SKL-HIDCA-2022-NKX2）
Last Update: 1900-01-01