A Novel Risk Score Model Based on Eleven Extracellular Matrix-Related Genes for Predicting Overall Survival of Glioma Patients

Xiaodong Li; Yichang Wang; Wei Wu; Jianyang Xiang; Lei Qi; Ning Wang; Maode Wang; Hai Yu

doi:10.1155/2022/4966820

A Novel Risk Score Model Based on Eleven Extracellular Matrix-Related Genes for Predicting Overall Survival of Glioma Patients

J Oncol. 2022 Apr 29:2022:4966820. doi: 10.1155/2022/4966820. eCollection 2022.

Authors

Xiaodong Li^{1

2}, Yichang Wang^{1

2}, Wei Wu^{1

2}, Jianyang Xiang^{1

2}, Lei Qi¹, Ning Wang¹, Maode Wang^{1

2}, Hai Yu^{1

2}

Affiliations

¹ Department of Neurosurgery, The First Affiliated Hospital of Xi'an Jiaotong University, Xi'an, Shaanxi, China.
² Center of Brain Science, The First Affiliated Hospital of Xi'an Jiaotong University, Xi'an, Shaanxi, China.

Abstract

Gliomas are the most common lethal primary brain tumors with variable survival outcomes for patients. The extracellular matrix (ECM) is linked with clinical prognosis of glioma patients, but it is not commonly used as a clinical indicator. Herein, we investigated changes in ECM-related genes (ECMRGs) via analyzing the transcriptional data of 938 gliomas from TCGA and CGGA datasets. Based on least absolute shrinkage and selection operator (LASSO) Cox regression analysis, a 11-ECMRG signature that is strongly linked with overall survival (OS) in glioma patients was identified. This signature was characterized by high-risk and low-risk score patterns. We found that the patients in the high-risk group are significantly linked with malignant molecular features and worse outcomes. Univariate and multivariate Cox regression analyses suggested that the signature is an independent indicator for glioma prognosis. The prediction accuracy of the signature was verified through time-dependent receiver operating characteristic (ROC) curves and calibration plots. Further bioinformatics analyses implied that the ECMRG signature is strongly associated with the activation of multiple oncogenic and metabolic pathways and immunosuppressive tumor microenvironment in gliomas. In addition, we confirmed that the high-risk score is an indicator for a therapy-resistant phenotype. In addition to bioinformatics analyses, we functionally verified the oncogenic role of bone morphogenetic protein 1 (BMP1) in gliomas in vitro.