Abstract
PurposeGlioblastoma (GBM) is one of the most aggressive brain tumors with high mortality, and tumor-derived exosomes provide new insight into the mechanisms of GBM tumorigenesis, metastasis and therapeutic resistance. We aimed to establish an exosome-derived competitive endogenous RNA (ceRNA) network for constructing a prognostic model for GBM.MethodsWe obtained the expression profiles of long noncoding RNAs (lncRNAs), miRNAs, and mRNAs from the GEO and TCGA databases and identified differentially expressed RNAs in GBM to construct a ceRNA network. By performing lasso and multivariate Cox regression analyses, we identified optimal prognosis-related differentially expressed lncRNAs (DElncRNAs) and generated a risk score model termed the exosomal lncRNA (exo-lncRNA) signature. The exo-lncRNA signature was subsequently validated in the CGGA GBM cohort. Finally, a novel prognostic nomogram was constructed based on the exo-lncRNA signature and clinicopathological parameters and validated in the CGGA external cohort. Based on the ceRNA hypothesis, oncocers were identified based on highly positive correlations between lncRNAs and mRNAs mediated by the same miRNAs. Furthermore, regression analyses were performed to assess correlations between the expression abundances of lncRNAs in tumors and exosomes.ResultsA total of 45 DElncRNAs, six DEmiRNAs, and 38 DEmRNAs were identified, and an exosome-derived ceRNA network was built. Three optimal prognostic-related DElncRNAs, HOTAIR (HR=0.341, P<0.001), SOX21-AS1 (HR=0.30, P<0.001), and STEAP3-AS1 (HR=2.47, P<0.001), were included to construct the exo-lncRNA signature, which was further proven to be an independent prognostic factor. The novel prognostic nomogram was constructed based on the exo-lncRNA signature, patient age, pharmacotherapy, radiotherapy, IDH mutation status, and MGMT promoter status, with a concordance index of 0.878. ROC and calibration plots both suggested that the nomogram had beneficial discrimination and predictive abilities. A total of 11 pairs of prognostic oncocers were identified. Regression analysis suggested excellent consistency of the expression abundance of the three exosomal lncRNAs between exosomes and tumor tissues.ConclusionsExosomal lncRNAs may serve as promising prognostic predictors and therapeutic targets. The prognostic nomogram based on the exo-lncRNA signature might provide an intuitive method for individualized survival prediction and facilitate better treatment strategies.
Highlights
Glioma is one of the most aggressive brain tumors, and it has received considerable attention due to its relatively high incidence, poor prognosis and significant impact on quality of life
Considerable studies have confirmed the role of the long noncoding RNAs (lncRNAs)-miRNA-messenger RNAs (mRNAs) regulation network, and based on the competitive endogenous RNA (ceRNA) hypothesis, oncocers that play crucial roles in oncogenic pathways have been identified in various cancers, such as lung cancer, prostate cancer, and liver cancer [12,13,14,15]. These results suggest the significance of the ceRNA network in the comprehensive analysis of gene interactions and the identification of potential biomarkers for tumor diagnosis, therapy, and prognosis
We aimed to investigate and validate an exosome-derived multiple gene expression signature based on a ceRNA network that can predict prognosis and provide potential targets for GBM treatment
Summary
Glioma is one of the most aggressive brain tumors, and it has received considerable attention due to its relatively high incidence, poor prognosis and significant impact on quality of life. An increasing number of molecularly targeted therapies have emerged but have not achieved satisfactory outcomes due to the complex pathogenesis and molecular heterogeneity of GBM. It is recognized that exosomes can regulate the bioactivity of the recipient cell by transferring molecular and genetic cargo, including proteins, lipids, and small RNAs [3]. Recent studies have highlighted the role of exosomes in tumors, including tumor progression, metastasis, establishment of the tumor microenvironment, and drug resistance [5,6,7]. The importance of exosomes and their cargo (especially small RNAs) for GBM has gradually been realized, as is the case for microRNAs (miRNAs) in regulating angiogenesis and tumor metastasis [8] and messenger RNAs (mRNAs) in mediating cell migration and drug resistance [9, 10]. Integration analysis of the exosome expression profile in GBM has not been fully elucidated
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