Abstract
Background: Glioblastoma Multiforme (GBM) is a common malignant neuroepithelial tumor originating from central nervous system and the prognosis is worse. This study aimed to identify potential cuprotosis-related lncRNAs and explore significance of prognostic prediction in GBM. Methods: RNA-seq and related clinical data of GBM were retrieved from TCGA. Univariate, multivariate, lasso and Cox regression analysis were used to screen the cuprotosis-related lncRNA associated with prognosis and established the corresponding risk model. Receiver operating curve (ROC) was used to assess the predictive power of the model. Results: 159 cases (including RNA-seq and related clinical information) were divided into training group (112) and verification group (47). Six prognostic cuprotosis-related lncRNAs (LINC02328, AC005229.4, CYTOR, AC019254.1, DLEU1, GNG12-AS1) were screened. The high-risk group had a poorer prognosis compared with the low-risk group. Kaplan-Meier curves showed that the risk model was a good prognostic indicator (Pā<ā0.001). The ROC analysis showed that the validity of the risk model was good. KEGG and GO enrichment analyses were performed on cuprotosis-related genes. Tumor mutation burden analysis was performed, and the mutation rates of TP53, PTEN, and EGFR were among the top three, and tumor mutation burden was associated with prognosis and survival. Cytolytic activity, T-cell co-stimulation, etc. found among high- and low-risk groups. Cuprotosis-related lncRNAs and genes were explored which can help predict prognosis and explore new therapeutic targets. Conclusion: The expression characteristics of cuprotosis-related lncRNAs in GBM were explored from the TCGA and cuprotosis-related genes, and a prognostic model was constructed to help improve the treatment prognosis of GBM patients and explore new therapeutic targets.
H. Sun, X. Li, J. YangāContributed to the work equally.
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Funding
This study was supported by the Fund for Shanxi ā1331 Projectā (2021-5-2-2-1); the Natural Science Foundation for Youths of Shanxi Province, China (20210302124301); the Provincial Science and Technology Grant of Shanxi Province (20210302124588).
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Sun, H., Li, X., Yang, J., Lyu, Y., Han, P., Zheng, J. (2022). A Novel Cuprotosis-Related lncRNA Signature Predicts Survival Outcomes in Patients with Glioblastoma. In: Huang, DS., Jo, KH., Jing, J., Premaratne, P., Bevilacqua, V., Hussain, A. (eds) Intelligent Computing Theories and Application. ICIC 2022. Lecture Notes in Computer Science, vol 13394. Springer, Cham. https://doi.org/10.1007/978-3-031-13829-4_48
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