| Literature DB >> 33713320 |
Aierpati Maimaiti1, Xixian Wang1, Yujun Hao1, Lei Jiang1, Xin Shi1, Yinan Pei1, Zhaohai Feng1, Maimaitijiang Kasimu2.
Abstract
Glioma is one of the most common neurological malignancies worldwide. Delta-like ligand 3 (DLL3), an inhibitory ligand-driven activation of the Notch pathway, has been shown to be significantly associated with overall survival in patients with glioma. Therefore, the purpose of this study was to determine whether DLL3 as a biomarker in glioma is associated with patients' clinicopathological features and prognosis. We identified differences in transcriptome and promoter methylation in the Chinese Glioma Genome Atlas (CGGA) in patients with malignant glioma with shorter (less than 1 year) and longer (greater than 3 years) survival time. Further analysis of The Cancer Genome Atlas (TCGA) revealed that four genes (DLL3, TSPAN15, RTN1, PAK7) are highly associated with patient prognosis and play an indispensable role in evolution. We chose the expression level of DLL3 in glioma patients for our study. Patients were divided into groups with low and high expression of DLL3 according to the cutoff values obtained, and Kaplan-Meier and Cox analysis were used to examine the correlation between DLL3 gene expression and patient survival. We then performed a gene set enrichment analysis (GSEA) to identify significantly enriched signaling pathways. Our results confirmed that the overall survival of patients with low DLL3 expression was significantly shorter than that of patients with high DLL3 expression. GSEA showed that the signaling pathways of the immune process and immune response, among others, were enhanced with the DLL3 low-expression phenotype. Collectively, our findings signify that DLL3 is a potent prognostic factor for glioma, which can provide a viable approach for glioma prognostic assessment and valuable insights for anti-tumor immune-targeted therapies.Entities:
Keywords: Chinese Glioma Genome Atlas (CGGA); DLL3; Differentially expressed genes (DEGs); Glioma; OS
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Year: 2021 PMID: 33713320 DOI: 10.1007/s12031-021-01817-7
Source DB: PubMed Journal: J Mol Neurosci ISSN: 0895-8696 Impact factor: 3.444