Literature DB >> 33896271

Study on the Prognostic Values of Dynactin Genes in Low-Grade Glioma.

Xiaotao Su1, Haoyu Li2, Shaohua Chen3, Chao Qin1.   

Abstract

OBJECTIVE: This present study aims to investigate the potential prognostic values of dynactin genes (DCTN) for predicting the overall survival (OS) in low-grade glioma (LGG) patients.
METHODS: The DCTN mRNA expression data were downloaded from The Cancer Genome Atlas database containing 518 patients with LGG. The Gene Ontology and Kyoto Encyclopedia of Genes and Genomes analyses for DCTN genes were performed by using Database for Annotation, Visualization, and Integrated Discovery platform, and their enrichment results were verified by using the Biological Networks Gene Ontology tool. Next, the correlations between DCTN genes and LGG were identified by Pearson correlation coefficient analysis. The OS was estimated by Kaplan-Meier survival analysis. The cBio Cancer Genomics Portal was used to analyze the mutations of DCTN genes and their effects on the prognosis of LGG. The correlation between the abundance of immune infiltration and tumor purity of DCTN genes were predicted by The Tumor Immune Estimation Resource.
RESULTS: Our research showed that the mRNA expression of DCTN4 in tumor tissues was much higher (P < 0.01) than that in normal tissues. Meanwhile, there was a certain correlation between the DCTN genes. Survival analysis showed that the high expression of DCTN1, DCTN3, DCTN4, DCTN6, and their co-expression were significantly correlated with favorable OS in LGG patients (P < 0.05). In DCTN2, a high mutation rate was observed. Further research showed that the genetic alteration in DCTN genes was related to a poor OS and progression-free survival of LGG patients. The expression of DCTN genes had a certain correlation with immune infiltrating cells.
CONCLUSION: Our study showed that the high expressions of DCTN1, DCTN3, DCTN4, and DCTN6 were associated with a favorable OS of LGG patients, indicating that these DCTN genes are potential biomarkers for evaluating the prognosis of LGG patients.

Entities:  

Keywords:  biomarker; dynactin protein; immune infiltration; low-grade glioma; mutation

Year:  2021        PMID: 33896271     DOI: 10.1177/15330338211010143

Source DB:  PubMed          Journal:  Technol Cancer Res Treat        ISSN: 1533-0338


  3 in total

1.  Identification of DNA Repair-Related Genes Predicting Clinical Outcome for Thyroid Cancer.

Authors:  Ai-Ying Zhang; Wei Li; Hai-Yan Zhou; Jing Chen; Li-Bin Zhang
Journal:  J Oncol       Date:  2022-01-06       Impact factor: 4.375

2.  Prediction of Survival Outcome in Lower-Grade Glioma Using a Prognostic Signature with 33 Immune-Related Gene Pairs.

Authors:  Shaohua Chen; Yongchu Sun; Xiaodong Zhu; Zengnan Mo
Journal:  Int J Gen Med       Date:  2021-11-13

3.  Glycosylation-Related Genes Predict the Prognosis and Immune Fraction of Ovarian Cancer Patients Based on Weighted Gene Coexpression Network Analysis (WGCNA) and Machine Learning.

Authors:  Chen Zhao; Kewei Xiong; Fangrui Zhao; Abdalla Adam; Xiangpan Li
Journal:  Oxid Med Cell Longev       Date:  2022-03-04       Impact factor: 6.543

  3 in total

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