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Published on: October 4, 2019
Identification of Dysregulated Competitive Endogenous RNA Networks Driven by Copy Number Variations in Malignant
Jinyuan Xu1, Xiaobo Hou1, Lin Pang1
1College of Bioinformatics Science and Technology, Harbin Medical University, Harbin, China.
Abstract:
Gliomas represent 80% of malignant brain tumors. Because of the high heterogeneity, the oncogenic mechanisms in gliomas are still unclear. In this study, we developed a new approach to identify dysregulated competitive endogenous RNA (ceRNA) interactions driven by copy number variation (CNV) in both lower-grade glioma (LGG) and glioblastoma multiforme (GBM). By analyzing genome and transcriptome data from The Cancer Genome Atlas (TCGA), we first found out the protein coding genes and long non-coding RNAs (lncRNAs) significantly affected by CNVs and further determined CNV-driven dysregulated ceRNA interactions by a customized pipeline. We obtained 13,776 CNV-driven dysregulated ceRNA pairs (including 3,954 mRNAs and 306 lncRNAs) in LGG and 262 pairs (including 221 mRNAs and 11 lncRNAs) in GBM, respectively. Our results showed that most of the ceRNA interactions were weakened by CNVs in both LGG and GBM, and many CNV-driven genes shared the same ceRNAs in the dysregulated ceRNA networks. Functional analysis indicated that the CNV-driven ceRNA network involved in some important mechanisms of tumorigenesis, such as cell cycle, p53 signaling pathway and TGF-beta signaling pathway. Further investigation of the ceRNA pairs in the communities from the dysregulated ceRNA network revealed more detailed biological functions related to the oncogenesis of malignant gliomas. Moreover, by exploring the association of CNV-driven ceRNAs with prognosis and histological subtype, we found that the copy number status of MTAP, KLHL9, and ELAVL2 related to the overall survival in LGG and showed high correlation with histological subtype. In conclusion, this study provided new insight into the molecular mechanisms and clinical biomarkers in gliomas.
Insights
This study reveals copy number variations (CNVs) disrupt competitive endogenous RNA (ceRNA) networks in brain gliomas, impacting tumorigenesis and offering potential biomarkers for prognosis. Understanding these CNV-driven ceRNA interactions provides new insights into glioma development.
Area of Science:
- Oncology
- Genomics
- Molecular Biology
Background:
- Gliomas are the most common malignant brain tumors, characterized by significant heterogeneity.
- The precise oncogenic mechanisms driving glioma development remain largely unclear.
- Competitive endogenous RNA (ceRNA) networks play a role in gene regulation, but their involvement in gliomas, particularly driven by genetic alterations, is not well understood.
Purpose of the Study:
- To develop and apply a novel approach for identifying copy number variation (CNV)-driven dysregulated ceRNA interactions in lower-grade glioma (LGG) and glioblastoma multiforme (GBM).
- To investigate the functional implications and clinical relevance of these CNV-driven ceRNA networks in glioma pathogenesis.
- To identify potential molecular mechanisms and clinical biomarkers associated with glioma progression.
Main Methods:
- Analysis of genome and transcriptome data from The Cancer Genome Atlas (TCGA) for LGG and GBM.
- Identification of protein-coding genes and long non-coding RNAs (lncRNAs) significantly affected by CNVs.
- Application of a customized pipeline to determine CNV-driven dysregulated ceRNA interactions.
- Functional enrichment analysis and investigation of ceRNA network communities.
- Correlation analysis of CNV-driven ceRNAs with patient prognosis and histological subtypes.
Main Results:
- Identification of a substantial number of CNV-driven dysregulated ceRNA pairs in both LGG (13,776 pairs) and GBM (262 pairs).
- Observation that CNVs predominantly weaken ceRNA interactions in both glioma types.
- Functional analysis linked the CNV-driven ceRNA network to key tumorigenic pathways, including cell cycle, p53 signaling, and TGF-beta signaling.
- Discovery that the copy number status of specific genes (MTAP, KLHL9, ELAVL1) is associated with overall survival and histological subtypes in LGG.
Conclusions:
- This study provides novel insights into the molecular mechanisms underlying glioma oncogenesis by elucidating CNV-driven ceRNA network dysregulation.
- The identified CNV-driven ceRNAs and their associated pathways offer a deeper understanding of glioma heterogeneity.
- Specific CNV-associated genes demonstrate potential as clinical biomarkers for glioma prognosis and subtyping.
