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Characterization of Functionally Associated miRNAs in Glioblastoma and their Engineering into Artificial Clusters for Gene Therapy
Published on: October 4, 2019
Identifying survival-associated modules from the dysregulated triplet network in glioblastoma multiforme
Jia-Bin Wang1, Feng-Hua Liu2, Jian-Hang Chen1
1Department of Neurosurgery, The First Affiliated Hospital of Harbin Medical University, Harbin, 150001, People's Republic of China.
Background:
Long noncoding RNAs (lncRNAs) can act as competitive endogenous RNAs (ceRNAs) to compete with mRNAs for binding miroRNAs (miRNAs). The dysregulated triplets, composed by mRNAs, lncRNAs, and miRNAs, contributed to the development and progression of diseases, such as cancer. However, the roles played by triplet biomarkers are not fully understand in glioblastoma multiforme (GBM) patient survival.
Objectives:
Here, we constructed a differential triplet interaction network (TriNet) between GBM and normal tissues and identified GBM survival related triplets.
Methods:
Four significantly dysregulated modules, enriched differentially expressed molecules, were identified by integrating affinity propagation method and hypergeometric method. Furthermore, knockdown of TP73-AS1 was implemented by siRNA and the expression of RFX1 was examined in U87 cells by qRT-PCR. The apoptosis of U87 cells was investigated using MTT assay and Acridine orange/Ethidium bromide (AO/EB) assay.
Results:
We randomly split GBM samples into training and testing sets, and found that these four modules can robustly and significantly distinguish low- and high-survival patients in both two sets. By manually curated literatures for triplets mediated by core interactions, we found that members involved tumor invasion, proliferation, and migration. The dysregulated triplets may cause the poor survival of GBM patients. We finally experimentally verified that knockdown of TP73-AS1, an lncRNA of one triplet, could not only reduce the expression of RFX1, an mRNA of this triplet, but also induce apoptosis in U87 cells.
Conclusions:
These results can provide further insights to understand the functions of triplet biomarkers that associated with GBM prognosis.
Insights
This study identifies key molecular triplets (lncRNA-miRNA-mRNA interactions) that predict glioblastoma multiforme (GBM) patient survival. Knocking down a specific long noncoding RNA (TP73-AS1) reduced tumor cell growth and increased apoptosis.
Area of Science:
- Molecular biology
- Genomics
- Cancer research
Background:
- Long noncoding RNAs (lncRNAs) function as competing endogenous RNAs (ceRNAs), interacting with microRNAs (miRNAs) and messenger RNAs (mRNAs).
- Dysregulated lncRNA-miRNA-mRNA interactions, termed triplets, are implicated in cancer development and progression.
- The prognostic significance of these triplet biomarkers in glioblastoma multiforme (GBM) remains incompletely understood.
Purpose of the Study:
- To construct a differential triplet interaction network (TriNet) comparing GBM and normal tissues.
- To identify GBM survival-related triplets and investigate their functional roles.
Main Methods:
- Integrated affinity propagation and hypergeometric methods to identify four significantly dysregulated modules.
- Randomly split GBM samples into training and testing sets for validation.
- Experimentally validated the role of TP73-AS1 and RFX1 in U87 GBM cells using siRNA, qRT-PCR, MTT, and AO/EB assays.
Main Results:
- Four identified modules robustly distinguished between low- and high-survival GBM patients in both training and testing sets.
- Core interactions within triplets were linked to tumor invasion, proliferation, and migration.
- Knockdown of lncRNA TP73-AS1 reduced mRNA RFX1 expression and induced apoptosis in U87 cells.
Conclusions:
- The identified triplet biomarkers offer insights into GBM patient prognosis.
- Understanding these triplet interactions can advance therapeutic strategies for glioblastoma.
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