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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 dysfunctional miRNA-mRNA regulatory modules by inverse activation, cofunction, and high interconnection
Yun Xiao1, Yanyan Ping, Huihui Fan
1College of Bioinformatics Science and Technology, Harbin Medical University, Harbin 150081, China.
Background:
Accumulating evidence demonstrates that complex diseases may arise from cooperative effects of multiple dysfunctional miRNAs. Thus, identifying abnormal functions cooperatively regulated by multiple miRNAs is useful for understanding the pathogenesis of complex diseases.
Methods:
In this study, we proposed a multistep method to identify dysfunctional miRNA-mRNA regulatory modules (dMiMRMs) in a specific disease, in which a group of miRNAs cooperatively regulate a group of target genes involved in a specific function. We identified dysfunctional miRNAs, which were differentially expressed and inversely regulated most of their target genes, by integrating paired miRNA and mRNA expression profiles and miRNA target information. Then, we identified cooperative functional units, in each of which a pair of miRNAs cooperatively repressed function-enriched and highly interconnected target genes. Finally, the cooperative functional units were assembled into dMiMRMs.
Results:
We applied our method to glioblastoma (GBM) and identified GBM-associated dMiMRMs at the population, subtype, and individual levels. We identified 5 common dMiMRMs using all GBM samples, 3 of which were associated with the prognosis in patients with GBM and were better predictors of prognosis than were miRNAs or mRNAs alone. By applying our approach to GBM subtypes, we found consistent dMiMRMs across GBM subtypes, and some subtype-specific dMiMRMs were observed. Furthermore, personalized dMiMRMs were identified, suggesting significant individual differences in different patients with GBM.
Conclusions:
Our method provides the capability to identify miRNA-mediated dysfunctional mechanisms underlying complex diseases.
Insights
Identifying dysfunctional miRNA-mRNA regulatory modules (dMiMRMs) helps understand complex diseases. This new method reveals disease mechanisms and predicts glioblastoma prognosis using miRNA and mRNA data.
Area of Science:
- Molecular Biology
- Genomics
- Computational Biology
Background:
- Complex diseases involve multiple microRNAs (miRNAs) acting cooperatively.
- Understanding these cooperative miRNA functions is key to disease pathogenesis.
Purpose of the Study:
- To develop a method for identifying dysfunctional miRNA-mRNA regulatory modules (dMiMRMs) in diseases.
- To apply this method to glioblastoma (GBM) for understanding disease mechanisms.
Main Methods:
- Integrated miRNA and mRNA expression profiles with miRNA target information.
- Identified dysfunctional miRNAs and cooperative functional units.
- Assembled these units into dMiMRMs.
Main Results:
- Identified GBM-associated dMiMRMs at population, subtype, and individual levels.
- Found 3 common dMiMRMs that predicted GBM prognosis better than individual miRNAs or mRNAs.
- Observed consistent and subtype-specific dMiMRMs, highlighting individual patient differences.
Conclusions:
- The developed method effectively identifies miRNA-mediated dysfunctional mechanisms in complex diseases.
- This approach offers insights into disease pathogenesis and personalized treatment strategies.
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