1. miRNA-targets cross-talks: key players in glioblastoma multiforme
Eman A Toraih1, Nagwa Mahmoud Ali2, Hoda Y Abdallah1, Saeed Awad M Al-Qahtani3, Aly A.M. Shaalan4,5, Mohammad H Hussein6, Manal Said Fawzy2
1 Genetics Unit, Histology and Cell Biology Department, Faculty of Medicine, Suez Canal University, (FOMSCU), Egypt , 2 Department of Medical Biochemistry, FOMSCU, Egypt, 3 Department of Physiology, FOM, Jazan University, Saudi Arabia, 4 Department of Histology and Cell Biology, FOMSCU, Ismailia, Egypt, 5 Department of Anatomy and Histology, FOM, Jazan University, Saudi Arabia, 6 Pulmonologist, Ministry of Health, Cairo, Egypt
ABSTRACT
INTRODUCTION
RESULTS
RESULTS
Background: The role of microRNAs in brain cancer is still naive. Some act as oncogene and others as tumor suppressors. Discovery of efficient biomarkers is mandatory to debate that aggressive disease.
Objective: Determine expression profile of bioinformatically-selected microRNAs and their targets.
Methodology: Three panels of microRNA, genes, and proteins were assessed in 43 glioblastoma and 10 normal brain samples by immunohistochemistry and qRT-PCR. MGMT promotor methylation and Epidermal growth factor receptor (EGFR) expression were used for molecular subtyping of tumor specimens.
Results: Our data demonstrated up- regulation of 5 microRNAs (hsa-miR- 16, hsa-miR-17, hsa-miR-21, hsa- miR-221, and hsa-miR-375), 3 genes (E2F3, PI3KCA, and Wnt5a), and 3 proteins (VEGFA, BAX, and BCL-2) and down-regulation of hsa-miR-34a and 3 other genes (DFFA, PDCD4, and EGFR) in brain cancer tissues. Moreover, VEGFA over-expression and down-regulation of TOM34 and BAX were associated with poor overall survival. Multivariate analysis by hierarchical clustering classified patients into 4 distinct groups based on gene panel signature.
Conclusion: microRNA and targets expression signature could pave the road towards developing personalized therapeutic strategies.
Glioblastoma multiforme (GBM, WHO grade IV) is the most common and most aggressive brain tumors, characterized by invasion, metastasis, and angiogenesis.
MicroRNAs act as maestros, fine-tuning hundreds of targets and display diverse functions across different cellular contexts.
Bioinformatically-selected microRNAs and their targets were selected to investigate their putative role as diagnostic and prognostic biomarkers in primary GBM.
Significant up-regulation of 5 microRNAs (miR- 16, miR-17, miR-21, miR-221, and miR-375), 3 genes (E2F3, PI3KCA, and Wnt5a), 2 proteins (VEGFA and BCL-2), and down-regulation of miR-34a and 3 other genes (DFFA, PDCD4, and EGFR) in brain cancer tissues.
METHODOLOGY
Bioinformatic-selection of panels .
Exploring miRNA-target interactions and pathway enrichment analysis
Molecular subtyping by MGMT promotor methylation
Expression profiling
Expression of panels of 7 microRNAs, 7 target genes, and 3 proteins in 43 GBM specimens were profiled compared to non-cancer tissues via qRT-PCR and IHC.
Fig. 3. Association with prognostic characteristics.
Fig. 1. Expression levels of miRNAs and gene panels.
Stepwise linear regression analysis: TOM34 and VEGFA levels were independent predictors for poor overall survival in GBM disease.
Hierarchical clustering classified GBM patients according to their expression profile, Fig. 5. Group 1 (green clade) attained lower expression levels for most genes and miRNAs; in contrast, Group 2 (red clade) almost all genes and miRNAs were over-expressed, in Group 3 (orange), miR-34a, miR-326, PDCD4, and DFFA were down-regulated, whereas Group 4 (blue) patients showed similar pattern to group 3 except for the consistent up-regulated miR-326 levels.
ROC analysis revealed miR-34a and miR-17 had the highest diagnostic performance, followed by miR-221, miR-21, Wnt5a, PDCD4, and PI3KCA.
Table 1. Predictive performance of miRNA and gene panels for discriminating cancer and non-cancer tissues.
Fig. 4. Kaplan-Meier analyses in GBM.
Fig. 5. Hierarchical clustering according to expression signature.
CONCLUSION
MicroRNAs expression deregulation and the miRNA–mRNA network could play an integral process in GBM. This greatly could be helpful in miRNAs-based molecular classification of GBM that aid in diagnosis and prognosis prediction as well as targeted molecular therapy.
CONTACT
Eman Ali Toraih
Phone:
Fig. 2. Immunohistochemistry analysis of proteins.