Hsa_circITGA4/ miR-1468/EGFR/ PTEN a Master Regulators Axis in Glioblastoma Development and Progression.
Sara TutunchiAhmad BereimipourSayyed Mohammad Hossein GhaderianPublished in: Molecular biotechnology (2023)
In the fight against glioblastoma, circular RNA is emerging as a functional molecule. However, how circular RNA (circRNA) is regulated and what role it plays is still a mystery. In this research, different bioinformatics approaches were used to evaluate glioblastoma circRNA sequencing and array data, with the goal of developing a putative molecular sponge mechanism control network. The circRNAs were obtained from the Gene Expression Omnibus datasets. MicroRNA-circRNA interactions were predicted using CircInteractome. The microRNAs' expression and survival trends were screened using the TCGA database. MicroRNA gene targets were predicted using the MiRnet database. Sponge network gene candidates were screened using data from the GEPIA. The roles of the targeted genes were to be explained by analyzing data from Gene Ontology and the Kyoto Encyclopedia of Genes and Genomes. To build the network and display the outcomes, we utilized python program, and enrichment online Bioinformatics databases. The circRNAs hsa_circITGA4_002, hsa_circITGA4_001, hsa_circITGA4_003, hsa_circ_0030855, hsa_circ_0030857 were chosen from among GBM patients and control group. Upregulation of hsa-miR-1468, hsa-miR-3683, hsa-miR-1273c, and hsa-miR-4665-3p were associated with a poor prognosis in GBM. MicroRNA targets such as ITGA4, LAMA2, EGFR, PTEN, COL1A4, and NCAM2 were analyzed using expression and survival data. The Apoptosis, cell adhesion molecules, PI3K/AKT and P53 signaling pathways were the most abundant functional categories among gene targets. The circRNA molecular sponge regulatory network includes hsa-miR-1468 and hsa-miR-4665-3p. In this network, hs hsa_circITGA4_002, hsa_circITGA4_001, hsa_circ_0030857, EGFR, PTEN, and ITGA4 may represent GBM therapeutic targets. Their role in GBM needs additional study.
Keyphrases
- cell proliferation
- poor prognosis
- long non coding rna
- pi k akt
- gene expression
- signaling pathway
- small cell lung cancer
- genome wide
- electronic health record
- transcription factor
- long noncoding rna
- big data
- machine learning
- type diabetes
- epidermal growth factor receptor
- genome wide identification
- adipose tissue
- skeletal muscle
- social media
- high resolution
- drug delivery
- newly diagnosed
- oxidative stress
- artificial intelligence
- high throughput
- cancer therapy
- chronic kidney disease
- mass spectrometry
- genome wide analysis
- epithelial mesenchymal transition
- binding protein