Bioinformatic Analysis of miR-200b/429 and Hub Gene Network in Cervical Cancer.
Vaibhav ShuklaSandeep MallyaDivya AdigaS SriharikrishnaaSanjiban ChakrabartyShama Prasada KabekkoduPublished in: Biochemical genetics (2023)
The miR-200b/429 located at 1p36 is a highly conserved miRNA cluster emerging as a critical regulator of cervical cancer. Using publicly available miRNA expression data from TCGA and GEO followed by independent validation, we aimed to identify the association between miR-200b/429 expression and cervical cancer. miR-200b/429 cluster was significantly overexpressed in cancer samples compared to normal samples. miR-200b/429 expression did not correlate with patient survival; however, its overexpression correlated with histological type. Protein-protein interaction analysis of 90 target genes of miR-200b/429 identified EZH2, FLT1, IGF2, IRS1, JUN, KDR, SOX2, MYB, ZEB1, and TIMP2 as the top ten hub genes. PI3K-AKT and MAPK signaling pathways emerged as major target pathways of miR-200b/429 and their hub genes. Kaplan-Meier survival analysis showed the expression of seven miR-200b/429 target genes (EZH2, FLT1, IGF2, IRS1, JUN, SOX2, and TIMP2) to influence the overall survival of patients. The miR-200a-3p and miR-200b-5p could help predict cervical cancer with metastatic potential. The cancer hallmark enrichment analysis showed hub genes to promote growth, sustained proliferation, resistance to apoptosis, induction of angiogenesis, activation of invasion, and metastasis, enabling replicative immortality, evading immune destruction, and tumor-promoting inflammation. The drug-gene interaction analysis identified 182 potential drugs to interact with 27 target genes of miR-200b/429 with paclitaxel, doxorubicin, dabrafenib, bortezomib, docetaxel, ABT-199, eribulin, vorinostat, etoposide, and mitoxantrone emerging as the top ten best candidate drugs. Taken together, miR-200b/429 and associated hub genes can be helpful for prognostic application and clinical management of cervical cancer.
Keyphrases
- bioinformatics analysis
- genome wide identification
- genome wide
- pi k akt
- transcription factor
- signaling pathway
- poor prognosis
- binding protein
- cell cycle arrest
- oxidative stress
- network analysis
- stem cells
- protein protein
- end stage renal disease
- cell proliferation
- acute myeloid leukemia
- dna methylation
- chronic kidney disease
- drug delivery
- papillary thyroid
- tyrosine kinase
- endothelial cells
- small cell lung cancer
- randomized controlled trial
- gene expression
- small molecule
- peritoneal dialysis
- radiation therapy
- big data
- multiple myeloma
- clinical trial
- electronic health record
- endoplasmic reticulum stress
- cancer therapy
- vascular endothelial growth factor
- patient reported
- rectal cancer
- data analysis
- locally advanced
- adverse drug