A computational approach to prediction of mirna targets narrowing down potential target sites for experimental validation. the aim of this study is to identify the breast cancer (bc) specific mirnas and their target mrnas in drug resistance pathway using a multi-step approach.
Methods
Microarray expression profile (gse24460, gse62259) merged and bioinformatics study was implemented to identify the bc specific mirna-mrna regulatory network. first, 69 differentially expressed mirnas and 3832 mrnas from bc samples compare with normal sample and mcf7 resistance cell were identified by microarray data analysis in expression console software (affymetrix) and flexarray software. then, about 30 dysregulated mirnas and their 68 target mrnas were identified by a combination of analysis and prediction by targetscan and miwalk. the mirna gene regulatory network was revealed by cytoscape software.
Results
Bioinformatics analysis displayed these mirna-mrnas were involved in wnt signaling and mdr pathway. also 98 tumor suppressor genes identified that down-regulated in analysis. furthermore, 5 up-regulated mirnas (mir-19a, mir-218, mir-200c, mir-99a, and mir-27a) and 4 down-regulated predicted target mrnas (wnt5a, tsc1, atxn1, cyp24a1) with upper score were selected in extensive analysis. finally, functional analysis was performed for the target genes followed by construction of a mirna‑target gene network.
Conclusion
The results in our study were useful to further research via a functional study to understand the underlying regulatory mechanisms of mirna and their target genes in bc that may be new targets for breast cancer therapy.
Keywords
micrornas, target mrnas, microarray, breast cancer, drug resistance
