Introduction: By expanding the range of information in biological fields, bioinformatics tools provide researchers with the possibility of using and analyzing data easily. Today, the use of bioinformatics tools has significantly reduced the time and cost of molecular studies in the field of diseases. MicroRNAs (miRNAs) are a relatively new class of functional small RNAs with diverse functions that have attracted the attention of many researchers in recent years. These small RNAs play a role in many metabolic and signaling pathways, and we see their dysregulation in many diseases including cancer. therefore, the study of these RNAs will be beneficial in finding treatment methods. It has been previously reported that KIF11 (Kinesin Family Member 11) is upregulated in breast cancer and is related to increased cell viability and proliferation, colony formation, migration and invasion; As a result, KIF11 as an Oncogene plays a key role in promoting breast cancer, hence new therapeutic pathways can be found by identifying its regulatory network through miRNAs.
Methods: Using the GENE section in the NCBI database, the number of nucleotides in the 3'UTR region of KIF11 was determined. Afterward, in the nucleotide section of the same database, the sequence of KIF11 was obtained in FASTA format and its 3' UTR region was highlighted on the sequence. 72 miRNAs that interact with KIF11 were predicted using miRTargetLink 2.0 database. The sequence of these miRNAs was obtained from the miRbase database. With the help of RNAHybrid, the interaction of each of the predicted miRNAs and the 3'UTR of KIF11 was analyzed bioinformatically. Eventually, Diana miRpathv3 was used to study metabolic and signaling pathways related to these miRNAs.
Results: After data analysis, among the 72 predicted miRNAs related to KIF11, all of which were analyzed by RNAHybrid, 7 miRNAs that showed a stronger relationship with KIF11 were selected; These 7 miRNAs are hsa-miR-432-5p, hsa-miR-296-3p, hsa-miR-145-5p, hsa-miR-1237-3p, hsa-miR-154-5p, hsa- miR-659-3p and hsa-miR-122-5p respectively. The data obtained from Diana miRpath show a strong relationship between hsa-miR-154-5p, hsa-miR-432-5p, hsa-miR-145-5p , hsa-miR-122-5p and ECM-receptor interaction pathways. Also, the heatmap designed by Diana tool showed that hsa-miR-296-3p, hsa-miR-145-5p, hsa-miR-432-5p and hsa-miR-122-5p are involved in transcriptional mis-regulation in cancer.
Conclusion: Considering the oncogenic role of KIF11 in progression and development of breast cancer and its upregulation in this disease that disrupts the natural balance of cell viability, proliferation, colony formation, migration and invasion, the reduction of its expression due to the overexpression of any of listed miRNAs above can inhibit the proliferation of breast cancer cells and as a result can be used as a new therapeutic approach in treatment of breast cancer.
Keywords: KIF11 , Breast cancer , miRNA , Bioinformatic analysis, microRNA