Predicting the interaction of hsa-miR-۱۳۳b in NELL۲ gene and also express this gene in ovarian cancer through bioinformatics analysis

Ovarian cancer is the leading cause of death among gynecological cancers. The disease typically presents in postmenopausal women, with several months of abdominal pain and distension. With the becoming better high-throughput profiling techniques and the availability of public data sets such as The Cancer Genome Atlas Program (TCGA), a broad range of coding transcripts have been profiled and their underlying modes of action have been mapped. The regulation of a lot of pathways in cell biology is regulated by miRNAs. Obtaining miRNA target genes is effective for controlling these pathways and can also help to understand the regulatory mechanism and treatment of cancer. Methods: In this project, we utilized the targetscan database to predict miRNA target genes, we performed an analysis of TCGA RNA-seq data and predicted gene expression patterns. Results: In this study, we observed that hsa-miR-۱۳۳b is found within the ۳' UTR region of the NELL۲ gene, specifically between nucleotides ۵۳ and ۵۹. The results of TCGA data analysis showed that the expression levels of this gene in tumor tissues from patients with ovarian cancer are significantly reduced. The results of these assessments indicated a strong link between NELL۲ and hsa-miR-۱۳۳b. Conclusion: Our predictions indicate that elevated levels of hsa-miR-۱۳۳b are associated with reduced expression of NELL۲ in ovarian cancer. It is also predicted that the reduction in the expression of NELL۲, in addition to the role of a biomarker in the diagnosis of ovarian cancer, can be a factor in the development of ovarian cancer and the activation of the pathway. According to the studies we obtained from bioinformatics tools, we can conclude that hsa-miR-۱۳۳b is related to ovarian cancer and this miR-۱۳۳b can be effective in the diagnosis and treatment of ovarian cancer. Given the absence of effective screening tests for ovarian cancer, this association could aid in the development of a diagnostic assay that fulfills screening criteria and thereby increases the early detection of ovarian cancer.

کلیدواژه ها:

ovarian cancer ، miR-۱۳۳b ، NELL۱ ، Bioinformatic analysis