Bioinformatics Prediction of miRNAs Targeting E6 and E7 Genes in Human Papillomavirus Types 16 and 18 in Cervical Cancer

Author:

Azimi TahereORCID, ,Bagheri MaliheORCID,Pariyan Mahdi,Khansarinejad BehzadORCID,Zamani AshrafORCID,Mondanizadeh MahdiehORCID, , , , ,

Abstract

Background and Aim: Cervical Cancer (CC) is the third most common malignancy in the women, the main cause of which is human papillomavirus (HPV). Both E6 and E7 oncogenes of the virus play an important role in its tumorigenesis. Today, methods available for screening CC are not capable of detecting the disease at an early stage. Therefore, it is important to identify new biomarkers for early detection of this cancer. For this purpose, in the present study, miRNAs targeting the two oncogenes E6 and E7 of human papillomavirus (types 16 and 18) were studied in CC by bioinformatics. Methods & Materials: First, using the NCBI database, the E6 and E7 gene sequences were obtained for both human papillomavirus types 16 and 18. Then, using the miRBase and RNA22 bioinformatics databases, the most appropriate targeting miRNAs for these genes were selected. Ethical Considerations: This study was approved by Ethics Committee of Arak University of Medical Sciences. Results: Based on the P obtained from bioinformatics databases, miRNA including miR-92a-5p (P=7.51e-2), miR-195-3p (P=2.24e-1), miR-34a-5p (P=2.73e-1) and miR-155-5p (P=4.95e-2) were introduced for the two genes E6 and E7. Conclusion: Results from bioinformatics studies revealed that of the four miRNAs identified, miR-155-5p and miR-92a-5p are probably the targeting miRNAs specific for the E6 and E7 genes, respectively. Therefore, it seems that these miRNAs can be a suitable candidate for in vitro studies in CC patients.

Publisher

Negah Scientific Publisher

Subject

General Engineering

Cited by 1 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3