[Regular Paper] Identification of Several Core Overexpressed MicroRNAs that Could Predict Survival in Patients with Ovarian Cancer

E. Dessie, Ezra B. Wijaya, Chien-Hung Huang, D. Agustriawan, J. Tsai, K. Ng
{"title":"[Regular Paper] Identification of Several Core Overexpressed MicroRNAs that Could Predict Survival in Patients with Ovarian Cancer","authors":"E. Dessie, Ezra B. Wijaya, Chien-Hung Huang, D. Agustriawan, J. Tsai, K. Ng","doi":"10.1109/BIBE.2018.00058","DOIUrl":null,"url":null,"abstract":"MicroRNAs as biomarkers play an important role in the oncogenesis process, including ovarian cancer. The objective of this study is to evaluate the miRNAs overexpression association with survival of ovarian cancer patients. MiRNA expression levels between tumor and normal samples were compared using t-test. Differentially expressed miRNAs were selected (p-value ≤ 0.001) and only 195 up-regulated miRNAs for 565 ovarian cancer samples were further analyzed using multivariate Cox regression and survival random forest. The median survival time for ovarian cancer patient was 33.64 months. The result of survival random forest and multivariate Cox regression showed that high level expression of nine miRNAs were associated with shorten survival of ovarian cancer patients; whereas high level expression of hsa-miR-154* was significantly correlated with a prolonged overall survival ovarian cancer patients. These nine aberrantly overexpressed miRNAs that resulted shorter survival time may play important roles in oncogenesis, growth, and metastasis of ovarian cancer. Hence, these findings may be used as novel prognostic biomarkers and therapeutic targets for ovarian cancer patients.","PeriodicalId":127507,"journal":{"name":"2018 IEEE 18th International Conference on Bioinformatics and Bioengineering (BIBE)","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2018-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2018 IEEE 18th International Conference on Bioinformatics and Bioengineering (BIBE)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/BIBE.2018.00058","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 1

Abstract

MicroRNAs as biomarkers play an important role in the oncogenesis process, including ovarian cancer. The objective of this study is to evaluate the miRNAs overexpression association with survival of ovarian cancer patients. MiRNA expression levels between tumor and normal samples were compared using t-test. Differentially expressed miRNAs were selected (p-value ≤ 0.001) and only 195 up-regulated miRNAs for 565 ovarian cancer samples were further analyzed using multivariate Cox regression and survival random forest. The median survival time for ovarian cancer patient was 33.64 months. The result of survival random forest and multivariate Cox regression showed that high level expression of nine miRNAs were associated with shorten survival of ovarian cancer patients; whereas high level expression of hsa-miR-154* was significantly correlated with a prolonged overall survival ovarian cancer patients. These nine aberrantly overexpressed miRNAs that resulted shorter survival time may play important roles in oncogenesis, growth, and metastasis of ovarian cancer. Hence, these findings may be used as novel prognostic biomarkers and therapeutic targets for ovarian cancer patients.
查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
【常规论文】几种核心过表达microrna的鉴定可预测卵巢癌患者的生存
microrna作为生物标志物在肿瘤发生过程中发挥着重要作用,包括卵巢癌。本研究的目的是评估miRNAs过表达与卵巢癌患者生存的关系。采用t检验比较肿瘤与正常样本的MiRNA表达水平。选择差异表达的mirna (p值≤0.001),使用多变量Cox回归和生存随机森林对565例卵巢癌样本中仅195个上调mirna进行进一步分析。卵巢癌患者的中位生存期为33.64个月。生存随机森林和多因素Cox回归结果显示,9种mirna的高表达与卵巢癌患者生存期缩短相关;而高水平表达hsa-miR-154*与卵巢癌患者总生存期的延长显著相关。这9个异常过表达的mirna导致存活时间缩短,可能在卵巢癌的发生、生长和转移中发挥重要作用。因此,这些发现可能作为卵巢癌患者新的预后生物标志物和治疗靶点。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 去求助
来源期刊
自引率
0.00%
发文量
0
期刊最新文献
Nonlinear CMOS Image Sensor with SOC Integrated Local Contrast Stretch for Bio-Microfluidic Imaging [Regular Paper] Recovering a Chemotopic Feature Space from a Group of Fruit Fly Antenna Chemosensors A Systems Biology Approach to Model Gene-Gene Interaction for Childhood Sarcomas Finite Element Modelling for the Detection of Breast Tumor [Regular Paper] Implementation of an Ultrasound Platform for Proposed Photoacoustic Image Reconstruction Algorithm
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 联系我们:info@booksci.cn
Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。
Copyright © 2023 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1