Exosomal insights into ovarian cancer stem cells: revealing the molecular hubs.

IF 3.8 3区 医学 Q1 REPRODUCTIVE BIOLOGY
Kiana Sojoudi, Maryam Solaimani, Hossein Azizi
{"title":"Exosomal insights into ovarian cancer stem cells: revealing the molecular hubs.","authors":"Kiana Sojoudi, Maryam Solaimani, Hossein Azizi","doi":"10.1186/s13048-025-01597-3","DOIUrl":null,"url":null,"abstract":"<p><p>Ovarian cancer is a deadly disease, often diagnosed at advanced stages due to a lack of reliable biomarkers. Exosomes, which carry a variety of molecules such as proteins, lipids, DNA, and non-coding RNAs, have recently emerged as promising tools for early cancer detection. While exosomes have been studied in various cancer types, comprehensive network analyses of exosome proteins in ovarian cancer remain limited. In this study, we used a protein-protein interaction (PPI) network. Using the Clustermaker2 app and the MCODE algorithm, we identified six significant clusters within the network, highlighting regions involved in functional pathways. A four-fold algorithmic approach, including MCC, DMNC, Degree, and EPC, identified 12 common hub genes. STRING analysis and visualization techniques provided a detailed understanding of the biological processes associated with these hub genes. Notably, 91.7% of the identified hub genes were involved in translational processes, showing an important role in protein synthesis regulation in ovarian cancer. In addition, we identified the miRNAs and LncRNAs carried by ovarian cancer exosomes. These findings highlight potential biomarkers for early detection and therapeutic targets.</p>","PeriodicalId":16610,"journal":{"name":"Journal of Ovarian Research","volume":"18 1","pages":"20"},"PeriodicalIF":3.8000,"publicationDate":"2025-01-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11784003/pdf/","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Ovarian Research","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.1186/s13048-025-01597-3","RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"REPRODUCTIVE BIOLOGY","Score":null,"Total":0}
引用次数: 0

Abstract

Ovarian cancer is a deadly disease, often diagnosed at advanced stages due to a lack of reliable biomarkers. Exosomes, which carry a variety of molecules such as proteins, lipids, DNA, and non-coding RNAs, have recently emerged as promising tools for early cancer detection. While exosomes have been studied in various cancer types, comprehensive network analyses of exosome proteins in ovarian cancer remain limited. In this study, we used a protein-protein interaction (PPI) network. Using the Clustermaker2 app and the MCODE algorithm, we identified six significant clusters within the network, highlighting regions involved in functional pathways. A four-fold algorithmic approach, including MCC, DMNC, Degree, and EPC, identified 12 common hub genes. STRING analysis and visualization techniques provided a detailed understanding of the biological processes associated with these hub genes. Notably, 91.7% of the identified hub genes were involved in translational processes, showing an important role in protein synthesis regulation in ovarian cancer. In addition, we identified the miRNAs and LncRNAs carried by ovarian cancer exosomes. These findings highlight potential biomarkers for early detection and therapeutic targets.

外泌体洞察卵巢癌干细胞:揭示分子枢纽。
卵巢癌是一种致命的疾病,由于缺乏可靠的生物标志物,通常在晚期才被诊断出来。外泌体携带多种分子,如蛋白质、脂质、DNA和非编码rna,最近成为早期癌症检测的有前途的工具。虽然外泌体已经在各种癌症类型中得到了研究,但对卵巢癌外泌体蛋白的全面网络分析仍然有限。在这项研究中,我们使用了蛋白质-蛋白质相互作用(PPI)网络。使用Clustermaker2应用程序和MCODE算法,我们在网络中确定了六个重要的集群,突出了涉及功能通路的区域。包括MCC、DMNC、Degree和EPC在内的四重算法方法确定了12个常见的枢纽基因。STRING分析和可视化技术提供了与这些中心基因相关的生物学过程的详细了解。值得注意的是,91.7%的中心基因参与了翻译过程,在卵巢癌的蛋白质合成调控中发挥了重要作用。此外,我们还鉴定了卵巢癌外泌体携带的mirna和lncrna。这些发现突出了早期检测和治疗靶点的潜在生物标志物。
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 求助全文
来源期刊
Journal of Ovarian Research
Journal of Ovarian Research REPRODUCTIVE BIOLOGY-
CiteScore
6.20
自引率
2.50%
发文量
125
审稿时长
>12 weeks
期刊介绍: Journal of Ovarian Research is an open access, peer reviewed, online journal that aims to provide a forum for high-quality basic and clinical research on ovarian function, abnormalities, and cancer. The journal focuses on research that provides new insights into ovarian functions as well as prevention and treatment of diseases afflicting the organ. Topical areas include, but are not restricted to: Ovary development, hormone secretion and regulation Follicle growth and ovulation Infertility and Polycystic ovarian syndrome Regulation of pituitary and other biological functions by ovarian hormones Ovarian cancer, its prevention, diagnosis and treatment Drug development and screening Role of stem cells in ovary development and function.
×
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
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
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 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信