Identification of novel serum protein biomarkers in the context of 3P medicine for intravenous leiomyomatosis: a data-independent acquisition mass spectrometry-based proteomics study.

IF 6.5 2区 医学 Q1 Medicine
Epma Journal Pub Date : 2023-09-04 eCollection Date: 2023-12-01 DOI:10.1007/s13167-023-00338-0
Zhitong Ge, Penghui Feng, Zijuan Zhang, Zhiyong Liang, Rong Chen, Jianchu Li
{"title":"Identification of novel serum protein biomarkers in the context of 3P medicine for intravenous leiomyomatosis: a data-independent acquisition mass spectrometry-based proteomics study.","authors":"Zhitong Ge, Penghui Feng, Zijuan Zhang, Zhiyong Liang, Rong Chen, Jianchu Li","doi":"10.1007/s13167-023-00338-0","DOIUrl":null,"url":null,"abstract":"<p><strong>Background: </strong>Intravenous leiomyomatosis (IVL) is a rare endocrine-associated tumor with unique characteristics of intravascular invasion. This study aimed to identify reliable biomarkers to supervise the development or recurrence of IVL in the context of predictive, preventive, and personalized medicine (PPPM/3PM).</p><p><strong>Methods: </strong>A total of 60 cases were recruited to detect differentially expressed proteins (DEPs) in serum samples from IVL patients. These cases included those with recurrent IVL, non-recurrent IVL, uterine myoma, and healthy individuals without uterine myoma, with 15 cases in each category. Then, weighted gene co-expression network analysis (WGCNA), lasso-penalized Cox regression analysis (Lasso), trend clustering, and a generalized linear regression model (GLM) were utilized to screen the hub proteins involved in IVL progression.</p><p><strong>Results: </strong>First, 93 differentially expressed proteins (DEPs) were determined from 2582 recognizable proteins, with 54 proteins augmented in the IVL group, and the remaining proteins declined. These proteins were enriched in the modulation of the immune environment, mainly by activating the function of B cells. After the integrated analyses mentioned above, a model based on four proteins (A0A5C2FUE5, A0A5C2GPQ1, A0A5C2GNC7, and A0A5C2GBR3) was developed to efficiently determine the potential of IVL lesions to progress. Among these featured proteins, our results demonstrated that the risk factor A0A5C2FUE5 was associated with IVL progression (OR = 2.64). Conversely, A0A5C2GPQ1, A0A5C2GNC7, and A0A5C2GBR3 might act in a protective manner and prevent disease development (OR = 0.32, 0.60, 0.53, respectively), which was further supported by the multi-class receiver operator characteristic curve analysis.</p><p><strong>Conclusion: </strong>Four hub proteins were eventually identified based on the integrated bioinformatics analyses. This study potentiates the promising application of these novel biomarkers to predict the prognosis or progression of IVL by a 3PM approach.</p><p><strong>Supplementary information: </strong>The online version contains supplementary material available at 10.1007/s13167-023-00338-0.</p>","PeriodicalId":54292,"journal":{"name":"Epma Journal","volume":null,"pages":null},"PeriodicalIF":6.5000,"publicationDate":"2023-09-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10713895/pdf/","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Epma Journal","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.1007/s13167-023-00338-0","RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2023/12/1 0:00:00","PubModel":"eCollection","JCR":"Q1","JCRName":"Medicine","Score":null,"Total":0}
引用次数: 0

Abstract

Background: Intravenous leiomyomatosis (IVL) is a rare endocrine-associated tumor with unique characteristics of intravascular invasion. This study aimed to identify reliable biomarkers to supervise the development or recurrence of IVL in the context of predictive, preventive, and personalized medicine (PPPM/3PM).

Methods: A total of 60 cases were recruited to detect differentially expressed proteins (DEPs) in serum samples from IVL patients. These cases included those with recurrent IVL, non-recurrent IVL, uterine myoma, and healthy individuals without uterine myoma, with 15 cases in each category. Then, weighted gene co-expression network analysis (WGCNA), lasso-penalized Cox regression analysis (Lasso), trend clustering, and a generalized linear regression model (GLM) were utilized to screen the hub proteins involved in IVL progression.

Results: First, 93 differentially expressed proteins (DEPs) were determined from 2582 recognizable proteins, with 54 proteins augmented in the IVL group, and the remaining proteins declined. These proteins were enriched in the modulation of the immune environment, mainly by activating the function of B cells. After the integrated analyses mentioned above, a model based on four proteins (A0A5C2FUE5, A0A5C2GPQ1, A0A5C2GNC7, and A0A5C2GBR3) was developed to efficiently determine the potential of IVL lesions to progress. Among these featured proteins, our results demonstrated that the risk factor A0A5C2FUE5 was associated with IVL progression (OR = 2.64). Conversely, A0A5C2GPQ1, A0A5C2GNC7, and A0A5C2GBR3 might act in a protective manner and prevent disease development (OR = 0.32, 0.60, 0.53, respectively), which was further supported by the multi-class receiver operator characteristic curve analysis.

Conclusion: Four hub proteins were eventually identified based on the integrated bioinformatics analyses. This study potentiates the promising application of these novel biomarkers to predict the prognosis or progression of IVL by a 3PM approach.

Supplementary information: The online version contains supplementary material available at 10.1007/s13167-023-00338-0.

Abstract Image

在静脉子宫肌瘤病 3P 医学背景下识别新型血清蛋白生物标志物:基于质谱的蛋白质组学研究的数据独立采集。
背景:静脉内黏液瘤病(IVL)是一种罕见的内分泌相关肿瘤,具有血管内侵犯的独特特征。本研究的目的是在预测、预防和个性化医疗(PPPM/3PM)的背景下,确定可靠的生物标志物,以监督IVL的发展或复发:方法:共招募了60个病例,检测IVL患者血清样本中的差异表达蛋白(DEPs)。这些病例包括复发性 IVL、非复发性 IVL、子宫肌瘤和无子宫肌瘤的健康人,每类 15 例。然后,利用加权基因共表达网络分析(WGCNA)、Lasso-penalized Cox回归分析(Lasso)、趋势聚类和广义线性回归模型(GLM)筛选出参与IVL进展的枢纽蛋白:首先,从 2582 个可识别蛋白中确定了 93 个差异表达蛋白(DEPs),其中 54 个蛋白在 IVL 组中增加,其余蛋白减少。这些蛋白质主要通过激活 B 细胞的功能来调节免疫环境。经过上述综合分析,建立了一个基于四种蛋白质(A0A5C2FUE5、A0A5C2GPQ1、A0A5C2GNC7 和 A0A5C2GBR3)的模型,以有效确定 IVL 病变进展的可能性。结果表明,在这些特征蛋白中,风险因子 A0A5C2FUE5 与 IVL 进展相关(OR = 2.64)。相反,A0A5C2GPQ1、A0A5C2GNC7 和 A0A5C2GBR3 可能以保护性方式发挥作用,防止疾病发展(OR 分别为 0.32、0.60 和 0.53),多级接收器运算特征曲线分析进一步证实了这一点:结论:基于综合生物信息学分析,最终确定了四个中心蛋白。结论:基于综合生物信息学分析,最终确定了四个枢纽蛋白,该研究为通过3PM方法预测IVL的预后或进展提供了新的生物标志物:在线版本包含补充材料,可在10.1007/s13167-023-00338-0上获取。
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
Epma Journal
Epma Journal Medicine-Biochemistry (medical)
CiteScore
11.30
自引率
23.10%
发文量
0
期刊介绍: PMA Journal is a journal of predictive, preventive and personalized medicine (PPPM). The journal provides expert viewpoints and research on medical innovations and advanced healthcare using predictive diagnostics, targeted preventive measures and personalized patient treatments. The journal is indexed by PubMed, Embase and Scopus.
×
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