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全蛋白质组孟德尔随机化分析以鉴定上皮性卵巢癌亚型的潜在血浆生物标志物和治疗靶点。

Proteome-Wide Mendelian Randomization Analysis to Identify Potential Plasma Biomarkers and Therapeutic Targets for Epithelial Ovarian Cancer Subtypes.

作者信息

Lin Qianhan, Li Jiajia, Sun Yating, Abudousalamu Zulimire, Xue Mengyang, Yao Liangqing, Chen Mo

机构信息

Department of Gynecologic Oncology, Obstetrics and Gynecology Hospital, Fudan University, Shanghai, 200011, People's Republic of China.

Department of Gynecologic Oncology, Guangzhou Women and Children's Medical Center, Guangzhou Medical University, Guangzhou, 510005, People's Republic of China.

出版信息

Int J Womens Health. 2024 Dec 21;16:2263-2279. doi: 10.2147/IJWH.S491414. eCollection 2024.

DOI:10.2147/IJWH.S491414
PMID:39726690
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC11669594/
Abstract

BACKGROUND

Epithelial ovarian cancer (EOC) remains an unmet medical challenge due to its insidious onset, atypical symptoms, and increasing resistance to conventional chemotherapeutic agents. It is imperative to explore novel biomarkers and generate innovative target drugs.

METHODS

To identify potential proteins with causal association to EOC subtypes, we conducted a Mendelian Randomization (MR) analysis using 15,419 protein quantitative trait loci (pQTLs) associated with 2015 proteins. Bayesian colocalization analysis, Summary-data-based MR, and Heterogeneity in Dependent Instruments tests were employed for validation. Enrichment and druggability analyses were performed to assess the biological significance and therapeutic potential of identified proteins.

RESULTS

Our analysis identified 455 unique proteins associated with at least one EOC subtype, with 14 protein-cancer associations confirmed by further validation. Ten proteins were prioritized as potential therapeutic targets, including α1B-glycoprotein (A1BG) and ephrin-A1 (EFNA1), which interact with the known drug targets human epidermal growth factor receptor 2 (HER2) and vascular endothelial growth factor receptor (VEGFR).

CONCLUSION

This study elucidated the plasma proteins causally associated with EOC subtypes, potentially offering easily detectable biomarkers and promising therapeutic targets. A1BG and EFNA1 were identified as druggable targets and confirmed to correspond with current pharmacological targets. Targeting these proteins in drug development potentially offers an avenue for innovative treatment strategies.

摘要

背景

上皮性卵巢癌(EOC)因其起病隐匿、症状不典型以及对传统化疗药物的耐药性不断增加,仍然是一个尚未解决的医学难题。探索新型生物标志物并研发创新靶向药物势在必行。

方法

为了确定与EOC亚型有因果关联的潜在蛋白质,我们使用与2015种蛋白质相关的15419个蛋白质定量性状位点(pQTL)进行了孟德尔随机化(MR)分析。采用贝叶斯共定位分析、基于汇总数据的MR分析和依赖工具中的异质性检验进行验证。进行富集和可成药分析,以评估已鉴定蛋白质的生物学意义和治疗潜力。

结果

我们的分析确定了455种与至少一种EOC亚型相关的独特蛋白质,其中14种蛋白质与癌症的关联通过进一步验证得到确认。十种蛋白质被列为潜在的治疗靶点,包括α1B-糖蛋白(A1BG)和ephrin-A1(EFNA1),它们与已知的药物靶点人表皮生长因子受体2(HER2)和血管内皮生长因子受体(VEGFR)相互作用。

结论

本研究阐明了与EOC亚型有因果关联的血浆蛋白质,可能提供易于检测的生物标志物和有前景的治疗靶点。A1BG和EFNA1被确定为可成药靶点,并被证实与当前的药理学靶点相对应。在药物研发中针对这些蛋白质可能为创新治疗策略提供一条途径。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5df9/11669594/56c4e51e9e8c/IJWH-16-2263-g0006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5df9/11669594/8762a6493bd6/IJWH-16-2263-g0001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5df9/11669594/a9b3a87a5bb5/IJWH-16-2263-g0002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5df9/11669594/1da2cd4a63a5/IJWH-16-2263-g0003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5df9/11669594/ec5e64c72d2d/IJWH-16-2263-g0004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5df9/11669594/a46e1acad820/IJWH-16-2263-g0005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5df9/11669594/56c4e51e9e8c/IJWH-16-2263-g0006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5df9/11669594/8762a6493bd6/IJWH-16-2263-g0001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5df9/11669594/a9b3a87a5bb5/IJWH-16-2263-g0002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5df9/11669594/1da2cd4a63a5/IJWH-16-2263-g0003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5df9/11669594/ec5e64c72d2d/IJWH-16-2263-g0004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5df9/11669594/a46e1acad820/IJWH-16-2263-g0005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5df9/11669594/56c4e51e9e8c/IJWH-16-2263-g0006.jpg

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