已发表论文

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

 

Authors Lin Q, Li J, Sun Y, Abudousalamu Z, Xue M, Yao L, Chen M 

Received 10 September 2024

Accepted for publication 5 December 2024

Published 21 December 2024 Volume 2024:16 Pages 2263—2279

DOI https://doi.org/10.2147/IJWH.S491414

Checked for plagiarism Yes

Review by Single anonymous peer review

Peer reviewer comments 2

Editor who approved publication: Professor Elie Al-Chaer

Qianhan Lin,1 Jiajia Li,1 Yating Sun,1 Zulimire Abudousalamu,1 Mengyang Xue,1 Liangqing Yao,2 Mo Chen1 

1Department of Gynecologic Oncology, Obstetrics and Gynecology Hospital, Fudan University, Shanghai, 200011, People’s Republic of China; 2Department of Gynecologic Oncology, Guangzhou Women and Children’s Medical Center, Guangzhou Medical University, Guangzhou, 510005, People’s Republic of China

Correspondence: Liangqing Yao, Department of Gynecologic Oncology, Guangzhou Women and Children’s Medical Center, Guangzhou Medical University, Guangzhou, 510005, People’s Republic of China, Email yaoliangqing@163.com Mo Chen, Department of Gynecologic Oncology, Obstetrics and Gynecology Hospital, Fudan University, Shanghai, 200011, People’s Republic of China, Email chenmo_nicy@163.com

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 α 1B-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.

Keywords: drug target prediction, novel circulation biomarkers, epithelial ovarian cancer, Mendelian randomization, plasma proteins