Proteome-wide association study and functional validation identify novel protein markers for pancreatic ductal adenocarcinoma.

IF 11.8 2区 生物学 Q1 MULTIDISCIPLINARY SCIENCES
Jingjing Zhu, Ke Wu, Shuai Liu, Alexandra Masca, Hua Zhong, Tai Yang, Dalia H Ghoneim, Praveen Surendran, Tanxin Liu, Qizhi Yao, Tao Liu, Sarah Fahle, Adam Butterworth, Md Ashad Alam, Jaydutt V Vadgama, Youping Deng, Hong-Wen Deng, Chong Wu, Yong Wu, Lang Wu
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引用次数: 0

Abstract

Pancreatic ductal adenocarcinoma (PDAC) remains a lethal malignancy, largely due to the paucity of reliable biomarkers for early detection and therapeutic targeting. Existing blood protein biomarkers for PDAC often suffer from replicability issues, arising from inherent limitations such as unmeasured confounding factors in conventional epidemiologic study designs. To circumvent these limitations, we use genetic instruments to identify proteins with genetically predicted levels to be associated with PDAC risk. Leveraging genome and plasma proteome data from the INTERVAL study, we established and validated models to predict protein levels using genetic variants. By examining 8,275 PDAC cases and 6,723 controls, we identified 40 associated proteins, of which 16 are novel. Functionally validating these candidates by focusing on 2 selected novel protein-encoding genes, GOLM1 and B4GALT1, we demonstrated their pivotal roles in driving PDAC cell proliferation, migration, and invasion. Furthermore, we also identified potential drug repurposing opportunities for treating PDAC.

Significance: PDAC is a notoriously difficult-to-treat malignancy, and our limited understanding of causal protein markers hampers progress in developing effective early detection strategies and treatments. Our study identifies novel causal proteins using genetic instruments and subsequently functionally validates selected novel proteins. This dual approach enhances our understanding of PDAC etiology and potentially opens new avenues for therapeutic interventions.

全蛋白质组关联研究和功能验证确定了胰腺导管腺癌的新型蛋白质标记物。
胰腺导管腺癌(PDAC)仍然是一种致命的恶性肿瘤,这在很大程度上是由于缺乏用于早期检测和靶向治疗的可靠生物标志物。现有的 PDAC 血液蛋白生物标志物往往存在可复制性问题,这是由于传统流行病学研究设计中存在未测量混杂因素等固有局限性造成的。为了规避这些局限性,我们使用基因仪器来鉴定具有基因预测水平的与 PDAC 风险相关的蛋白质。利用 INTERVAL 研究的基因组和血浆蛋白质组数据,我们建立并验证了利用基因变异预测蛋白质水平的模型。通过研究 8275 例 PDAC 病例和 6723 例对照,我们确定了 40 种相关蛋白,其中 16 种是新蛋白。通过对两个选定的新蛋白编码基因 GOLM1 和 B4GALT1 进行功能验证,我们证明了这些候选蛋白在驱动 PDAC 细胞增殖、迁移和侵袭中的关键作用。此外,我们还发现了治疗 PDAC 的潜在药物再利用机会:PDAC是一种众所周知的难以治疗的恶性肿瘤,而我们对病因蛋白标记物的了解有限,这阻碍了开发有效早期检测策略和治疗方法的进展。我们的研究利用基因仪器鉴定了新的病因蛋白,并随后对选定的新蛋白进行了功能验证。这种双重方法增强了我们对 PDAC 病因学的了解,并有可能为治疗干预开辟新的途径。
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来源期刊
GigaScience
GigaScience MULTIDISCIPLINARY SCIENCES-
CiteScore
15.50
自引率
1.10%
发文量
119
审稿时长
1 weeks
期刊介绍: GigaScience seeks to transform data dissemination and utilization in the life and biomedical sciences. As an online open-access open-data journal, it specializes in publishing "big-data" studies encompassing various fields. Its scope includes not only "omic" type data and the fields of high-throughput biology currently serviced by large public repositories, but also the growing range of more difficult-to-access data, such as imaging, neuroscience, ecology, cohort data, systems biology and other new types of large-scale shareable data.
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