基于遗传预测模型的血液蛋白生物标志物与前列腺癌风险的鉴定:对超过140,000名受试者的分析。
Identification of blood protein biomarkers associated with prostate cancer risk using genetic prediction models: analysis of over 140 000 subjects.
发表日期:2023 Aug 25
作者:
Hua Zhong, Jingjing Zhu, Shuai Liu, Dalia H Ghoneim, Praveen Surendran, Tao Liu, Sarah Fahle, Adam Butterworth, Md Ashad Alam, Hong-Wen Deng, Herbert Yu, Chong Wu, Lang Wu
来源:
HUMAN MOLECULAR GENETICS
摘要:
前列腺癌(PCa)在男性中造成了巨大的公共卫生负担。越来越多的传统观察性研究报告了多种循环蛋白与PCa风险的相关性。然而,现有的研究结果可能受到传统流行病学研究不一致的偏差的影响。为了更好地描述它们的关联性,我们在此评估了基因预测浆液蛋白浓度与PCa风险的关联性。我们为血浆中的蛋白质水平开发了全面的基因预测模型。在包括BPC3、CAPS、CRUK、PEGASUS和PRACTICAL的欧洲血统的79194个病例和61112个对照组中测试了1308种蛋白质,其中24种蛋白质与PCa风险显著相关,包括16种先前报道的蛋白质和8种新的蛋白质。其中,有14种蛋白质与PCa风险呈负相关,有10种蛋白质与PCa风险呈正相关。在发现的18种蛋白质中,检测到在前列腺癌患者中编码基因的潜在功能性变化,这些编码这些蛋白质的基因在癌症相关途径中显著参与。我们进一步确定了靶向这些蛋白质的药物,这些药物可能作为治疗前列腺癌的药物再利用的候选药物。总之,本研究确定了前列腺癌风险的新型蛋白质生物标志物候选物,这可能为前列腺癌的病因学提供新的视角,改善其治疗策略。©2023作者。由牛津大学出版社出版。保留所有权利。有关权限,请发送电子邮件至:journals.permissions@oup.com。
Prostate cancer (PCa) brings huge public health burden in men. A growing number of conventional observational studies report associations of multiple circulating proteins with PCa risk. However, the existing findings may be subject to incoherent biases of conventional epidemiologic studies. To better characterize their associations, herein, we evaluated associations of genetically predicted concentrations of plasma proteins with PCa risk. We developed comprehensive genetic prediction models for protein levels in plasma. After testing 1308 proteins in 79 194 cases and 61 112 controls of European ancestry included in the consortia of BPC3, CAPS, CRUK, PEGASUS, and PRACTICAL, 24 proteins showed significant associations with PCa risk, including 16 previously reported proteins and eight novel proteins. Of them, 14 proteins showed negative associations and 10 showed positive associations with PCa risk. For 18 of the identified proteins, potential functional somatic changes of encoding genes were detected in PCa patients in The Cancer Genome Atlas. Genes encoding these proteins were significantly involved in cancer-related pathways. We further identified drugs targeting the identified proteins, which may serve as candidates for drug repurposing for treating PCa. In conclusion, this study identifies novel protein biomarker candidates for PCa risk, which may provide new perspectives on the etiology of PCa and improve its therapeutic strategies.© The Author(s) 2023. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com.