Identification of blood protein biomarkers associated with prostate cancer risk using genetic prediction models: analysis of over 140,000 subjects

被引:4
作者
Zhong, Hua [1 ]
Zhu, Jingjing [1 ]
Liu, Shuai [1 ]
Ghoneim, Dalia H. [1 ]
Surendran, Praveen [2 ]
Liu, Tao [3 ]
Fahle, Sarah [2 ]
Butterworth, Adam [2 ,4 ]
Alam, Md Ashad [5 ,6 ]
Deng, Hong-Wen [5 ]
Yu, Herbert [1 ]
Wu, Chong [7 ]
Wu, Lang [1 ]
机构
[1] Univ Hawaii Manos, Univ Hawaii Canc Ctr, Canc Epidemiol Div, Populat Sci Pacific Program, 701 Ilalo Str, Honolulu, HI 96813 USA
[2] Univ Cambridge, Dept Publ Hlth & Primary Care, MRC BHF Cardiovasc Epidemiol Unit, Papworth Rd Cambridge Biomed Campus, Cambridge CB2 0BB, England
[3] Pacific Northwest Natl Lab, Biol Sci Div, Richland, WA 99354 USA
[4] Univ Cambridge, Dept Publ Hlth & Primary Care, NIHR Blood & Transplant Res Unit Donor Hlth & Gen, Papworth Rd Cambridge Biomed Campus, Cambridge CB20BB, England
[5] Tulane Univ, Deming Dept Med, Div Biomed Informat & Genom, Tulane Ctr Biomed Informat & Gen, 1440 Canal Str, New Orleans, LA 70112 USA
[6] Ochsner Clin Foundat, Ctr Outcomes Res, New Orleans, LA 70121 USA
[7] Univ Texas MD Anderson Canc Ctr, Dept Biostat, 1400 Pressler St, Houston, TX 77030 USA
关键词
protein biomarker; genetics; prostate cancer; risk; HEPATOCYTE GROWTH-FACTOR; SUSCEPTIBILITY LOCI; EXPRESSION; CARCINOMA; PLASMA; LAMC1; QUANTIFICATION; PROLIFERATION; METAANALYSIS; PLASMINOGEN;
D O I
10.1093/hmg/ddad139
中图分类号
Q5 [生物化学]; Q7 [分子生物学];
学科分类号
071010 ; 081704 ;
摘要
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 (TCGA). 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. [GRAPHICS] .
引用
收藏
页码:3181 / 3193
页数:13
相关论文
共 69 条
[61]   Expression of a novel biomarker, EPCA, in adenocarcinomas and precancerous lesions in the prostate [J].
Uetsuki, H ;
Tsunemori, H ;
Taoka, R ;
Haba, R ;
Ishikawa, M ;
Kakehi, Y .
JOURNAL OF UROLOGY, 2005, 174 (02) :514-518
[62]   PKMYT1 is associated with prostate cancer malignancy and may serve as a therapeutic target [J].
Wang, Jianan ;
Wang, Lin ;
Chen, Saipeng ;
Peng, Huahong ;
Xiao, Longfei ;
Du, E. ;
Liu, Yan ;
Lin, Dong ;
Wang, Yuzhuo ;
Xu, Yong ;
Yang, Kuo .
GENE, 2020, 744
[63]   DrugBank:: a comprehensive resource for in silico drug discovery and exploration [J].
Wishart, David S. ;
Knox, Craig ;
Guo, An Chi ;
Shrivastava, Savita ;
Hassanali, Murtaza ;
Stothard, Paul ;
Chang, Zhan ;
Woolsey, Jennifer .
NUCLEIC ACIDS RESEARCH, 2006, 34 :D668-D672
[64]   Novel strategy for disease risk prediction incorporating predicted gene expression and DNA methylation data: a multi-phased study of prostate cancer [J].
Wu, Chong ;
Zhu, Jingjing ;
King, Austin ;
Tong, Xiaoran ;
Lu, Qing ;
Park, Jong Y. ;
Wang, Liang ;
Gao, Guimin ;
Deng, Hong-Wen ;
Yang, Yaohua ;
Knudsen, Karen E. ;
Rebbeck, Timothy R. ;
Long, Jirong ;
Zheng, Wei ;
Pan, Wei ;
Conti, David, V ;
Haiman, Christopher A. ;
Wu, Lang .
CANCER COMMUNICATIONS, 2021, 41 (12) :1387-1397
[65]   Analysis of Over 140,000 European Descendants Identifies Genetically Predicted Blood Protein Biomarkers Associated with Prostate Cancer Risk [J].
Wu, Lang ;
Shu, Xiang ;
Bao, Jiandong ;
Guo, Xingyi ;
Kote-Jarai, Zsofia ;
Haiman, Christopher A. ;
Eeles, Rosalind A. ;
Zheng, Wei .
CANCER RESEARCH, 2019, 79 (18) :4592-4598
[66]   Identification of Novel Susceptibility Loci and Genes for Prostate Cancer Risk: A Transcriptome-Wide Association Study in over 140,000 European Descendants [J].
Wu, Lang ;
Wang, Jifeng ;
Cai, Qiuyin ;
Cavazos, Taylor B. ;
Emami, Nima C. ;
Long, Jirong ;
Shu, Xiao-Ou ;
Lu, Yingchang ;
Guo, Xingyi ;
Bauer, Joshua A. ;
Pasaniuc, Bogdan ;
Penney, Kathryn L. ;
Freedman, Matthew L. ;
Kote-Jarai, Zsofia ;
Witte, John S. ;
Haiman, Christopher A. ;
Eeles, Rosalind A. ;
Zheng, Wei ;
Benlloch, Sara ;
Henderson, Brian E. ;
Conti, David, V ;
Schumacher, Fredrick R. ;
Easton, Douglas ;
Al Olama, Ali Amin ;
Muir, Kenneth ;
Berndt, Sonja, I ;
Chanock, Stephen ;
Albanes, Demetrius ;
Weinstein, Stephanie ;
Koutros, Stella ;
Wildund, Fredrik ;
Gronberg, Henrik ;
Gapstur, Susan M. ;
Stevens, Victoria L. ;
Tangen, Catherine M. ;
Batra, Jyotsna ;
Clements, Judith ;
Pashayan, Nora ;
Schleutker, Johanna ;
Wolk, Alicia ;
West, Catharine ;
Mucci, Lorelei ;
Cancel-Tassin, Geraldine ;
Sorensen, Karina Dalsgaard ;
Grindedal, Eli Marie ;
Neal, David E. ;
Hamdy, Freddie C. ;
Donovan, Jenny L. ;
Travis, Ruth C. ;
Hamilton, Robert J. .
CANCER RESEARCH, 2019, 79 (13) :3192-3204
[67]   Causal Inference in Transcriptome-Wide Association Studies with Invalid Instruments and GWAS Summary Data [J].
Xue, Haoran ;
Shen, Xiaotong ;
Pan, Wei .
JOURNAL OF THE AMERICAN STATISTICAL ASSOCIATION, 2023, 118 (543) :1525-1537
[68]   Associations between genetically predicted levels of blood metabolites and pancreatic cancer risk [J].
Zhong, Hua ;
Liu, Shuai ;
Zhu, Jingjing ;
Wu, Lang .
INTERNATIONAL JOURNAL OF CANCER, 2023, 153 (01) :103-110
[69]   Integration of summary data from GWAS and eQTL studies predicts complex trait gene targets [J].
Zhu, Zhihong ;
Zhang, Futao ;
Hu, Han ;
Bakshi, Andrew ;
Robinson, Matthew R. ;
Powell, Joseph E. ;
Montgomery, Grant W. ;
Goddard, Michael E. ;
Wray, Naomi R. ;
Visscher, Peter M. ;
Yang, Jian .
NATURE GENETICS, 2016, 48 (05) :481-+