Evaluation of associations between genetically predicted circulating protein biomarkers and breast cancer risk

被引：15

作者：

Shu, Xiang ^{[1
]}

Bao, Jiandong ^{[1
]}

Wu, Lang ^{[1
]}

Long, Jirong ^{[1
]}

Shu, Xiao-Ou ^{[1
]}

Guo, Xingyi ^{[1
]}

Yang, Yaohua ^{[1
]}

Michailidou, Kyriaki ^{[2
,3
]}

Bolla, Manjeet K. ^{[2
]}

Wang, Qin ^{[2
]}

Dennis, Joe ^{[2
]}

Andrulis, Irene L. ^{[4
,5
]}

Castelao, Jose E. ^{[6
]}

Doerk, Thilo ^{[7
]}

Gago-Dominguez, Manuela ^{[8
,9
]}

Garcia-Closas, Montserrat ^{[10
]}

Giles, Graham G. ^{[11
,12
]}

Lophatananon, Artitaya ^{[13
,14
]}

Muir, Kenneth ^{[13
,14
]}

Olsson, Hakan ^{[15
]}

Rennert, Gadi ^{[16
,17
]}

Saloustros, Emmanouil ^{[18
]}

Scott, Rodney J. ^{[19
,20
]}

Southey, Melissa C. ^{[21
]}

Pharoah, Paul D. P. ^{[2
,22
]}

Milne, Roger L. ^{[11
,12
]}

Kraft, Peter ^{[23
,24
]}

Simard, Jacques ^{[25
]}

Easton, Douglas F. ^{[2
,22
]}

Zheng, Wei ^{[1
]}

机构：

[1] Vanderbilt Univ, Sch Med, Vanderbilt Ingram Canc Ctr, Div Epidemiol,Dept Med,Vanderbilt Epidemiol Ctr, Nashville, TN 37212 USA

[2] Univ Cambridge, Dept Publ Hlth & Primary Care, Ctr Canc Genet Epidemiol, Cambridge, England

[3] Cyprus Inst Neurol & Genet, Dept Electron Microscopy Mol Pathol, Nicosia, Cyprus

[4] Mt Sinai Hosp, Lunenfeld Tanenbaum Res Inst, Fred A Litwin Ctr Canc Genet, Toronto, ON, Canada

[5] Univ Toronto, Dept Mol Genet, Toronto, ON, Canada

[6] Xerencia Xest Integrada Vigo SERGAS, Inst Invest Biomed IBI Galicia Sur, Oncol & Genet Unit, Vigo, Spain

[7] Hannover Med Sch, Gynaecol Res Unit, Hannover, Germany

[8] Complejo Hosp Univ Santiago, Inst Invest Sanitaria Santiago Compostela IDIS, Galician Fdn Genom Med, Genom Med Grp,SERGAS, Santiago De Compostela, Spain

[9] Univ Calif San Diego, Moores Canc Ctr, La Jolla, CA 92093 USA

[10] NCI, Div Canc Epidemiol & Genet, Rockville, MD USA

[11] Canc Council Victoria, Canc Epidemiol & Intelligence Div, Melbourne, Vic, Australia

[12] Univ Melbourne, Melbourne Sch Populat & Global Hlth, Ctr Epidemiol & Biostat, Melbourne, Vic, Australia

[13] Univ Warwick, Warwick Med Sch, Div Hlth Sci, Coventry, W Midlands, England

[14] Univ Manchester, Inst Populat Hlth, Manchester, Lancs, England

[15] Lund Univ, Clin Sci, Dept Canc Epidemiol, Lund, Sweden

[16] Carmel Hosp, Clalit Natl Canc Control Ctr, Haifa, Israel

[17] Technion Fac Med, Haifa, Israel

[18] Univ Hosp Heraklion, Hereditary Canc Clin, Iraklion, Greece

[19] John Hunter Hosp, Pathol North, Div Mol Med, Newcastle, NSW, Australia

[20] Univ Newcastle, Fac Hlth, Sch Biomed Sci & Pharm, Discipline Med Genet, Callaghan, NSW, Australia

[21] Univ Melbourne, Dept Pathol, Melbourne, Vic, Australia

[22] Univ Cambridge, Dept Oncol, Ctr Canc Genet Epidemiol, Cambridge, England

[23] Harvard TH Chan Sch Publ Hlth, Program Genet Epidemiol & Stat Genet, Boston, MA USA

[24] Harvard TH Chan Sch Publ Hlth, Dept Epidemiol, Boston, MA USA

[25] Laval Univ, CHU Quebec, Res Ctr, Genom Ctr, Quebec City, PQ, Canada

来源：

INTERNATIONAL JOURNAL OF CANCER | 2020年 / 146卷 / 08期

基金：

美国国家卫生研究院; 加拿大健康研究院;

关键词：

breast cancer; circulating protein biomarkers; genetics; instruments; GENOME-WIDE ASSOCIATION; HEPATOCYTE GROWTH-FACTOR; C-REACTIVE PROTEIN; SUSCEPTIBILITY LOCI; SIGNATURES; ATLAS;

D O I：

10.1002/ijc.32542

中图分类号：

R73 [肿瘤学];

学科分类号：

100214 ;

摘要：

A small number of circulating proteins have been reported to be associated with breast cancer risk, with inconsistent results. Herein, we attempted to identify novel protein biomarkers for breast cancer via the integration of genomics and proteomics data. In the Breast Cancer Association Consortium (BCAC), with 122,977 cases and 105,974 controls of European descendants, we evaluated the associations of the genetically predicted concentrations of >1,400 circulating proteins with breast cancer risk. We used data from a large-scale protein quantitative trait loci (pQTL) analysis as our study instrument. Summary statistics for these pQTL variants related to breast cancer risk were obtained from the BCAC and used to estimate odds ratios (OR) for each protein using the inverse-variance weighted method. We identified 56 proteins significantly associated with breast cancer risk by instrumental analysis (false discovery rate <0.05). Of these, the concentrations of 32 were influenced by variants close to a breast cancer susceptibility locus (ABO, 9q34.2). Many of these proteins, such as insulin receptor, insulin-like growth factor receptor 1 and other membrane receptors (OR: 0.82-1.18, p values: 6.96 x 10(-4)-3.28 x 10(-8)), are linked to insulin resistance and estrogen receptor signaling pathways. Proteins identified at other loci include those involved in biological processes such as alcohol and lipid metabolism, proteolysis, apoptosis, immune regulation and cell motility and proliferation. Consistent associations were observed for 22 proteins in the UK Biobank data (p < 0.05). The study identifies potential novel biomarkers for breast cancer, but further investigation is needed to replicate our findings.

引用

页码：2130 / 2138

页数：9

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