Evaluation of associations between genetically predicted circulating protein biomarkers and breast cancer risk. Issue 8 (16th July 2019)

• Record Type: Journal Article
• Authors: Shu, Xiang; Bao, Jiandong; Wu, Lang; Long, Jirong; Shu, Xiao‐Ou; Guo, Xingyi; Yang, Yaohua; Michailidou, Kyriaki; Bolla, Manjeet K.; Wang, Qin; Dennis, Joe; Andrulis, Irene L.; Castelao, Jose E.; Dörk, Thilo; Gago‐Dominguez, Manuela; García‐Closas, Montserrat; Giles, Graham G.; Lophatananon, Artitaya; Muir, Kenneth; Olsson, Håkan; Rennert, Gadi; Saloustros, Emmanouil; Scott, Rodney J.; Southey, Melissa C.; Pharoah, Paul D.P.; Milne, Roger L.; Kraft, Peter; Simard, Jacques; Easton, Douglas F.; Zheng, Wei
• Is Part Of: International journal of cancer. Volume 146:Issue 8(2020)
• Page Start: 2130
• Page End: 2138
• Publication Date: 2019-07-16
• Subjects: breast cancer -- circulating protein biomarkers -- genetics -- instruments; Cancer -- Periodicals; Cancer -- Prevention -- Periodicals; 616.994
• DOI: 10.1002/ijc.32542
• Languages: English
• ISSNs: 0020-7136

Abstract

Abstract : 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 × 10 −4 –3.28 × 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. Abstract : What's new? Reliable biomarkers for breast cancer are critically needed, but results from existing studies have been inconsistent. Here the authors combined genomics and proteomics expertise and identified 56 circulating proteins, for which genetically predicted levels were associated with breast cancer risk. These proteins are involved in relevant biological processes such as estrogen receptor signaling and insulin resistance and will serve as candidates for further evaluative investigations.