Abstract 2286: Integrating multi-ancestry genomic and proteomic data to identify blood risk biomarkers and target proteins for breast cancer genetic risk loci
Authors: Guochong Jia, Jie Ping, Ran Tao, Jirong Long, Lili Liu, Shuai Xu, Stefan Ambs, Mollie E. Barnard, Yu Chen, Ji-Yeob Choi, Yu-Tang Gao, Montserrat Garcia-Closas, Jian Gu, Jennifer J. Hu, Motoki Iwasaki, Esther M. John, Sun-Seog Kweon, Koichi Matsuda, Keitaro Matsuo, Katherine L. Nathanson, Barbara Nemesure, Olufunmilayo I. Olopade, Tuya Pal, Sue K. Park, Boyoung Park, Michael F. Press, Maureen Sanderson, Dale P. Sandler, Song Yao, Ying Zheng, Prisca O. Adejumo, Thomas Ahearn, Abenaa M. Brewster, Anselm J. Hennis, Hidemi Ito, Michiaki Kubo, Eun-Sook Lee, Siew-Kee Low, Timothy Makumbi, Paul Ndom, Dong-Young Noh, Katie M. O'Brien, Andrew F. Olshan, Mojisola M. Oluwasanu, Min-Ho Park, Sonya Reid, Taiki Yamaji, Gary Zirpoli, Ebonee N. Butler, Wei Zheng
Journal: Cancer Research (2025)

Abstract Genome-wide association studies (GWAS) have identified more than 200 risk loci for breast cancer. However, target genes and their encoded proteins in these loci remain largely unknown. In this study, we utilized genetic prediction models for 1, 350 circulating proteins derived from individuals of African (n= 1, 871) and European (n= 7, 213) ancestry to investigate genetically predicted protein levels in association with breast cancer risk among females of African (n=40, 138), Asian (n= 137, 677), and European (n=247, 173) ancestry. We identified 70 blood protein biomarkers associated with breast cancer risk, overall or by subtypes, at a false discovery rate (FDR) &amp;lt;0.05, including 37 proteins encoded by genes located at least 500kb away from any of the known risk loci identified in GWAS. Of the 33 proteins located at GWAS-identified risk loci, associations for 14 proteins were significantly attenuated after adjustment for the index risk variant of each respective locus, suggesting that these proteins may be target proteins for the risk loci. Encoding gene expression levels in normal breast tissue could be genetically predicted for 35 of the 70 identified proteins, and 17 encoding genes were associated with breast cancer risk in the same direction (P &amp;lt;0.05). Our study identified potential protein targets of GWAS risk loci and biomarkers for breast cancer risk and provided additional insights into breast cancer genetics and etiology. Citation Format: Guochong Jia, Jie Ping, Ran Tao, Jirong Long, Lili Liu, Shuai Xu, Stefan Ambs, Mollie E. Barnard, Yu Chen, Ji-Yeob Choi, Yu-Tang Gao, Montserrat Garcia-Closas, Jian Gu, Jennifer J. Hu, Motoki Iwasaki, Esther M. John, Sun-Seog Kweon, Koichi Matsuda, Keitaro Matsuo, Katherine L. Nathanson, Barbara Nemesure, Olufunmilayo I. Olopade, Tuya Pal, Sue K. Park, Boyoung Park, Michael F. Press, Maureen Sanderson, Dale P. Sandler, Song Yao, Ying Zheng, Prisca O. Adejumo, Thomas Ahearn, Abenaa M. Brewster, Anselm J. Hennis, Hidemi Ito, Michiaki Kubo, Eun-Sook Lee, Siew-Kee Low, Timothy Makumbi, Paul Ndom, Dong-Young Noh, Katie M. O'Brien, Andrew F. Olshan, Mojisola M. Oluwasanu, Min-Ho Park, Sonya Reid, Taiki Yamaji, Gary Zirpoli, Ebonee N. Butler, Wei Zheng. Integrating multi-ancestry genomic and proteomic data to identify blood risk biomarkers and target proteins for breast cancer genetic risk loci [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2025; Part 1 (Regular Abstracts); 2025 Apr 25-30; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2025;85(8_Suppl_1):Abstract nr 2286.