Abstract 1716: A proteome-wide association study identifies putative causal proteins for breast cancer

Abstract Background: Genome-wide association studies (GWAS) have identified over 200 breast cancer risk associated genetic loci, yet the causal genes and biological mechanisms for most loci remain elusive. Proteins, as final gene products, are pivotal in cellular function. In this study, we conducted a proteome-wide association study (PWAS) to identify proteins in breast tissue in relation to breast cancer risk. Methods: We profiled the proteome in breast tissue samples from 120 cancer-free European-ancestry women from the Susan G. Komen Tissue Bank. Protein expression levels were log2 transferred and then normalized via quantile and inverse-rank transformations. The elastic net method was used to build statistical models to predict protein expression levels via genetic variants. The prediction models were then applied to the GWAS summary statistics data of 133, 384 breast cancer cases and 113, 789 controls to assess the associations of genetically predicted protein expression levels with breast cancer risk overall and its sub-types using the S-PrediXcan method. Results: A total of 6, 388 proteins were detected in the normal breast tissue samples from 120 women with a high detection false discovery rate (FDR). Among the 5, 823 proteins detected in more than 80% of participants, prediction models were successfully built for 2, 041 proteins with R0. 1 and P0. 05. Among these 2, 041 proteins, six proteins were significantly associated with overall breast cancer risk at an FDR P 0. 05. Among these six proteins, the corresponding genes for proteins DCTN3 and DDX6 were located at least 500kb away from the GWAS-identified breast cancer risk variants. Both DCTN3 and DDX6 were associated with a decreased risk of breast cancer with P values of 8. 46 × 10−4 and 2. 27 × 10−4, respectively. The corresponding genes for the remaining four proteins, LMNA, LSP1, RPS6KA5, and DNAJA3, were located in previously GWAS-identified breast cancer risk loci. After adjusting for GWAS-identified risk variants, the associations for LMNA and RPS6KA5 were still significant (P=2. 54 × 10−7 and 2. 79 × 10−5, respectively), however, the associations for LSP1 and DNAJA3 became weaker with P values of 0. 65 and 2. 10 × 10−4 respectively. Stratification analyses by breast cancer subtypes identified three proteins, LMNA, LSP1, and NCKAP1L, associated with luminal A, luminal B, and ER-positive subtypes. NCKAP1L was located at least 500kb away from risk loci. After adjusting for GWAS-risk variants, the associations for LMNA were still significant (P=2. 58 × 10−5 and 4. 08 × 10−6 for luminal A and ER-positive respectively). Conclusion: We conducted the first breast-tissue-based PWAS and identified seven proteins associated with breast cancer, including six proteins that were not previously implicated. These findings help improve our understanding of the underlying genetic mechanism of breast cancer development. Citation Format: Tianying Zhao, Shuai Xu, Jie Ping, Guochong Jia, Yongchao Dou, Bing Zhang, Xingyi Guo, Qiuyin Cai, Xiao-Ou Shu, Wei Zheng, Jirong Long. A proteome-wide association study identifies putative causal proteins for breast cancer abstract. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts) ; 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84 (6Suppl): Abstract nr 1716.