Abstract 2340: Proteomic profiling of breast tissue: identifying protein associations with breast density in premenopausal women
Authors: Ghazaleh Pourali, Chao Li, Minsoo Son, Young Ah Goo, Graham A. Colditz, Xingyi Guo, Adetunji T. Toriola
Journal: Cancer Research (2025)

Abstract Introduction: Mammographic breast density (MBD) is a well-established risk factor for breast cancer. However, the underlying molecular pathways that lead to breast cancer development in women with dense breasts remain less understood. Proteomics is a robust method of understanding these mechanisms by directly analyzing the functional state of cells. However, data on tissue proteomics of premenopausal breast cancer is limited. To address this, we performed proteomic profiling of breast tissues from premenopausal women with breast cancer and examined the associations between protein expression and MBD. Methods: We performed proteomic profiling of adjacent normal breast tissues in 50 premenopausal women with breast cancer archived at St. Louis Breast Tumor Registry. Samples were analyzed with Orbitrap Eclipse Tribrid coupled with Vanquish Neo LC system (Thermo Fisher Scientific). Data were processed using MaxQuant (v2.5.0.0) with default settings. The Andromeda search engine scored MS2 spectra against tryptic peptides from the UniProt human reference proteome (20, 419 entries, release 2023/11). Label-free quantitation was used for relative protein quantification, with precursor mass tolerance set at 4.5 ppm and fragment ion mass tolerance at 20 ppm. A target-decoy approach was used to ensure a false discovery rate of &amp;lt;1%. We performed imputation and quantile normalization in the Perseus framework. We investigated associations of protein expression with MBD (dense vs. non-dense) using logistic regression models, adjusted for confounders. We corrected for multiple testing by the Benjamini-Hochberg procedure. Statistical analyses were conducted in R (v4.3.2). Results: Out of 3376 proteins, we identified 63 proteins positively associated with MBD, and 84 proteins inversely associated with MBD (adjusted-p &amp;lt;0.05). Top three proteins positively associated with MBD were MBD3 (β=3.49, SE=1.17; p=2.96×10−3), involved in chromatin remodeling, KAT7 (β=2.95, SE=1.07; p=5.75×10−3), a histone acetyltransferase that regulates gene expression, and ERBIN (β=3.54, SE=1.32; p=7.20×10−3), which interacts with ERBB2/HER2. Conversely, top three proteins inversely associated with MBD were GPX4 (β=-1.67, SE=0.58; p=4.12×10−3), an antioxidant enzyme, NDRG1 (β=-1.20, SE=0.42; p=4.31×10−3), involved in stress responses, and CDKN2A (β=-3.02, SE=1.10; p=6.12×10−3), a tumor suppressor that regulates the cell cycle by inhibiting cyclin-dependent kinases. Conclusions: Our findings reveal several proteins associated with MBD in premenopausal women, some of which are targets of approved drugs, highlighting the potential for targeting them in premenopausal breast cancer prevention. Larger studies are needed to validate these findings. Additionally, these proteins and their downstream pathways can be investigated in preclinical studies to confirm their translational potential. Citation Format: Ghazaleh Pourali, 1 Chao Li, 2 Minsoo Son, 1 Young Ah Goo, 1 Graham A. Colditz, 1 Xingyi Guo, 2 Adetunji T. Toriola1. Proteomic profiling of breast tissue: identifying protein associations with breast density in premenopausal women [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 2340.