Grant Number:	1R01CA316722-01 Interpret this number
Primary Investigator:	Berger, Kimberly
Organization:	Sequoia Foundation
Project Title:	The Pregnancy Exposome and Metabolome and Risk for Premenopausal Breast Cancer
Fiscal Year:	2026

Project Summary/Abstract Premenopausal breast cancer (PMBC), particularly when diagnosed postpartum, is increasing in incidence and is often more aggressive than breast cancer diagnosed later in life. Environmental chemical exposures may initiate or promote carcinogenesis in the breast and risk may be modified by endogenous metabolic pathways. Pregnant individuals are especially susceptible to effects of exogenous chemicals due to changes in substance metabolism, transport, and intake, which is critically important during hormone-induced breast differentiation and development. Pregnant people are exposed to a vast multiplicity of exogenous chemicals that may act synergistically on later disease risk, however little is known on how chemical exposures and metabolic responses during this critical window affect future PMBC risk. Research at the exposome scale, with the ability to comprehensively account for co-pollutant confounding and investigate expansive chemical mixtures, may reveal disease relationships undetectable in single-pollutant or lower-dimensional approaches. Biologic reactions to these chemical exposures, along with numerous endogenous processes that modulate breast cancer risk are encoded in metabolic pathways, which change substantially with both pregnancy and menopause. Metabolomic profiling may yield identification of early biologic signatures of PMBC risk as well as insight into underlying mechanisms and the potential development of predictive biomarkers during pregnancy. This study will be the first to jointly analyze the untargeted pregnancy exposome and metabolome in relation to future PMBC risk. Using prenatal serum specimens from an established, population-based case-cohort of over 3,000 women pregnant in 2003-2019 in California (including 1,283 PMBC cases), high-throughput, ultra-high resolution mass spectrometry and gas and liquid chromatography will quantify more than 600 environmental chemicals and over 1,000 metabolites per sample. Advanced bioinformatics tools such as high-dimensional mixture modeling, network analysis, and multiomics data integration techniques will be used to characterize exposure and metabolic profiles, identify single and multiomic patterns associated with PMBC risk, and uncover mechanistic pathways linking environmental exposures to PMBC development. By quantifying both the exposome and metabolome we can determine PMBC risk in relation to complex patterns of real-world environmental exposures; metabolic biomarkers of endogenous biological risk; and, crucially, patterns of cross-omics interaction. Subtype-specific analyses will focus on more aggressive forms of early breast cancer, such as triple negative tumors and diagnoses within five or ten years of delivery. By capturing complex interactions between exposures and metabolic responses during pregnancy, this study has the potential to transform understanding of early-life breast cancer risk and guide novel prevention efforts. Findings from this work will fill critical gaps in breast cancer etiology, identify modifiable risk factors and early biologic markers, and lay groundwork for prevention or screening strategies tailored to pregnancy and the postpartum period.





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