Abstract PS1-06-20: Nipple Aspirate Cell-free DNA Methylation Signatures for Early Breast Cancer Detection

Abstract Background: Cell-free DNA (cfDNA), shed by malignant tumor cells into extracellular fluid, provides valuable epigenetic information indicative of cancer status. Nipple aspirate fluid (NAF), a noninvasive liquid biopsy from at-risk women, contains nucleic acid and protein biomarkers from adjacent cancer cells, showing promise for breast cancer (BrC) detection. However, despite its potential, the application of cfDNA in NAF for BrC screening is still underexplored. This study aims to assess the utility and sensitivity of NAF cfDNA methylation signatures as biomarkers for early detection and risk stratification of BrC. Methods: A low-input cfDNA bisulfite sequencing (cfBS) protocol was developed and optimized for profiling genome-wide DNA methylation at single-base resolution using nanogram-scale cfDNA from NAF. A total of 76 NAF samples (17 BrC and 59 benign) were sequenced and analyzed. An epithelial-mesenchymal transition (EMT) methylation scoring metric was developed to quantify tumor phenotype. CpG methylation regions were identified using an in-house mean shift-based machine learning algorithm. Differentially methylated regions (DMRs) were identified using one-way ANOVA stratified by clinical stage. Predictive modeling was performed using random forest, LASSO regression, and support vector machine (SVM) classifiers. Results: When comparing cancer versus benign samples, differentially methylated regions were significantly enriched for EMT-related pathways. EMT scores were significantly elevated in BrC samples (p 0.01) and positively correlated with clinical risk scores (R = 0.32, p = 0.0043). Validation in the Cancer Genome Atlas (TCGA-BRCA) cohort confirmed that methylation alterations in key EMT-related regions were strongly associated with corresponding changes in gene expression. One-way ANOVA identified 1,737 CpG regions with methylation levels significantly associated with increasing clinical risk. SVM-based predictive models using these methylation signatures achieved 90% accuracy in distinguishing BrC from benign cases, including early-stage tumors. These signatures consisted of 30 genes involved in the Gene Ontology biological process regulation of intracellular signal transduction. Conclusions: Our findings demonstrate that cfDNA methylation profiling from NAF is both technically feasible and biologically informative, offering a highly sensitive, noninvasive strategy for early BrC detection. By capturing EMT-associated epigenetic alterations, NAF cfBS has the potential to identify aggressive phenotypes at early stages. The high predictive accuracy achieved through machine learning models highlights its clinical utility as a complementary tool to existing screening modalities, especially for women with inconclusive mammograms, which is especially common in women with dense breast tissue. These results strongly support further validation in larger, prospective cohorts and suggest that NAF-based liquid biopsy could be integrated into personalized screening frameworks to improve early detection, reduce unnecessary biopsies, and guide preventative care. Financial Disclosures: The study is supported by the Texas A 2025 Dec 9-12; San Antonio, TX. Philadelphia (PA): AACR; Clin Cancer Res 2026;32(4 Suppl):Abstract nr PS1-06-20.