Abstract 2436: In-depth analysis of microRNA signature in breast cancer derived extracellular vesicles: A potential biomarker repository for breast cancer diagnosis

Abstract Breast cancer remains one of the leading causes of cancer-related mortality among women worldwide. With the rising incidence of breast cancer, early and accurate diagnosis is pivotal in improving survival rates and patient outcomes. Our study addresses to identify vesicles associated with breast cancer in scope of miRNA signature. We focused on isolating breast cancer-derived extracellular vesicles (BEVs) from the bloodstream with immune affinity capture techniques. Then, we analyzed the miRNA profiles of BEVs in plasma samples from 120 breast cancer patients, 46 individuals with benign tumors, and 45 healthy controls. In this study, we analyzed to discover miRNA candidates for diagnosis of breast cancer with The Gene Expression Omnibus (GEO) database and found 379 down-regulated and 584 up-regulated differentially expressed miRNAs (DEMs) in tissue samples across 5 GEO datasets, and 28 down-regulated and 80 up-regulated DEMS in blood samples. Subsequently, we measured the expression levels of these 10 candidate miRNAs in BEVs from breast cancer cells and compared them with EVs from human mammary cells (MCF10a), using our BEV isolation method. The expression profiles of these miRNAs in BEVs were significantly elevated, supporting their potential as surrogate markers for breast cancer diagnosis. When comparing the AUC values of 10 candidate miRNAs through ROC analysis, 5 EV miRNAs (miR-21, miR-106b, miR-181a, miR-484, and miR-1260b) showed a high AUC values above 0. 8. Subsequently, we verified a distinct signature of 5 EV miRNAs that effectively differentiate breast cancer patients from normal controls with 57. 14% of sensitivity and 95% of specificity. Overall, our study not only complements existing diagnostic methods with high accuracy but also provides a deeper understanding of the molecular aspects of breast cancer, heralding a significant advancement in precision medicine and personalized cancer care. Citation Format: Jee Ye Kim, Min Woo Kim, Young Kim, Sol Moon, Suji Lee, Hyojung Lee, Joon Ye Kim, Seung Il Kim. In-depth analysis of microRNA signature in breast cancer derived extracellular vesicles: A potential biomarker repository for breast cancer diagnosis 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 2436.