Abstract
OBJECTIVES/GOALS: Reveal common immune mechanisms in dysregulated age-related lobular involution (ARLI) and post-partum lobular involution (PPLI) to understand their link to increased breast cancer risk, challenging the traditional view of their distinctiveness. Ultimately, to improve breast cancer risk assessment and personalized prevention METHODS/STUDY POPULATION: The Mayo Clinic Benign Breast Disease (BBD) cohort comprises of ~20,000 women with benign biopsies, including ~1000 women with sequential benign biopsies. Lobular involution (LI) status was assessed by selecting perimenopausal women, ages 45-55, with sequential biopsies, comparing acini number and lobule size between initial and subsequent biopsies. NanoString IO360/ BC360 RNA profiling identified differentially expressed genes associated with dysregulated LI. Using multiplex immunofluorescence (mIF), I'll analyze and spatially map immune biomarkers related to dysregulated ARLI and PPLI in BBD tissue from perimenopausal women who did or did not go on to develop breast cancer, assessing the commonality of ARLI and PPLI markers and exploring their potential as risk biomarkers for breast cancer. RESULTS/ANTICIPATED RESULTS: Preliminary findings link patients who display dysregulated ARLI with an increased breast cancer risk and identify vital PPLI biomarkers in perimenopausal women. I expect the biopsies of women who developed post-menopausal breast cancer (PMBC) and post-partum breast cancer (PPBC) to exhibit elevated levels of dysregulated ARLI immune biomarkers and PPLI biomarkers. Spatially mapping these markers promises to provide a more comprehensive understanding of their interactions, potentially revealing common immunological pathways. These findings could transform our current paradigm of ARLI and PPLI as distinct processes and demonstrate their interconnection in shaping breast cancer risk. DISCUSSION/SIGNIFICANCE: PMBC and PPBC dominate majority of breast cancer cases. Both involve activation of the understudied process of lobular involution, which has been shown to have pro-tumorigenic traits. Elucidating these mechanisms will aid more efficient risk stratification and personalized prevention to reduce incidence and mortality of breast cancer.
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