Yang Jun, Hawthorne Lauren, Stack Sharon, Blagg Brian, Ali Aktar, Zorlutuna Pinar
Department of Chemical and Biomolecular Engineering, University of Notre Dame, Notre Dame, IN, 46556, USA.
Department of Aerospace and Mechanical Engineering, University of Notre Dame, Notre Dame, IN, 46556, USA.
bioRxiv. 2024 Oct 10:2024.10.06.616903. doi: 10.1101/2024.10.06.616903.
Aging is one of the most significant risk factors for breast cancer. With the growing interests in the alterations of the aging breast tissue microenvironment, it has been identified that aging is related to tumorigenesis, invasion, and drug resistance. However, current pre-clinical disease models often neglect the impact of aging and sometimes result in worse clinical outcomes. In this study, we utilized aged animal-generated materials to create and validate a novel age-mimetic breast cancer model that generates an aging microenvironment for cells and alters cells towards a phenotype found in the aged environment. Furthermore, we utilized the age-mimetic models for 3D breast cancer invasion assessment and high-throughput screening of over 700 drugs in the FDA-approved drug library. We identified 36 potential effective drug targets and 34 potential drug targets with different drug responses in different age groups, demonstrating the potential of this age-mimetic breast cancer model for further in-depth breast cancer studies and drug development.
衰老是乳腺癌最重要的风险因素之一。随着人们对衰老乳腺组织微环境改变的兴趣日益浓厚,已确定衰老与肿瘤发生、侵袭和耐药性有关。然而,目前的临床前疾病模型往往忽视衰老的影响,有时会导致更差的临床结果。在本研究中,我们利用老龄动物生成的材料创建并验证了一种新型的模拟衰老乳腺癌模型,该模型为细胞生成衰老微环境,并使细胞向衰老环境中发现的表型转变。此外,我们利用该模拟衰老模型进行三维乳腺癌侵袭评估以及对FDA批准的药物库中的700多种药物进行高通量筛选。我们确定了36个潜在的有效药物靶点以及在不同年龄组具有不同药物反应的34个潜在药物靶点,证明了这种模拟衰老乳腺癌模型在进一步深入开展乳腺癌研究和药物开发方面的潜力。