City of Hope and UC Berkeley Scientists Develop AI-Driven Platform to Assess Breast Cancer Risk via Cellular Mechanics Scientists at City of Hope and the University of California, Berkeley, have developed a groundbreaking microfluidic platform that uses artificial intelligence to assess breast cancer risk by analyzing the mechanical properties of single breast epithelial cells. The innovation, published in The Lancet’s eBioMedicine, introduces a novel method to evaluate cellular aging and stress resilience, offering a direct biophysical measure of cancer susceptibility. This technology marks a significant departure from traditional risk assessment tools, which have historically relied on genetic factors and indirect methods like mammographic breast density. The platform applies mechanical stress to individual cells by squeezing them through narrow microfluidic channels, mimicking biomechanical stressors. By measuring how quickly cells deform and recover their shape, researchers can quantify their "mechanical age"—a concept borrowed from material engineering that assesses wear and fatigue in metals and polymers. This approach reveals subtle differences in cellular behavior that correlate with heightened cancer risk, even in individuals without known genetic predispositions. For example, some younger women’s cells exhibited stiffness and prolonged recovery times, indicating advanced mechanical aging despite their chronological age. Traditional methods, such as genetic testing for mutations like BRCA1/BRCA2, account for only about 6% of breast cancer cases. For the remaining 94%, risk stratification has been imprecise, often leading to over-diagnosis or missed early warnings. The MechanoAge platform addresses this gap by providing a direct, cell-level assessment.#national_institutes_of_health #university_of_california_berkeley #city_of_hope #the_lancet_ebmedicine #mechanoage
