MechanoAge Platform Assesses Breast Cancer Risk

Researchers at City of Hope and University of California, Berkeley have developed a novel microfluidic platform called MechanoAge, which uses a machine learning algorithm to assess women's breast cancer risk at the cellular level. The platform squeezes individual breast epithelial cells to measure their deformation and recovery under stress, revealing a 'mechanical age' that correlates with cancer risk. This innovative approach addresses a critical gap in risk assessment for the over 90% of women without known genetic predispositions or family history of breast cancer. The technology is designed to be affordable and scalable, potentially saving countless lives by identifying high-risk individuals earlier than current methods like mammograms. Key researchers Mark LaBarge and Lydia Sohn highlighted the 12-year collaboration that led to this discovery, which was published in The Lancet's eBioMedicine and supported by the United States — National Institutes of Health and the American Cancer Society.