AI Technology Assesses Breast Cancer Risk Through Cellular Mechanics
Researchers at City of Hope and the University of California, Berkeley have developed a novel microfluidic platform, known as mechano-node-pore sensing (mechano-NPS), to assess breast cancer risk by analyzing the mechanical properties of human mammary epithelial cells. This platform measures how cells deform and recover when subjected to stress, providing a 'mechanical age' that correlates with breast cancer susceptibility. The study, published in eBioMedicine, highlights that cells from older women are stiffer and take longer to recover, indicating a higher risk of breast cancer. The researchers also developed a machine learning algorithm, MechanoAge, to estimate chronological age and a risk index, Mechano-RISQ, based on these mechanical properties.