{"id":285192,"date":"2026-04-25T07:23:01","date_gmt":"2026-04-25T07:23:01","guid":{"rendered":"https:\/\/www.newsbeep.com\/us-ca\/285192\/"},"modified":"2026-04-25T07:23:01","modified_gmt":"2026-04-25T07:23:01","slug":"researchers-teach-ai-to-spot-cancer-risk-by-squeezing-individual-breast-cells","status":"publish","type":"post","link":"https:\/\/www.newsbeep.com\/us-ca\/285192\/","title":{"rendered":"Researchers teach AI to spot cancer risk by squeezing individual breast cells"},"content":{"rendered":"

UC Berkeley and City of Hope scientists discover that a cell’s mechanical age can effectively signal cancer risk<\/p>\n

April 23, 2026 by Ilima Loomis, City of Hope<\/p>\n

Researchers at UC Berkeley and City of Hope, a cancer research and treatment organization, have created a novel microfluidic platform that can assess women\u2019s breast cancer risk at the cellular level. \u00a0<\/p>\n

The first-of-its-kind platform squeezes individual breast epithelial cells, creating a taxing environment to measure how they deform,\u00a0recover\u00a0and behave under stress, according to a new study published today in Lancet\u2019s\u00a0eBioMedicine<\/a>.\u00a0\u00a0<\/p>\n

Because more than 90% of women lack a known genetic predisposition to or\u00a0a\u00a0family history of breast cancer, this innovative\u00a0approach could fill a critical gap in risk assessment\u00a0and\u00a0save countless lives.\u00a0\u00a0<\/p>\n

\"Side-by-side<\/p>\n

UC Berkeley\u2019s Lydia Sohn and City of Hope\u2019s Mark LaBarge developed an AI-based platform, MechanoAge, to detect breast cancer risk based on a cell\u2019s mechanical age. (Photo courtesy of Berkeley Engineering and City of Hope)<\/p>\n

\u201cFor women with a known genetic risk factor for breast cancer, there are things you can do, like follow a higher-risk screening protocol. For everybody else, you\u2019re left wondering, \u2018Am I at high risk?\u2019\u201d said\u00a0Mark LaBarge<\/a>, professor in the Department of Population Sciences at City of Hope. \u201cBy translating physical changes in cells into quantifiable data, this tool gives women something tangible to discuss with their doctors \u2014 not just risk estimates, but evidence drawn directly from their own cells.\u201d\u00a0<\/p>\n

Researchers from the two institutions developed a machine learning algorithm that identifies and measures cells that show signs of accelerated aging, quantifying an individual breast cancer risk score. Importantly, the AI platform, called MechanoAge, uses simple electronics that would be easy and affordable to replicate on a large scale.<\/p>\n

\u201cOur team isn\u2019t the first to measure the mechanical properties of cells; however, other approaches require advanced imaging technology that\u2019s expensive, cumbersome and has limited availability,\u201d\u00a0said\u00a0Lydia Sohn<\/a>, the Almy C. Maynard and Agnes Offield Maynard Chair in Mechanical Engineering at UC Berkeley. \u201cIn contrast, MechanoAge uses computer chips that are simpler than an Apple Watch and Radio Shack parts that are cheap and easy to assemble, potentially making the device highly scalable.\u201d\u00a0\u00a0<\/p>\n

About\u00a06% of women who develop breast cancer carry known genetic mutations. For women outside this group, risk is estimated indirectly based on population models or measurements like breast density. These\u00a0approaches can both overestimate and underestimate women\u2019s individual breast cancer risk, leading to over-screening, under-screening,\u00a0unnecessary\u00a0worry\u00a0or missed warning signs.\u00a0\u00a0<\/p>\n

Currently, there is no non-genetic test available that can identify women at higher risk for breast cancer. A downside to screening mammograms is that they catch cancer only once it has begun to grow. With the MechanoAge platform, researchers shifted the scientific lens to the cellular level, calculating risk by looking for physical changes in individual cells. \u00a0<\/p>\n

\"Mechanical<\/p>\n

Mechanical engineering professor Lydia Sohn holds a petri dish with several mechano-node-pore sensing devices. (Photo by Adam Lau\/Berkeley Engineering)<\/p>\n

Using the innovative platform, researchers uncovered an unexpected insight: breast cells appear to have a \u201cmechanical age,\u201d separate from a person\u2019s chronological age, demonstrated by how the cells physically respond to stress.\u00a0While\u00a0engineers\u00a0study the\u00a0aging of\u00a0materials such as\u00a0metals,\u00a0concrete\u00a0and polymers, this\u00a0is the first time\u00a0that\u00a0mechanical age\u00a0has been quantified in\u00a0biological cells. This fundamental scientific discovery\u00a0would not have been possible without\u00a0MechanoAge.\u00a0\u00a0\u00a0<\/p>\n

\u201cWe learned that the older the mechanical age, as determined by how cells respond to being squeezed through our microfluidic device, the higher the risk for breast cancer,\u201d Sohn said.\u00a0<\/p>\n

In\u00a0this type of\u00a0mechano-node-pore sensing,\u00a0an electrical current\u00a0is measured across a liquid-filled channel,\u00a0much like how\u00a0current is measured across a\u00a0wire.\u00a0As cells pass through, they disrupt the current, generating measurements about the cells\u2019 size and shape. By making parts of the channel very narrow, researchers squeeze cells, then measure how long it takes each cell to recover its normal shape.\u00a0\u00a0<\/p>\n

Machine learning algorithms developed by the researchers were then used to detect differences in cells from older and younger women. The researchers found that the physical properties of breast cells changed with age; cells from older women were stiffer and took longer to bounce back after being squeezed.\u00a0<\/p>\n

Then came a surprising finding: a subset of younger women had cells that behaved like they came from older women. These cells came from women with genetic mutations that put them at\u00a0high risk\u00a0of breast cancer.\u00a0\u00a0<\/p>\n

Researchers then refined the algorithm to assign a risk score based on all the mechanical and physical properties measured in the cells. This algorithm successfully identified women with known genetic risks. Next, the team used it to compare cells from healthy women, women who had a family history of breast cancer and cells taken from the healthy breast of women with breast cancer in the other breast.<\/p>\n

\u201cWith accuracy, we were able to figure out which women were at high risk of breast cancer and which women didn\u2019t seem to be,\u201d LaBarge said.<\/p>\n

This\u00a0work grew out of more than 12\u00a0years of\u00a0collaboration between the two labs, combining engineering innovation with cancer and aging biology. The\u00a0long-term partnership enabled discoveries\u00a0that\u00a0neither group could have reached alone.\u00a0<\/p>\n

\u201cIt\u2019s a true collaboration,\u201d said Sohn. \u201cWe\u2019ve learned a lot from each other.\u201d\u00a0<\/p>\n

\u201cIn my view, this is what happens when you have a real collaboration that develops over a long time,\u201d LaBarge added. \u201cThis result is not what we imagined at the beginning.\u201d \u00a0<\/p>\n

See related<\/p>\n","protected":false},"excerpt":{"rendered":"UC Berkeley and City of Hope scientists discover that a cell’s mechanical age can effectively signal cancer risk…\n","protected":false},"author":2,"featured_media":285193,"comment_status":"","ping_status":"","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[34],"tags":[143,145,144],"class_list":["post-285192","post","type-post","status-publish","format-standard","has-post-thumbnail","category-oakland","tag-oakland","tag-oakland-headlines","tag-oakland-news"],"_links":{"self":[{"href":"https:\/\/www.newsbeep.com\/us-ca\/wp-json\/wp\/v2\/posts\/285192","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/www.newsbeep.com\/us-ca\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/www.newsbeep.com\/us-ca\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/www.newsbeep.com\/us-ca\/wp-json\/wp\/v2\/users\/2"}],"replies":[{"embeddable":true,"href":"https:\/\/www.newsbeep.com\/us-ca\/wp-json\/wp\/v2\/comments?post=285192"}],"version-history":[{"count":0,"href":"https:\/\/www.newsbeep.com\/us-ca\/wp-json\/wp\/v2\/posts\/285192\/revisions"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/www.newsbeep.com\/us-ca\/wp-json\/wp\/v2\/media\/285193"}],"wp:attachment":[{"href":"https:\/\/www.newsbeep.com\/us-ca\/wp-json\/wp\/v2\/media?parent=285192"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/www.newsbeep.com\/us-ca\/wp-json\/wp\/v2\/categories?post=285192"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/www.newsbeep.com\/us-ca\/wp-json\/wp\/v2\/tags?post=285192"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}