A pilot study found that proteins on tiny vesicles shed into blood could pick out early pancreatic, ovarian and bladder cancers from people without cancer.
Hinestrosa and colleagues purified extracellular vesicles from plasma with an alternating current electrokinetics platform and built a machine-learning classifier on vesicle protein measurements. In a case-control pilot of 139 stage I and II pancreatic, ovarian or bladder cancers against 184 controls, the area under the curve was 0.95, with sensitivity 71.2% (63.2 to 78.1) at 99.5% specificity; stage I sensitivity was 70.5%, reaching 95.5% in pancreatic, 74.4% in ovarian and 43.8% in bladder cancer.
Proof of principle in three cancers from a small case-control set; it is not a screening result.
Shares Proteomics & phosphoproteomics, Bladder & urothelial cancer.
Shares Proteomics & phosphoproteomics, Multi-cancer early detection (MCED).
Shares Proteomics & phosphoproteomics, Multi-cancer early detection (MCED).
Shares Proteomics & phosphoproteomics, Multi-cancer early detection (MCED).
Shares Proteomics & phosphoproteomics, Multi-cancer early detection (MCED).
Shares Proteomics & phosphoproteomics, Multi-cancer early detection (MCED).
Shares Proteomics & phosphoproteomics, Multi-cancer early detection (MCED).
Shares Proteomics & phosphoproteomics, Multi-cancer early detection (MCED).
Every source this page cites, grouped by who published it. Grouping is read from the web address, not assigned by hand.
A source that has moved or gone is reported by the weekly link check. /audit/