Cedars-Sinai Cancer investigators have used a unique precision medicine and artificial intelligence (AI) tool called the Molecular Twin Precision Oncology Platform to identify biomarkers that outperform the standard test for predicting pancreatic cancer survival.
Their study, published in the peer-reviewed journal Nature Cancer, demonstrates the viability of a tool that could one day guide and improve treatment for all cancer patients.
Investigators used the Molecular Twin platform to analyze blood and tissue samples from 74 patients with the most common and most aggressive pancreatic cancer type, pancreatic ductal adenocarcinoma. The disease begins in the cells lining ducts that carry digestive enzymes from the pancreas to the small intestine.
Investigators first combined 6,363 different biological data points, including genetic and molecular information, to create a model that accurately predicted disease survival in 87% of patients. The team then used AI to streamline the data and create a model that performed nearly as well with just 589 points of data. Zeroing in even further, investigators determined that proteins found in the blood were the best single predictor of pancreatic cancer survival.
The full and streamlined models, and the blood-protein test, outperformed the Food and Drug Administration-approved pancreatic cancer test, a blood test called CA 19-9. The findings were validated in independent datasets from The Cancer Genome Atlas, Massachusetts General Hospital and Johns Hopkins University.