Researchers identify potential breakthroughs in pancreatic cancer detection and treatment

New scientific studies have identified potential methods to improve the detection and treatment of pancreatic cancer, specifically targeting pancreatic ductal adenocarcinoma.

Researchers at Mayo Clinic utilized artificial intelligence to analyze abdominal CT scans from over 5,000 individuals. The study, published in Pancreatology, found that patients who later developed pancreatic cancer experienced a more pronounced loss of subcutaneous and visceral fat, as well as muscle mass, in the 36 months preceding their diagnosis. This pattern of body fat and muscle changes could potentially serve as an early indicator for clinicians.

Separately, scientists at Texas A&M University have discovered that two natural microRNA molecules, miR-15a and miR-16, may help slow tumor growth. In laboratory settings, increasing these molecules reduced the production of proteins necessary for cancer cell proliferation. While these findings offer hope for future clinical applications, researchers noted that significant further study is required before these methods can be used in human patients.