Researchers from City of Hope®, one of the largest and most advanced cancer research and treatment organizations in the United States with its National Medical Center ranked among the nation’s top cancer centers by U.S. News & World Report, presented scientific results on novel therapies, treatment strategies, and approaches to managing side effects and complications for blood cancer patients at the 2025 American Society of Hematology (ASH) conference in Orlando, Florida, held Dec. 6 to 9.

Researchers and clinicians from the Icahn School of Medicine at Mount Sinai will present new discoveries in breast cancer biology, treatment, and real-world patient outcomes at the 2025 San Antonio Breast Cancer Symposium (SABCS), Tuesday-Friday, December 9-12, in San Antonio, Texas.  

A systematic review and meta-analysis evaluated the risk for obesity-related cancer associated with glucagon-like peptide-1 receptor agonists (GLP-1RAs) in patients with type 2 diabetes (T2D) or overweight or obesity.

A new decision framework developed by MIT researchers shows that, when patients with aggressive T-cell lymphoma relapse within 12 months of initial therapy, their chances for survival decline dramatically. This prognostic marker could help clinicians identify high-risk patients earlier.

New research on public attitudes toward AI indicates that most people are reluctant to let ChatGPT and other AI tools diagnose their health condition, but see promise in technologies that use AI to help diagnose cancer. These and other results of two nationally representative surveys will be presented at the annual meeting of the Society for Risk Analysis Dec. 7-10 in Washington, DC.

Measuring the lymphocytes (white blood cells that fight infection) in a patient’s blood can be used to predict outcomes in non-Hodgkin lymphoma patients who receive CAR T-cell therapy, according to research from physicians at Fox Chase Cancer Center and Temple Health. 

 While targeted radiation can be an effective treatment for brain tumours, subsequent potential necrosis of the treated areas can be hard to distinguish from the tumours on a standard MRI. A new study led by a York University professor in the Lassonde School of Engineering found that a novel AI-based method is better able to distinguish between the two types of lesions on advanced MRI than the human eye alone, a discovery that could help clinicians more accurately identify and treat the issues.