-KAIST and UNIST Researchers Develop Shape-Morphing Device to Overcome Pancreatic Tumor Microenvironment Barriers

Conventional pancreatic cancer treatments face a critical hurdle due to the dense tumor microenvironment (TME). This biological barrier surrounds the tumor, severely limiting the infiltration of chemotherapy agents and immune cells. While photodynamic therapy (PDT) offers a promising alternative, existing external light sources, such as lasers, fail to penetrate deep tissues effectively and pose risks of thermal damage and inflammation to healthy organs

Researchers have reported initial findings from a public-private partnership between the ECOG-ACRIN Cancer Research Group and Caris Life Sciences to improve recurrence risk assessment in early-stage breast cancer using artificial intelligence (AI). They are pairing ECOG-ACRIN’s extensive clinical trial expertise and biorepository resources with Caris’ comprehensive MI Cancer Seek® whole exome and whole transcriptome profiling, whole slide imaging, and advanced machine learning platforms. New multimodal–multitask deep learning algorithms were trained on histopathologic imaging, clinical data, and molecular profiling data from over 4,000 patient cases in the biorepository of the groundbreaking TAILORx cancer clinical trial, one of the world’s largest such resources. Analyses of these AI-driven models demonstrated they were more effective than existing methods for assessing recurrence risk. This research highlights the potential of AI to support more personalized treatment decisions in early-stage breast cancer. Such a level of multimodal integration is unprecedented at this scale in the prognostication of early breast cancer.