Renowned molecular biologist Yunsun Nam, Ph.D., Professor in the Departments of Biochemistry and Biophysics and the Doris and Bryan Wildenthal Distinguished Chair in Medical Science at UT Southwestern Medical Center, is the recipient of the 2026 Edith and Peter O’Donnell Award in Biological Sciences from TAMEST. She was chosen for her groundbreaking research into how RNAs and proteins interact at the molecular level – providing key insights for gene regulation, cancer biology and RNA-based therapeutics.

Researchers from Okayama University and Tohoku University have discovered that targeting collagen signaling through the discoidin domain receptor 1 (DDR1) enhances drug delivery and reverses therapy-induced resistance in pancreatic cancer. Their study shows that DDR1 inhibition improves macromolecular drug penetration and mitigates fibrosis triggered by MEK inhibitors, offering new hope for more effective treatment strategies.

Colorectal cancer is considered a disease of old age, but young adults are increasingly affected. The research network “PerMiCCion”, led by Prof. Gianni Panagiotou at the Leibniz Institute for Natural Product Research and Infection Biology (Leibniz-HKI) and the University of Jena, is investigating why this is the case and what role the microbes in the gut play. The consortium, funded by the German Federal Ministry of Research, Technology and Space (BMFTR), is entering a second four-year funding phase. The project will receive a total of more than four million euros over eight years.

-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.