by Christos Evangelou, MSc, PhD – Medical Writer and Editor A collaborative effort involving universities and research institutes in China and Germany led to the development of a deep learning model trained on standard hematoxylin and eosin (H&E)-stained whole-slide images to predict tumor lactate metabolic status, a feature that is typically assessed using molecular profiling. The researchers validated the model across 13 cancer types and in an independent real-world cohort, and found that it accurately predicted tumor lactate metabolism from routine histology, providing a scalable and practical digital biomarker for metabolism-informed precision oncology.  The study was published in Frontiers in Immunology.    Study Rationale   Lactate, the end product of [...]