Genetic signature in T cells could improve personalization of immunotherapy treatments

Considered to be one of the greatest revolutions in cancer treatment, immunotherapy enhances the immune system’s ability to target and destroy cancer cells efficiently. One of the key challenges in immunotherapy is the uncertainty regarding patients’ responses—not all patients respond to the treatment, and some may experience side effects without meaningful therapeutic gain. Therefore, there is a need to identify biomarkers that can predict treatment effectiveness based on individual patient data.
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A new computational framework illuminates the hidden ecology of diseased tissues

To understand what drives disease progression in tissues, scientists need more than just a snapshot of cells in isolation—they need to see where the cells are, how they interact, and how that spatial organization shifts across disease states. A computational method called MESA (Multiomics and Ecological Spatial Analysis), detailed in a study published in Nature Genetics, is helping researchers study diseased tissues in more meaningful ways.
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