Study identifies molecular drivers of drug resistance in HER2-positive breast cancer Multi-omics analysis reveals a nine-gene signature linked to treatment failure in aggressive tumor behavior. Written byAndrea Corona +++

https://www.drugdiscoverynews.com/study-identifies-molecular-drivers-of-drug-resistance-in-her2-positive-breast-cancer-16980?utm_campaign=DDN_Newsletter_Dose&utm_medium=email&_hsenc=p2ANqtz-_CpmESppmKro_OVr_yM8tT3e2ghrotBLtG8pzY6BDlyUfgEviAkt43phJLtcoe6MiQg57lofImSyh87ui7_Th0uUQhxw&_hsmi=422413512&utm_content=422413512&utm_source=hs_email Breast cancer is the most commonly diagnosed cancer worldwide, with more than 2.3 million new cases reported each year. Roughly 15 to 20 percent of those tumors overexpress HER2 (human epidermal growth factor receptor 2), a subtype historically associated with aggressive disease and poor outcomes. Although HER2-targeted therapies have transformed treatment over the past two decades, resistance remains common, particularly in later lines of therapy. Intratumoral therapy shows promise in treating metastatic breast cancer lesions Early clinical data suggest that intratumoral delivery may halt tumor activity and support bone regeneration in metastatic breast cancer. Written byBree Foster, PhD https://www.drugdiscoverynews.com/intratumoral-therapy-shows-promise-in-treating-metastatic-breast-cancer-lesions-16870?utm_campaign=DDN_Newsletter_Dose&utm_medium=email&_hsenc=p2ANqtz--osmSYLu7kXIecpvoAAdE1d4XhmDCsgURL32Z6I5b2uT_p_mEg28Kgm_2yzGESITriDqR1wMXxYlFWQqk5nxx3dl09nw&_hsmi=422413512&utm_content=422413512&utm_source=hs_email Metastatic cancer that spreads to the bone is one of the most painful and life-altering complications patients face. Lytic bone lesions weaken the skeleton, increase the risk of fractures, and often lead to severe pain and reduced mobility. Despite their prevalence, the current standard of care remains largely palliative, offering temporary symptom relief but no true repair of the underlying bone damage. Can better training data fix AI antibody design? The field has invested heavily in building better models for antibody discovery. The structural interaction data those models are trained on has not kept pace — and that shortfall is now a defining constraint on what AI can reliably do. Written byAndrea Corona https://www.drugdiscoverynews.com/can-better-training-data-fix-ai-antibody-design-17211 The last several years of progress in protein artificial intelligence (AI) have been undeniably impactful. AlphaFold's demonstration that protein folding could be predicted with near-experimental accuracy reset expectations across structural biology, and the models that followed, for protein design, interaction prediction, and sequence generation, have moved antibody discovery into a new computational era. And yet a practical problem persists, one that has become increasingly difficult to ignore. The antibody-antigen structural data those tools depend on is not keeping up with the demands being placed on it. The models built on that foundation perform well on the problems it covers. They struggle, often silently, on the problems it does not.