دورية أكاديمية

Predicting treatment outcome using kinome activity profiling in HER2+ breast cancer biopsies

التفاصيل البيبلوغرافية
العنوان: Predicting treatment outcome using kinome activity profiling in HER2+ breast cancer biopsies
المؤلفون: Donna O. Debets, Erik L. de Graaf, Marte C. Liefaard, Gabe S. Sonke, Esther H. Lips, Anna Ressa, Maarten Altelaar
المصدر: iScience, Vol 27, Iss 6, Pp 109858- (2024)
بيانات النشر: Elsevier, 2024.
سنة النشر: 2024
المجموعة: LCC:Science
مصطلحات موضوعية: Oncology, molecular biology, cancer, proteomics, Science
الوصف: Summary: In this study, we measured the kinase activity profiles of 32 pre-treatment tumor biopsies of HER2-positive breast cancer patients. The aim of this study was to assess the prognostic potential of kinase activity levels, to identify potential mechanisms of resistance and to predict treatment success of HER2-targeted therapy combined with chemotherapy. Indeed, our system-wide kinase activity analysis allowed us to link kinase activity to treatment response. Overall, high kinase activity in the HER2-pathway was associated with good treatment outcome. We found eleven kinases differentially regulated between treatment outcome groups, including well-known players in therapy resistance, such as p38a, ERK, and FAK, and an unreported one, namely MARK1. Lastly, we defined an optimal signature of four kinases in a multiple logistic regression diagnostic test for prediction of treatment outcome (AUC = 0.926). This kinase signature showed high sensitivity and specificity, indicating its potential as predictive biomarker for treatment success of HER2-targeted therapy.
نوع الوثيقة: article
وصف الملف: electronic resource
اللغة: English
تدمد: 2589-0042
Relation: http://www.sciencedirect.com/science/article/pii/S2589004224010800; https://doaj.org/toc/2589-0042
DOI: 10.1016/j.isci.2024.109858
URL الوصول: https://doaj.org/article/bfdbc26b61c74528a8ee376a35d970f6
رقم الأكسشن: edsdoj.bfdbc26b61c74528a8ee376a35d970f6
قاعدة البيانات: Directory of Open Access Journals
الوصف
تدمد:25890042
DOI:10.1016/j.isci.2024.109858