| Autor: |
Andreas Trumpp, Tim Sauer, Carsten Müller-Tidow, Simon Raffel, Michael Heuser, Caroline Pabst, Michael Hundemer, Christoph Röllig, Richard F. Schlenk, Lisa Vierbaum, Stefanie Gryzik, Susanna Grabowski, Julia M. Unglaub, Vera Thiel, Darja Karpova, Elisa Donato, Rabia Shahswar, Maike Janssen, Barbara Betz, Cecilia Reyneri, Karolin Stumpf, Simon Renders, Aino-Maija Leppä, Alexander Waclawiczek |
| Rok vydání: |
2023 |
| Popis: |
The BCL2 inhibitor venetoclax (VEN) in combination with azacitidine (5-AZA) is currently transforming acute myeloid leukemia (AML) therapy. However, there is a lack of clinically relevant biomarkers that predict response to 5-AZA/VEN. Here, we integrated transcriptomic, proteomic, functional, and clinical data to identify predictors of 5-AZA/VEN response. Although cultured monocytic AML cells displayed upfront resistance, monocytic differentiation was not clinically predictive in our patient cohort. We identified leukemic stem cells (LSC) as primary targets of 5-AZA/VEN whose elimination determined the therapy outcome. LSCs of 5-AZA/VEN-refractory patients displayed perturbed apoptotic dependencies. We developed and validated a flow cytometry-based “Mediators of apoptosis combinatorial score” (MAC-Score) linking the ratio of protein expression of BCL2, BCL-xL, and MCL1 in LSCs. MAC scoring predicts initial response with a positive predictive value of more than 97% associated with increased event-free survival. In summary, combinatorial levels of BCL2 family members in AML-LSCs are a key denominator of response, and MAC scoring reliably predicts patient response to 5-AZA/VEN.Significance:Venetoclax/azacitidine treatment has become an alternative to standard chemotherapy for patients with AML. However, prediction of response to treatment is hampered by the lack of clinically useful biomarkers. Here, we present easy-to-implement MAC scoring in LSCs as a novel strategy to predict treatment response and facilitate clinical decision-making. |
| Databáze: |
OpenAIRE |
| Externí odkaz: |
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