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• W4385667536 abstract "Background: In recent years, Venetoclax (VEN), a potent BCL2 inhibitor, in combination with 5-Azazythidin (5-AZA), has transformed treatment for Acute Myeloid Leukemia (AML) patients unfit for intensive induction chemotherapy. Comparable efficacy of 5-AZA/VEN combined with superior tolerability over standard chemotherapy demands for better biomarkers to select fit patients benefiting from 5-AZA/VEN as first line therapy. Aims: The aim of this study was to establish and benchmark a novel biomarker to enable personalized medicine in AML induction therapy. Methods: Here, we integrated transcriptomic and multi-colour flowcytometry with functional data on ex vivo drug treatment of cell lines or primary patient samples and subpopulation specific BH-3 profiling. These data, accompanied by in vivo analysis of xenograft mouse assays and clinical data are used to establish and benchmark a novel predictor of 5-AZA/VEN response. Results: In 54 patients treated with 5-AZA/VEN at Heidelberg University hospital we could not reproduce previously identified risk factors for AML therapy response like monocytic differentiation, although cultured monocytic AML cell lines displayed upfront resistance ex vivo. Additionally, published genomic predictors of response like IDH1/2-mutations or complex aberrant karyotype were not significant in multiple testing. Therefore, we assessed heterogeneous AML subpopulations, and identified leukemic stem cells (LSC) as primary targets of 5-AZA/VEN whose elimination in ex vivo assays determined therapy outcome. Importantly, LSC-like cells derived from both monocytic or primitive AML patients are the only population consistently engrafting in mice. LSC-like cells from monocytic or primitive AMLs are indistinguishable from one another based on RNA-sequencing, BCL2-family expression or apoptotic-dependency assessed by BH3-profiling. Meanwhile mature blasts from either monocytic or primitive samples are highly MCL1 dependent but fail to consistently induce AML in mice. Based on these results, we compared LSC-like cells from 5-AZA/VEN responders with refractory patients and identified perturbed apoptotic dependencies. By integrating these data, we developed and validated a intracellular flow cytometry-based “Mediators of Apoptosis Combinatorial-Score” (MAC-Score), combining BCL-2, BCL-xL and MCL-1 ratios in LSCs, predicting initial response with a positive predictive-value of >97%. Patients with above median MAC-Score had a 4-time increase in event-free survival. The score was validated in 2 independent cohort and also predicted response to 5-AZA/VEN as salvage therapy after failure of standard induction therapy, in total 72 patients were assessed. We next compared the accuracy of response prediction to BH-3 profiling and genetic predictors in the same patients and found MAC-Score to yield superior results. MAC-Scores correctly identified responders even within mutational subgroups like IDH1/2-mutated or complex aberrant karyotype patients. This score can be generated within hours, allowing immediate biomarker-based clinical decision making. Importantly, prediction failed when unselected bulk AML cells instead of LSC-like population was chosen as basis for MAC-Score, highlighting the importance of assessing resistance factors in the disease-driving population. Summary/Conclusion: In summary, combinatorial levels of BCL-2-family members in disease-propagating LSC-like cells are a key denominator of response to 5-AZA/VEN. MAC-Score allows an affordable, fast, translatable and versatile flow cytometry-based prediction to identify VEN/HMA-sensitive patients and provide personalized medicine in high-risk patients.Keywords: Acute myeloid leukemia, Venetoclax, Acute monoblastic leukemia" @default.
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• W4385667536 date "2023-08-01" @default.
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• W4385667536 title "P408: COMBINATORIAL BCL-2 FAMILY EXPRESSION IN ACUTE MYELOID LEUKEMIA STEM CELLS PREDICTS CLINICAL RESPONSE TO AZACITIDINE/VENETOCLAX" @default.
• W4385667536 doi "https://doi.org/10.1097/01.hs9.0000968540.33925.b8" @default.
• W4385667536 hasPublicationYear "2023" @default.
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