Combinatorial BCL-2 family expression in Acute Myeloid Leukemia Stem Cells predicts clinical response to Azacitidine/Venetoclax.
Alexander WaclawiczekAino-Maija LeppäSimon RendersKarolin StumpfCecilia ReyneriBarbara BetzMaike JanssenRabia ShahswarElisa DonatoDarja KarpovaVera ThielJulia M UnglaubSusanna GrabowskiStefanie GryzikLisa VierbaumRichard F SchlenkChristoph RölligMichael HundemerCaroline PabstMichael HeuserSimon RaffelCarsten Muller-TidowTim SauerFlavia Carla MeottiPublished in: Cancer discovery (2023)
The BCL-2 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 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 BCL-2, BCL-xL, and MCL-1 in LSCs. MAC-Scoring predicts initial response with a positive predictive-value of >97% associated to increased event-free survival. In summary, combinatorial levels of BCL-2-family members in AML-LSCs are a key denominator of response and MAC-Scoring reliably predicts patient response to 5-AZA/VEN.
Keyphrases
- acute myeloid leukemia
- stem cells
- allogeneic hematopoietic stem cell transplantation
- flow cytometry
- cell cycle arrest
- free survival
- cell death
- end stage renal disease
- chronic kidney disease
- case report
- newly diagnosed
- induced apoptosis
- ejection fraction
- cell therapy
- endoplasmic reticulum stress
- electronic health record
- prognostic factors
- big data
- single cell
- binding protein
- patient reported outcomes
- signaling pathway
- deep learning
- pi k akt
- artificial intelligence
- patient reported