This Study Aims to Improve the Stratification of Patients With Acute Myeloid Leukemia to Enable More Personalized and Effective Treatments, and to Identify and Functionally Validate, at the Single-cell Level, Biomarkers That Can Predict Response to Venetoclax.

The current classification of acute myeloid leukemias (AML) includes more than 20 different diseases, grouped based on their distinctive genomic characteristics, which reflect substantial heterogeneity. The rationale underlying this project is the idea that an effective diagnostic process and functional dissection of transcriptional heterogeneity at the single-cell level will lead to the identification of cell-intrinsic or cell-extrinsic biomarkers of response to novel therapies in order to improve patient care. In particular, with the study presented here, the investigators intend to obtain data relating to the sub-classification of patients into genomic subgroups with biological and prognostic relevance. Genomic subgroups are categories into which patients affected by the same disease can be divided based on the genetic characteristics found in each patient. The study foresees that par