<HashMap><database>biostudies-arrayexpress</database><scores/><additional><submitter>Aino-Maija Leppä</submitter><organism>Homo sapiens</organism><full_dataset_link>https://www.ebi.ac.uk/biostudies/studies/E-MTAB-14143</full_dataset_link><description>Acute myeloid leukemia (AML) remains a cancer with dismal prognosis, particularly in high-risk disease patients and those ineligible for allogeneic stem cell transplantation. BCL-2 inhibitor venetoclax, in combination with hypomethylating agents, has emerged as an effective therapy and forms the backbone of multiple combination therapies in clinical trials. However, venetoclax-based therapy is rarely curative. While multiple venetoclax resistance mechanisms have been discovered, most of these have been identified using cell line models that only partially reflect the heterogeneous composition of human AML. Using paired single-cell data from 8 AML patients with pre- and post-venetoclax therapy samples, we aimed to characterize mechanisms driving venetoclax resistance in a clinically relevant setting.</description><repository>biostudies-arrayexpress</repository><sample_protocol>Nucleic Acid Extraction - Primary AML cells were stained with cell surface antibodies and sorted for live CD45+ cells in PBS/BSA. scRNA-seq library preparation was performed using the Chromium Single Cell 3’ Library and Gel Bead Kit (10X Genomics, cat # 1000128), according to manufacturer's instructions. Five to ten thousand cells were targeted for each sample, and processed according to the 10X Genomics Single Cell 3′ v3.1 protocol to generate the transcriptome libraries.</sample_protocol><sample_protocol>Sequencing - scRNA-seq libraries were pooled and sequenced on an Illumina NovaSeq 6000 (300pM with 1% PhiX loading concentration, 28+94 bp read configuration).</sample_protocol><sample_protocol>Library Construction - The standard 10x Genomics Chromium Single Cell 3’ (v.3.1 chemistry) protocols were carried out according to manufacturer’s recommendations for the generation of scRNA-seq libraries.</sample_protocol><sample_protocol>Sample Collection - AML samples were collected from diagnostic peripheral blood or bone marrow aspirations at the University Hospitals in Heidelberg or Hannover in accordance with the Declaration of Helsinki and based on institutional approvals after obtaining written informed consent from each patient. The project was approved by the Ethics Committee of the Medical Faculty of Heidelberg (S-169/2017 and S-648/2021) and the local Ethics Review Committee of Hannover Medical School (ethical vote No.7972_BO_K_2018). Mononuclear cells were isolated by density gradient centrifugation using Ficoll Paque Plus (GE Healthcare, cat #GE17-1440-03), and stored in liquid nitrogen until further use.</sample_protocol><figure_sub>Organization</figure_sub><figure_sub>MINSEQE Score</figure_sub><figure_sub>Assays and Data</figure_sub><figure_sub>Processed Data</figure_sub><figure_sub>MAGE-TAB Files</figure_sub><data_protocol>Data Transformation - The uploaded processed data contains the detected cell-associated barcodes in MEX format. For each feature, the feature ID and name are stored in the first and second column of the  features.tsv.gz file, respectively. The third column identifies the type of feature (Gene Expression). Barcode sequences are stored in the barcodes.tsv.gz file.</data_protocol><data_protocol>Sequence Alignment - Cell Ranger v.6.1.1 (10X Genomics) was used to align the sequencing reads to the GRCh38 human reference genome build, distinguish cells from the background, and generate a unified feature-barcode matrix that contains gene expression counts for each cell barcode.</data_protocol><omics_type>Metabolomics</omics_type><omics_type>Unknown</omics_type><omics_type>Transcriptomics</omics_type><omics_type>Genomics</omics_type><omics_type>Proteomics</omics_type><instrument_platform>Illumina NovaSeq 6000</instrument_platform><study_type>RNA-seq of coding RNA from single cells</study_type><species>Homo sapiens</species><pubmed_title>Leukemic stem cell subtypes determine venetoclax resistance and therapeutic vulnerabilities in AML.</pubmed_title><pubmed_authors>Aino-Maija Leppä</pubmed_authors><pubmed_authors>Waclawiczek A, Leppä AM, Renders S, Bergerweiss I, Stumpf K, Betz B, Gabrowski S, Huang FY, Lalioti ME, Hempel B, Sohn M, Kuusanmäki H, Thiel V, Unglaub JM, Shahswar R, Richter S, Janssen M, Karpova D, Donato E, Bonig H, Röllig C, Raffel S, Heuser M, Hundemer M, Kontro M, Eisfeld AK, Sauer T, Cabezas-Wallscheid N, Müller-Tidow C, Trumpp A.</pubmed_authors></additional><is_claimable>false</is_claimable><name>Paired single-cell RNA-seq pre- and post-venetoclax therapy of 8 AML patients</name><description>Acute myeloid leukemia (AML) remains a cancer with dismal prognosis, particularly in high-risk disease patients and those ineligible for allogeneic stem cell transplantation. BCL-2 inhibitor venetoclax, in combination with hypomethylating agents, has emerged as an effective therapy and forms the backbone of multiple combination therapies in clinical trials. However, venetoclax-based therapy is rarely curative. While multiple venetoclax resistance mechanisms have been discovered, most of these have been identified using cell line models that only partially reflect the heterogeneous composition of human AML. Using paired single-cell data from 8 AML patients with pre- and post-venetoclax therapy samples, we aimed to characterize mechanisms driving venetoclax resistance in a clinically relevant setting.</description><dates><release>2025-12-31T00:00:00Z</release><modification>2026-06-08T14:07:15.836Z</modification><creation>2024-06-04T11:38:22.635Z</creation></dates><accession>E-MTAB-14143</accession><cross_references><pubmed>publ-0-he9m-removable</pubmed><ENA>ERP160846</ENA><EFO>EFO_0002944</EFO><EFO>EFO_0004170</EFO><EFO>EFO_0005684</EFO><EFO>EFO_0004917</EFO><EFO>EFO_0005518</EFO><EFO>EFO_0003816</EFO><EFO>EFO_0004184</EFO><doi>10.1016/j.stem.2026.04.012</doi></cross_references></HashMap>