{"database":"biostudies-arrayexpress","file_versions":[],"scores":null,"additional":{"submitter":["Aino-Maija Leppä"],"organism":["Homo sapiens"],"full_dataset_link":["https://www.ebi.ac.uk/biostudies/studies/E-MTAB-14142"],"description":["Acute myeloid leukemia (AML) is a highly heterogeneous disease consisting of different cell states that drive therapy resistance. We aimed to transcriptionally characterize AML subpopulations from patients treated with standard chemotherapy or BCL-2 inhibitor Venetoclax. We used CD64 and CD11b expression to define Mature blasts and labelled the rest as Immature. We used GPR56 expression to further enrich for LSC-like cells within the Immature cells. We performed RNA sequencing on 169 FACS-sorted LSC-like (GPR56+) and 111 Mature (CD64+CD11b+) cells."],"repository":["biostudies-arrayexpress"],"sample_protocol":["Sequencing - All RNA libraries were pooled and sequenced together on an Illumina NextSeq 550 high output sequencer (1.4 pM with 1% PhiX loading concentration, single-end 75bp read configuration).","Sample Collection - AML samples were collected from bone marrow (BM) and/or peripheral blood (PB) aspirations at the University hospital in Heidelberg or Hannover in accordance with the Declaration of Helsinki after obtaining written 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 (MNCs) were isolated by density gradient centrifugation using Ficoll Paque Plus (GE Healthcare, cat # GE17-1440-03), and stored in liquid nitrogen until further use.","Nucleic Acid Extraction - Primary AML cells were stained with cell-surface antibodies. Cells were sorted into populations according to CD11b, CD64, and GPR56 expression within the live lineage-negative gate. Cells from each population were sorted directly into RNA extraction buffer (Thermo Fisher, cat #KIT0214), snap-frozen, and stored at −80°C until RNA extraction. RNA extraction and purification of FACS-sorted cells was done using PicoPure RNA Isolation Kit according to manufacturer’s instructions (Thermo Fisher, cat # KIT0214).","Library Construction - Whole transcriptome amplification was performed using a modified Smart-Seq2 protocol (Picelli et al 2014), with 5μl of a modified RT buffer containing 1× SMART First Strand Buffer (Takara Bio Clontech, cat # 639538), 1 mM dithiothreitol (Takara Bio Clontech), 1 μM template switching oligo (IDT), 10 U μl−1 SMARTScribe (Takara Bio Clontech, cat # 639538) and 1 U μl−1 RNasin Plus RNase Inhibitor (Promega, cat # N2615). Tagmentation of cDNA was done using Nextera XT DNA Library Preparation Kit (Illumina, cat # FC-121-1030)."],"figure_sub":["Organization","MINSEQE Score","Assays and Data","Processed Data","MAGE-TAB Files"],"data_protocol":["Sequence Alignment - Reads were demultiplexed, and STAR aligner v. 2.5.3a was used to align FASTQ files containing reads for individual samples by two-pass alignment (Dobin et al (2013)). Reads were aligned to a STAR index generated from the 1000 Genomes Project human genomes assembly (hs37d5), using GENCODE v.19 gene models.  Sambamba v.0.6.5 was used for the alignment file sorting, duplicate marking and BAM index generation using eight threads (Tarasov et al (2015)). Quality control analysis was performed using the sambamba flagstat command and rnaseqc v.1.1.8 with the hs37d5 assembly and GENCODE v.19 gene models. Depth of Coverage analysis for rnaseqc was turned off.","Data Transformation - Gene-specific gene counting over exon features based on GENCODE v.19 gene models was performed using featureCounts v.1.5.1 (Liao et al (2015)). Quality threshold was set to 255 and strand-unspecific counting was used.  Uploaded data files contain the raw count matrix."],"omics_type":["Metabolomics","Unknown","Transcriptomics","Genomics","Proteomics"],"instrument_platform":["NextSeq 550"],"study_type":["RNA-seq of coding RNA"],"species":["Homo sapiens"],"pubmed_title":["Leukemic stem cell subtypes determine venetoclax resistance and therapeutic vulnerabilities in AML."],"pubmed_authors":["Aino-Maija Leppä","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."],"additional_accession":[]},"is_claimable":false,"name":"RNA-seq of LSC-like and Mature populations from human AML patient samples","description":"Acute myeloid leukemia (AML) is a highly heterogeneous disease consisting of different cell states that drive therapy resistance. We aimed to transcriptionally characterize AML subpopulations from patients treated with standard chemotherapy or BCL-2 inhibitor Venetoclax. We used CD64 and CD11b expression to define Mature blasts and labelled the rest as Immature. We used GPR56 expression to further enrich for LSC-like cells within the Immature cells. We performed RNA sequencing on 169 FACS-sorted LSC-like (GPR56+) and 111 Mature (CD64+CD11b+) cells.","dates":{"release":"2025-12-31T00:00:00Z","modification":"2026-06-08T14:06:18.608Z","creation":"2024-06-04T08:09:26.944Z"},"accession":"E-MTAB-14142","cross_references":{"pubmed":["publ-0-qpr4-removable"],"ENA":["ERP160831"],"Biostudies":["E-MTAB-11976"],"EFO":["EFO_0002944","EFO_0004170","EFO_0004917","EFO_0005518","EFO_0003816","EFO_0003738","EFO_0004184"],"doi":["10.1016/j.stem.2026.04.012"]}}