<HashMap><database>biostudies-arrayexpress</database><scores/><additional><submitter/><organism>Homo sapiens</organism><full_dataset_link>https://www.ebi.ac.uk/biostudies/studies/E-MTAB-14549</full_dataset_link><description>Single-cell RNA sequencing of BM resident immune cells of patients undergoing CAR T-cell infusion and their Infusion Product (IP). Data in this study were generated from a patients enrolled in the FT01CARCIK Phase I/IIb clinical trial (NCT03389035) and two patients treated with autologous commercial CAR T cells (tisagenlecleucel). BM samples have been collected before CAR T treatment (pre) and at early time points (1-2 months) after treatment (post). CD45+CD3+ T cells, and CD45+/lowCD3-, encompassing the hematopoietic immune niche of the TME cells, have been separated by flow cytometry-based cell sorting and compared to cells of the corresponding patient’s BM before CAR T-cell treatment at the moment of relapse. In parallel, CAR T-cell infusion products (IP) have been sorted according to the surface CAR expression. Significance: This study highlights the critical role of the tumor microenvironment on CAR T-cell fate and endogenous immunity in B-cell acute lymphoblastic leukemia. We demonstrate that IFN response, hypoxia, and TGF-b signaling lead to general immune suppression, resulting in endogenous T-cell exhaustion and compromising CAR T-cell efficacy</description><repository>biostudies-arrayexpress</repository><sample_protocol>Sample Collection - Frozen human BM and Infusion Product (IP) cryotubes were rapidly thawed and stained with hCD45 PO (clone HI30, Invitrogen) and CD3 PerCP (clone SK7, BD) or with CD19 biotin protein (Miltenyi) followed by Biotin APC (REA746, Miltenyi) and CD3 PercP (clone SK7, BD) antibodies, respectively. BM cells were separated into CD45+CD3+ and CD45+CD3- fractions, whereas IP was separated into CD3+CAR+ and CD3+CAR- cells by flow cytometry-based sorting (BD FACS ARIA III analyser). All samples were gated based on physical parameters, followed by the exclusion of doublets and death cells (DAPI high). After sorting, cells were counted and checked for viability</sample_protocol><sample_protocol>Nucleic Acid Extraction - For each sample,cells were loaded in a 10x Genomics Chromium Next GEM Chip according to manusfacturer’s protocol</sample_protocol><sample_protocol>Library Construction - Libraries were constructed using 10x Genomics Chromium Next GEM Single Cell 5’ v1 kit</sample_protocol><sample_protocol>Sequencing - Sequecing was performed with NovaSeq S2 flowcell in 150 bp paired end</sample_protocol><figure_sub>MINSEQE Score</figure_sub><figure_sub>Assays and Data</figure_sub><figure_sub>Processed Data</figure_sub><figure_sub>organisation</figure_sub><figure_sub>MAGE-TAB Files</figure_sub><data_protocol>Data Transformation - Raw fastq.gz files were processed using cellranger software v3.1.0 from 10x Genomics with --include-introns and --nosecondary flags, setting --localcores=7 and --localmem=56. For the alignment, GRCh38 version of the human genome was emplyed with annotations taken from gencode v.32. Both reference genome and annotations were modified to include sequences from CAR constructs to allow quantification.</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>10x Genomics Chromium</instrument_platform><instrument_platform>Illumina NovaSeq 6000</instrument_platform><instrument_platform>BD FACS ARIA III analyser</instrument_platform><study_type>RNA-seq of coding RNA from single cells</study_type><species>Homo sapiens</species><additional_accession>ERP165349</additional_accession><pubmed_authors>Giuseppe Gaipa</pubmed_authors><pubmed_authors>Raoul Bonnal</pubmed_authors><pubmed_authors>Giulia Risca</pubmed_authors><pubmed_authors>Lorenzo Drufuca</pubmed_authors><pubmed_authors>Markus G. Manz</pubmed_authors><pubmed_authors>Massimiliano Pagani</pubmed_authors><pubmed_authors>Christian Pellegrino</pubmed_authors><pubmed_authors>Alessandro Rambaldi</pubmed_authors><pubmed_authors>Benedetta Rambaldi</pubmed_authors><pubmed_authors>Cristina Bugarin</pubmed_authors><pubmed_authors>Andrea Biondi</pubmed_authors><pubmed_authors>Silvia Ferrari</pubmed_authors><pubmed_authors>Silvia Nucera</pubmed_authors><pubmed_authors>Marco M. Sindoni</pubmed_authors><pubmed_authors>Cristian Meli</pubmed_authors><pubmed_authors>Chiara F. Magnani</pubmed_authors><pubmed_authors>Chiara Buracchi</pubmed_authors><pubmed_authors>Grazisa Rossetti</pubmed_authors><pubmed_authors>Federico Lussana</pubmed_authors><pubmed_authors>Stefania Galimberti</pubmed_authors><pubmed_authors>Alex Moretti</pubmed_authors><pubmed_authors>Marianna Ponzo</pubmed_authors><pubmed_authors>Giuseppe Dastoli</pubmed_authors><pubmed_authors>Ramona Bason</pubmed_authors></additional><is_claimable>false</is_claimable><name>Single cell RNA-seq analysis of bone marrow (BM) samples of patients with B-Cell Acute Lymphoblastic Leukemia treated with anti CD19 CAR T cells</name><description>Single-cell RNA sequencing of BM resident immune cells of patients undergoing CAR T-cell infusion and their Infusion Product (IP). Data in this study were generated from a patients enrolled in the FT01CARCIK Phase I/IIb clinical trial (NCT03389035) and two patients treated with autologous commercial CAR T cells (tisagenlecleucel). BM samples have been collected before CAR T treatment (pre) and at early time points (1-2 months) after treatment (post). CD45+CD3+ T cells, and CD45+/lowCD3-, encompassing the hematopoietic immune niche of the TME cells, have been separated by flow cytometry-based cell sorting and compared to cells of the corresponding patient’s BM before CAR T-cell treatment at the moment of relapse. In parallel, CAR T-cell infusion products (IP) have been sorted according to the surface CAR expression. Significance: This study highlights the critical role of the tumor microenvironment on CAR T-cell fate and endogenous immunity in B-cell acute lymphoblastic leukemia. We demonstrate that IFN response, hypoxia, and TGF-b signaling lead to general immune suppression, resulting in endogenous T-cell exhaustion and compromising CAR T-cell efficacy</description><dates><release>2025-12-31T00:00:00Z</release><modification>2025-12-31T02:02:48.52Z</modification><creation>2024-10-21T20:33:05.228Z</creation></dates><accession>E-MTAB-14549</accession><cross_references><ENA>ERP165349</ENA><EFO>EFO_0002944</EFO><EFO>EFO_0004170</EFO><EFO>EFO_0005684</EFO><EFO>EFO_0005518</EFO><EFO>EFO_0003816</EFO><EFO>EFO_0004184</EFO></cross_references></HashMap>