<HashMap><database>biostudies-arrayexpress</database><scores/><additional><submitter>Teresa Ruckenbrod</submitter><organism>Homo sapiens</organism><full_dataset_link>https://www.ebi.ac.uk/biostudies/studies/E-MTAB-15362</full_dataset_link><description>As pancreatic ductal adenocarcinoma (PDAC) is the deadliest solid cancer, and new immunological therapies have only marginally improved patient survival, we aimed at better understainding the immunological fingerprint of this disease. PDAC development involves inflammatory reprogramming and bacterial colonization, conditions that influence the adaptation of mucosa-associated invariant T cells (MAIT). We investigated MAIT signatures in patients with PDAC, chronic pancreatitis (CP), a risk factor for PDAC, and healthy donors (HD) using high-dimensional single-cell techniques, complemented by serum proteomics and multicolor histology. In our manuscript, we identify for the first-time human effector MAIT1 cells likely involved in protecting against PDAC. We characterize the transcriptional, phenotypic, and metabolic signatures of human MAIT1 compared to MAIT17-like cells, their adaptation to the PDAC inflammatory microenvironment, and provide insights into mechanisms underlying MAIT1-mediated protection against PDAC.</description><repository>biostudies-arrayexpress</repository><sample_protocol>Sample Collection - PBMCs were isolated from fresh whole blood by density gradient centrifugation (Pancoll 1.077 g/ml, PanBiotech) at 841g for 20 min with no brake. Cells were cryopreserved in liquid nitrogen and thawed in complete medium (RPMI 1640, 10% FCS, 1% Penicillin/Streptomycin; Sigma) on the day of use. On the day of the experiment frozen PBMC from HD (n=4) and PDAC patients (n=7) of our cohort were thawed, stained, and sorted for live CD45+CD3+CD8a+CD161+TCRVa7.2+ cells on a Cytek Aurora Cs 5L.</sample_protocol><sample_protocol>Nucleic Acid Extraction - About 6,500 viable single cells of the pooled samples were captured using the BD Rhapsody Legacy system.  Single-cell suspensions were prepared from human mucosa-associated invariant T cells and processed using the BD Rhapsody Express Single-Cell Analysis System (BD Biosciences) according to the manufacturer's instructions. Cells were loaded into the BD Rhapsody cartridge, where individual cells were captured and lysed. mRNA hybridized to barcoded beads within the microwells, enabling transcript capture without a separate RNA extraction step.</sample_protocol><sample_protocol>Sequencing - Libraries were sequenced with 100,000 reads per cell on a NovaSeq X Plus (Illumina) with paired-end 2x150 bp reads (Novogene).</sample_protocol><sample_protocol>Library Construction - Subsequently, sorted cells were used to prepare scRNA-Seq libraries using the BD Rhapsody system (BD Biosciences). First, sample tags were added to individual cell samples (BD Human Single Cell Sample Multiplexing Kit (Cat. No. 633781). Next, about 6,500 viable single cells of the pooled samples were captured using the BD Rhapsody Legacy system, followed by reverse transcription and cDNA amplification with the BD Rhapsody cDNA Kit (Cat. No. 633773). Sequencing libraries were constructed using the BD Rhapsody WTA Amplification Kit (Cat. No. 633801). QC analysis of libraries was performed with Bioanalyzer 2100 using the High Sensitivity DNA Kit (Agilent) and the Qubit 2.0 fluorometer with the Qubit 1X dsDNA HS Assay-Kit (Invitrogen).</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 - We used the BD Rhapsody Sequence Analysis Pipeline (v2.2.1) to assign reads to samples, cells, and genes using the reference archive RhapRef_Human_WTA_2023-02.tar.gz</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>BD Rhapsody</instrument_platform><instrument_platform>BD Rhapsody Sequence Analysis Pipeline</instrument_platform><instrument_platform>Illumina NovaSeq X</instrument_platform><instrument_platform>Aurora Cytek Cs 5L</instrument_platform><study_type>RNA-seq of coding RNA from single cells</study_type><species>Homo sapiens</species><pubmed_authors>Teresa Ruckenbrod</pubmed_authors></additional><is_claimable>false</is_claimable><name>scRNA-Seq of human MAIT cells sorted from PBMCs of pancreatic ductal adenocarcinoma patients and healthy controls</name><description>As pancreatic ductal adenocarcinoma (PDAC) is the deadliest solid cancer, and new immunological therapies have only marginally improved patient survival, we aimed at better understainding the immunological fingerprint of this disease. PDAC development involves inflammatory reprogramming and bacterial colonization, conditions that influence the adaptation of mucosa-associated invariant T cells (MAIT). We investigated MAIT signatures in patients with PDAC, chronic pancreatitis (CP), a risk factor for PDAC, and healthy donors (HD) using high-dimensional single-cell techniques, complemented by serum proteomics and multicolor histology. In our manuscript, we identify for the first-time human effector MAIT1 cells likely involved in protecting against PDAC. We characterize the transcriptional, phenotypic, and metabolic signatures of human MAIT1 compared to MAIT17-like cells, their adaptation to the PDAC inflammatory microenvironment, and provide insights into mechanisms underlying MAIT1-mediated protection against PDAC.</description><dates><release>2026-06-01T00:00:00Z</release><modification>2026-06-01T01:01:01.535Z</modification><creation>2025-07-14T13:46:09.867Z</creation></dates><accession>E-MTAB-15362</accession><cross_references><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>