Metabolomics,Unknown,Transcriptomics,Genomics,Proteomics

Dataset Information

Spatially resolved transcriptomic profiling: an experimental comparison of GeoMx Digital Spatial Profiling and Visium CytAssist spatial transcriptomics in three cancer types (GeoMx)

ABSTRACT: We performed Visium CytAssist (10X), GeoMx DSP (Nanostring) and Chromium Flex (10X Genomics) full transcriptome profiling on Breast Cancer (BC), Lung Cancer (LC) and diffuse large B cell lymphoma (DLBCL) samples from archival FFPE blocks. We explore the data quality across blocks with different storage times and DV200 values for all the three methods. We compared the cell type signature purity between ST methods Visium and GeoMx by utilising pathology annotations and scRNAseq. For the Visium and Chromium methods with a large number of data points we explored the heterogeneity between tissues. Finally, we demonstrate the discovery of patient-specific tumor-TME interactions across all three methods.

INSTRUMENT(S): Illumina HiSeq 2000

ORGANISM(S): Homo sapiens

SUBMITTER: Senbai Kang

PROVIDER: E-MTAB-14566 | biostudies-arrayexpress |

REPOSITORIES: biostudies-arrayexpress

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Project description:A recently identified unconventional T cell population known as mucosal-associated invariant T (MAIT) cells are characterized by the expression of semi-invariant T cell receptor (TCR) with a canonical TRAV1-2/TRAJ33 (Vα7.2/Jα33). These evolutionary conserved, innate-like T cells recognize vitamin B metabolites, derived from some bacteria and fungi. Due to their presence not only in the T cell repertoire of mucosal surfaces but also in peripheral blood and liver, and their significant involvement in a wide range of diseases, in-depth characterization of human MAIT cells is a timely requirement. Studies that examined the transcriptome, immunoproteome, and whole-cell proteome characterized the role of cytotoxic molecules and cytokines in effector functions of MAIT cells and their relationship with some other immune cell subsets. As MAIT cells are classified under the CD3+ T cell compartment and the majority express surface receptor CD8, identifying their proteomic relationship with CD3+ and CD8+ T cells is pivotal. Thus, a high-resolution dataset was generated using the cell populations sorted from peripheral blood mononuclear cells of three healthy volunteers to describe the whole cell proteomes of MAIT, CD3+, and CD8+ T cells. Trypsin-digested peptide samples obtained from the methanol co-precipitation method were analyzed using an Orbitrap FusionTM TribridTM mass spectrometer (Thermo Fisher Scientific, USA) inline coupled to nanoACQUITY ultra-performance liquid chromatography system (Waters, USA) to acquire data-dependent shotgun proteomic data (DDA-MS) for label-free quantification. Analysis of raw DDA-MS data using MaxQuant software and maxLFQ identified and quantified 4,442 protein groups at a 1% false discovery rate. Further analysis identified 3,680 proteins which were detected with a single UniProt accession and a minimum of 2 unique or razor peptides. Thus this proteomic dataset can be used as a reference proteome for future studies on human MAIT cells.

Dataset Information

Spatially resolved transcriptomic profiling: an experimental comparison of GeoMx Digital Spatial Profiling and Visium CytAssist spatial transcriptomics in three cancer types (GeoMx)

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