DOI: 10.5061/dryad.2z34tmprw
title: Imaging mass cytometry data from IDH wildtype glioblastomas

description: Myeloid cells are highly prevalent in glioblastoma (GBM), existing in a
 spectrum of phenotypic and activation states. We now have limited
 knowledge of the tumor microenvironment (TME) determinants that influence
 the localization and the functions of the diverse myeloid cell populations
 in GBM. In this dataset, we have used imaging mass cytometry to identify
 and map the various myeloid populations in the human GBM tumor
 microenvironment (TME) using known markers for myeloid and neoplastic
 cells in GBM. Our analyses of these data found that different myeloid
 populations had distinct and reproducible compartmentalization patterns in
 the GBM TME that were driven by tissue hypoxia and varied homotypic and
 heterotypic cellular interactions. This dataset consists of imaging mass
 cytometry data (16-bit TIFF images) for 8 glioblastomas and 1 tonsil
 sourced from the Salford Royal NHS Trust Biobank.
description: In brief, 5 um FFPE sections from 8 primary glioblastomas
 (see <em><strong>Cases.xls</strong></em>) and 1
 tonsil (as a control) were stained using the protocol recommended by
 Standard BioTools
 (https://www.standardbio.com/products/instruments/hyperion) using a panel
 of metal-conjugated antibodies. They were then imaged on the Hyperion
 using the standard settings. Regions of interest were identified on
 serial-cut H&E stained sections by a neuropathologist, targeting
 regions either in the tumor or infiltrating the edge of the tumor. Raw
 TIFF images were then extracted from MCD files, and denoised using the
 IMC-Denoise method (https://www.nature.com/articles/s41467-023-37123-6).
 Single-cell information for each of the channels was extracted using the
 Bodenmiller pipeline
 (https://github.com/BodenmillerGroup/ImcSegmentationPipeline), with the
 resulting cell table (see
 <em><strong>cell_table.csv</strong></em>)
 detailing the single-cell expression of each of the markers in the panel,
 along with their X and Y locations in the region of interest. Details of
 whether the regions of interest (ROI) came from either edge or core
 regions (as defined by histopathological features by a neuropathologist)
 are detailed in
 <em><strong>edge_core.csv</strong></em>.
description: # Imaging mass cytometry data from IDH wildtype glioblastomas --- ##
 Description of the data and file structure Denoised images are supplied as
 32-bit TIFF files, with individual files for each metal channel. Each
 pixel is 1 um^2, and pixel values correspond to the total counts for that
 metal in that pixel. The cell table (***cell_table.csv***) is the output
 of the Bodenmiller pipeline, in which each cell is one row, and the
 columns are either the mean marker expression for that channel, the
 cells' location (Location_Center_X, Location_Center_Y), the region
 name (ROI), or cell ID within that ROI (ObjectNumber). The details for the
 different regions can be found in the ROI tab of the ***Cases.xls*** file.
 Details of whether the regions of interest (ROI) came from either edge or
 core regions (as defined by histopathological features by a
 neuropathologist) are detailed in ***edge_core.csv***. ***Cases.xls*** -
 Information about the glioblastoma cases and regions of interest
 ***cell_table.csv*** - Single-cell data, with each row for one cell
 ***images.zip*** - Zipped and denoised IMC images, with each channel being
 an individual .tiff file, with each region of interest (ROI) having its
 own folder. ***edge_core.csv*** - Details of whether the regions of
 interest (ROI) came from either edge or core regions as defined by
 histopathological features by a neuropathologist. ## Sharing/Access
 information This data was generated by Michael Haley and Kevin Couper at
 the University of Manchester, please cite our publication if you use this
 data. ## Versions July 31 2024 - Added edge_core.csv