DOI: 10.5061/dryad.pc866t1wz
title: Processed CODEX multiplexed imaging data of cellular microenvironment around T cell stimulating hydrogels

description: Our research used CODEX (Co-Detection by Indexing) multiplexed imaging to
 gain insights into the cellular microenvironment surrounding T cell
 stimulating hydrogels. These hydrogels were engineered with signals that
 could locally expand antigen-specific T cells for use in tumor
 immunotherapy. CODEX imaging involves an iterative process of annealing
 and stripping fluorophore-labeled oligonucleotide barcodes, complementing
 the barcodes attached to over 40 antibodies used for tissue staining.
 Subsequently, images underwent standard CODEX image processing (tile
 stitching, drift compensation, cycle concatenation, background
 subtraction, deconvolution, and determination of best focal plane), single
 cell segmentation, and column marker z-normalization by tissue. Our
 datasets comprise individual cells as rows, each characterized by 40+
 antibody fluorescence values quantified from various markers evaluated for
 each study. These markers correspond to the antibodies targeting specific
 proteins within the tissue, quantified at the single-cell level. The
 values represent per-cell/area-averaged fluorescent intensities,
 z-normalized along each column. Each cell is mapped with its cell type,
 defined by x and y coordinates representing pixel locations in the
 original image.  We then used this data to investigate how
 different proportions of the cell types change over time in response to
 the stimulating hydrogel injection with antigen-specific T cells. These
 data could be used to understand the cellular interactions, composition,
 and structure of T cell stimulating biomaterials for antigen-specific
 immunotherapy and with adoptive T cell transfer. These datasets offer
 valuable insights for researchers interested in engineering T cell
 stimulating microenvironments, immune responses, and therapeutic
 interventions such as T cell therapies. We investigate the dynamic
 interplay between immune responses, antigen-specific T cell interactions,
 and hydrogel environment in a murine melanoma model. We injected
 antigen-specific T cells with microparticle T cell stimulating hydrogels
 into mice subcutaneously. Injection sites were take out at different time
 points day=0 (just after injection), day=3, and day=9 (n=3-6 per time
 point). Our 51-plex CODEX antibody panel characterizes immune cell types,
 T cell phenotypes, and stromal cell types, resulting in a rich dataset of
 241,685 cells across 51 marker channels.
description: For a detailed description of each of the steps of
 protocols and processes to obtain this data see the detailed materials and
 methods in the associated manuscript. Briefly, murine injection sites were
 extracted from sacrificed mice at indicated timepoint post therapy and
 frozen in OCT. These were assembled into an array of 4-7 tissues, cut into
 7 um slices, and stained with a panel of 40+ CODEX DNA-oligonucleotide
 barcoded antibodies. Tissues were imaged with a Phenocycler Fusion imaging
 system from Akoya Biosciences and processed using manufacturer’s v1.6.0
 (e.g., background-subtracted, stitched, and shading correction).
 Processed data were then segmented using CellVisionSegmenter, a
 neural network R-CNN-based single-cell segmentation algorithm. Cell type
 analysis was completed by z normalization of protein markers used for
 clustering and then overclustered using leiden-based clustering. The cell
 type labels were verified by looking back at the original image.
description: # Processed CODEX Multiplexed Imaging Data of Cellular Microenvironment
 Around T Cell Stimulating Hydrogels
 Our research used CODEX
 (Co-Detection by Indexing) multiplexed imaging to gain insights into the
 microenvironment in and surrounding bioengineered hydrogels meant to
 stimulate antigen-specific T cell responses in situ. CODEX imaging
 involves an iterative process of annealing and stripping
 fluorophore-labeled oligonucleotide barcodes, complementing the barcodes
 attached to over 40 antibodies used for tissue staining. Subsequently,
 images underwent standard CODEX image processing (tile stitching, drift
 compensation, cycle concatenation, background subtraction, deconvolution,
 and determination of best focal plane), single cell segmentation, and
 column marker z-normalization by tissue. ## Description of the data and
 file structure Our datasets comprise individual cells as rows, each
 characterized by 40+ antibody fluorescence values quantified from various
 markers evaluated for each study. These markers correspond to the
 antibodies targeting specific proteins within the tissue, quantified at
 the single-cell level. The values represent per-cell/area-averaged
 fluorescent intensities, z-normalized along each column. Each of these
 antibodies are described in detail in the Supplementary Table of the
 manuscript. Each cell is mapped with its cell type and defined by x and y
 coordinates representing pixel locations in the original image. We then
 used this data investigate the major cellular organization of the hydrogel
 microenvironments we imaged, with downstream analysis of composition from
 various subgroups of cells. These data could be used to understand the
 cellular interactions, composition, and structure of responses induced by
 antigen-specific T cell stimulating hydrogels or biomaterials with
 adoptive T cell transfer. These datasets offer valuable insights for
 researchers interested in immunotherapies with both biomaterials and T
 cell therapies. **Filename: 20231127_Gels_CellTypeAnnotated.csv**\
 Hydrogel injection sites were harvested and imaged with CODEX imaging at
 0-, 3-, and 9-days post-T cell therapy (n=3-6 per time point). Our CODEX
 antibody panel characterizes immune cell types, T cell phenotypes, and
 stromal cell types, resulting in a rich dataset of 241,685 cells across
 marker channels. All other descriptive columns are described below: | x |
 Tissue x position in each region imaged | | :------------ |
 :------------------------------------------------------ | | y | Tissue y
 position in each region imaged | | array | Experiment group for each set
 of samples | | region\_array | Tissue array from which each region was
 imaged | | Xcorr | Corrected x position in each array imaged | | Ycorr |
 Corrected y position in each array imaged | | replicate | Which replicate
 of the treated mice the cells came from | | cell\_type | Cell type labels
 used for the paper analysis | | region | Number region from initial
 imaging data | | day | Day that the injection sites were taken from mice |
 | cell\_id | Original cell index from segmentation | ## Sharing/Access
 information N/A ## Code/Software N/A