Biology subjects

Corwin, A.

Publications and source records attributed to Corwin, A..

3 recordsLinked to original sources

bioRxiv2025

An end-to-end framework for Cell DIVE multiplexed imaging and spatial immune microenvironment analysis

This paper describes an end-to-end workflow for highly multiplexed fluorescence imaging with the Cell DIVE platform, allowing simultaneous detection of 40+ markers at single-cell resolution. Combining whole-slide multiplexed imaging with a dedicated analysis pipeline provides a powerful approach to investigate immune cell interactions with stromal and vascular networks within human tissue microenvironments. With a focus on spatial investigation of human immune niches, here we provide a complete framework for tissue preparation, autofluorescence reduction, multiplex panel design and whole-slide image analysis. For complete details on the use and execution of this protocol, please refer to Korsunsky et al. (Med, 2022) [1]. HighlightsO_LIComplete workflow for Cell DIVE multiplex imaging and quantitative image analysis. C_LIO_LIHuman FFPE tissue preparation, LED-based reduction of tissue autofluorescence. C_LIO_LIAntibody panel design for 3-40 marker multiplexing, in-house antibody conjugation. C_LIO_LIQuPath and DeepCell based analysis workflows for whole-slide multi-marker images. C_LIO_LIAdaptable code templates to accelerate cell segmentation and spatial niche analysis. C_LI Graphical abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=113 SRC="FIGDIR/small/656440v1_ufig1.gif" ALT="Figure 1"> View larger version (42K): org.highwire.dtl.DTLVardef@1ef708dorg.highwire.dtl.DTLVardef@c6422dorg.highwire.dtl.DTLVardef@22d961org.highwire.dtl.DTLVardef@1ed7479_HPS_FORMAT_FIGEXP M_FIG C_FIG

immunology↗

bioRxiv2022

Human Digital Twin: Automated Cell Type Distance Computation and 3D Atlas Construction in Multiplexed Skin Biopsies

Mapping the human body at single cell resolution in three-dimensions (3D) is an important step toward a "digital twin" model that captures important structure and dynamics of cell-cell interactions. Current 3D imaging methods suffer from low resolution and are limited in their ability to distinguish cell types and their spatial relationships. We present a novel 3D workflow: MATRICS-A (Multiplexed Image Three-D Reconstruction and Integrated Cell Spatial - Analysis) that generates a 3D map of cells from multiplexed images and calculates cell type distance from endothelial cells and other features of interest. We applied this workflow to multiplexed data from sequential skin sections from younger and older donors (n=10; 33-72 years) with biopsies from ten anatomical regions with different sun exposure effects (mild, moderate-marked). Up to 26 sequential sections from each sample underwent multiplexed imaging with 18 biomarkers covering 12 cell types (keratinocytes (granular, spinous, basal), epithelial and myoepithelial cells, fibroblasts, macrophages, T helpers, T killers, T regs, neurons and endothelial cells, markers of DNA damage and repair (p53, DDB2) and cell proliferation (Ki67). Following cell classification, the tissue and classified cells were reconstructed into 3D volumes. A significant inverse correlation between DDB2 positive cells and age was found (corr= -0.78, adj. p=0.047). This suggests reduced capacity for repair in non-cancer older sun-exposed individuals. While absolute immune cell count did not differ by age or sun exposure, the ratio of T Helper/T Killer cells was positively correlated with age (corr=0.82, adj. p=0.048) This is the first such 3D study in skin and paves the way for cataloging more cell types and spatial relationships in aging and disease in skin and other organs.

cell biology↗

bioRxiv2021

Stratification Of Chemotherapy-Treated Stage III Colorectal Cancer Patients Using Multiplexed Imaging And Single Cell Analysis Of T Cell Populations

Colorectal cancer (CRC) has one of the highest cancer incidences and mortality rates. In stage III, postoperative chemotherapy benefits <20% of patients, while more than 50% will develop distant metastases. Predictive biomarkers for identification of patients with increased risk for disease recurrence are currently lacking, with progress in biomarker discovery hindered by the diseases inherent heterogeneity. The immune profile of colorectal tumors has previously been found to have prognostic value. The aims of this study were to evaluate immune signatures in the tumor microenvironment (TME) using an in situ multiplexed immunofluorescence imaging and single cell analysis technology (Cell DIVE). Tissue microarrays (TMAs) with up to three 1mm diameter cores per patient were prepared from 117 stage III CRC patients treated with adjuvant fluoropyrimidine/oxaliplatin chemotherapy. Single sections underwent multilplexed immunofluorescence with Cy3- and Cy5-conjugated antibodies for immune cell markers (CD45, CD3, CD4, CD8, FOXP3, PD1) and cell segmentation markers (DAPI, pan-cytokeratin, AE1, NaKATPase and S6). We applied a probabilistic multi-class, multi-label classification algorithm based on multi-parametric models to build statistical models of protein expression to classify immune cells. Expert annotations of immune cell markers were made on a range of images, and Support Vector Machines (SVM) were used to derive a statistical model for cell classification. Images were also manually scored independently by a Pathologist as high, moderate or low, for stromal and total immune cell content. Excellent agreement was found between manual and total automated scores (p<0.0001). Higher levels of multi-marker classified regulatory T cells (CD3+CD4+FOXP3+PD1-) were significantly associated with disease-free survival (DFS) and overall-survival (OS) (p=0.049 and 0.032), compared to FOXP3 alone. Our results also showed that PD1- Tregs rather than PD1+ Tregs were associated with improved survival. Overall, compared to single markers, multi-marker classification provided more accurate quantitation of immune cells with greater potential for predicting patient outcomes.

cancer biology↗