Single-cell, spatially resolved omics analysis of tissues is poised to transform biomedical research and clinical practice. We have developed an open-source, computational histology topography cytometry analysis toolbox (histoCAT) to enable interactive, quantitative, and comprehensive exploration of individual cell phenotypes, cell-cell interactions, microenvironments, and morphological structures within intact tissues. We highlight the unique abilities of histoCAT through analysis of highly multiplexed mass cytometry images of human breast cancer tissues.
Download full-text PDF |
Source |
|---|---|
| http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5617107 | PMC |
| http://dx.doi.org/10.1038/nmeth.4391 | DOI Listing |
Publication Analysis
Top Keywords
Similar Publications
Imaging Mass Cytometry Reveals Predominant Innate Immune Signature and Endothelial-Immune Cell Interaction in Juvenile Myositis Compared to Lupus Skin.
Arthritis Rheumatol
December 2022
Division of Rheumatology, Department of Internal Medicine, University of Michigan, Ann Arbor.
Objective: Cutaneous inflammation can signal disease in juvenile dermatomyositis (DM) and childhood-onset systemic lupus erythematosus (cSLE), but we do not fully understand cellular mechanisms of cutaneous inflammation. In this study, we used imaging mass cytometry to characterize cutaneous inflammatory cell populations and cell-cell interactions in juvenile DM as compared to cSLE.
Methods: We performed imaging mass cytometry analysis on skin biopsy samples from juvenile DM patients (n = 6) and cSLE patients (n = 4).
Highly multiplexed immunofluorescence images and single-cell data of immune markers in tonsil and lung cancer.
Sci Data
December 2019
Department of Pathology, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, United States.
In this data descriptor, we document a dataset of multiplexed immunofluorescence images and derived single-cell measurements of immune lineage and other markers in formaldehyde-fixed and paraffin-embedded (FFPE) human tonsil and lung cancer tissue. We used tissue cyclic immunofluorescence (t-CyCIF) to generate fluorescence images which we artifact corrected using the BaSiC tool, stitched and registered using the ASHLAR algorithm, and segmented using ilastik software and MATLAB. We extracted single-cell features from these images using HistoCAT software.
View Article and Find Full Text PDFMultidimensional profiling of drug-treated cells by Imaging Mass Cytometry.
FEBS Open Bio
September 2019
Proteomics R&D Department, Fluidigm Canada Inc., Markham, Canada.
In pharmaceutical research, high-content screening is an integral part of lead candidate development. Measuring drug response in vitro by examining over 40 parameters, including biomarkers, signaling molecules, cell morphological changes, proliferation indices, and toxicity in a single sample, could significantly enhance discovery of new therapeutics. As a proof of concept, we present here a workflow for multidimensional Imaging Mass Cytometry™ (IMC™) and data processing with open source computational tools.
View Article and Find Full Text PDFhistoCAT: analysis of cell phenotypes and interactions in multiplex image cytometry data.
Nat Methods
September 2017
Institute of Molecular Life Sciences, University of Zurich, Zurich, Switzerland.
Single-cell, spatially resolved omics analysis of tissues is poised to transform biomedical research and clinical practice. We have developed an open-source, computational histology topography cytometry analysis toolbox (histoCAT) to enable interactive, quantitative, and comprehensive exploration of individual cell phenotypes, cell-cell interactions, microenvironments, and morphological structures within intact tissues. We highlight the unique abilities of histoCAT through analysis of highly multiplexed mass cytometry images of human breast cancer tissues.
View Article and Find Full Text PDFWant AI Summaries of new PubMed Abstracts delivered to your In-box?
Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!