Multiplex staining for CD4 CD8 CD28 CD68 MRP8 CD34 and Dapi for the identification of immune cells in COVID-19 human lungs



This set of images was used to analyse the immune environment in human COVID-19 lungs from autopsies in mid-2020 of patients with fatal COVID infection. All patients had antemortem PCR-confirmed SARS-CoV-2 infection and evidence of lower respiratory tract disease. Using these images and multiplex immunofluorescence we defined immune-cell populations (CD4, CD8 [T cells]; CD20 [B cells]; CD68 [macrophages]; MRP8 [neutrophils and myeloid lineage cells]) demonstrating MRP8 immunopositive mononuclear cells to be the predominant cell type) and quantified vasculitis by analysing arteries/arterioles from two selected patients. Formalin-fixed, paraffin-embedded (FFPE) tissue blocks were processed and hematoxylin and eosin–stained after a standardized process in the hospital diagnostic pathology laboratory. Slides were reviewed by a group of specialist histopathologists. For immunophenotyping, multiplex immunofluorescence on deparaffinized rehydrated FFPE slides was performed using combinations of primary antibodies against CD34, CD68, MRP8, CD4, CD8, and CD20, labeled with Tyramide Signal Amplification (TSA)-conjugated fluorophores, with antibody removal between steps and counterstained with DAPI. Images were captured using a Vectra Polaris slide scanner (Akoya Biosciences). Control tissue for immunophenotyping was histologically normal lung sampled from lung cancer–resection specimens. Uninflamed lung tissue distinct from the site of carcinoma was used for immunofluorescence. The images were scanned using a Vectra Polaris (Akoya) and MSI (multispectrum images .im3) captured at 20X resolution in selected areas of the biopsies for digital image analysis. The images were unmixed and analysed using InForm2.4 (Akoya) according to the attached algorithm. Unmixed images (multiTiff files labelled “component images” .tiff) using the same spectral library are also provided and can be analysed using other image analysis software. The image names are labelled as PatientCode-BlockCode-COV2_[x,y] Corresponding patient codes in the published manuscript (   are A for IC001 ; B for IC002 ; C for IC003 etc
Date made available12 Oct 2023
PublisherEdinburgh DataShare

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