825 Deep immune profiling of SARS-CoV-2 associated immune microenvironment in cancer tissues from recovered COVID-19 patients

BackgroundPersistence of SARS-CoV-2 virus particles in recovered COVID-19 patients remains a challenge as we continue to fight the ongoing pandemic. For instance, despite three negative consecutive nasopharyngeal swab PCR tests, residual SARS-CoV-2 was reported in the lungs of a deceased patient.1 Moreover, viral RNA could also be detected in rectal tissues that were obtained during incubation period.2 To date, there is no data regarding residual viral particles present in tissues from recovered COVID-19 patients. Hereby, we reported our findings of SARS-CoV-2 viral antigen in liver tissues from a recovered COVID-19 patient. These findings raise concern for potential transmissibility in recovered individuals.MethodsA 49-year-old South Asian male diagnosed with COVID-19 in June 2020, with incidental discovery of hepatitis B virus (HBV)-associated R0 Grade 2 hepatocellular carcinoma (HCC), was consented for our study. He did not develop significant acute respiratory symptoms throughout the course of the disease. He underwent curative resection of HCC 85 days after being tested COVID-19 negative where his blood, normal tissue and tumour samples were obtained for further analysis (figure 1). We performed deep immunopathological profiling on the specimens using multiplex immunohistochemistry and 25-colour flow cytometry to study SARS-CoV-2-elicited immune response.ResultsMultiplex immunohistochemistry detected SARS-CoV-2 nucleocapsid protein only in adjacent normal liver tissue but not within tumour core (figure 2). We also observed SARS-CoV-2 in some immune cells such as sinusoidal Kupffer cells (figure 2). Additionally, upon stimulation with SARS-CoV-2 peptides, we successfully elicited SARS-CoV-2-specific memory response which is distinct from the response upon challenge with HBV peptides. These findings were similar to our previous discovery in a patient with colorectal adenocarcinoma where we have shown viral antigen detection, validated with PCR to detect viral RNA, as well as the detection of SARS-CoV-2 memory-like T cells in situ (figure 2). Deep profiling of the samples is on-going with single-cell analysis and digital spatial profiling.Abstract 825 Figure 1Study design, methodology and brief summary of the findingsBlood, normal tissue and tumour samples were obtained from a 49-year-old South Asian male who was diagnosed with COVID-19 and hepatocellular carcinoma. Normal tissue and tumour samples were analysed with multiplex immunohistochemistry, while dissociated cells from blood and tissue samples were subjected to SARS-CoV-2 peptide stimulation and analysed with 25-colour flow cytometry. Multiplex immunohistochemistry detected SARS-CoV-2 proteins in both tumour and adjacent normal tissues, while flow cytometry identified distinct immune microenvironment involving memory-like T cells.Abstract 825 Figure 2Immunohistochemical staining of the SARS-CoV-2 nucleocapsid protein and immune profiling with 25-colour flow cytometry in normal colon and liver tissue a, Liver tissues were immunostained with SARS-CoV-2 nucleocapsid protein (NP), nuclei were counterstained with haematoxylin. Positive SARS-CoV-2 nucleocapsid staining in benign hepatocytes and sinusoidal Kupffer cells. Scale bar represents 50μm. b, Multiplex immunohistochemistry of normal liver tissue. From left to right, top to bottom: SARS-CoV-2 nucleocapsid (green), SARS-CoV-2 nucleocapsid (green) with CD14 (red), SARS-CoV-2 nucleocapsid (green) with CD68 (pink) and composite. Co-localisation were observed as shown by the white arrows. Scale bar represents 100μm. c, Colon tissues were immunostained with SARS-CoV-2 nucleocapsid protein, nuclei were counterstained with haematoxylin. Positive SARS-CoV-2 nucleocapsid staining in colonic crypts, with granular supranuclear cytoplasmic pattern. Scale bar represents 50μm. d, Multiplex immunohistochemistry of colon tissue. From left to right, top to bottom: DAPI (blue), CD3 (magenta), CD38 (green), granzyme B (yellow), interferon-gamma (red) and composite. Co-localisation was observed as shown by the white arrows. Scale bar represents 100μm, Magnification x200. e, Flow cytometry immune profiling of blood from colorectal cancer patient with COVID-19 following stimulation with SARS-CoV-2 peptides. Highlighted populations showed CD3 cells expressing CD38, supporting the CD3+ CD38+ co-localization findings observed in (c).ConclusionsWe believe this is the first immune profiling report of the in situ tumour microenvironment in a cancer patient with COVID-19. Our findings demonstrated the presence of viral proteins in the liver despite negative swab test result and the ability to elicit ex vivo SARS-CoV-2-specific immune responses through peptide stimulation assays. We also detected same immune cell phenotypes in situ in the cancer tissues. Taken together, we propose caution when handling tissues from patients who have a recent history of COVID-19, particularly during aerosol-generating procedures such as ultrasonic dissection surgery.Ethics ApprovalThis study was approved by Centralised Institutional Review Board of SingHealth, approval number 2019/2653.ConsentWritten informed consent was obtained from the patient for publication of this abstract and any accompanying images. A copy of the written consent is available for review by the Editor of this journal.ReferencesYao XH, He ZC, Li TY, Zhang HR, Wang Y, Mou H, et al. Pathological evidence for residual SARS-CoV-2 in pulmonary tissues of a ready-for-discharge patient. Cell Res 2020;30(6):541-3.Qian Q, Fan L, Liu W, Li J, Yue J, Wang M, et al. Direct evidence of active SARS-CoV-2 replication in the intestine. Clin Infect Dis 2020.

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Glutathione and GSH-dependent enzymes in patients with liver cirrhosis and hepatocellular carcinoma.

Acta Biochimica Polonica ◽

10.18388/abp.2006_3384 ◽

2006 ◽

Vol 53 (1) ◽

pp. 237-241 ◽

Cited By ~ 61

Author(s):

Hanna Czeczot ◽

Dorota Scibior ◽

Michał Skrzycki ◽

Małgorzata Podsiad

Keyword(s):

Hepatocellular Carcinoma ◽

Liver Tissue ◽

Normal Liver ◽

Cancer Tissue ◽

Glutathione Level ◽

Normal Tissues ◽

Control Tissue ◽

Cirrhotic Tissue ◽

Cancer Tissues ◽

Gst Activity

We investigated glutathione level, activities of selenium independent GSH peroxidase, selenium dependent GSH peroxidase, GSH S-transferase, GSH reductase and the rate of lipid peroxidation expressed as the level of malondialdehyde in liver tissues obtained from patients diagnosed with cirrhosis or hepatocellular carcinoma. GSH level was found to be lower in malignant tissues compared to adjacent normal tissues and it was higher in cancer than in cirrhotic tissue. Non-Se-GSH-Px activity was lower in cancer tissue compared with adjacent normal liver or cirrhotic tissue, while Se-GSH-Px activity in cancer was found to be similar to its activity in cirrhotic tissue and lower compared to control tissue. An increase in GST activity was observed in cirrhotic tissue compared with cancer tissue, whereas the GST activity in cancer was lower than in adjacent normal tissue. The activity of GSH-R was similar in cirrhotic and cancer tissues, but higher in cancer tissue compared to control liver tissue. An increased level of MDA was found in cancer tissue in comparison with control tissue, besides its level was higher in cancer tissue than in cirrhotic tissue. Our results show that the antioxidant system of cirrhosis and hepatocellular carcinoma is severely impaired. This is associated with changes of glutathione level and activities of GSH-dependent enzymes in liver tissue. GSH and enzymes cooperating with it are important factors in the process of liver diseases development.

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On the Origin of Tetraploid Vernal Grasses (Anthoxanthum) in Europe

Genes ◽

10.3390/genes12070966 ◽

2021 ◽

Vol 12 (7) ◽

pp. 966

Author(s):

Zuzana Chumová ◽

Terezie Mandáková ◽

Pavel Trávníček

Keyword(s):

Flow Cytometry ◽

In Situ Hybridization ◽

Crucial Role ◽

Evolutionary History ◽

Essential Role ◽

Grass Species ◽

Polyploid Species ◽

Anthoxanthum Odoratum ◽

European Populations

Polyploidy has played a crucial role in the evolution of many plant taxa, namely in higher latitudinal zones. Surprisingly, after several decades of an intensive research on polyploids, there are still common polyploid species whose evolutionary history is virtually unknown. Here, we addressed the origin of sweet vernal grass (Anthoxanthum odoratum) using flow cytometry, DNA sequencing, and in situ hybridization-based cytogenetic techniques. An allotetraploid and polytopic origin of the species has been verified. The chromosome study reveals an extensive variation between the European populations. In contrast, an autopolyploid origin of the rarer tetraploid vernal grass species, A. alpinum, has been corroborated. Diploid A. alpinum played an essential role in the polyploidization of both European tetraploids studied.

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Multi-pronged approach to human mesenchymal stromal cells senescence quantification with a focus on label-free methods

Scientific Reports ◽

10.1038/s41598-020-79831-9 ◽

2021 ◽

Vol 11 (1) ◽

Author(s):

Weichao Zhai ◽

Jerome Tan ◽

Tobias Russell ◽

Sixun Chen ◽

Dennis McGonagle ◽

...

Keyword(s):

Flow Cytometry ◽

Mesenchymal Stromal Cells ◽

Stromal Cells ◽

Preclinical Model ◽

Label Free ◽

Current Standard ◽

Differentiation Potential ◽

Human Mesenchymal Stromal Cells ◽

Endogenous Fluorophores

AbstractHuman mesenchymal stromal cells (hMSCs) have demonstrated, in various preclinical settings, consistent ability in promoting tissue healing and improving outcomes in animal disease models. However, translation from the preclinical model into clinical practice has proven to be considerably more difficult. One key challenge being the inability to perform in situ assessment of the hMSCs in continuous culture, where the accumulation of the senescent cells impairs the culture’s viability, differentiation potential and ultimately leads to reduced therapeutic efficacies. Histochemical $$\upbeta $$ β -galactosidase staining is the current standard for measuring hMSC senescence, but this method is destructive and not label-free. In this study, we have investigated alternatives in quantification of hMSCs senescence, which included flow cytometry methods that are based on a combination of cell size measurements and fluorescence detection of SA-$$\upbeta $$ β -galactosidase activity using the fluorogenic substrate, C$${_{12}}$$ 12 FDG; and autofluorescence methods that measure fluorescence output from endogenous fluorophores including lipopigments. For identification of senescent cells in the hMSC batches produced, the non-destructive and label-free methods could be a better way forward as they involve minimum manipulations of the cells of interest, increasing the final output of the therapeutic-grade hMSC cultures. In this work, we have grown hMSC cultures over a period of 7 months and compared early and senescent hMSC passages using the advanced flow cytometry and autofluorescence methods, which were benchmarked with the current standard in $$\upbeta $$ β -galactosidase staining. Both the advanced methods demonstrated statistically significant values, (r = 0.76, p $$\le $$ ≤ 0.001 for the fluorogenic C$${_{12}}$$ 12 FDG method, and r = 0.72, p $$\le $$ ≤ 0.05 for the forward scatter method), and good fold difference ranges (1.120–4.436 for total autofluorescence mean and 1.082–6.362 for lipopigment autofluorescence mean) between early and senescent passage hMSCs. Our autofluroescence imaging and spectra decomposition platform offers additional benefit in label-free characterisation of senescent hMSC cells and could be further developed for adoption for future in situ cellular senescence evaluation by the cell manufacturers.

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Corrigendum to “Multicentre Harmonisation of a Six-Colour Flow Cytometry Panel for Naïve/Memory T Cell Immunomonitoring”

Journal of Immunology Research ◽

10.1155/2020/2698258 ◽

2020 ◽

Vol 2020 ◽

pp. 1-2

Author(s):

Iole Macchia ◽

Valentina La Sorsa ◽

Irene Ruspantini ◽

Massimo Sanchez ◽

Valentina Tirelli ◽

...

Keyword(s):

Flow Cytometry ◽

T Cell ◽

Memory T Cell ◽

Colour Flow

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Preliminary Study on In Situ Realtime Quantitation of Target Bacteria on the Principle of Flow Cytometry

Solid State Phenomena ◽

10.4028/www.scientific.net/ssp.262.224 ◽

2017 ◽

Vol 262 ◽

pp. 224-227

Author(s):

Gen Murakami ◽

Yuichi Sugai ◽

Kyuro Sasaki

Keyword(s):

Flow Cytometry ◽

Bacterial Culture ◽

Scattered Light ◽

Bacterial Suspension ◽

Culture Solution ◽

Bacterial Cells ◽

Monitoring Wells ◽

Measurement Principle ◽

Preliminary Study

In-situ realtime method that can monitor the target bacteria should be used to determine the real situation of the bacteria in deep parts of heaps in heap bioleaching plants. This study suggest to apply flow cytometry technology to in-situ realtime monitoring of target bacteria. Flow cytometry is a method that can rapidly quantify the bacterial cells in bacterial suspension based on the detection of lights that are emitted from bacterial cells. In this study, we estimated the possibility of the application of flow cytometry to the selective detection of target bacteria. The bacterial culture solution that had been diluted by water including other bacteria was provided for fluorescence spectral analysis and scattered light analysis that were functions of flow cytometry. Our target bacteria could be selectively detected by those analyses in this study, therefore, it was shown that the flow cytometry could be useful for detecting target bacteria selectively. Because the measurement principle of flow cytometry is quite simple, it can be expected to be installed into deep heaps through the monitoring wells and determine the dominance of target bacteria in-situ and realtime in the future.

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Telomere length analysis by fluorescence in situ hybridization and flow cytometry (Flow-FISH)/Telomerlängen-Messung mittels Fluoreszenz-in-situ-Hybridisierung und Durchflusszytometrie (Flow-FISH)

LaboratoriumsMedizin ◽

10.1515/labmed.2004.047 ◽

2004 ◽

Vol 28 (4) ◽

pp. 307-316

Author(s):

Ulrike Hartmann ◽

Fabian Beier ◽

Tim H. Brümmendorf

Keyword(s):

Flow Cytometry ◽

In Situ Hybridization ◽

Fluorescence In Situ Hybridization ◽

Telomere Length ◽

Length Analysis

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Digital dynamic discrimination of primary colorectal cancer using systemic indocyanine green with near-infrared endoscopy

Scientific Reports ◽

10.1038/s41598-021-90089-7 ◽

2021 ◽

Vol 11 (1) ◽

Author(s):

Jeffrey Dalli ◽

Eamon Loughman ◽

Niall Hardy ◽

Anwesha Sarkar ◽

Mohammad Faraz Khan ◽

...

Keyword(s):

Indocyanine Green ◽

Real Time ◽

Normal Tissue ◽

Near Infrared ◽

Malignant Lesion ◽

Fluorescence Analysis ◽

Video Tracking ◽

Continuous Stream ◽

Rich Data

AbstractAs indocyanine green (ICG) with near-infrared (NIR) endoscopy enhances real-time intraoperative tissue microperfusion appreciation, it may also dynamically reveal neoplasia distinctively from normal tissue especially with video software fluorescence analysis. Colorectal tumours of patients were imaged mucosally following ICG administration (0.25 mg/kg i.v.) using an endo-laparoscopic NIR system (PINPOINT Endoscopic Fluorescence System, Stryker) including immediate, continuous in situ visualization of rectal lesions transanally for up to 20 min. Spot and dynamic temporal fluorescence intensities (FI) were quantified using ImageJ (including videos at one frame/second, fps) and by a bespoke MATLAB® application that provided digitalized video tracking and signal logging at 30fps (Fluorescence Tracker App downloadable via MATLAB® file exchange). Statistical analysis of FI-time plots compared tumours (benign and malignant) against control during FI curve rise, peak and decline from apex. Early kinetic FI signal measurement delineated discriminative temporal signatures from tumours (n = 20, 9 cancers) offering rich data for analysis versus delayed spot measurement (n = 10 cancers). Malignant lesion dynamic curves peaked significantly later with a shallower gradient than normal tissue while benign lesions showed significantly greater and faster intensity drop from apex versus cancer. Automated tracker quantification efficiently expanded manual results and provided algorithmic KNN clustering. Photobleaching appeared clinically irrelevant. Analysis of a continuous stream of intraoperatively acquired early ICG fluorescence data can act as an in situ tumour-identifier with greater detail than later snapshot observation alone. Software quantification of such kinetic signatures may distinguish invasive from non-invasive neoplasia with potential for real-time in silico diagnosis.

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Discovering Digital Tumor Signatures—Using Latent Code Representations to Manipulate and Classify Liver Lesions

Cancers ◽

10.3390/cancers13133108 ◽

2021 ◽

Vol 13 (13) ◽

pp. 3108

Author(s):

Jens Kleesiek ◽

Benedikt Kersjes ◽

Kai Ueltzhöffer ◽

Jacob M. Murray ◽

Carsten Rother ◽

...

Keyword(s):

Unsupervised Learning ◽

Liver Tissue ◽

Synthetic Data ◽

Normal Liver ◽

Chance Level ◽

Ct Scans ◽

Liver Lesions ◽

Abdominal Ct ◽

Latent Representations ◽

Spatial Locations

Modern generative deep learning (DL) architectures allow for unsupervised learning of latent representations that can be exploited in several downstream tasks. Within the field of oncological medical imaging, we term these latent representations “digital tumor signatures” and hypothesize that they can be used, in analogy to radiomics features, to differentiate between lesions and normal liver tissue. Moreover, we conjecture that they can be used for the generation of synthetic data, specifically for the artificial insertion and removal of liver tumor lesions at user-defined spatial locations in CT images. Our approach utilizes an implicit autoencoder, an unsupervised model architecture that combines an autoencoder and two generative adversarial network (GAN)-like components. The model was trained on liver patches from 25 or 57 inhouse abdominal CT scans, depending on the experiment, demonstrating that only minimal data is required for synthetic image generation. The model was evaluated on a publicly available data set of 131 scans. We show that a PCA embedding of the latent representation captures the structure of the data, providing the foundation for the targeted insertion and removal of tumor lesions. To assess the quality of the synthetic images, we conducted two experiments with five radiologists. For experiment 1, only one rater and the ensemble-rater were marginally above the chance level in distinguishing real from synthetic data. For the second experiment, no rater was above the chance level. To illustrate that the “digital signatures” can also be used to differentiate lesion from normal tissue, we employed several machine learning methods. The best performing method, a LinearSVM, obtained 95% (97%) accuracy, 94% (95%) sensitivity, and 97% (99%) specificity, depending on if all data or only normal appearing patches were used for training of the implicit autoencoder. Overall, we demonstrate that the proposed unsupervised learning paradigm can be utilized for the removal and insertion of liver lesions at user defined spatial locations and that the digital signatures can be used to discriminate between lesions and normal liver tissue in abdominal CT scans.

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