The Extra-Islet Pancreas Supports Autoimmunity in Human Type 1 Diabetes

In autoimmune Type 1 diabetes (T1D), immune cells progressively infiltrate and destroy the islets of Langerhans - islands of endocrine tissue dispersed throughout the pancreas. However, it is unclear how this process, called 'insulitis', develops and progresses within this organ. Here, using highly multiplexed CO-Detection by indEXing (CODEX) tissue imaging and cadaveric pancreas samples from pre-T1D, T1D, and non-T1D donors, we examine pseudotemporal-spatial patterns of insulitis and exocrine inflammation within large pancreatic tissue sections. We identify four sub-states of insulitis characterized by CD8 ⁺ T cells at different stages of activation. We further find that exocrine compartments of pancreatic lobules affected by insulitis have distinct cellularity, suggesting that extra-islet factors may make particular lobules permissive to disease. Finally, we identify "staging areas" - immature tertiary lymphoid structures away from islets where CD8 ⁺ T cells appear to assemble before they navigate to islets. Together, these data implicate the extra-islet pancreas in autoimmune insulitis, greatly expanding the boundaries of T1D pathogenesis.

A tissue atlas of ulcerative colitis revealing evidence of sex-dependent differences in disease-driving inflammatory cell types and resistance to TNF inhibitor therapy

Although literature suggests that resistance to TNF inhibitor (TNFi) therapy in patients with ulcerative colitis (UC) is partially linked to immune cell populations in the inflamed region, there is still substantial uncertainty underlying the relevant spatial context. Here, we used the highly multiplexed immunofluorescence imaging technology CODEX to create a publicly browsable tissue atlas of inflammation in 42 tissue regions from 29 patients with UC and 5 healthy individuals. We analyzed 52 biomarkers on 1,710,973 spatially resolved single cells to determine cell types, cell-cell contacts, and cellular neighborhoods. We observed that cellular functional states are associated with cellular neighborhoods. We further observed that a subset of inflammatory cell types and cellular neighborhoods are present in patients with UC with TNFi treatment, potentially indicating resistant niches. Last, we explored applying convolutional neural networks (CNNs) to our dataset with respect to patient clinical variables. We note concerns and offer guidelines for reporting CNN-based predictions in similar datasets.

Immunotherapy of glioblastoma explants induces interferon-γ responses and spatial immune cell rearrangements in tumor center, but not periphery

A patient-tailored, ex vivo drug response platform for glioblastoma (GBM) would facilitate therapy planning, provide insights into treatment-induced mechanisms in the immune tumor microenvironment (iTME), and enable the discovery of biomarkers of response. We cultured regionally annotated GBM explants in perfusion bioreactors to assess iTME responses to immunotherapy. Explants were treated with anti-CD47, anti-PD-1, or their combination, and analyzed by multiplexed microscopy [CO-Detection by indEXing (CODEX)], enabling the spatially resolved identification of >850,000 single cells, accompanied by explant secretome interrogation. Center and periphery explants differed in their cell type and soluble factor composition, and responses to immunotherapy. A subset of explants displayed increased interferon-γ levels, which correlated with shifts in immune cell composition within specified tissue compartments. Our study demonstrates that ex vivo immunotherapy of GBM explants enables an active antitumoral immune response within the tumor center and provides a framework for multidimensional personalized assessment of tumor response to immunotherapy.

Biochemical, biophysical, and immunological characterization of respiratory secretions in severe SARS-CoV-2 infections

Thick, viscous respiratory secretions are a major pathogenic feature of COVID-19, but the composition and physical properties of these secretions are poorly understood. We characterized the composition and rheological properties (i.e., resistance to flow) of respiratory secretions collected from intubated COVID-19 patients. We found the percentages of solids and protein content were greatly elevated in COVID-19 compared with heathy control samples and closely resembled levels seen in cystic fibrosis, a genetic disease known for thick, tenacious respiratory secretions. DNA and hyaluronan (HA) were major components of respiratory secretions in COVID-19 and were likewise abundant in cadaveric lung tissues from these patients. COVID-19 secretions exhibited heterogeneous rheological behaviors, with thicker samples showing increased sensitivity to DNase and hyaluronidase treatment. In histologic sections from these same patients, we observed increased accumulation of HA and the hyaladherin versican but reduced tumor necrosis factor-stimulated gene-6 staining, consistent with the inflammatory nature of these secretions. Finally, we observed diminished type I interferon and enhanced inflammatory cytokines in these secretions. Overall, our studies indicated that increases in HA and DNA in COVID-19 respiratory secretion samples correlated with enhanced inflammatory burden and suggested that DNA and HA may be viable therapeutic targets in COVID-19 infection.

Biochemical, Biophysical, and Immunological Characterization of Respiratory Secretions in Severe SARS-CoV-2 (COVID-19) Infections.. [PMID: 35411348 PMCID: PMC8996635 DOI: 10.1101/2022.03.28.22272848] [Citation(s) in RCA: 0] [Impact Index Per Article: 0]

Thick, viscous respiratory secretions are a major pathogenic feature of COVID-19 disease, but the composition and physical properties of these secretions are poorly understood. We characterized the composition and rheological properties (i.e. resistance to flow) of respiratory secretions collected from intubated COVID-19 patients. We find the percent solids and protein content are greatly elevated in COVID-19 compared to heathy control samples and closely resemble levels seen in cystic fibrosis, a genetic disease known for thick, tenacious respiratory secretions. DNA and hyaluronan (HA) are major components of respiratory secretions in COVID-19 and are likewise abundant in cadaveric lung tissues from these patients. COVID-19 secretions exhibit heterogeneous rheological behaviors with thicker samples showing increased sensitivity to DNase and hyaluronidase treatment. In histologic sections from these same patients, we observe increased accumulation of HA and the hyaladherin versican but reduced tumor necrosis factor–stimulated gene-6 (TSG6) staining, consistent with the inflammatory nature of these secretions. Finally, we observed diminished type I interferon and enhanced inflammatory cytokines in these secretions. Overall, our studies indicate that increases in HA and DNA in COVID-19 respiratory secretion samples correlate with enhanced inflammatory burden and suggest that DNA and HA may be viable therapeutic targets in COVID-19 infection.

CellSeg: a robust, pre-trained nucleus segmentation and pixel quantification software for highly multiplexed fluorescence images

BACKGROUND

Algorithmic cellular segmentation is an essential step for the quantitative analysis of highly multiplexed tissue images. Current segmentation pipelines often require manual dataset annotation and additional training, significant parameter tuning, or a sophisticated understanding of programming to adapt the software to the researcher's need. Here, we present CellSeg, an open-source, pre-trained nucleus segmentation and signal quantification software based on the Mask region-convolutional neural network (R-CNN) architecture. CellSeg is accessible to users with a wide range of programming skills.

RESULTS

CellSeg performs at the level of top segmentation algorithms in the 2018 Kaggle Data Challenge both qualitatively and quantitatively and generalizes well to a diverse set of multiplexed imaged cancer tissues compared to established state-of-the-art segmentation algorithms. Automated segmentation post-processing steps in the CellSeg pipeline improve the resolution of immune cell populations for downstream single-cell analysis. Finally, an application of CellSeg to a highly multiplexed colorectal cancer dataset acquired on the CO-Detection by indEXing (CODEX) platform demonstrates that CellSeg can be integrated into a multiplexed tissue imaging pipeline and lead to accurate identification of validated cell populations.

CONCLUSION

CellSeg is a robust cell segmentation software for analyzing highly multiplexed tissue images, accessible to biology researchers of any programming skill level.

Tissue schematics map the specialization of immune tissue motifs and their appropriation by tumors

A schematic of a biological system, i.e., a representation of its pieces, how they are combined, and what they do, would facilitate understanding its essential organization and alteration in pathogenesis or evolution. We present a computational approach for constructing tissue schematics (TSs) from high-parameter imaging data and a biological model for interpreting them. TSs map the spatial assembly of cellular neighborhoods into tissue motifs, whose modular composition, we propose, enables the generation of complex outputs. We developed our approach in human lymphoid tissue (HLT), identifying the follicular outer zone as a potential relay between neighboring zones and a core lymphoid assembly with modifications characteristic of each HLT type. Applying the TS approach to the tumor microenvironment in human colorectal cancer identified a higher-order motif, whose mutated assembly was negatively associated with patient survival. TSs may therefore elucidate how immune architectures can be specialized and become vulnerable to reprogramming by tumors.

Highly multiplexed tissue imaging using repeated oligonucleotide exchange reaction

Multiparameter tissue imaging enables analysis of cell-cell interactions in situ, the cellular basis for tissue structure, and novel cell types that are spatially restricted, giving clues to biological mechanisms behind tissue homeostasis and disease. Here, we streamlined and simplified the multiplexed imaging method CO-Detection by indEXing (CODEX) by validating 58 unique oligonucleotide barcodes that can be conjugated to antibodies. We showed that barcoded antibodies retained their specificity for staining cognate targets in human tissue. Antibodies were visualized one at a time by adding a fluorescently labeled oligonucleotide complementary to oligonucleotide barcode, imaging, stripping, and repeating this cycle. With this we developed a panel of 46 antibodies that was used to stain five human lymphoid tissues: three tonsils, a spleen, and a LN. To analyze the data produced, an image processing and analysis pipeline was developed that enabled single-cell analysis on the data, including unsupervised clustering, that revealed 31 cell types across all tissues. We compared cell-type compositions within and directly surrounding follicles from the different lymphoid organs and evaluated cell-cell density correlations. This sequential oligonucleotide exchange technique enables a facile imaging of tissues that leverages pre-existing imaging infrastructure to decrease the barriers to broad use of multiplexed imaging.

Hyaluronan synthesis inhibition impairs antigen presentation and delays transplantation rejection

A coat of pericellular hyaluronan surrounds mature dendritic cells (DC) and contributes to cell-cell interactions. We asked whether 4-methylumbelliferone (4MU), an oral inhibitor of HA synthesis, could inhibit antigen presentation. We find that 4MU treatment reduces pericellular hyaluronan, destabilizes interactions between DC and T-cells, and prevents T-cell proliferation in vitro and in vivo. These effects were observed only when 4MU was added prior to initial antigen presentation but not later, consistent with 4MU-mediated inhibition of de novo antigenic responses. Building on these findings, we find that 4MU delays rejection of allogeneic pancreatic islet transplant and allogeneic cardiac transplants in mice and suppresses allogeneic T-cell activation in human mixed lymphocyte reactions. We conclude that 4MU, an approved drug, may have benefit as an adjunctive agent to delay transplantation rejection.

Coordinated Cellular Neighborhoods Orchestrate Antitumoral Immunity at the Colorectal Cancer Invasive Front

Antitumoral immunity requires organized, spatially nuanced interactions between components of the immune tumor microenvironment (iTME). Understanding this coordinated behavior in effective versus ineffective tumor control will advance immunotherapies. We re-engineered co-detection by indexing (CODEX) for paraffin-embedded tissue microarrays, enabling simultaneous profiling of 140 tissue regions from 35 advanced-stage colorectal cancer (CRC) patients with 56 protein markers. We identified nine conserved, distinct cellular neighborhoods (CNs)-a collection of components characteristic of the CRC iTME. Enrichment of PD-1+CD4+ T cells only within a granulocyte CN positively correlated with survival in a high-risk patient subset. Coupling of tumor and immune CNs, fragmentation of T cell and macrophage CNs, and disruption of inter-CN communication was associated with inferior outcomes. This study provides a framework for interrogating how complex biological processes, such as antitumoral immunity, occur through concerted actions of cells and spatial domains.

Abstract 6669: Cellular neighborhoods predict pembrolizumab response in cutaneous T cell lymphoma

Cutaneous T-cell lymphoma (CTCL) is a rare, incurable CD4+ T cell malignancy of the skin with a 5-year survival rate of less than 30% in advanced stages. Immune checkpoint inhibitors, such as anti-PD-1 antibodies, have shown dramatic clinical efficacy in multiple advanced cancers, but the majority of cancer patients do not respond to these treatments. The clinical use of immunotherapies will increase considerably in the near future; therefore, predictive biomarkers of response to stratify patients for treatment are needed to limit potentially devastating adverse effects and reduce costs for healthcare systems. A clinical trial of the anti-PD-1 antibody pembrolizumab in CTCL showed that 38% of patients have a durable clinical response. However, standard tests, including comprehensive immunohistochemistry and single-cell quantification of PD-1 expression, have so far failed to identify a predictive biomarker for pembrolizumab response in this cohort. We reasoned that deep profiling of the CTCL tumor microenvironment (TME) using CODEX–a novel technology that allows for highly multiplexed tissue microscopy with >50 simultaneous parameters–could provide insight into the mechanisms of pembrolizumab response and enable prediction. We analyzed the CTCL TME using a tissue microarray of matched biopsies taken before and after pembrolizumab therapy in 7 responders and 7 non-responders. Imaging of 55 markers allowed discriminating malignant CD4+ tumor cells from reactive CD4+ T cells based on nuclear size and differential expression of CD7, CD25 and Ki-67. Unsupervised machine learning followed by supervised curation identified 21 different cell type clusters with spatial information. Integrating these data using advanced computational analysis revealed 10 distinct, conserved cellular neighborhoods (CNs) in the CTCL TME that changed in frequency and distribution during pembrolizumab therapy. In responders, effector-type CNs, including a tumor/dendritic cell CN and a tumor/CD4+ T cell CN, were significantly increased after treatment. In contrast, in non-responders, an immunosuppressive-type CN enriched in regulatory T cells was significantly increased before and after therapy. Importantly, the global frequencies in the tissues of the cell types defining these CNs were not different between patient groups. In addition, RNA sequencing of matched tissue sections revealed higher expression of effector-type cytokines and chemokines in responders. In sum, highly multiplexed analysis of the CTCL TME architecture in combination with RNA sequencing allows discovering novel, predictive spatial biomarkers of immunotherapy response and will pave the way for future studies that functionally address the identified cell types and cellular interactions.

Citation Format: Christian M. Schürch, Darci J. Phillips, Belén Rivero Gutierrez, Magdalena Matusiak, Salil S. Bhate, Graham L. Barlow, Steven P. Fling, Nirasha Ramchurren, Robert H. Pierce, Martin A. Cheever, Michael S. Khodadoust, Robert West, Youn H. Kim, Garry P. Nolan. Cellular neighborhoods predict pembrolizumab response in cutaneous T cell lymphoma [abstract]. In: Proceedings of the Annual Meeting of the American Association for Cancer Research 2020; 2020 Apr 27-28 and Jun 22-24. Philadelphia (PA): AACR; Cancer Res 2020;80(16 Suppl):Abstract nr 6669.

Combining RNA in situ hybridization and spectral flow cytometry to investigate the leukocyte glycocalyx in autoimmunity

The glycocalyx surrounding leukocytes has been studied for its role in immunomodulation and its potential as a therapeutic target. 4-methylumbelliferone (4MU) is a small molecule that inhibits production of the glycocalyx’s primary polysaccharide component hyaluronan (HA), by targeting the HA synthase (HAS). Oral treatment with 4MU has proved efficacious in preventing the development and progression of autoimmunity, though the mechanism is contested.

We have previously shown that 4MU strongly inhibits T-cell mediated autoimmunity, and report here that it also attenuates formation of antigen-specific plasmablasts and subsequent autoantibody production. This suggests that the HA glycocalyx plays a role in promoting the humoral component of autoimmunity.

The HAS proteins are deeply membrane embedded, preventing the use of traditional flow cytometry antibodies to define expression levels across leukocyte compartments. This limitation has made it difficult to identify cellular targets of 4MU. Alternative measurements must be used to study the HA glycocalyx. Surface HA content of a cell can be measured with labelled HA binding protein (HABP), though this does not explain whether HA was synthesized or scavenged with HA-binding receptors. RNA measurement can also be used to look at transcript levels of the HAS proteins.

Here, we combine RNA in situ hybridization, fluorescently labeled HA binding protein (HABP), and conventional flow cytometry antibodies to define the HA glycocalyx on leukocytes during autoimmunity. Utilizing Spectral Flow Cytometry, we can assess parameters in numbers comparable to Mass Cytometry (CyTOF) to identify which cells are most likely targeted by 4MU to prevent antibody formation during autoimmunity.