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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.

Recent therapeutic strategies for glioblastoma (GBM) aim at targeting immune tumor microenvironment (iTME) components to induce antitumoral immunity. A patient-tailored, ex vivo drug testing and response analysis platform for GBM would facilitate personalized therapy planning, provide insights into treatment-induced immune mechanisms in the iTME, and enable the discovery of biomarkers of therapy response and resistance.We cultured 47 GBM explants from tumor center and periphery from 7 patients in perfusion bioreactors to assess iTME responses to immunotherapy. Explants were exposed to antibodies blocking the immune checkpoints CD47, PD-1 or or their combination, and were analyzed by highly multiplexed microscopy (CODEX, co-detection by indexing) using an immune-focused 55-marker panel. Culture media were examined for changes of soluble factors including cytokines, chemokines and metabolites. CODEX enabled the spatially resolved identification and quantification of >850,000 single cells in explants, which were classified into 10 cell types by clustering. Explants from center and periphery differed significantly in their cell type composition, their levels of soluble factors, and their responses to immunotherapy. In a subset of explants, culture media displayed increased interferon-γ levels, which correlated with shifts in immune cell composition within specific tissue compartments, including the enrichment of CD4+ and CD8+ T cells within an adaptive immune compartment. Furthermore, significant differences in the expression levels of functional molecules in innate and adaptive immune cell types were found between explants responding or not to immunotherapy. In non-responder explants, T cells showed higher expression of PD-1, LAG-3, TIM-3 and VISTA, whereas in responders, macrophages and microglia showed higher cathepsin D levels. Our study demonstrates that ex vivo immunotherapy of GBM explants enables an active antitumoral immune response within the tumor center in a subset of patients, and provides a framework for multidimensional personalized assessment of tumor response to immunotherapy.

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., We simplified the multiplexed imaging method CO‐Detection by indEXing (CODEX) by employing cyclic stripping and annealing of fluorescent oligonucleotides to DNA‐barcoded antibodies. We stained five human lymphoid tissues with a panel of 46 antibodies. This enabled quantitative spatial single‐cell biology analysis of differential cell‐type composition of immune follicles.

Cutaneous T cell lymphomas (CTCL) are rare but aggressive cancers without effective treatments. While a subset of patients derive benefit from PD-1 blockade, there is a critically unmet need for predictive biomarkers of response. Herein, we perform CODEX multiplexed tissue imaging and RNA sequencing on 70 tumor regions from 14 advanced CTCL patients enrolled in a pembrolizumab clinical trial (NCT02243579). We find no differences in the frequencies of immune or tumor cells between responders and non-responders. Instead, we identify topographical differences between effector PD-1+ CD4+ T cells, tumor cells, and immunosuppressive Tregs, from which we derive a spatial biomarker, termed the SpatialScore, that correlates strongly with pembrolizumab response in CTCL. The SpatialScore coincides with differences in the functional immune state of the tumor microenvironment, T cell function, and tumor cell-specific chemokine recruitment and is validated using a simplified, clinically accessible tissue imaging platform. Collectively, these results provide a paradigm for investigating the spatial balance of effector and suppressive T cell activity and broadly leveraging this biomarker approach to inform the clinical use of immunotherapies., PD-1 blockade is effective for only a subset of patients with cutaneous T cell lymphomas. Here, the authors report a spatial biomarker that uses immune and cancer cell topography to predict response to PD-1 blockade in this disease.

Simultaneous visualization of the relationship between multiple biomolecules and their ligands or small molecules at the nanometer scale in cells will enable greater understanding of how biological processes operate. We present here high-definition multiplex ion beam imaging (HD-MIBI), a secondary ion mass spectrometry approach capable of high-parameter imaging in 3D of targeted biological entities and exogenously added structurally-unmodified small molecules. With this technology, the atomic constituents of the biomolecules themselves can be used in our system as the “tag” and we demonstrate measurements down to ~30 nm lateral resolution. We correlated the subcellular localization of the chemotherapy drug cisplatin simultaneously with five subnuclear structures. Cisplatin was preferentially enriched in nuclear speckles and excluded from closed-chromatin regions, indicative of a role for cisplatin in active regions of chromatin. Unexpectedly, cells surviving multi-drug treatment with cisplatin and the BET inhibitor JQ1 demonstrated near total cisplatin exclusion from the nucleus, suggesting that selective subcellular drug relocalization may modulate resistance to this important chemotherapeutic treatment. Multiplexed high-resolution imaging techniques, such as HD-MIBI, will enable studies of biomolecules and drug distributions in biologically relevant subcellular microenvironments by visualizing the processes themselves in concert, rather than inferring mechanism through surrogate analyses., Multiplexed ion beam imaging can provide subcellular localisation information but with limited resolution. Here the authors report an ion beam imaging method with nanoscale resolution which they use to assess the subcellular distribution of cisplatin.

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.

A thorough understanding of complex spatial host-disease interactions in situ is necessary in order to develop effective preventative measures and therapeutic strategies. Here, we developed Protein And Nucleic acid IN situ Imaging (PANINI) and coupled it with Multiplexed Ion Beam Imaging (MIBI) to sensitively and simultaneously quantify DNA, RNA, and protein levels within the microenvironments of tissue compartments. The PANINI-MIBI approach was used to measure over 30 parameters simultaneously across large sections of archival lymphoid tissues from non-human primates that were healthy or infected with simian immunodeficiency virus (SIV), a model that accurately recapitulates human immunodeficiency virus infection (HIV). This enabled multiplexed dissection of cellular phenotypes, functional markers, viral DNA integration events, and viral RNA transcripts as resulting from viral infection. The results demonstrated immune coordination from an unexpected upregulation of IL10 in B cells in response to SIV infection that correlated with macrophage M2 polarization, thus conditioning a potential immunosuppressive environment that allows for viral production. This multiplexed imaging strategy also allowed characterization of the coordinated microenvironment around latently or actively infected cells to provide mechanistic insights into the process of viral latency. The spatial multi-modal framework presented here is applicable to deciphering tissue responses in other infectious diseases and tumor biology.

Ulcerative colitis is a chronic-relapsing inflammatory disease of the large intestine with a complex, multifactorial pathogenesis. TNF inhibitors are widely used to suppress immune-mediated tissue damage in ulcerative colitis patients; however, therapy failures are common. Predicting TNF inhibitor response requires an understanding of the architectural features that underlie mucosal inflammation and those responsible for resistance. Here, we used highly multiplexed immunofluorescence to uncover the spatially resolved tissue architectures underlying disease progression and treatment response in 42 tissue regions from 34 individuals. We created a tissue atlas and performed spatial analysis to identify cell-cell contacts and cellular neighborhoods. We observed that cellular functional states depend on cellular neighborhood and that a subset of inflammatory cell types and cellular neighborhoods in ulcerative colitis patients persisted even during treatment with TNF inhibitor, indicating resistant niches. A computer vision model, with no a priori assumptions regarding cellular architectural features, was able to predict TNF inhibitor resistance. This spatial model significantly outperformed classification models based on single-cell data alone. Our results demonstrate the value of a spatial tissue atlas as a precision medicine tool to guide treatment of patients suffering from autoimmune diseases.

A thorough understanding of complex spatial host-disease interactions in situ is necessary in order to develop effective preventative measures and therapeutic strategies. Here, we developed Protein And Nucleic acid IN situ Imaging (PANINI) and coupled it with Multiplexed Ion Beam Imaging (MIBI) to sensitively and simultaneously quantify DNA, RNA, and protein levels within the microenvironments of tissue compartments. The PANINI-MIBI approach was used to measure over 30 parameters simultaneously across large sections of archival lymphoid tissues from non-human primates that were healthy or infected with simian immunodeficiency virus (SIV), a model that accurately recapitulates human immunodeficiency virus infection (HIV). This enabled multiplexed dissection of cellular phenotypes, functional markers, viral DNA integration events, and viral RNA transcripts as resulting from viral infection. The results demonstrated immune coordination from an unexpected upregulation of IL10 in B cells in response to SIV infection that correlated with macrophage M2 polarization, thus conditioning a potential immunosuppressive environment that allows for viral production. This multiplexed imaging strategy also allowed characterization of the coordinated microenvironment around latently or actively infected cells to provide mechanistic insights into the process of viral latency. The spatial multi-modal framework presented here is applicable to deciphering tissue responses in other infectious diseases and tumor biology.

Understanding the mechanisms of HIV tissue persistence necessitates the ability to visualize tissue microenvironments where infected cells reside; however, technological barriers limit our ability to dissect the cellular components of these HIV reservoirs. Here, we developed protein and nucleic acid in situ imaging (PANINI) to simultaneously quantify DNA, RNA, and protein levels within these tissue compartments. By coupling PANINI with multiplexed ion beam imaging (MIBI), we measured over 30 parameters simultaneously across archival lymphoid tissues from healthy or simian immunodeficiency virus (SIV)-infected nonhuman primates. PANINI enabled the spatial dissection of cellular phenotypes, functional markers, and viral events resulting from infection. SIV infection induced IL-10 expression in lymphoid B cells, which correlated with local macrophage M2 polarization. This highlights a potential viral mechanism for conditioning an immunosuppressive tissue environment for virion production. The spatial multimodal framework here can be extended to decipher tissue responses in other infectious diseases and tumor biology.

Background Immunotherapies have induced long-lasting remissions in countless advanced-stage cancer patients, but many more patients have not benefitted. Therefore, novel predictive markers are needed to stratify patients before treatment and select those who will most likely benefit from immunotherapy, while avoiding potentially devastating adverse effects and high treatment costs for those who will not. We reasoned that thoroughly characterizing the architecture of the tumor microenvironment (TME) at the single-cell level by highly multiplexed tissue imaging should reveal novel spatial biomarkers of immunotherapy response. Materials and Methods We used CODEX (CO-Detection by indEXing) highly multiplexed fluorescence microscopy to investigate the TME of cutaneous T cell lymphoma (CTCL) in samples from patients treated with pembrolizumab. 55 protein markers were visualized simultaneously using a tissue microarray of matched pre- and post-treatment skin biopsies from 7 pembrolizumab responders and 7 non-responders. After computational image processing and extraction of single-cell information, cell types were identified by unsupervised clustering followed by supervised curation, and cell-cell distances and ‘cellular neighborhoods’ were computed. We also performed RNA sequencing on laser-capture microdissected tissue microarray cores to extract cell-type specific gene expression profiles by CIBERSORTx analysis. Results CODEX enabled the identification and characterization of malignant CD4+ tumor cells and reactive immune cells in the CTCL TME at the single-cell level, resulting in 21 different cell type clusters with spatial information. Cluster frequencies were not significantly different between responders and non-responders pre- and post-treatment. However, advanced computational analysis of the tumor architecture revealed cellular neighborhoods (CNs) that dynamically changed during pembrolizumab therapy and were correlated with response. Effector-type CNs enriched in tumor-infiltrating CD4+ T cells and dendritic cells were significantly increased after treatment in responders. In contrast, a regulatory T cell-enriched CN was significantly increased in non-responders before and after therapy. Furthermore, a spatial signature of cell-cell distances between tumor cells and effector/regulatory immune cells predicted therapy outcome. In addition, CIBERSORTx analysis revealed that tumor cells in responders, but not in non-responders, increased their expression of immune-activating genes. Conclusions High-dimensional spatial analysis of CTCL tumors revealed a pre-existing immunosuppressive state in pembrolizumab non-responders. Thorough analysis of the TME therefore enables the discovery of novel spatial biomarkers in a concept that accounts for both cell type information and higher-order tumor architecture. Combining highly multiplexed microscopy with CIBERSORTx allows for the discovery of novel, predictive spatial biomarkers of immunotherapy response and will pave the way for future studies that functionally address these cell types and their interactions. Disclosure Information C.M. Schurch: F. Consultant/Advisory Board; Modest; Enable Medicine, LLC. D.J. Phillips: None. M. Matusiak: None. B. Rivero Gutierrez: None. S.S. Bhate: None. G.L. Barlow: None. M.S. Khodadoust: B. Research Grant (principal investigator, collaborator or consultant and pending grants as well as grants already received); Significant; Corvus Pharmaceuticals. R. West: None. Y.H. Kim: B. Research Grant (principal investigator, collaborator or consultant and pending grants as well as grants already received); Significant; Merck, Horizon, Soligenix, miRagen, Forty Seven Inc., Neumedicine, Trillium, Galderma, Elorac. D. Speakers Bureau/Honoraria (speakers bureau, symposia, and expert witness); Significant; Innate Pharma, Eisai, Kyowa Hakko Kirin, Takeda, Seattle Genetics, Medivir, Portola Pharmaceuticals, Corvus Pharmaceuticals. G.P. Nolan: E. Ownership Interest (stock, stock options, patent or other intellectual property); Significant; Akoya Biosciences. F. Consultant/Advisory Board; Significant; Akoya Biosciences.

COVID-19 respiratory infections are associated with copious, adherent respiratory secretions that prolong chronic ventilation and contribute to the morbidity and mortality caused by the disease. We hypothesized that hyaluronan, an extracellular matrix glycosaminoglycan produced at sites of active inflammation that promotes edema in other settings, might be a component of these secretions. To interrogate this, we examined the respiratory secretions collected from eight intubated patients with COVID-19, six control patients with cystic fibrosis (CF), a different respiratory disease also associated with thick adherent secretions, and eight healthy controls. In this sample set we found that hyaluronan content is increased approximately 20-fold in both CF and COVID-19 patients compared to healthy controls. The hyaluronan in COVID-19 samples was comprised of low-molecular weight fragments, the hyaluronan form most strongly linked with pro-inflammatory functions. Hyaluronan is similarly abundant in histologic sections from cadaveric lung tissue from COVID-19 patients. These findings implicate hyaluronan in the thick respiratory secretions characteristic of COVID-19 infection. Therapeutic strategies targeting hyaluronan should be investigated further for potential use in patients with COVID-19.

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.

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.

Technologies that visualize multiple biomolecules at the nanometer scale in cells will enable deeper understanding of biological processes that proceed at the molecular scale. Current fluorescence-based methods for microscopy are constrained by a combination of spatial resolution limitations, limited parameters per experiment, and detector systems for the wide variety of biomolecules found in cells. We present here super-resolution ion beam imaging (srIBI), a secondary ion mass spectrometry approach capable of high-parameter imaging in 3D of targeted biological entities and exogenously added small molecules. Uniquely, the atomic constituents of the biomolecules themselves can often be used in our system as the “tag”. We visualized the subcellular localization of the chemotherapy drug cisplatin simultaneously with localization of five other nuclear structures, with further carbon elemental mapping and secondary electron visualization, down to ∼30 nm lateral resolution. Cisplatin was preferentially enriched in nuclear speckles and excluded from closed-chromatin regions, indicative of a role for cisplatin in active regions of chromatin. These data highlight how multiplexed super-resolution techniques, such as srIBI, will enable studies of biomolecule distributions in biologically relevant subcellular microenvironments.One Sentence SummaryThree-dimensional multiplexed mass spectrometry-based imaging revealed the subcellular localization of proteins and small molecules at super-resolution.

Summary 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., Graphical Abstract, Highlights • FFPE-CODEX multiplexed tissue imaging of 56 markers in 140 tissues of 35 CRC patients • Cellular neighborhoods reveal spatial organization of the tumor microenvironment • Altered organization of tumor and immune components in low- versus high-risk patients • Local enrichment of PD-1+CD4+ T cells correlates with survival in high-risk patients, A multiplexed tissue imaging and computational analysis framework applied to colorectal cancer allows interrogation of how spatial organization of the immune tumor microenvironment is linked to clinical outcomes.

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.

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.

Cutaneous T cell lymphoma (CTCL) is a CD4+ T cell malignancy of the skin with heterogeneous outcomes and limited treatment options. Monoclonal antibodies directed against PD-1, such as pembrolizumab, have shown impressive efficacy in multiple advanced malignancies, and are currently tested in clinical trials in patients with CTCL. Initial data indicate that about half of the patients experience treatment response, whereas the other half are non-responders. Non-responders can be further divided into patients with stable disease versus rapid progressors. It is currently unknown why some CTCL patients respond to pembrolizumab while others rapidly progress, and no predictive biomarkers are available. Single-cell analysis approaches to identify biomarkers of response, for example quantifying the expression of PD-1 on tumor cells vs. reactive immune cells, have not enabled stratification of patients. We therefore hypothesized that more complex spatial cellular interactions within the immune tumor microenvironment (iTME) of CTCL could provide insight into the mechanisms of pembrolizumab response and enable prediction. We applied CODEX (CO-Detection by indEXing) highly multiplexed tissue imaging to study the CTCL iTME in matched biopsies before and after pembrolizumab therapy in 7 responders and 7 non-responders (see the Figure). Using 54 markers simultaneously allowed discriminating malignant CD4+ tumor cells from reactive CD4+ T cells and identified 30 different cell clusters with spatial information, including an M2 macrophage cluster that was enriched in non-responders before therapy. Unexpectedly, in pembrolizumab responders compared to non-responders, PD-1 expression levels were higher in multiple clusters of tumor cells and reactive T cells. Computational spatial analysis revealed ten distinct, conserved cellular neighborhoods in the CTCL iTME that changed in composition and frequency during therapy. Interestingly, one cellular neighborhood to be presented dramatically increased after therapy only in responders. Therefore, highly multiplexed spatial analysis of the CTCL iTME allows discovering novel, predictive biomarkers of immunotherapy response and will pave the way for future studies that functionally address the identified cell types and cellular interactions. Disclosures Khodadoust: Corvus Pharmaceuticals: Research Funding. Kim:miRagen: Research Funding; Merck: Research Funding; Medivir: Honoraria, Membership on an entity's Board of Directors or advisory committees; Innate Pharma: Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding; Soligenix: Research Funding; Forty Seven Inc: Research Funding; Neumedicine: Research Funding; Takeda: Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding; Trillium: Research Funding; Elorac: Research Funding; Galderma: Research Funding; Corvus: Honoraria, Membership on an entity's Board of Directors or advisory committees; Portola Pharmaceuticals: Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding; Seattle Genetics: Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding; Kyowa Hakko Kirin: Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding; Eisai: Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding; Horizon: Research Funding. Nolan:Akoya Biosciences Inc.: Consultancy, Equity Ownership, Patents & Royalties.

Introduction The bone marrow (BM) microenvironment consists of various cell types such as mesenchymal stromal cells, endothelial cells, osteoblastic cells and multiple immune cell types including mature myeloid cells and lymphocytes. Recent studies have shown that leukemias can create and maintain a leukemia-supporting BM microenvironment, and vice versa, a dysfunctional BM microenvironment can contribute to leukemia development and progression. Moreover, in tumors the microenvironment is often immunosuppressive and restrains effective anti-tumoral immune responses by adaptive and innate immunity. A better understanding of the precise localization of microenvironmental and immune cell types in intact tissue, and how they physically interact with each other and with tumor cells, will improve our understanding of the mechanisms by which cancer reprograms its microenvironment and may form the basis for novel immunotherapies. Methods CO-Detection by antibody indEXing (CODEX) is a multiplex fluorescence microscopy platform based on DNA-conjugated antibodies that allows the analysis of 50+ markers in a single tissue section. After staining with an antibody cocktail, tissues are imaged in a multi-cycle reaction using a microfluidics system and a fluorescence microscope with a computer automated X/Y/Z stage. DNA-conjugated antibodies are rendered visible using complementary fluorescent DNA probes, followed by imaging, probe stripping, washing and re-rendering. This process is repeated until all the antibodies present in the initial cocktail have been rendered and imaged. Here, we used CODEX to analyze intact BM at the single-cell level (~200nm resolution) during leukemic progression. Chronic myeloid leukemia (CML)-like disease was induced in non-irradiated mice using BCR-ABL1-GFP retrovirus. Tissue sections of femoral bones harvested at different time points after leukemia onset were stained using a 50+ marker CODEX antibody panel to simultaneously identify hematopoietic and leukemic stem and progenitor cells, multiple BM microenvironmental cell types, myeloid and lymphoid cells as well as functional markers. Results We have built an integrated computational pipeline for the analysis of high-dimensional CODEX data that enables the identification and characterization of BM cell types as well as their spatial organization in situ. Raw images were concatenated and aligned using Hoechst nuclear stain as a reference, followed by deconvolution, segmentation, marker expression quantification and spatial compensation. Exported data were clustered in an unsupervised manner using VorteX algorithm, which identified 28 distinct cellular clusters based on marker expression values. All major BM compartments including stromal (vascular, pericytes, osteoblastic), lymphoid (T and B cell subsets), myeloid (megakaryocytes, macrophages, dendritic cells, granulocytes) and progenitor cell types, as well as leukemic cells, were represented. During leukemic progression, the BM microenvironment was dramatically rearranged. Besides the expected growth of the leukemic clone, we observed a massive increase in vascular and osteoblastic cell types, whereas immune cell clusters were significantly reduced. Interestingly, CD71, the transferrin receptor, was strongly up-regulated on tumor cells in advanced leukemia, indicating towards a role for iron metabolism in malignant progression. Furthermore, hierarchical clustering of tissue regions based on cellular composition using X/Y/Z positional information pointed towards the emergence of specific cell-cell interaction modules that developed during leukemic progression, including mutual attraction between B cells and central arterioles. Conclusions High-dimensional imaging of the BM microenvironment by CODEX allows studying the abundance and distribution of cellular elements that are often underestimated or missed by traditional flow cytometry, such as stromal cells, vasculature and megakaryocytes. Importantly, CODEX identifies single cells in their tissue context during leukemic progression and facilitates the discovery of novel cell-cell interactions and cell types as well as unexpected marker constellations. Disclosures Samusik: Akoya Biosciences: Consultancy, Equity Ownership, Honoraria, Membership on an entity's Board of Directors or advisory committees, Patents & Royalties. Nolan:Akoya Biosciences: Equity Ownership, Membership on an entity's Board of Directors or advisory committees, Patents & Royalties. Goltsev:Akoya Biosciences: Equity Ownership, Membership on an entity's Board of Directors or advisory committees, Patents & Royalties.