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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.

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.

We develop a mathematical theory proposing that complex molecular phenotypes (CMPs, e.g., single-cell gene expression distributions and tissue organization) are produced from templates in the genome. We validate our theory using a procedure termed Causal Phenotype Sequence Alignment (CPSA). CPSA finds a candidate template of a CMP by aligning – without using genetic variation or biological annotations – a phenotypic measurement (e.g., a tissue image) with a reference genome. Given any edit to the CMP (e.g., changing cellular localization), CPSA outputs the genomic loci in the alignment corresponding to the edit. We confirm that three CMPs (single-cell gene expression distributions of the immune system and of embryogenesis, and tissue organization of the tumor microenvironment) have templates: the loci output by CPSA for therapeutically significant edits of these CMPs reveal genes, regulatory regions and active-sites whose experimental manipulation causes the edits. Our theory provides a systematic framework for genetically redesigning CMPs.

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.

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.

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.

Influenza is a significant cause of morbidity and mortality worldwide. Here we show changes in the abundance and activation states of more than 50 immune cell subsets in 35 individuals over 11 time points during human A/California/2009 (H1N1) virus challenge monitored using mass cytometry along with other clinical assessments. Peak change in monocyte, B cell, and T cell subset frequencies coincided with peak virus shedding, followed by marked activation of T and NK cells. Results led to the identification of CD38 as a critical regulator of plasmacytoid dendritic cell function in response to influenza virus. Machine learning using study-derived clinical parameters and single-cell data effectively classified and predicted susceptibility to infection. The coordinated immune cell dynamics defined in this study provide a framework for identifying novel correlates of protection in the evaluation of future influenza therapeutics.

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.

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.

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.

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.

A cytometric imaging approach, called CO-Detection by indEXing (CODEX), that enables high parameter multiplexing of antibody-tagged target epitopes is used here to create high parameter imaging datasets of normal mouse and lupus (MRL/lpr) spleens. In this procedure, antibody binding events are rendered iteratively using DNA barcodes, fluorescent dNTP analogs, and an in-situ polymerization-based indexing procedure. Fluorescent signals from multiple rounds of indexing are computationally combined into a multi-channel image stack and subjected to image segmentation and quantification. A segmentation and linear model algorithm was developed to accurately quantify membrane antigen levels on dissociated cells as well as tissue sections. Leveraging the spatially resolved nature of CODEX multiplexed single-cell imaging data, quantitative de novo characterization of lymphoid tissue architecture was enabled and overlaid onto previously described morphological features. We observed an unexpected, profound impact of the cellular neighborhood on the expression of protein receptors on immune cells. By comparing normal murine spleen to spleens from animals with systemic autoimmune disease (MRL/lpr), extensive and previously uncharacterized splenic cell interaction dynamics in the healthy versus diseased state was observed. The fidelity of multiplexed imaging data analysis demonstrated here will allow deep proteomic analysis and systematic characterization of complex tissue architecture in normal and clinically aberrant samples.

Summary A highly multiplexed cytometric imaging approach, termed co-detection by indexing (CODEX), is used here to create multiplexed datasets of normal and lupus (MRL/lpr) murine spleens. CODEX iteratively visualizes antibody binding events using DNA barcodes, fluorescent dNTP analogs, and an in situ polymerization-based indexing procedure. An algorithmic pipeline for single-cell antigen quantification in tightly packed tissues was developed and used to overlay well-known morphological features with de novo characterization of lymphoid tissue architecture at a single-cell and cellular neighborhood levels. We observed an unexpected, profound impact of the cellular neighborhood on the expression of protein receptors on immune cells. By comparing normal murine spleen to spleens from animals with systemic autoimmune disease (MRL/lpr), extensive and previously uncharacterized splenic cell-interaction dynamics in the healthy versus diseased state was observed. The fidelity of multiplexed spatial cytometry demonstrated here allows for quantitative systemic characterization of tissue architecture in normal and clinically aberrant samples., Graphical Abstract, Highlights • Autoimmunity analyzed by multiplexed DNA-tagged antibody staining (CODEX) • CODEX data reveal pairwise interactions and niches changing with disease • First tier of neighbors significantly impacts marker expression in the index cells • Changes in splenic morphology correlate with shifts in cell frequencies, A DNA barcoding-based imaging technique uses multiplexed tissue antigen staining to enable the characterization of cell types and dynamics in a model of autoimmune disease.

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.

Chronic myeloid leukemia (CML) is a typical stem-cell driven malignancy, driven by leukemia stem cells (LSCs). LSCs are resistant to conventional therapies. This resistance is mediated by cell-intrinsic mechanisms and interactions with the microenvironment. LSCs depend on signals from a specialized microenvironment, a so called niche, to maintain their stem cell characteristics. In CML the bone marrow (BM) as a niche is well-investigated and several therapeutic targets, which aim at LSCs by interrupting their interaction with the BM-niche are under investigation. However, even though splenomegaly is a hallmark of CML the contribution of the splenic microenvironment to CML development has not been studied so far. This project aims to investigate the role of the splenic microenvironment as an independent secondary LSC niche and its contribution to disease development. To induce a CML-like disease in mice we retrovirally transduced FACS-sorted Lineage- Sca-1+ cKit+ BM cells with pMSCV-p210BCR/ABL-IRES-GFP and injected the transduced cells into non-irradiated mice. To find out if the spleen contributes to disease development we induced CML in splenectomized and sham operated mice. Splenectomized mice survived significantly longer compared to sham operated controls (median survival 31 vs. 22 days; p=0.0006) with 20% of the splenectomized mice surviving longer than 90 days. Moreover, the number of LSCs in the BM of splenectomized mice was reduced 3.7-fold (p=0.002). Flowcytometric analysis of the spleen and BM compartments of CML bearing mice revealed that the majority of the leukemic stem and progenitor cells (LSPCs) were located in the spleen (19-fold more LSCs in the spleen; p =0.007). Moreover we found the leukemic compartment in the spleen to be enriched for LSPCs compared to the BM (20 % spleen vs. 10 % BM; % LSPCs of total leukemic cells; p=0.01). To confirm this phenotypic observation functionally we performed a limiting dilution transplantation of leukemic cells from spleen and BM. In line with the phenotypic observation we found a higher frequency of LSCs in the spleen compared to the BM (1/41'703 vs. 1/432'594; p=0.02). We next analyzed the gene expression of LSPCs from spleen and BM. We found that the gene expression profile of splenic LSPCs showed higher expression of stemness-related genes and reduced expression of myeloid differentiation genes compared to BM LSPCs, indicating that the spleen is more supportive of primitive LSPCs. Knowing that the spleen contributes to disease development by providing an alternate niche for LSCs we next analyzed the spleens using confocal microscopy. We found that the LSCs resided exclusively in the red pulp. Previous studies have shown that HSCs reside in direct contact with red pulp macrophages (RPMs) during extramedullary hematopoiesis (Dutta et al., JEM, 2015). In addition we found that in spleens from human CML patients CD34+ leukemia cells localized together with macrophages (p=0.001). Furthermore we could show that RPMs are capable of producing both SCF and G-CSF. To test the role of RPMs as a potential niche component in vitro we co-incubated LSCs and RPMs overnight before plating the LSCs in a colony formation assay. We found that the co-incubation with RPMs improved the colony formation capacity of LSCs (CFUs 166 vs. 138; p=0.0356). To test the role of RPMs in vivo we depleted macrophages in CML mice using clodronate liposomes. This resulted in significantly reduced splenomegaly (867mg vs. 249mg; p In summary, we found that the spleen provides an alternate niche for LSCs, thereby contributing to CML development. Compared to the BM niche the splenic niche is more supportive of primitive LSPCs, as shown by the higher frequency of LSCSs found in the spleen and the higher expression of stemness related genes in splenic LSCs compared to BM LSCs. Moreover we identified CD24low RPMs as a unique and central component of the splenic LSC niche. Even though we could show that RPMs are capable of producing SCF and G-CSF the exact mechanisms by which RPMs support LSCs remains to be investigated. Disclosures No relevant conflicts of interest to declare.

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.

Comprehensive identification of factors that can specify neuronal fate could provide valuable insights into lineage specification and reprogramming, but systematic interrogation of transcription factors, and their interactions with each other, has proven technically challenging. We developed a CRISPR activation (CRISPRa) approach to systematically identify regulators of neuronal-fate specification. We activated expression of all endogenous transcription factors and other regulators via a pooled CRISPRa screen in embryonic stem cells, revealing genes including epigenetic regulators such as Ezh2 that can induce neuronal fate. Systematic CRISPR-based activation of factor pairs allowed us to generate a genetic interaction map for neuronal differentiation, with confirmation of top individual and combinatorial hits as bona fide inducers of neuronal fate. Several factor pairs could directly reprogram fibroblasts into neurons, which shared similar transcriptional programs with endogenous neurons. This study provides an unbiased discovery approach for systematic identification of genes that drive cell-fate acquisition.