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SummaryMacrophages are the most abundant immune cell type in the tumor microenvironment (TME). Yet the spatial distribution and cell interactions that shape macrophage function are incompletely understood. Here we use single-cell RNA sequencing data and multiplex imaging to discriminate and spatially resolve macrophage niches within benign and malignant breast and colon tissue. We discover four distinct tissue-resident macrophage (TRM) layers within benign bowel, two TRM niches within benign breast, and three tumor-associated macrophage (TAM) populations within breast and colon cancer. We demonstrate that IL4I1 marks phagocytosing macrophages, SPP1 TAMs are enriched in hypoxic and necrotic tumor regions, and a novel subset of FOLR2 TRMs localizes within the plasma cell niche. Furthermore, NLRP3 TAMs that colocalize with neutrophils activate an inflammasome in the TME and in Crohn’s disease and are associated with poor outcomes in breast cancer patients. This work suggests novel macrophage therapy targets and provides a framework to study human macrophage function in clinical samples.

Advances in multiplexed imaging technologies have drastically improved our ability to characterize healthy and diseased tissues at the single-cell level. Co-detection by indexing (CODEX) relies on DNA-conjugated antibodies and the cyclic addition and removal of complementary fluorescently labeled DNA probes and has been used so far to simultaneously visualize up to 60 markers in situ. CODEX enables a deep view into the single-cell spatial relationships in tissues and is intended to spur discovery in developmental biology, disease and therapeutic design. Herein, we provide optimized protocols for conjugating purified antibodies to DNA oligonucleotides, validating the conjugation by CODEX staining and executing the CODEX multicycle imaging procedure for both formalin-fixed, paraffin-embedded (FFPE) and fresh-frozen tissues. In addition, we describe basic image processing and data analysis procedures. We apply this approach to an FFPE human tonsil multicycle experiment. The hands-on experimental time for antibody conjugation is ~4.5 h, validation of DNA-conjugated antibodies with CODEX staining takes ~6.5 h and preparation for a CODEX multicycle experiment takes ~8 h. The multicycle imaging and data analysis time depends on the tissue size, number of markers in the panel and computational complexity. This protocol describes co-detection by indexing, a highly multiplexed imaging technology that uses DNA-conjugated antibodies to image up to 60 markers in formalin-fixed, paraffin-embedded and fresh-frozen tissues.

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.

Chronic cutaneous graft‐vs‐host disease (GVHD) has several atypical variants. We describe two cases of GVHD with clinical and histopathologic features of pityriasis rubra pilaris (PRP), which responded to additional immunosuppression. Recognition of this newly described PRP‐like clinical presentation of GVHD may prompt early consideration of additional steroid‐sparing therapies.

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.

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.

Multiple myeloma (MM) is a plasma cell malignancy and the second most common hematological neoplasm in adults, comprising 1.8% of all cancers. With an annual incidence of ~30,770 cases in the United States, MM has a high mortality rate, leading to 12,770 deaths per year. MM is a genetically complex, highly heterogeneous malignancy, with significant inter- and intra-patient clonal variability. Recent years have witnessed dramatic improvements in the diagnostics, classification, and treatment of MM. However, patients with high-risk disease have not yet benefited from therapeutic advances. High-risk patients are often primary refractory to treatment or relapse early, ultimately resulting in progression toward aggressive end-stage MM, with associated extramedullary disease or plasma cell leukemia. Therefore, novel treatment modalities are needed to improve the outcomes of these patients. Bispecific antibodies (BsAbs) are immunotherapeutics that simultaneously target and thereby redirect effector immune cells to tumor cells. BsAbs have shown high efficacy in B cell malignancies, including refractory/relapsed acute lymphoblastic leukemia. Various BsAbs targeting MM-specific antigens such as B cell maturation antigen (BCMA), CD38, and CD138 are currently in pre-clinical and clinical development, with promising results. In this review, we outline these advances, focusing on BsAb drugs, their targets, and their potential to improve survival, especially for high-risk MM patients. In combination with current treatment strategies, BsAbs may pave the way toward a cure for MM.

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.

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 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.