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Background Inflammatory bowel disease (IBD) is a complex disease with variable presentation, progression, and response to therapies. Current disease classification is based on subjective clinical phenotypes. The peripheral blood immunophenome can reflect local inflammation, and thus we measured 39 circulating immune cell types in a large cohort of IBD and control subjects and performed immunotype:phenotype associations. Methods We performed fluorescence-activated cell sorting or CyTOF analysis on blood from 728 Crohn’s disease, 464 ulcerative colitis, and 334 non-IBD patients, with available demographics, endoscopic and clinical examinations and medication use. Results We observed few immune cell types commonly affected in IBD (lowered natural killer cells, B cells, and CD45RA– CD8 T cells). Generally, the immunophenome was distinct between ulcerative colitis and Crohn’s disease. Within disease subtype, there were further distinctions, with specific immune cell types associating with disease duration, behavior, and location. Thiopurine monotherapy altered abundance of many cell types, often in the same direction as disease association, while anti-tumor necrosis factor (anti-TNF) monotherapy demonstrated an opposing pattern. Concomitant use of an anti-TNF and thiopurine was not synergistic, but rather was additive. For example, thiopurine monotherapy use alone or in combination with anti-TNF was associated with a dramatic reduction in major subclasses of B cells. Conclusions We present a peripheral map of immune cell changes in IBD related to disease entity and therapies as a resource for hypothesis generation. We propose the changes in B cell subsets could affect antibody formation and potentially explain the mechanism behind the superiority of combination therapy through the impact of thiopurines on pharmacokinetics of anti-TNFs., Graphical abstract

Pancreatic ductal adenocarcinoma (PDA) is characterized by an immune-suppressive tumor microenvironment that renders it largely refractory to immunotherapy. We implemented a multimodal analysis approach to elucidate the immune landscape in PDA. Using a combination of CyTOF, single-cell RNA sequencing and multiplex immunohistochemistry on patient tumors, matched blood and non-malignant samples, we uncovered a complex network of immune-suppressive cellular interactions. These experiments revealed heterogeneous expression of immune checkpoint receptors in individual patients’ T cells and increased markers of CD8+ T cell dysfunction in the advanced disease stage. Tumor-infiltrating CD8+ T cells had an increased proportion of cells expressing an exhausted expression profile that included upregulation of the immune checkpoint TIGIT, a finding that we validated at the protein level. Our findings point to a profound alteration of the immune landscape of tumors, and to patient-specific immune changes that should be taken into account as combination immunotherapy becomes available for pancreatic cancer. Using single-cell RNA sequencing, CyTOF and multiplex immunohistochemistry, Steele et al. survey the immune landscape in pancreatic cancers, adjacent tissue and blood, observing heterogeneous immune checkpoint receptor expression within patients.

Cancer Radiation therapy (RT) induces cardiovascular disease (CVD) even when the heart is shealed or not irradiated, but there is a paucity of available preventive measures for RT-induced CVD. Ionizing radiation (IR) induces senescence, which was originally discovered to suppress tumorigenesis by inducing cell cycle blockade and necrosis, and positioned IR as pro-senescence cancer therapy. IR-induced senescence cells secrete cytokines, growth factors, and reactive oxygen species (ROS), becoming so called senescence associated secretory phenotype (SASP), and we hypothesize that SASP induction in immune cells cause CVD after RT. Although the involvement of DNA damage response (DDR), efferocytosis, and clonal hematopoiesis drivers (CHD) to SASP induction has been suggested, the exact mechanisms through which RT induces SASP in a specific cell type remains unclear. We characterize most of the major human immune cell lineages in a single assay using mass cytometery (CyTOF). We generated a CyTOF panel which includes antibodies against various senescence phenotype, DDR, efferocytosis, and CHD. We isolated peripheral blood mononuclear cells (PBMCs) before and 3 month after RT from 16 thoracic cancer patients. First, we found the frequency of only B cell subtype was decreased after RT. Second, we obtained 138 functional profiling subsets by unsupervised clustering with our antibody set, and found that T-bet expression was increased in the largest B cell subset of naïve B Cell (CD27 - ) Ki67 lo CD38 lo DNMT3a hi after RT, which showed the good correlation with p-p90RSK expression in the samples from pre-RT and post-RT. Lastly, the significant increase of CD38 expression in the subsets of naïve B cell (CD27 - ) and CD8 + T cell (EMRA) was detected. These data suggest the unique response of naïve B cell (CD27-) to RT with the increase of CD38 expression, and T-bet in the subset of B Cell (CD27 - ) Ki67 lo CD38 lo DNMT3a hi , and also the potential role of p90RSK activation in IR-induced T-bet expression. T-bet plays a role in developing the age-associated B cell (ABC), and the increase of CD38 expression promotes aging-related events. Therefore, the induction of T-bet and CD38 in naïve B (CD27 - ) cell after RT supports the novel role of naïve B cell in IR-induced SASP and subsequent CVD.

SUMMARYAtherosclerosis is driven by multifaceted contributions of the immune system within the circulation and at vascular focal sites. Yet the specific immune dysregulations within the atherosclerotic lesions that lead to clinical cerebro- and cardiovascular complications (i.e. ischemic stroke and myocardial infarction) are poorly understood. Here, using single-cell mass cytometry with Cellular Indexing of Transcriptomes and Epitopes by Sequencing (CITE-seq) we found that atherosclerotic plaques were enriched in activated, differentiated, and exhausted subsets of T cells vs. blood. Next, using single-cell proteomic, transcriptomic, and cell-to-cell interaction analyses we found unique functional dysregulations of both T cells and macrophages in plaques of patients with clinically symptomatic (SYM; recent stroke of TIA) or asymptomatic (ASYM, no recent stroke) carotid artery disease. SYM plaques were enriched with a distinct CD4+T cell subset, and T cells were activated, differentiated and presented subset specific exhaustion. SYM macrophages presented alternatively activated phenotypes including subsets associated with plaque vulnerability. In ASYM plaques, T cells and macrophages were activated and displayed a strong IL-1β signaling across cell types, that was absent in SYM plaques. The identification of plaque-specific innate and adaptive immune dysregulations associated with cerebrovascular events provides the basis for the design of precisely tailored cardiovascular immunotherapies.

Summary The success of immunotherapy has led to a myriad of clinical trials accompanied by efforts to gain mechanistic insight and identify predictive signatures for personalization. However, many immune monitoring technologies face investigator bias, missing unanticipated cellular responses in limited clinical material. We present here a mass cytometry (CyTOF) workflow for standardized, systems-level biomarker discovery in immunotherapy trials. To broadly enumerate immune cell identity and activity, we established and extensively assessed a reference panel of 33 antibodies to cover major cell subsets, simultaneously quantifying activation and immune checkpoint molecules in a single assay. This assay enumerates ≥98% of peripheral immune cells with ≥4 positively identifying antigens. Robustness and reproducibility are demonstrated on multiple samples types, across two research centers and by orthogonal measurements. Using automated analysis, we identify stratifying immune signatures in bone marrow transplantation-associated graft-versus-host disease. Together, this validated workflow ensures comprehensive immunophenotypic analysis and data comparability and will accelerate biomarker discovery., Graphical Abstract, Highlights • Single assay to identify and characterize all major human immune cell lineages • Readily available and extensively validated antibody panel • Additional (>10) targets can be added to meet specific hypotheses • Allows identification of disease-associated immune signatures and biomarkers, Hartmann et al. provide an experimental framework to identify and characterize all major human immune cell lineages in a single assay using mass cytometry (CyTOF). This validated and readily available workflow ensures comprehensive immunophenotypic analysis, improves data comparability, and allows identification of disease-associated immune signatures and biomarkers for human immunotherapy.

Atherosclerosis is driven by multifaceted contributions of the immune system within the circulation and at vascular focal sites. However, specific characteristics of dysregulated immune cells within atherosclerotic lesions that lead to clinical events such as ischemic stroke or myocardial infarction are poorly understood. Here, using single-cell proteomic and transcriptomic analyses, we uncovered distinct features of both T cells and macrophages in carotid artery plaques of patients with clinically symptomatic disease (recent stroke or transient ischemic attack) compared to asymptomatic disease (no recent stroke). Plaques from symptomatic patients were characterized by a distinct subset of CD4+ T cells and by T cells that were activated and differentiated. Moreover, some T cell subsets in these plaques presented markers of T cell exhaustion. Additionally, macrophages from these plaques contained alternatively activated phenotypes, including subsets associated with plaque vulnerability. In plaques from asymptomatic patients, T cells and macrophages were activated and displayed evidence of interleukin-1β signaling. The identification of specific features of innate and adaptive immune cells in plaques that are associated with cerebrovascular events may enable the design of more precisely tailored cardiovascular immunotherapies.

Chikungunya virus (CHIKV) is a mosquito‐borne alphavirus that causes global epidemics of debilitating disease worldwide. To gain functional insight into the host cellular genes required for virus infection, we performed whole‐blood RNA‐seq, 37‐plex mass cytometry of peripheral blood mononuclear cells (PBMCs), and serum cytokine measurements of acute‐ and convalescent‐phase samples obtained from 42 children naturally infected with CHIKV. Semi‐supervised classification and clustering of single‐cell events into 57 sub‐communities of canonical leukocyte phenotypes revealed a monocyte‐driven response to acute infection, with the greatest expansions in “intermediate” CD14++ CD16+ monocytes and an activated subpopulation of CD14+ monocytes. Increases in acute‐phase CHIKV envelope protein E2 expression were highest for monocytes and dendritic cells. Serum cytokine measurements confirmed significant acute‐phase upregulation of monocyte chemoattractants. Distinct transcriptomic signatures were associated with infection timepoint, as well as convalescent‐phase anti‐CHIKV antibody titer, acute‐phase viremia, and symptom severity. We present a multiscale network that summarizes all observed modulations across cellular and transcriptomic levels and their interactions with clinical outcomes, providing a uniquely global view of the biomolecular landscape of human CHIKV infection.

Background B cells play a critical role in the development and maintenance of food allergy by producing allergen-specific IgE. Despite the importance of B cells in IgE-mediated food allergy, the identity of sIgE-producing human B cells and how IgE is regulated are poorly understood. Objective To identify the immunophenotypes of circulating B cells associated with the production of galactose-alpha-1,3-galactose-specific IgE production in patients with red meat allergy. Methods B cells in PBMC samples obtained from 19 adults with physician-diagnosed red meat allergy and 20 non-meat allergic healthy controls were assessed by mass cytometry along with a bioinformatics analysis pipeline to identify discrete B cell phenotypes that associated with serum sIgE. Fluorescent flow cytometry was then applied to sort purify discrete B cell subsets, and B cells were functionally evaluated on an individual cell level for the production of sIgE by ELISPOT. Results Discrete B cell phenotypes abundant in meat allergic subjects compared to non-meat allergic controls were found in peripheral blood that do not share typical characteristics of classical isotype-switched memory B cells that express high levels of CD27. These B cell subsets shared higher IgD and lower IgM expression levels coupled with CXCR4, CCR6 and CD25 expression. In vitro polyclonal stimulation of purified B cell subsets from meat allergic subjects demonstrated that these subsets were enriched for cells induced to secrete sIgE. Conclusions and clinical relevance Circulating B cells display increased abundance of discrete B cell subsets in meat allergic subjects. This observation, coupled with the capacity of individual B cell subsets to produce sIgE following activation, implicates these novel B cell phenotypes in promoting IgE in meat allergy.

CRISPR pools are being widely employed to identify gene functions. However, current technology, which utilizes DNA as barcodes, permits limited phenotyping and bulk-cell resolution. To enable novel screening capabilities, we developed a barcoding system operating at the protein level. We synthesized modules encoding triplet combinations of linear epitopes to generate >100 unique protein barcodes (Pro-Codes). Pro-Code-expressing vectors were introduced into cells and analyzed by CyTOF mass cytometry. Using just 14 antibodies, we detected 364 Pro-Code populations; establishing the largest set of protein-based reporters. By pairing each Pro-Code with a different CRISPR, we simultaneously analyzed multiple phenotypic markers, including phospho-signaling, on dozens of knockouts. Pro-Code/CRISPR screens found two interferon-stimulated genes, the immunoproteasome component Psmb8 and a chaperone Rtp4, are important for antigen-dependent immune editing of cancer cells and identified Socs1 as a negative regulator of Pd-l1. The Pro-Code technology enables simultaneous high-dimensional protein-level phenotyping of 100s of genes with single-cell resolution.

Mass-tag cell barcoding (MCB) labels individual cell samples with unique combinatorial barcodes, after which they are pooled for processing and measurement as a single multiplexed sample. The MCB method eliminates variability between samples in antibody staining and instrument sensitivity, reduces antibody consumption, and shortens instrument measurement time. Here, we present an optimized MCB protocol with several improvements over previously described methods. The use of palladium-based labeling reagents expands the number of measurement channels available for mass cytometry and reduces interference with lanthanide-based antibody measurement. An error-detecting combinatorial barcoding scheme allows cell doublets to be identified and removed from the analysis. A debarcoding algorithm that is single cell-based rather than population-based improves the accuracy and efficiency of sample deconvolution. This debarcoding algorithm has been packaged into software that allows rapid and unbiased sample deconvolution. The MCB procedure takes 3–4 h, not including sample acquisition time of ~1 h per million cells.

Dengue virus (DENV) is the most prevalent mosquito-borne virus causing human disease. Of the 4 DENV serotypes, epidemiological data suggest that DENV-2 secondary infections are associated with more severe disease than DENV-4 infections. Mass cytometry by time-of-flight (CyTOF) was used to dissect immune changes induced by DENV-2 and DENV-4 in human DCs, the initial targets of primary infections that likely affect infection outcomes. Strikingly, DENV-4 replication peaked earlier and promoted stronger innate immune responses, with increased expression of DC activation and migration markers and increased cytokine production, compared with DENV-2. In addition, infected DCs produced higher levels of inflammatory cytokines compared with bystander DCs, which mainly produced IFN-induced cytokines. These high-dimensional analyses during DENV-2 and DENV-4 infections revealed distinct viral signatures marked by different replication strategies and antiviral innate immune induction in DCs, which may result in different viral fitness, transmission, and pathogenesis.

Atherosclerosis is a disease characterized by immune infiltration of the arterial wall in response to tissue damage and systemic inflammation. In the era of precision medicine, is essential to gain insights on immune contexture of atherosclerotic tissue taking into account disease-specific cell variation in patients. We applied high-dimensional technologies for the analysis of multiple parameters at the single-cell level in clinical samples of patients undergoing carotid endatherectomy (CEA, n=15). Using time-of-flight mass-cytometry (CyTOF), we simultaneously analyzed 32 parameters at the single-cell level in peripheral blood mononuclear cells (PBMCs) and atherosclerotic-tissue associated immune cells of the same patient. Using viSNE, we mapped single-cell heterogeneity into two dimensions to discriminate PBMCs and tissue-associated CD45+ immune cells. Next, we employed Phenograph to cluster cells into phenotypically related populations, which were annotated based on canonical marker expression patterns. We identified several major immune subsets including two subsets of macrophages (CD163 low and CD163 high ), monocytes, dendritic cells (DCs), B and T cells. The most prevalent CD45+ cells identified in atherosclerotic tissue were CD4 + (25.8%) and CD8 + (25.2%) T cells, macrophages (12.8%), monocytes (7.7%) and B (2.1%) cells. Using a regression analysis similar to that employed by CITRUS, we determined that macrophages and a subset of CD8 T cells characterized by low expression of CD127 were selectively enriched in tissue vs. blood. Multiplexed immunohistochemistry confirmed that T cells comprised a major portion of the CD45+ cells in atherosclerotic tissue, even more abundant than macrophages. This study of deep phenotyping across-atherosclerotic tissue and blood demonstrate a significant T cell tissue infiltration of a specific subset of CD8 T cells. This suggests that adaptive T cell immunity plays a critical role in advanced atherosclerosis. The extension of this systems biology analysis pipeline to larger datasets can improve our understanding of the core mechanisms of chronic inflammation in atherosclerosis.

High dimensional cytometry now allows measurement of over 50 parameters in a single sample, and is typically visualized using sophisticated dimensionality-reducing methods and analyzed with automated clustering algorithms. While these tools facilitate the identification and presentation of key findings, it remains challenging to effectively monitor and report the staining quality of individual markers. We present the Average Overlap Frequency (AOF), a simple and efficient metric to evaluate and quantify the robustness of staining and clustering quality in high-dimensional data. We leverage the AOF to compare and determine the optimal storage conditions for stained whole blood samples prior to mass cytometry analysis. We also show that the AOF can be easily incorporated as part of automated analysis pipelines in large scale immune monitoring studies and used to flag and exclude samples with poor staining quality. We propose that the AOF may be incorporated as an essential quality control metric to better identify and report the underlying sample quality in all CyTOF and other high-dimensional cytometry experiments.

Rotatable torsion angles are the major degrees of freedom in proteins. Adjacent angles are highly correlated and energy terms that rely on these correlations are intensively used in molecular modeling. However, the utility of torsion based terms is not yet fully exploited. Many of these terms do not capture the full scale of the correlations. Other terms, which rely on lookup tables, cannot be used in the context of force-driven algorithms because they are not fully differentiable. This study aims to extend the usability of torsion terms by presenting a set of high-dimensional and fully-differentiable energy terms that are derived from high-resolution structures. The set includes terms that describe backbone conformational probabilities and propensities, side-chain rotamer probabilities, and an elaborate term that couples all the torsion angles within the same residue. The terms are constructed by cubic spline interpolation with periodic boundary conditions that enable full differentiability and high computational efficiency. We show that the spline implementation does not compromise the accuracy of the original database statistics. We further show that the side-chain relevant terms are compatible with established rotamer probabilities. Despite their very local characteristics, the new terms are often able to identify native and native-like structures within decoy sets. Finally, force-based minimization of NMR structures with the new terms improves their torsion angle statistics with minor structural distortion (0.5 A RMSD on average). The new terms are freely available in the MESHI molecular modeling package. The spline coefficients are also available as a documented MATLAB file. Proteins 2008. © 2008 Wiley-Liss, Inc.

Summary While conventional pathogenic protists have been extensively studied, there is an underappreciated constitutive protist microbiota that is an integral part of the vertebrate microbiome. The impact of these species on the host and their potential contributions to mucosal immune homeostasis remain poorly studied. Here, we show that the protozoan Tritrichomonas musculis activates the host epithelial inflammasome to induce IL-18 release. Epithelial-derived IL-18 promotes dendritic cell-driven Th1 and Th17 immunity and confers dramatic protection from mucosal bacterial infections. Along with its role as a "protistic" antibiotic, colonization with T. musculis exacerbates the development of T-cell-driven colitis and sporadic colorectal tumors. Our findings demonstrate a novel mutualistic host-protozoan interaction that increases mucosal host defenses at the cost of an increased risk of inflammatory disease.

Despite recent advances in single-cell genomic, transcriptional, and mass-cytometric profiling, it remains a challenge to collect highly multiplexed measurements of secreted proteins from single cells for comprehensive analysis of functional states. Herein, we combine spatial and spectral encoding with polydimethylsiloxane (PDMS) microchambers for codetection of 42 immune effector proteins secreted from single cells, representing the highest multiplexing recorded to date for a single-cell secretion assay. Using this platform to profile differentiated macrophages stimulated with lipopolysaccharide (LPS), the ligand of Toll-like receptor 4 (TLR4), reveals previously unobserved deep functional heterogeneity and varying levels of pathogenic activation. Uniquely protein profiling on the same single cells before and after LPS stimulation identified a role for macrophage inhibitory factor (MIF) to potentiate the activation of LPS-induced cytokine production. Advanced clustering analysis identified functional subsets including quiescent, polyfunctional fully activated, partially activated populations with different cytokine profiles. This population architecture is conserved throughout the cell activation process and prevails as it is extended to other TLR ligands and to primary macrophages derived from a healthy donor. This work demonstrates that the phenotypically similar cell population still exhibits a large degree of intrinsic heterogeneity at the functional and cell behavior level. This technology enables full-spectrum dissection of immune functional states in response to pathogenic or environmental stimulation, and opens opportunities to quantify deep functional heterogeneity for more comprehensive and accurate immune monitoring.

Summary To guide the design of immunotherapy strategies for patients with early stage lung tumors, we developed a multiscale immune profiling strategy to map the immune landscape of early lung adenocarcinoma lesions to search for tumor-driven immune changes. Utilizing a barcoding method that allows a simultaneous single-cell analysis of the tumor, non-involved lung, and blood cells, we provide a detailed immune cell atlas of early lung tumors. We show that stage I lung adenocarcinoma lesions already harbor significantly altered T cell and NK cell compartments. Moreover, we identified changes in tumor-infiltrating myeloid cell (TIM) subsets that likely compromise anti-tumor T cell immunity. Paired single-cell analyses thus offer valuable knowledge of tumor-driven immune changes, providing a powerful tool for the rational design of immune therapies. Video Abstract

New high-dimensional, single-cell technologies offer unprecedented resolution in the analysis of heterogeneous tissues. However, because these technologies can measure dozens of parameters simultaneously in individual cells, data interpretation can be challenging. Here we present viSNE, a tool that allows one to map high-dimensional cytometry data onto two dimensions, yet conserve the high-dimensional structure of the data. viSNE plots individual cells in a visual similar to a scatter plot, while using all pairwise distances in high dimension to determine each cell's location in the plot. We integrated mass cytometry with viSNE to map healthy and cancerous bone marrow samples. Healthy bone marrow automatically maps into a consistent shape, whereas leukemia samples map into malformed shapes that are distinct from healthy bone marrow and from each other. We also use viSNE and mass cytometry to compare leukemia diagnosis and relapse samples, and to identify a rare leukemia population reminiscent of minimal residual disease. viSNE can be applied to any multi-dimensional single-cell technology.

Flow cytometry is an essential tool for dissecting the functional complexity of hematopoiesis. We used single-cell "mass cytometry" to examine healthy human bone marrow, measuring 34 parameters simultaneously in single cells (binding of 31 antibodies, viability, DNA content, and relative cell size). The signaling behavior of cell subsets spanning a defined hematopoietic hierarchy was monitored with 18 simultaneous markers of functional signaling states perturbed by a set of ex vivo stimuli and inhibitors. The data set allowed for an algorithmically driven assembly of related cell types defined by surface antigen expression, providing a superimposable map of cell signaling responses in combination with drug inhibition. Visualized in this manner, the analysis revealed previously unappreciated instances of both precise signaling responses that were bounded within conventionally defined cell subsets and more continuous phosphorylation responses that crossed cell population boundaries in unexpected manners yet tracked closely with cellular phenotype. Collectively, such single-cell analyses provide system-wide views of immune signaling in healthy human hematopoiesis, against which drug action and disease can be compared for mechanistic studies and pharmacologic intervention.

Rotatable torsion angles are the major degrees of freedom in proteins. Adjacent angles are highly correlated and energy terms that rely on these correlations are intensively used in molecular modeling. However, the utility of torsion based terms is not yet fully exploited. Many of these terms do not capture the full scale of the correlations. Other terms, which rely on lookup tables, cannot be used in the context of force-driven algorithms because they are not fully differentiable. This study aims to extend the usability of torsion terms by presenting a set of high-dimensional and fully-differentiable energy terms that are derived from high-resolution structures. The set includes terms that describe backbone conformational probabilities and propensities, side-chain rotamer probabilities, and an elaborate term that couples all the torsion angles within the same residue. The terms are constructed by cubic spline interpolation with periodic boundary conditions that enable full differentiability and high computational efficiency. We show that the spline implementation does not compromise the accuracy of the original database statistics. We further show that the side-chain relevant terms are compatible with established rotamer probabilities. Despite their very local characteristics, the new terms are often able to identify native and native-like structures within decoy sets. Finally, force-based minimization of NMR structures with the new terms improves their torsion angle statistics with minor structural distortion (0.5 A RMSD on average). The new terms are freely available in the MESHI molecular modeling package. The spline coefficients are also available as a documented MATLAB file.

It is now well appreciated that intra-tumor heterogeneity is of critical importance. There is remarkable molecular variability between and within populations of tumor cells, driven by both genetic and epigenetic variation. We address the challenge of identifying and characterizing tumor sub-populations through a combined experimental and computational approach. In two examples, we will demonstrate approaches to address each type of heterogeneity. Seventy percent of melanoma tumors have activated, and dependent on, MAPK pathway. However, the phenotypic response to MAPK inhibition is heterogeneous, both in vitro and in patients. While this heterogeneity is well characterized, we attempted to better understand its underlying mechanism. We used gene expression data both before and after pathway inhibition in a panel of cell lines to decipher the network structure under MAPK, and to identify network rewiring that contribute to the phenotypic response. To our surprise, the targets of the MAPK pathway vary dramatically between cell lines. We found that most targets are context-specific, regulated by MAPK only in a subset of samples. We therefore developed an algorithm to detect context-specific targets, and we used those targets to identify the pathways that are being regulated by MAPK. We found that NFkB and STAT3 activation status is correlated with apoptosis levels induced by MAPK inhibition. Furthermore, we show that they protect cells from the cytotoxic effects of MAPK inhibition. We employ mass cytometry, which accurately measures the expression and phosphorylation states of more than forty proteins in thousands of single cells, including surface proteins and signaling molecules. We present results on both healthy bone marrow and bone marrow from both ALL and AML patients. To understand abnormal, we first built a more accurate map of normal, modeling B-cell development in the marrow at unprecedented resolution. We measured 8 healthy marrows with 42 antibody parameters with mass cytometry targeting a multitude of phenotypic markers, intracellular signaling molecules, hallmarks of cell cycle and apoptosis all in the context of in vitro perturbations relevant to B cell development (including IL-7 and BCR crosslinking). We developed a graph based trajectory algorithm (wanderlust) that can trace a continuous progression from the hematopoietic stem cells, through the progenitor cells, to the final, committed B-cells. Our derived map of healthy B-cell development revealed the order and timing of developmental events at unprecedented resolution. The resulting multidimensional data was modeled using wanderlust and the predicted trajectory was then used to inform a traditional ‘gating’ analysis of the data and provide a higher resolution view of human B cell development than previously published. This healthy map was used to help provide a backbone on which to further understand how these trajectories are dysregulated in ALL. Citation Format: El-ad David Amir, Oren Litvin, Jacob Levine, Sean C. Bendall, Kara L. Davis, Erin F. Simonds, Tanya Schild, Mark Rocco, Neal Rosen, Garry P. Nolan, Dana Pe'er. Towards rationale therapy: Dealing with intertumor and intratumor heterogeneity. [abstract]. In: Proceedings of the Third AACR International Conference on Frontiers in Basic Cancer Research; Sep 18-22, 2013; National Harbor, MD. Philadelphia (PA): AACR; Cancer Res 2013;73(19 Suppl):Abstract nr IA30.

Acute myeloid leukemia (AML) can present with multiple concurrent subclones at diagnosis. Subclone-specific mutations may confer resistance to molecular-targeted drugs through loss of antigen expression or rewiring of intracellular signaling pathways, leading to relapse. Deep sequencing approaches improve the detection of rare subclones, but the ability to prospectively identify subclones (i.e. without relapse material) is limited, and the effects of subclone-specific mutations on phenotype are poorly understood. In the course of a broader study of oligoclonal pediatric AML patients, we focused investigation on a diagnosis bone marrow sample from a patient harboring 3 presumed subclones (two with distinct NRAS-G12D, NRAS-G13D mutations) as determined by whole-genome sequencing (WGS). We employed a combination of 31-parameter mass cytometry, deep sequencing, FACS sorting, and computational modeling to produce a detailed profile of the subclonal genotypes and phenotypes in this patient. The 3 anticipated subclones did not correlate with a clear subset of surface markers in the mass cytometry analysis. Instead, we observed a single continuous ‘differentiation trajectory’ from progenitor-like to monocyte-like blasts. To dissect this trajectory, 7 distinct myeloid/progenitor subsets were FACS-sorted, plus T/B cells as a non-leukemic control. For each subset we performed capture-based deep sequencing of 307 tumor-specific variants (Tier 1: 13; Tier 2: 33; Tier 3: 261; median depth: 1420x). Shifts in allele frequencies among the FACS-sorted subsets provided critical information to a Bayesian mixture modeling algorithm, allowing identification of 5 subclones, as opposed to the 3 subclones anticipated by WGS. The inferred subclonal genotypes were validated and further refined by targeted single-cell Sanger sequencing of multiple Tier 3 loci. Although all 5 subclones were present throughout the differentiation trajectory, some were enriched in certain phenotypic states or ‘reservoirs’. For example, the NRAS-G12D subclone was enriched in a progenitor-like subset, but its daughter subclone, which harbored an additional mutation in RAC2 (implicated in HSC engraftment), was enriched in the more differentiated subsets, suggesting an opposing effect. Notably, the T/B cell population harbored 2 tumor-specific Tier 1 mutations at >15% allele frequency, suggesting its presence in a preleukemic, multilineage-competent HSC. Taken together, subclone-specific mutations appear to skew cells toward either progenitor or mature phenotypes, but the developmental trajectory enforced by parental mutations is resistant to change. Furthermore, characterization of subclones is possible at diagnosis, and may improve the selection of targeted therapies. *Contributed equally: EFS, SCB & ALG Citation Format: Erin F. Simonds, Sean C. Bendall, Amanda L. Gedman, Jacob H. Levine, Kara L. Davis, Harris G. Fienberg, Astraea Jager, El-ad D. Amir, Ina Radtke, Wendy J. Fantl, Dana Pe'er, James R. Downing, Garry P. Nolan. Deep sequencing of immunophenotypically distinct subsets in acute myeloid leukemia reveals reservoirs of genetically distinct subclones along a conserved differentiation trajectory. [abstract]. In: Proceedings of the 104th Annual Meeting of the American Association for Cancer Research; 2013 Apr 6-10; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2013;73(8 Suppl):Abstract nr 3178. doi:10.1158/1538-7445.AM2013-3178

Abstract 1451 Simultaneously examining multiple epitopes in single cells has become increasingly useful as improvements are made to multi-parametric flow techniques. Increased parameterization has enabled subdivision of functionally distinct cell populations based on an increasing variety of physiological attributes. It has not only helped better define the landscape of “normal” hematopoiesis, but also has been clinically applied in detection of minimal residual disease (MRD) in hematopoietic malignancies. Detection of rare “abnormal” cells is the crux of MRD-based risk stratification where sporadic residual cancer cells are identified through multi-parameter flow cytometry. Current methods for the detection and characterization of cellular populations are generally reliant on manual examination and targeted gating techniques. This approach relies almost entirely on prior knowledge and leaves little room for discovery of novel populations. As the number of parameter per cell increases there is a rising need for dimensionality reduction (DR) methods to resolve high dimensional data “down” into a human-interpretable space. Classical DR, such as principle component analysis (PCA), fail to address the non-linear relationships in cellular phenotypes while newer approaches, such as spanning-tree progression of density normalized events (SPADE), have an inherent level of stochasticity that might adversely affect the robust separation of cellular phenotypes (i.e. discriminating healthy vs. diseased cells). Here, we present a novel algorithm that identifies and characterizes distinct cell populations, preserving the high dimensional information, but providing an interpretable visualization of their phenotypic relationships. This approach was applied to a cohort of normal human bone marrow (BM) specimens to discern a landscape of normal hematopoietic phenotypes. We then contrasted this to overlays of human leukemic bone marrow aspirates (AML and ALL) to understand the extent to which cancer corrupts the shape and form of the landscape. We illustrate the application for automated MRD detection in human leukemia (Figure 1). Method: Our approach, CellSNE, is an adaptation of t-Distributed Stochastic Neighbor Embedding (t-SNE), a non-linear dimensionality reduction algorithm. CellSNE finds a low dimensional mapping of cells that preserves their pairwise distances in a high dimensional space. A distance between each cell to every other cell in the dataset is calculated, based on a vector defined by the combined values of cellular parameters measure. An optimization algorithm then searches for a projection of the points into 2D, in such a way that maximizes the similarity in pairwise distances between the high-dimensional and two dimensional spaces. The resulting 2D projection organizes the sample into subpopulations that conserve the shape and relative distances between each cell. Results/Conclusion: Application of CellSNE to healthy BM clearly separated cells based on their known immune subtype and was confirmed by manual analysis (Figure 1A). The results are robust across data collected from different individuals on different days as well as in analyses conducted using low numbers of single cell parameters, suggesting that healthy BM generally maintains the same cellular population characteristics (or “shape”) across samples. When applied to leukemic BM from patients with AML and ALL CellSNE demonstrates a unique cancer landscape (“shape”) for each patient that is dramatically different from normal (Figure 1B). It is critical to note that despite the overwhelming infiltration by cancer cells, rare “normal” cell populations can still be discerned in the ALL BM. CellSNE succeeded in automatically identifying rare ( Disclosures: No relevant conflicts of interest to declare.

Abstract 2565 Acute myeloid leukemia (AML) encompasses a broad spectrum of cellular morphologies. This spectrum exists both within each patient in the form of a malignant developmental hierarchy, and across patients in the form of distinct disease classes with distinguishing mutational or pathological hallmarks. Flow cytometry has long been an essential tool for classifying AML surface markers, and has enabled improved diagnosis, minimal residual disease monitoring, and cell sorting for functional studies. Previous work by our laboratory and others (Irish et al., Cell 2004; Kornblau et al., Clin. Cancer Res. 2010) has shown that clinically relevant heterogeneity also exists at the level of single-cell intracellular signaling capabilities, particularly in response to ex vivo perturbations. Due to the constraints of fluorescent flow cytometry, the limited number of simultaneous parameters measured per cell in these studies was limited (e.g., 3–6). We hypothesized that there may exist additional layers of heterogeneity in both surface marker phenotypes and signaling responses which were invisible to the low-parameter systems used in these studies. To address this challenge, we used a next-generation 31-parameter ‘mass cytometry’ platform to survey the diversity of signaling responses and their relationship to subsets defined by surface marker patterns. We measured the simultaneous co-expression of 16 surface markers and 15 dynamic intracellular signaling epitopes (e.g. phosphorylated kinase substrates) in a cohort of pediatric AML diagnosis bone marrow samples (n=18) and healthy adult bone marrow controls (n=3). Signaling dynamics were measured under 18 stimulation conditions, including a battery of cytokines, chemical stimuli, and small molecule kinase inhibitors. The resulting single-cell data was overlaid and compared using a new, unsupervised flow cytometry analysis and visualization program–SPADE (Spanning-tree Progression Analysis of Density-Normalized Events)–which links rare, transitional, and abundant cell types alike along a branching tree organized by phenotypic progression. Thus, we distilled the diversity of cellular phenotypes, their relative frequencies, and the corresponding signaling dynamics of each cell population onto a single graph structure representing the distinct and overlapping expression patterns in the 16-dimensional “immunophenotypic space” explored by the 21 individuals. Striking signaling and immunophenotypic diversity was observed between the AML samples, particularly in response to pervanadate stimulation. Pervanadate liberates intracellular kinase cascades by broadly inhibiting tyrosine phosphatases, and thus reveals the cell's potential for kinase activity and the interplay of signaling circuits in different cell populations. Interestingly, two transcription factors implicated in AML pathogenesis – CREB and c-Cbl–often exhibited mutually exclusive phosphorylation patterns in different subsets of primitive (CD34+) cells. Specifically, CREB was readily phosphorylated at Ser133 upon pervanadate exposure in the CD34+CD123- cells, while c-Cbl phosphorylation at Tyr700 was restricted to CD34+CD123+ cells. As CD123 (IL-3Ra) has been implicated as a marker of AML stem cells, the finding that these cells are poised for c-Cbl signaling may suggest a potential therapeutic avenue. This work demonstrates the utility of 31-parameter mass cytometry for the simultaneous characterization of multiple cancer stem cell markers and comparison of their expression patterns to the normal tissue hierarchy. These results will inform future studies of AML signaling biology, prognostic biomarkers, and indicators of minimum residual disease. EFS and SCB contributed equally to this work. Disclosures: No relevant conflicts of interest to declare.

SummaryTissue regeneration is an orchestrated progression of cells from an immature state to a mature one, conventionally represented as distinctive cell subsets. A continuum of transitional cell states exists between these discrete stages. We combine the depth of single-cell mass cytometry and an algorithm developed to leverage this continuum by aligning single cells of a given lineage onto a unified trajectory that accurately predicts the developmental path de novo. Applied to human B cell lymphopoiesis, the algorithm (termed Wanderlust) constructed trajectories spanning from hematopoietic stem cells through to naive B cells. This trajectory revealed nascent fractions of B cell progenitors and aligned them with developmentally cued regulatory signaling including IL-7/STAT5 and cellular events such as immunoglobulin rearrangement, highlighting checkpoints across which regulatory signals are rewired paralleling changes in cellular state. This study provides a comprehensive analysis of human B lymphopoiesis, laying a foundation to apply this approach to other tissues and “corrupted” developmental processes including cancer.