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Mass-tag cell barcoding has increased the throughput, multiplexing, and robustness of multiple cytometry approaches. Previously, we adapted mass cytometry for cells to analyze synaptosome preparations (mass synaptometry or SynTOF), extending mass cytometry to these smaller, anuclear particles. To improve throughput and individual event resolution, we report here the application of palladium-based barcoding in human synaptosomes. Up to 20 individual samples, each with a unique combinatorial barcode, were pooled for labeling with an antibody cocktail. Our synaptosome protocol used six palladium-based barcoding reagents, and in combination with sequential gating increased the identification of presynaptic events approximately 4-fold. These same parameters also efficiently resolved two other anuclear particles: human red blood cells (RBCs) and platelets. The addition of palladium-based mass-tag barcoding to our approach improves mass cytometry of synaptic particles.

Summary Immune checkpoint blockade using PD-1 inhibition is an effective approach for treating a wide variety of cancer subtypes. While lower gastrointestinal (GI) side effects are more common, upper gastrointestinal adverse events are rarely reported. Here, we present a case of nivolumab-associated autoimmune gastritis. To elucidate the immunology underlying this condition, we leverage multiplexed ion beam imaging by time-of-flight (MIBI-TOF) to identify the presence and proportion of infiltrating immune cells from a single section of biopsy specimen. Using MIBI-TOF, we analyze formalin-fixed, paraffin-embedded human gastric tissue with 28 labels simultaneously. Our analyses reveal a gastritis characterized by severe mucosal injury, interferon gamma (IFN-γ)-producing gastric epithelial cells, and mixed inflammation that includes CD8 and CD4 T cell infiltrates with reduced expression of granzyme B and FOXP3, respectively. Here, we provide a comprehensive multiplexed histopathological mapping of gastric tissue, which identifies IFN-γ-producing epithelial cells as possible contributors to the nivolumab-associated gastritis., Graphical abstract, Highlights Multiplexed imaging of gastric toxicity associated with anti-PD-1 immunotherapy Analysis reveals severe mucosal injury associated with IFN-γ-expressing epithelial cells Inflamed gastric epithelium is accompanied by mixed infiltration of CD4 and CD8 T cells, Ferrian et al. leverage multiplexed ion beam imaging by time-of-flight to characterize a case of anti-PD-1-associted autoimmune gastritis. This study reveals gastritis characterized by severe mucosal injury, IFN-γ-producing gastric epithelial cells, and inflammation that includes CD8 and CD4 T cell infiltrates with reduced expression of granzyme B and FOXP3, respectively.

SummaryγδT cells contribute to host immune defense uniquely; but how they function in different stages (e.g., acute versus chronic) of a specific infection remains unclear. As the role ofγδT cells in early, activeMycobacterium tuberculosis(Mtb) infection is well documented, we focused on elucidating theγδT cell response in persistent or controlled Mtb infection. Systems analysis of circulatingγδT cells from a South African adolescent cohort identified a distinct population of CD8+γδT cells that expanded in this state. These cells had features indicative of persistent antigenic exposure but were robust cytolytic effectors and cytokine/chemokine producers. While theseγδT cells displayed an attenuated response to TCR-mediated stimulation, they expressed Natural Killer (NK) cell receptors and had robust CD16 (FcγRIIIA)-mediated cytotoxic response, suggesting alternative ways forγδT cells to control this stage of the infection. Despite this NK- like functionality, the CD8+γδT cells consisted of highly expanded clones, which utilized TCRs with different Vγ/δpairs. Theses TCRs could respond to an Mtb-lysate, but not to phosphoantigens, which are components of Mtb-lysate that activateγδT cells in acute Mtb infection, indicating that the CD8+γδT cells were induced in a stage-specific, antigen-driven manner. Indeed, trajectory analysis showed that theseγδT cells arose from naive cells that had traversed distinct differentiation paths in this infection stage. Importantly, increased levels of CD8+γδT cells were also found in other chronic inflammatory conditions, including cardiovascular disease and cancer, suggesting that persistent antigenic exposure may lead to similarγδT cell responses.

Regulatory B cells (Bregs) can suppress immune responses through the secretion of IL-10 and other anti-inflammatory cytokines. This immunomodulatory capacity holds therapeutic potential, yet a definitional immunophenotype for enumeration and prospective isolation of B cells capable of IL-10 production remains elusive. We therefore applied mass cytometry to simultaneously quantify cytokine production and immunophenotype in human peripheral B cells across a range of stimulatory conditions and timepoints. While multiple B cell subsets produced IL-10, no phenotype uniquely identified IL-10+ B cells and a significant portion of IL-10+ B cells co-expressed the proinflammatory cytokines IL-6 and TNFα. Despite this heterogeneity, we found operationally tolerant liver transplant recipients had a unique enrichment of IL-10+, but not TNFα+ or IL-6+, B cells as compared to transplant recipients receiving immunosuppression. Thus, human IL-10-producing B cells constitute an induced, transient state arising from a diversity of B cell subsets that may contribute to maintenance of immune homeostasis.

Alzheimer’s disease (AD) differentially and specifically affects brain regions and neuronal cell types in a predictable pattern. Damage to the brain appears to spread and worsens with time, taking over more regions and activating multiple stressors that can converge to promote vulnerability of certain cell types. At the same time, other cell types and brain regions remain intact in the face of this onslaught of neuropathology. Although neuropathologic descriptions of AD have been extensively expanded and mapped over the last several decades, our understanding of the mechanisms underlying how certain regions and cell populations are specifically vulnerable or resistant has lagged behind. In this review, we detail what is known about the selectivity of local initiation of AD pathology in the hippocampus, its proposed spread via synaptic connections, and the diversity of clinical phenotypes and brain atrophy patterns that may arise from different fibrillar strains of pathologic proteins or genetic predispositions. We summarize accumulated and emerging knowledge of the cellular and molecular basis for neuroanatomic selectivity, consider potential disease-relevant differences between vulnerable and resistant neuronal cell types and isolate molecular markers to identify them.

Cellular products derived from the activity of DNA, RNA, and protein synthesis collectively control cell identity and function. Yet there is little information on how these three biosynthesis activities are coordinated during transient and sparse cellular processes, such as activation and differentiation. Here, we describe Simultaneous Overview of tri-Molecule Biosynthesis (SOM3B), a molecular labeling and simultaneous detection strategy to quantify DNA, RNA, and protein synthesis in individual cells. Comprehensive interrogation of biosynthesis activities during transient cell states, such as progression through cell cycle or cellular differentiation, is achieved by partnering SOM3B with parallel quantification of select biomolecules with conjugated antibody reagents. Here, we investigate differential de novo DNA, RNA, and protein synthesis dynamics in transformed human cell lines, primary activated human immune cells, and across the healthy human hematopoietic continuum, all at a single-cell resolution., Simultaneous quantification of DNA, RNA and protein at the single cell level has not yet been possible. Here the authors introduce a molecular labelling and detection strategy to quantify synthesis of these biomolecules and couple it to transient cell states through parallel quantification of state-dependent biomolecules.

Selective differentiation of naive T cells into multipotent T cells is of great interest clinically for the generation of cell-based cancer immunotherapies. Cellular differentiation depends crucially on division state and time. Here we adapt a dye dilution assay for tracking cell proliferative history through mass cytometry and uncouple division, time and regulatory protein expression in single naive human T cells during their activation and expansion in a complex ex vivo milieu. Using 23 markers, we defined groups of proteins controlled predominantly by division state or time and found that undivided cells account for the majority of phenotypic diversity. We next built a map of cell state changes during naive T-cell expansion. By examining cell signaling on this map, we rationally selected ibrutinib, a BTK and ITK inhibitor, and administered it before T cell activation to direct differentiation toward a T stem cell memory (TSCM)-like phenotype. This method for tracing cell fate across division states and time can be broadly applied for directing cellular differentiation.

Background Synaptic alterations, especially presynaptic changes, are cardinal features of neurodegenerative diseases and strongly correlate with cognitive decline. New method We report “Mass Synaptometry” for the high-dimensional analysis of individual human synaptosomes, enriched nerve terminals from brain. This method was adapted from cytometry by time-of-flight mass spectrometry (CyTOF), which is commonly used for single-cell analysis of immune and blood cells. Result Here we overcome challenges for single synapse analysis by optimizing synaptosome preparations, generating a ‘SynTOF panel,’ recalibrating acquisition settings, and applying computational analyses. Through the analysis of 390,000 individual synaptosomes, we also provide proof-of principle validation by characterizing changes in synaptic diversity in Lewy Body Disease (LBD), Alzheimer’s disease and normal brain. Comparison with existing method(s) Current imaging methods to study synapses in humans are capable of analyzing a limited number of synapses, and conventional flow cytometric techniques are typically restricted to fewer than 6 parameters. Our method allows for the simultaneous detection of 34 parameters from tens of thousands of individual synapses. Conclusion We applied Mass Synaptometry to analyze 34 parameters simultaneously on more than 390,000 synaptosomes from 13 human brain samples. This new approach revealed regional and disease-specific changes in synaptic phenotypes, including validation of this method with the expected changes in the molecular composition of striatal dopaminergic synapses in Lewy body disease and Alzheimer’s disease. Mass synaptometry enables highly parallel molecular profiling of individual synaptic terminals.

The immune system and placenta have a dynamic relationship across gestation to accommodate fetal growth and development. High-resolution characterization of this maternal- fetal interface is necessary to better understand the immunology of pregnancy and its complications. We developed a single-cell framework to simultaneously immuno-phenotype circulating, endovascular, and tissue-resident cells at the maternal-fetal interface throughout gestation, discriminating maternal and fetal contributions. Our data reveal distinct immune profiles across the endovascular and tissue compartments with tractable dynamics throughout gestation that respond to a systemic immune challenge in a gestationally-dependent manner. We uncover that mononuclear phagocytes and neutrophils drive the temporal immune composition of the placenta with remarkably diverse populations, including PD-L1-expressing subsets having compartmental and early gestational bias. Our approach and accompanying datasets provide a resource for additional investigations into gestational immunology and evoke a more significant role for the innate immune system in establishing the microenvironment of early pregnancy.Abstract Figure

Description, Multiplex single-synapse events from multiple regions of Alzheimer’s disease brain revealed new alterations unique to humans., Synaptic molecular characterization is limited for Alzheimer’s disease (AD). Our newly invented mass cytometry–based method, synaptometry by time of flight (SynTOF), was used to measure 38 antibody probes in approximately 17 million single-synapse events from human brains without pathologic change or with pure AD or Lewy body disease (LBD), nonhuman primates (NHPs), and PS/APP mice. Synaptic molecular integrity in humans and NHP was similar. Although not detected in human synapses, Aβ was in PS/APP mice single-synapse events. Clustering and pattern identification of human synapses showed expected disease-specific differences, like increased hippocampal pathologic tau in AD and reduced caudate dopamine transporter in LBD, and revealed previously unidentified findings including increased hippocampal CD47 and lowered DJ1 in AD and higher ApoE in AD with dementia. Our results were independently supported by multiplex ion beam imaging of intact tissue. This highlights the higher depth and breadth of insight on neurodegenerative diseases obtainable through SynTOF.

Purpose: Immunoprofiling to identify biomarkers and integration with clinical trial outcomes are critical to improving immunotherapy approaches for patients with cancer. However, the translational potential of individual studies is often limited by small sample size of trials and the complexity of immuno-oncology biomarkers. Variability in assay performance further limits comparison and interpretation of data across studies and laboratories. Experimental Design: To enable a systematic approach to biomarker identification and correlation with clinical outcome across trials, the Cancer Immune Monitoring and Analysis Centers and Cancer Immunologic Data Commons (CIMAC-CIDC) Network was established through support of the Cancer MoonshotSM Initiative of the National Cancer Institute (NCI) and the Partnership for Accelerating Cancer Therapies (PACT) with industry partners via the Foundation for the NIH. Results: The CIMAC-CIDC Network is composed of four academic centers with multidisciplinary expertise in cancer immunotherapy that perform validated and harmonized assays for immunoprofiling and conduct correlative analyses. A data coordinating center (CIDC) provides the computational expertise and informatics platforms for the storage, integration, and analysis of biomarker and clinical data. Conclusions: This overview highlights strategies for assay harmonization to enable cross-trial and cross-site data analysis and describes key elements for establishing a network to enhance immuno-oncology biomarker development. These include an operational infrastructure, validation and harmonization of core immunoprofiling assays, platforms for data ingestion and integration, and access to specimens from clinical trials. Published in the same volume are reports of harmonization for core analyses: whole-exome sequencing, RNA sequencing, cytometry by time of flight, and IHC/immunofluorescence.

Ductal carcinomain situ(DCIS) is a pre-invasive lesion that is thought to be a precursor to invasive breast cancer (IBC). To understand how the tumor microenvironment (TME) changes with transition to IBC, we used Multiplexed Ion Beam Imaging by time of flight (MIBI-TOF) and a 37-plex antibody staining panel to analyze 140 clinically annotated surgical resections covering the full spectrum of breast cancer progression. We compared normal, DCIS, and IBC tissues using machine learning tools for multiplexed cell segmentation, pixel-based clustering, and object morphometrics. Transition from DCIS to IBC was found to occur along a trajectory marked by coordinated shifts in location and function of myoepithelium, fibroblasts, and infiltrating immune cells in the surrounding stroma. Taken together, this comprehensive study within the HTAN Breast PreCancer Atlas offers insight into the etiologies of DCIS, its transition to IBC, and emphasizes the importance of the TME stroma in promoting these processes.

Innate pattern recognition receptor agonists, including Toll-like receptors (TLRs), alter the tumor microenvironment and prime adaptive antitumor immunity. However, TLR agonists present toxicities associated with widespread immune activation after systemic administration. To design a TLR-based therapeutic suitable for systemic delivery and capable of safely eliciting tumor-targeted responses, we developed immune-stimulating antibody conjugates (ISACs) comprising a TLR7/8 dual agonist conjugated to tumor-targeting antibodies. Systemically administered human epidermal growth factor receptor 2 (HER2)-targeted ISACs were well tolerated and triggered a localized immune response in the tumor microenvironment that resulted in tumor clearance and immunological memory. Mechanistically, ISACs required tumor antigen recognition, Fcγ-receptor-dependent phagocytosis and TLR-mediated activation to drive tumor killing by myeloid cells and subsequent T-cell-mediated antitumor immunity. ISAC-mediated immunological memory was not limited to the HER2 ISAC target antigen since ISAC-treated mice were protected from rechallenge with the HER2− parental tumor. These results provide a strong rationale for the clinical development of ISACs. Alonso and colleagues develop immune-stimulating antibody conjugates capable of specific delivery of TLR7/8 agonists to tumors, which induces durable antitumor immunity.

Background Immune stimulating antibody conjugates (ISACs) covalently attach TLR7/8 immune stimulants to tumor-targeting antibodies. ISACs can be delivered systemically and act locally in the tumor microenvironment by requiring the following biological steps to elicit immune activation: 1) tumor antigen recognition, 2) Fc receptor mediated phagocytosis by myeloid antigen presenting cells (APCs), and 3) activation of endosomal TLR7 and TLR8. Here, we demonstrate that covalent attachment of our TLR7/8 agonist to tumor-targeting antibodies not only enables the resulting ISACs to be safely administered systemically in preclinical models, but also unexpectedly promotes synergy between the FcgR and TLR pathways that results in amplified anti-tumor immunity in mice and robust immune activation in human leukocytes as compared to the co-administration of the components. Methods ISAC activity and mechanistic studies were analyzed via flow cytometry, ELISA and CyTOF following in vitro coculture of human leukocytes with tumor cell lines. In vivo efficacy of HER2-targeting ISACs following systemic administration was assessed in a trastuzumab-resistant HER2+ human tumor xenograft model. Safety and tolerability were assessed in tumor-bearing mice and healthy non-human primates (NHP). Results While co-administration of intratumoral TLR7/8 agonist and intraperitoneal trastuzumab failed to control tumor growth, systemic administration of the same TLR7/8 agonist and trastuzumab in our ISAC format was efficacious and induced complete tumor regression in an Fc- and TLR-dependent manner. Analysis of primary human leukocytes stimulated with ISACs in tumor co-culture assays indicated that ISACs elicit amplified and sustained phosphorylation of Fc and TLR signaling pathways, such as pERK1/2 and pIRF-7, as compared to the unconjugated mixture of the same TLR7/8 agonist and tumor targeted antibody. ISAC stimulation was largely restricted to antigen presenting cells such as dendritic cells and plasmacytoid dendritic cells that express the relevant Fc receptors and TLR7 and/or TLR8. Modifications to the ISAC that reduce FcgR engagement (N297A/Q) or render the agonist inactive halted ISAC-mediated activation and in vivo anti-tumor efficacy. Lastly, our HER2-targeting ISACs were well-tolerated when delivered systemically in mice and NHPs. Conclusions Our ISACs enable potent TLR agonists to be safely administered systemically in preclinical models. ISACs provide distinct and unexpected advantages over unconjugated TLR agonists, notably by driving synergy between FcgR and TLR pathways, leading to robust myeloid activation and anti-tumor efficacy. These data support the evaluation of BDC-1001, a HER2-targeted ISAC in the ongoing Phase 1/2 trial (NCT04278144).

Background Sipuleucel-T (Provenge) is the first therapeutic vaccination approved by the FDA so far, indicated for advanced metastatic prostate cancer patients. Despite an improvement of the overall survival, the benefits of the therapy are still short-term so increasing the duration of the efficacy is necessary. Specifically, T-cell anergy is one of the challenges that we need to overcome to improve the overall efficacy. IL-7 is known to promote the naive T cell activation and to increase the proliferation and activation of the T cell memory subsets. Therefore, in this phase II clinical trial, we tested the therapeutic potential of a human recombinant glycosylated IL-7 after completion of the Provenge therapy on asymptomatic advanced prostate cancer patients. Methods To get a comprehensive analysis of the immune landscape in these patients, we performed CyTOF analysis on PBMC samples obtained at week 1 (baseline) and week 6 after the beginning of the IL-7 therapy. After stimulation with PMA/Ionomycin, we proceeded to surface and intracellular cytokine staining before acquisition on the CyTOF. The data were then analyzed by expert gating on Cytobank. Results At 6 weeks post therapy, our data showed an increase in the number of circulating T lymphocytes in the IL-7 cohort, especially CD8 T cells, in accordance with previous literature. Even though of the frequency of CD4 T cells did not increase, the cells showed greater functionalities, with increased expression of IL-2, TNFα and IL-6 upon stimulation by PMA-Ionomycine. Cytotoxic subsets were also positively affected, with increased expression of IFNγ in CD8 T cells, TNFα in NK cells and IL-2 in γδ T cells. Moreover, PD-1 expression was decreased on CD4, CD8 and γδ T cells while CD137 increased on CD4, CD8 and NK cells. In addition, despite a reduction in the pool of circulating monocytes, we observed higher TNFα expression in these cells. Conclusions Altogether, our data revealed multiple effects of IL-7 in these patients, highlighting a complex set of in vivo mechanisms. In the future, knowledge of these effects may help in choosing the best agents to use in combination with IL-7 and/or the best patients to benefit from IL-7 as part of their therapeutic approach. Trial Registration NCT01881867 Ethics Approval The study was last approved by Fred Hutchinson Cancer Research Center Institutional Review Board, IR file 8037, on January 23, 2020

Summary Basophils, the rarest granulocyte, play critical roles in parasite- and allergen-induced inflammation. We applied mass cytometry (CyTOF) to simultaneously asses 44 proteins to phenotype and functionally characterize neutrophils, eosinophils, and basophils from 19 healthy donors. There was minimal heterogeneity seen in eosinophils and neutrophils, but data-driven analyses revealed four unique subpopulations within phenotypically basophilic granulocytes (PBG; CD45+HLA-DR−CD123+). Through CyTOF and fluorescence-activated cell sorting (FACS), we classified these four PBG subpopulations as (I) CD16lowFcεRIhighCD244high (88.5 ± 1.2%), (II) CD16highFcεRIhighCD244high (9.1 ± 0.4%), (III) CD16lowFcεRIlowCD244low (2.3 ± 1.3), and (IV) CD16highFcεRIlowCD244low (0.4 ± 0.1%). Prospective isolation confirmed basophilic-morphology of PBG I–III, but neutrophilic-morphology of PBG IV. Functional interrogation via IgE-crosslinking or IL-3 stimulation demonstrated that PBG I–II had significant increases in CD203c expression, whereas PBG III–IV remained unchanged compared with media-alone conditions. Thus, PBG III–IV could serve roles in non-IgE-mediated immunity. Our findings offer new perspectives in human basophil heterogeneity and the varying functional potential of these new subsets in health and disease., Graphical Abstract, Highlights • Unsupervised clustering revealed 4 basophil populations, driven by CD16, CD244, and FcεRI • The rarest basophil subpopulation IV was morphologically neutrophils • Anti-IgE and IL-3 stimulation did not induce functional responses in III and IV • Basophil subpopulation heterogeneity was observed in healthy and CML samples, Immunology; Systems Biology

Tuberculosis (TB) is an infectious disease caused byMycobacterium tuberculosisthat is distinctly characterized by granuloma formation within infected tissues. Granulomas are dynamic and organized immune cell aggregates that limit dissemination, but can also hinder bacterial clearance. Consequently, outcome in TB is influenced by how granuloma structure and composition shift the balance between these two functions. To date, our understanding of what factors drive granuloma function in humans is limited. With this in mind, we used Multiplexed Ion Beam Imaging by Time-of-Flight (MIBI-TOF) to profile 37 proteins in tissues from thirteen patients with active TB disease from the U.S. and South Africa. With this dataset, we constructed a comprehensive tissue atlas where the lineage, functional state, and spatial distribution of 19 unique cell subsets were mapped onto eight phenotypically-distinct granuloma microenvironments. This work revealed an immunosuppressed microenvironment specific to TB granulomas with spatially coordinated co-expression of IDO1 and PD-L1 by myeloid cells and proliferating regulatory T cells. Interestingly, this microenvironment lacked markers consistent with T-cell activation, supporting a myeloid-mediated mechanism of immune suppression. We observed similar trends in gene expression of immunoregulatory proteins in a confirmatory transcriptomic analysis of peripheral blood collected from over 1500 individuals with latent or active TB infection and healthy controls across 29 cohorts spanning 14 countries. Notably, PD-L1 gene expression was found to correlate with TB progression and treatment response, supporting its potential use as a blood-based biomarker. Taken together, this study serves as a framework for leveraging independent cohorts and complementary methodologies to understand how local and systemic immune responses are linked in human health and disease.

Diagnosing lymphomas and leukemias requires challenging integration of microscopically-visible cellular morphology and antibody-identified cell type-specific molecule expression. Here, we merge these orthogonal techniques onto a single, high-throughput, highly-multiplexed, single cell assay. Using single cell mass cytometry, we simultaneously quantify 12 molecular components underlying cell morphological features with a multitude of phenotypes across 71 diverse hematologic diagnoses. This method, “single cell morphometric profiling,” reveals robust patterns of “morphometric” markers for each microscopically-identifiable cell type, distinct from other cell lineages. Individual features have particular diagnostic utilities, such as: VAMP-7 for flow cytometric side scatter; lamin B1 and rRNA highlighting progenitor populations comprising acute leukemias; and lamin A/C distinguishing mature T-cell lymphomas from normal T-cells. Computationally combined with machine learning, they form consistent two-dimensional maps for visualizing sample composition and tracing differentiation of normal and leukemic myeloid cells. Benchmarking against hematopathologists, we used morphometric machine learning for blast enumeration in myeloid leukemias – a classically difficult problem with existing technologies. Integrating morphometry with deep surface immunophenotyping yields a versatile platform amendable to both traditional cytometry plots and high-dimensional augmentation with new diagnostic capabilities, lending itself to automation for routine, systematic hematopathology diagnosis.

SummaryCellular metabolism regulates immune cell activation, differentiation and effector functions to the extent that its perturbation can augment immune responses. However, the analytical technologies available to study cellular metabolism lack single-cell resolution, obscuring metabolic heterogeneity and its connection to immune phenotype and function. To that end, we utilized high-dimensional, antibody-based technologies to simultaneously quantify the single-cell metabolic regulome in combination with phenotypic identity. Mass cytometry (CyTOF)-based application of this approach to early human T cell activation enabled the comprehensive reconstruction of the coordinated metabolic remodeling of naïve CD8+T cells and aligned with conventional bulk assays for glycolysis and oxidative phosphorylation. Extending this analysis to a variety of tissue-resident immune cells revealed tissue-restricted metabolic states of human cytotoxic T cells, including metabolically repressed subsets that expressed CD39 and PD1 and that were enriched in colorectal carcinoma versus healthy adjacent tissue. Finally, combining this approach with multiplexed ion beam imaging by time-of-flight (MIBI-TOF) demonstrated the existence of spatially enriched metabolic neighborhoods, independent of cell identity and additionally revealed exclusion of metabolically repressed cytotoxic T cell states from the tumor-immune boundary in human colorectal carcinoma. Overall, we provide an approach that permits the robust approximation of metabolic states in individual cells along with multimodal analysis of cell identity and functional characteristics that can be applied to human clinical samples to study cellular metabolism how it may be perturbed to affect immunological outcomes.

Insight into the cancer cell populations that are responsible for relapsed disease is needed to improve outcomes. Here we report a single-cell-based study of B cell precursor acute lymphoblastic leukemia at diagnosis that reveals hidden developmentally dependent cell signaling states that are uniquely associated with relapse. By using mass cytometry we simultaneously quantified 35 proteins involved in B cell development in 60 primary diagnostic samples. Each leukemia cell was then matched to its nearest healthy B cell population by a developmental classifier that operated at the single-cell level. Machine learning identified six features of expanded leukemic populations that were sufficient to predict patient relapse at diagnosis. These features implicated the pro-BII subpopulation of B cells with activated mTOR signaling, and the pre-BI subpopulation of B cells with activated and unresponsive pre-B cell receptor signaling, to be associated with relapse. This model, termed 'developmentally dependent predictor of relapse' (DDPR), significantly improves currently established risk stratification methods. DDPR features exist at diagnosis and persist at relapse. By leveraging a data-driven approach, we demonstrate the predictive value of single-cell 'omics' for patient stratification in a translational setting and provide a framework for its application to human cancer.

Despite improvements in overall survival for children with B-cell progenitor acute lymphoblastic leukemia (BCP-ALL), it remains the second-leading cause of cancer related death in children with approximately 200 deaths per year in the U.S. Thus, there remains a critical need for a definitive cure to prevent relapse for patients with BCP ALL. The accumulation of BCP ALL blasts results from the disruption of normal developmental checkpoints. One of these checkpoints, as pro-B cells transition to become pre-B cells, involves surface expression of the precursor-B-cell receptor (pre-BCR). Prior work has categorized BCP ALL into pre-BCR positive and pre-BCR negative subtypes based on the protein expression of Ig light chain and active signaling of SRC family kinases, SYK, BTK. Combining single cell analysis and machine learning, we previously identified pre-B cells with activation of pre-BCR signaling, namely CREB, 4EBP1, rpS6 and SYK, that are present at diagnosis and highly predictive of relapse. We call these relapse predictive cells. Relapse predictive cells were enriched in relapse samples, demonstrating their persistence from diagnosis to relapse and making them an actionable target to prevent relapse altogether. To better understand relapse predictive cells, we enriched pre-B cells from patients with known relapse status and performed whole transcriptome sequencing. Relapse predictive cells demonstrated significant upregulation of genes in the oxidative phosphorylation (OXPHOS), glycolysis, and reactive oxygen species (ROS) pathways compared to pre-B-like leukemia cells from patients who will not go on to relapse. Analysis of public genome-wide CRISPR screen datasets in 2 pre-BCR+ and 4 pre-BCR- cell lines found 69 essential genes uniquely present in pre-BCR+ cell lines, related to mitochondria translation, OXPHOS and TCA cycle pathway. We performed CRISPR knock down of proximal pre-BCR related tyrosine kinase SYK in pre-BCR+ (Nalm6, Kasumi-2) and pre-BCR- (697, REH, SUPB15) cell lines to understand how activated pre-BCR impacts cellular metabolism in pre-BCR+ and pre-BCR- cells. CyTOF analysis of pre-BCR signaling demonstrated effective inhibition of downstream pre-BCR pathway members in the KD cells (pSYK, pBLNK, pBTK). RNA sequencing demonstrated upregulation of mitochondrial translation and OXPHOS pathways with downregulation of hypoxia pathways in pre-BCR+ but not pre-BCR- SYK KD cells. Functional extracellular flux experiments by Seahorse confirmed pre-BCR+ SYK KD cells to have higher basal oxygen consumption rate (OCR) and lower extracellular acidification rate (ECAR) compared to wild-type pre-BCR+ cells, indicating a switch from highly glycolytic to aerobic metabolism. To determine the interplay between pre-BCR signaling and cellular metabolism at the single cell level, we performed CYTOF with a panel examining pre-BCR pathway members, developmental phenotype and metabolism in these cell lines as well as matched diagnosis-relapse patient-derived xenografts. These results indicate, in line with the RNA sequencing and Seahorse data, that inhibiting pre-BCR signaling is accompanied by inhibition of glycolysis with lower protein expression of glycolytic related enzymes HIF1A, GLUT1, PFKFB4, GAPDH, ENO1 and LDHA. Further, we observed in cells completely deficient in the ability to initiate pre-BCR signal (SYK knock out), activated p4EBP1 indicating signaling feedback from the PI3K-AKT pathway and a metabolic adaption indicating utilization of energy sources other than glucose in cells surviving SYK loss. Finally, to determine the impact of loss of pre-BCR signaling on proliferation, in vitro competition assays demonstrated SYK KD cells to be less proliferative in all the cell lines except pre-BCR- cell line 697. In vivo, SYK KO demonstrated significantly slower engraftment (median %hCD45: 84% vs 54%, P=0.009) in NSG mice and significantly longer survival time than the mice xenografted with wild-type cells (median survival 28 vs 39 days, P=0.0004). Together, our data indicate that individual BCP ALL cells with active pre-BCR signaling are associated with relapse and that these cells have a unique metabolic state that relies on active glycolysis and metabolic flexibility supporting proliferation in vitro as well as engraftment and aggressivity in vivo. Further metabolomics experiments and characterization of primary patient samples are underway. Disclosures Mullighan: Pfizer: Research Funding; Illumina: Membership on an entity's Board of Directors or advisory committees; AbbVie: Research Funding; Amgen: Current equity holder in publicly-traded company. Davis: Novartis Pharmaceuticals: Honoraria; Jazz Pharmaceuticals: Research Funding.

The cellular complexity and functional diversity of the human immune system necessitate the use of high-dimensional single-cell tools to uncover its role in multifaceted diseases such as rheumatic diseases, as well as other autoimmune and inflammatory disorders. Proteomic technologies that use elemental (heavy metal) reporter ions, such as mass cytometry (also known as CyTOF) and analogous high-dimensional imaging approaches (including multiplexed ion beam imaging (MIBI) and imaging mass cytometry (IMC)), have been developed from their low-dimensional counterparts, flow cytometry and immunohistochemistry, to meet this need. A growing number of studies have been published that use these technologies to identify functional biomarkers and therapeutic targets in rheumatic diseases, but the full potential of their application to rheumatic disease research has yet to be fulfilled. This Review introduces the underlying technologies for high-dimensional immune monitoring and discusses aspects necessary for their successful implementation, including study design principles, analytical tools and future developments for the field of rheumatology.

This study defines a single-cell proteomic atlas of human OA cartilage to reveal rare subpopulations that stratify patients., Aging or injury leads to degradation of the cartilage matrix and the development of osteoarthritis (OA). Because of a paucity of single-cell studies of OA cartilage, little is known about the interpatient variability in its cellular composition and, more importantly, about the cell subpopulations that drive the disease. Here, we profiled healthy and OA cartilage samples using mass cytometry to establish a single-cell atlas, revealing distinct chondrocyte progenitor and inflammation-modulating subpopulations. These rare populations include an inflammation-amplifying (Inf-A) population, marked by interleukin-1 receptor 1 and tumor necrosis factor receptor II, whose inhibition decreased inflammation, and an inflammation-dampening (Inf-D) population, marked by CD24, which is resistant to inflammation. We devised a pharmacological strategy targeting Inf-A and Inf-D cells that significantly decreased inflammation in OA chondrocytes. Using our atlas, we stratified patients with OA in three groups that are distinguished by the relative proportions of inflammatory to regenerative cells, making it possible to devise precision therapeutic approaches.

Assessing the health and competence of the immune system is central to evaluating vaccination responses, autoimmune conditions, cancer prognosis and treatment. With an increasing number of studies examining immune dysregulation, there is a growing need for a curated reference of variation in immune parameters in healthy individuals. We used mass cytometry (CyTOF) to profile blood from 86 humans in response to 15 ex vivo immune stimuli. We present reference ranges for cell-specific immune markers and highlight differences that appear across sex and age. We identified modules of immune features that suggests there exists and underlying structure to the immune system based on signaling pathway responses across cell types. We observed increased MAPK signaling in inflammatory pathways in innate immune cells and greater overall coordination of immune cell responses in women. In contrast, men exhibited stronger STAT1 and TBK1 responses. These reference data are publicly available as a resource for immune profiling studies.

Elucidating the spectrum of epithelial-mesenchymal transition (EMT) and mesenchymal-epithelial transition (MET) states in clinical samples promises insights on cancer progression and drug resistance. Using mass cytometry time-course analysis, we resolve lung cancer EMT states through TGFβ-treatment and identify, through TGFβ-withdrawal, a distinct MET state. We demonstrate significant differences between EMT and MET trajectories using a computational tool (TRACER) for reconstructing trajectories between cell states. In addition, we construct a lung cancer reference map of EMT and MET states referred to as the EMT-MET PHENOtypic STAte MaP (PHENOSTAMP). Using a neural net algorithm, we project clinical samples onto the EMT-MET PHENOSTAMP to characterize their phenotypic profile with single-cell resolution in terms of our in vitro EMT-MET analysis. In summary, we provide a framework to phenotypically characterize clinical samples in the context of in vitro EMT-MET findings which could help assess clinical relevance of EMT in cancer in future studies., Intermediate transitions between epithelial and mesenchymal states are associated with tumor progression. Here using mass cytometry, Plevritis and colleagues develop a computational framework to resolve and map these trajectories in lung cancer cells and clinical specimens.

Transforming growth factor β (TGF-β) is well known for its important function in hematopoietic stem cell (HSC) quiescence. However, the molecular mechanism underlining this function remains obscure. Endoglin (Eng), a type III receptor for the TGF-β superfamily, has been shown to selectively mark long-term HSCs; however, its necessity in adult HSCs is unknown due to embryonic lethality. Using conditional deletion of Eng combined with serial transplantation, we show that this TGF-β receptor is critical to maintain the HSC pool. Transplantation of Eng-deleted whole bone marrow or purified HSCs into lethally irradiated mice results in a profound engraftment defect in tertiary and quaternary recipients. Cell cycle analysis of primary grafts revealed decreased frequency of HSCs in G0, suggesting that lack of Eng impairs reentry of HSCs to quiescence. Using cytometry by time of flight (CyTOF) to evaluate the activity of signaling pathways in individual HSCs, we find that Eng is required within the Lin−Sca+Kit+–CD48− CD150+ fraction for canonical and noncanonical TGF-β signaling, as indicated by decreased phosphorylation of SMAD2/3 and the p38 MAPK-activated protein kinase 2, respectively. These findings support an essential role for Eng in positively modulating TGF-β signaling to ensure maintenance of HSC quiescence.

To evaluate the impact of heterogeneous B cells in health and disease, comprehensive profiling is needed at a single cell resolution. We developed a highly-multiplexed screen to quantify the co-expression of 351 surface molecules on low numbers of primary cells. We identified dozens of differentially expressed molecules and aligned their variance with B cell isotype usage, metabolism, biosynthesis activity, and signaling response. Here, we propose a new classification scheme to segregate peripheral blood B cells into ten unique subsets, including a CD45RB+ CD27- early memory population and a CD19hi CD11c+ memory population that is a potent responder to immune activation. Furthermore, we quantify the contributions of antibody isotype and cell surface phenotype to various cell processes and find that phenotype largely drives B cell function. Taken together, these findings provide an extensive profile of human B cell diversity that can serve as a resource for further immunological investigations.

Single cell analysis, starting with the earliest low parameter fluorescent cytometry and microscopy experiments, helped define the major cell subsets of human cellular systems as we understand them today. Now, a novel combination of elemental mass spectrometry with single cell analysis (mass cytometry – CyTOF, Science 2011) and imaging (multiplexed ionbeam imaging – MIBI, Nature Med. 2014, Cell 2018) offers routine examination of >50 parameters without fluorescent agents or interference from spectral overlap using heavy metal isotopes as reporters. With these platforms, we have reached new levels of organizational understanding in human pathobiology. Here, we will review the evolution of these technologies and present our latest efforts to create assays with these platforms in order to quantify multiple levels of regulation including metabolism, proteome dynamics, and chromatin content regulating the epigenome. Further to this, we will highlight recent efforts to leverage structural characteristics of leukemia dysplasias to facilitate automated identification and classification from multiplexed single cell datasets (Tsai & Glass et al. Nature Med. 2020). Overall, these new approaches can reveal new layers of human cellular organization and structure that can be exploited to understand dysfunction in general and provide avenues for more automated and robust clinical classification. Citation Format: Sean Bendall. Single cell proteomics to capture human dysplasia and dysfunction [abstract]. In: Proceedings of the AACR Virtual Special Conference on Tumor Heterogeneity: From Single Cells to Clinical Impact; 2020 Sep 17-18. Philadelphia (PA): AACR; Cancer Res 2020;80(21 Suppl):Abstract nr IA22.

Pediatric acute myeloid leukemia (AML) is a rare disease characterized by an accumulation of immature white blood cells in the bone marrow and/or peripheral blood. In some cases, it is thought that the predisposition to leukemia begins in utero. Often, leukemogenesis in children is caused by recurrent chromosomal translocations that result in fusion proteins that do not occur in AML in adults. In particular, NUP98-JARID1A is a recurrent fusion that occurs in an aggressive AML characterized by malignant megakaryoblasts. The prognosis for these patients is poor and there are few novel therapies on the horizon. Using human pluripotent stem cells, we can model this disease by recapitulating the events of leukemogenesis with the goal to better understand the pathogenesis of this disease and to identify better treatments for children. To this end, we generated human pluripotent cell lines that express the NUP98-JARID1A (NJ) fusion protein through a lentiviral expression system. These cells have been characterized in the pluripotent state by RNAseq and molecular and cell culture methods. The cell lines can be differentiated to the three germ layers, and we can focus on the myeloid lineage. Here we are using mass cytometry to analyze the differentiation phenotypes of these cells in comparison to both normal bone marrow stem and progenitor populations as well as primary patient samples. Induced pluripotent cells carrying the NJ fusion maintain their pluripotent state by the presence of surface markers and expression of pluripotent genes despite a higher sensitivity to stress and difficulties to culture them. These cells display abnormal mitosis showing multiple poles and bad segregation of chromosomes, which results in aberrant karyotypes. Interestingly, as NJ iPS cells differentiate to the three germ layers, NJ iPS demonstrate a substantial increase in specific mesodermal markers as CD34 and KDR, but without differences in ectoderm or endoderm specific markers. We will discuss comparisons between myeloid developmental populations from NJ iPS cells, wild-type iPS cells differentiated to the myeloid lineage and normal bone marrow. Finally, we compare differentiated NJ iPS leukemic cells to primary patient samples based on their phenotypic and signaling features as determined by CyTOF. In conclusion, we demonstrate an early model of NUP98-JARID1A fusion AML that recapitulates the genomic instability of this leukemia and demonstrates a deregulation of mesodermal development and further myeloid differentiation. NUP98 has been described with 30 other fusion partners, all related to leukemia, and this model may be used as a basis for understanding its role in leukemogenesis. Citation Format: Joan Domingo-Reines, Samuel Kimmey, Kausalia Vijayaragavan, Marc Bosse, Sean Bendall, Kara Davis, Veronica Ramos-Mejía. Validation of a model of pediatric leukemia based on pluripotent stem cells using mass cytometry [abstract]. In: Proceedings of the AACR Special Conference on the Advances in Pediatric Cancer Research; 2019 Sep 17-20; Montreal, QC, Canada. Philadelphia (PA): AACR; Cancer Res 2020;80(14 Suppl):Abstract nr B29.

Summary B cells are capable of a wide range of effector functions including antibody secretion, antigen presentation, cytokine production, and generation of immunological memory. A consistent strategy for classifying human B cells by using surface molecules is essential to harness this functional diversity for clinical translation. We developed a highly multiplexed screen to quantify the co-expression of 351 surface molecules on millions of human B cells. We identified differentially expressed molecules and aligned their variance with isotype usage, VDJ sequence, metabolic profile, biosynthesis activity, and signaling response. Based on these analyses, we propose a classification scheme to segregate B cells from four lymphoid tissues into twelve unique subsets, including a CD45RB+CD27− early memory population, a class-switched CD39+ tonsil-resident population, and a CD19hiCD11c+ memory population that potently responds to immune activation. This classification framework and underlying datasets provide a resource for further investigations of human B cell identity and function., Graphical Abstract, Highlights • A mass cytometry screen reveals 98 surface molecules expressed by human B cells • High-dimensional analysis identifies twelve B cell subsets across four tissues • CD45RB, CD11c, CD39, CD73, and CD95 define subsets of antigen-experienced B cells • Isotype usage, signaling, and metabolism vary in accordance with cell surface phenotype, To identify molecules that distinguish functionally distinct subsets of human B cells, Glass et al. screened the expression of 351 surface molecules by mass cytometry. By combining identified molecules with functional readouts, they propose a new classification scheme to segregate B cells from four lymphoid tissues into twelve unique subsets.

e15242 Background: The Cancer Immune Monitoring and Analysis Centers – Cancer Immunology Data Commons (CIMAC-CIDC) network is a National Cancer Institute-funded initiative to identify biomarkers of mechanisms and response to cancer immunotherapy clinical trials, using state-of-the-art assay technologies. A primary platform for CIMAC-CIDC biomarker studies is CyTOF mass cytometry, which is performed at all four CIMAC laboratories. Methods: To test the ability to generate comparable data across labs, a cross-site harmonization effort was undertaken. We first harmonized SOPs between centers. Because of a new acquisition protocol introduced by the vendor (Fluidigm), we also tested this protocol across sites before finalizing the harmonized SOP. We then performed a cross-site assay harmonization experiment, using 5 shared cryopreserved PBMC samples and one lyophilized control cell preparation, along with a shared lyophilized antibody cocktail consisting of 14 markers, as validated in the HIPC consortium, plus CD45. These reagents and samples were distributed to the four sites, and FCS files were centrally analyzed by both manual gating and automated methods (Astrolabe). Results: Average CVs across sites for each cell population were reported and compared to a previous multisite CyTOF study. Once a cell recovery issue at two sites was resolved, this experiment resulted in inter-site reproducibility of under 20% CV for most cell subsets, very similar to the previous study. Conclusions: These results emphasize the ability to reproduce CyTOF across sites, and also highlights procedures, such as use of spike-in control samples, useful for tracking variability in this assay.

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.

Motivation High-parameter single-cell technologies can reveal novel cell populations of interest, but studying or validating these populations using lower-parameter methods remains challenging. Results Here, we present GateFinder, an algorithm that enriches high-dimensional cell types with simple, stepwise polygon gates requiring only two markers at a time. A series of case studies of complex cell types illustrates how simplified enrichment strategies can enable more efficient assays, reveal novel biomarkers and clarify underlying biology. Availability and implementation The GateFinder algorithm is implemented as a free and open-source package for BioConductor: https://nalab.stanford.edu/gatefinder. Supplementary information Supplementary data are available at Bioinformatics online.

Advances in single-cell mass cytometry have increasingly improved highly multidimensional characterization of immune cell heterogeneity. The immunoassay multiplexing capacity relies on monoclonal antibodies labeled with stable heavy-metal isotopes. To date, a variety of rare-earth elements and noble and post-transition metal isotopes have been used in mass cytometry; nevertheless, the methods used for antibody conjugation differ because of the individual metal coordination chemistries and distinct stabilities of various metal cations. Herein, we provide three optimized protocols for conjugating monoclonal IgG antibodies with 48 high-purity heavy-metal isotopes: (i) 38 isotopes of lanthanides, 2 isotopes of indium, and 1 isotope of yttrium; (ii) 6 isotopes of palladium; and (iii) 1 isotope of bismuth. Bifunctional chelating agents containing coordinative ligands of monomeric DOTA (1,4,7,10-tetraazacyclododecane-1,4,7,10-tetraacetic acid) or polymeric pentetic acid (DTPA) were used to stably sequester isotopic cations in aqueous solutions and were subsequently coupled to IgG antibodies using site-specific biorthogonal reactions. Furthermore, quantification methods based on antibody inherent absorption at 280 nm and on extrinsic absorption at 562 nm after staining with bicinchoninic acid (BCA) are reported to determine metal-isotope-tagged antibodies. In addition, a freeze-drying procedure to prepare palladium isotopic mass tags is described. To demonstrate the utility, experiments using six palladium-tagged CD45 antibodies for barcoding assays of live immune cells in cytometry by time-of-flight (CyTOF) are described. Conjugation of pure isotopes of lanthanides, indium, or yttrium takes ~3.5 h. Conjugation of bismuth takes ~4 h. Preparation of palladium mass tags takes ~8 h. Conjugation of pure isotopes of palladium takes ~2.5 h. Antibody titration takes ~4 h.

Single-cell barcoding enables the combined processing and acquisition of multiple individual samples as one. This maximizes assay efficiency and eliminates technical variability in both sample preparation and analysis. Remaining challenges are the barcoding of live, unprocessed cells to increase downstream assay performance combined with the flexibility of the approach towards a broad range of cell types. To that end, we developed a novel antibody-based platform that allows the robust barcoding of live human cells for mass cytometry (CyTOF). By targeting both the MHC class I complex (beta-2-microglobulin) and a broadly expressed sodium-potassium ATPase-subunit (CD298) with platinum-conjugated antibodies, human immune cells, stem cells as well as tumor cells could be multiplexed in the same single-cell assay. In addition, we present a novel palladium-based covalent viability reagent compatible with this barcoding strategy. Altogether, this platform enables mass cytometry-based, live-cell barcoding across a multitude of human sample types and provides a scheme for multiplexed barcoding of human single-cell assays in general.

Significance Single-cell high-throughput technologies enable the ability to identify combination cancer therapies that account for intratumoral heterogeneity, a phenomenon that has been shown to influence the effectiveness of cancer treatment. We developed and applied an approach that identifies top-ranking drug combinations based on the single-cell perturbation response when an individual tumor sample is screened against a panel of single drugs. This approach optimizes drug combinations by choosing the minimum number of drugs that produce the maximal intracellular desired effects for an individual sample., An individual malignant tumor is composed of a heterogeneous collection of single cells with distinct molecular and phenotypic features, a phenomenon termed intratumoral heterogeneity. Intratumoral heterogeneity poses challenges for cancer treatment, motivating the need for combination therapies. Single-cell technologies are now available to guide effective drug combinations by accounting for intratumoral heterogeneity through the analysis of the signaling perturbations of an individual tumor sample screened by a drug panel. In particular, Mass Cytometry Time-of-Flight (CyTOF) is a high-throughput single-cell technology that enables the simultaneous measurements of multiple (>40) intracellular and surface markers at the level of single cells for hundreds of thousands of cells in a sample. We developed a computational framework, entitled Drug Nested Effects Models (DRUG-NEM), to analyze CyTOF single-drug perturbation data for the purpose of individualizing drug combinations. DRUG-NEM optimizes drug combinations by choosing the minimum number of drugs that produce the maximal desired intracellular effects based on nested effects modeling. We demonstrate the performance of DRUG-NEM using single-cell drug perturbation data from tumor cell lines and primary leukemia samples.

Purpose: To identify an optimal drug combination for addressing intratumor heterogeneity by measuring single drug responses at the level of single cells. Background: Drug combination strategies have been derived from drug-drug and drug-target interaction inferences made based on genomic network analysis, such as synthetic lethality network analysis and protein network analysis. A key limitation with these approaches is that they do not account for intratumor heterogeneity. A next generation high throughput single cell technology such as Cytometry Time-of-Flight (CyTOF) has the potential to circumvent this limitation by providing the key information for optimally targeting intratumor heterogeneity within the context of personalized medicine. Methods: We propose a systems level modeling framework for analyzing heterogeneous drug response data across a population of single cells. Our approach, called Mixture Nested Effects Models (MNEM), identifies multi-target drug combinations from single drug effects measured at the level of single cells. MNEM analyzes drug responses among subpopulations (aka clusters) of similar cells, where the subpopulations are defined by cellular surface markers. MNEM infers the nested drug target hierarchy (directed network) from a heterogeneous population of drug effects by combining subpopulation identification, subpopulation matching to infer the drug response pre- and post-treatment, and nested effects modeling for each subpopulation individually or through a mixture of subpopulations. An MNEM infers that Drug A targets are a superset of Drug B targets, if the heterogeneous downstream target effects resulting from Drug B are a noisy subset of those resulting from Drug A. This relationship is represented as a directed edge from Drug A to Drug B. From the graphical model of nested drug effects, a scoring function is superimposed to identify the optimal drug combinations. Results: We apply MNEM to CyTOF drug screening data derived from treating three well-established cancer cell lines: HeLa (ovarian), NCIH460 (lung) and HCT116 (colon) with Mek, mTOR, pP38MAPK, JnK I and PI3K inhibitors at different optimal dose levels in addition to the base line treatment TRAIL, an apoptotic stimulator. MNEM indicates that pP38MAPK and Mek inhibitors are important candidates for targeting the ovarian and lung cancer cell lines. The MNEM analysis from the colon cancer cell line data indicates that several optimal drug regimens may have equivalent efficacy. Survival data from drug combination invitro experiments using clonogenic assays support the results from MNEM. Overall, these analyses suggest that MNEM could be used to optimize drug combinations based on responses from single drugs measured at the single cell level. Conclusion: Intratumor heterogeneity in tumor response, measured at the level of single cells, upon exposure to single drugs may be combined through Mixture Nested Effects Modeling (MNEM) to infer optimal drug combinations. Citation Format: Benedict Anchang, Harris Fienberg, Sean Bendall, Robert Tibshirani, Sylvia K. Plevritis. Multi-target drug combinations from single drug responses measured at the level of single cells using Mixture Nested Effects Models (MNEMs) applied to cancer. [abstract]. In: Proceedings of the AACR Special Conference on Computational and Systems Biology of Cancer; Feb 8-11 2015; San Francisco, CA. Philadelphia (PA): AACR; Cancer Res 2015;75(22 Suppl 2):Abstract nr B1-39.

The present study describes an efficient and reliable method for the preparation of MS2 viral capsids that are synthetically modified with antibodies using a rapid oxidative coupling strategy. The overall protocol delivers conjugates in high yields and recoveries, requires a minimal excess of antibody to achieve modification of more than 95% of capsids, and can be completed in a short period of time. Antibody-capsid conjugates targeting extracellular receptors on human breast cancer cell lines were prepared and characterized. Notably, conjugation to the capsid did not significantly perturb the binding of the antibodies, as indicated by binding affinities similar to those obtained for the parent antibodies. An array of conjugates was synthesized with various reporters on the interior surface of the capsids to be used in cell studies, including fluorescence-based flow cytometry, confocal microscopy, and mass cytometry. The results of these studies lay the foundation for further exploration of these constructs in the context of clinically relevant applications, including drug delivery and in vivo diagnostics.

Muscle regeneration is a dynamic process during which cell state and identity change over time. A major roadblock has been a lack of tools to resolve a myogenic progression in vivo. Here we capitalize on a transformative technology, single-cell mass cytometry (CyTOF), to identify in vivo skeletal muscle stem cell and previously unrecognized progenitor populations that precede differentiation. We discovered two cell surface markers, CD9 and CD104, whose combined expression enabled in vivo identification and prospective isolation of stem and progenitor cells. Data analysis using the X-shift algorithm paired with single-cell force directed layout visualization, defined a molecular signature of the activated stem cell state (CD44+/CD98+/MyoD+) and delineated a myogenic trajectory during recovery from acute muscle injury. Our studies uncover the dynamics of skeletal muscle regeneration in vivo and pave the way for the elucidation of the regulatory networks that underlie cell-state transitions in muscle diseases and aging.

Immune responses involve coordination across cell types and tissues. However, studies in cancer immunotherapy have focused heavily on local immune responses in the tumor microenvironment. To investigate immune activity more broadly, we performed an organism-wide study in genetically engineered cancer models using mass cytometry. We analyzed immune responses in several tissues after immunotherapy by developing intuitive models for visualizing single-cell data with statistical inference. Immune activation was evident in the tumor and systemically shortly after effective therapy was administered. However, during tumor rejection, only peripheral immune cells sustained their proliferation. This systemic response was coordinated across tissues and required for tumor eradication in several immunotherapy models. An emergent population of peripheral CD4 Tcells conferred protection against new tumors and was significantly expanded in patients responding to immunotherapy. These studies demonstrate the critical impact of systemic immune responses that drive tumor rejection.

Mutant RAS oncoproteins activate signaling molecules that drive oncogenesis in multiple human tumors including acute myelogenous leukemia (AML). However, the specific functions of these pathways in AML are unclear, thwarting the rational application of targeted therapeutics. To elucidate the downstream functions of activated NRAS in AML, we used a murine model that harbors Mll-AF9 and a tetracycline-repressible, activated NRAS (NRAS(G12V)). Using computational approaches to explore our gene-expression data sets, we found that NRAS(G12V) enforced the leukemia self-renewal gene-expression signature and was required to maintain an MLL-AF9- and Myb-dependent leukemia self-renewal gene-expression program. NRAS(G12V) was required for leukemia self-renewal independent of its effects on growth and survival. Analysis of the gene-expression patterns of leukemic subpopulations revealed that the NRAS(G12V)-mediated leukemia self-renewal signature is preferentially expressed in the leukemia stem cell-enriched subpopulation. In a multiplexed analysis of RAS-dependent signaling, Mac-1(Low) cells, which harbor leukemia stem cells, were preferentially sensitive to NRAS(G12V) withdrawal. NRAS(G12V) maintained leukemia self-renewal through mTOR and MEK pathway activation, implicating these pathways as potential targets for cancer stem cell-specific therapies. Together, these experimental results define a RAS oncogene-driven function that is critical for leukemia maintenance and represents a novel mechanism of oncogene addiction.

Summary Although pathogens must infect differentiated host cells that exhibit substantial diversity, documenting the consequences of infection against this heterogeneity is challenging. Single-cell mass cytometry permits deep profiling based on combinatorial expression of surface and intracellular proteins. We used this method to investigate varicella-zoster virus (VZV) infection of tonsil T cells, which mediate viral transport to skin. Our results indicate that VZV induces a continuum of changes regardless of basal phenotypic and functional T cell characteristics. Contrary to the premise that VZV selectively infects T cells with skin trafficking profiles, VZV infection altered T cell surface proteins to enhance or induce these properties. Zap70 and Akt signaling pathways that trigger such surface changes were activated in VZV-infected naive and memory cells by a T cell receptor (TCR)-independent process. Single-cell mass cytometry is likely to be broadly relevant for demonstrating how intracellular pathogens modulate differentiated cells to support pathogenesis in the natural host.

Axicabtagene ciloleucel (Axi-cel) is an autologous anti-CD19 chimeric antigen receptor (CAR) T-cell therapy approved for the treatment of relapsed or refractory diffuse large B-cell lymphoma (r/r DLBCL). Long-term analysis of the ZUMA-1 phase 1-2 clinical trial showed that ~40% of Axi-cel patients remained progression-free at 2 years (Locke et al., Lancet Oncology 2019). Those patients who achieved a complete response (CR) at 6 months generally remained progression-free long-term. The biological basis for achieving a durable CR in patients receiving Axi-cel remains poorly understood. Here, we sought to identify CAR T-cell intrinsic features associated with CR at 6 months in DLBCL patients receiving commercial Axi-cel at our institution. Using mass cytometry, we assessed expression of 33 surface or intracellular proteins relevant to T-cell function on blood collected before CAR T cell infusion, on day 7 (peak expansion), and on day 21 (late expansion) post-infusion. To identify cell features that distinguish patients with durable CR (n = 11) from those who developed progressive disease (PD, n = 14) by 6 months following Axi-cel infusion, we performed differential abundance analysis of multiparametric protein expression on CAR T cells. This unsupervised analysis identified populations on day 7 associated with persistent CR or PD at 6 months. Using 10-fold cross-validation, we next fitted a least absolute shrinkage and selection operator (lasso) model that identified two clusters of CD4+ CAR T cells on day 7 as potentially predictive of clinical outcome. The first cluster identified by our model was associated with CR at 6 months and had high expression of CD45RO, CD57, PD1, and T-bet transcription factor. Analysis of protein co-expression in this cluster enabled us to define a simple gating scheme based on high expression of CD57 and T-bet, which captured a population of CD4+ CAR T cells on day 7 with greater expansion in patients experiencing a durable CR (mean±s.e.m. CR: 26.13%±2.59%, PD: 10.99%±2.53%, P = 0.0014). In contrast, the second cluster was associated with PD at 6 months and had high expression of CD25, TIGIT, and Helios transcription factor with no CD57. A CD57-negative Helios-positive gate captured a population of CD4+ CAR T cells was enriched on day 7 in patients who experienced progression (CR: 9.75%±2.70%, PD: 20.93%±3.70%, P = 0.016). Co-expression of CD4, CD25, and Helios on these CAR T cells highlights their similarity to regulatory T cells, which could provide a basis for their detrimental effects. In this exploratory analysis of 25 patients treated with Axi-cel, we identified two populations of CD4+ CAR T cells on day 7 that were highly associated with clinical outcome at 6 months. Ongoing analyses are underway to fully characterize this dataset, to explore the biological activity of the populations identified, and to assess the presence of other populations that may be associated with CAR-T expansion or neurotoxicity. This work demonstrates how multidimensional correlative studies can enhance our understanding of CAR T-cell biology and uncover populations associated with clinical outcome in CAR T cell therapies. This work was supported by the Parker Institute for Cancer Immunotherapy. Figure Disclosures Muffly: Pfizer: Consultancy; Adaptive: Research Funding; KITE: Consultancy. Miklos:Celgene: Membership on an entity's Board of Directors or advisory committees; BMS: Membership on an entity's Board of Directors or advisory committees; Kite-Gilead: Membership on an entity's Board of Directors or advisory committees, Research Funding; AlloGene: Membership on an entity's Board of Directors or advisory committees; Precision Bioscience: Membership on an entity's Board of Directors or advisory committees; Miltenyi Biotech: Membership on an entity's Board of Directors or advisory committees; Becton Dickinson: Research Funding; Adaptive Biotechnologies: Membership on an entity's Board of Directors or advisory committees; Novartis: Membership on an entity's Board of Directors or advisory committees, Research Funding; Juno: Membership on an entity's Board of Directors or advisory committees. Mackall:Vor: Other: Scientific Advisory Board; Roche: Other: Scientific Advisory Board; Adaptimmune LLC: Other: Scientific Advisory Board; Glaxo-Smith-Kline: Other: Scientific Advisory Board; Allogene: Equity Ownership, Membership on an entity's Board of Directors or advisory committees; Apricity Health: Equity Ownership, Membership on an entity's Board of Directors or advisory committees; Unum Therapeutics: Equity Ownership, Membership on an entity's Board of Directors or advisory committees; Obsidian: Research Funding; Lyell: Consultancy, Equity Ownership, Other: Founder, Research Funding; Nektar: Other: Scientific Advisory Board; PACT: Other: Scientific Advisory Board; Bryologyx: Other: Scientific Advisory Board.

This work summarizes cellular apoptotic and signaling response to TRAIL across 10 cell lines and for the first time links signaling diversity to nongenetic resistance. This high-dimensional, single-cell approach toward TRAIL resistance sets a standard in studying nongenetic resistance., TNFα-related apoptosis-inducing ligand (TRAIL), specifically initiates programmed cell death, but often fails to eradicate all cells, making it an ineffective therapy for cancer. This fractional killing is linked to cellular variation that bulk assays cannot capture. Here, we quantify the diversity in cellular signaling responses to TRAIL, linking it to apoptotic frequency across numerous cell systems with single-cell mass cytometry (CyTOF). Although all cells respond to TRAIL, a variable fraction persists without apoptotic progression. This cell-specific behavior is nonheritable where both the TRAIL-induced signaling responses and frequency of apoptotic resistance remain unaffected by prior exposure. The diversity of signaling states upon exposure is correlated to TRAIL resistance. Concomitantly, constricting the variation in signaling response with kinase inhibitors proportionally decreases TRAIL resistance. Simultaneously, TRAIL-induced de novo translation in resistant cells, when blocked by cycloheximide, abrogated all TRAIL resistance. This work highlights how cell signaling diversity, and subsequent translation response, relates to nonheritable fractional escape from TRAIL-induced apoptosis. This refined view of TRAIL resistance provides new avenues to study death ligands in general.