Guidelines for establishing a cytometry laboratory.

The purpose of this document is to provide guidance for establishing and maintaining growth and development of flow cytometry shared resource laboratories. While the best practices offered in this manuscript are not intended to be universal or exhaustive, they do outline key goals that should be prioritized to achieve operational excellence and meet the needs of the scientific community. Additionally, this document provides information on available technologies and software relevant to shared resource laboratories. This manuscript builds on the work of Barsky et al. 2016 published in Cytometry Part A and incorporates recent advancements in cytometric technology. A flow cytometer is a specialized piece of technology that require special care and consideration in its housing and operations. As with any scientific equipment, a thorough evaluation of the location, space requirements, auxiliary resources, and support is crucial for successful operation. This comprehensive resource has been written by past and present members of the International Society for Advancement of Cytometry (ISAC) Shared Resource Laboratory (SRL) Emerging Leaders Program https://isac-net.org/general/custom.asp?page=SRL-Emerging-Leaders with extensive expertise in managing flow cytometry SRLs from around the world in different settings including academia and industry. It is intended to assist in establishing a new flow cytometry SRL, re-purposing an existing space into such a facility, or adding a flow cytometer to an individual lab in academia or industry. This resource reviews the available cytometry technologies, the operational requirements, and best practices in SRL staffing and management.

A multicenter phase Ib trial of the histone deacetylase inhibitor entinostat in combination with pembrolizumab in patients with myelodysplastic syndromes/neoplasms or acute myeloid leukemia refractory to hypomethylating agents.

Patients with myelodysplastic syndromes/neoplasms (MDS) or acute myeloid leukemia (AML) with hypomethylating agent failure have a poor prognosis. Myeloid-derived suppressor cells (MDSCs) can contribute to MDS progression and mediate resistance to anti-PD1 therapy. As histone deacetylase inhibitors (HDACi) decrease MDSCs in preclinical models, we conducted an investigator-initiated, NCI-Cancer Therapy Evaluation Program-sponsored, multicenter, dose escalation, and expansion phase Ib trial (NCT02936752) of the HDACi entinostat and the anti-PD1 antibody pembrolizumab. Twenty-eight patients (25 MDS and 3 AML) were enrolled. During dose escalation (n=13 patients), there was one dose-limiting toxicity (DLT) on dose level (DL) 1 (G5 pneumonia/bronchoalveolar hemorrhage) and two DLTs at DL 2 (G3 pharyngeal mucositis and G3 anorexia). Per the 3 + 3 dose escalation design, DL 1 (entinostat 8 mg PO days 1 and 15 + pembrolizumab 200 mg IV day 1 every 21 days) was expanded and another 15 patients were enrolled. Hematologic adverse events (AEs) were common. The most common non-hematologic ≥G3 AEs were infection (32%), hypoxia/respiratory failure (11%), and dyspnea (11%). There were no protocol-defined responses among the 28 patients enrolled. Two patients achieved a marrow complete remission (mCR). Using a systems immunology approach with mass cytometry and machine learning analysis, mCR patients had increased classical monocytes and macrophages but there was no significant change of MDSCs. In conclusion, combining entinostat with pembrolizumab in patients with advanced MDS and AML was associated with limited clinical efficacy and substantial toxicity. Absence of an effect on MDSCs could be a potential explanation for the limited efficacy of this combination. ClinicalTrial.gov Identifier: NCT02936752.

Shared Resource Laboratory Operations: Changes Made During Initial Global COVID-19 Lockdown of 2020.

Undoubtedly, the global pandemic caused by the SARS-CoV-2 virus has had a significant impact on Shared Resource Laboratories (SRL) operations worldwide. Unlike other crises (e.g., natural disasters, acts of war, or terrorism) which often result in a sudden and sustained cessation of scientific research usually affecting one or two cities at a time, this impact is being seen simultaneously in every SRL worldwide albeit to a varying degree. The alterations to SRL operations caused by the COVID-19 pandemic can generally be divided into three categories: (1) complete shutdown, (2) partial shutdown, and (3) uninterrupted operations. In many cases, SRLs that remained partially or fully operational during the initial wave of global infections saw a concurrent increase in COVID-19-related research coming through their facilities. This forced SRLs to make rapid adjustments to core operations at the same time as infectious disease experts were still developing recommendations for the safety of frontline medical workers. Although many SRLs already had contingency plans in place, this pandemic has highlighted the importance of having such plans for continuity of service, if possible, during a crisis. Immediate changes have occurred in the way SRLs operate due to potential virus transmission and in line with this new "Best Practices" have been established, that is,social distancing, remote working, and technology-based meetings and training. Many of these changes are likely to be in place for some time with the threat of further waves of infections toward the end of 2020 and into 2021. Some of these best practices, such as having many training resources recorded and available online, are likely to remain long-term. Although many changes have been made in haste, these will alter the future operations of SRLs. In addition, we have learnt how to deal with future crises that may be encountered in the workplace. © 2020 The Authors. Cytometry Part A published by Wiley Periodicals LLC. on behalf of International Society for Advancement of Cytometry.

Mass cytometry defines distinct immune profile in germinal center B-cell lymphomas.

Tumor-associated macrophage and T-cell subsets are implicated in the pathogenesis of diffuse large B-cell lymphoma, follicular lymphoma, and classical Hodgkin lymphoma. Macrophages provide essential mechanisms of tumor immune evasion through checkpoint ligand expression and secretion of suppressive cytokines. However, normal and tumor-associated macrophage phenotypes are less well characterized than those of tumor-infiltrating T-cell subsets, and it would be especially valuable to know whether the polarization state of macrophages differs across lymphoma tumor microenvironments. Here, an established mass cytometry panel designed to characterize myeloid-derived suppressor cells and known macrophage maturation and polarization states was applied to characterize B-lymphoma tumors and non-malignant human tissue. High-dimensional single-cell analyses were performed using dimensionality reduction and clustering tools. Phenotypically distinct intra-tumor macrophage subsets were identified based on abnormal marker expression profiles that were associated with lymphoma tumor types. While it had been proposed that measurement of CD163 and CD68 might be sufficient to reveal macrophage subsets in tumors, results here indicated that S100A9, CCR2, CD36, Slan, and CD32 should also be measured to effectively characterize lymphoma-specific tumor macrophages. Additionally, the presence of phenotypically distinct, abnormal macrophage populations was closely linked to the phenotype of intra-tumor T-cell populations, including PD-1 expressing T cells. These results further support the close links between macrophage polarization and T-cell functional state, as well as the rationale for targeting tumor-associated macrophages in cancer immunotherapies.

An immunosuppressed microenvironment distinguishes lateral ventricle-contacting glioblastomas.

Radiographic contact of glioblastoma (GBM) tumors with the lateral ventricle and adjacent stem cell niche correlates with poor patient prognosis, but the cellular basis of this difference is unclear. Here, we reveal and functionally characterize distinct immune microenvironments that predominate in subtypes of GBM distinguished by proximity to the lateral ventricle. Mass cytometry analysis of isocitrate dehydrogenase wild-type human tumors identified elevated T cell checkpoint receptor expression and greater abundance of a specific CD32+CD44+HLA-DRhi macrophage population in ventricle-contacting GBM. Multiple computational analysis approaches, phospho-specific cytometry, and focal resection of GBMs validated and extended these findings. Phospho-flow quantified cytokine-induced immune cell signaling in ventricle-contacting GBM, revealing differential signaling between GBM subtypes. Subregion analysis within a given tumor supported initial findings and revealed intratumor compartmentalization of T cell memory and exhaustion phenotypes within GBM subtypes. Collectively, these results characterize immunotherapeutically targetable features of macrophages and suppressed lymphocytes in GBMs defined by MRI-detectable lateral ventricle contact.

Single-cell profiling of the antigen-specific response to BNT162b2 SARS-CoV-2 RNA vaccine.

RNA-based vaccines against SARS-CoV-2 have proven critical to limiting COVID-19 disease severity and spread. Cellular mechanisms driving antigen-specific responses to these vaccines, however, remain uncertain. Here we identify and characterize antigen-specific cells and antibody responses to the RNA vaccine BNT162b2 using multiple single-cell technologies for in depth analysis of longitudinal samples from a cohort of healthy participants. Mass cytometry and unbiased machine learning pinpoint an expanding, population of antigen-specific memory CD4+ and CD8+ T cells with characteristics of follicular or peripheral helper cells. B cell receptor sequencing suggest progression from IgM, with apparent cross-reactivity to endemic coronaviruses, to SARS-CoV-2-specific IgA and IgG memory B cells and plasmablasts. Responding lymphocyte populations correlate with eventual SARS-CoV-2 IgG, and a participant lacking these cell populations failed to sustain SARS-CoV-2-specific antibodies and experienced breakthrough infection. These integrated proteomic and genomic platforms identify an antigen-specific cellular basis of RNA vaccine-based immunity.

Single-Cell Profiling of the Antigen-Specific Response to BNT162b2 SARS-CoV-2 RNA Vaccine.

RNA-based vaccines against SARS-CoV-2 are critical to limiting COVID-19 severity and spread. Cellular mechanisms driving antigen-specific responses to these vaccines, however, remain uncertain. We used single-cell technologies to identify and characterized antigen-specific cells and antibody responses to the RNA vaccine BNT162b2 in longitudinal samples from a cohort of healthy donors. Mass cytometry and machine learning pinpointed a novel expanding, population of antigen-specific non-canonical memory CD4 + and CD8 + T cells. B cell sequencing suggested progression from IgM, with apparent cross-reactivity to endemic coronaviruses, to SARS-CoV-2-specific IgA and IgG memory B cells and plasmablasts. Responding lymphocyte populations correlated with eventual SARS-CoV-2 IgG and a donor lacking these cell populations failed to sustain SARS-CoV-2-specific antibodies and experienced breakthrough infection. These integrated proteomic and genomic platforms reveal an antigen-specific cellular basis of RNA vaccine-based immunity. ONE SENTENCE SUMMARY: Single-cell profiling reveals the cellular basis of the antigen-specific response to the BNT162b2 SARS-CoV-2 RNA vaccine.

Selective Inhibition of JAK1 Primes STAT5-Driven Human Leukemia Cells for ATRA-Induced Differentiation.

BACKGROUND: All-trans retinoic acid (ATRA), a derivate of vitamin A, has been successfully used as a therapy to induce differentiation in M3 acute promyelocytic leukemia (APML), and has led to marked improvement in outcomes. Previously, attempts to use ATRA in non-APML in the clinic, however, have been underwhelming, likely due to persistent signaling through other oncogenic drivers. Dysregulated JAK/STAT signaling is known to drive several hematologic malignancies, and targeting JAK1 and JAK2 with the JAK1/JAK2 inhibitor ruxolitinib has led to improvement in survival in primary myelofibrosis and alleviation of vasomotor symptoms and splenomegaly in polycythemia vera and myelofibrosis. OBJECTIVE: While dose-dependent anemia and thrombocytopenia limit the use of JAK2 inhibition, selectively targeting JAK1 has been explored as a means to suppress inflammation and STAT-associated pathologies related to neoplastogenesis. The objective of this study is to employ JAK1 inhibition (JAK1i) in the presence of ATRA as a potential therapy in non-M3 acute myeloid leukemia (AML). METHODS: Efficacy of JAK1i using INCB52793 was assessed by changes in cell cycle and apoptosis in treated AML cell lines. Transcriptomic and proteomic analysis evaluated effects of JAK1i. Synergy between JAK1i+ ATRA was assessed in cell lines in vitro while efficacy in vivo was assessed by tumor reduction in MV-4-11 cell line-derived xenografts. RESULTS: Here we describe novel synergistic activity between JAK1i inhibition and ATRA in non-M3 leukemia. Transcriptomic and proteomic analysis confirmed structural and functional changes related to maturation while in vivo combinatory studies revealed significant decreases in leukemic expansion. CONCLUSIONS: JAK1i+ ATRA lead to decreases in cell cycle followed by myeloid differentiation and cell death in human leukemias. These findings highlight potential uses of ATRA-based differentiation therapy of non-M3 human leukemia.

Training Novices in Generation and Analysis of High-Dimensional Human Cell Phospho-Flow Cytometry Data.

This article presents a single experiment designed to introduce a trainee to multiple advanced bench and analysis techniques, including high-dimensional cytometry, profiling cell signaling networks, functional assays with primary human tissue, and single-cell analysis with machine learning tools. The trainee is expected to have only minimal laboratory experience and is not required to have any prior training in flow cytometry, immunology, or data science. This article aims to introduce the advanced research areas with a design that is robust enough that novice trainees will succeed, flexible enough to allow some project customization, and fundamental enough that the skills and knowledge gained will provide a template for future experiments. For advanced users, the updated phospho-flow protocol and the established controls, best practices, and expected outcomes presented here also provide a framework for adapting these tools in new areas with unexplored biology. © 2020 by John Wiley & Sons, Inc. Basic Protocol: Phospho-protein stimulation and mass cytometry data collection Support Protocol: Analysis of signaling mass cytometry data.

CD28 costimulation drives tumor-infiltrating T cell glycolysis to promote inflammation.

Metabolic reprogramming dictates the fate and function of stimulated T cells, yet these pathways can be suppressed in T cells in tumor microenvironments. We previously showed that glycolytic and mitochondrial adaptations directly contribute to reducing the effector function of renal cell carcinoma (RCC) CD8+ tumor-infiltrating lymphocytes (TILs). Here we define the role of these metabolic pathways in the activation and effector functions of CD8+ RCC TILs. CD28 costimulation plays a key role in augmenting T cell activation and metabolism, and is antagonized by the inhibitory and checkpoint immunotherapy receptors CTLA4 and PD-1. While RCC CD8+ TILs were activated at a low level when stimulated through the T cell receptor alone, addition of CD28 costimulation greatly enhanced activation, function, and proliferation. CD28 costimulation reprogrammed RCC CD8+ TIL metabolism with increased glycolysis and mitochondrial oxidative metabolism, possibly through upregulation of GLUT3. Mitochondria also fused to a greater degree, with higher membrane potential and overall mass. These phenotypes were dependent on glucose metabolism, as the glycolytic inhibitor 2-deoxyglucose both prevented changes to mitochondria and suppressed RCC CD8+ TIL activation and function. These data show that CD28 costimulation can restore RCC CD8+ TIL metabolism and function through rescue of T cell glycolysis that supports mitochondrial mass and activity.

Computational Immune Monitoring Reveals Abnormal Double-Negative T Cells Present across Human Tumor Types.

Advances in single-cell biology have enabled measurements of >40 protein features on millions of immune cells within clinical samples. However, the data analysis steps following cell population identification are susceptible to bias, time-consuming, and challenging to compare across studies. Here, an ensemble of unsupervised tools was developed to evaluate four essential types of immune cell information, incorporate changes over time, and address diverse immune monitoring challenges. The four complementary properties characterized were (i) systemic plasticity, (ii) change in population abundance, (iii) change in signature population features, and (iv) novelty of cellular phenotype. Three systems immune monitoring studies were selected to challenge this ensemble approach. In serial biopsies of melanoma tumors undergoing targeted therapy, the ensemble approach revealed enrichment of double-negative (DN) T cells. Melanoma tumor-resident DN T cells were abnormal and phenotypically distinct from those found in nonmalignant lymphoid tissues, but similar to those found in glioblastoma and renal cell carcinoma. Overall, ensemble systems immune monitoring provided a robust, quantitative view of changes in both the system and cell subsets, allowed for transparent review by human experts, and revealed abnormal immune cells present across multiple human tumor types.

Generating Quantitative Cell Identity Labels with Marker Enrichment Modeling (MEM).

Multiplexed single-cell experimental techniques like mass cytometry measure 40 or more features and enable deep characterization of well-known and novel cell populations. However, traditional data analysis techniques rely extensively on human experts or prior knowledge, and novel machine learning algorithms may generate unexpected population groupings. Marker enrichment modeling (MEM) creates quantitative identity labels based on features enriched in a population relative to a reference. While developed for cell type analysis, MEM labels can be generated for a wide range of multidimensional data types, and MEM works effectively with output from expert analysis and diverse machine learning algorithms. MEM is implemented as an R package and includes three steps: (1) calculation of MEM values that quantify each feature's relative enrichment in the population, (2) reporting of MEM labels as a heatmap or as a text label, and (3) quantification of MEM label similarity between populations. The protocols here show MEM analysis using datasets from immunology and oncology. These MEM implementations provide a way to characterize population identity and novelty in the context of computational and expert analyses. © 2018 by John Wiley & Sons, Inc.

BRAF and MEK inhibitor therapy eliminates Nestin-expressing melanoma cells in human tumors.

Little is known about the in vivo impacts of targeted therapy on melanoma cell abundance and protein expression. Here, 21 antibodies were added to an established melanoma mass cytometry panel to measure 32 cellular features, distinguish malignant cells, and characterize dabrafenib and trametinib responses in BRAFV600mut melanoma. Tumor cells were biopsied before neoadjuvant therapy and compared to cells surgically resected from the same site after 4 weeks of therapy. Approximately 50,000 cells per tumor were characterized by mass cytometry and computational tools t-SNE/viSNE, FlowSOM, and MEM. The resulting single-cell view of melanoma treatment response revealed initially heterogeneous melanoma tumors were consistently cleared of Nestin-expressing melanoma cells. Melanoma cell subsets that persisted to week 4 were heterogeneous but expressed SOX2 or SOX10 proteins and specifically lacked surface expression of MHC I proteins by MEM analysis. Traditional histology imaging of tissue microarrays from the same tumors confirmed mass cytometry results, including persistence of NES- SOX10+ S100ß+ melanoma cells. This quantitative single-cell view of melanoma treatment response revealed protein features of malignant cells that are not eliminated by targeted therapy.