Best practices for user consultation in flow cytometry shared resource laboratories.

This "Best Practices in User Consultation" article is the result of a 2022 International Society for the Advancement of Cytometry (ISAC) membership survey that collected valuable insights from the shared research laboratory (SRL) community and of a group discussion at the CYTO 2022 workshop of the same name. One key takeaway is the importance of initiating a consultation at the outset of a flow cytometry project, particularly for trainees. This approach enables the improvement and standardization of every step, from planning experiments to interpreting data.

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.

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.

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.

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.

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

Unlabelled: 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.

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.

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.

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.

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.

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.

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.

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 BRAF melanoma. Tumor cells were biopsied before neoadjuvant therapy and compared to cells surgically resected from the same site after 4 weeks of therapy.

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.