Method for the Analysis of the Tumor Microenvironment by Mass Cytometry: Application to Chronic Lymphocytic Leukemia

Eμ-TCL1 adoptive transfer mouse model of chronic lymphocytic leukemia

Despite being the most common adult leukemia in the western world, Chronic Lymphocytic Leukemia (CLL) remains a life-threatening and incurable disease. Efforts to develop new treatments are highly dependent on the availability of appropriate mouse models for pre-clinical testing. The Eμ-TCL1 mouse model is the most established pre-clinical approach to study CLL pathobiology and response to treatment, backed by numerous studies highlighting its resemblance to the most aggressive form of this malignancy. In contrast to the transgenic Eμ-TCL1 model, employing the adoptive transfer of Eμ-TCL1-derived splenocytes in immunocompetent C57BL/6 mice results in a comparably rapid (e.g., leukemic development within weeks compared to months in the transgenic model) and reliable model mimicking CLL. In this chapter, we would like to provide readers with a thoroughly optimized, detailed, and comprehensive protocol to use the adoptive transfer Eμ-TCL1 model in their research.

Profiling of Natural Killer Interactions With Cancer Cells Using Mass Cytometry

We developed a comprehensive method for functional assessment of the changes in immune populations and killing activity of peripheral blood mononuclear cells after cocultures with cancer cells using mass cytometry. In this study, a 43-marker mass cytometry panel was applied to a coculture of immune cells from healthy donors' peripheral blood mononuclear cells with diverse cancer cell lines. DNA content combined with classical CD45 surface staining was used as gating parameters for cocultures of immune cells (CD45high/DNAlow) with hematological (CD45low/DNAhigh) and solid cancer cell lines (CD45neg/DNAhigh). This strategy allows for universal discrimination of cancer cells from immune populations without the need for a specific cancer cell marker and simultaneous assessment of phenotypical changes in both populations. The use of mass cytometry allows for simultaneous detection of changes in natural killer, natural killer T cell, and T cell phenotypes and degranulation of immune populations upon target recognition, analysis of target cells for cytotoxic protein granzyme B content, and cancer cell death. These findings have broad applicability in research and clinical settings with the aim to phenotype and assess functional changes following not only NK-cancer cell interactions but also the effect of those interactions on other immune populations.

Novel approach to analysis of the immune system using an ungated model of immune surface marker abundance to predict health outcomes

Traditionally, the immune system is understood to be divided into discrete cell types that are identified via surface markers. While some cell type distinctions are no doubt discrete, others may in fact vary on a continum, and even within discrete types, differences in surface marker abundance could have functional implications. Here we propose a new way of looking at immune data, which is by looking directly at the values of the surface markers without dividing the cells into different subtypes. To assess the merit of this approach, we compared it with manual gating using cytometry data from the Singapore Longitudinal Aging Study (SLAS) database. We used two different neural networks (one for each method) to predict the presence of several health conditions. We found that the model built using raw surface marker abundance outperformed the manual gating one and we were able to identify some markers that contributed more to the predictions. This study is intended as a brief proof-of-concept and was not designed to predict health outcomes in an applied setting; nonetheless, it demonstrates that alternative methods to understand the structure of immune variation hold substantial progress.

Simplified mass cytometry protocol for in-plate staining, barcoding, and cryopreservation of human PBMC samples in clinical trials

With the increasing use of mass cytometry in clinical research, a simplified and standardized protocol for immunophenotyping human peripheral blood mononuclear cells (PBMCs) in clinical trials is needed. We present a simplified in-plate staining protocol for up to 80 samples, for laboratories of all mass cytometry expertise levels, aimed to generate reproducible datasets for large clinical cohorts. In this protocol, we provide details on the requirements to obtain meaningful results, spanning from sample quality, barcoding, and batch-freezing of stained samples.

CyTOF® for the Masses

Mass cytometry has revolutionized immunophenotyping, particularly in exploratory settings where simultaneous breadth and depth of characterization of immune populations is needed with limited samples such as in preclinical and clinical tumor immunotherapy. Mass cytometry is also a powerful tool for single-cell immunological assays, especially for complex and simultaneous characterization of diverse intratumoral immune subsets or immunotherapeutic cell populations. Through the elimination of spectral overlap seen in optical flow cytometry by replacement of fluorescent labels with metal isotopes, mass cytometry allows, on average, robust analysis of 60 individual parameters simultaneously. This is, however, associated with significantly increased complexity in the design, execution, and interpretation of mass cytometry experiments. To address the key pitfalls associated with the fragmentation, complexity, and analysis of data in mass cytometry for immunologists who are novices to these techniques, we have developed a comprehensive resource guide. Included in this review are experiment and panel design, antibody conjugations, sample staining, sample acquisition, and data pre-processing and analysis. Where feasible multiple resources for the same process are compared, allowing researchers experienced in flow cytometry but with minimal mass cytometry expertise to develop a data-driven and streamlined project workflow. It is our hope that this manuscript will prove a useful resource for both beginning and advanced users of mass cytometry.

Flow Cytometry and Mass Cytometry for Measuring the Immune Cell Infiltrate in Atherosclerotic Arteries

Atherosclerosis is characterized by the abundant infiltration of immune cells starting at early stages and progressing to late stages of the disease. The study and characterization of immune cells infiltrating and residing in the aorta has being tackled by several methodologies such as flow cytometry and mass cytometry (CyTOF). Flow cytometry has been primarily used to address the aortic leukocyte composition; however, only a limited number of markers can be analyzed simultaneously. CyTOF started to overcome these limitations by employing rare element-tagged antibodies and combines mass spectrometry with the ease and precision of flow cytometry. CyTOF currently allows for the simultaneous measurement of more than 40 cellular parameters at single-cell resolution.In this chapter, we describe the methodology used to isolate single immune cells from mouse aortas, followed by protocols for flow cytometry and CyTOF for aortic immune cell characterization.

New insights into the tumour immune microenvironment of nasopharyngeal carcinoma

Nasopharyngeal carcinoma (NPC) is unique among head and neck cancers for its strong causative association with Epstein Barr-Virus and high levels of immune infiltration that play a role in pathogenesis. As such, immunotherapy for the treatment of NPC is a promising area of research in the pursuit of improving patient outcomes. Understanding the tumour immune microenvironment (TIME) of NPC is the key to developing targeted immunotherapies and stratifying patients to determine optimal treatment regimens. Recent research has uncovered distinct characteristics of the TIME in NPC as well as important differences between the different disease subtypes; however, reviewing the state of the field reveals a further need for the application of novel techniques like multiplexed hyperspectral imaging and mass cytometry. These techniques can be used to identify spatial, compositional, and functional aspects of the TIME in NPC such as immune cell sociology, novel immune populations, and differences in immune-related signalling pathways in NPC in order to identify clinically relevant characteristics for targeted immunotherapy development and biomarker discovery.

Mass cytometry profiling of human dendritic cells in blood and tissues

The immune system comprises distinct functionally specialized cell populations, which can be characterized in depth by mass cytometry protein profiling. Unfortunately, the low-throughput nature of mass cytometry has made it challenging to analyze minor cell populations. This is the case for dendritic cells, which represent 0.2-2% of all immune cells in tissues and yet perform the critical task of initiating and modulating immune responses. Here, we provide an optimized step-by-step protocol for the characterization of well-known and emerging human dendritic cell populations in blood and tissues using mass cytometry. We provide detailed instructions for the generation of single-cell suspensions, sample enrichment, staining, acquisition and data analysis. We also include a barcoding option that reduces acquisition variability and allows the analysis of low numbers of dendritic cells, i.e., ~20,000. In contrast to other protocols, we emphasize the use of negative selection approaches to enrich for minor populations of immune cells while avoiding their activation. The entire procedure can be completed in 2-3 d and can be conveniently paused at several stages. The procedure described in this robust and reliable protocol allows the analysis of human dendritic cells in health and disease and during vaccination.

Advanced Flow Cytometry Analysis Algorithms for Optimizing the Detection of "Different From Normal" Immunophenotypes in Acute Myeloid Blasts

Acute myeloid leukemias (AMLs) are a group of hematologic malignancies that are heterogeneous in their molecular and immunophenotypic profiles. Identification of the immunophenotypic differences between AML blasts and normal myeloid hematopoietic precursors (myHPCs) is a prerequisite to achieving better performance in AML measurable residual disease follow-ups. In the present study, we applied high-dimensional analysis algorithms provided by the Infinicyt 2.0 and Cytobank software to evaluate the efficacy of antibody combinations of the EuroFlow AML/myelodysplastic syndrome panel to distinguish AML blasts with recurrent genetic abnormalities (n = 39 AML samples) from normal CD45low CD117+ myHPCs (n = 23 normal bone marrow samples). Two types of scores were established to evaluate the abilities of the various methods to identify the most useful parameters/markers for distinguishing between AML blasts and normal myHPCs, as well as to distinguish between different AML groups. The Infinicyt Compass database-guided analysis was found to be a more user-friendly tool than other analysis methods implemented in the Cytobank software. According to the developed scoring systems, the principal component analysis based algorithms resulted in better discrimination between AML blasts and myHPCs, as well as between blasts from different AML groups. The most informative markers for the discrimination between myHPCs and AML blasts were CD34, CD36, human leukocyte antigen-DR (HLA-DR), CD13, CD105, CD71, and SSC, which were highly rated by all evaluated analysis algorithms. The HLA-DR, CD34, CD13, CD64, CD33, CD117, CD71, CD36, CD11b, SSC, and FSC were found to be useful for the distinction between blasts from different AML groups associated with recurrent genetic abnormalities. This study identified both benefits and the drawbacks of integrating multiple high-dimensional algorithms to gain complementary insights into the flow-cytometry data.

The Tumor Microenvironment-Dependent Transcription Factors AHR and HIF-1α Are Dispensable for Leukemogenesis in the Eµ-TCL1 Mouse Model of Chronic Lymphocytic Leukemia

Simple Summary

Chronic lymphocytic leukemia (CLL) is the most common leukemia in Western countries, mostly affecting the elderly. The survival of leukemic cells depends on multiple soluble factors and on the stimulation of the BCR signaling pathway. Microenvironment-dependent transcription factors also contribute to CLL biology. Here, we generated new transgenic murine conditional knock-out models of CLL to study the role of the two transcription factors HIF-1α and AHR. Unexpectedly, we observed that both factors are dispensable for leukemia development in these models.

Abstract

Chronic lymphocytic leukemia (CLL) is the most frequent leukemia in the elderly and is characterized by the accumulation of mature B lymphocytes in peripheral blood and primary lymphoid organs. In order to proliferate, leukemic cells are highly dependent on complex interactions with their microenvironment in proliferative niches. Not only soluble factors and BCR stimulation are important for their survival and proliferation, but also the activation of transcription factors through different signaling pathways. The aryl hydrocarbon receptor (AHR) and hypoxia-inducible factor (HIF)-1α are two transcription factors crucial for cancer development, whose activities are dependent on tumor microenvironment conditions, such as the presence of metabolites from the tryptophan pathway and hypoxia, respectively. In this study, we addressed the potential role of AHR and HIF-1α in chronic lymphocytic leukemia (CLL) development in vivo. To this end, we crossed the CLL mouse model Eµ-TCL1 with the corresponding transcription factor-conditional knock-out mice to delete one or both transcription factors in CD19+ B cells only. Despite AHR and HIF-1α being activated in CLL cells, deletion of either or both of them had no impact on CLL progression or survival in vivo, suggesting that these transcription factors are not crucial for leukemogenesis in CLL.