Ruthenium counterstaining for imaging mass cytometry

Deep cell phenotyping and spatial analysis of multiplexed imaging with TRACERx-PHLEX

The growing scale and dimensionality of multiplexed imaging require reproducible and comprehensive yet user-friendly computational pipelines. TRACERx-PHLEX performs deep learning-based cell segmentation (deep-imcyto), automated cell-type annotation (TYPEx) and interpretable spatial analysis (Spatial-PHLEX) as three independent but interoperable modules. PHLEX generates single-cell identities, cell densities within tissue compartments, marker positivity calls and spatial metrics such as cellular barrier scores, along with summary graphs and spatial visualisations. PHLEX was developed using imaging mass cytometry (IMC) in the TRACERx study, validated using published Co-detection by indexing (CODEX), IMC and orthogonal data and benchmarked against state-of-the-art approaches. We evaluated its use on different tissue types, tissue fixation conditions, image sizes and antibody panels. As PHLEX is an automated and containerised Nextflow pipeline, manual assessment, programming skills or pathology expertise are not essential. PHLEX offers an end-to-end solution in a growing field of highly multiplexed data and provides clinically relevant insights.

The CD8+ T cell content of transbronchial biopsies from patients with a first episode of clinically stable grade A1 cellular rejection is associated with future chronic lung allograft dysfunction

BACKGROUND

T cells drive acute cellular rejection (ACR) and its progression to chronic lung allograft dysfunction (CLAD) following lung transplantation. International Society for Heart and Lung Transplantation grade A1 ACR without associated allograft dysfunction is often untreated, yet some patients develop progressive graft dysfunction. T-cell composition of A1 ACR lesions may have prognostic value; therefore, protein-level and epigenetic techniques were applied to transbronchial biopsy tissue to determine whether differential T-cell infiltration in recipients experiencing a first episode of stable grade A1 ACR (StA1R) is associated with early CLAD.

METHODS

Sixty-two patients experiencing a first episode of StA1R were divided into those experiencing CLAD within 2 years (n = 13) and those remaining CLAD-free for 5 or more years (n = 49). Imaging mass cytometry (IMC) was used to profile the spectrum and distribution of intragraft T cell phenotypes on a subcohort (n = 16; 8 early-CLAD and 8 no early-CLAD). Immunofluorescence was used to quantify CD4+, CD8+, and FOXP3+ cells. Separately, CD3+ cells were fluorescently labeled, micro-dissected, and the degree of Treg-specific demethylated region methylation was determined.

RESULTS

PhenoGraph unsupervised clustering on IMC revealed 50 unique immune cell subpopulations. Methylation and immunofluorescence analyses demonstrated no significant differences in Tregs between early-CLAD and no early-CLAD groups. Immunofluorescence revealed that patients who developed CLAD within 2 years of lung transplantation showed greater CD8+ T cell infiltration compared to those who remained CLAD-free for 5 or more years.

CONCLUSIONS

In asymptomatic patients with a first episode of A1 rejection, greater CD8+ T cell content may be indicative of worse long-term outlook.

Spatial Architecture of Myeloid and T Cells Orchestrates Immune Evasion and Clinical Outcome in Lung Cancer

Understanding the role of the tumor microenvironment (TME) in lung cancer is critical to improving patient outcomes. We identified four histology-independent archetype TMEs in treatment-naïve early-stage lung cancer using imaging mass cytometry in the TRACERx study (n = 81 patients/198 samples/2.3 million cells). In immune-hot adenocarcinomas, spatial niches of T cells and macrophages increased with clonal neoantigen burden, whereas such an increase was observed for niches of plasma and B cells in immune-excluded squamous cell carcinomas (LUSC). Immune-low TMEs were associated with fibroblast barriers to immune infiltration. The fourth archetype, characterized by sparse lymphocytes and high tumor-associated neutrophil (TAN) infiltration, had tumor cells spatially separated from vasculature and exhibited low spatial intratumor heterogeneity. TAN-high LUSC had frequent PIK3CA mutations. TAN-high tumors harbored recently expanded and metastasis-seeding subclones and had a shorter disease-free survival independent of stage. These findings delineate genomic, immune, and physical barriers to immune surveillance and implicate neutrophil-rich TMEs in metastasis.

SIGNIFICANCE

This study provides novel insights into the spatial organization of the lung cancer TME in the context of tumor immunogenicity, tumor heterogeneity, and cancer evolution. Pairing the tumor evolutionary history with the spatially resolved TME suggests mechanistic hypotheses for tumor progression and metastasis with implications for patient outcome and treatment. This article is featured in Selected Articles from This Issue, p. 897.

Decoding the tumor microenvironment with spatial technologies

Visualization of the cellular heterogeneity and spatial architecture of the tumor microenvironment (TME) is becoming increasingly important to understand mechanisms of disease progression and therapeutic response. This is particularly relevant in the era of cancer immunotherapy, in which the contexture of immune cell positioning within the tumor landscape has been proven to affect efficacy. Although single-cell technologies have mostly replaced conventional approaches to analyze specific cellular subsets within tumors, those that integrate a spatial dimension are now on the rise. In this Review, we assess the strengths and limitations of emerging spatial technologies with a focus on their applications in tumor immunology, as well as forthcoming opportunities for artificial intelligence (AI) and the value of integrating multiomics datasets to achieve a holistic picture of the TME.

A novel process for H&E, immunofluorescence, and imaging mass cytometry on a single slide with a concise analytics pipeline

Imaging mass cytometry (IMC) is a powerful spatial technology that utilizes cytometry time of flight to acquire multiplexed image datasets with up to 40 markers, via metal-tagged antibodies. Recent advances in IMC have led to the inclusion of RNAScope probes and multiple new analysis pipelines have led to faster analyses and better results. However, IMC still suffers from lower resolution (1 μm2 pixels) and relatively small regions of interest (ROIs) (<2 mm2 ) compared to other, light-based microscope technologies. Capturing higher-resolution images on serial sections causes great difficulty when attempting to align cells and structures across serial sections, especially when observing smaller cell types and structures. Therefore, we demonstrate the combination of H&E and multiplex immunofluorescence imaging, for much higher resolution of the structural and cellular compartments found throughout the entire tissue section, with the high-dimensionality of IMC for specific ROIs on a single slide. Additionally, we demonstrate a simple and effective open-source cell segmentation and IMC analysis pipeline with previously published and freely available software.

An end-to-end workflow for multiplexed image processing and analysis

Multiplexed imaging enables the simultaneous spatial profiling of dozens of biological molecules in tissues at single-cell resolution. Extracting biologically relevant information, such as the spatial distribution of cell phenotypes from multiplexed tissue imaging data, involves a number of computational tasks, including image segmentation, feature extraction and spatially resolved single-cell analysis. Here, we present an end-to-end workflow for multiplexed tissue image processing and analysis that integrates previously developed computational tools to enable these tasks in a user-friendly and customizable fashion. For data quality assessment, we highlight the utility of napari-imc for interactively inspecting raw imaging data and the cytomapper R/Bioconductor package for image visualization in R. Raw data preprocessing, image segmentation and feature extraction are performed using the steinbock toolkit. We showcase two alternative approaches for segmenting cells on the basis of supervised pixel classification and pretrained deep learning models. The extracted single-cell data are then read, processed and analyzed in R. The protocol describes the use of community-established data containers, facilitating the application of R/Bioconductor packages for dimensionality reduction, single-cell visualization and phenotyping. We provide instructions for performing spatially resolved single-cell analysis, including community analysis, cellular neighborhood detection and cell-cell interaction testing using the imcRtools R/Bioconductor package. The workflow has been previously applied to imaging mass cytometry data, but can be easily adapted to other highly multiplexed imaging technologies. This protocol can be implemented by researchers with basic bioinformatics training, and the analysis of the provided dataset can be completed within 5-6 h. An extended version is available at https://bodenmillergroup.github.io/IMCDataAnalysis/ .

Unlocking the Hidden Depths: Multi-Modal Integration of Imaging Mass Spectrometry-Based and Molecular Imaging Techniques

Multimodal imaging (MMI) has emerged as a powerful tool in clinical research, combining different imaging modes to acquire comprehensive information and enabling scientists and surgeons to study tissue identification, localization, metabolic activity, and molecular discovery, thus aiding in disease progression analysis. While multimodal instruments are gaining popularity, challenges such as non-standardized characteristics, custom software, inadequate commercial support, and integration issues with other instruments need to be addressed. The field of multimodal imaging or multiplexed imaging allows for simultaneous signal reproduction from multiple imaging strategies. Intraoperatively, MMI can be integrated into frameless stereotactic surgery. Recent developments in medical imaging modalities such as magnetic resonance imaging (MRI), and Positron Emission Topography (PET) have brought new perspectives to multimodal imaging, enabling early cancer detection, molecular tracking, and real-time progression monitoring. Despite the evidence supporting the role of MMI in surgical decision-making, there is a need for comprehensive studies to validate and perform integration at the intersection of multiple imaging technologies. They were integrating mass spectrometry-based technologies (e.g., imaging mass spectrometry (IMS), imaging mass cytometry (IMC), and Ion mobility mass spectrometry ((IM-IM) with medical imaging modalities, offering promising avenues for molecular discovery and clinical applications. This review emphasizes the potential of multi-omics approaches in tissue mapping using MMI integrated into desorption electrospray ionization (DESI) and matrix-assisted laser desorption ionization (MALDI), allowing for sequential analyses of the same section. By addressing existing knowledge gaps, this review encourages future research endeavors toward multi-omics approaches, providing a roadmap for future research and enhancing the value of MMI in molecular pathology for diagnosis.

Cell State and Cell Type: Deconvoluting Circulating Tumor Cell Populations in Liquid Biopsies by Multi-Omics

Bi-directional crosstalk between the tumor and the tumor microenvironment (TME) has been shown to increase the rate of tumor evolution and to play a key role in neoplastic progression, therapeutic resistance, and a patient's overall survival. Here, we set out to use a comprehensive liquid-biopsy analysis to study cancer and specific TME cells in circulation and their association with disease status. Cytokeratin+, CD45- circulating rare cells (CRCs) from nine breast and four prostate cancer patients were characterized through morphometrics, single-cell copy number analysis, and targeted multiplexed proteomics to delineate cancer cell lineage from other rare cells originating in the TME. We show that we can detect epithelial circulating tumor cells (EPI.CTC), CTCs undergoing epithelial-to-mesenchymal transition (EMT.CTC) and circulating endothelial cells (CECs) using a universal rare event detection platform (HDSCA). Longitudinal analysis of an index patient finds that CTCs are present at the time of disease progression, while CECs are predominately present at the time of stable disease. In a small cohort of prostate and breast cancer patients, we find high inter-patient and temporal intra-patient variability in the expression of tissue specific markers such as ER, HER2, AR, PSA and PSMA and EpCAM. Our study stresses the importance of the multi-omic characterization of circulating rare cells in patients with breast and prostate carcinomas, specifically highlighting overlapping and cell type defining proteo-genomic characteristics of CTCs and CECs.

Global and single-cell proteomics view of the co-evolution between neural progenitors and breast cancer cells in a co-culture model

Tumor neurogenesis, a process by which new nerves invade tumors, is a growing area of interest in cancer research. Nerve presence has been linked to aggressive features of various solid tumors, including breast and prostate cancer. A recent study suggested that the tumor microenvironment may influence cancer progression through recruitment of neural progenitor cells from the central nervous system. However, the presence of neural progenitors in human breast tumors has not been reported. Here, we investigate the presence of Doublecortin (DCX) and Neurofilament-Light (NFL) co-expressing (DCX+/NFL+) cells in patient breast cancer tissue using Imaging Mass Cytometry. To map the interaction between breast cancer cells and neural progenitor cells further, we created an in vitro model mimicking breast cancer innervation, and characterized using mass spectrometry-based proteomics on the two cell types as they co- evolved in co-culture. Our results indicate stromal presence of DCX+/NFL+ cells in breast tumor tissue from a cohort of 107 patient cases, and that neural interaction contribute to drive a more aggressive breast cancer phenotype in our co-culture models. Our results support that neural involvement plays an active role in breast cancer and warrants further studies on the interaction between nervous system and breast cancer progression.

Recent advances in microfluidics for single-cell functional proteomics

Single-cell proteomics (SCP) reveals phenotypic heterogeneity by profiling individual cells, their biological states and functional outcomes upon signaling activation that can hardly be probed via other omics characterizations. This has become appealing to researchers as it enables an overall more holistic view of biological details underlying cellular processes, disease onset and progression, as well as facilitates unique biomarker identification from individual cells. Microfluidic-based strategies have become methods of choice for single-cell analysis because they allow facile assay integrations, such as cell sorting, manipulation, and content analysis. Notably, they have been serving as an enabling technology to improve the sensitivity, robustness, and reproducibility of recently developed SCP methods. Critical roles of microfluidics technologies are expected to further expand rapidly in advancing the next phase of SCP analysis to reveal more biological and clinical insights. In this review, we will capture the excitement of the recent achievements of microfluidics methods for both targeted and global SCP, including efforts to enhance the proteomic coverage, minimize sample loss, and increase multiplexity and throughput. Furthermore, we will discuss the advantages, challenges, applications, and future prospects of SCP.

Reagents for Mass Cytometry

Mass cytometry (cytometry by time-of-flight detection [CyTOF]) is a bioanalytical technique that enables the identification and quantification of diverse features of cellular systems with single-cell resolution. In suspension mass cytometry, cells are stained with stable heavy-atom isotope-tagged reagents, and then the cells are nebulized into an inductively coupled plasma time-of-flight mass spectrometry (ICP-TOF-MS) instrument. In imaging mass cytometry, a pulsed laser is used to ablate ca. 1 μm² spots of a tissue section. The plume is then transferred to the CyTOF, generating an image of biomarker expression. Similar measurements are possible with multiplexed ion bean imaging (MIBI). The unit mass resolution of the ICP-TOF-MS detector allows for multiparametric analysis of (in principle) up to 130 different parameters. Currently available reagents, however, allow simultaneous measurement of up to 50 biomarkers. As new reagents are developed, the scope of information that can be obtained by mass cytometry continues to increase, particularly due to the development of new small molecule reagents which enable monitoring of active biochemistry at the cellular level. This review summarizes the history and current state of mass cytometry reagent development and elaborates on areas where there is a need for new reagents. Additionally, this review provides guidelines on how new reagents should be tested and how the data should be presented to make them most meaningful to the mass cytometry user community.

Single-cell high-dimensional imaging mass cytometry: one step beyond in oncology

Solid tumors have a dynamic ecosystem in which malignant and non-malignant (endothelial, stromal, and immune) cell types constantly interact. Importantly, the abundance, localization, and functional orientation of each cell component within the tumor microenvironment vary significantly over time and in response to treatment. Such intratumoral heterogeneity influences the tumor course and its sensitivity to treatments. Recently, high-dimensional imaging mass cytometry (IMC) has been developed to explore the tumor ecosystem at the single-cell level. In the last years, several studies demonstrated that IMC is a powerful tool to decipher the tumor complexity. In this review, we summarize the potential of this technology and how it may be useful for cancer research (from preclinical to clinical studies).

DUSP6 mediates resistance to JAK2 inhibition and drives leukemic progression

Myeloproliferative neoplasms (MPNs) exhibit a propensity for transformation to secondary acute myeloid leukemia (sAML), for which the underlying mechanisms remain poorly understood, resulting in limited treatment options and dismal clinical outcomes. Here, we performed single-cell RNA sequencing on serial MPN and sAML patient stem and progenitor cells, identifying aberrantly increased expression of DUSP6 underlying disease transformation. Pharmacologic dual-specificity phosphatase (DUSP)6 targeting led to inhibition of S6 and Janus kinase (JAK)-signal transducer and activator of transcription (STAT) signaling while also reducing inflammatory cytokine production. DUSP6 perturbation further inhibited ribosomal S6 kinase (RSK)1, which we identified as a second indispensable candidate associated with poor clinical outcome. Ectopic expression of DUSP6 mediated JAK2-inhibitor resistance and exacerbated disease severity in patient-derived xenograft (PDX) models. Contrastingly, DUSP6 inhibition potently suppressed disease development across Jak2V617F and MPLW515L MPN mouse models and sAML PDXs without inducing toxicity in healthy controls. These findings underscore DUSP6 in driving disease transformation and highlight the DUSP6-RSK1 axis as a vulnerable, druggable pathway in myeloid malignancies.

Metabolic adaptation of ovarian tumors in patients treated with an IDO1 inhibitor constrains antitumor immune responses

To uncover underlying mechanisms associated with failure of indoleamine 2,3-dioxygenase 1 (IDO1) blockade in clinical trials, we conducted a pilot, window-of-opportunity clinical study in 17 patients with newly diagnosed advanced high-grade serous ovarian cancer before their standard tumor debulking surgery. Patients were treated with the IDO1 inhibitor epacadostat, and immunologic, transcriptomic, and metabolomic characterization of the tumor microenvironment was undertaken in baseline and posttreatment tumor biopsies. IDO1 inhibition resulted in efficient blockade of the kynurenine pathway of tryptophan degradation and was accompanied by a metabolic adaptation that shunted tryptophan catabolism toward the serotonin pathway. This resulted in elevated nicotinamide adenine dinucleotide (NAD⁺), which reduced T cell proliferation and function. Because NAD⁺ metabolites could be ligands for purinergic receptors, we investigated the impact of blocking purinergic receptors in the presence or absence of NAD⁺ on T cell proliferation and function in our mouse model. We demonstrated that A2a and A2b purinergic receptor antagonists, SCH58261 or PSB1115, respectively, rescued NAD⁺-mediated suppression of T cell proliferation and function. Combining IDO1 inhibition and A2a/A2b receptor blockade improved survival and boosted the antitumor immune signature in mice with IDO1 overexpressing ovarian cancer. These findings elucidate the downstream adaptive metabolic consequences of IDO1 blockade in ovarian cancers that may undermine antitumor T cell responses in the tumor microenvironment.

Immune landscape of human placental villi using single-cell analysis

Maintenance of a healthy pregnancy is reliant on a successful balance between the fetal and maternal immune systems. Although the maternal mechanisms responsible have been well studied, those used by the fetal immune system remain poorly understood. Using suspension mass cytometry and various imaging modalities, we report a complex immune system within the mid-gestation (17-23 weeks) human placental villi (PV). Consistent with recent reports in other fetal organs, T cells with memory phenotypes, although rare in abundance, were detected within the PV tissue and vasculature. Moreover, we determined that T cells isolated from PV samples may be more proliferative after T cell receptor stimulation than adult T cells at baseline. Collectively, we identified multiple subtypes of fetal immune cells within the PV and specifically highlight the enhanced proliferative capacity of fetal PV T cells.

A SIMPLI (Single-cell Identification from MultiPLexed Images) approach for spatially-resolved tissue phenotyping at single-cell resolution

Multiplexed imaging technologies enable the study of biological tissues at single-cell resolution while preserving spatial information. Currently, high-dimension imaging data analysis is technology-specific and requires multiple tools, restricting analytical scalability and result reproducibility. Here we present SIMPLI (Single-cell Identification from MultiPLexed Images), a flexible and technology-agnostic software that unifies all steps of multiplexed imaging data analysis. After raw image processing, SIMPLI performs a spatially resolved, single-cell analysis of the tissue slide as well as cell-independent quantifications of marker expression to investigate features undetectable at the cell level. SIMPLI is highly customisable and can run on desktop computers as well as high-performance computing environments, enabling workflow parallelisation for large datasets. SIMPLI produces multiple tabular and graphical outputs at each step of the analysis. Its containerised implementation and minimum configuration requirements make SIMPLI a portable and reproducible solution for multiplexed imaging data analysis. Software is available at “SIMPLI [https://github.com/ciccalab/SIMPLI]”.

Current high-dimension imaging data analysis methods are technology-specific and require multiple tools, restricting analytical scalability and result reproducibility. Here the authors present SIMPLI, a software that overcomes these limitations for single-cell and pixel analysis of multiplexed images at spatial resolution.

Three-dimensional imaging mass cytometry for highly multiplexed molecular and cellular mapping of tissues and the tumor microenvironment

A holistic understanding of tissue and organ structure and function requires the detection of molecular constituents in their original three-dimensional (3D) context. Imaging mass cytometry (IMC) enables simultaneous detection of up to 40 antigens and transcripts using metal-tagged antibodies but has so far been restricted to two-dimensional imaging. Here we report the development of 3D IMC for multiplexed 3D tissue analysis at single-cell resolution and demonstrate the utility of the technology by analysis of human breast cancer samples. The resulting 3D models reveal cellular and microenvironmental heterogeneity and cell-level tissue organization not detectable in two dimensions. 3D IMC will prove powerful in the study of phenomena occurring in 3D space such as tumor cell invasion and is expected to provide invaluable insights into cellular microenvironments and tissue architecture.

Using Imaging Mass Cytometry to Define Cell Identities and Interactions in Human Tissues

In the evolving landscape of highly multiplexed imaging techniques that can be applied to study complex cellular microenvironments, this review characterizes the use of imaging mass cytometry (IMC) to study the human kidney. We provide technical details for antibody validation, cell segmentation, and data analysis specifically tailored to human kidney samples, and elaborate on phenotyping of kidney cell types and novel insights that IMC can provide regarding pathophysiological processes in the injured or diseased kidney. This review will provide the reader with the necessary background to understand both the power and the limitations of IMC and thus support better perception of how IMC analysis can improve our understanding of human disease pathogenesis and can be integrated with other technologies such as single cell sequencing and proteomics to provide spatial context to cellular data.

An Iodinated DAPI-Based Reagent for Mass Cytometry

Multiparametric single-cell analysis has seen dramatic improvements with the introduction of mass cytometry (MC) and imaging mass cytometry (IMC^™ ). These technologies expanded the number of biomarkers that can be identified simultaneously by using heavy-isotope-tagged antibody reagents. Small-molecule probes bearing heavy isotopes are emerging as additional useful functional reporters of cellular features. Realizing this, we explored the iodination of DAPI to produce a heavy-atom-substituted derivative of the commonly used fluorescent DNA stain. Although exhibiting a drastically reduced fluorescence emission profile, I-DAPI retains strong binding affinity for DNA. I-DAPI was used to detect cellular DNA in MC and IMC™ assays with comparable efficiency to known Ir-containing DNA intercalators. This work suggests repurposing well-known colorimetric stains through simple reactions could be an effective strategy to develop new, functional MC and IMC™ reagents.

Overview of multiplex immunohistochemistry/immunofluorescence techniques in the era of cancer immunotherapy

Conventional immunohistochemistry (IHC) is a widely used diagnostic technique in tissue pathology. However, this technique is associated with a number of limitations, including high inter-observer variability and the capacity to label only one marker per tissue section. This review details various highly multiplexed techniques that have emerged to circumvent these constraints, allowing simultaneous detection of multiple markers on a single tissue section and the comprehensive study of cell composition, cellular functional and cell-cell interactions. Among these techniques, multiplex Immunohistochemistry/Immunofluorescence (mIHC/IF) has emerged to be particularly promising. mIHC/IF provides high-throughput multiplex staining and standardized quantitative analysis for highly reproducible, efficient and cost-effective tissue studies. This technique has immediate potential for translational research and clinical practice, particularly in the era of cancer immunotherapy.

Immune monitoring using mass cytometry and related high-dimensional imaging approaches

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.

Laser ablation-ICP-TOFMS imaging of germ cell tumors of patients undergoing platinum-based chemotherapy

A low dispersion laser ablation setup in combination with inductively coupled plasma-time-of-flight mass spectrometry (LA-ICP-TOFMS) was applied to clinical samples of patients undergoing platinum-based chemotherapy.

Single-Cell Transcriptome Analysis Reveals Disease-Defining T-cell Subsets in the Tumor Microenvironment of Classic Hodgkin Lymphoma

Hodgkin lymphoma is characterized by an extensively dominant tumor microenvironment (TME) composed of different types of noncancerous immune cells with rare malignant cells. Characterization of the cellular components and their spatial relationship is crucial to understanding cross-talk and therapeutic targeting in the TME. We performed single-cell RNA sequencing of more than 127,000 cells from 22 Hodgkin lymphoma tissue specimens and 5 reactive lymph nodes, profiling for the first time the phenotype of the Hodgkin lymphoma-specific immune microenvironment at single-cell resolution. Single-cell expression profiling identified a novel Hodgkin lymphoma-associated subset of T cells with prominent expression of the inhibitory receptor LAG3, and functional analyses established this LAG3⁺ T-cell population as a mediator of immunosuppression. Multiplexed spatial assessment of immune cells in the microenvironment also revealed increased LAG3⁺ T cells in the direct vicinity of MHC class II-deficient tumor cells. Our findings provide novel insights into TME biology and suggest new approaches to immune-checkpoint targeting in Hodgkin lymphoma. SIGNIFICANCE: We provide detailed functional and spatial characteristics of immune cells in classic Hodgkin lymphoma at single-cell resolution. Specifically, we identified a regulatory T-cell-like immunosuppressive subset of LAG3⁺ T cells contributing to the immune-escape phenotype. Our insights aid in the development of novel biomarkers and combination treatment strategies targeting immune checkpoints.See related commentary by Fisher and Oh, p. 342.This article is highlighted in the In This Issue feature, p. 327.

Hair eruption initiates and commensal skin microbiota aggravate adverse events of anti-EGFR therapy

Epidermal growth factor receptor (EGFR)-targeted anticancer therapy induces stigmatizing skin toxicities affecting patients' quality of life and therapy adherence. The lack of mechanistic details underlying these adverse events hampers their management. We found that EGFR/ERK signaling is required in LRIG1-positive stem cells during de novo hair eruption to secure barrier integrity and prevent the invasion of commensal microbiota and inflammatory skin disease. EGFR-deficient epidermis is permissive for microbiota outgrowth and displays an atopic-like TH2-dominated signature. The opening of the follicular ostia during hair eruption allows invasion of commensal microbiota into the hair follicle, initiating an additional TH1 and TH17 response culminating in chronic folliculitis. Restoration of epidermal ERK signaling via prophylactic FGF7 treatment or transgenic SOS expression rescues the barrier defect in the absence of EGFR, highlighting a therapeutic anchor point. These data reveal that commensal skin microbiota provoke atopic-like inflammatory skin diseases by invading into the follicular opening of erupting hair.

Mass Cytometry Imaging for the Study of Human Diseases-Applications and Data Analysis Strategies

High parameter imaging is an important tool in the life sciences for both discovery and healthcare applications. Imaging Mass Cytometry (IMC) and Multiplexed Ion Beam Imaging (MIBI) are two relatively recent technologies which enable clinical samples to be simultaneously analyzed for up to 40 parameters at subcellular resolution. Importantly, these "Mass Cytometry Imaging" (MCI) modalities are being rapidly adopted for studies of the immune system in both health and disease. In this review we discuss, first, the various applications of MCI to date. Second, due to the inherent challenge of analyzing high parameter spatial data, we discuss the various approaches that have been employed for the processing and analysis of data from MCI experiments.

Methods for analyzing tellurium imaging mass cytometry data

Imaging mass cytometry (IMC) is a technique allowing visualization and quantification of over 40 biological parameters in a single experiment with subcellular spatial resolution, however most IMC experiments are limited to endpoint analysis with antibodies and DNA stains. Small molecules containing tellurium are promising probes for IMC due to their cell permeability, synthetic versatility, and most importantly their application to sequential labelling with isotopologous probes (SLIP) experiments. SLIP experiments with tellurium-containing probes allow quantification of intracellular biology at multiple timepoints with IMC. Despite the promise of tellurium in IMC, there are unique challenges in image processing associated with tellurium IMC data. Here, we address some of these issues by demonstrating the removal of xenon background signal, combining channels to improve signal-to-noise ratio, and calculating isotope transmission efficiency biases. These developments add accuracy to the unique temporal resolution afforded by tellurium IMC probes.

Cross-Species Single-Cell Analysis of Pancreatic Ductal Adenocarcinoma Reveals Antigen-Presenting Cancer-Associated Fibroblasts

Cancer-associated fibroblasts (CAF) are major players in the progression and drug resistance of pancreatic ductal adenocarcinoma (PDAC). CAFs constitute a diverse cell population consisting of several recently described subtypes, although the extent of CAF heterogeneity has remained undefined. Here we use single-cell RNA sequencing to thoroughly characterize the neoplastic and tumor microenvironment content of human and mouse PDAC tumors. We corroborate the presence of myofibroblastic CAFs and inflammatory CAFs and define their unique gene signatures in vivo. Moreover, we describe a new population of CAFs that express MHC class II and CD74, but do not express classic costimulatory molecules. We term this cell population "antigen-presenting CAFs" and find that they activate CD4⁺ T cells in an antigen-specific fashion in a model system, confirming their putative immune-modulatory capacity. Our cross-species analysis paves the way for investigating distinct functions of CAF subtypes in PDAC immunity and progression. SIGNIFICANCE: Appreciating the full spectrum of fibroblast heterogeneity in pancreatic ductal adenocarcinoma is crucial to developing therapies that specifically target tumor-promoting CAFs. This work identifies MHC class II-expressing CAFs with a capacity to present antigens to CD4⁺ T cells, and potentially to modulate the immune response in pancreatic tumors.See related commentary by Belle and DeNardo, p. 1001.This article is highlighted in the In This Issue feature, p. 983.

High-resolution imaging and single-cell analysis via laser ablation-inductively coupled plasma-mass spectrometry for the determination of membranous receptor expression levels in breast cancer cell lines using receptor-specific hybrid tracers

This work evaluates the possibility of placement of high-resolution imaging and single-cell analysis via laser ablation-inductively coupled plasma-mass spectrometry (LA-ICP-MS) within precision medicine by assessing the suitability of LA-ICP-MS as a micro-analytical technique for the localization and quantification of membranous receptors in heterogeneous cell samples that express both the membrane-bound receptors C-X-C chemokine receptor type 4 (CXCR4) and epidermal growth factor receptor (EGFR). Staining of the breast cancer cell lines MDA-MB-231 X4 and MDA-MB-468 was achieved using receptor-specific hybrid tracers, containing both a fluorophore and a DTPA single-lanthanide chelate. Prior to LA-ICP-MS imaging, fluorescence confocal microscopy (FCM) imaging was performed to localize the receptors, hereby enabling direct comparison. Based on the different expression levels of CXCR4 and EGFR, a distinction could be made between the cell lines using both imaging modalities. Furthermore, FCM and LA-ICP-MS demonstrated complementary characteristics, as a more distinct discrimination could be made between both cell lines based on the EGFR-targeting hybrid tracer via LA-ICP-MS, due to the intrinsic CXCR4-related green fluorescent protein (GFP) signal present in the MDA-MB-231 X4 cells. Employing state-of-the-art LA-ICP-MS instrumentation in bidirectional area scanning mode for sub-cellular imaging of MDA-MB-231 X4 cells enabled the specific binding of the CXCR4-targeting hybrid tracer to the cell membrane to be clearly demonstrated. The stretching of cells over the glass substrate led to a considerably higher signal response for pixels at the cell edges, relative to the more central pixels. The determination of the expression levels of CXCR4 and EGFR for the MDA-MB-468 cell line was performed using LA-ICP-MS single-cell analysis (sc-LA-ICP-MS) and external calibration, based on the quantitative ablation of Ho-spiked dried gelatin droplet standards. Additionally, a second calibration approach was applied based on spot ablation of highly homogeneous dried gelatin gels in combination with the determination of the ablated volume using atomic force microscopy (AFM) and yielded results which were in good agreement with the expression levels determined via flow cytometry (FC) and mass cytometry (MC). Hybrid tracers enable a direct comparison between (i) FCM and LA-ICP-MS imaging for the evaluation of the microscopic binding pattern and between (ii) FC, MC and sc-LA-ICP-MS for the quantification of receptor expression levels in single cells.

Three-dimensional reconstruction of the distribution of elemental tags in single cells using laser ablation ICP-mass spectrometry via registration approaches

This paper describes a workflow towards the reconstruction of the three-dimensional elemental distribution profile within human cervical carcinoma cells (HeLa), at a spatial resolution down to 1 μm, employing state-of-the-art laser ablation-inductively coupled plasma-mass spectrometry (LA-ICP-MS) instrumentation. The suspended cells underwent a series of fixation/embedding protocols and were stained with uranyl acetate and an Ir-based DNA intercalator. A priori, laboratory-based absorption micro-computed tomography (μ-CT) was applied to acquire a reference frame of the morphology of the cells and their spatial distribution before sectioning. After CT analysis, a trimmed 300 × 300 × 300 μm³ block was sectioned into a sequential series of 132 sections with a thickness of 2 μm, which were subjected to LA-ICP-MS imaging. A pixel acquisition rate of 250 pixels s^-1 was achieved, through a bidirectional scanning strategy. After acquisition, the two-dimensional elemental images were reconstructed using the timestamps in the laser log file. The synchronization of the data required an improved optimization algorithm, which forces the pixels of scans in different ablation directions to be spatially coherent in the direction orthogonal to the scan direction. The volume was reconstructed using multiple registration approaches. Registration using the section outline itself as a fiducial marker resulted into a volume which was in good agreement with the morphology visualized in the μ-CT volume. The 3D μ-CT volume could be registered to the LA-ICP-MS volume, consisting of 2.9 × 10⁷ voxels, and the nucleus dimensions in 3D space could be derived.