Multi-center harmonization of flow cytometers in the context of the European “PRECISESADS” project

The role of immunophenotyping in common variable immunodeficiency: a narrative review

Common variable immunodeficiency (CVID) is a heterogeneous primary immunodeficiency (PID) characterized by an impaired immunoglobulin production, in association with an increased susceptibility to infections and a diversity of clinical manifestations. This narrative review summarizes immunophenotypic abnormalities in CVID patients and their relevance for diagnosis and disease classification. A comprehensive search across four databases - PubMED, Web of Science, EMBASE and Google Scholar - yielded 170 relevant studies published between 1988 and April 31, 2023. Over the past decades, the role of immunophenotyping in CVID diagnosis has become evident by identifying "hallmark" immunophenotypic aberrancies in patient subsets, with some now integrated in the consensus diagnostic criteria. Furthermore, the role of immunophenotyping in subclassifying CVID in relation to clinical presentation and prognosis has been extensively studied. Certain immunophenotypic patterns consistently correlate with clinical manifestations and/or subsets of CVID, particularly those associated with noninfectious complications (i.e. low switched memory B cells, shifts in follicular helper T cell subsets, low naïve CD4+ T cells, low regulatory T cells, and expansion of CD21low B cells, often associated with autoimmunity and/or splenomegaly). Also, efforts to associate subset levels of innate immune cells, such as Natural Killer (NK) cells, invariant (i)NKT cells, innate lymphoid cells (ILCs), and dendritic cells (DCs) to CVID complications are evident albeit in a lesser degree. However, inconsistencies regarding the role of flow cytometry in classification and prognosis persist, reflecting the disease complexity, but probably also cohort variations and methodological differences between published studies. This underscores the need for collaborative efforts to integrate emerging concepts, such as standardized flow cytometry and computational tools, for a more precise CVID classification approach. Additionally, recent studies suggest a potential value of (epi)genetic-based molecular assays to this effort.

The EuroFlow PIDOT external quality assurance scheme: enhancing laboratory performance evaluation in immunophenotyping of rare lymphoid immunodeficiencies

OBJECTIVES

The development of External Quality Assessment Schemes (EQAS) for clinical flow cytometry (FCM) is challenging in the context of rare (immunological) diseases. Here, we introduce a novel EQAS monitoring the primary immunodeficiency Orientation Tube (PIDOT), developed by EuroFlow, in both a 'wet' and 'dry' format. This EQAS provides feedback on the quality of individual laboratories (i.e., accuracy, reproducibility and result interpretation), while eliminating the need for sample distribution.

METHODS

In the wet format, marker staining intensities (MedFIs) within landmark cell populations in PIDOT analysis performed on locally collected healthy control (HC) samples, were compared to EQAS targets. In the dry format, participants analyzed centrally distributed PIDOT flow cytometry data (n=10).

RESULTS

We report the results of six EQAS rounds across 20 laboratories in 11 countries. The wet format (212 HC samples) demonstrated consistent technical performance among laboratories (median %rCV on MedFIs=34.5 %; average failure rate 17.3 %) and showed improvement upon repeated participation. The dry format demonstrated effective proficiency of participants in cell count enumeration (range %rCVs 3.1-7.1 % for the major lymphoid subsets), and in identifying lymphoid abnormalities (79.3 % alignment with reference).

CONCLUSIONS

The PIDOT-EQAS allows laboratories, adhering to the standardized EuroFlow approach, to monitor interlaboratory variations without the need for sample distribution, and provides them educational support to recognize rare clinically relevant immunophenotypic patterns of primary immunodeficiencies (PID). This EQAS contributes to quality improvement of PID diagnostics and can serve as an example for future flow cytometry EQAS in the context of rare diseases.

T Cell Peptide Prediction, Immune Response, and Host-Pathogen Relationship in Vaccinated and Recovered from Mild COVID-19 Subjects

COVID-19 remains a significant threat, particularly to vulnerable populations. The emergence of new variants necessitates the development of treatments and vaccines that induce both humoral and cellular immunity. This study aimed to identify potentially immunogenic SARS-CoV-2 peptides and to explore the intricate host-pathogen interactions involving peripheral immune responses, memory profiles, and various demographic, clinical, and lifestyle factors. Using in silico and experimental methods, we identified several CD8-restricted SARS-CoV-2 peptides that are either poorly studied or have previously unreported immunogenicity: fifteen from the Spike and three each from non-structural proteins Nsp1-2-3-16. A Spike peptide, LA-9, demonstrated a 57% response rate in ELISpot assays using PBMCs from 14 HLA-A*02:01 positive, vaccinated, and mild-COVID-19 recovered subjects, indicating its potential for diagnostics, research, and multi-epitope vaccine platforms. We also found that younger individuals, with fewer vaccine doses and longer intervals since infection, showed lower anti-Spike (ELISA) and anti-Wuhan neutralizing antibodies (pseudovirus assay), higher naïve T cells, and lower central memory, effector memory, and CD4hiCD8low T cells (flow cytometry) compared to older subjects. In our cohort, a higher prevalence of Vδ2-γδ and DN T cells, and fewer naïve CD8 T cells, seemed to correlate with strong cellular and lower anti-NP antibody responses and to associate with Omicron infection, absence of confusional state, and habitual sporting activity.

Interlaboratory comparison of high-throughput protein biomarker assay quantifications for radiation exposure classification

In the event of a widespread radiological incident, thousands of individuals will require rapid assessment of exposure using validated biodosimetry assays to inform clinical triage. In this scenario, multiple biodosimetry laboratories may be necessary for large-volume sample processing. To meet this need, we have developed a high-throughput assay for the rapid measurement of intracellular protein biomarkers in human peripheral blood samples using an Imaging Flow Cytometry (IFC) platform. The objective of this work was to harmonize and validate the reproducibility of our blood biomarker assay for radiation exposure across three IFC instruments, two located at Columbia University (CU) and the third at Health Canada. The Center for Radiological Research (CRR) at CU served as the central laboratory and reference instrument, where samples were prepared in triplicate, labeled with two radiation responsive leukocyte biomarkers (BAX and phosphor-p53 (Ser37)), and distributed for simultaneous interrogation by each IFC. Initial tests showed that significantly different baseline biomarker measurements were generated on each instrument when using the same acquisition settings, suggesting that harmonization of signal intensities is necessary. Subsequent tests harmonized biomarker measurements after irradiation by modulating laser intensity using two reference materials: unstained samples and standardized rainbow beads. Both methods generated measurements on each instrument without significant differences between the new and references instruments, allowing for the use of one master template to quantify biomarker expression across multiple instruments. Deming regression analyses of 0-5 Gy dose-response curves showed overall good correlation of BAX and p53 values across new and reference instruments. While Bland-Altman analyses indicated low to moderate instrument biases, ROC Curve analyses ultimately show successful discrimination between exposed and unexposed samples on each instrument (AUC values > 0.85).

Approaching Mass Cytometry Translational Studies by Experimental and Data Curation Settings

Clinical studies are conducted to better understand the pathological mechanism of diseases and to find biomarkers associated with disease activity, drug response, or outcome prediction. Mass cytometry (MC) is a high-throughput single-cell technology that measures hundreds of cells per second with more than 40 markers per cell. Thus, it is a suitable tool for immune monitoring and biomarker discovery studies. Working in translational and clinical settings requires a careful experimental design to minimize, monitor, and correct the variations introduced during sample collection, preparation, acquisition, and analysis. In this review, we will focus on these important aspects of MC-related experiments and data curation in the context of translational clinical research projects.

Antibody-mediated neutralization of galectin-3 as a strategy for the treatment of systemic sclerosis

Systemic sclerosis (SSc) is an autoimmune, inflammatory and fibrotic disease with limited treatment options. Developing new therapies is therefore crucial to address patient needs. To this end, we focused on galectin-3 (Gal-3), a lectin known to be associated with several pathological processes seen in SSc. Using RNA sequencing of whole-blood samples in a cross-sectional cohort of 249 patients with SSc, Gal-3 and its interactants defined a strong transcriptomic fingerprint associated with disease severity, pulmonary and cardiac malfunctions, neutrophilia and lymphopenia. We developed new Gal-3 neutralizing monoclonal antibodies (mAb), which were then evaluated in a mouse model of hypochlorous acid (HOCl)-induced SSc. We show that two of these antibodies, D11 and E07, reduced pathological skin thickening, lung and skin collagen deposition, pulmonary macrophage content, and plasma interleukin-5 and -6 levels. Moreover, E07 changed the transcriptional profiles of HOCl-treated mice, resulting in a gene expression pattern that resembled that of control mice. Similarly, pathological pathways engaged in patients with SSc were counteracted by E07 in mice. Collectively, these findings demonstrate the translational potential of Gal-3 blockade as a therapeutic option for SSc.

Eosinophils as potential biomarkers in respiratory viral infections

Eosinophils are bone marrow-derived granulocytes that, under homeostatic conditions, account for as much as 1-3% of peripheral blood leukocytes. During inflammation, eosinophils can rapidly expand and infiltrate inflamed tissues, guided by cytokines and alarmins (such as IL-33), adhesion molecules and chemokines. Eosinophils play a prominent role in allergic asthma and parasitic infections. Nonetheless, they participate in the immune response against respiratory viruses such as respiratory syncytial virus and influenza. Notably, respiratory viruses are associated with asthma exacerbation. Eosinophils release several molecules endowed with antiviral activity, including cationic proteins, RNases and reactive oxygen and nitrogen species. On the other hand, eosinophils release several cytokines involved in homeostasis maintenance and Th2-related inflammation. In the context of SARS-CoV-2 infection, emerging evidence indicates that eosinophils can represent possible blood-based biomarkers for diagnosis, prognosis, and severity prediction of disease. In particular, eosinopenia seems to be an indicator of severity among patients with COVID-19, whereas an increased eosinophil count is associated with a better prognosis, including a lower incidence of complications and mortality. In the present review, we provide an overview of the role and plasticity of eosinophils focusing on various respiratory viral infections and in the context of viral and allergic disease comorbidities. We will discuss the potential utility of eosinophils as prognostic/predictive immune biomarkers in emerging respiratory viral diseases, particularly COVID-19. Finally, we will revisit some of the relevant methods and tools that have contributed to the advances in the dissection of various eosinophil subsets in different pathological settings for future biomarker definition.

Deep Immunophenotyping of Human Whole Blood by Standardized Multi-parametric Flow Cytometry Analyses

Immunophenotyping is proving crucial to understanding the role of the immune system in health and disease. High-throughput flow cytometry has been used extensively to reveal changes in immune cell composition and function at the single-cell level. Here, we describe six optimized 11-color flow cytometry panels for deep immunophenotyping of human whole blood. A total of 51 surface antibodies, which are readily available and validated, were selected to identify the key immune cell populations and evaluate their functional state in a single assay. The gating strategies for effective flow cytometry data analysis are included in the protocol. To ensure data reproducibility, we provide detailed procedures in three parts, including (1) instrument characterization and detector gain optimization, (2) antibody titration and sample staining, and (3) data acquisition and quality checks. This standardized approach has been applied to a variety of donors for a better understanding of the complexity of the human immune system.

Supplementary Information

The online version contains supplementary material available at 10.1007/s43657-022-00092-9.

Protocol for large scale whole blood immune monitoring by mass cytometry and Cyto Quality Pipeline

Mass cytometry (MC) is a powerful large-scale immune monitoring technology. To maximize MC data quality, we present a protocol for whole blood analysis together with an R package, Cyto Quality Pipeline (CytoQP), which minimizes the experimental artifacts and batch effects to ensure data reproducibility. We describe the steps to stimulate, fix, and freeze blood samples before acquisition to make them suitable for retrospective studies. We then detail the use of barcoding and reference samples to facilitate multicenter and multi-batch experiments. For complete details on the use and execution of this protocol, please refer to Rybakowska et al. (2021a) and (2021b).

ImmUniverse Consortium: Multi-omics integrative approach in personalized medicine for immune-mediated inflammatory diseases

Immune mediated inflammatory diseases (IMIDs) are a heterogeneous group of debilitating, multifactorial and unrelated conditions featured by a dysregulated immune response leading to destructive chronic inflammation. The immune dysregulation can affect various organ systems: gut (e.g., inflammatory bowel disease), joints (e.g., rheumatoid arthritis), skin (e.g., psoriasis, atopic dermatitis), resulting in significant morbidity, reduced quality of life, increased risk for comorbidities, and premature death. As there are no reliable disease progression and therapy response biomarkers currently available, it is very hard to predict how the disease will develop and which treatments will be effective in a given patient. In addition, a considerable proportion of patients do not respond sufficiently to the treatment. ImmUniverse is a large collaborative consortium of 27 partners funded by the Innovative Medicine Initiative (IMI), which is sponsored by the European Union (Horizon 2020) and in-kind contributions of participating pharmaceutical companies within the European Federation of Pharmaceutical Industries and Associations (EFPIA). ImmUniverse aims to advance our understanding of the molecular mechanisms underlying two immune-mediated diseases, ulcerative colitis (UC) and atopic dermatitis (AD), by pursuing an integrative multi-omics approach. As a consequence of the heterogeneity among IMIDs patients, a comprehensive, evidence-based identification of novel biomarkers is necessary to enable appropriate patient stratification that would account for the inter-individual differences in disease severity, drug efficacy, side effects or prognosis. This would guide clinicians in the management of patients and represent a major step towards personalized medicine. ImmUniverse will combine the existing and novel advanced technologies, including multi-omics, to characterize both the tissue microenvironment and blood. This comprehensive, systems biology-oriented approach will allow for identification and validation of tissue and circulating biomarker signatures as well as mechanistic principles, which will provide information about disease severity and future disease progression. This truly makes the ImmUniverse Consortium an unparalleled approach.

Mapping Cell Phenomics with Multiparametric Flow Cytometry Assays

Phenomics explores the complex interactions among genes, epigenetics, symbiotic microorganisms, diet, and environmental exposure based on the physical, chemical, and biological characteristics of individuals and groups. Increasingly efficient and comprehensive phenotyping techniques have been integrated into modern phenomics-related research. Multicolor flow cytometry technology provides more measurement parameters than conventional flow cytometry. Based on detailed descriptions of cell phenotypes, rare cell populations and cell subsets can be distinguished, new cell phenotypes can be discovered, and cell apoptosis characteristics can be detected, which will expand the potential of cell phenomics research. Based on the enhancements in multicolor flow cytometry hardware, software, reagents, and method design, the present review summarizes the recent advances and applications of multicolor flow cytometry in cell phenomics, illuminating the potential of applying phenomics in future studies.

2021 White Paper on Recent Issues in Bioanalysis: ISR for Biomarkers, Liquid Biopsies, Spectral Cytometry, Inhalation/Oral & Multispecific Biotherapeutics, Accuracy/LLOQ for Flow Cytometry (Part 2 - Recommendations on Biomarkers/CDx Assays Development & Validation, Cytometry Validation & Innovation, Biotherapeutics PK LBA Regulated Bioanalysis, Critical Reagents & Positive Controls Generation)

The 15th edition of the Workshop on Recent Issues in Bioanalysis (15th WRIB) was held on 27 September to 1 October 2021. Even with a last-minute move from in-person to virtual, an overwhelmingly high number of nearly 900 professionals representing pharma and biotech companies, contract research organizations (CROs), and multiple regulatory agencies still eagerly convened to actively discuss the most current topics of interest in bioanalysis. The 15th WRIB included three Main Workshops and seven Specialized Workshops that together spanned 1 week in order to allow exhaustive and thorough coverage of all major issues in bioanalysis, biomarkers, immunogenicity, gene therapy, cell therapy and vaccines. Moreover, in-depth workshops on biomarker assay development and validation (BAV) (focused on clarifying the confusion created by the increased use of the term "context of use" [COU]); mass spectrometry of proteins (therapeutic, biomarker and transgene); state-of-the-art cytometry innovation and validation; and critical reagent and positive control generation were the special features of the 15th edition. This 2021 White Paper encompasses recommendations emerging from the extensive discussions held during the workshop, and is aimed to provide the bioanalytical community with key information and practical solutions on topics and issues addressed, in an effort to enable advances in scientific excellence, improved quality and better regulatory compliance. Due to its length, the 2021 edition of this comprehensive White Paper has been divided into three parts for editorial reasons. This publication (Part 2) covers the recommendations on ISR for Biomarkers, Liquid Biopsies, Spectral Cytometry, Inhalation/Oral & Multispecific Biotherapeutics, Accuracy/LLOQ for Flow Cytometry. Part 1A (Endogenous Compounds, Small Molecules, Complex Methods, Regulated Mass Spec of Large Molecules, Small Molecule, PoC), Part 1B (Regulatory Agencies' Inputs on Bioanalysis, Biomarkers, Immunogenicity, Gene & Cell Therapy and Vaccine) and Part 3 (TAb/NAb, Viral Vector CDx, Shedding Assays; CRISPR/Cas9 & CAR-T Immunogenicity; PCR & Vaccine Assay Performance; ADA Assay Comparability & Cut Point Appropriateness) are published in volume 14 of Bioanalysis, issues 9 and 11 (2022), respectively.

Prediction of standard cell types and functional markers from textual descriptions of flow cytometry gating definitions using machine learning

BACKGROUND

A key step in clinical flow cytometry data analysis is gating, which involves the identification of cell populations. The process of gating produces a set of reportable results, which are typically described by gating definitions. The non-standardized, non-interpreted nature of gating definitions represents a hurdle for data interpretation and data sharing across and within organizations. Interpreting and standardizing gating definitions for subsequent analysis of gating results requires a curation effort from experts. Machine learning approaches have the potential to help in this process by predicting expert annotations associated with gating definitions.

METHODS

We created a gold-standard dataset by manually annotating thousands of gating definitions with cell type and functional marker annotations. We used this dataset to train and test a machine learning pipeline able to predict standard cell types and functional marker genes associated with gating definitions.

RESULTS

The machine learning pipeline predicted annotations with high accuracy for both cell types and functional marker genes. Accuracy was lower for gating definitions from assays belonging to laboratories from which limited or no prior data was available in the training. Manual error review ensured that resulting predicted annotations could be reused subsequently as additional gold-standard training data.

CONCLUSIONS

Machine learning methods are able to consistently predict annotations associated with gating definitions from flow cytometry assays. However, a hybrid automatic and manual annotation workflow would be recommended to achieve optimal results.

Integrative epigenomics in Sjögren´s syndrome reveals novel pathways and a strong interaction between the HLA, autoantibodies and the interferon signature

Primary Sjögren's syndrome (SS) is a systemic autoimmune disease characterized by lymphocytic infiltration and damage of exocrine salivary and lacrimal glands. The etiology of SS is complex with environmental triggers and genetic factors involved. By conducting an integrated multi-omics study, we confirmed a vast coordinated hypomethylation and overexpression effects in IFN-related genes, what is known as the IFN signature. Stratified and conditional analyses suggest a strong interaction between SS-associated HLA genetic variation and the presence of Anti-Ro/SSA autoantibodies in driving the IFN epigenetic signature and determining SS. We report a novel epigenetic signature characterized by increased DNA methylation levels in a large number of genes enriched in pathways such as collagen metabolism and extracellular matrix organization. We identified potential new genetic variants associated with SS that might mediate their risk by altering DNA methylation or gene expression patterns, as well as disease-interacting genetic variants that exhibit regulatory function only in the SS population. Our study sheds new light on the interaction between genetics, autoantibody profiles, DNA methylation and gene expression in SS, and contributes to elucidate the genetic architecture of gene regulation in an autoimmune population.

A new molecular classification to drive precision treatment strategies in primary Sjögren's syndrome

There is currently no approved treatment for primary Sjögren's syndrome, a disease that primarily affects adult women. The difficulty in developing effective therapies is -in part- because of the heterogeneity in the clinical manifestation and pathophysiology of the disease. Finding common molecular signatures among patient subgroups could improve our understanding of disease etiology, and facilitate the development of targeted therapeutics. Here, we report, in a cross-sectional cohort, a molecular classification scheme for Sjögren's syndrome patients based on the multi-omic profiling of whole blood samples from a European cohort of over 300 patients, and a similar number of age and gender-matched healthy volunteers. Using transcriptomic, genomic, epigenetic, cytokine expression and flow cytometry data, combined with clinical parameters, we identify four groups of patients with distinct patterns of immune dysregulation. The biomarkers we identify can be used by machine learning classifiers to sort future patients into subgroups, allowing the re-evaluation of response to treatments in clinical trials.

Integrative Analysis Reveals a Molecular Stratification of Systemic Autoimmune Diseases

OBJECTIVE

Clinical heterogeneity, a hallmark of systemic autoimmune diseases, impedes early diagnosis and effective treatment, issues that may be addressed if patients could be classified into groups defined by molecular pattern. This study was undertaken to identify molecular clusters for reclassifying systemic autoimmune diseases independently of clinical diagnosis.

METHODS

Unsupervised clustering of integrated whole blood transcriptome and methylome cross-sectional data on 955 patients with 7 systemic autoimmune diseases and 267 healthy controls was undertaken. In addition, an inception cohort was prospectively followed up for 6 or 14 months to validate the results and analyze whether or not cluster assignment changed over time.

RESULTS

Four clusters were identified and validated. Three were pathologic, representing "inflammatory," "lymphoid," and "interferon" patterns. Each included all diagnoses and was defined by genetic, clinical, serologic, and cellular features. A fourth cluster with no specific molecular pattern was associated with low disease activity and included healthy controls. A longitudinal and independent inception cohort showed a relapse-remission pattern, where patients remained in their pathologic cluster, moving only to the healthy one, thus showing that the molecular clusters remained stable over time and that single pathogenic molecular signatures characterized each individual patient.

CONCLUSION

Patients with systemic autoimmune diseases can be jointly stratified into 3 stable disease clusters with specific molecular patterns differentiating different molecular disease mechanisms. These results have important implications for future clinical trials and the study of nonresponse to therapy, marking a paradigm shift in our view of systemic autoimmune diseases.

Natural killer cells activated through NKG2D mediate lung ischemia-reperfusion injury

Pulmonary ischemia-reperfusion injury (IRI) is a clinical syndrome of acute lung injury that occurs after lung transplantation or remote organ ischemia. IRI causes early mortality and has no effective therapies. While NK cells are innate lymphocytes capable of recognizing injured cells, their roles in acute lung injury are incompletely understood. Here, we demonstrated that NK cells were increased in frequency and cytotoxicity in 2 different IRI mouse models. We showed that NK cells trafficked to the lung tissue from peripheral reservoirs and were more mature within lung tissue. Acute lung ischemia-reperfusion injury was blunted in a NK cell-deficient mouse strain but restored with adoptive transfer of NK cells. Mechanistically, NK cell NKG2D receptor ligands were induced on lung endothelial and epithelial cells following IRI, and antibody-mediated NK cell depletion or NKG2D stress receptor blockade abrogated acute lung injury. In human lung tissue, NK cells were increased at sites of ischemia-reperfusion injury and activated NK cells were increased in prospectively collected human bronchoalveolar lavage in subjects with severe IRI. These data support a causal role for recipient peripheral NK cells in pulmonary IRI via NK cell NKG2D receptor ligation. Therapies targeting NK cells may hold promise in acute lung injury.

Genomic Risk Score impact on susceptibility to systemic sclerosis

OBJECTIVES

Genomic Risk Scores (GRS) successfully demonstrated the ability of genetics to identify those individuals at high risk for complex traits including immune-mediated inflammatory diseases (IMIDs). We aimed to test the performance of GRS in the prediction of risk for systemic sclerosis (SSc) for the first time.

METHODS

Allelic effects were obtained from the largest SSc Genome-Wide Association Study (GWAS) to date (9 095 SSc and 17 584 healthy controls with European ancestry). The best-fitting GRS was identified under the additive model in an independent cohort that comprised 400 patients with SSc and 571 controls. Additionally, GRS for clinical subtypes (limited cutaneous SSc and diffuse cutaneous SSc) and serological subtypes (anti-topoisomerase positive (ATA+) and anti-centromere positive (ACA+)) were generated. We combined the estimated GRS with demographic and immunological parameters in a multivariate generalised linear model.

RESULTS

The best-fitting SSc GRS included 33 single nucleotide polymorphisms (SNPs) and discriminated between patients with SSc and controls (area under the receiver operating characteristic (ROC) curve (AUC)=0.673). Moreover, the GRS differentiated between SSc and other IMIDs, such as rheumatoid arthritis and Sjögren's syndrome. Finally, the combination of GRS with age and immune cell counts significantly increased the performance of the model (AUC=0.787). While the SSc GRS was not able to discriminate between ATA+ and ACA+ patients (AUC<0.5), the serological subtype GRS, which was based on the allelic effects observed for the comparison between ACA+ and ATA+ patients, reached an AUC=0.693.

CONCLUSIONS

GRS was successfully implemented in SSc. The model discriminated between patients with SSc and controls or other IMIDs, confirming the potential of GRS to support early and differential diagnosis for SSc.

Stabilization of Human Whole Blood Samples for Multicenter and Retrospective Immunophenotyping Studies

Whole blood is often collected for large-scale immune monitoring studies to track changes in cell frequencies and responses using flow (FC) or mass cytometry (MC). In order to preserve sample composition and phenotype, blood samples should be analyzed within 24 h after bleeding, restricting the recruitment, analysis protocols, as well as biobanking. Herein, we have evaluated two whole blood preservation protocols that allow rapid sample processing and long-term stability. Two fixation buffers were used, Phosphoflow Fix and Lyse (BD) and Proteomic Stabilizer (PROT) to fix and freeze whole blood samples for up to 6 months. After analysis by an 8-plex panel by FC and a 26-plex panel by MC, manual gating of circulating leukocyte populations and cytokines was performed. Additionally, we tested the stability of a single sample over a 13-months period using 45 consecutive aliquots and a 34-plex panel by MC. We observed high correlation and low bias toward any cell population when comparing fresh and 6 months frozen blood with FC and MC. This correlation was confirmed by hierarchical clustering. Low coefficients of variation (CV) across studied time points indicate good sample preservation for up to 6 months. Cytokine detection stability was confirmed by low CVs, with some differences between fresh and fixed conditions. Thirteen months regular follow-up of PROT samples showed remarkable sample stability. Whole blood can be preserved for phenotyping and cytokine-response studies provided the careful selection of a compatible antibody panel. However, possible changes in cell morphology, differences in antibody affinity, and changes in cytokine-positive cell frequencies when compared to fresh blood should be considered. Our setting constitutes a valuable tool for multicentric and retrospective studies. © 2020 International Society for Advancement of Cytometry.

Genome-wide whole blood transcriptome profiling in a large European cohort of systemic sclerosis patients

OBJECTIVES

The analysis of annotated transcripts from genome-wide expression studies may help to understand the pathogenesis of complex diseases, such as systemic sclerosis (SSc). We performed a whole blood (WB) transcriptome analysis on RNA collected in the context of the European PRECISESADS project, aiming at characterising the pathways that differentiate SSc from controls and that are reproducible in geographically diverse populations.

METHODS

Samples from 162 patients and 252 controls were collected in RNA stabilisers. Cases and controls were divided into a discovery (n=79+163; Southern Europe) and validation cohort (n=83+89; Central-Western Europe). RNA sequencing was performed by an Illumina assay. Functional annotations of Reactome pathways were performed with the Functional Analysis of Individual Microarray Expression (FAIME) algorithm. In parallel, immunophenotyping of 28 circulating cell populations was performed. We tested the presence of differentially expressed genes/pathways and the correlation between absolute cell counts and RNA transcripts/FAIME scores in regression models. Results significant in both populations were considered as replicated.

RESULTS

Overall, 15 224 genes and 1277 functional pathways were available; of these, 99 and 225 were significant in both sets. Among replicated pathways, we found a deregulation in type-I interferon, Toll-like receptor cascade, tumour suppressor p53 protein function, platelet degranulation and activation. RNA transcripts or FAIME scores were jointly correlated with cell subtypes with strong geographical differences; neutrophils were the major determinant of gene expression in SSc-WB samples.

CONCLUSIONS

We discovered a set of differentially expressed genes/pathways validated in two independent sets of patients with SSc, highlighting a number of deregulated processes that have relevance for the pathogenesis of autoimmunity and SSc.

Standardization procedure for flow cytometry data harmonization in prospective multicenter studies

One of the most challenging objective for clinical cytometry in prospective multicenter immunomonitoring trials is to compare frequencies, absolute numbers of leukocyte populations and further the mean fluorescence intensities of cell markers, especially when the data are generated from different instruments. Here, we describe an innovative standardization workflow to compare all data to carry out any large-scale, prospective multicentric flow cytometry analysis whatever the duration, the number or type of instruments required for the realization of such projects.

Multicentre Harmonisation of a Six-Colour Flow Cytometry Panel for Naïve/Memory T Cell Immunomonitoring

Background

Personalised medicine in oncology needs standardised immunological assays. Flow cytometry (FCM) methods represent an essential tool for immunomonitoring, and their harmonisation is crucial to obtain comparable data in multicentre clinical trials. The objective of this study was to design a harmonisation workflow able to address the most effective issues contributing to intra- and interoperator variabilities in a multicentre project.

Methods

The Italian National Institute of Health (Istituto Superiore di Sanità, ISS) managed a multiparametric flow cytometric panel harmonisation among thirteen operators belonging to five clinical and research centres of Lazio region (Italy). The panel was based on a backbone mixture of dried antibodies (anti-CD3, anti-CD4, anti-CD8, anti-CD45RA, and anti-CCR7) to detect naïve/memory T cells, recognised as potential prognostic/predictive immunological biomarkers in cancer immunotherapies. The coordinating centre distributed frozen peripheral blood mononuclear cells (PBMCs) and fresh whole blood (WB) samples from healthy donors, reagents, and Standard Operating Procedures (SOPs) to participants who performed experiments by their own equipment, in order to mimic a real-life scenario. Operators returned raw and locally analysed data to ISS for central analysis and statistical elaboration.

Results

Harmonised and reproducible results were obtained by sharing experimental set-up and procedures along with centralising data analysis, leading to a reduction of cross-centre variability for naïve/memory subset frequencies particularly in the whole blood setting.

Conclusion

Our experimental and analytical working process proved to be suitable for the harmonisation of FCM assays in a multicentre setting, where high-quality data are required to evaluate potential immunological markers, which may contribute to select better therapeutic options.

Key steps and methods in the experimental design and data analysis of highly multi-parametric flow and mass cytometry

High-dimensional, single-cell cell technologies revolutionized the way to study biological systems, and polychromatic flow cytometry (FC) and mass cytometry (MC) are two of the drivers of this revolution. As up to 30-50 dimensions respectively can be measured per single-cell, they allow deep phenotyping combined with cellular functions studies, like cytokine production or protein phosphorylation. In parallel, the bioinformatics field develops algorithms that are able to process incoming data and extract the most useful and meaningful biological information. However, the success of automated analysis tools depends on the generation of high-quality data. In this review we present the most recent FC and MC computational approaches that are used to prepare, process and interpret high-content cytometry data. We also underscore proper experimental design as a key step for obtaining good quality data.

Flow cytometry evaluation of infection-related biomarkers in febrile subjects in the emergency department

Aim: In an Emergency Department (ED), the etiological identification of infected subjects is essential. 13 infection-related biomarkers were assessed using a new flow cytometry procedure. Materials & methods: If subjects presented with febrile symptoms at the ED, 13 biomarkers' levels, including CD64 on neutrophils (nCD64) and CD169 on monocytes (mCD169), were tested and compared with clinical records. Results: Among 50 subjects, 78% had bacterial infections and 8% had viral infections. nCD64 showed 82% sensitivity and 91% specificity for identifying subjects with bacterial infections. mCD169, HLA-ABC ratio and HLA-DR on monocytes had high values in subjects with viral infections. Conclusion: Biomarkers showed promising performances to improve the ED's infectious stratification.

Moving towards a molecular taxonomy of autoimmune rheumatic diseases

Autoimmune rheumatic diseases pose many problems that have, in general, already been solved in the field of cancer. The heterogeneity of each disease, the clinical similarities and differences between different autoimmune rheumatic diseases and the large number of patients that remain without a diagnosis underline the need to reclassify these diseases via new approaches. Knowledge about the molecular basis of systemic autoimmune diseases, along with the availability of bioinformatics tools capable of handling and integrating large volumes of various types of molecular data at once, offer the possibility of reclassifying these diseases. A new taxonomy could lead to the discovery of new biomarkers for patient stratification and prognosis. Most importantly, this taxonomy might enable important changes in clinical trial design to reach the expected outcomes or the design of molecularly targeted therapies. In this Review, we discuss the basis for a new molecular taxonomy for autoimmune rheumatic diseases. We highlight the evidence surrounding the idea that these diseases share molecular features related to their pathogenesis and development and discuss previous attempts to classify these diseases. We evaluate the tools available to analyse and combine different types of molecular data. Finally, we introduce PRECISESADS, a project aimed at reclassifying the systemic autoimmune diseases.

Immunophenotyping Using Dried and Lyophilized Reagents

Antibody reagents that are used for flow cytometry immunophenotyping have traditionally been prepared by combining individual liquid antibody conjugates into mixtures. These cocktails have limited shelf-life, and their preparation is time-consuming and prone to laboratory error. Manufacturers of these reagents, in collaboration with several clinical and research centers, have made advances in constructing dried antibody cocktails which have addressed many of the problems inherent in preparing the liquid cocktails on the lab bench. This chapter discusses methods for the use of dried reagents.

Lymphocytes as Biomarkers of Therapeutic Response in Rheumatic Autoimmune Diseases, Is It a Realistic Goal?

Many therapies are available for patients with rheumatoid arthritis (RA) while biological therapies have limited effects in patients with systemic lupus erythematosus (SLE) and primary Sjögren's syndrome (pSS). In both cases, biomarkers predicting drug response would be very useful to guide clinicians in their choice. We performed a systematic review to evaluate the value of lymphocyte phenotyping as a marker of therapeutic response. Of the 1063 articles retrieved, 39 fulfilled inclusion criteria and were included in the present review (25 for RA, 10 for SLE, and 4 for pSS). Lymphocyte phenotyping was described as a biomarker of therapeutic response in many studies, but most results could not be confirmed by independent teams using multivariate analysis. The most consistent result might be the association between rituximab response and the levels of memory B cells before therapy, although some studies were controversial. Thus, lymphocyte phenotyping cannot yet be proposed as a biomarker of response in rheumatic autoimmune diseases. The lack of reproducibility between studies may be explained by technical issues influencing lymphocyte phenotyping so standardization procedures should be developed for future studies. The patients' characteristics vary between studies, and large population studies, including a wide range of patients' characteristics and biomarkers, are required to provide predictive models for clinical outcomes. The use of new flow cytometry techniques such as single-cell mass cytometry technology might also help finder reliable biomarkers in the future.

Could Lymphocyte Profiling be Useful to Diagnose Systemic Autoimmune Diseases?

Considering the implications of B, T, and natural killer (NK) cells in the pathophysiology of systemic autoimmune diseases, the assessment of their distribution in the blood could be helpful for physicians in the complex process of determining a precise diagnosis. In primary Sjögren's syndrome, transitional and active naive B cells are increased and memory B cells are decreased compared to healthy controls and other systemic diseases. However, their utility to improve the accuracy of classification criteria has not been proven. In early untreated rheumatoid arthritis, proportions of regulatory T cells are constantly reduced, but other patterns are difficult to determine given the heterogeneity of published studies. In systemic lupus erythematosus, the lack of studies using large cohorts of patients and the diversity of the possible pathological mechanisms involved are also important impediments. Nevertheless, transitional B cell and plasma cell proportions are increased in most of the studies, the CD4/CD8 ratio is decreased, and the number of NK cells is reduced. Despite the low number of studies, anomalies of lymphocyte subset distribution was also described in ANCA-associated vasculitis, systemic scleroderma, and myositis. For now, flow cytometric analysis of lymphocyte subsets has focused mainly on specific subpopulations and is more useful for basic and translational research than for diagnostics in clinical practice. However, new modern methods such as mass cytometry and bioinformatics analyses may offer the possibility to simultaneously account for the relative proportions of multiple lymphocyte subsets and define a global profile in homogeneous groups of patients. The years to come will certainly incorporate such global lymphocyte profiling in reclassification of systemic autoimmune diseases.

A standardized flow cytometry procedure for the monitoring of regulatory T cells in clinical trials

BACKGROUND

Quantification of regulatory T cells (Tregs) is crucial in immunomonitoring in clinical trials as this cell population has been shown to be involved in a wide range of diseases, including cancers, autoimmune diseases, infections, and allergies. Human Tregs are defined as CD4⁺ CD25⁺ CD127^low FoxP3⁺ cells, and the standardization of their staining by flow cytometry is a challenge, especially in multicenter clinical trials, notably because of the intracellular location of FoxP3.

METHOD

A flow cytometry staining procedure was settled and standardized to measure human Tregs in peripheral whole blood using precoated dried antibodies in ready-to-use tubes. It was compared with reference methods and implemented and validated to be suitable with different cytometer platforms.

RESULTS

The standardized protocol developed with dried antibodies and reduced volumes of whole blood allows an optimal identification of Tregs. Compared with classical staining procedure, it reduces the number of steps required, in a very fast and simple technique. The accuracy of the method was confirmed by a multicenter comparison with different cytometer brands.

CONCLUSIONS

Our results highlight the reliability of this high-standard protocol that could become a reference method for the monitoring of Tregs in clinical trials. © 2018 International Clinical Cytometry Society.

Heterogeneity of Metazoan Cells and Beyond: To Integrative Analysis of Cellular Populations at Single-Cell Level

In this paper, we review some of the recent advances in cellular heterogeneity and single-cell analysis methods. In modern research of cellular heterogeneity, there are four major approaches: analysis of pooled samples, single-cell analysis, high-throughput single-cell analysis, and lately integrated analysis of cellular population at a single-cell level. Recently developed high-throughput single-cell genetic analysis methods such as RNA-Seq require purification step and destruction of an analyzed cell often are providing a snapshot of the investigated cell without spatiotemporal context. Correlative analysis of multiparameter morphological, functional, and molecular information is important for differentiation of more uniform groups in the spectrum of different cell types. Simplified distributions (histograms and 2D plots) can underrepresent biologically significant subpopulations. Future directions may include the development of nondestructive methods for dissecting molecular events in intact cells, simultaneous correlative cellular analysis of phenotypic and molecular features by hybrid technologies such as imaging flow cytometry, and further progress in supervised and non-supervised statistical analysis algorithms.

The Growing Need for Validated Biomarkers and Endpoints for Dry Eye Clinical Research

Purpose

Biomarkers with minimally invasive and reproducible objective metrics provide the key to future paradigm shifts in understanding of the underlying causes of dry eye disease (DED) and approaches to treatment of DED. We review biomarkers and their validity in providing objective metrics for DED clinical research and patient care.

Methods

The English-language literature in PubMed primarily over the last decade was surveyed for studies related to identification of biomarkers of DED: (1) inflammation, (2) point-of-care, (3) ocular imaging, and (4) genetics. Relevant studies in each group were individually evaluated for (1) methodological and analytical details, (2) data and concordance with other similar studies, and (3) potential to serve as validated biomarkers with objective metrics.

Results

Significant work has been done to identify biomarkers for DED clinical trials and for patient care. Interstudy variation among studies dealing with the same biomarker type was high. This could be attributed to biologic variations and/or differences in processing, and data analysis. Correlation with other signs and symptoms of DED was not always clear or present.

Conclusions

Many of the biomarkers reviewed show the potential to serve as validated and objective metrics for clinical research and patient care in DED. Interstudy variation for a given biomarker emphasizes the need for detailed reporting of study methodology, including information on subject characteristics, quality control, processing, and analysis methods to optimize development of nonsubjective metrics. Biomarker development offers a rich opportunity to significantly move forward clinical research and patient care in DED.

Overview

DED is an unmet medical need - a chronic pain syndrome associated with variable vision that affects quality of life, is common with advancing age, interferes with the comfortable use of contact lenses, and can diminish results of eye surgeries, such as cataract extraction, LASIK, and glaucoma procedures. It is a worldwide medical challenge with a prevalence rate ranging from 8% to 50%. Many clinicians and researchers across the globe are searching for better answers to understand the mechanisms related to the development and chronicity of DED. Though there have been many clinical trials for DED, few new treatments have emerged over the last decade. Biomarkers may provide the needed breakthrough to propel our understanding of DED to the next level and the potential to realize our goal of truly personalized medicine based on scientific evidence. Clinical trials and research on DED have suffered from the lack of validated biomarkers and less than objective and reproducible endpoints. Current work on biomarkers has provided the groundwork to move forward. This review highlights primarily ocular biomarkers that have been investigated for use in DED, discusses the methodologic outcomes in providing objective metrics for clinical research, and suggests recommendations for further work.