Single-cell analysis by mass cytometry reveals metabolic states of early-activated CD8+ T cells during the primary immune response.

Memory T cells are thought to rely on oxidative phosphorylation and short-lived effector T cells on glycolysis. Here, we investigated how T cells arrive at these states during an immune response. To understand the metabolic state of rare, early-activated T cells, we adapted mass cytometry to quantify metabolic regulators at single-cell resolution in parallel with cell signaling, proliferation, and effector function. We interrogated CD8+ T cell activation in vitro and in response to Listeria monocytogenes infection in vivo. This approach revealed a distinct metabolic state in early-activated T cells characterized by maximal expression of glycolytic and oxidative metabolic proteins. Cells in this transient state were most abundant 5 days post-infection before rapidly decreasing metabolic protein expression. Analogous findings were observed in chimeric antigen receptor (CAR) T cells interrogated longitudinally in advanced lymphoma patients. Our study demonstrates the utility of single-cell metabolic analysis by mass cytometry to identify metabolic adaptations of immune cell populations in vivo and provides a resource for investigations of metabolic regulation of immune responses across a variety of applications.

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

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

Mechanism of CD79A and CD79B Support for IgM+ B Cell Fitness through B Cell Receptor Surface Expression.

The BCR consists of surface-bound Ig and a heterodimeric signaling unit comprised of CD79A and CD79B. Upon cognate Ag recognition, the receptor initiates important signals for B cell development and function. The receptor also conveys Ag-independent survival signals termed tonic signaling. Although the requirement of a CD79A/CD79B heterodimer for BCR complex assembly and surface expression is well established based on mice models, few studies have investigated this in human mature B cells. In this study, we found that human tonsillar B cells with high surface expression of IgM or IgG had potentiated BCR signaling compared with BCRlow cells, and high IgM expression in germinal center B cells was associated with reduced apoptosis. We explored the mechanism for IgM surface expression by CRISPR/Cas9-induced deletion of CD79A or CD79B in four B lymphoma cell lines. Deletion of either CD79 protein caused loss of surface IgM in all cell lines and reduced fitness in three. From two cell lines, we generated stable CD79A or CD79B knockout clones and demonstrated that loss of CD79A or CD79B caused a block in N-glycan maturation and accumulation of immature proteins, compatible with retention of BCR components in the endoplasmic reticulum. Rescue experiments with CD79B wild-type restored surface expression of CD79A and IgM with mature glycosylation, whereas a naturally occurring CD79B G137S mutant disrupting CD79A/CD79B heterodimerization did not. Our study highlights that CD79A and CD79B are required for surface IgM expression in human B cells and illuminates the importance of the IgM expression level for signaling and fitness.

An immunogenic cell injury module for the single-cell multiplexed activity metabolomics platform to identify promising anti-cancer natural products.

Natural products constitute and significantly impact many current anti-cancer medical interventions. A subset of natural products induces injury processes in malignant cells that recruit and activate host immune cells to produce an adaptive anti-cancer immune response, a process known as immunogenic cell death. However, a challenge in the field is to delineate forms of cell death and injury that best promote durable antitumor immunity. Addressing this with a single-cell chemical biology natural product discovery platform, like multiplex activity metabolomics, would be especially valuable in human leukemia, where cancer cells are heterogeneous and may react differently to the same compounds. Herein, a new ten-color, fluorescent cell barcoding-compatible module measuring six immunogenic cell injury signaling readouts are as follows: DNA damage response (γH2AX), apoptosis (cCAS3), necroptosis (p-MLKL), mitosis (p-Histone H3), autophagy (LC3), and the unfolded protein response (p-EIF2α). A proof-of-concept screen was performed to validate functional changes in single cells induced by secondary metabolites with known mechanisms within bacterial extracts. This assay was then applied in multiplexed activity metabolomics to reveal an unexpected mammalian cell injury profile induced by the natural product narbomycin. Finally, the functional consequences of injury pathways on immunogenicity were compared with three canonical assays for immunogenic hallmarks, ATP, HMGB1, and calreticulin, to correlate secondary metabolite-induced cell injury profiles with canonical markers of immunogenic cell death. In total, this work demonstrated a new phenotypic screen for discovery of natural products that modulate injury response pathways that can contribute to cancer immunogenicity.

CMV exposure drives long-term CD57+ CD4 memory T-cell inflation following allogeneic stem cell transplant.

Donor and recipient cytomegalovirus (CMV) serostatus correlate with transplant-related mortality that is associated with reduced survival following allogeneic stem cell transplant (SCT). Prior epidemiologic studies have suggested that CMV seronegative recipients (R-) receiving a CMV-seropositive graft (D+) experience inferior outcomes compared with other serostatus combinations, an observation that appears independent of viral reactivation. We therefore investigated the hypothesis that prior donor CMV exposure irreversibly modifies immunologic function after SCT. We identified a CD4+/CD57+/CD27- T-cell subset that was differentially expressed between D+ and D- transplants and validated results with 120 patient samples. This T-cell subset represents an average of 2.9% (D-/R-), 18% (D-/R+), 12% (D+/R-), and 19.6% (D+/R+) (P < .0001) of the total CD4+ T-cell compartment and stably persists for at least several years post-SCT. Even in the absence of CMV reactivation post-SCT, D+/R- transplants displayed a significant enrichment of these cells compared with D-/R- transplants (P = .0078). These are effector memory cells (CCR7-/CD45RA+/-) that express T-bet, Eomesodermin, granzyme B, secrete Th1 cytokines, and are enriched in CMV-specific T cells. These cells are associated with decreased T-cell receptor diversity (P < .0001) and reduced proportions of major histocompatibility class (MHC) II expressing classical monocytes (P < .0001), myeloid (P = .024), and plasmacytoid dendritic cells (P = .0014). These data describe a highly expanded CD4+ T-cell population and putative mechanisms by which prior donor or recipient CMV exposure may create a lasting immunologic imprint following SCT, providing a rationale for using D- grafts for R- transplant recipients.

Targeting In Vivo Metabolic Vulnerabilities of Th2 and Th17 Cells Reduces Airway Inflammation.

T effector cells promote inflammation in asthmatic patients, and both Th2 and Th17 CD4 T cells have been implicated in severe forms of the disease. The metabolic phenotypes and dependencies of these cells, however, remain poorly understood in the regulation of airway inflammation. In this study, we show the bronchoalveolar lavage fluid of asthmatic patients had markers of elevated glucose and glutamine metabolism. Further, peripheral blood T cells of asthmatics had broadly elevated expression of metabolic proteins when analyzed by mass cytometry compared with healthy controls. Therefore, we hypothesized that glucose and glutamine metabolism promote allergic airway inflammation. We tested this hypothesis in two murine models of airway inflammation. T cells from lungs of mice sensitized with Alternaria alternata extract displayed genetic signatures for elevated oxidative and glucose metabolism by single-cell RNA sequencing. This result was most pronounced when protein levels were measured in IL-17-producing cells and was recapitulated when airway inflammation was induced with house dust mite plus LPS, a model that led to abundant IL-4- and IL-17-producing T cells. Importantly, inhibitors of the glucose transporter 1 or glutaminase in vivo attenuated house dust mite + LPS eosinophilia, T cell cytokine production, and airway hyperresponsiveness as well as augmented the immunosuppressive properties of dexamethasone. These data show that T cells induce markers to support metabolism in vivo in airway inflammation and that this correlates with inflammatory cytokine production. Targeting metabolic pathways may provide a new direction to protect from disease and enhance the effectiveness of steroid therapy.

Two New Neutrophil Subsets Define a Discriminating Sepsis Signature.

Rationale: Sepsis is the leading cause of death in adult ICUs. At present, sepsis diagnosis relies on nonspecific clinical features. It could transform clinical care to have immune-cell biomarkers that could predict sepsis diagnosis and guide treatment. For decades, neutrophil phenotypes have been studied in sepsis, but a diagnostic cell subset has yet to be identified. Objectives: To identify an early, specific immune signature of sepsis severity that does not overlap with other inflammatory biomarkers and that distinguishes patients with sepsis from those with noninfectious inflammatory syndrome. Methods: Mass cytometry combined with computational high-dimensional data analysis was used to measure 42 markers on whole-blood immune cells from patients with sepsis and control subjects and to automatically and comprehensively characterize circulating immune cells, which enables identification of novel, disease-specific cellular signatures. Measurements and Main Results: Unsupervised analysis of high-dimensional mass cytometry data characterized previously unappreciated heterogeneity within the CD64+ immature neutrophils and revealed two new subsets distinguished by CD123 and PD-L1 (programmed death ligand 1) expression. These immature neutrophils exhibited diminished activation and phagocytosis functions. The proportion of CD123-expressing neutrophils correlated with clinical severity. Conclusions: This study showed that these two new neutrophil subsets were specific to sepsis and detectable through routine flow cytometry by using seven markers. The demonstration here that a simple blood test distinguishes sepsis from other inflammatory conditions represents a key biological milestone that can be immediately translated into improvements in patient care.

Treg sensitivity to FasL and relative IL-2 deprivation drive idiopathic aplastic anemia immune dysfunction.

Idiopathic aplastic anemia (AA) has 2 key characteristics: an autoimmune response against hematopoietic stem/progenitor cells and regulatory T-cells (Tregs) deficiency. We have previously demonstrated reduction in a specific subpopulation of Treg in AA, which predicts response to immunosuppression. The aims of the present study were to define mechanisms of Treg subpopulation imbalance and identify potential for therapeutic intervention. We have identified 2 mechanisms that lead to skewed Treg composition in AA: first, FasL-mediated apoptosis on ligand interaction; and, second, relative interleukin-2 (IL-2) deprivation. We have shown that IL-2 augmentation can overcome these mechanisms. Interestingly, when high concentrations of IL-2 were used for in vitro Treg expansion cultures, AA Tregs were able to expand. The expanded populations expressed a high level of p-BCL-2, which makes them resistant to apoptosis. Using a xenograft mouse model, the function and stability of expanded AA Tregs were tested. We have shown that these Tregs were able to suppress the macroscopic clinical features and tissue manifestations of T-cell-mediated graft-versus-host disease. These Tregs maintained their suppressive properties as well as their phenotype in a highly inflammatory environment. Our findings provide an insight into the mechanisms of Treg reduction in AA. We have identified novel targets with potential for therapeutic interventions. Supplementation of ex vivo expansion cultures of Tregs with high concentrations of IL-2 or delivery of IL-2 directly to patients could improve clinical outcomes in addition to standard immunosuppressive therapy.

DebarcodeR increases fluorescent cell barcoding capacity and accuracy.

Fluorescent cell barcoding (FCB) enables efficient collection of tens to hundreds of flow cytometry samples by covalently marking cells with varying concentration of spectrally distinct dyes. A key consideration in FCB is to balance the density of dye barcodes, the complexity of cells in the sample, and the desired accuracy of the debarcoding. Unfortunately, barcoding bench and computational methods have not benefited from the high dimensional revolution in cytometry due to a lack of automated computational tools that effectively balance these common cytometry needs. DebarcodeR addresses these unmet needs by providing a framework for computational debarcoding augmented by improvements to experimental methods. Adaptive regression modeling accounted for differential dye uptake between different cell types and Gaussian mixture modeling provided a robust method to probabilistically assign cells to samples. Assignment tolerance parameters are available to allow users to balance high cell recovery with accurate assignments. Improvements to experimental methods include: (1) inclusion of an "external standard" control where a pool of all cells was stained a single level of each barcoding dyes and (2) an "internal standard" where each cell is stained with a single level of a separate dye. DebarcodeR significantly improved speed, accuracy, and reproducibility of FCB while avoiding selective loss of unusual cell subsets when debarcoding microtiter plates of cell lines and heterogenous mixtures of primary cells. DebarcodeR is available on Github as an R package that works with flowCore and Cytoverse packages at github.com/cytolab/DebarcodeR.

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

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

Characterizing cell subsets using marker enrichment modeling.

Learning cell identity from high-content single-cell data presently relies on human experts. We present marker enrichment modeling (MEM), an algorithm that objectively describes cells by quantifying contextual feature enrichment and reporting a human- and machine-readable text label. MEM outperforms traditional metrics in describing immune and cancer cell subsets from fluorescence and mass cytometry. MEM provides a quantitative language to communicate characteristics of new and established cytotypes observed in complex tissues.

Human Germinal Center B Cells Differ from Naïve and Memory B Cells in CD40 Expression and CD40L-Induced Signaling Response.

CD40 expression is required for germinal center (GC) formation and function, but the kinetics and magnitude of signaling following CD40 engagement remain poorly characterized in human B cells undergoing GC reactions. Here, differences in CD40 expression and signaling responses were compared across differentiation stages of mature human tonsillar B cells. A combination of mass cytometry and phospho-specific flow cytometry was used to quantify protein expression and CD40L-induced signaling in primary human naïve, GC, and memory B cells. Protein expression signatures of cell subsets were quantified using viSNE and Marker Enrichment Modeling (MEM). This approach revealed enriched expression of CD40 protein in GC B cells, compared to naïve and memory B cells. Despite this, GC B cells responded to CD40L engagement with lower phosphorylation of NFκB p65 during the first 30 min following CD40L activation. Before CD40L stimulation, GC B cells expressed higher levels of suppressor protein IκBα than naïve and memory B cells. Following CD40 activation, IκBα was rapidly degraded and reached equivalently low levels in naïve, GC, and memory B cells at 30 min following CD40L. Quantifying CD40 signaling responses as a function of bound ligand revealed a correlation between bound CD40L and degree of induced NFκB p65 phosphorylation, whereas comparable IκBα degradation occurred at all measured levels of CD40L binding. These results characterize cell-intrinsic signaling differences that exist in mature human B cells undergoing GC reactions. © 2019 International Society for Advancement of Cytometry.

Distinct patterns of B-cell receptor signaling in non-Hodgkin lymphomas identified by single-cell profiling.

Kinases downstream of B-cell antigen receptor (BCR) represent attractive targets for therapy in non-Hodgkin lymphoma (NHL). As clinical responses vary, improved knowledge regarding activation and regulation of BCR signaling in individual patients is needed. Here, using phosphospecific flow cytometry to obtain malignant B-cell signaling profiles from 95 patients representing 4 types of NHL revealed a striking contrast between chronic lymphocytic leukemia (CLL) and mantle cell lymphoma (MCL) tumors. Lymphoma cells from diffuse large B-cell lymphoma patients had high basal phosphorylation levels of most measured signaling nodes, whereas follicular lymphoma cells represented the opposite pattern with no or very low basal levels. MCL showed large interpatient variability in basal levels, and elevated levels for the phosphorylated forms of AKT, extracellular signal-regulated kinase, p38, STAT1, and STAT5 were associated with poor outcome. CLL tumors had elevated basal levels for the phosphorylated forms of BCR-signaling nodes (Src family tyrosine kinase, spleen tyrosine kinase [SYK], phospholipase Cγ), but had low α-BCR-induced signaling. This contrasted MCL tumors, where α-BCR-induced signaling was variable, but significantly potentiated as compared with the other types. Overexpression of CD79B, combined with a gating strategy whereby signaling output was directly quantified per cell as a function of CD79B levels, confirmed a direct relationship between surface CD79B, immunoglobulin M (IgM), and IgM-induced signaling levels. Furthermore, α-BCR-induced signaling strength was variable across patient samples and correlated with BCR subunit CD79B expression, but was inversely correlated with susceptibility to Bruton tyrosine kinase (BTK) and SYK inhibitors in MCL. These individual differences in BCR levels and signaling might relate to differences in therapy responses to BCR-pathway inhibitors.

Machine learning reveals chronic graft-versus-host disease phenotypes and stratifies survival after stem cell transplant for hematologic malignancies.

The application of machine learning in medicine has been productive in multiple fields, but has not previously been applied to analyze the complexity of organ involvement by chronic graft-versus-host disease. Chronic graft-versus-host disease is classified by an overall composite score as mild, moderate or severe, which may overlook clinically relevant patterns in organ involvement. Here we applied a novel computational approach to chronic graft-versus-host disease with the goal of identifying phenotypic groups based on the subcomponents of the National Institutes of Health Consensus Criteria. Computational analysis revealed seven distinct groups of patients with contrasting clinical risks. The high-risk group had an inferior overall survival compared to the low-risk group (hazard ratio 2.24; 95% confidence interval: 1.36-3.68), an effect that was independent of graft-versus-host disease severity as measured by the National Institutes of Health criteria. To test clinical applicability, knowledge was translated into a simplified clinical prognostic decision tree. Groups identified by the decision tree also stratified outcomes and closely matched those from the original analysis. Patients in the high- and intermediate-risk decision-tree groups had significantly shorter overall survival than those in the low-risk group (hazard ratio 2.79; 95% confidence interval: 1.58-4.91 and hazard ratio 1.78; 95% confidence interval: 1.06-3.01, respectively). Machine learning and other computational analyses may better reveal biomarkers and stratify risk than the current approach based on cumulative severity. This approach could now be explored in other disease models with complex clinical phenotypes. External validation must be completed prior to clinical application. Ultimately, this approach has the potential to reveal distinct pathophysiological mechanisms that may underlie clusters. Clinicaltrials.gov identifier: NCT00637689.

Deep phenotyping of Tregs identifies an immune signature for idiopathic aplastic anemia and predicts response to treatment.

Idiopathic aplastic anemia (AA) is an immune-mediated and serious form of bone marrow failure. Akin to other autoimmune diseases, we have previously shown that in AA regulatory T cells (Tregs) are reduced in number and function. The aim of this study was to further characterize Treg subpopulations in AA and investigate the potential correlation between specific Treg subsets and response to immunosuppressive therapy (IST) as well as their in vitro expandability for potential clinical use. Using mass cytometry and an unbiased multidimensional analytical approach, we identified 2 specific human Treg subpopulations (Treg A and Treg B) with distinct phenotypes, gene expression, expandability, and function. Treg B predominates in IST responder patients, has a memory/activated phenotype (with higher expression of CD95, CCR4, and CD45RO within FOXP3(hi), CD127(lo) Tregs), expresses the interleukin-2 (IL-2)/STAT5 pathway and cell-cycle commitment genes. Furthermore, in vitro-expanded Tregs become functional and take on the characteristics of Treg B. Collectively, this study identifies human Treg subpopulations that can be used as predictive biomarkers for response to IST in AA and potentially other autoimmune diseases. We also show that Tregs from AA patients are IL-2-sensitive and expandable in vitro, suggesting novel therapeutic approaches such as low-dose IL-2 therapy and/or expanded autologous Tregs and meriting further exploration.

Regulatory myeloid cells: an underexplored continent in B-cell lymphomas.

In lymphomas arising from the germinal center, prognostic factors are linked to the myeloid compartment. In particular, high circulating monocyte or myeloid-derived suppressor cell counts are associated with poor prognosis for patients with high-grade B-cell lymphomas. Macrophages with an M2 phenotype are enriched within lymphoma tumors. However, the M1/M2 nomenclature is now deprecated and the clinical impact of this phenotype remains controversial. Across cancer types, myeloid cells are primarily thought to function as immune suppressors during tumor initiation and maintenance, but the biological mechanisms behind the myeloid signatures are still poorly understood in germinal center B-cell lymphomas. Herein, we describe the role and clinical relevance of myeloid cells in B-cell lymphoma and propose innovative approaches to decipher this complex cellular compartment. Indeed, characterization of this heterogeneous cell ecosystem has been largely accomplished with "low-resolution" approaches like morphological evaluation and immunohistochemistry, where cells are characterized using a few proteins and qualitative metrics. High-resolution, quantitative approaches, such as mass cytometry, are valuable to better understand myeloid cell diversity, functions, and to identify potential targets for novel therapies.

Cutting Edge: Redox Signaling Hypersensitivity Distinguishes Human Germinal Center B Cells.

Differences in the quality of BCR signaling control key steps of B cell maturation and differentiation. Endogenously produced H2O2 is thought to fine tune the level of BCR signaling by reversibly inhibiting phosphatases. However, relatively little is known about how B cells at different stages sense and respond to such redox cues. In this study, we used phospho-specific flow cytometry and high-dimensional mass cytometry (CyTOF) to compare BCR signaling responses in mature human tonsillar B cells undergoing germinal center (GC) reactions. GC B cells, in contrast to mature naive B cells, memory B cells, and plasmablasts, were hypersensitive to a range of H2O2 concentrations and responded by phosphorylating SYK and other membrane-proximal BCR effectors in the absence of BCR engagement. These findings reveal that stage-specific redox responses distinguish human GC B cells.

Multiparameter analysis of stimulated human peripheral blood mononuclear cells: A comparison of mass and fluorescence cytometry.

Mass and fluorescence cytometry are quantitative single cell flow cytometry approaches that are powerful tools for characterizing diverse tissues and cellular systems. Here mass cytometry was directly compared with fluorescence cytometry by studying phenotypes of healthy human peripheral blood mononuclear cells (PBMC) in the context of superantigen stimulation. One mass cytometry panel and five fluorescence cytometry panels were used to measure 20 well-established lymphocyte markers of memory and activation. Comparable frequencies of both common and rare cell subpopulations were observed with fluorescence and mass cytometry using biaxial gating. The unsupervised high-dimensional analysis tool viSNE was then used to analyze data sets generated from both mass and fluorescence cytometry. viSNE analysis effectively characterized PBMC using eight features per cell and identified similar frequencies of activated CD4+ T cells with both technologies. These results suggest combinations of unsupervised analysis programs and extended multiparameter cytometry will be indispensable tools for detecting perturbations in protein expression in both health and disease.