Diminished cytokine-induced Jak/STAT signaling is associated with rheumatoid arthritis and disease activity.

Rheumatoid arthritis (RA) is a systemic and incurable autoimmune disease characterized by chronic inflammation in synovial lining of joints. To identify the signaling pathways involved in RA, its disease activity, and treatment response, we adapted a systems immunology approach to simultaneously quantify 42 signaling nodes in 21 immune cell subsets (e.g., IFNα→p-STAT5 in B cells) in peripheral blood mononuclear cells (PBMC) from 194 patients with longstanding RA (including 98 patients before and after treatment), and 41 healthy controls (HC). We found multiple differences between patients with RA compared to HC, predominantly in cytokine-induced Jak/STAT signaling in many immune cell subsets, suggesting pathways that may be associated with susceptibility to RA. We also found that high RA disease activity, compared to low disease activity, was associated with decreased (e.g., IFNα→p-STAT5, IL-10→p-STAT1) or increased (e.g., IL-6→STAT3) response to stimuli in multiple cell subsets. Finally, we compared signaling in patients with established, refractory RA before and six months after initiation of methotrexate (MTX) or TNF inhibitors (TNFi). We noted significant changes from pre-treatment to post-treatment in IFNα→p-STAT5 signaling and IL-10→p-STAT1 signaling in multiple cell subsets; these changes brought the aberrant RA signaling profiles toward those of HC. This large, comprehensive functional signaling pathway study provides novel insights into the pathogenesis of RA and shows the potential of quantification of cytokine-induced signaling as a biomarker of disease activity or treatment response.

A monoclonal antibody to Siglec-8 suppresses non-allergic airway inflammation and inhibits IgE-independent mast cell activation.

In addition to their well characterized role in mediating IgE-dependent allergic diseases, aberrant accumulation and activation of mast cells (MCs) is associated with many non-allergic inflammatory diseases, whereby their activation is likely triggered by non-IgE stimuli (e.g., IL-33). Siglec-8 is an inhibitory receptor expressed on MCs and eosinophils that has been shown to inhibit IgE-mediated MC responses and reduce allergic inflammation upon ligation with a monoclonal antibody (mAb). Herein, we evaluated the effects of an anti-Siglec-8 mAb (anti-S8) in non-allergic disease models of experimental cigarette-smoke-induced chronic obstructive pulmonary disease and bleomycin-induced lung injury in Siglec-8 transgenic mice. Therapeutic treatment with anti-S8 inhibited MC activation and reduced recruitment of immune cells, airway inflammation, and lung fibrosis. Similarly, using a model of MC-dependent, IL-33-induced inflammation, anti-S8 treatment suppressed neutrophil influx, and cytokine production through MC inhibition. Transcriptomic profiling of MCs further demonstrated anti-S8-mediated downregulation of MC signaling pathways induced by IL-33, including TNF signaling via NF-κB. Collectively, these findings demonstrate that ligating Siglec-8 with an antibody reduces non-allergic inflammation and inhibits IgE-independent MC activation, supporting the evaluation of an anti-Siglec-8 mAb as a therapeutic approach in both allergic and non-allergic inflammatory diseases in which MCs play a role.

Baseline T cell dysfunction by single cell network profiling in metastatic breast cancer patients.

BACKGROUND: We previously reported the results of a multicentric prospective randomized trial of chemo-refractory metastatic breast cancer patients testing the efficacy of two doses of TGFß blockade during radiotherapy. Despite a lack of objective responses to the combination, patients who received a higher dose of TGFß blocking antibody fresolimumab had a better overall survival when compared to those assigned to lower dose (hazard ratio of 2.73, p = 0.039). They also demonstrated an improved peripheral blood mononuclear cell (PBMC) counts and increase in the CD8 central memory pool. We performed additional analysis on residual PBMC using single cell network profiling (SCNP). METHODS: The original trial randomized metastatic breast cancer patients to either 1 or 10 mg/kg of fresolimumab, every 3 weeks for 5 cycles, combined with radiotherapy to a metastatic site at week 1 and 7 (22.5 Gy given in 3 doses of 7.5 Gy). Trial immune monitoring results were previously reported. In 15 patients with available residual blood samples, additional functional studies were performed, and compared with data obtained in parallel from seven healthy female donors (HD): SCNP was applied to analyze T cell receptor (TCR) modulated signaling via CD3 and CD28 crosslinking and measurement of evoked phosphorylation of AKT and ERK in CD4 and CD8 T cell subsets defined by PD-1 expression. RESULTS: At baseline, a significantly higher level of expression (p < 0.05) of PD-L1 was identified in patient monocytes compared to HD. TCR modulation revealed dysfunction of circulating T-cells in patient baseline samples as compared to HD, and this was more pronounced in PD-1+ cells. Treatment with radiotherapy and fresolimumab did not resolve this dyfunctional signaling. However, in vitro PD-1 blockade enhanced TCR signaling in patient PD-1+ T cells and not in PD-1- T cells or in PD-1+ T cells from HD. CONCLUSIONS: Functional T cell analysis suggests that baseline T cell functionality is hampered in metastatic breast cancer patients, at least in part mediated by the PD-1 signaling pathway. These preliminary data support the rationale for investigating the possible beneficial effects of adding PD-1 blockade to improve responses to TGFß blockade and radiotherapy. TRIAL REGISTRATION: NCT01401062 .

High-dimensional analysis of the aging immune system: verification of age-associated differences in immune signaling responses in healthy donors.

BACKGROUND: Single-cell network profiling (SCNP) is a multiparametric flow cytometry-based approach that simultaneously measures evoked signaling in multiple cell subsets. Previously, using the SCNP approach, age-associated immune signaling responses were identified in a cohort of 60 healthy donors. METHODS: In the current study, a high-dimensional analysis of intracellular signaling was performed by measuring 24 signaling nodes in 7 distinct immune cell subsets within PBMCs in an independent cohort of 174 healthy donors [144 elderly (>65 yrs); 30 young (25-40 yrs)]. RESULTS: Associations between age and 9 immune signaling responses identified in the previously published 60 donor cohort were confirmed in the current study. Furthermore, within the current study cohort, 48 additional immune signaling responses differed significantly between young and elderly donors. These associations spanned all profiled modulators and immune cell subsets. CONCLUSIONS: These results demonstrate that SCNP, a systems-based approach, can capture the complexity of the cellular mechanisms underlying immunological aging. Further, the confirmation of age associations in an independent donor cohort supports the use of SCNP as a tool for identifying reproducible predictive biomarkers in areas such as vaccine response and response to cancer immunotherapies.

Association between B-cell receptor responsiveness and disease progression in B-cell chronic lymphocytic leukemia: results from single cell network profiling studies.

While many prognostic markers in B-cell chronic lymphocytic leukemia provide insight into the biology of the disease, few have been demonstrated to be useful in the daily management of patients. B-cell receptor signaling is a driving event in the progression of B-cell chronic lymphocytic leukemia and markers of B-cell receptor responsiveness have been shown to be of prognostic value. Single cell network profiling, a multiparametric flow cytometry-based assay, allows functional signaling analysis at the level of the single cell. B-cell receptor signaling proteins (i.e. p-SYK, p-NF-κB p65, p-ERK, p-p38, p-JNK) were functionally characterized by single cell network profiling in samples from patients with B-cell chronic lymphocytic leukemia in an exploratory study (n=27) after stimulation with anti-IgM. Significant associations of single cell network profiling data with clinical outcome (i.e. time to first treatment), as assessed by Cox regression models, were then confirmed in patients' samples in two other sequential independent studies, i.e. test study 1 (n=30), and test study 2 (n=37). In the exploratory study, higher responsiveness of the B-cell receptor signaling proteins to anti-IgM was associated with poor clinical outcomes. Patients' clustering based on signaling response was at least as powerful in discriminating different disease courses as traditional prognostic markers. In an unselected subgroup of patients with Binet stage A disease (n=21), increased anti-IgM-modulated p-ERK signaling was shown to be a significant, independent predictor of shorter time to first treatment. This result was independently confirmed in two test cohorts from distinct populations of patients. In conclusion, these findings support the utility of the single cell network profiling assay in elucidating signaling perturbations with the potential for the development of a clinically useful prognostic test in patients with early stage B-cell chronic lymphocytic leukemia. These data support the clinical relevance of B-cell receptor signaling in B-cell chronic lymphocytic leukemia, and suggest a key role of ERK activation in the physiopathology of this leukemia.

Single-cell network profiling of peripheral blood mononuclear cells from healthy donors reveals age- and race-associated differences in immune signaling pathway activation.

A greater understanding of the function of the human immune system at the single-cell level in healthy individuals is critical for discerning aberrant cellular behavior that occurs in settings such as autoimmunity, immunosenescence, and cancer. To achieve this goal, a systems-level approach capable of capturing the response of the interdependent immune cell types to external stimuli is required. In this study, an extensive characterization of signaling responses in multiple immune cell subpopulations within PBMCs from a cohort of 60 healthy donors was performed using single-cell network profiling (SCNP). SCNP is a multiparametric flow cytometry-based approach that enables the simultaneous measurement of basal and evoked signaling in multiple cell subsets within heterogeneous populations. In addition to establishing the interindividual degree of variation within a broad panel of immune signaling responses, the possible association of any observed variation with demographic variables including age and race was investigated. Using half of the donors as a training set, multiple age- and race-associated variations in signaling responses in discrete cell subsets were identified, and several were subsequently confirmed in the remaining samples (test set). Such associations may provide insight into age-related immune alterations associated with high infection rates and diminished protection following vaccination and into the basis for ethnic differences in autoimmune disease incidence and treatment response. SCNP allowed for the generation of a functional map of healthy immune cell signaling responses that can provide clinically relevant information regarding both the mechanisms underlying immune pathological conditions and the selection and effect of therapeutics.

Association of reactive oxygen species-mediated signal transduction with in vitro apoptosis sensitivity in chronic lymphocytic leukemia B cells.

BACKGROUND: Chronic lymphocytic leukemia (CLL) is a B cell malignancy with a variable clinical course and unpredictable response to therapeutic agents. Single cell network profiling (SCNP) utilizing flow cytometry measures alterations in signaling biology in the context of molecular changes occurring in malignancies. In this study SCNP was used to identify proteomic profiles associated with in vitro apoptotic responsiveness of CLL B cells to fludarabine, as a basis for ultimately linking these with clinical outcome. METHODOLOGY/PRINCIPAL FINDING: SCNP was used to quantify modulated-signaling of B cell receptor (BCR) network proteins and in vitro F-ara-A mediated apoptosis in 23 CLL samples. Of the modulators studied the reactive oxygen species, hydrogen peroxide (H2O2), a known intracellular second messenger and a general tyrosine phosphatase inhibitor stratified CLL samples into two sub-groups based on the percentage of B cells in a CLL sample with increased phosphorylation of BCR network proteins. Separately, in the same patient samples, in vitro exposure to F-ara-A also identified two sub-groups with B cells showing competence or refractoriness to apoptotic induction. Statistical analysis showed that in vitro F-ara-A apoptotic proficiency was highly associated with the proficiency of CLL B cells to undergo H2O2-augmented signaling. CONCLUSIONS/SIGNIFICANCE: This linkage in CLL B cells among the mechanisms governing chemotherapy-induced apoptosis increased signaling of BCR network proteins and a likely role of phosphatase activity suggests a means of stratifying patients for their response to F-ara-A based regimens. Future studies will examine the clinical applicability of these findings and also the utility of this approach in relating mechanism to function of therapeutic agents.

Functional characterization of FLT3 receptor signaling deregulation in acute myeloid leukemia by single cell network profiling (SCNP).

BACKGROUND: Molecular characterization of the FMS-like tyrosine kinase 3 receptor (FLT3) in cytogenetically normal acute myeloid leukemia (AML) has recently been incorporated into clinical guidelines based on correlations between FLT3 internal tandem duplications (FLT3-ITD) and decreased disease-free and overall survival. These mutations result in constitutive activation of FLT3, and FLT3 inhibitors are currently undergoing trials in AML patients selected on FLT3 molecular status. However, the transient and partial responses observed suggest that FLT3 mutational status alone does not provide complete information on FLT3 biological activity at the individual patient level. Examination of variation in cellular responsiveness to signaling modulation may be more informative. METHODOLOGY/PRINCIPAL FINDINGS: Using single cell network profiling (SCNP), cells were treated with extracellular modulators and their functional responses were quantified by multiparametric flow cytometry. Intracellular signaling responses were compared between healthy bone marrow myeloblasts (BMMb) and AML leukemic blasts characterized as FLT3 wild type (FLT3-WT) or FLT3-ITD. Compared to healthy BMMb, FLT3-WT leukemic blasts demonstrated a wide range of signaling responses to FLT3 ligand (FLT3L), including elevated and sustained PI3K and Ras/Raf/Erk signaling. Distinct signaling and apoptosis profiles were observed in FLT3-WT and FLT3-ITD AML samples, with more uniform signaling observed in FLT3-ITD AML samples. Specifically, increased basal p-Stat5 levels, decreased FLT3L induced activation of the PI3K and Ras/Raf/Erk pathways, decreased IL-27 induced activation of the Jak/Stat pathway, and heightened apoptotic responses to agents inducing DNA damage were observed in FLT3-ITD AML samples. Preliminary analysis correlating these findings with clinical outcomes suggests that classification of patient samples based on signaling profiles may more accurately reflect FLT3 signaling deregulation and provide additional information for disease characterization and management. CONCLUSIONS/SIGNIFICANCE: These studies show the feasibility of SCNP to assess modulated intracellular signaling pathways and characterize the biology of individual AML samples in the context of genetic alterations.

Ligand design by a combinatorial approach based on modeling and experiment: application to HLA-DR4.

Combinatorial synthesis and large scale screening methods are being used increasingly in drug discovery, particularly for finding novel lead compounds. Although these "random" methods sample larger areas of chemical space than traditional synthetic approaches, only a relatively small percentage of all possible compounds are practically accessible. It is therefore helpful to select regions of chemical space that have greater likelihood of yielding useful leads. When three-dimensional structural data are available for the target molecule this can be achieved by applying structure-based computational design methods to focus the combinatorial library. This is advantageous over the standard usage of computational methods to design a small number of specific novel ligands, because here computation is employed as part of the combinatorial design process and so is required only to determine a propensity for binding of certain chemical moieties in regions of the target molecule. This paper describes the application of the Multiple Copy Simultaneous Search (MCSS) method, an active site mapping and de novo structure-based design tool, to design a focused combinatorial library for the class II MHC protein HLA-DR4. Methods for the synthesizing and screening the computationally designed library are presented; evidence is provided to show that binding was achieved. Although the structure of the protein-ligand complex could not be determined, experimental results including cross-exclusion of a known HLA-DR4 peptide ligand (HA) by a compound from the library. Computational model building suggest that at least one of the ligands designed and identified by the methods described binds in a mode similar to that of native peptides.

Performance of 3D-database molecular docking studies into homology models.

The performance of docking studies into protein active sites constructed by homology model building was investigated using CDK2 and factor VIIa screening data sets. When the sequence identity between model and template near the binding site area is greater than approximately 50%, roughly 5 times more active compounds are identified than would be found randomly. This performance is comparable to docking to crystal structures.

Comparing performance of computational tools for combinatorial library design.

In using computational tools for library design it is necessary to understand the performance and limitations of available methods. This letter reports systematic comparisons of applying ligand-based and structure-based tools across therapeutic project-derived data sets. Included are assessments of performance in real-world iterative design applications and the utility of target structural information. The results suggest that combining screening and target structure information is robust; further, a well-designed screening library can compensate for lacking structural information.

Coupling structure-based design with combinatorial chemistry: application of active site derived pharmacophores with informative library design.

Protein structural information is combined with combinatorial library design in the following protocol. Active site maps are generated from protein structures. All possible 2-, 3- and 4-point pharmacophores are enumerated from the active site map and encoded as bit strings. The pharmacophores define a design space that can be used to select compounds using an informative library design tool. The method was evaluated against a collection of compounds assayed previously against a cyclin-dependent kinase target, CDK-2, starting with 23 X-ray co-crystal structures. Performance was assessed based on the number of active scaffolds selected after four rounds of iterative informative library design. The method selects compounds from 12 out of the 15 active scaffolds from the CDK-2 library and outperforms a two-dimensional similarity search and docking calculations.

A computational ensemble pharmacophore model for identifying substrates of P-glycoprotein.

P-glycoprotein (P-gp) functions as a drug efflux pump, mediating multidrug resistance and limiting the efficacy of many drugs. Clearly, identification of potential P-gp substrate liability early in the drug discovery process would be advantageous. We describe a multiple-pharmacophore model that can discriminate between substrates and nonsubstrates of P-gp with an accuracy of 63%. The application of this filter allows large virtual libraries to be screened efficiently for compounds less likely to be transported by P-gp.