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

Integration of B-cell receptor-induced ERK1/2 phosphorylation and mutations of SF3B1 gene refines prognosis in treatment-na\uefve chronic lymphocytic leukemia

ADP-ribosyl Cyclase 1; Disease Progression; Humans; Immunoglobulin Heavy Chains; Immunoglobulin Variable[no abstract available

Distinct Patterns of DNA Damage Response and Apoptosis Correlate with Jak/Stat and PI3Kinase Response Profiles in Human Acute Myelogenous Leukemia

BACKGROUND:Single cell network profiling (SCNP) utilizing flow cytometry measures alterations in intracellular signaling responses. Here SCNP was used to characterize Acute Myeloid Leukemia (AML) disease subtypes based on survival, DNA damage response and apoptosis pathways. METHODOLOGY AND PRINCIPAL FINDINGS:Thirty four diagnostic non-M3 AML samples from patients with known clinical outcome were treated with a panel of myeloid growth factors and cytokines, as well as with apoptosis-inducing agents. Analysis of induced Jak/Stat and PI3K pathway responses in blasts from individual patient samples identified subgroups with distinct signaling profiles that were not seen in the absence of a modulator. In vitro exposure of patient samples to etoposide, a DNA damaging agent, revealed three distinct "DNA damage response (DDR)/apoptosis" profiles: 1) AML blasts with a defective DDR and failure to undergo apoptosis; 2) AML blasts with proficient DDR and failure to undergo apoptosis; 3) AML blasts with proficiency in both DDR and apoptosis pathways. Notably, AML samples from clinical responders fell within the "DDR/apoptosis" proficient profile and, as well, had low PI3K and Jak/Stat signaling responses. In contrast, samples from clinical non responders had variable signaling profiles often with in vitro apoptotic failure and elevated PI3K pathway activity. Individual patient samples often harbored multiple, distinct, leukemia-associated cell populations identifiable by their surface marker expression, functional performance of signaling pathway in the face of cytokine or growth factor stimulation, as well as their response to apoptosis-inducing agents. CONCLUSIONS AND SIGNIFICANCE:Characterizing and tracking changes in intracellular pathway profiles in cell subpopulations both at baseline and under therapeutic pressure will likely have important clinical applications, potentially informing the selection of beneficial targeted agents, used either alone or in combination with chemotherapy

Functional Characterization of FLT3 Receptor Signaling Deregulation in Acute Myeloid Leukemia by Single Cell Network Profiling (SCNP)

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.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.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

Feature-map vectors: a new class of informative descriptors for computational drug discovery.

In order to develop robust machine-learning or statistical models for predicting biological activity, descriptors that capture the essence of the protein-ligand interaction are required. In the absence of structural information from X-ray or NMR experiments, deriving informative descriptors can be difficult. We have developed feature-map vectors (FMVs), a new class of descriptors based on chemical features, to address this challenge. FMVs, which are derived from the conformational models of a few actives, are low dimensional, problem specific, and highly interpretable. By using shape-based alignments and scoring with chemical features, FMVs can combine information about a molecule's shape and the pharmacophores it can match. In five validation studies, bag classifiers built using FMVs have shown high enrichments for identifying actives for five diverse targets: CDK2, 5-HT(3), DHFR, thrombin, and ACE. The interpretability of these descriptors has been demonstrated for CDK2 and 5-HT(3), where the method automatically discovers the standard literature pharmacophore