Shannon L. Werner

A Fourth IκB Protein within the NF-κB Signaling Module

An assay method incorporating at least two different chemiluminescent compounds for detection and/or quantitation of at least two substances in a test sample is described. The synthesis of chemiluminescent reagents or conjugates for use in such methods as well as kits incorporating such reagents are also disclosed. The assays have particular application in the field of clinical diagnostics.

IκBε provides negative feedback to control NF-κB oscillations, signaling dynamics, and inflammatory gene expression

NF-κB signaling is known to be critically regulated by the NF-κB–inducible inhibitor protein IκBα. The resulting negative feedback has been shown to produce a propensity for oscillations in NF-κB activity. We report integrated experimental and computational studies that demonstrate that another IκB isoform, IκBɛ, also provides negative feedback on NF-κB activity, but with distinct functional consequences. Upon stimulation, NF-κB–induced transcription of IκBɛ is delayed, relative to that of IκBα, rendering the two negative feedback loops to be in antiphase. As a result, IκBɛ has a role in dampening IκBα-mediated oscillations during long-lasting NF-κB activity. Furthermore, we demonstrate the requirement of both of these distinct negative feedback regulators for the termination of NF-κB activity and NF-κB–mediated gene expression in response to transient stimulation. Our findings extend the capabilities of a computational model of IκB–NF-κB signaling and reveal a novel regulatory module of two antiphase negative feedback loops that allows for the fine-tuning of the dynamics of a mammalian signaling pathway.

Encoding NF-κB temporal control in response to TNF: distinct roles for the negative regulators IκBα and A20

TNF-induced NF-kappaB activity shows complex temporal regulation whose different phases lead to distinct gene expression programs. Combining experimental studies and mathematical modeling, we identify two temporal amplification steps-one determined by the obligate negative feedback regulator IkappaBalpha-that define the duration of the first phase of NF-kappaB activity. The second phase is defined by A20, whose inducible expression provides for a rheostat function by which other inflammatory stimuli can regulate TNF responses. Our results delineate the nonredundant functions implied by the knockout phenotypes of ikappabalpha and a20, and identify the latter as a signaling cross-talk mediator controlling inflammatory and developmental responses.

Transient IκB Kinase Activity Mediates Temporal NF-κB Dynamics in Response to a Wide Range of Tumor Necrosis Factor-α Doses

Dynamic properties of signaling pathways control their behavior and function. We undertook an iterative computational and experimental investigation of the dynamic properties of tumor necrosis factor (TNF)α-mediated activation of the transcription factor NF-κB. Surprisingly, we found that the temporal profile of the NF-κB activity is invariant to the TNFα dose. We reverse engineered a computational model of the signaling pathway to identify mechanisms that impart this important response characteristic, thus predicting that the IKK activity profile must transiently peak at all TNFα doses to generate the observed NF-κB dynamics. Experimental confirmation of this prediction emphasizes the importance of mechanisms that rapidly down-regulate IKK following TNFα activation. A refined computational model further revealed signaling characteristics that ensure robust TNFα-mediated cell-cell communication over considerable distances, allowing for fidelity of cellular inflammatory responses in infected tissue.

A homeostatic model of IκB metabolism to control constitutive NF-κB activity

Cellular signal transduction pathways are usually studied following administration of an external stimulus. However, disease‐associated aberrant activity of the pathway is often due to misregulation of the equilibrium state. The transcription factor NF‐κB is typically described as being held inactive in the cytoplasm by binding its inhibitor, IκB, until an external stimulus triggers IκB degradation through an IκB kinase‐dependent degradation pathway. Combining genetic, biochemical, and computational tools, we investigate steady‐state regulation of the NF‐κB signaling module and its impact on stimulus responsiveness. We present newly measured in vivo degradation rate constants for NF‐κB‐bound and ‐unbound IκB proteins that are critical for accurate computational predictions of steady‐state IκB protein levels and basal NF‐κB activity. Simulations reveal a homeostatic NF‐κB signaling module in which differential degradation rates of free and bound pools of IκB represent a novel cross‐regulation mechanism that imparts functional robustness to the signaling module.

Transient IKK activity mediates NF-κB temporal dynamics in response to a wide range of TNFα doses

Dynamic properties of signaling pathways control their behavior and function. We undertook an iterative computational and experimental investigation of the dynamic properties of tumor necrosis factor (TNF)α-mediated activation of the transcription factor NF-κB. Surprisingly, we found that the temporal profile of the NF-κB activity is invariant to the TNFα dose. We reverse engineered a computational model of the signaling pathway to identify mechanisms that impart this important response characteristic, thus predicting that the IKK activity profile must transiently peak at all TNFα doses to generate the observed NF-κB dynamics. Experimental confirmation of this prediction emphasizes the importance of mechanisms that rapidly down-regulate IKK following TNFα activation. A refined computational model further revealed signaling characteristics that ensure robust TNFα-mediated cell-cell communication over considerable distances, allowing for fidelity of cellular inflammatory responses in infected tissue.

The Dynamics of Signaling as a Pharmacological Target

Highly networked signaling hubs are often associated with disease, but targeting them pharmacologically has largely been unsuccessful in the clinic because of their functional pleiotropy. Motivated by the hypothesis that a dynamic signaling code confers functional specificity, we investigated whether dynamic features may be targeted pharmacologically to achieve therapeutic specificity. With a virtual screen, we identified combinations of signaling hub topologies and dynamic signal profiles that are amenable to selective inhibition. Mathematical analysis revealed principles that may guide stimulus-specific inhibition of signaling hubs, even in the absence of detailed mathematical models. Using the NFκB signaling module as a test bed, we identified perturbations that selectively affect the response to cytokines or pathogen components. Together, our results demonstrate that the dynamics of signaling may serve as a pharmacological target, and we reveal principles that delineate the opportunities and constraints of developing stimulus-specific therapeutic agents aimed at pleiotropic signaling hubs.

Analytical Validation and Capabilities of the Epic CTC Platform: Enrichment-Free Circulating Tumour Cell Detection and Characterization

The Epic Platform was developed for the unbiased detection and molecular characterization of circulating tumour cells (CTCs). Here, we report assay performance data, including accuracy, linearity, specificity and intra/inter-assay precision of CTC enumeration in healthy donor (HD) blood samples spiked with varying concentrations of cancer cell line controls (CLCs). Additionally, we demonstrate clinical feasibility for CTC detection in a small cohort of metastatic castrate-resistant prostate cancer (mCRPC) patients. The Epic Platform demonstrated accuracy, linearity and sensitivity for the enumeration of all CLC concentrations tested. Furthermore, we established the precision between multiple operators and slide staining batches and assay specificity showing zero CTCs detected in 18 healthy donor samples. In a clinical feasibility study, at least one traditional CTC/mL (CK+, CD45-, and intact nuclei) was detected in 89 % of 44 mCRPC samples, whereas 100 % of samples had CTCs enumerated if additional CTC subpopulations (CK-/CD45- and CK+ apoptotic CTCs) were included in the analysis. In addition to presenting Epic Platforms performance with respect to CTC enumeration, we provide examples of its integrated downstream capabilities, including protein biomarker expression and downstream genomic analyses at single cell resolution.

Enhanced Targeting of the EGFR Network with MM-151, an Oligoclonal Anti-EGFR Antibody Therapeutic

Although EGFR is a validated therapeutic target across multiple cancer indications, the often modest clinical responses to current anti-EGFR agents suggest the need for improved therapeutics. Here, we demonstrate that signal amplification driven by high-affinity EGFR ligands limits the capacity of monoclonal anti-EGFR antibodies to block pathway signaling and cell proliferation and that these ligands are commonly coexpressed with low-affinity EGFR ligands in epithelial tumors. To develop an improved antibody therapeutic capable of overcoming high-affinity ligand-mediated signal amplification, we used a network biology approach comprised of signaling studies and computational modeling of receptor–antagonist interactions. Model simulations suggested that an oligoclonal antibody combination may overcome signal amplification within the EGFR:ERK pathway driven by all EGFR ligands. Based on this, we designed MM-151, a combination of three fully human IgG1 monoclonal antibodies that can simultaneously engage distinct, nonoverlapping epitopes on EGFR with subnanomolar affinities. In signaling studies, MM-151 antagonized high-affinity EGFR ligands more effectively than cetuximab, leading to an approximately 65-fold greater decrease in signal amplification to ERK. In cell viability studies, MM-151 demonstrated antiproliferative activity against high-affinity EGFR ligands, either singly or in combination, while cetuximab activity was largely abrogated under these conditions. We confirmed this finding both in vitro and in vivo in a cell line model of autocrine high-affinity ligand expression. Together, these preclinical studies provide rationale for the clinical study of MM-151 and suggest that high-affinity EGFR ligand expression may be a predictive response marker that distinguishes MM-151 from other anti-EGFR therapeutics. Mol Cancer Ther; 14(7); 1625–36. ©2015 AACR.

Chromosomal Instability Estimation Based on Next Generation Sequencing and Single Cell Genome Wide Copy Number Variation Analysis

Genomic instability is a hallmark of cancer often associated with poor patient outcome and resistance to targeted therapy. Assessment of genomic instability in bulk tumor or biopsy can be complicated due to sample availability, surrounding tissue contamination, or tumor heterogeneity. The Epic Sciences circulating tumor cell (CTC) platform utilizes a non-enrichment based approach for the detection and characterization of rare tumor cells in clinical blood samples. Genomic profiling of individual CTCs could provide a portrait of cancer heterogeneity, identify clonal and sub-clonal drivers, and monitor disease progression. To that end, we developed a single cell Copy Number Variation (CNV) Assay to evaluate genomic instability and CNVs in patient CTCs. For proof of concept, prostate cancer cell lines, LNCaP, PC3 and VCaP, were spiked into healthy donor blood to create mock patient-like samples for downstream single cell genomic analysis. In addition, samples from seven metastatic castration resistant prostate cancer (mCRPC) patients were included to evaluate clinical feasibility. CTCs were enumerated and characterized using the Epic Sciences CTC Platform. Identified single CTCs were recovered, whole genome amplified, and sequenced using an Illumina NextSeq 500. CTCs were then analyzed for genome-wide copy number variations, followed by genomic instability analyses. Large-scale state transitions (LSTs) were measured as surrogates of genomic instability. Genomic instability scores were determined reproducibly for LNCaP, PC3, and VCaP, and were higher than white blood cell (WBC) controls from healthy donors. A wide range of LST scores were observed within and among the seven mCRPC patient samples. On the gene level, loss of the PTEN tumor suppressor was observed in PC3 and 5/7 (71%) patients. Amplification of the androgen receptor (AR) gene was observed in VCaP cells and 5/7 (71%) mCRPC patients. Using an in silico down-sampling approach, we determined that DNA copy number and genomic instability can be detected with as few as 350K sequencing reads. The data shown here demonstrate the feasibility of detecting genomic instabilities at the single cell level using the Epic Sciences CTC Platform. Understanding CTC heterogeneity has great potential for patient stratification prior to treatment with targeted therapies and for monitoring disease evolution during treatment.