Multiplex proteomic approaches to sepsis research: case studies employing new technologies

Prognostic and predictive biomarkers of abdominal aortic aneurysm growth rate

OBJECTIVES

To test the utility of clinical and circulating biomarkers to predict abdominal aortic aneurysm (AAA) growth rate and response to doxycycline therapy.

METHODS

Plasma samples were obtained in the Pharmaceutical Aneurysm Stabilization Trial that tested the effect of doxycycline (n = 44) vs. placebo (n = 49) in patients with a 35-50 mm AAA. Approximately 200 biomarkers were evaluated in a candidate approach that included markers of matrix turnover and cathepsin S activity and a broad-based approach of predominantly inflammation-related and clinical biomarkers.

RESULTS

In a recursive partitioning based analysis, total cholesterol, baseline AAA size, and apolipoprotein B were prognostic of AAA growth in the placebo group whereas elastin and biglycan degradation products were predictive of AAA growth with doxycycline treatment. Univariate analysis of these biomarkers showed that baseline total cholesterol (r = 0.38, unadjusted P = 0.011), apolipoprotein B (r = 0.41, unadjusted P = 0.005), and baseline AAA size (r = 0.35, unadjusted P = 0.013) correlated with AAA growth in the placebo but not the doxycycline group. Elastin fragments were associated with 18 month AAA growth (r = 0.33, unadjusted P = 0.031) in the doxycycline group.

LIMITATIONS

Limitations of this study include small sample size, a retrospective growth analysis, and translatability of the method used to measure the analytes.

CONCLUSIONS

This study implies that total cholesterol, baseline AAA size, and apolipoprotein B are predictors of AAA growth. Levels of elastin and biglycan fragments are predictive of doxycycline effects on AAA growth and provide a clue towards this unexpected negative effect.

Characterization of AQX-1125, a small-molecule SHIP1 activator: Part 2. Efficacy studies in allergic and pulmonary inflammation models in vivo

BACKGROUND

The efficacy of AQX-1125, a small-molecule SH2-containing inositol-5'-phosphatase 1 (SHIP1) activator and clinical development candidate, is investigated in rodent models of inflammation.

EXPERIMENTAL APPROACH

AQX-1125 was administered orally in a mouse model of passive cutaneous anaphylaxis (PCA) and a number of rodent models of respiratory inflammation including: cigarette smoke, LPS and ovalbumin (OVA)-mediated airway inflammation. SHIP1 dependency of the AQX-1125 mechanism of action was investigated by comparing the efficacy in wild-type and SHIP1-deficient mice subjected to an intrapulmonary LPS challenge.

RESULTS

AQX-1125 exerted anti-inflammatory effects in all of the models studied. AQX-1125 decreased the PCA response at all doses tested. Using bronchoalveolar lavage (BAL) cell counts as an end point, oral or aerosolized AQX-1125 dose dependently decreased the LPS-mediated pulmonary neutrophilic infiltration at 3-30 mg kg⁻¹ and 0.15-15 μg kg⁻¹ respectively. AQX-1125 suppressed the OVA-mediated airway inflammation at 0.1-10 mg kg⁻¹. In the smoke-induced airway inflammation model, AQX-1125 was tested at 30 mg kg⁻¹ and significantly reduced the neutrophil infiltration of the BAL fluid. AQX-1125 (10 mg kg⁻¹) decreased LPS-induced pulmonary neutrophilia in wild-type mice but not in SHIP1-deficient mice.

CONCLUSIONS

The SHIP1 activator, AQX-1125, suppresses leukocyte accumulation and inflammatory mediator release in rodent models of pulmonary inflammation and allergy. As shown in the mouse model of LPS-induced lung inflammation, the efficacy of the compound is dependent on the presence of SHIP1. Pharmacological SHIP1 activation may have clinical potential for the treatment of pulmonary inflammatory diseases.

Protein microarrays: effective tools for the study of inflammatory diseases

Inflammation is a defense reaction of an organism against harmful stimuli such as tissue injury or infectious agents. The relationship between the infecting microorganism and the immune, inflammatory, and coagulation responses of the host is intricately intertwined. Due to its complex nature, the molecular mechanisms of inflammation are not yet understood in detail and additional diagnostic tools are required to clarify further aspects. In recent years, protein microarray-based research has moved from being technology-based to application-oriented. Protein microarrays are perfect tools for studying inflammatory diseases. High-density protein arrays enable new classes of autoantibodies, which cause autoimmune diseases, to be discovered. Protein arrays consisting of miniaturized multiplexed sandwich immunoassays allow the simultaneous expression analysis of dozens of signaling molecules such as the cytokines and chemokines involved in the regulation of the immune system. The data enable statements to be made on the status of the disease and its progression as well as support for the clinicians in choosing patient-specific treatment. This chapter reviews the technology and the applications of protein microarrays in diagnosing and monitoring inflammatory diseases.

Suspension microarrays for the identification of the response patterns in hyperinflammatory diseases

Miniaturized and parallelized sandwich immunoassays allow the simultaneous analysis of a variety of parameters in a single experiment. Bead-based protein array systems or suspension microarrays are well-established multiplex sandwich immunoassay formats. To study inflammatory diseases, protein arrays can be used to analyze changes in plasma protein levels, such as cytokines, chemokines, soluble receptors, and matrix metalloproteinases. Using the bead-based Luminex system, multiplexed sandwich immunoassays have been developed to analyze the plasma concentrations of soluble receptors: sTNF-RI, sTNF-RII, sIL-2R, sgp130, sFas, sRAGE, sE-selectin, sICAM-1, sVCAM-1, sMIF-1 and sFasL. This newly established 11-plex soluble receptors assay demonstrated acceptable intra-assay and inter-assay precision, appropriate accuracy, and no crossreactivity between analytes. Using this assay, 100 plasma samples derived from 36 critically ill intensive care unit (ICU) patients with trauma or sepsis were analyzed for their soluble receptor plasma concentrations. Results obtained allowed grouping of patients' samples into a trauma and a sepsis group. Four candidate molecules: sFas, sICAM-1, sTNF-RI, and sTNF-RII had higher concentrations in patients with sepsis than in those with trauma, contributing the highest discriminatory values to define the nature of the inflammatory disease originating from pathogen-involved (sepsis) or pathogen-independent inflammation.

Protein microarray platforms for clinical proteomics

Proteomics for clinical applications is presently in a state of transition. It has become clear that the classical approaches based on 2-DE and/or MS need to be complemented by different kinds of technologies. The well-known problems include sample complexity, sensitivity, quantitation, reproducibility, and analysis time. We suggest that the new technologies for clinical proteomics can be supported by antibody-centric protein microarray platforms. These platforms presently include antibody microarrays and lysate, or reverse capture/reverse phase protein microarrays. Other forms of these arrays are in less mature developmental stages, including ORF and self assembling protein microarrays. Bioinformatic support for interpreting these arrays is becoming more available as the whole field of systems biology begins to mature. The present set of applications for these platforms is profoundly focused on certain common cancers, immunology, and cystic fibrosis. However, we predict that many more disease entities will become studied as knowledge of the power and availability of these platforms becomes more widely established. We anticipate that these platforms will eventually evolve to accommodate label-free detection technologies, human genome-scale numbers of analytes, and increases in analytic and bioinformatic speeds.

Better Understanding of Organ Dysfunction Requires Proteomic Involvement

Organ dysfunction is defined as a systemic consequence of acute and chronic diseases, a critical and important phase of disease development. The mortality of patients with severe illness is highly correlated with the number and duration of dysfunctional organs. There is still not an efficient and specific therapy to improve the prognosis of patients with organ dysfunction, due to the complexity and severity of the disease. There is a great need to understand molecular mechanisms of the disease, identify disease-related biomarkers, and validate therapeutic effects. Thus, it is important to have a special attention from proteomic scientists to explore the combination between advanced proteomic biotechnology, clinical proteomics, tissue imaging and profiling, and organ dysfunction score systems, to improve the clinical outcomes of these patients.