Cdc42 and Rac1 activity is reduced in human pheochromocytoma and correlates with FARP1 and ARHGEF1 expression.

Among small GTPases from the Rho family, Cdc42, RAC, and Rho are well known to mediate a large variety of cellular processes linked with cancer biology through their ability to cycle between an inactive (GDP-bound) and an active (GTP-bound) state. Guanine nucleotide exchange factors (GEFs) stimulate the exchange of GDP for GTP to generate the activated form, whereas the GTPase-activating proteins (GAPs) catalyze GTP hydrolysis, leading to the inactivated form. Modulation of Rho GTPase activity following altered expression of RHO-GEFs and/or RHO-GAPs has already been reported in various human tumors. However, nothing is known about the Rho GTPase activity or the expression of their regulators in human pheochromocytomas, a neuroendocrine tumor (NET) arising from chromaffin cells of the adrenal medulla. In this study, we demonstrate, through an ELISA-based activity assay, that Rac1 and Cdc42 activities decrease in human pheochromocytomas (PCCs) compared with the matched adjacent non-tumor tissue. Furthermore, through quantitative mass spectrometry (MS) approaches, we show that the expression of two RHO-GEF proteins, namely ARHGEF1 and FARP1, is significantly reduced in tumors compared with matched non-tumor tissue, whereas ARHGAP36 expression is increased. Moreover, siRNA-based knockdown of ARHGEF1 and FARP1 in PC12 cells leads to a significant inhibition of Rac1 and Cdc42 activities, respectively. Finally, a principal component analysis (PCA) of our dataset was able to discriminate PCC from non-tumor tissue and indicates a close correlation between Cdc42/Rac1 activity and FARP1/ARHGEF1 expression. Altogether, our findings reveal for the first time the importance of modulation of Rho GTPase activities and expression of their regulators in human PCCs.

Development and evaluation of a multiplexed mass spectrometry based assay for measuring candidate peptide biomarkers in Alzheimer's Disease Neuroimaging Initiative (ADNI) CSF.

PURPOSE: We describe the outcome of the Biomarkers Consortium CSF Proteomics Project (where CSF is cerebral spinal fluid), a public-private partnership of government, academia, nonprofit, and industry. The goal of this study was to evaluate a multiplexed MS-based approach for the qualification of candidate Alzheimer's disease (AD) biomarkers using CSF samples from the AD Neuroimaging Initiative. EXPERIMENTAL DESIGN: Reproducibility of sample processing, analytic variability, and ability to detect a variety of analytes of interest were thoroughly investigated. Multiple approaches to statistical analyses assessed whether panel analytes were associated with baseline pathology (mild cognitive impairment (MCI), AD) versus healthy controls or associated with progression for MCI patients, and included (i) univariate association analyses, (ii) univariate prediction models, (iii) exploratory multivariate analyses, and (iv) supervised multivariate analysis. RESULTS: A robust targeted MS-based approach for the qualification of candidate AD biomarkers was developed. The results identified several peptides with potential diagnostic or predictive utility, with the most significant differences observed for the following peptides for differentiating (including peptides from hemoglobin A, hemoglobin B, and superoxide dismutase) or predicting (including peptides from neuronal pentraxin-2, neurosecretory protein VGF (VGF), and secretogranin-2) progression versus nonprogression from MCI to AD. CONCLUSIONS AND CLINICAL RELEVANCE: These data provide potential insights into the biology of CSF in AD and MCI progression and provide a novel tool for AD researchers and clinicians working to improve diagnostic accuracy, evaluation of treatment efficacy, and early diagnosis.

A blood-based proteomic classifier for the molecular characterization of pulmonary nodules.

Each year, millions of pulmonary nodules are discovered by computed tomography and subsequently biopsied. Because most of these nodules are benign, many patients undergo unnecessary and costly invasive procedures. We present a 13-protein blood-based classifier that differentiates malignant and benign nodules with high confidence, thereby providing a diagnostic tool to avoid invasive biopsy on benign nodules. Using a systems biology strategy, we identified 371 protein candidates and developed a multiple reaction monitoring (MRM) assay for each. The MRM assays were applied in a three-site discovery study (n = 143) on plasma samples from patients with benign and stage IA lung cancer matched for nodule size, age, gender, and clinical site, producing a 13-protein classifier. The classifier was validated on an independent set of plasma samples (n = 104), exhibiting a negative predictive value (NPV) of 90%. Validation performance on samples from a nondiscovery clinical site showed an NPV of 94%, indicating the general effectiveness of the classifier. A pathway analysis demonstrated that the classifier proteins are likely modulated by a few transcription regulators (NF2L2, AHR, MYC, and FOS) that are associated with lung cancer, lung inflammation, and oxidative stress networks. The classifier score was independent of patient nodule size, smoking history, and age, which are risk factors used for clinical management of pulmonary nodules. Thus, this molecular test provides a potential complementary tool to help physicians in lung cancer diagnosis.

An evaluation of multidimensional fingerprinting in the context of clinical proteomics.

Multidimensional fingerprinting (MDF) utilizes measurable peptide characteristics to identify proteins. In this study, 3-D fingerprinting, namely, parent protein molecular weight, peptide mass, and peptide retention time on RPLC, is used to identify 331 differentially expressed proteins between normal and human colon cancer plasma membrane samples. A false discovery rate (FDR) procedure is introduced to evaluate the performance of MDF on the colon cancer dataset. This evaluation establishes a false protein identification rate below 15% for this dataset. Western blot analysis is performed to validate the differential expression of the MDF-identified protein VDAC1 on the original tissue samples. The limits of MDF are further assessed by a simulation study where key parameters such as database size, query size, and mass accuracy are varied. The results of this simulation study demonstrate that fingerprinting with three dimensions yields low FDR values even for large queries on the complete human proteome without the need for prior peptide sequencing by tandem mass spectrometry. Specifically, when mass accuracy is 10 ppm or lower, full human proteome searches can achieve FDR values of 10% or less.

Exploring structure-activity relationships of tricyclic farnesyltransferase inhibitors using ECLiPS libraries.

The development of structure-activity relationships (SARs) relating to the function of a biological protein is often a long and protracted undertaking when using an iterative medicinal chemistry approach. High throughput screening of ECLiPS (Encoded Combinatorial Libraries on Polymeric Support) libraries can be used to simplify this process. In this paper, we illustrate how a large ECLiPS library of 26,908 compounds, based on a tricyclic core structure, was used to define a multitude of SARs for the oncogenic target, farnesyltransferase (FTase). This library, FT-2, was prepared using a split-and-pool approach in which small molecules are constructed on resin that contains tag/linker constructs to track the synthetic process [1-5] Highly defined SARs were produced from this screen that enhanced our understanding of FTase binding site interactions. The pivotal compounds culled from this library were potent in both cell-free and cell-based FTase assays, selective over the closely related enzyme, geranylgeranyltransferase I (GGTase I), and inhibited the adherent-independent growth of a transformed cell line.

Organ messenger ribonucleic acid and plasma proteome changes in the adjuvant-induced arthritis model: responses to disease induction and therapy with the estrogen receptor-beta selective agonist ERB-041.

Two receptors [estrogen receptor (ER)alpha and ERbeta] mediate the manifold effects of estrogens throughout the body. Although a clear role has been established for ERalpha in the classical effects of estrogen activity, the physiological role of ERbeta is less well understood. A small-molecule ERbeta selective agonist, ERB-041, has potent antiinflammatory activity in the Lewis rat model of adjuvant-induced arthritis. To characterize the response of target organs and pathways responsible for this antiinflammatory effect, mRNA expression profiling of the spleen, lymph node, and liver was performed, in conjunction with a global analysis of the plasma proteome. We find that the expression of a large number of genes and proteins are altered in the disease model and the majority of these are partially or fully reversed by ERB-041 treatment. Regulated pathways include the acute-phase response, eicosanoid synthesis, fatty acid metabolism, and iron metabolism. In addition, many of the regulated genes and proteins are known to be dysregulated in human rheumatoid arthritis, providing further evidence that the manifestations of the Lewis rat adjuvant-induced arthritis model bear similarity to the human disease.