Contactin proteins in cerebrospinal fluid show different alterations in dementias.

BACKGROUND: The proteins contactin (CNTN) 1-6 are synaptic proteins for which there is evidence that they are dysregulated in neurodegenerative dementias. Less is known about CNTN changes and differences in cerebrospinal fluid (CSF) of dementias, which can provide important information about alterations of the CNTN network and be of value for differential diagnosis. METHODS: We developed a mass spectrometry-based multiple reaction monitoring (MRM) method to simultaneously determine all six CNTNs in CSF samples using stable isotope-labeled standard peptides. The analytical performance of the method was evaluated for peptide stability, dilution linearity and precision. CNTNs were measured in 82 CSF samples from patients with Alzheimer's disease (AD, n = 19), behavioural variant frontotemporal dementia (bvFTD, n = 18), Parkinson's disease dementia/dementia with Lewy bodies (PDD/DLB, n = 18) and non-neurodegenerative controls (n = 27) and compared with core AD biomarkers. RESULTS: The MRM analysis revealed down-regulation of CNTN2 (fold change (FC) = 0.77), CNTN4 (FC = 0.75) and CNTN5 (FC = 0.67) in bvFTD and CNTN3 (FC = 0.72), CNTN4 (FC = 0.75) and CNTN5 (FC = 0.73) in PDD/DLB compared to AD. CNTN levels strongly correlated with each other in controls (r = 0.73), bvFTD (r = 0.86) and PDD/DLB (r = 0.70), but the correlation was significantly lower in AD (r = 0.41). CNTNs in AD did not show correlation even with core AD biomarkers. Combined use of CNTN1-6 levels increased diagnostic performance of AD core biomarkers. CONCLUSIONS: Our data show CNTNs differentially altered in dementias and indicate CNTN homeostasis being selectively dysregulated in AD. The combined use of CNTNs with AD core biomarkers might help to improve differential diagnosis.

Metabolomics implicate eicosanoids in severe functional mitral regurgitation.

AIMS: Secondary, or functional, mitral regurgitation (FMR) was recently recognized as a separate clinical entity, complicating heart failure with reduced ejection fraction (HFrEF) and entailing particularly poor outcome. Currently, there is a lack of targeted therapies for FMR due to the fact that pathomechanisms leading to FMR progression are incompletely understood. In this study, we sought to perform metabolomic profiling of HFrEF patients with severe FMR, comparing results to patients with no or mild FMR. METHODS AND RESULTS: Targeted plasma metabolomics and untargeted eicosanoid analyses were performed in samples drawn from HFrEF patients (n = 80) on optimal guideline-directed medical therapy. Specifically, 17 eicosanoids and 188 metabolites were analysed. Forty-seven patients (58.8%) had severe FMR, and 33 patients (41.2%) had no or non-severe FMR. Comparison of eicosanoid levels between groups, accounting for age, body mass index, and sex, revealed significant up-regulation of six eicosanoids (11,12-EET, 13(R)-HODE, 12(S)-HETE, 8,9-DiHETrE, metPGJ2, and 20-HDoHE) in severe FMR patients. Metabolites did not differ significantly. In patients with severe FMR, but not in those without severe FMR, levels of 8,9-DiHETrE above a cut-off specified by receiver-operating characteristic analysis independently predicted all-cause mortality after a median follow-up of 43 [interquartile range 38, 48] months [hazard ratio 12.488 (95% confidence interval 3.835-40.666), P < 0.0001]. CONCLUSIONS: We report the up-regulation of various eicosanoids in patients with severe FMR, with 8,9-DiHETrE appearing to predict mortality. Our observations may serve as a nucleus for further investigations into the causes and consequences of metabolic derangements in this important valvular abnormality.

Peptidomic Approaches and Observations in Neurodegenerative Diseases.

Mass spectrometry (MS), with its immense technological developments over the last two decades, has emerged as an unavoidable technique in analyzing biomolecules such as proteins and peptides. Its multiplexing capability and explorative approach make it a valuable tool for analyzing complex clinical samples concerning biomarker research and investigating pathophysiological mechanisms. Peptides regulate various biological processes, and several of them play a critical role in many disease-related pathological conditions. One important example in neurodegenerative diseases is the accumulation of amyloid-beta peptides (Aß) in the brain of Alzheimer's disease (AD) patients. When investigating brain function and brain-related pathologies, such as neurodegenerative diseases, cerebrospinal fluid (CSF) represents the most suitable sample because of its direct contact with the brain. In this review, we evaluate publications applying peptidomics analysis to CSF samples, focusing on neurodegenerative diseases. We describe the methodology of peptidomics analysis and give an overview of the achievements of CSF peptidomics over the years. Finally, publications reporting peptides regulated in AD are discussed.

Prediction of Neurological Recovery After Cardiac Arrest Using Neurofilament Light Chain is Improved by a Proteomics-Based Multimarker Panel.

BACKGROUND: Continuous advances in resuscitation care have increased survival, but the rate of favorable neurological outcome remains low. We have shown the usefulness of proteomics in identifying novel biomarkers to predict neurological outcome. Neurofilament light chain (NfL), a marker of axonal damage, has since emerged as a promising single marker. The aim of this study was to assess the predictive value of NfL in comparison with and in addition to our established model. METHODS: NfL was measured in plasma samples drawn at 48 h after cardiac arrest using single-molecule assays. Neurological function was recorded on the cerebral performance category (CPC) scale at discharge from the intensive care unit and after 6 months. The ability to predict a dichotomized outcome (CPC 1-2 vs. 3-5) was assessed with receiver operating characteristic (ROC) curves. RESULTS: Seventy patients were included in this analysis, of whom 21 (30%) showed a favorable outcome (CPC 1-2), compared with 49 (70%) with an unfavorable outcome (CPC 3-5) at discharge. NfL increased from CPC 1 to 5 (16.5 pg/ml to 641 pg/ml, p < 0.001). The addition of NfL to the existing model improved it significantly (Wald test, p < 0.001), and the combination of NfL with a multimarker model showed high areas under the ROC curve (89.7% [95% confidence interval 81.7-97.7] at discharge and 93.7% [88.2-99.2] at 6 months) that were significantly greater than each model alone. CONCLUSIONS: The combination of NfL with other plasma and clinical markers is superior to that of either model alone and achieves high areas under the ROC curve in this relatively small sample.

Catalase Predicts In-Hospital Mortality after Out-of-Hospital Cardiac Arrest.

The generation of harmful reactive oxygen species (ROS), including hydrogen peroxide, in out-of-hospital cardiac arrest (OHCA) survivors causes systemic ischemia/reperfusion injury that may lead to multiple organ dysfunction and mortality. We hypothesized that the antioxidant enzyme catalase may attenuate these pathophysiological processes after cardiac arrest. Therefore, we aimed to analyze the predictive value of catalase levels for mortality in OHCA survivors. In a prospective, single-center study, catalase levels were determined in OHCA survivors 48 h after the return of spontaneous circulation. Thirty-day mortality was defined as the study end point. A total of 96 OHCA survivors were enrolled, of whom 26% (n = 25) died within the first 30 days after OHCA. The median plasma intensity levels (log2) of catalase were 8.25 (IQR 7.64-8.81). Plasma levels of catalase were found to be associated with mortality, with an adjusted HR of 2.13 (95% CI 1.07-4.23, p = 0.032). A Kaplan-Meier analysis showed a significant increase in 30-day mortality in patients with high catalase plasma levels compared to patients with low catalase levels (p = 0.012). High plasma levels of catalase are a strong and independent predictor for 30-day mortality in OHCA survivors. This indicates that ROS-dependent tissue damage is playing a crucial role in fatal outcomes of post-cardiac syndrome patients.

Reduced LDL-Cholesterol and Reduced Total Cholesterol as Potential Indicators of Early Cancer in Male Treatment-Naïve Cancer Patients With Pre-cachexia and Cachexia.

Cancer cachexia is characterized by the impairment of glucose and lipid homeostasis, the acceleration of processes promoting the mobilization of energy-rich compounds (e.g., insulin resistance, gluconeogenesis, and lipolysis) and the simultaneous activation of highly energy-demanding processes (e.g., systemic inflammation and activation of brown adipose tissue). We hypothesized that these processes might themselves change during cancer cachexia progression, such that plasma levels of glucose and lipids might be used to distinguish between the non-malignant state, pre-cachexia and cachexia. We performed an initial cross-sectional study including 60 treatment naïve cancer patients (38 with cancer cachexia and 22 with cancer pre-cachexia) and 61 patients without malignancy (21 with metabolic syndrome and 40 controls). Differences in lipids (total cholesterol, LDL and HDL cholesterol) and plasma fasting glucose were analyzed across various group configurations, with adjustments to age and antidiabetic or lipid-lowering drugs. Our study showed that levels of LDL cholesterol and total cholesterol might indicate cachexia stages irrespective of the presence of metabolic syndrome or lipid-lowering medication. High levels of plasma glucose were only seen in cachectic cancer patients on antidiabetics. These observations indicate that markers of metabolic dysregulation associated with cachexia progression might be exploited for early detection of malignancy.

Neutrophil Extracellular Trap Formation Correlates with Favorable Overall Survival in High Grade Ovarian Cancer.

It is still a question of debate whether neutrophils, often found in the tumor microenvironment, mediate tumor-promoting or rather tumor-inhibiting activities. The present study focuses on the involvement of neutrophils in high grade serous ovarian cancer (HGSOC). Macroscopic features classify two types of peritoneal tumor spread in HGSOC. Widespread and millet sized lesions characterize the miliary type, while non-miliary metastases are larger and associated with better prognosis. Multi-omics and FACS data were generated from ascites samples. Integrated data analysis demonstrates a significant increase of neutrophil extracellular trap (NET)-associated molecules in non-miliary ascites samples. A co-association network analysis performed with the ascites data further revealed a striking correlation between NETosis-associated metabolites and several eicosanoids. The congruence of data generated from primary neutrophils with ascites analyses indicates the predominance of NADPH oxidase 2 (NOX)-independent NETosis. NETosis is associated with protein S100A8/A9 release. An increase of the S100A8/CRP abundance ratio was found to correlate with favorable survival of HGSOC patients. The analysis of additional five independent proteome studies with regard to S100A8/CRP ratios confirmed this observation. In conclusion, NET formation seems to relate with better cancer patient outcome.

Proteomics-Enriched Prediction Model for Poor Neurologic Outcome in Cardiac Arrest Survivors.

OBJECTIVES: Neurologic outcome prediction in out-of-hospital cardiac arrest survivors is highly limited due to the lack of consistent predictors of clinically relevant brain damage. The present study aimed to identify novel biomarkers of neurologic recovery to improve early prediction of neurologic outcome. DESIGN: Prospective, single-center study, SETTING:: University-affiliated tertiary care center. PATIENTS: We prospectively enrolled 96 out-of-hospital cardiac arrest survivors into our study. INTERVENTIONS: None. MEASUREMENTS AND MAIN RESULTS: Neurologic outcome was assessed by the Cerebral Performance Categories score. To identify plasma biomarkers for poor neurologic outcome (Cerebral Performance Categories score ≥ 3), we performed a three-step proteomics strategy of preselection by shotgun analyses, crosschecking in brain tissue samples, and verification by targeted proteomic analyses using a multistep statistical modeling approach. Sixty-three patients (66%) had a poor neurologic outcome. Out of a total of 299 proteins, we identified α-enolase, 14-3-3 protein ζ/δ, cofilin-1, and heat shock cognate 71 kDa protein as novel biomarkers for poor neurologic outcome. The implementation of these biomarkers into a clinical multimarker model, consisting of previously identified covariates associated to outcome, resulted in a significant improvement of neurologic outcome prediction (C-index, 0.70; explained variation, 11.9%; p for added value, 0.019). CONCLUSIONS: This study identified four novel biomarkers for the prediction of poor neurologic outcome in out-of-hospital cardiac arrest survivors. The implementation of α-enolase, 14-3-3 protein ζ/δ, cofilin-1, and heat shock cognate 71 kDa protein into a multimarker predictive model along with previously identified risk factors significantly improved neurologic outcome prediction. Each of the proteomically identified biomarkers did not only outperform current risk stratification models but may also reflect important pathophysiologic pathways undergoing during cerebral ischemia.

NECTIN4 (PVRL4) as Putative Therapeutic Target for a Specific Subtype of High Grade Serous Ovarian Cancer-An Integrative Multi-Omics Approach.

In high grade serous ovarian cancer patients with peritoneal involvement and unfavorable outcome would benefit from targeted therapies. The aim of this study was to find a druggable target against peritoneal metastasis. We constructed a planar-scale free small world-co-association gene expression network and searched for clusters with hub-genes associated to peritoneal spread. Protein expression and impact was validated via immunohistochemistry and correlations of deregulated pathways with comprehensive omics data were used for biological interpretation. A cluster up-regulated in miliary tumors with NECTIN4 as hub-gene was identified and impact on survival validated. High Nectin 4 protein expression was associated with unfavorable survival and (i) reduced expression of HLA genes (mainly MHC I); (ii) with reduced expression of genes from chromosome 22q11/12; (iii) higher BCAM in ascites and in a high-scoring expression cluster; (iv) higher Kallikrein gene and protein expressions; and (v) substantial immunologic differences; locally and systemically; e.g., reduced CD14 positive cells and reduction of different natural killer cell populations. Each three cell lines with high (miliary) or low NECTIN4 expression (non-miliary) were identified. An anti-Nectin 4 antibody with a linked antineoplastic drug-already under clinical investigation-could be a candidate for a targeted therapy in patients with extensive peritoneal involvement.

Curcumin exerts its antitumor effects in a context dependent fashion.

Proteome profiling profoundly contributes to the understanding of cell response mechanisms to drug actions. Such knowledge may become a key to improve personalized medicine. In the present study, the effects of the natural remedy curcumin on breast cancer model systems were investigated. MCF-7, ZR-75-1 and TGF-ß1 pretreated fibroblasts, mimicking cancer-associated fibroblasts (CAFs), were treated independently as well as in tumor cell/CAF co-cultures. Remarkably, co-culturing with CAF-like cells (CLCs) induced different proteome alterations in MCF-7 and ZR-75-1 cells, respectively. Curcumin significantly induced HMOX1 in single cell type models and co-cultures. However, other curcumin effects differed. In the MCF-7/CLC co-culture, curcumin significantly down-regulated RC3H1, a repressor of inflammatory signaling. In the ZR-75-1/CLC co-culture, curcumin significantly down-regulated PEG10, an anti-apoptotic protein, and induced RRAGA, a pro-apoptotic protein involved in TNF-alpha signaling. Furthermore, curcumin induced AKR1C2, an important enzyme for progesterone metabolism. None of these specific curcumin effects were observed in single cell type cultures. All high-resolution mass spectrometry data are available via ProteomeXchange with the identifier PXD008719. The present data demonstrate that curcumin induces proteome alterations, potentially accounting for its known antitumor effects, in a strongly context-dependent fashion. BIOLOGICAL SIGNIFICANCE: Better means to understand and potentially predict individual variations of drug effects are urgently required. The present proteome profiling study of curcumin effects demonstrates the massive impact of the cell microenvironment on cell responses to drug action. Co-culture models apparently provide more biologically relevant information regarding curcumin effects than single cell type cultures.