Serum biomarker signature is predictive of the risk of hepatocellular cancer in patients with cirrhosis.

BACKGROUND: Inflammatory and metabolic biomarkers have been associated with hepatocellular cancer (HCC) risk in phases I and II biomarker studies. We developed and internally validated a robust metabolic biomarker panel predictive of HCC in a longitudinal phase III study. METHODS: We used data and banked serum from a prospective cohort of 2266 adult patients with cirrhosis who were followed until the development of HCC (n=126). We custom designed a FirePlex immunoassay to measure baseline serum levels of 39 biomarkers and established a set of biomarkers with the highest discriminatory ability for HCC. We performed bootstrapping to evaluate the predictive performance using C-index and time-dependent area under the receiver operating characteristic curve (AUROC). We quantified the incremental predictive value of the biomarker panel when added to previously validated clinical models. RESULTS: We identified a nine-biomarker panel (P9) with a C-index of 0.67 (95% CI 0.66 to 0.67), including insulin growth factor-1, interleukin-10, transforming growth factor ß1, adipsin, fetuin-A, interleukin-1 ß, macrophage stimulating protein α chain, serum amyloid A and TNF-α. Adding P9 to our clinical model with 10 factors including AFP improved AUROC at 1 and 2 years by 4.8% and 2.7%, respectively. Adding P9 to aMAP score improved AUROC at 1 and 2 years by 14.2% and 7.6%, respectively. Adding AFP L-3 or DCP did not change the predictive ability of the P9 model. CONCLUSIONS: We identified a panel of nine serum biomarkers that is independently associated with developing HCC in cirrhosis and that improved the predictive ability of risk stratification models containing clinical factors.

Arabidopsis ADC1 functions as an Nδ -acetylornithine decarboxylase.

Polyamines are small aliphatic amines found in almost all organisms, ranging from bacteria to plants and animals. In most plants, putrescine, the metabolic precursor for longer polyamines, such as spermidine and spermine, is produced from arginine, with either agmatine or ornithine as intermediates. Here we show that Arabidopsis thaliana (Arabidopsis) arginine decarboxylase 1 (ADC1), one of the two known arginine decarboxylases in Arabidopsis, not only synthesizes agmatine from arginine, but also converts Nδ -acetylornithine to N-acetylputrescine. Phylogenetic analyses indicate that duplication and neofunctionalization of ADC1 and NATA1, the enzymes that synthesize Nδ -acetylornithine in Arabidopsis, co-occur in a small number of related species in the Brassicaceae. Unlike ADC2, which is localized in the chloroplasts, ADC1 is in the endoplasmic reticulum together with NATA1, an indication that these two enzymes have access to the same substrate pool. Together, these results are consistent with a model whereby NATA1 and ADC1 together provide a pathway for the synthesis of N-acetylputrescine in Arabidopsis.

Differences in Prediagnostic Serum Metabolomic and Lipidomic Profiles Between Cirrhosis Patients with and without Incident Hepatocellular Carcinoma.

Background: Early detection of hepatocellular carcinoma (HCC) is crucial for improving patient outcomes, but we lack robust clinical biomarkers. This study aimed to identify a metabolite and/or lipid panel for early HCC detection. Methods: We developed a high-resolution liquid chromatography mass spectrometry (LC-MS)-based profiling platform and evaluated differences in the global metabolome and lipidome between 28 pre-diagnostic serum samples from patients with cirrhosis who subsequently developed HCC (cases) and 30 samples from patients with cirrhosis and no HCC (controls). We linked differentially expressed metabolites and lipids to their associated genes, proteins, and transcriptomic signatures in publicly available datasets. We used machine learning models to identify a minimal panel to distinguish between cases and controls. Results: Among cases compared with controls, 124 metabolites and 246 lipids were upregulated, while 208 metabolites and 73 lipids were downregulated. The top upregulated metabolites were glycoursodeoxycholic acid, 5-methyltetrahydrofolic acid, octanoyl-coenzyme A, and glycocholic acid. Elevated lipids comprised glycerol lipids, cardiolipin, and phosphatidylethanolamine, whereas suppressed lipids included oxidized phosphatidylcholine and lysophospholipids. There was an overlap between differentially expressed metabolites and lipids and previously published transcriptomic signatures, illustrating an association with liver disease severity. A panel of 12 metabolites that distinguished between cases and controls with an area under the receiver operating curve of 0.98 for the support vector machine (interquartile range, 0.9-1). Conclusion: Using prediagnostic serum samples, we identified a promising metabolites panel that accurately identifies patients with cirrhosis who progressed to HCC. Further validation of this panel is required.

A Structural Approach to Anti-Virulence: A Discovery Pipeline.

The anti-virulence strategy is designed to prevent bacterial virulence factors produced by pathogenic bacteria from initiating and sustaining an infection. One family of bacterial virulence factors is the mono-ADP-ribosyltransferase toxins, which are produced by pathogens as tools to compromise the target host cell. These toxins are bacterial enzymes that exploit host cellular NAD+ as the donor substrate to modify an essential macromolecule acceptor target in the host cell. This biochemical reaction modifies the target macromolecule (often protein or DNA) and functions in a binary fashion to turn the target activity on or off by blocking or impairing a critical process or pathway in the host. A structural biology approach to the anti-virulence method to neutralize the cytotoxic effect of these factors requires the search and design of small molecules that bind tightly to the enzyme active site and prevent catalytic function essentially disarming the pathogen. This method requires a high-resolution structure to serve as the model for small molecule inhibitor development, which illuminates the path to drug development. This alternative strategy to antibiotic therapy represents a paradigm shift that may circumvent multi-drug resistance in the offending microbe through anti-virulence therapy. In this report, the rationale for the anti-virulence structural approach will be discussed along with recent efforts to apply this method to treat honey bee diseases using natural products.

Stress increases attentional bias for alcohol cues in social drinkers who drink to cope.

AIMS: To investigate the effects of stress on alcohol craving and attentional bias for alcohol-related cues in a group of heavy social drinkers. METHOD: Forty-four heavy social drinkers were exposed to either a laboratory stressor task or a control manipulation before completing a questionnaire measure of alcohol craving and a visual probe task which measured attentional bias for alcohol-related cues. Participants were subdivided into those with high and low levels of coping motives for drinking. RESULTS: Compared to a control manipulation, the laboratory stressor task produced increases in alcohol craving (P < 0.01). The laboratory stressor task also produced a significant attentional bias for alcohol-related cues, but only among participants who had high levels of coping motives (P < 0.05). CONCLUSIONS: Findings are broadly consistent with contemporary negative reinforcement models of substance abuse, and with models of subjective craving and attentional biases for substance-related cues.