Renal cell carcinoma (RCC) accounts for 11,000 deaths per year in the United States. When detected early, generally serendipitously by imaging conducted for other reasons, long term survival is generally excellent. When detected with symptoms, prognosis is poor. Under these circumstances, a screening biomarker has the potential for substantial public health benefit. The purpose of this study was to evaluate the utility of urine metabolomics analysis for metabolomic profiling, identification of biomarkers, and ultimately for devising a urine screening test for RCC. Fifty urine samples were obtained from RCC and control patients from two institutions, and in a separate study, urine samples were taken from 13 normal individuals. Hydrophilic interaction chromatography-mass spectrometry was performed to identify small molecule metabolites present in each sample. Cluster analysis, principal components analysis, linear discriminant analysis, differential analysis, and variance component analysis were used to analyze the data. Previous work is extended to confirm the effectiveness of urine metabolomics analysis using a larger and more diverse patient cohort. It is now shown that the utility of this technique is dependent on the site of urine collection and that there exist substantial sources of variation of the urinary metabolomic profile, although group variation is sufficient to yield viable biomarkers. Surprisingly there is a small degree of variation in the urinary metabolomic profile in normal patients due to time since the last meal, and there is little difference in the urinary metabolomic profile in a cohort of pre- and postnephrectomy (partial or radical) renal cell carcinoma patients, suggesting that metabolic changes associated with RCC persist after removal of the primary tumor. After further investigations relating to the discovery and identity of individual biomarkers and attenuation of residual sources of variation, our work shows that urine metabolomics analysis has potential to lead to a diagnostic assay for RCC.

Multiple redundant and diverse intranodal pacemakers and conduction pathways allow the human sinoatrial node to robustly maintain cardiac rhythm.

Background: A typical microarray experiment has many sources of variation which can be attributed to biological and technical causes. Identifying sources of variation and assessing their magnitude, among other factors, are important for optimal experimental design. The objectives of this study were: (1) to estimate relative magnitudes of different sources of variation and (2) to evaluate agreement between biological and technical replicates.Results: We performed a microarray experiment using a total of 24 Affymetrix GeneChip^®arrays. The study included 4^thmammary gland samples from eight 21-day-oldSprague Dawley CDfemale rats exposed to genistein (soy isoflavone). RNA samples from each rat were split to assess variation arising at labeling and hybridization steps. A general linear model was used to estimate variance components. Pearson correlations were computed to evaluate agreement between technical and biological replicates.Conclusion: The greatest source of variation was biological variation, followed by residual error, and finally variation due to labeling when *.cel files were processed with dChip and RMA image processing algorithms. When MAS 5.0 or GCRMA-EB were used, the greatest source of variation was residual error, followed by biology and labeling. Correlations between technical replicates were consistently higher than between biological replicates.

Background: Adenosine provokes atrial fibrillation (AF) with a higher activation frequency in right atria (RA) versus left atria (LA) in patients, but the underlying molecular and functional substrates are unclear. We tested the hypothesis that adenosine-induced AF is driven by localized reentry in RA areas with highest expression of adenosine A1 receptor and its downstream GIRK (G protein-coupled inwardly rectifying potassium channels) channels ( I _K,Ado ). Methods: We applied biatrial optical mapping and immunoblot mapping of various atrial regions to reveal the mechanism of adenosine-induced AF in explanted failing and nonfailing human hearts (n=37). Results: Optical mapping of coronary-perfused atria (n=24) revealed that adenosine perfusion (10–100 µmol/L) produced more significant shortening of action potential durations in RA (from 290±45 to 239±41 ms, 17.3±10.4%; P <0.01) than LA (from 307±24 to 286±23 ms, 6.7±6.6%; P <0.01). In 10 hearts, adenosine induced AF (317±116 s) that, when sustained (≥2 minutes), was primarily maintained by 1 to 2 localized reentrant drivers in lateral RA. Tertiapin (10–100 nmol/L), a selective GIRK channel blocker, counteracted adenosine-induced action potential duration shortening and prevented AF induction. Immunoblotting showed that the superior/middle lateral RA had significantly higher adenosine A1 receptor (2.7±1.7-fold; P <0.01) and GIRK4 (1.7±0.8-fold; P <0.05) protein expression than lateral/posterior LA. Conclusions: This study revealed a 3-fold RA-to-LA adenosine A1 receptor protein expression gradient in the human heart, leading to significantly greater RA versus LA repolarization sensitivity in response to adenosine. Sustained adenosine-induced AF is maintained by reentrant drivers localized in lateral RA regions with the highest adenosine A1 receptor/GIRK4 expression. Selective atrial GIRK channel blockade may effectively treat AF during conditions with increased endogenous adenosine.