Exhaled-breath Testing for Prostate Cancer Based on Volatile Organic Compound Profiling Using an Electronic Nose Device (Aeonose (TM)): A Preliminary Report
EUROPEAN UROLOGY FOCUS
Authors: Waltman, Claire G.; Marcelissen, Tom A. T.; van Roermund, Joep G. H.
Abstract
Background: Prostate biopsy, an invasive examination, is the gold standard for diagnosing prostate cancer (PCa). There is a need for a novel noninvasive diagnostic tool that achieves a significantly high pretest probability for PCa, reducing unnecessary biopsy numbers. Recent studies have shown that volatile organic compounds (VOCs) in exhaled breath can be used to detect different types of cancers via training of an artificial neural network (ANN). Objective: To determine whether exhaled-breath analysis using a handheld electronic nose device can be used to discriminate between VOC patterns between PCa patients and healthy individuals. Design, setting, and participants: This prospective pilot study was conducted in the outpatient urology clinic of the Maastricht University Medical Center, the Netherlands. Patients with histologically proven PCa were already included before initial biopsy or during follow-up, with no prior treatment for their PCa. Urological patients with negative biopsies in the past year or patients with prostate enlargement (PE) with low or stable serum prostate-specific antigen were used as controls. Exhaled breath was probed from 85 patients: 32 with PCa and 53 controls (30 having negative biopsies and 23 PE). Outcome measurements and statistical analysis: Patient characteristics were statistically analyzed using independent sample t test and Pearson's chi-square test. Data analysis was performed by Aethena software after data compression using the TUCKER 3 algorithm. ANN models were trained and evaluated using the leave-10%-out cross-validation method. Results and limitations: Our trained ANN showed an accuracy of 0.75, with an area under the curve of 0.79 with sensitivity and specificity of 0.84 (95% confidence interval [CI] 0.66-0.94) and 0.70 (95% CI 0.55-0.81) respectively, comparing PCa with control individuals. The negative predictive value was found to be 0.88. The main limitation is the relatively small sample size. Conclusions: Our findings imply that the Aeonose allows us to discriminate between patients with untreated, histologically proven primary PCa and control patients based on exhaled-breath analysis. Patient summary: We explored the possibility of exhaled-breath analysis using an electronic nose, to be used as a noninvasive tool in clinical practice, as a pretest for diagnosing prostate cancer. We found that the electronic nose was able to discriminate between prostate cancer patients and control individuals. (C) 2018 European Association of Urology. Published by Elsevier B.V. All rights reserved.
Nephrocytes are part of the spectrum of filtration epithelial diversity
CELL AND TISSUE RESEARCH
Authors: Miyaki, Takayuki; Kawasaki, Yuto; Matsumoto, Akira; Kakuta, Soichiro; Sakai, Tatsuo; Ichimura, Koichiro
Abstract
The excretory system produces urine by ultrafiltration via a filtration epithelium. Podocytes are widely found as filtration epithelial cells in eucoelomates. In some animal taxa, including insects and crustaceans, nephrocytes serve to separate toxic substances from the body fluid, in addition to podocytes. Drosophila nephrocytes have been recently utilized as a model system to study podocyte function and disease. However, functionality and cellular architecture are strikingly different between Drosophila nephrocytes and eucoelomate podocytes, and the phylogenetic relationship between these cells remains enigmatic. In this study, using focused-ion beam-scanning electron microscopy (FIB-SEM) tomography, we revealed three-dimensional architecture of decapod nephrocytes with unprecedented accuracy-they filled an enormous gap, which can be called "missing link," in the evolutionary diversity of podocytes and nephrocytes. Thus, we concluded that nephrocytes are part of the spectrum of filtration epithelial diversity in animal phylogeny.