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电子鼻在前列腺癌中的挥发物分析:一项单中心初步研究

Volatilome Analysis in Prostate Cancer by Electronic Nose: A Pilot Monocentric Study.

作者信息

Filianoti Alessio, Costantini Manuela, Bove Alfredo Maria, Anceschi Umberto, Brassetti Aldo, Ferriero Mariaconsiglia, Mastroianni Riccardo, Misuraca Leonardo, Tuderti Gabriele, Ciliberto Gennaro, Simone Giuseppe

机构信息

Department of Urology, IRCCS-"Regina Elena" National Cancer Institute, 00144 Rome, Italy.

Department of Urology, San Filippo Neri Hospital, 00135 Rome, Italy.

出版信息

Cancers (Basel). 2022 Jun 14;14(12):2927. doi: 10.3390/cancers14122927.

Abstract

Urine analysis via an electronic nose provides volatile organic compounds easily usable in the diagnosis of urological diseases. Although challenging and highly expensive for health systems worldwide, no useful markers are available in clinical practice that aim to anticipate prostate cancer (PCa) diagnosis in the early stages in the context of wide population screening. Some previous works suggested that dogs trained to smell urine could recognize several types of cancers with various success rates. We hypothesized that urinary volatilome profiling may distinguish PCa patients from healthy controls. In this study, 272 individuals, 133 patients, and 139 healthy controls participated. Urine samples were collected, stabilized at 37 °C, and analyzed using a commercially available electronic nose (Cyranose C320). Statistical analysis of the sensor responses was performed off-line using principal component (PCA) analyses, discriminant analysis (CDA), and ROC curves. Principal components best discriminating groups were identified with univariable ANOVA analysis. groups were identified with univariable ANOVA analysis. Here, 110/133 and 123/139 cases were correctly identified in the PCa and healthy control cohorts, respectively (sensitivity 82.7%, specificity 88.5%; positive predictive value 87.3%, negative predictive value 84.2%). The Cross Validated Accuracy (CVA 85.3%, p < 0.001) was calculated. Using ROC analysis, the area under the curve was 0.9. Urine volatilome profiling via an electronic nose seems a promising non-invasive diagnostic tool.

摘要

通过电子鼻进行尿液分析可提供易于用于泌尿系统疾病诊断的挥发性有机化合物。尽管对全球卫生系统来说具有挑战性且成本高昂,但在广泛人群筛查的背景下,临床实践中尚无旨在早期预测前列腺癌(PCa)诊断的有用标志物。先前的一些研究表明,经过尿液气味训练的犬类能够以不同的成功率识别多种类型的癌症。我们推测尿液挥发物谱分析可能会区分PCa患者和健康对照者。在本研究中,共有272人参与,其中包括133例患者和139名健康对照者。收集尿液样本,在37℃下稳定保存,并使用市售电子鼻(Cyranose C320)进行分析。使用主成分分析(PCA)、判别分析(CDA)和ROC曲线对传感器响应进行离线统计分析。通过单因素方差分析确定最能区分组别的主成分。在PCa和健康对照队列中,分别正确识别出110/133例和123/139例(敏感性82.7%,特异性88.5%;阳性预测值87.3%,阴性预测值84.2%)。计算交叉验证准确率(CVA 85.3%,p<0.001)。使用ROC分析,曲线下面积为0.9。通过电子鼻进行尿液挥发物谱分析似乎是一种有前景的非侵入性诊断工具。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a92d/9220860/5123606771e2/cancers-14-02927-g001.jpg

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