Khalid Tanzeela, Aggio Raphael, White Paul, De Lacy Costello Ben, Persad Raj, Al-Kateb Huda, Jones Peter, Probert Chris S, Ratcliffe Norman
Department of Surgery and Cancer, Imperial College London, London, United Kingdom.
Institute of Translational Medicine, University of Liverpool, Liverpool, United Kingdom.
PLoS One. 2015 Nov 24;10(11):e0143283. doi: 10.1371/journal.pone.0143283. eCollection 2015.
The aim of this work was to investigate volatile organic compounds (VOCs) emanating from urine samples to determine whether they can be used to classify samples into those from prostate cancer and non-cancer groups. Participants were men referred for a trans-rectal ultrasound-guided prostate biopsy because of an elevated prostate specific antigen (PSA) level or abnormal findings on digital rectal examination. Urine samples were collected from patients with prostate cancer (n = 59) and cancer-free controls (n = 43), on the day of their biopsy, prior to their procedure. VOCs from the headspace of basified urine samples were extracted using solid-phase micro-extraction and analysed by gas chromatography/mass spectrometry. Classifiers were developed using Random Forest (RF) and Linear Discriminant Analysis (LDA) classification techniques. PSA alone had an accuracy of 62-64% in these samples. A model based on 4 VOCs, 2,6-dimethyl-7-octen-2-ol, pentanal, 3-octanone, and 2-octanone, was marginally more accurate 63-65%. When combined, PSA level and these four VOCs had mean accuracies of 74% and 65%, using RF and LDA, respectively. With repeated double cross-validation, the mean accuracies fell to 71% and 65%, using RF and LDA, respectively. Results from VOC profiling of urine headspace are encouraging and suggest that there are other metabolomic avenues worth exploring which could help improve the stratification of men at risk of prostate cancer. This study also adds to our knowledge on the profile of compounds found in basified urine, from controls and cancer patients, which is useful information for future studies comparing the urine from patients with other disease states.
这项工作的目的是研究尿液样本中散发的挥发性有机化合物(VOCs),以确定它们是否可用于将样本分为前列腺癌组和非癌组。参与者是因前列腺特异性抗原(PSA)水平升高或直肠指检结果异常而被转诊进行经直肠超声引导下前列腺活检的男性。在活检当天,在手术前,从前列腺癌患者(n = 59)和无癌对照组(n = 43)收集尿液样本。使用固相微萃取从碱化尿液样本的顶空中提取VOCs,并通过气相色谱/质谱分析。使用随机森林(RF)和线性判别分析(LDA)分类技术开发分类器。在这些样本中,仅PSA的准确率为62-64%。基于4种VOCs(2,6-二甲基-7-辛烯-2-醇、戊醛、3-辛酮和2-辛酮)的模型准确率略高,为63-65%。当PSA水平与这四种VOCs结合时,使用RF和LDA的平均准确率分别为74%和65%。通过重复双交叉验证,使用RF和LDA时,平均准确率分别降至71%和65%。尿液顶空VOC分析的结果令人鼓舞,表明还有其他代谢组学途径值得探索,这可能有助于改善前列腺癌风险男性的分层。这项研究还增加了我们对碱化尿液中发现的化合物谱的了解,这些化合物来自对照组和癌症患者,这对于未来比较其他疾病状态患者尿液的研究是有用的信息。