Kumar Deepak, Gupta Ashish, Mandhani Anil, Sankhwar Satya Narain
Department of Metabolomics, Centre of Biomedical Research, SGPGIMS Campus, Lucknow, India.
Uttar Pradesh Technical University, Lucknow, India.
Prostate. 2016 Sep;76(12):1106-19. doi: 10.1002/pros.23198. Epub 2016 May 16.
To address the shortcomings of digital rectal examinations (DRE), serum prostate-specific antigen (PSA), and trans-rectal ultrasound (TRUS) for precise determination of prostate cancer (PC) and differentiation from benign prostatic hyperplasia (BPH), we applied (1) H-nuclear magnetic resonance (NMR) spectroscopy as a surrogate tactic for probing and prediction of PC and BPH.
The study comprises 210 filtered sera from suspected PC, BPH, and a healthy subjects' cohort (HC). The filtered serum approach delineates to identify and quantify 52 metabolites using (1) H NMR spectroscopy. All subjects had undergone clinical evaluations (DRE, PSA, and TRUS) followed by biopsy for Gleason score, if needed. NMR-measured metabolites and clinical evaluation data were examined separately using linear multivariate discriminant function analysis (DFA) to probe the signature descriptors for each cohort.
DFA indicated that glycine, sarcosine, alanine, creatine, xanthine, and hypoxanthine were able to determine abnormal prostate (BPH + PC). DFA-based classification presented high precision (86.2% by NMR and 68.1% by clinical laboratory method) in discriminating HC from BPH + PC. DFA reveals that alanine, sarcosine, creatinine, glycine, and citrate were able to discriminate PC from BPH. DFA-based categorization exhibited high accuracy (88.3% by NMR and 75.2% by clinical laboratory method) to differentiate PC from BPH.
(1) H NMR-based metabolic profiling of filtered-serum sample appears to be assuring, swift, and least-invasive for probing and prediction of PC and BPH with its signature metabolic profile. This novel technique is not only on a par with histopathological evaluation of PC determination but is also comparable to liquid chromatography-based mass spectrometry to identify the metabolites. Prostate 76:1106-1119, 2016. © 2016 Wiley Periodicals, Inc.
为解决直肠指检（DRE）、血清前列腺特异性抗原（PSA）和经直肠超声（TRUS）在精确诊断前列腺癌（PC）以及与良性前列腺增生（BPH）鉴别方面的不足，我们应用（1）氢核磁共振（NMR）波谱作为探测和预测PC及BPH的替代策略。
该研究纳入了来自疑似PC、BPH患者以及健康受试者队列（HC）的210份过滤血清。采用过滤血清方法，利用（1）H NMR波谱鉴定和定量52种代谢物。所有受试者均接受了临床评估（DRE、PSA和TRUS），必要时进行活检以确定Gleason评分。分别使用线性多变量判别函数分析（DFA）对NMR测量的代谢物和临床评估数据进行分析，以探寻每个队列的特征性描述指标。
DFA表明，甘氨酸、肌氨酸、丙氨酸、肌酸、黄嘌呤和次黄嘌呤能够确定前列腺异常（BPH + PC）。基于DFA的分类在区分HC与BPH + PC方面具有较高的准确性（NMR法为86.2%，临床实验室方法为68.1%）。DFA显示，丙氨酸、肌氨酸、肌酐、甘氨酸和柠檬酸盐能够区分PC与BPH。基于DFA的分类在区分PC与BPH方面具有较高的准确率（NMR法为88.3%，临床实验室方法为75.2%）。
基于（1）H NMR的过滤血清样本代谢谱分析对于探测和预测PC及BPH及其特征性代谢谱而言，似乎是可靠、快速且侵入性最小的。这项新技术不仅与PC诊断的组织病理学评估相当，而且与基于液相色谱的质谱法在鉴定代谢物方面也具有可比性。《前列腺》76:1106 - 1119，2016年。© 2016威利期刊公司。
