LC-QTOF-ESI(+)/MS代谢组学分析用于鉴定良性增生和前列腺癌的血液生物标志物。

Ramona Maria Maxim, Florina Romanciuc, N. Crisan, I. Andras, C. Socaciu
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引用次数: 1

摘要

前列腺癌(PCa)是导致男性死亡的第二大原因,目前的诊断方法是基于血清前列腺特异性抗原(PSA)筛查,特异性低且估值过高。采用HPLC-(ESI+) QTOF-MS分析方法,对健康(n=11)、增生(n=39)和前列腺癌(n=83)患者的血清代谢物进行了非靶向和靶向代谢组学研究。血清样品的轮廓提供了从基峰色谱和解剖色谱获得的补充信息。基于层析图,使用了两种不同的统计分析方法,一种是基于仪器软件进行自动校准(带/不带归一化),另一种是基于手动校准然后进行统计分析(Unscrambler10)。X软件)。两种方法都使用无监督主成分分析来区分正常、增生和癌症患者。第二种方法可以通过定性和定量参数(m/z值与峰面积)更好地区分群体,并更好地识别导致这种区分的分子。考虑到保留时间间隔(6-17 min),确定了前列腺增生或前列腺癌的四种可能的生物标志物:前列腺素E2/G2、孕烯醇酮/乙基睾酮、溶血磷脂酰胆碱18:2/0:0、半乳糖神经酰胺(18:1/24:1)。通过使用更大的患者队列,优化数据处理和化学计量学分析,可以发现和量化更可靠的前列腺增生和癌症的生物标志物。这项初步研究为临床实验室中代谢组学靶向分析的实施和验证提供了有希望的发现。
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LC-QTOF-ESI(+)/MS metabolomic profile analysis applied to identify blood biomarkers of benign hyperplasia and prostate cancer.
Prostate cancer (PCa) is the second leading cause of mortality in men, the present diagnosis method being based on serum prostate-specific antigen (PSA) screening, with low specificity and overestimated values. A combined untargeted and targeted metabolomic study of metabolites from blood serum samples collected from healthy (n=11), hyperplasia (n=39) and prostate cancer (n=83) patients is presented, using the HPLC-(ESI+) QTOF-MS analysis. The profile of blood serum samples provided complementary information obtained from Base Peak Chromatograms and Dissect chromatograms. Based on dissect chromatograms, two different methods of statistical analysis were used, either based on the instrument software with automated alignments with/without normalization (Profile Analysis), or based on manual alignment followed by statistical analysis (Unscrambler10.X software). Both methods used the unsupervised Principal Component Analysis which discriminated between normal, hyperplasia and cancer patients. The second method allowed a better discrimination between groups, by qualitative and quantitative parameters (m/z values versus peak areas) and better possibilities to identify the molecules responsible for such discriminations.Considering the retention time interval (6-17 min), four molecules to be considered as putative biomarkers for hyperplasia or prostate cancer were identified: Prostaglandins E2/G2, Pregnenolone/ethyltestosterone, Lysophosphatidylcholine18:2/0:0, Galactosylceramide (18:1/24:1).By using larger patient cohorts and optimizing the data processing and chemometric analysis, more reliable biomarkers for prostate hyperplasia and cancer can be discovered and quantified. This preliminary study has had promising findings for the implementation and validation of metabolomic targeted analysis in clinical laboratories.
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