Introduction

The metabolic alterations reflecting the influence of prostate cancer cells can be captured through metabolomic profiling.

Objective

To characterize the plasma metabolomic profile in prostatic intraepithelial neoplasia (PIN) and prostate cancer (PCa).

Methods

Metabolomics analyses were performed in plasma samples from individuals classified as non-cancerous control (n = 36), with PIN (n = 16), or PCa (n = 27). Untargeted [26 moieties identified after pre-processing by gas chromatography/mass spectrometry (GC/MS)] and targeted [46 amino acids, carbohydrates, organic acids and fatty acids by GC/MS, and 16 nucleosides and amino acids by ultra performance liquid chromatography-triple quadrupole/mass spectrometry (UPLC-TQ/MS)] analyses were performed. Prostate specific antigen (PSA) concentrations were measured in all samples. In PCa patients, the Gleason scores were determined.

Results

The metabolites that were best discriminated (p < 0.05, FDR < 0.2) for the Kruskal–Wallis test with Dunn’s post-hoc comparing the control versus the PIN and PCa groups included isoleucine, serine, threonine, cysteine, sarcosine, glyceric acid, among several others. PIN was mainly characterized by alterations on steroidogenesis, glycine and serine metabolism, methionine metabolism and arachidonic acid metabolism, among others. In the case of PCa, the most predominant metabolic alterations were ubiquinone biosynthesis, catecholamine biosynthesis, thyroid hormone synthesis, porphyrin and purine metabolism. In addition, we identified metabolites that were correlated to the PSA [i.e. hypoxanthine (r = − 0.60, p < 0.05; r = − 0.54, p < 0.01) and uridine (r = − 0.58, p < 0.05; r = − 0.50, p < 0.01) in PIN and PCa groups, respectively] and metabolites that were significantly different in PCa patients with Gleason score < 7 and ≥ 7 [i.e. arachidonic acid, median (P25–P75) = 883.0 (619.8–956.4) versus 570.8 (505.6–651.8), respectively (p < 0.01)].

Conclusions

This human plasma metabolomic assessment contributes to the understanding of the unique metabolic features exhibited in PIN and PCa and provides a list of metabolites that can have the potential to be used as biomarkers for early detection of disease progression and management.

中文翻译：

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前列腺上皮内瘤变和前列腺癌中的血浆代谢组学谱以及与前列腺特异性抗原和格里森评分的关系。

介绍

反映前列腺癌细胞影响的代谢变化可通过代谢组学分析来捕获。

目的

表征前列腺上皮内瘤变（PIN）和前列腺癌（PCa）的血浆代谢组学特征。

方法

代谢组学分析是在血浆样品中进行的，这些血浆样品来自被分类为非癌性对照（n = 36），PIN（n = 16）或PCa（n = 27）的个体。未靶向[在通过气相色谱/质谱（GC / MS）进行预处理后鉴定出的26个部分]，并靶向[通过GC / MS鉴定出的46种氨基酸，碳水化合物，有机酸和脂肪酸，以及通过超高效液相色谱得到的16种核苷和氨基酸进行了色谱-三重四极杆/质谱（UPLC-TQ / MS）分析。在所有样品中测量前列腺特异性抗原（PSA）浓度。在PCa患者中，确定了格里森评分。

结果

用Dunn在事后比较对照组和PIN组和PCa组的Kruskal-Wallis试验，可以最好地区分的代谢物（p <0.05，FDR <0.2），包括异亮氨酸，丝氨酸，苏氨酸，半胱氨酸，肌氨酸，甘油酸，其他几个。PIN的主要特征是类固醇生成，甘氨酸和丝氨酸代谢，蛋氨酸代谢和花生四烯酸代谢发生变化。就PCa而言，最主要的代谢改变是泛醌生物合成，儿茶酚胺生物合成，甲状腺激素合成，卟啉和嘌呤代谢。此外，我们鉴定了与PSA相关的代谢物（即次黄嘌呤（r =-0.60，p <0.05; r =-0.54，p <0.01）和尿苷（r =-0.58，p <0.05; r = − 0.50 ，p <0.01）在PIN和PCa组中，

结论

人体血浆代谢组学评估有助于了解PIN和PCa中表现出的独特代谢特征，并提供了一系列代谢物，这些代谢物有可能被用作早期检测疾病进展和控制疾病的生物标志物。