Laboratory of Pharmacokinetics and Metabolomic Analysis, Institute of Translational Medicine and Biotechnology, I.M. Sechenov First Moscow State Medical University, 2-4 Bolshaya Pirogovskaya St., Moscow, Russia, 119991.
PhD Program in Nanosciences and Advanced Technologies, University of Verona, Verona, Italy.
Metabolomics. 2020 Jun 17;16(7):74. doi: 10.1007/s11306-020-01694-y.
The metabolic alterations reflecting the influence of prostate cancer cells can be captured through metabolomic profiling.
To characterize the plasma metabolomic profile in prostatic intraepithelial neoplasia (PIN) and prostate cancer (PCa).
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.
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)].
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.
反映前列腺癌细胞影响的代谢改变可以通过代谢组学分析来捕捉。
描绘前列腺上皮内瘤变（PIN）和前列腺癌（PCa）患者的血浆代谢组图谱。
对分类为非癌对照（n=36）、PIN（n=16）或 PCa（n=27）个体的血浆样本进行代谢组学分析。通过气相色谱/质谱（GC/MS）进行非靶向[26 种经预处理后鉴定的代谢物]和靶向[GC/MS 分析 46 种氨基酸、碳水化合物、有机酸和脂肪酸，UPLC-TQ/MS 分析 16 种核苷和氨基酸]分析。所有样本均测量前列腺特异性抗原（PSA）浓度。在 PCa 患者中，测定 Gleason 评分。
Kruskal-Wallis 检验和 Dunn 事后检验（p<0.05， FDR<0.2）最佳区分的代谢物为异亮氨酸、丝氨酸、苏氨酸、半胱氨酸、肌氨酸、甘油酸等。PIN 主要表现为类固醇生成、甘氨酸和丝氨酸代谢、蛋氨酸代谢和花生四烯酸代谢的改变。在 PCa 中，最主要的代谢改变为泛醌生物合成、儿茶酚胺生物合成、甲状腺激素合成、卟啉和嘌呤代谢。此外，我们还鉴定了与 PSA 相关的代谢物[即 PIN 和 PCa 组中的次黄嘌呤（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）]和 Gleason 评分<7 和≥7 的 PCa 患者中差异显著的代谢物[即花生四烯酸，中位数（P25-P75）=883.0（619.8-956.4）与 570.8（505.6-651.8），p<0.01]。
这项人体血浆代谢组学评估有助于了解 PIN 和 PCa 中独特的代谢特征，并提供了一组可能用作疾病进展和管理早期检测的潜在生物标志物的代谢物。
