Department of Chemistry, University of Turin, Via P. Giuria 7, 10125, Turin, Italy.
Department of Chemistry, Università di Roma "La Sapienza", Sapienza University of Rome, Piazzale Aldo Moro 5, 00185, Rome, Italy.
Sci Rep. 2022 Mar 14;12(1):4361. doi: 10.1038/s41598-022-08435-2.
Prostate cancer (PCa) is the most commonly diagnosed cancer in male individuals, principally affecting men over 50 years old, and is the leading cause of cancer-related deaths. Actually, the measurement of prostate-specific antigen level in blood is affected by limited sensitivity and specificity and cannot discriminate PCa from benign prostatic hyperplasia patients (BPH). In the present paper, 20 urine samples from BPH patients and 20 from PCa patients were investigated to develop a metabolomics strategy useful to distinguish malignancy from benign hyperplasia. A UHPLC-HRMS untargeted approach was carried out to generate two large sets of candidate biomarkers. After mass spectrometric analysis, an innovative chemometric data treatment was employed involving PLS-DA classification with repeated double cross-validation and permutation test to provide a rigorously validated PLS-DA model. Simultaneously, this chemometric approach filtered out the most effective biomarkers and optimized their relative weights to yield the highest classification efficiency. An unprecedented portfolio of prostate carcinoma biomarkers was tentatively identified including 22 and 47 alleged candidates from positive and negative ion electrospray (ESI+ and ESI-) datasets. The PLS-DA model based on the 22 ESI+ biomarkers provided a sensitivity of 95 ± 1% and a specificity of 83 ± 3%, while that from the 47 ESI- biomarkers yielded an 88 ± 3% sensitivity and a 91 ± 2% specificity. Many alleged biomarkers were annotated, belonging to the classes of carnitine and glutamine metabolites, C21 steroids, amino acids, acetylcholine, carboxyethyl-hydroxychroman, and dihydro(iso)ferulic acid.
前列腺癌（PCa）是男性中最常见的癌症，主要影响 50 岁以上的男性，是癌症相关死亡的主要原因。实际上，血液中前列腺特异性抗原水平的测量受到有限的灵敏度和特异性的影响，无法将 PCa 与良性前列腺增生患者（BPH）区分开来。在本研究中，我们研究了 20 例 BPH 患者和 20 例 PCa 患者的尿液样本，以开发一种有用的代谢组学策略来区分恶性肿瘤和良性增生。采用 UHPLC-HRMS 无靶向方法生成了两组候选生物标志物。经过质谱分析，我们采用了一种创新的化学计量学数据处理方法，包括使用具有重复双交叉验证和置换检验的 PLS-DA 分类，以提供严格验证的 PLS-DA 模型。同时，这种化学计量学方法筛选出最有效的生物标志物并优化其相对权重，以获得最高的分类效率。我们暂定鉴定了一组前所未有的前列腺癌生物标志物，包括正离子和负离子电喷雾（ESI+和 ESI-）数据集的 22 个和 47 个候选生物标志物。基于 22 个 ESI+生物标志物的 PLS-DA 模型提供了 95±1%的灵敏度和 83±3%的特异性，而基于 47 个 ESI-生物标志物的模型则提供了 88±3%的灵敏度和 91±2%的特异性。许多候选生物标志物被注释，属于肉碱和谷氨酰胺代谢物、C21 类固醇、氨基酸、乙酰胆碱、羧乙基-羟基色满和二氢（异）阿魏酸。
