Sequeiros Tamara, Bastarós Juan M, Sánchez Milagros, Rigau Marina, Montes Melania, Placer José, Planas Jaques, de Torres Inés, Reventós Jaume, Pegtel D Michiel, Doll Andreas, Morote Juan, Olivan Mireia
Group of Biomedical Research in Urology, Vall d'Hebron Research Institute (VHIR) and Universitat Autònoma de Barcelona (UAB), Barcelona, Spain.
Department of Urology, Vall d'Hebron University Hospital and Universitat Autònoma de Barcelona (UAB), Barcelona, Spain.
Prostate. 2015 Jul 1;75(10):1102-13. doi: 10.1002/pros.22995. Epub 2015 Apr 1.
High-grade prostatic intraepithelial neoplasia (HGPIN) is a recognized precursor stage of PCa. Men who present HGPIN in a first prostate biopsy face years of active surveillance including repeat biopsies. This study aimed to identify non-invasive prognostic biomarkers that differentiate early on between indolent HGPIN cases and those that will transform into actual PCa.
We measured the expression of 21 candidate mRNA biomarkers using quantitative PCR in urine sediment samples from a cohort of 90 patients with initial diagnosis of HGPIN and a posterior follow up of at least two years. Uni- and multivariate statistical analyses were applied to analyze the candidate biomarkers and multiplex models using combinations of these biomarkers.
PSMA, PCA3, PSGR, GOLM, KLK3, CDH1, and SPINK1 behaved as predictors for PCa presence in repeat biopsies. Multiplex models outperformed (AUC = 0.81-0.86) the predictive power of single genes, including the FDA-approved PCA3 (AUC = 0.70). With a fixed sensitivity of 95%, the specificity of our multiplex models was of 41-58%, compared to the 30% of PCA3. The PPV of our models (30-38%) was also higher than the PPV of PCA3 (27%), suggesting that benign cases could be more accurately identified. Applying statistical models, we estimated that 33% to 47% of repeat biopsies could be prevented with a multiplex PCR model, representing an easy applicable and significant advantage over the current gold standard in urine sediment.
Using multiplex RTqPCR-based models in urine sediment it is possible to improve the current diagnostic method of choice (PCA3) to differentiate between benign HGPIN and PCa cases.
高级别前列腺上皮内瘤变（HGPIN）是公认的前列腺癌前驱阶段。在首次前列腺活检中发现HGPIN的男性需接受数年的主动监测，包括重复活检。本研究旨在识别非侵入性预后生物标志物，以便早期区分惰性HGPIN病例和将转变为实际前列腺癌的病例。
我们使用定量PCR测量了90例初诊为HGPIN且后续至少随访两年的患者尿液沉淀物样本中21种候选mRNA生物标志物的表达。应用单变量和多变量统计分析来分析候选生物标志物以及使用这些生物标志物组合的多重模型。
前列腺特异性膜抗原（PSMA）、前列腺癌抗原3（PCA3）、前列腺分泌蛋白基因受体（PSGR）、高尔基体膜蛋白（GOLM）、激肽释放酶3（KLK3）、钙黏蛋白1（CDH1）和丝氨酸蛋白酶抑制剂Kazal型1（SPINK1）可作为重复活检中前列腺癌存在的预测指标。多重模型的预测能力优于（曲线下面积[AUC]=0.81 - 0.86）单个基因，包括美国食品药品监督管理局（FDA）批准的PCA3（AUC = 0.70）。在固定灵敏度为95%的情况下，我们多重模型的特异性为41% - 58%，而PCA3为30%。我们模型的阳性预测值（PPV）（30% - 38%）也高于PCA3的PPV（27%），这表明可以更准确地识别良性病例。应用统计模型，我们估计使用多重PCR模型可避免33%至47%的重复活检，这相对于目前尿液沉淀物检测的金标准而言，是一种易于应用且具有显著优势的方法。
在尿液沉淀物中使用基于多重逆转录定量PCR的模型有可能改进当前的诊断方法（PCA3），以区分良性HGPIN和前列腺癌病例。
