Department of Laboratory Medicine, Keenan Research Centre in the Li Ka Shing Knowledge Institute St. Michael's Hospital, Toronto, Canada;
Clin Chem. 2013 Nov;59(11):1595-603. doi: 10.1373/clinchem.2013.205450. Epub 2013 Aug 19.
Prostate-specific antigen testing has led to overtreatment of prostate cancer (PCa). Only a small subset of PCa patients will have an aggressive disease that requires intensive therapy, and there is currently no biomarker to predict disease aggressiveness at the time of surgery. MicroRNAs (miRNAs) are reported to be involved in PCa pathogenesis.
This study involved 105 participants. For the discovery phase, prostatectomy samples were dichotomized to high-risk (n = 27, biochemical failure <36 months after prostatectomy) and low-risk groups (n = 14, ≥ 36 months without biochemical failure). Expression of 754 mature miRNAs was compared between the 2 groups. Linear regression models were built to accurately predict biochemical failure risk. miRNA mimics were transfected into PCa model cell lines to test effects on proliferation and to deduce responding signaling pathways.
We identified 25 differentially expressed miRNAs between the biochemical failure risk groups. Based on the expression of 2-3 miRNAs, 3 logistic regression models were developed, each with a high positive predictive value. Candidate miRNAs and the best-performing model were also verified on an independent PCa set. miRNA-152, featured in the models, was further investigated by using cell line models and was shown to affect cell proliferation. Predicted interaction between miR-152 and (mRNA)ERBB3 (erythroblastic leukemia viral oncogene homolog 3) was experimentally validated in vitro.
miRNAs can help to predict biochemical failure risk at the time of prostatectomy.
前列腺特异性抗原检测导致了前列腺癌（PCa）的过度治疗。只有一小部分 PCa 患者会患有需要强化治疗的侵袭性疾病，目前尚无生物标志物可在手术时预测疾病侵袭性。MicroRNAs（miRNAs）据报道参与了 PCa 的发病机制。
本研究涉及 105 名参与者。在发现阶段，将前列腺切除术样本分为高危组（n=27，前列腺切除术后生化失败<36 个月）和低危组（n=14，生化失败≥36 个月）。比较两组之间 754 个成熟 miRNA 的表达。建立线性回归模型以准确预测生化失败风险。将 miRNA 模拟物转染到 PCa 模型细胞系中，以测试对增殖的影响，并推断出相应的信号通路。
我们在生化失败风险组之间鉴定出 25 个差异表达的 miRNA。基于 2-3 个 miRNA 的表达，建立了 3 个逻辑回归模型，每个模型的阳性预测值都很高。候选 miRNA 和表现最佳的模型也在独立的 PCa 组中得到了验证。模型中特征的 miRNA-152 进一步通过使用细胞系模型进行了研究，结果表明其影响细胞增殖。体外实验验证了 miR-152 和（mRNA）ERBB3（红细胞生成性白血病病毒癌基因同源物 3）之间预测的相互作用。
miRNAs 可帮助预测前列腺切除术时的生化失败风险。
