Plasma microRNA profiles for bladder cancer detection.
Plasma microRNA profiles for bladder cancer detection.
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DOI：
10.1016/j.urolonc.2012.06.010
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发表时间：
2013-11
期刊：
影响因子：
--
通讯作者：
Dinney CP
中科院分区：
文献类型：
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作者：
Adam L;Wszolek MF;Liu CG;Jing W;Diao L;Zien A;Zhang JD;Jackson D;Dinney CP
膀胱癌（BC）是一种负担沉重的疾病，具有显著的发病率、死亡率和成本。开发新的基于血浆的BC诊断和监测生物标志物可以显著改善临床结果并减少卫生支出。血浆mirna是一种有前景的生物标志物，尚未在BC中进行严格的研究。目的：探讨血浆miRNA信号检测BC的可行性和有效性。从20例膀胱癌患者和18例非癌对照中分离出血浆miRNA。样本用包含Sanger数据库中每个miRNA的重复探针的miRNA阵列进行分析。采用Logistic回归模型优化诊断性miRNA特征，以区分肌肉浸润性BC （MIBC）、非肌肉浸润性BC （NMIBC）和非癌对照。在有或没有BC的患者中鉴定出79种差异表达的血浆mirna（局部错误发现率[FDR] <0.5）。一些诊断相关的mirna，如miR-200b，在MIBC患者中上调，而其他mirna，如miR-92和miR-33，与晚期临床阶段呈负相关，这支持了在循环中释放的mirna具有多种细胞起源的观点。逻辑回归模型能够预测诊断，检测BC存在与否的准确率为89%，区分浸润性BC与其他病例的准确率为92%，区分MIBC与对照组的准确率为100%，区分MIBC、NIMBC和对照组的三种分类准确率为79%。该研究提供了初步数据，支持使用血浆mirna作为BC检测的非侵入性手段。未来的研究将需要进一步明确最佳的血浆miRNA特征，并将这些特征应用于临床场景，如初始BC检测和BC监测。
Bladder cancer (BC) is a burdensome disease with significant morbidity, mortality, and cost. The development of novel plasma-based biomarkers for BC diagnosis and surveillance could significantly improve clinical outcomes and decrease health expenditures. Plasma miRNAs are promising biomarkers that have yet to be rigorously investigated in BC. To determine the feasibility and efficacy of detecting BC with plasma miRNA signatures. Plasma miRNA was isolated from 20 patients with bladder cancer and 18 noncancerous controls. Samples were analyzed with a miRNA array containing duplicate probes for each miRNA in the Sanger database. Logistic regression modeling was used to optimize diagnostic miRNA signatures to distinguish between muscle invasive BC (MIBC), non-muscle-invasive BC (NMIBC) and noncancerous controls. Seventy-nine differentially expressed plasma miRNAs (local false discovery rate [FDR] <0.5) in patients with or without BC were identified. Some diagnostically relevant miRNAs, such as miR-200b, were up-regulated in MIBC patients, whereas others, such as miR-92 and miR-33, were inversely correlated with advanced clinical stage, supporting the notion that miRNAs released in the circulation have a variety of cellular origins. Logistic regression modeling was able to predict diagnosis with 89% accuracy for detecting the presence or absence of BC, 92% accuracy for distinguishing invasive BC from other cases, 100% accuracy for distinguishing MIBC from controls, and 79% accuracy for three-way classification between MIBC, NIMBC, and controls. This study provides preliminary data supporting the use of plasma miRNAs as a noninvasive means of BC detection. Future studies will be required to further specify the optimal plasma miRNA signature, and to apply these signatures to clinical scenarios, such as initial BC detection and BC surveillance.