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组织微小 RNA 用于 Barrett 食管非内镜诊断的选择和应用。

Selection and Application of Tissue microRNAs for Nonendoscopic Diagnosis of Barrett's Esophagus.

机构信息

MRC Cancer Unit, Hutchison-MRC Research Centre, University of Cambridge, Cambridge, UK.

Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Department of Health and Human Services, Rockville, Maryland.

出版信息

Gastroenterology. 2018 Sep;155(3):771-783.e3. doi: 10.1053/j.gastro.2018.05.050. Epub 2018 Jun 12.

Abstract

BACKGROUND & AIMS: MicroRNA (miRNA) is highly stable in biospecimens and provides tissue-specific profiles, making it a useful biomarker of carcinogenesis. We aimed to discover a set of miRNAs that could accurately discriminate Barrett's esophagus (BE) from normal esophageal tissue and to test its diagnostic accuracy when applied to samples collected by a noninvasive esophageal cell sampling device.

METHODS

We analyzed miRNA expression profiles of 2 independent sets of esophageal biopsy tissues collected during endoscopy from 38 patients with BE and 26 patients with normal esophagus (controls) using Agilent microarray and Nanostring nCounter assays. Consistently up-regulated miRNAs were quantified by real-time polymerase chain reaction in esophageal tissues collected by Cytosponge from patients with BE vs without BE. miRNAs were expressed from plasmids and antisense oligonucleotides were expressed in normal esophageal squamous cells; effects on proliferation and gene expression patterns were analyzed.

RESULTS

We identified 15 miRNAs that were significantly up-regulated in BE vs control tissues. Of these, 11 (MIR215, MIR194, MIR 192, MIR196a, MIR199b, MIR10a, MIR145, MIR181a, MIR30a, MIR7, and MIR199a) were validated in Cytosponge samples. The miRNAs with the greatest increases in BE tissues (7.9-fold increase in expression or more, P < .0001: MIR196a, MIR192, MIR194, and MIR215) each identified BE vs control tissues with area under the curve (AUC) values of 0.82 or more. We developed an optimized multivariable logistic regression model, based on expression levels of 6 miRNAs (MIR7, MIR30a, MIR181a, MIR192, MIR196a, and MIR199a), that identified patients with BE with an AUC value of 0.89, 86.2% sensitivity, and 91.6% specificity. Expression level of MIR192, MIR196a, MIR199a, combined that of trefoil factor 3, identified patients with BE with an AUC of 0.93, 93.1% sensitivity, and 93.7% specificity. Hypomethylation was observed in the promoter region of the highly up-regulated cluster MIR192-MIR194. Overexpression of these miRNAs in normal esophageal squamous cells increased their proliferation, via GRHL3 and PTEN signaling.

CONCLUSIONS

In analyses of miRNA expression patterns of BE vs non-BE tissues, we identified a profile that can identify Cytosponge samples from patients with BE with an AUC of 0.93. Expression of MIR194 is increased in BE samples via epigenetic mechanisms that might be involved in BE pathogenesis.

摘要

背景与目的

微小 RNA(miRNA)在生物标本中高度稳定,提供组织特异性谱,是致癌作用的有用生物标志物。我们旨在发现一组 miRNA,可准确区分 Barrett 食管(BE)与正常食管组织,并在应用于非侵入性食管细胞采样装置采集的样本时测试其诊断准确性。

方法

我们使用 Agilent 微阵列和 Nanostring nCounter 检测,分析了 38 例 BE 患者和 26 例正常食管(对照)患者内镜检查期间采集的 2 组食管活检组织的 miRNA 表达谱。使用 Cytosponge 从 BE 患者与无 BE 患者采集的食管组织中通过实时聚合酶链反应定量检测一致上调的 miRNA。miRNA 由质粒表达,反义寡核苷酸在正常食管鳞状细胞中表达;分析其对增殖和基因表达模式的影响。

结果

我们确定了 15 种在 BE 与对照组织中显著上调的 miRNA。其中 11 种(MIR215、MIR194、MIR192、MIR196a、MIR199b、MIR10a、MIR145、MIR181a、MIR30a、MIR7 和 MIR199a)在 Cytosponge 样本中得到验证。在 BE 组织中表达增加最大的 miRNA(表达增加 7.9 倍或更多,P<.0001:MIR196a、MIR192、MIR194 和 MIR215),每个 miRNA 均能以曲线下面积(AUC)值 0.82 或更高来识别 BE 与对照组织。我们基于 6 种 miRNA(MIR7、MIR30a、MIR181a、MIR192、MIR196a 和 MIR199a)的表达水平,开发了一种优化的多变量逻辑回归模型,该模型可识别出 BE 患者的 AUC 值为 0.89、86.2%的敏感性和 91.6%的特异性。MIR192、MIR196a、MIR199a、三叶因子 3 联合表达可识别出 AUC 为 0.93、93.1%敏感性和 93.7%特异性的 BE 患者。高度上调簇 MIR192-MIR194 的启动子区域观察到低甲基化。这些 miRNA 在正常食管鳞状细胞中的过度表达通过 GRHL3 和 PTEN 信号增加其增殖。

结论

在分析 BE 与非 BE 组织的 miRNA 表达模式时,我们确定了一种可以识别 Cytosponge 样本中 BE 患者的 AUC 为 0.93 的图谱。BE 样本中 MIR194 的表达增加是通过表观遗传机制介导的,该机制可能与 BE 的发病机制有关。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0119/6158680/18417e7f1946/fx1.jpg

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