AO Vector-Best, 630117 Novosibirsk, Russia.
N.N. Petrov Research Institute of Oncology, 197758 Saint Petersburg, Russia.
Oncol Rep. 2018 Mar;39(3):1099-1111. doi: 10.3892/or.2018.6214. Epub 2018 Jan 12.
Recent studies have shown that changes in the expression levels of certain microRNAs correlate with the degree of severity of cervical lesions. The aim of the present study was to develop a microRNA-based classifier for the detection of high-grade cervical intraepithelial neoplasia (CIN ≥2) in cytological samples from patients with different high-risk human papillomavirus (HR-HPV) viral loads. For this purpose, raw RT-qPCR data for 25 candidate microRNAs, U6 snRNA and human DNA in air-dried PAP smears from 174 women with different cervical cytological diagnoses, 144 of which were HR-HPV-positive [40 negative for intraepithelial lesion or malignancy (NILM), 34 low-grade squamous intraepithelial lesions (L-SIL), 57 high-grade squamous intraepithelial lesions (H-SIL), 43 invasive cancers], were statistically processed. The expression level changes of various individual microRNAs were found to be significantly correlated with the cytological diagnosis but the statistical significance of this correlation was critically dependent on the normalization strategy. We developed a linear classifier based on the paired ratios of 8 microRNA concentrations and cellular DNA content. The classifier determines the dimensionless coefficient (DF value), which increases with the severity of cervical lesion. The high- and low-grade CINs were better distinguished by the microRNA classifier than by the measurement of individual microRNA levels with the use of traditional normalization methods. The diagnostic sensitivity of detecting high-grade lesions (CIN ≥2) with the developed microRNA classifier was 83.4%, diagnostic specificity 81.2%, ROC AUC=0.913. The analysis can be performed with the same nucleic acid preparation as used for HPV testing. No statistically significant correlation of the DF value and HR-HPV DNA load was found. The DF value and the HR HPV presence and viral DNA load may be regarded as independent criteria that can complement each other in molecular screening for high-grade cervical intraepithelial neoplasia. Although it has several limitations, the present study showed that the small-scale analysis of microRNA signatures performed by simple PCR-based methods may be useful for improving the diagnostic/prognostic value of cervical screening.
最近的研究表明,某些 microRNA 表达水平的变化与宫颈病变的严重程度相关。本研究旨在开发一种基于 microRNA 的分类器,用于检测不同高危型人乳头瘤病毒(HR-HPV)病毒载量的细胞学样本中高级别宫颈上皮内瘤变(CIN≥2)。为此,对来自 174 名具有不同宫颈细胞学诊断的女性的空气干燥 PAP 涂片的 25 个候选 microRNA、U6 snRNA 和人 DNA 的原始 RT-qPCR 数据进行了统计处理,其中 144 例为 HR-HPV 阳性[40 例为上皮内病变或恶性肿瘤(NILM)阴性,34 例为低级别鳞状上皮内病变(L-SIL),57 例为高级别鳞状上皮内病变(H-SIL),43 例为浸润性癌]。结果发现,各种单个 microRNA 的表达水平变化与细胞学诊断显著相关,但这种相关性的统计学意义严重依赖于归一化策略。我们基于 8 个 microRNA 浓度和细胞 DNA 含量的配对比开发了一个线性分类器。该分类器确定无量纲系数(DF 值),该系数随宫颈病变的严重程度而增加。与使用传统归一化方法测量单个 microRNA 水平相比,microRNA 分类器可以更好地区分高低级别 CIN。开发的 microRNA 分类器检测高级别病变(CIN≥2)的诊断灵敏度为 83.4%,诊断特异性为 81.2%,ROC AUC=0.913。该分析可以使用与 HPV 检测相同的核酸制备进行。未发现 DF 值与 HR-HPV DNA 载量之间存在统计学显著相关性。DF 值和 HR-HPV 存在及其病毒 DNA 载量可被视为独立标准,可在高级别宫颈上皮内瘤变的分子筛查中相互补充。虽然存在一些局限性,但本研究表明,通过简单的基于 PCR 的方法进行 microRNA 特征的小规模分析可能有助于提高宫颈筛查的诊断/预后价值。