Detection of high-grade neoplasia in air-dried cervical PAP smears by a microRNA-based classifier.

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.

HMGA2 gene is a promising target for ovarian cancer silencing therapy.

Ovarian cancer is one of the most lethal gynecological malignancies and the small success rate of routine therapeutic methods justifies efforts to develop new approaches. Evaluation of targets for effective inhibition of ovarian cancer cell growth should precipitate clinical application of gene silencing therapy. In our previous work, we showed upregulation of HMGA2 gene expression as a result of Ras-induced rat ovarian surface epithelial cell transformation. This gene codes the HMGA2 protein, a member of the high-mobility group AT-hook (HMGA) family of nonhistone chromatin proteins. Genome-wide studies revealed upregulation of the HMGA2 gene in human ovarian carcinomas. Herein we have evaluated over-expression of the HMGA2 gene, relevant to ovarian cancer, in subsets of human specimens and cell lines by in situ RNA hybridization and RT-PCR. Transient silencing of HMGA2 gene by means of siRNA inhibited proliferation of those ovarian cancer cells, which over-express this gene initially. Growth suppression was mediated by cell-cycle arrest. Stable silencing of highly expressed HMGA2 gene by shRNAi in A27/80, Ovcar-3 and OAW-42 ovarian cancer cell lines resulted in growth inhibition because of G1 arrest and increase of apoptosis as well. The tumor growth inhibition effect of HMGA2 silencing for Ovcar-3 cells was validated in vivo. Our findings revealed that the HMGA2 gene represents a promising target for gene silencing therapy in ovarian cancer.