Cervicovaginal-Microbiome Analysis by 16S Sequencing and Real-Time PCR in Patients from Novosibirsk (Russia) with Cervical Lesions and Several Years after Cancer Treatment.

Disturbed cervicovaginal-microbiome (CVM) structure promotes human papillomavirus (HPV) persistence and reflects risks of cervical lesions and cancer onset and recurrence. Therefore, microbiomic biomarkers may be useful for cervical disease screening and patient management. Here, by 16S rRNA gene sequencing and commercial PCR-based diagnostic kits, we profiled CVM in cytological preparations from 140 HPV-tested women (from Novosibirsk, Russia) with normal cytological findings, cervical lesions, or cancer and from 101 women who had recently received different cancer therapies. An increase in lesion severity was accompanied by higher HPV prevalence and elevated CVM biodiversity. Post-treatment CVM was found to be enriched with well-known microbial biomarkers of dysbiosis, just as in cervical disease. Nonetheless, concentrations of some skin-borne and environmental species (which gradually increased with increasing lesion severity)-especially Cutibacterium spp., Achromobacter spp., and Ralstonia pickettii-was low in post-treatment patients and depended on treatment types. Frequency of Lactobacillus iners dominance was high in all groups and depended on treatment types in post-treatment patients. Microbiome analysis via PCR-based kits revealed statistically significant differences among all groups of patients. Thus, microbiome profiling may help to find diagnostic and prognostic markers for management of cervical lesions; quantitative PCR-based kits may be suitable for these purposes.

Detection of Cervical Lesions and Cancer in Air-Dried Cytologic Smears by Combined Analysis of mRNA and miRNA Expression Levels.

Cervical cancer screening is based on cytologic analysis and high-risk human papillomavirus (HR-HPV) testing, each having their drawbacks. Implementation of new biomarker-based methods may improve screening accuracy. Here, the levels of 25 microRNAs (miRNAs, miRs) and 12 mRNAs involved in cervical carcinogenesis in 327 air-dried Papanicolaou-stained cervical smears from patients with cervical precancerous lesions, cancer, or without the disease were estimated by real-time PCR. Using logistic regression analysis, small-scale miRNA-based, mRNA-based, and combined molecular classifiers were built based on paired ratios of miRNA or mRNA concentrations; their ability to detect high-grade cervical lesions and cancer was then compared. Combined mRNA-miRNA classifiers manifested a better combination of sensitivity and specificity than miRNA- and mRNA-based classifiers. The best classifier, combining miR-375, miR-20, miR-96, CDKN2A, TSP4, and ECM1, predicted high-grade lesions with diagnostic sensitivity of 89.0%, specificity of 84.2%, and a receiver-operating characteristic area under the curve of 0.913. Additionally, in a subsample of the same specimens, the levels of MIR124-2 and MAL promoter methylation, HR-HPV genotypes, and viral loads were analyzed. The relative high-grade lesion risk estimated by the classifier correlated with the frequency of MAL and MIR124-2 methylation but not with the HR-HPV genotype or viral load. The results support the feasibility of cellular biomarker-based methods for cervical screening and patient management.

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.