Shotgun Lipidomics for Differential Diagnosis of HPV-Associated Cervix Transformation

A Glimmer of Hope for Patients with a T3 Transformation Zone: miRNAs Are Potential Biomarkers for Cervical Dysplasia

BACKGROUND

This pilot study assesses the potential use of miRNAs in the triage of colposcopy patients with type 3 (nonvisible) cervical transformation zone (TZ). Type 3 TZ is a constitutional finding associated with many problems and controversies in colposcopy patient management. Here, we present miRNAs as a potential biomarker for the detection of CIN3 in these cases.

MATERIALS AND METHODS

Cervical mucosa samples (CMS) were collected from patients presenting with T3 transformation zone during routine workup using the Cytobrush. Depending on the histological and cytological result, as well as the result of the routinely performed HPV PCR, patients were divided into three groups: patients with a high-grade intraepithelial lesion (CIN3) and a positive high-risk HPV test (CIN3 group), patients without an intraepithelial lesion and a positive high-risk HPV test (HPV group), and healthy controls (N = no intraepithelial lesion and negative HPV test). The cervical mucus samples included in the study were tested for their expression levels of distinct miRNAs using qPCR.

RESULTS

All investigated miRNAs were consistently detectable in every sample. The CMSs of histologically graded CIN 3 showed consistently high expression levels of all eight miRNAs, whereas the CMSs from healthy patients (N) show generally lower expression levels. However, CMSs from patients of the HPV group represented a very heterogeneous group.

CONCLUSIONS

The data presented here can provide a solid basis for future research into a triage test for patients with a T3 transformation zone on the basis of commonly used clinical equipment.

Non-Invasive Differential Diagnosis of Cervical Neoplastic Lesions by the Lipid Profile Analysis of Cervical Scrapings

Cervical cancer is one of the most common cancers in women with pronounced stages of precancerous lesions. Accurate differential diagnosis of such lesions is one of the primary challenges of medical specialists, which is vital to improving patient survival. The aim of this study was to develop and test an algorithm for the differential diagnosis of cervical lesions based on lipid levels in scrapings from the cervical epithelium and cervicovaginal canal. The lipid composition of the samples was analyzed by high-performance chromato-mass spectrometry. Lipid markers were selected using the Mann–Whitney test with a cutoff value of 0.05 and by projections to latent structures discriminant analysis, where a projection threshold of one was chosen. The final selection of variables for binomial logistic regressions was carried out using the Akaike information criterion. As a result, a final neoplasia classification method, based on 20 logistic regression sub-models, has an accuracy of 79% for discrimination NILM/cervicitis/LSIL/HSIL/cancer. The model has a sensitivity of 83% and a specificity of 88% for discrimination of several lesions (HSIL and cancer). This allows us to discuss the prospective viability of further validation of the developed non-invasive method of differential diagnosis.