# MicroRNA-Based Triage of HPV-Positive Women Using Liquid-Based Cytology: Diagnostic Performance and Network-Level Insights

## TL;DR

This study explores using microRNAs in cervical screening to better identify women with advanced HPV-related lesions, improving diagnostic accuracy beyond current methods.

## Contribution

The study introduces miRNA regulatory network analysis as a novel approach to enhance triage accuracy in HPV-positive women.

## Key findings

- Certain miRNAs, like miR-16-5p and miR-155-5p, show high accuracy in distinguishing healthy from high-grade lesions.
- Network-level analysis reveals significant miRNA co-expression changes during disease progression, especially from CIN II to CIN III.
- Diagnostic performance of miRNAs is not solely dependent on expression levels but also on their regulatory roles in networks.

## Abstract

Current cervical cancer screening utilizes Pap smears and HPV DNA tests, which have high sensitivity but low specificity, as many of these infections are transient and leave no lesions in the cervix. This diagnostic approach has increased the number of tests and associated costs. Therefore, screening methods still require refinement to achieve greater diagnostic accuracy. In this study, we examined the utility of selected small, non-coding regulatory RNAs (miRNAs) as biomarkers to enhance the diagnostic accuracy of screening tests. Liquid-based cytology samples were used as the starting material for the analyses. We found that some miRNAs accurately distinguished women with advanced precancerous lesions or cancer from healthy women, while others reflected broader molecular instability associated with disease progression. Importantly, changes in miRNA interactions provided additional information beyond simple expression levels. These findings suggest that combining miRNA-based diagnostics with analysis at the miRNA regulatory network level may improve diagnosis and enable more precise disease risk stratification in screening.

Background: Human papillomavirus (HPV)-based screening has substantially improved sensitivity for cervical cancer detection but remains limited by low specificity, leading to unnecessary colposcopy referrals. MicroRNAs (miRNAs) represent promising biomarkers for improving triage of HPV-positive women. This study evaluated the diagnostic and regulatory roles of selected miRNAs in cervical lesion progression using liquid-based cytology (LBC) specimens. Methods: Expression of six biologically relevant miRNAs (miR-15a-5p, miR-16-5p, miR-20b-5p, miR-155-5p, miR-34a-5p, and miR-140-3p) was analyzed across NILM, CIN II, CIN III, and cervical cancer (CC) samples. All miRNA analyses were performed using residual cellular material derived from the same liquid-based cytology (LBC) specimens collected during the HPV screening visit, without requiring any additional sampling prior to colposcopy. Diagnostic performance was assessed using ROC analysis. To capture regulatory dynamics beyond expression magnitude, correlation, and differential correlation (Δρ), network analyses were applied. Results: Stage-dependent changes in miRNA expression were observed across disease categories; however, expression magnitude alone did not fully explain diagnostic performance. Upregulated miRNAs, particularly miR-16-5p, miR-20b-5p, and miR-155-5p, demonstrated high diagnostic accuracy for distinguishing NILM from high-grade lesions and invasive cancer. In contrast, downregulated miRNAs showed limited diagnostic utility. Correlation analyses revealed progressive remodeling of miRNA co-expression networks, with the most pronounced changes occurring during the CIN II–to–CIN III transition. Notably, miRNAs with strong diagnostic performance did not uniformly function as network hubs, indicating distinct roles as biomarkers versus regulators of network dynamics. Conclusions: Cervical lesion progression is characterized not only by changes in miRNA expression levels but also by stage-specific reorganization of miRNA regulatory networks. Integrating diagnostic performance with network-level analysis enables improved identification of clinically robust triage markers and provides additional insight into regulatory instability associated with progression.