# Non-invasive host transcriptome and HPV oncogene expression map the molecular landscape of HPV-driven cervical lesions

## TL;DR

This study uses transcriptomic profiling to identify molecular changes in cervical lesions caused by HPV, offering new biomarkers for better risk assessment and treatment.

## Contribution

The study introduces stage-specific transcriptomic signatures and integrates HPV oncogene expression to improve cervical cancer screening.

## Key findings

- NILM showed upregulated growth signaling and immune suppression, indicating stealth infection.
- HSIL was marked by cell cycle hyperactivation and epithelial dedifferentiation, showing molecular discontinuity from earlier stages.
- Higher E6/E7 mRNA levels correlated with more severe lesions, suggesting their use as biomarkers.

## Abstract

Cervical cancer remains a significant global health burden. Current screening methods are not yet capable of detecting molecular alterations preceding cytological abnormalities. In this study, we performed integrative transcriptomic profiling of 132 HPV-positive cervical Pap Smear specimens (NILM, ASCUS, LSIL, HSIL), combining HPV genotyping, and E6/E7 mRNA quantification to map molecular progression. Our analysis revealed stage-specific signatures: NILM displayed a “stealth infection” profile marked by upregulated protein synthesis and growth signaling (EGFR/ERBB2) alongside immune suppression. ASCUS presented a critical tipping point with introduction of early oncogenic drivers (CCND1, SHH), while LSIL prioritized viral productivity with suppressed antimicrobial defenses (MPO, DEFA1). HSIL was distinct from earlier stages and defined by cell cycle hyperactivation (CDK1, PLK1), replication licensing (MCMs), and epithelial dedifferentiation. Pathway crosstalk analysis demonstrated minimal overlap between HSIL and earlier stages (OC < 0.07), highlighting molecular discontinuity during malignant transformation. Additionally, E6/E7 mRNA Ct levels were significantly associated with lesion severity (X2 = 24.407, df = 9, p = 0.003), indicating higher viral mRNA expression are associated with more severe cytological abnormalities. These findings highlight the transformative potential of transcriptomic profiling in cervical cancer prevention, offering stage-specific biomarkers to refine risk stratification. By integrating transcriptomics profiling with current clinical testing, clinicians can distinguish transient infections from high-risks lesions likely to progress. This combined approach addresses the critical limitations of morphology and DNA-based methods, enabling more precise therapeutic interventions and reducing unnecessary overtreatment, and the risk of undertreatment or dismissal of high-risk cases.