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For several decades, researchers have sought to identify biomarkers capable of accurately predicting the outcome of an infection with a high-risk oncogenic HPV type. Despite significant advances, no viral, immune-related or molecular marker can currently and reliably predict which infections will regress spontaneously and which will progress to more severe disease.

This difficulty stems from the complex and dynamic nature of HPV-associated carcinogenesis (the biological process by which a healthy cell becomes a cancer cell). The outcome of an infection is shaped by numerous factors, including viral characteristics, the host immune response, genetic and epigenetic factors, the microbiome, hormonal influences and environmental exposures. These interactions are further complicated by random biological events, including the accumulation of mutations associated with virus-induced genomic instability.

"The main challenge may no longer be to discover a new biomarker, but rather to understand how all these biological mechanisms interact to determine the outcome of an HPV infection," explains Michael Herfs, an oncologist at GIGA (University of Liège).

The paper is published in the journal Trends in Molecular Medicine.

Faced with this complexity, Diane Bruyère, Romane Geuzaine and Herfs believe that approaches based on a single biomarker have probably reached their limits. Recent advances in high-throughput molecular profiling and artificial intelligence are now opening up new perspectives.

These technologies make it possible to integrate large amounts of biological data simultaneously to build more comprehensive predictive models.

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