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News • Experimental pathology
Predicting which HPV infections will progress to cancer: are we there yet?
Infection with the human papillomavirus (HPV) is extremely common and, in the vast majority of cases, clears up on its own. However, in some people, the infection persists and can develop into precancerous lesions or even cancer.
How can these high-risk situations be identified at an early stage? This is the central question of a study conducted by Michael Herfs’s team at the Interdisciplinary Biomedical Research Center GIGA’s Laboratory of Experimental Pathology at the University of Liège, published in Trends in Molecular Medicine.
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.
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
Michael Herfs
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, oncologist at GIGA (University of Liège).
Faced with this complexity, Diane Bruyère, Romane Geuzaine, and Michael 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. The objective is to better distinguish between the possible trajectories of an HPV infection or a low-grade precancerous lesion: spontaneous regression, persistence, or progression to a more severe lesion, including invasive cancer. These integrative approaches are currently considered among the most promising avenues for improving risk stratification. "Artificial intelligence and integrative models could help us better understand the diversity of biological trajectories observed among patients and, ultimately, provide a more personalized assessment of risk," says Diane Bruyère.
Although these new models generate considerable hope, they have not yet been sufficiently validated for routine clinical use. Today, patient management still relies on HPV testing, cytology, and histopathological assessment, combined with relatively non-individualized follow-up.
According to the researchers, the future lies in developing a broader understanding of the biology of HPV infections rather than in the search for a single predictive marker. Ultimately, more accurate individual risk assessment could make it possible to tailor patient follow-up, reduce unnecessary interventions, and improve the management of people with HPV infections.
Source: University of Liège
17.10.2026
