A quantitative treatment assessment for optimizing combined virotherapy-chemotherapy regimens against HPV-induced cervical cancer

Cervical cancer is strongly associated with persistent infection by high-risk human papillomavirus (HPV) and continues to pose a major global health burden in recent times. Oncolytic virotherapy has emerged as a promising targeted strategy that selectively eliminates cancer cells while simultaneously activating host immune responses. In this study, a deterministic mathematical model is developed to investigate the dynamics of HPV-induced cervical cancer under oncolytic virotherapy, both as a standalone intervention and in combination with chemotherapy. The model captures the interactions among HPV-infected epithelial cells, cancer cells, oncolytic virus–infected cancer cells, free viral particles, and virus-specific cytotoxic T-lymphocytes. Fundamental qualitative properties of the system are established, and threshold conditions governing oncolytic virus persistence are identified. To elucidate the relative influence of biological and therapeutic parameters, a comprehensive global sensitivity analysis is performed using the extended Fourier amplitude sensitivity test (eFAST) and partial rank correlation coefficients. This analysis reveals key mechanisms regulating cancer cell dynamics and highlights parameters that critically shape treatment outcomes. An optimal control framework is further employed to assess time-dependent therapeutic strategies, providing insight into effective scheduling of virotherapy and chemotherapy while balancing treatment cost. Furthermore, numerical simulation-based evidences justify the analytical findings obtained in the study and demonstrate the comparative advantages of the combined strategy.

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Publication Details

Journal
PLoS ONE
Published
2026-09-21
DOI
https://doi.org/10.1371/journal.pone.0342672
Primary Topic
Virus-based gene therapy research
Type
article
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article

A quantitative treatment assessment for optimizing combined virotherapy-chemotherapy regimens against HPV-induced cervical cancer

Xianbing Cao, Salil K Ghosh, Amar Nath Chatterjee, Priti Kumar Roy et al.
PLoS ONE
Virus-based gene therapy research
article

A quantitative treatment assessment for optimizing combined virotherapy-chemotherapy regimens against HPV-induced cervical cancer

Xianbing Cao, Salil K Ghosh, Amar Nath Chatterjee, Priti Kumar Roy, Satyajit Mukherjee, Amit Kumar Bag
article en

Abstract

Cervical cancer is strongly associated with persistent infection by high-risk human papillomavirus (HPV) and continues to pose a major global health burden in recent times. Oncolytic virotherapy has emerged as a promising targeted strategy that selectively eliminates cancer cells while simultaneously activating host immune responses. In this study, a deterministic mathematical model is developed to investigate the dynamics of HPV-induced cervical cancer under oncolytic virotherapy, both as a standalone intervention and in combination with chemotherapy. The model captures the interactions among HPV-infected epithelial cells, cancer cells, oncolytic virus–infected cancer cells, free viral particles, and virus-specific cytotoxic T-lymphocytes. Fundamental qualitative properties of the system are established, and threshold conditions governing oncolytic virus persistence are identified. To elucidate the relative influence of biological and therapeutic parameters, a comprehensive global sensitivity analysis is performed using the extended Fourier amplitude sensitivity test (eFAST) and partial rank correlation coefficients. This analysis reveals key mechanisms regulating cancer cell dynamics and highlights parameters that critically shape treatment outcomes. An optimal control framework is further employed to assess time-dependent therapeutic strategies, providing insight into effective scheduling of virotherapy and chemotherapy while balancing treatment cost. Furthermore, numerical simulation-based evidences justify the analytical findings obtained in the study and demonstrate the comparative advantages of the combined strategy.

PLoS ONEVol. 21(9)
Magadh University (IN), Jadavpur University (IN), Beijing Technology and Business University (CN)
Good health and well-being
Openalex Percentile: Top 12%
Virus-based gene therapy research
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