A quantitative treatment assessment for optimizing combined virotherapy-chemotherapy regimens against HPV-induced cervical cancer
- 1School of Mathematics and Statistics, Beijing Technology and Business University, Beijing, P. R. China
- 2Department of Mathematics, Centre for Mathematical Biology and Ecology, Jadavpur University, Kolkata, West Bengal, India
- 3Department of Mathematics, K. L. S. College, Magadh University, Nawada, Bodh Gaya, Bihar, India
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.
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BibTeX
@article{ghosh2026quantitative,
title = {{A quantitative treatment assessment for optimizing combined virotherapy-chemotherapy regimens against HPV-induced cervical cancer}},
author = {Salil Ghosh and Amit Kumar Bag and Satyajit Mukherjee and Xianbing Cao and Amarnath Chatterjee and Priti Kumar Roy},
journal = {PLOS One},
year = {2026},
month = sep,
doi = {10.1371/journal.pone.0342672},
url = {https://doi.org/10.1371/journal.pone.0342672},
note = {CC BY 4.0},
}
RIS
TY - JOUR
TI - A quantitative treatment assessment for optimizing combined virotherapy-chemotherapy regimens against HPV-induced cervical cancer
AU - Salil Ghosh
AU - Amit Kumar Bag
AU - Satyajit Mukherjee
AU - Xianbing Cao
AU - Amarnath Chatterjee
AU - Priti Kumar Roy
PY - 2026
DA - 2026/09/21
JO - PLOS One
DO - 10.1371/journal.pone.0342672
UR - https://doi.org/10.1371/journal.pone.0342672
AB - 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.
SN - 1932-6203
ER -