Optimizing chemoradiotherapy to target multi-site metastatic disease and tumor growth

TL;DR

This paper develops a mathematical model to optimize chemoradiotherapy schedules, aiming to minimize metastatic cancer cells across multiple sites while preserving primary tumor control, revealing insights into optimal fractionation strategies.

Contribution

It introduces a novel mathematical framework for optimizing combined chemoradiotherapy protocols with explicit consideration of metastatic disease control.

Findings

Hypo-fractionated radiotherapy schedules are optimal regardless of radiosensitivity.

Chemotherapy schedules depend on parameters like cell-kill effectiveness and metastasis initiation.

Immediate radiotherapy initiation is optimal across scenarios.

Abstract

The majority of cancer-related fatalities are due to metastatic disease. In chemoradiotherapy, chemotherapeutic agents are administered along with radiation to increase damage to the primary tumor and control systemic disease such as metastasis. This work introduces a mathematical model to obtain optimal drug and radiation protocols in a chemoradiotherapy scheduling problem with the objective of minimizing metastatic cancer cell populations at multiple potential sites while maintaining a minimum level of damage to the primary tumor site. We derive closed-form expressions for an optimal chemotherapy fractionation regimen. A dynamic programming framework is used to determine the optimal radiotherapy fractionation regimen. Results show that chemotherapeutic agents do not change the optimal radiation fractionation regimens, and vice-versa. Interestingly, we observe that regardless of radio-sensitivity parameters, hypo-fractionated schedules are optimal solutions for the radiotherapy fractionation problem. Furthermore, it is optimal to immediately start radiotherapy. However, for chemotherapy, we find that the structure of the optimal schedule depends on model parameters such as chemotherapy-induced cell-kill at primary and metastatic sites, as well as the ability of primary tumor cells to initiate successful metastasis at different body sites. We quantify the trade-off between the new and traditional objectives of minimizing the metastatic population size and maximizing the tumor control probability, respectively, for a cervical cancer case. The trade-off information indicates the potential for significant reduction in the metastatic population with minimal loss in primary tumor control.