A Review of Mathematical Models for Tumor Dynamics and Treatment Resistance Evolution of Solid Tumors
Anyue Yin,Dirk Jan A.R. Moes,Johan G.C. van Hasselt,Jesse J. Swen,Henk-Jan Guchelaar +4 more
- Vol. 8, Iss: 10, pp 720-737
TLDR
The opportunities of a model‐based approach as discussed in this review can be of great benefit for future optimizing and personalizing anticancer treatment.Abstract:
Increasing knowledge of intertumor heterogeneity, intratumor heterogeneity, and cancer evolution has improved the understanding of anticancer treatment resistance. A better characterization of cancer evolution and subsequent use of this knowledge for personalized treatment would increase the chance to overcome cancer treatment resistance. Model-based approaches may help achieve this goal. In this review, we comprehensively summarized mathematical models of tumor dynamics for solid tumors and of drug resistance evolution. Models displayed by ordinary differential equations, algebraic equations, and partial differential equations for characterizing tumor burden dynamics are introduced and discussed. As for tumor resistance evolution, stochastic and deterministic models are introduced and discussed. The results may facilitate a novel model-based analysis on anticancer treatment response and the occurrence of resistance, which incorporates both tumor dynamics and resistance evolution. The opportunities of a model-based approach as discussed in this review can be of great benefit for future optimizing and personalizing anticancer treatment.read more
Citations
More filters
Book ChapterDOI
The Mathematical Model
TL;DR: The death rate per tumor cell due to immunological response is proportional to the total number of antigen-producing (tumor) cells; thus, the total death rate is quadratic.
Journal ArticleDOI
Cancer modeling: From mechanistic to data-driven approaches, and from fundamental insights to clinical applications
TL;DR: A non-exhaustive overview of models according to their intrinsic features of in silico cancer models is provided, using the hallmarks of cancer as a guidance.
Journal ArticleDOI
Optimal control of cytotoxic and antiangiogenic therapies on prostate cancer growth
Pierluigi Colli,Hector Gomez,Guillermo Lorenzo,Guillermo Lorenzo,Gabriela Marinoschi,Alessandro Reali,Elisabetta Rocca +6 more
TL;DR: The results suggest that only cytotoxic chemotherapy is required to optimize therapeutic performance and it is shown that the optimal control framework can produce superior solutions to combined therapy with docetaxel and bevacizumab.
Journal ArticleDOI
Tumor Growth Dynamic Modeling in Oncology Drug Development and Regulatory Approval: Past, Present, and Future Opportunities.
TL;DR: This review is to comprehensively summarize the history of TGD, and present case examples of the recent advance ofTGD modeling (mixture model and joint model), as well as the TGD impact on regulatory decisions, thus illustrating challenges and opportunities.
Journal ArticleDOI
Treatment-driven tumour heterogeneity and drug resistance: Lessons from solid tumours.
Stefania Crucitta,Federico Cucchiara,Ron H.J. Mathijssen,Joaquin Mateo,Agnes Jager,Arjen Joosse,Antonio Passaro,Ilaria Attili,Iacopo Petrini,Ron H.N. van Schaik,Romano Danesi,Marzia Del Re +11 more
TL;DR: In this paper , the authors focused on tumour heterogeneity and its relation to resistance to targeted-therapy, based on treatment selective pressure across different tumour types, including lung, colorectal, prostate, breast cancer and melanoma.
References
More filters
Journal ArticleDOI
A two-clones tumor model: Spontaneous growth and response to treatment.
TL;DR: The findings indicate that the eradication of the metastatic population is much more critical in the presence of mutations, either spontaneous or therapy-induced, and a treatment that eradicates only the primary tumor is ultimately not successful but promotes a "growth spurt" in the latter.
Journal ArticleDOI
Modeling and simulation of maintenance treatment in first-line non-small cell lung cancer with external validation.
TL;DR: The model successfully predicted the OS outcomes of an independent study based on interim TGI data and thus may facilitate trial simulation and interpretation of interim data, suggesting that TGI-OS models may be treatment-independent.
Book ChapterDOI
Mathematical Modeling of Cyclic Cancer Treatments
TL;DR: This work examines cyclic treatment regimes, which involve alternating applications of two (or more) different drugs, given one at a time, and shows that the best strategy is to start with the stronger drug, but use longer cycle durations for the weaker drug.