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Open AccessJournal ArticleDOI

A Review of Mathematical Models for Tumor Dynamics and Treatment Resistance Evolution of Solid Tumors

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.

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Posted ContentDOI

Borrowing ecological theory to infer interactions between sensitive and resistant breast cancer cell populations

TL;DR: It is suggested that ecological dynamics change in the presence of therapy, and that an adaptive treatment protocol can induce cycling behavior suggesting that heterogeneous ecological effects contribute to empirically observed adaptive-therapeutic dynamics.
Journal ArticleDOI

Current State of Adjuvant Therapy for Melanoma: Less Is More, or More Is Better?

TL;DR: The lack of overall survival benefit in clinical trials of patients with high-risk stage II and stage III disease raises the question of whether it is more efficacious to treat when there is residual microscopic disease, or to wait until the disease recurs.
Journal ArticleDOI

Geometric analysis enables biological insight from complex non-identifiable models using simple surrogates

TL;DR: In this article , the authors study the geometry of a map in parameter space from a complex model to a simple, identifiable, surrogate model, by studying how non-identifiable parameters in the complex model quantitatively relate to identifiable parameters in surrogate.
Posted Content

Optimal control of cytotoxic and antiangiogenic therapies on prostate cancer growth

TL;DR: In this paper, an optimal control framework is proposed to robustly compute the drug-independent cytotoxic and anti-angiogenic effects enabling an optimal therapeutic control of tumor dynamics, and numerical algorithms based on isogeometric analysis are presented to run a preliminary simulation study over a single cycle of combined therapy.
References
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BookDOI

The Case Study

TL;DR: On May 25, 1977, IEEE member, Virginia Edgerton, a senior information scientist employed by the City of New York, telephoned the chairman of CSIT's Working Group on Ethics and Employment Practices, having been referred to the committee by IEEE Headquarters.
Journal ArticleDOI

Liquid biopsies come of age: towards implementation of circulating tumour DNA

TL;DR: The field is now in an exciting transitional period in which ctDNA analysis is beginning to be applied clinically, although there is still much to learn about the biology of cell-free DNA.
Journal ArticleDOI

Chemoresistance Evolution in Triple-Negative Breast Cancer Delineated by Single-Cell Sequencing

TL;DR: The data showed that resistant genotypes were pre-existing and adaptively selected by NAC, while transcriptional profiles were acquired by reprogramming in response to chemotherapy in TNBC patients.
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.
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