scholarly journals Optimizing chemo-scheduling based on tumor growth rates

2018 ◽  
Author(s):  
Jeffrey West ◽  
Paul Newton
Keyword(s):  
Tumor Growth ◽  
Low Dose ◽  
Cell Kinetics ◽  
Evolutionary Game ◽  
Maximum Tolerated Dose ◽  
General Concept ◽  
Theory Model ◽  
Moran Process ◽  
Evolutionary Features ◽  
Gompertzian Growth

AbstractWe review the classic tumor growth and regression laws of Skipper and Schable based on fixed exponential growth assumptions, and Norton and Simon’s law based on a Gompertzian growth assumption. We then discuss ways to optimize chemotherapeutic scheduling using a Moran process evolutionary game-theory model of tumor growth that incorporates more general dynamical and evolutionary features of tumor cell kinetics. Using this model, and employing the quantitative notion of Shannon entropy which assigns high values to low-dose metronomic (LDM) therapies, and low values to maximum tolerated dose (MTD) therapies, we show that low-dose metronomic strategies can outperform maximum tolerated dose strategies, particularly for faster growing tumors. The general concept of designing different chemotherapeutic strategies for tumors with different growth characteristics is discussed.

scholarly journals On the design of treatment schedules that avoid chemotherapeutic resistance

2018 ◽  
Author(s):  
Y. Ma ◽  
P.K. Newton
Keyword(s):  
Cell Population ◽  
Evolutionary Game ◽  
Maximum Tolerated Dose ◽  
Payoff Matrix ◽  
Theory Model ◽  
Release Mechanism ◽  
Trajectory Design ◽  
Chemotherapeutic Resistance ◽  
Competitive Release ◽  
Resistant Cells

We introduce a method of designing treatment schedules for a model three-component replicator dynamical system that avoids chemotherapeutic resistance by controlling and managing the competitive release of resistant cells in the tumor. We use an evolutionary game theory model with prisoner’s dilemma payoff matrix that governs the competition among healthy cells, chemo-sensitive cells, and chemo-resistant cells and the goal is to control the evolution of chemo-resistance via the competitive release mechanism. The method is based on nonlinear trajectory design and energy transfer methods first introduced in the orbital mechanics literature for Hamiltonian systems. By using the structure of the trajectories defined by solutions of the replicator system for different constant chemotherapeutic concentrations (which produces a curvilinear coordinate system spanning the full region), we construct periodic (closed) orbits by switching the chemo-dose at carefully chosen times and appropriate levels to design schedules that are superior to both maximum tolerated dose (MTD) schedules and low-dose metronomic (LDM) schedules, both of which ultimately lead to fixation of either sensitive cells or resistant cells. By keeping the three sub-populations of cells in competition with each other, neither the sensitive cell population nor the resitant cell population are able to dominate as we balance the populations indefinitely (closed periodic orbits), thereby avoiding fixation of the cancer cell population and re-growth of a resistant tumor. The schedules we design have the feature that they maintain a higher average population fitness than either the MTD or the LDM schedules.PACS numbers: 87.23.Kg; 87.55.de; 87.19.Xj; 87.19.lr

scholarly journals Chemotherapeutic dose scheduling based on tumor growth rates: the case for low dose metronomic high entropy therapies

2017 ◽  
Author(s):  
Jeffrey West ◽  
Paul K. Newton
Keyword(s):  
Tumor Growth ◽  
Tumor Cell ◽  
Growth Rates ◽  
Process Model ◽  
Low Dose ◽  
Maximum Tolerated Dose ◽  
High Density ◽  
High Dose ◽  
Single Cycle ◽  
Chemotherapy Drugs

AbstractWe extend classical tumor regression models, such as the Norton-Simon hypothesis, from instantaneous regression rates (i.e. the derivative) to the cumulative effect (i.e. the integral) over one (or many) cycles of chemotherapy. To achieve this end, we use a stochastic Moran process model of tumor cell kinetics, coupled with a prisoner’s dilemma game-theoretic cell-cell interaction model to design chemotherapeutic strategies tailored to different tumor growth characteristics. Using the Shannon entropy as a novel tool to quantify the success of dosing strategies, we contrast maximum tolerated dose (MTD) strategies as compared with low dose, high density metronomic strategies (LDM) for tumors with different growth rates. Our results show that LDM strategies can outperform MTD strategies in total tumor cell reduction (TCR). The advantage is magnified for fast growing tumors that thrive on long periods of unhindered growth without chemotherapy drugs present and is not evident after a single cycle of chemotherapy, but grows after each subsequent cycle of repeated chemotherapy. The model supports the concept of designing different chemotherapeutic schedules for tumors with different growth rates and develops quantitative tools to optimize these schedules for maintaining low volume tumors. The evolutionary model we introduce in this paper is compared with regression data from murine models and shown to be in good agreement.Major FindingsModel simulations show that metronomic (low dose, high density) therapies can outperform maximum tolerated dose (high dose, low density) therapies. This is due to the fact that tumor cell reduction is more sensitive to changes in dose density than changes in dose concentration, especially for faster growing tumors. This effect is negligible after a single cycle of chemotherapy, but magnified after many cycles. The model also allows for novel chemotherapeutic schedules and quantifies their performance according to tumor growth rate.

scholarly journals Low-Dose Histone Deacetylase Inhibitor Treatment Leads to Tumor Growth Arrest and Multi-Lineage Differentiation of Malignant Rhabdoid Tumors

2016 ◽  
Vol 22 (14) ◽  
pp. 3560-3570 ◽  
Author(s):  
Andrea Muscat ◽  
Dean Popovski ◽  
W. Samantha N. Jayasekara ◽  
Fernando J. Rossello ◽  
Melissa Ferguson ◽  
...  
Keyword(s):  
Tumor Growth ◽  
Histone Deacetylase ◽  
Histone Deacetylase Inhibitor ◽  
Low Dose ◽  
Growth Arrest ◽  
Lineage Differentiation ◽  
Deacetylase Inhibitor ◽  
Rhabdoid Tumors ◽  
Inhibitor Treatment

Macrophages and Tumor Growth. II. Cell Kinetics at the Site of Allogeneic Tumor Growth

1985 ◽  
Vol 3 (1) ◽  
pp. 7-13 ◽  
Author(s):  
Clydes N. Barrera ◽  
Alicia B. Mazzolli ◽  
Oscar D. Bustuoabad ◽  
Maria Andreetta ◽  
Christiane Dosne Pasqualini
Keyword(s):  
Tumor Growth ◽  
Cell Kinetics ◽  
Allogeneic Tumor

Low-dose curcumin leads to the inhibition of tumor growth via enhancing CTL-mediated antitumor immunity

2011 ◽  
Vol 11 (9) ◽  
pp. 1234-1240 ◽  
Author(s):  
Feifei Luo ◽  
Xiao Song ◽  
Yi Zhang ◽  
Yiwei Chu
Keyword(s):  
Tumor Growth ◽  
Antitumor Immunity ◽  
Low Dose ◽  
Inhibition Of Tumor Growth

scholarly journals A Comparative Analysis of Low-Dose Metronomic Cyclophosphamide Reveals Absent or Low-Grade Toxicity on Tissues Highly Sensitive to the Toxic Effects of Maximum Tolerated Dose Regimens

2004 ◽  
Vol 64 (11) ◽  
pp. 3994-4000 ◽  
Author(s):  
Urban Emmenegger ◽  
Shan Man ◽  
Yuval Shaked ◽  
Giulio Francia ◽  
John W. Wong ◽  
...  
Keyword(s):  
Comparative Analysis ◽  
Low Dose ◽  
Maximum Tolerated Dose ◽  
Toxic Effects ◽  
Low Grade ◽  
Highly Sensitive ◽  
Metronomic Cyclophosphamide

Nude mouse xenograft study for treatment of neuroblastoma: Effects of chemotherapeutic agents and surgery on tumor growth and cell kinetics

1984 ◽  
Vol 19 (1) ◽  
pp. 72-76 ◽  
Author(s):  
Yoshiaki Tsuchida ◽  
Kinji Yokomori ◽  
Tadashi Iwanaka ◽  
Sumio Saito
Keyword(s):  
Tumor Growth ◽  
Nude Mouse ◽  
Cell Kinetics ◽  
Chemotherapeutic Agents ◽  
Mouse Xenograft

scholarly journals Inhibition of IL-17A Suppresses Enhanced-Tumor Growth in Low Dose Pre-Irradiated Tumor Beds

PLoS ONE ◽  
2014 ◽  
Vol 9 (9) ◽  
pp. e106423 ◽  
Author(s):  
Eun-Jung Lee ◽  
Hyo Jin Park ◽  
Ik-Jae Lee ◽  
Won Woo Kim ◽  
Sang-Jun Ha ◽  
...  
Keyword(s):  
Tumor Growth ◽  
Low Dose
Sign in / Sign up

Export Citation Format

Share Document