Spatial structure impacts adaptive therapy by shaping intra-tumoral competition

Strobl, Maximilian; Gallaher, Jill; West, Jeffrey; Robertson-Tessi, Mark; Maini, P. K.; Anderson, Alexander R.A.

doi:10.1101/2020.11.03.365163

Cited by 17 publications

(30 citation statements)

References 65 publications

(185 reference statements)

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“…Furthermore, the results of Vander Velde et al [65] suggest implementing a continuous phenotype landscape in our model as well as extending our analysis to study combination therapies, strategies for drug combination, and the continued evolution of treatment resistance. Moreover, we do not consider the role of spatial and metabolic heterogeneity [69][70][71], drug infiltration [72,73], nor the role of other cells in the tumour micro-environment [74].…”

Section: Discussionmentioning

confidence: 99%

The role of memory in non-genetic inheritance and its impact on cancer treatment resistance

et al. 2021

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Intra-tumour heterogeneity is a leading cause of treatment failure and disease progression in cancer. While genetic mutations have long been accepted as a primary mechanism of generating this heterogeneity, the role of phenotypic plasticity is becoming increasingly apparent as a driver of intra-tumour heterogeneity. Consequently, understanding the role of this plasticity in treatment resistance and failure is a key component of improving cancer therapy. We develop a mathematical model of stochastic phenotype switching that tracks the evolution of drug-sensitive and drug-tolerant subpopulations to clarify the role of phenotype switching on population growth rates and tumour persistence. By including cytotoxic therapy in the model, we show that, depending on the strategy of the drug-tolerant subpopulation, stochastic phenotype switching can lead to either transient or permanent drug resistance. We study the role of phenotypic heterogeneity in a drug-resistant, genetically homogeneous population of non-small cell lung cancer cells to derive a rational treatment schedule that drives population extinction and avoids competitive release of the drug-tolerant sub-population. This model-informed therapeutic schedule results in increased treatment efficacy when compared against periodic therapy, and, most importantly, sustained tumour decay without the development of resistance.

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Section: Discussionmentioning

confidence: 99%

The role of memory in non-genetic inheritance and its impact on cancer treatment resistance

et al. 2021

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“…While this assumption of a discrete phenotype landscape simplifies the mathematical modelling, it is not biologically realistic. Moreover, we do not consider the role of spatial and metabolic heterogeneity [56][57][58], drug infiltration [59,60], nor the role of other cells in the tumour micro-environment [61].…”

Section: Discussionmentioning

confidence: 99%

The role of memory in non-genetic inheritance and its impact on cancer treatment resistance

Cassidy

Nichol

Robertson-Tessi

et al. 2021

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Intra-tumour heterogeneity is a leading cause of treatment failure and disease progression in cancer. While genetic mutations have long been accepted as a primary mechanism of generating this heterogeneity, the role of phenotypic plasticity is becoming increasingly apparent as a driver of intra-tumour heterogeneity. Consequently, understanding the role of plasticity in treatment resistance and failure is a key component of improving cancer therapy. We develop a mathematical model of stochastic phenotype switching that tracks the evolution of drug-sensitive and drug-tolerant subpopulations to clarify the role of phenotype switching on population growth rates and tumour persistence. By including cytotoxic therapy in the model, we show that, depending on the strategy of the drug-tolerant subpopulation, stochastic phenotype switching can lead to either transient or permanent drug resistance. We study the role of phenotypic heterogeneity in a drug-resistant, genetically homogeneous population of non-small cell lung cancer cells to derive a rational treatment schedule that drives population extinction and avoids competitive release of the drug-tolerant sub-population. This model-informed therapeutic schedule results in increased treatment efficacy when compared against periodic therapy, and, most importantly, sustained tumour decay without the development of resistance.

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“…Within tumorous tissues and throughout normal tissues, cells compete for space and survival with their neighbors. As recent studies have demonstrated, the spatial structure can shape a tumor's evolution [19,27,28,38]. This spatial competitive aspect has been further experimentally investigated [27,39], but more work needs to be done to better understand how Our analysis of the effects of the distribution of fibroblasts on resistance suggested that there may be an optimal proximity to fibroblasts for maximal tumor cell growth advantage.…”

Section: Discussionmentioning

confidence: 99%

“…In tumors with cells of a varied range of sensitivity, AT resulted in trapping of the resistant cells by the sensitive cells, thus limiting the growth of the tumor [19]. Tumors with spread randomly resistant cells were reported to grow much faster than tumors with resistant cells that were clustered together [27,28]. AT has even been found to delay progression in the absence of fitness costs [27,28], which, however, are assumed to be a key element for the success of AT [12,13].…”

Section: Introduction 19mentioning

confidence: 99%

The impact of the spatial heterogeneity of resistant cells and fibroblasts on treatment response

Chi

Kim

2021

Preprint

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A long-standing practice in the treatment of cancer is that of hitting hard with the maximum tolerated dose to eradicate tumors. This continuous therapy, however, selects for resistant cells, leading to the failure of the treatment. A different type of treatment strategy, adaptive therapy, has recently been shown to have a degree of success in both preclinical xenograft experiments and clinical trials. Adaptive therapy is used to maintain a tumor's volume by exploiting the competition between drug-sensitive and drug-resistant cells with minimum effective drug doses or timed drug holidays. To further understand the role of competition in the outcomes of adaptive therapy, we developed a 2D on-lattice agent-based model. Our simulations show that the superiority of the adaptive strategy over continuous therapy depends on the local competition shaped by the spatial distribution of resistant cells. Cancer cell migration and increased carrying capacity accelerate the progression of the tumor under both types of treatments by reducing the spatial competition. Intratumor competition can also be affected by fibroblasts, which produce microenvironmental factors that promote cancer cell growth. Our simulations show that the spatial architecture of fibroblasts modulates the benefits of adaptive therapy. Finally, as a proof of concept, we simulated the outcomes of adaptive therapy in multiple metastatic sites composed of different spatial distributions of fibroblasts and drug-resistant cell populations.

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Spatial structure impacts adaptive therapy by shaping intra-tumoral competition

Cited by 17 publications

References 65 publications

The role of memory in non-genetic inheritance and its impact on cancer treatment resistance

The role of memory in non-genetic inheritance and its impact on cancer treatment resistance

The role of memory in non-genetic inheritance and its impact on cancer treatment resistance

The impact of the spatial heterogeneity of resistant cells and fibroblasts on treatment response

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