The role of phenotypic plasticity in the escape of cancer cells from targeted therapy

Emmons, Michael F.; Faião-Flores, Fernanda; Smalley, Keiran S.M.

doi:10.1016/j.bcp.2016.06.014

Cited by 34 publications

(32 citation statements)

References 102 publications

(150 reference statements)

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“…Microenvironment-driven transitions between phenotypes with substantially different sensitivities to targeted or immunotherapies represent a moving target and consequently pose a major challenge to effective therapy (Landsberg et al 2012;Hugo et al 2015;Emmons et al 2016). However, the phenotypic plasticity of cancer cells also offers an opportunity for pharmacologic intervention aimed at diverting cells away from a drug-resistant state to one that is drug sensitive (Sáez-Ayala et al 2013) or by targeting the events that lead to the generation or stabilization of specific phenotypic states (Gupta et al 2009b;Rambow et al 2018) However, to do so effectively requires an in-depth understanding of the molecular mechanisms underpinning cancer-associated phenotypic transitions, and knowledge of the repertoire of phenotypes present both prior to and as a consequence of therapy.…”

Section: Genetic Vs Nongenetic Intratumor Heterogeneitymentioning

confidence: 99%

Melanoma plasticity and phenotypic diversity: therapeutic barriers and opportunities

2019

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An incomplete view of the mechanisms that drive metastasis, the primary cause of cancer-related death, has been a major barrier to development of effective therapeutics and prognostic diagnostics. Increasing evidence indicates that the interplay between microenvironment, genetic lesions, and cellular plasticity drives the metastatic cascade and resistance to therapies. Here, using melanoma as a model, we outline the diversity and trajectories of cell states during metastatic dissemination and therapy exposure, and highlight how understanding the magnitude and dynamics of nongenetic reprogramming in space and time at single-cell resolution can be exploited to develop therapeutic strategies that capitalize on nongenetic tumor evolution.

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Section: Genetic Vs Nongenetic Intratumor Heterogeneitymentioning

confidence: 99%

Melanoma plasticity and phenotypic diversity: therapeutic barriers and opportunities

2019

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“…Multiple resistance mechanisms to MAPKi and ICi have been proposed and confirmed over the years and summarized in recent reviews . Additional important contributors to melanoma drug resistance are defective apoptosis, tumor heterogeneity and phenotypic plasticity . A hallmark of the latter is differential proliferative behaviour of tumor subpopulations .…”

Section: Introductionmentioning

confidence: 97%

Cell cycle‐tailored targeting of metastatic melanoma: Challenges and opportunities

Haass

Gabrielli

2017

Experimental Dermatology

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The advent of targeted therapies of metastatic melanoma, such as MAPK pathway inhibitors and immune checkpoint antagonists, has turned dermato-oncology from the "bad guy" to the "poster child" in oncology. Current targeted therapies are effective, although here is a clear need to develop combination therapies to delay the onset of resistance. Many antimelanoma drugs impact on the cell cycle but are also dependent on certain cell cycle phases resulting in cell cycle phase-specific drug insensitivity.Here, we raise the question: Have combination trials been abandoned prematurely as ineffective possibly only because drug scheduling was not optimized? Firstly, if both drugs of a combination hit targets in the same melanoma cell, cell cycle-mediated drug insensitivity should be taken into account when planning combination therapies, timing of dosing schedules and choice of drug therapies in solid tumors. Secondly, if the combination is designed to target different tumor cell subpopulations of a heterogeneous tumor, one drug effective in a particular subpopulation should not negatively impact on the other drug targeting another subpopulation. In addition to the role of cell cycle stage and progression on standard chemotherapeutics and targeted drugs, we discuss the utilization of cell cycle checkpoint control defects to enhance chemotherapeutic responses or as targets themselves. We propose that cell cycle-tailored targeting of metastatic melanoma could further improve therapy outcomes and that our real-time cell cycle imaging 3D melanoma spheroid model could be utilized as a tool to measure and design drug scheduling approaches. K E Y W O R D Scell cycle, drug resistance, drug sensitivity, fluorescent ubiquitination-based cell cycle indicator, melanoma therapy, real-time imaging

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“…Cell-to-cell variability may generate subpopulations of drug-tolerant cells that diminish cancer drug efficacy [24][25][26][27][28][29][30]. Heterogeneity is observed following the emergence of adaptive resistance or selection of resistant subclones even in populations of cells that are scored as highly responsive based on drug potency (e.g.…”

Section: Introductionmentioning

confidence: 99%

Phenotype-based probabilistic analysis of heterogeneous responses to cancer drugs and their combination efficacy

et al. 2020

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Cell-to-cell variability generates subpopulations of drug-tolerant cells that diminish the efficacy of cancer drugs. Efficacious combination therapies are thus needed to block drug-tolerant cells via minimizing the impact of heterogeneity. Probabilistic models such as Bliss independence have been developed to evaluate drug interactions and their combination efficacy based on probabilities of specific actions mediated by drugs individually and in combination. In practice, however, these models are often applied to conventional dose-response curves in which a normalized parameter with a value between zero and one, generally referred to as fraction of cells affected (f a ), is used to evaluate the efficacy of drugs and their combined interactions. We use basic probability theory, computer simulations, time-lapse live cell microscopy, and single-cell analysis to show that f a metrics may bias our assessment of drug efficacy and combination effectiveness. This bias may be corrected when dynamic probabilities of drug-induced phenotypic events, i.e. induction of cell death and inhibition of division, at a single-cell level are used as metrics to assess drug efficacy. Probabilistic phenotype metrics offer the following three benefits. First, in contrast to the commonly used f a metrics, they directly represent probabilities of drug action in a cell population. Therefore, they deconvolve differential degrees of drug effect on tumor cell killing versus inhibition of cell division, which may not be correlated for many drugs. Second, they increase the sensitivity of short-term drug response assays to cell-to-cell heterogeneities and the presence of drug-tolerant subpopulations. Third, their probabilistic nature allows them to be used directly in unbiased evaluation of synergistic efficacy in drug combinations using probabilistic models such as Bliss independence. Altogether, we envision that probabilistic analysis of single-cell phenotypes complements currently available assays via improving our understanding of heterogeneity in drug response, thereby facilitating the discovery of more efficacious combination therapies to block drug-tolerant cells. PLOS Computational Biology | https://doi.Citation: Comandante-Lou N, Khaliq M, Venkat D, Manikkam M, Fallahi-Sichani M (2020) Phenotypebased probabilistic analysis of heterogeneous responses to cancer drugs and their combination efficacy. PLoS Comput Biol 16(2): e1007688.Resistance to therapy due to tumor cell heterogeneity poses a major challenge to the use of cancer drugs. Cell-to-cell variability generates subpopulations of drug-tolerant cells that diminish therapeutic efficacy, even in populations of cells that are scored as highly sensitive based on drug potency. Overcoming such heterogeneity and blocking subpopulations of drug-tolerant cells motivate efforts toward identifying efficacious combination therapies. The success of these efforts depends on our ability to distinguish how heterogeneous populations of cells respond to individual drugs, and how these responses are inf...

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The role of phenotypic plasticity in the escape of cancer cells from targeted therapy

Cited by 34 publications

References 102 publications

Melanoma plasticity and phenotypic diversity: therapeutic barriers and opportunities

Melanoma plasticity and phenotypic diversity: therapeutic barriers and opportunities

Cell cycle‐tailored targeting of metastatic melanoma: Challenges and opportunities

Phenotype-based probabilistic analysis of heterogeneous responses to cancer drugs and their combination efficacy

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