Reinforcing targeted therapeutics with phenotypic stability factors

Yaswen, Paul

doi:10.4161/15384101.2014.985071

Cited by 21 publications

(23 citation statements)

References 39 publications

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“…The activity of these miRNAs is thus an important feature to be explored on the tristable dynamics triggered by TGF‐β during EMT. The identification of PSFs has been an important strategy to understand the ability of cells to restrict phenotypic changes in a biological process . Moreover, less toxic treatments can be implemented through the combination of low drug doses and the suppression of these factors in order to eradicate cells in the H state.…”

Section: Discussionmentioning

confidence: 99%

Dynamics of the feedback loops required for the phenotypic stabilization in the epithelial‐mesenchymal transition

Silveira

Mombach

2019

The FEBS Journal

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The epithelial‐mesenchymal transition (EMT) is a complex mechanism in which cells undergo a transition from epithelial to mesenchymal phenotypes (there is also an intermediary hybrid state) in response to microenvironmental alterations and aberrant stimuli triggered by molecules such as TGF‐β. Recent studies in breast cancer progression reported new feedback loops and new participant molecules such as microRNAs 340 and 1199. In this work, we propose a logical model of EMT contemplating the influence of these new published molecules on the regulatory core of EMT. The model results were compared with theoretical and experimental data for the human breast epithelial cell line MCF10A presenting excellent agreement. We propose that the miRNAs 340 and 1199 should be considered phenotypic stability factors of the hybrid state based on the positive feedback loops they form with ZEB1. In addition, the model allows the prediction of phenotype probabilities at the coexistence region. For the tristable dynamics when epithelial, hybrid, and mesenchymal phenotypes coexist, we found that the hybrid state is the most probable, agreeing with experiments. Our results highlight new mechanisms related to the EMT dynamics in response to TGF‐β stimulus in epithelial breast cells and might help the design of therapeutic strategies for breast cancer.

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Section: Discussionmentioning

confidence: 99%

Dynamics of the feedback loops required for the phenotypic stabilization in the epithelial‐mesenchymal transition

Silveira

Mombach

2019

The FEBS Journal

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“…In another preclinical study, EMT‐regulating genes were reported to be differentially expressed in CDK4/6 inhibitor‐resistant breast cancer . TGF‐β phosphorylates and activates Smad2 and Smad3, which then form a complex with Smad4, leading to EMT via the activation of EMT transcription factors . Additionally, TGF‐β also induces EMT via PI3K/AKT/mTOR signaling, which is independent of the Smad pathway .…”

Section: Mechanisms Of Resistance To Cdk4/6 Inhibitorsmentioning

confidence: 99%

“…89 TGF-β phosphorylates and activates Smad2 and Smad3, which then form a complex with Smad4, leading to EMT via the activation of EMT transcription factors. 90,91 Additionally, TGF-β also induces EMT via PI3K/AKT/mTOR signaling, which is independent of the Smad pathway. 85,92 Therefore, the inhibition of TGF-β or EMT in combination with CDK4/6 inhibitors may overcome the resistance to CDK4/6 inhibitors.…”

Section: Cell Cycle-nonspecific Mechanismsmentioning

confidence: 99%

Molecular mechanisms of resistance to CDK4/6 inhibitors in breast cancer: A review

Pandey

Kim

et al. 2019

Intl Journal of Cancer

249

211

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Deregulation of the cyclin D‐CDK4/6‐INK4‐RB pathway leading to uncontrolled cell proliferation, is frequently observed in breast cancer. Currently, three selective CDK4/6 inhibitors have been FDA approved: palbociclib, ribociclib and abemaciclib. Despite promising clinical outcomes, intrinsic or acquired resistance to CDK4/6 inhibitors has limited the success of these treatments; therefore, the development of various strategies to overcome this resistance is of great importance. We highlight the various mechanisms that are directly or indirectly responsible for resistance to CDK4/6 inhibitors, categorizing them into two broad groups; cell cycle‐specific mechanisms and cell cycle‐nonspecific mechanisms. Elucidation of the diverse mechanisms through which resistance to CDK4/6 inhibitors occurs, may aid in the design of novel therapeutic strategies to improve patient outcomes. This review summarizes the currently available knowledge regarding mechanisms of resistance to CDK4/6 inhibitors, and possible therapeutic strategies that may overcome this resistance as well.

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“…Knockdown of either GRHL2 or OVOL2 in H1975 cells destabilized the hybrid E/M phenotype and cells progressing to a complete EMT state [ 54 ]. Thus, these “phenotypic stability factors” (PSFs) GRHL2 and OVOL [ 57 ] act as “critical molecular brakes” by preventing “cells that have gained partial plasticity from crossing the line to undergo complete EMT” [ 58 ]. Of note, there may exist multiple hybrid E/M phenotypes characterized by different gene expression profiles [ 56 , 59 ], and other players such as JAG1 (ligand of cell-cell communication pathway—Notch signaling) and ∆NP63α can also act as PSFs [ 60 , 61 ].…”

Section: Cell Fate Decision-making During Epithelial-to-mesenchymamentioning

confidence: 99%

Phenotypic Plasticity and Cell Fate Decisions in Cancer: Insights from Dynamical Systems Theory

Jia

Jolly

Kulkarni

et al. 2017

Cancers

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Waddington’s epigenetic landscape, a famous metaphor in developmental biology, depicts how a stem cell progresses from an undifferentiated phenotype to a differentiated one. The concept of “landscape” in the context of dynamical systems theory represents a high-dimensional space, in which each cell phenotype is considered as an “attractor” that is determined by interactions between multiple molecular players, and is buffered against environmental fluctuations. In addition, biological noise is thought to play an important role during these cell-fate decisions and in fact controls transitions between different phenotypes. Here, we discuss the phenotypic transitions in cancer from a dynamical systems perspective and invoke the concept of “cancer attractors”—hidden stable states of the underlying regulatory network that are not occupied by normal cells. Phenotypic transitions in cancer occur at varying levels depending on the context. Using epithelial-to-mesenchymal transition (EMT), cancer stem-like properties, metabolic reprogramming and the emergence of therapy resistance as examples, we illustrate how phenotypic plasticity in cancer cells enables them to acquire hybrid phenotypes (such as hybrid epithelial/mesenchymal and hybrid metabolic phenotypes) that tend to be more aggressive and notoriously resilient to therapies such as chemotherapy and androgen-deprivation therapy. Furthermore, we highlight multiple factors that may give rise to phenotypic plasticity in cancer cells, such as (a) multi-stability or oscillatory behaviors governed by underlying regulatory networks involved in cell-fate decisions in cancer cells, and (b) network rewiring due to conformational dynamics of intrinsically disordered proteins (IDPs) that are highly enriched in cancer cells. We conclude by discussing why a therapeutic approach that promotes “recanalization”, i.e., the exit from “cancer attractors” and re-entry into “normal attractors”, is more likely to succeed rather than a conventional approach that targets individual molecules/pathways.

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Reinforcing targeted therapeutics with phenotypic stability factors

Cited by 21 publications

References 39 publications

Dynamics of the feedback loops required for the phenotypic stabilization in the epithelial‐mesenchymal transition

Dynamics of the feedback loops required for the phenotypic stabilization in the epithelial‐mesenchymal transition

Molecular mechanisms of resistance to CDK4/6 inhibitors in breast cancer: A review

Phenotypic Plasticity and Cell Fate Decisions in Cancer: Insights from Dynamical Systems Theory

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