Neuroblastoma signalling models unveil combination therapies targeting feedback-mediated resistance

Very high risk neuroblastoma is characterised by increased MAPK signalling, and targeting MAPK signalling is a promising therapeutic strategy. We used a deeply characterised panel of neuroblastoma cell lines and found that the sensitivity to MEK inhibitors varied drastically between these cell lines...

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Autores principales:	Mathurin Dorel, Bertram Klinger, Tommaso Mari, Joern Toedling, Eric Blanc, Clemens Messerschmidt, Michal Nadler-Holly, Matthias Ziehm, Anja Sieber, Falk Hertwig, Dieter Beule, Angelika Eggert, Johannes H. Schulte, Matthias Selbach, Nils Blüthgen
Formato:	article
Lenguaje:	EN
Publicado:	Public Library of Science (PLoS) 2021
Materias:	Biology (General) QH301-705.5
Acceso en línea:	https://doaj.org/article/eb0d4b5da0ad4179bece23442265192b
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spelling	oai:doaj.org-article:eb0d4b5da0ad4179bece23442265192b2021-11-25T05:42:04ZNeuroblastoma signalling models unveil combination therapies targeting feedback-mediated resistance1553-734X1553-7358https://doaj.org/article/eb0d4b5da0ad4179bece23442265192b2021-11-01T00:00:00Zhttps://www.ncbi.nlm.nih.gov/pmc/articles/PMC8604339/?tool=EBIhttps://doaj.org/toc/1553-734Xhttps://doaj.org/toc/1553-7358Very high risk neuroblastoma is characterised by increased MAPK signalling, and targeting MAPK signalling is a promising therapeutic strategy. We used a deeply characterised panel of neuroblastoma cell lines and found that the sensitivity to MEK inhibitors varied drastically between these cell lines. By generating quantitative perturbation data and mathematical modelling, we determined potential resistance mechanisms. We found that negative feedbacks within MAPK signalling and via the IGF receptor mediate re-activation of MAPK signalling upon treatment in resistant cell lines. By using cell-line specific models, we predict that combinations of MEK inhibitors with RAF or IGFR inhibitors can overcome resistance, and tested these predictions experimentally. In addition, phospho-proteomic profiling confirmed the cell-specific feedback effects and synergy of MEK and IGFR targeted treatment. Our study shows that a quantitative understanding of signalling and feedback mechanisms facilitated by models can help to develop and optimise therapeutic strategies. Our findings should be considered for the planning of future clinical trials introducing MEKi in the treatment of neuroblastoma. Author summary Only few targeted therapies are currently available to treat high-risk neuroblastoma. To address this issue we characterized the drug response of high risk neuroblastoma cell lines and correlated it with genomic and transcriptomic data. Particularly for MEK inhibition, we saw that our panel could be nicely separated into two groups of resistant and sensitive cell lines. Genomic and transcriptomic markers alone did not help to discriminate between responders and non-responders. We used signalling perturbation data to build cell line specific signalling models. Our models suggest that negative feedbacks within MAPK signalling lead to a stronger reactivation of MEK in MEKi resistant cell lines after MEK inhibition. Model analysis suggested that combining MEK inhibition with IGF1R or RAF inhibition could be an effective treatment and we characterised this combination using phosphoproteomics by mass-spectrometry and growth assays. Our study confirms the importance of quantitative understanding of signalling and may help plan future clinical trials involving MEK inhibition for the treatment of neuroblastoma.Mathurin DorelBertram KlingerTommaso MariJoern ToedlingEric BlancClemens MesserschmidtMichal Nadler-HollyMatthias ZiehmAnja SieberFalk HertwigDieter BeuleAngelika EggertJohannes H. SchulteMatthias SelbachNils BlüthgenPublic Library of Science (PLoS)articleBiology (General)QH301-705.5ENPLoS Computational Biology, Vol 17, Iss 11 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	Biology (General) QH301-705.5
spellingShingle	Biology (General) QH301-705.5 Mathurin Dorel Bertram Klinger Tommaso Mari Joern Toedling Eric Blanc Clemens Messerschmidt Michal Nadler-Holly Matthias Ziehm Anja Sieber Falk Hertwig Dieter Beule Angelika Eggert Johannes H. Schulte Matthias Selbach Nils Blüthgen Neuroblastoma signalling models unveil combination therapies targeting feedback-mediated resistance
description	Very high risk neuroblastoma is characterised by increased MAPK signalling, and targeting MAPK signalling is a promising therapeutic strategy. We used a deeply characterised panel of neuroblastoma cell lines and found that the sensitivity to MEK inhibitors varied drastically between these cell lines. By generating quantitative perturbation data and mathematical modelling, we determined potential resistance mechanisms. We found that negative feedbacks within MAPK signalling and via the IGF receptor mediate re-activation of MAPK signalling upon treatment in resistant cell lines. By using cell-line specific models, we predict that combinations of MEK inhibitors with RAF or IGFR inhibitors can overcome resistance, and tested these predictions experimentally. In addition, phospho-proteomic profiling confirmed the cell-specific feedback effects and synergy of MEK and IGFR targeted treatment. Our study shows that a quantitative understanding of signalling and feedback mechanisms facilitated by models can help to develop and optimise therapeutic strategies. Our findings should be considered for the planning of future clinical trials introducing MEKi in the treatment of neuroblastoma. Author summary Only few targeted therapies are currently available to treat high-risk neuroblastoma. To address this issue we characterized the drug response of high risk neuroblastoma cell lines and correlated it with genomic and transcriptomic data. Particularly for MEK inhibition, we saw that our panel could be nicely separated into two groups of resistant and sensitive cell lines. Genomic and transcriptomic markers alone did not help to discriminate between responders and non-responders. We used signalling perturbation data to build cell line specific signalling models. Our models suggest that negative feedbacks within MAPK signalling lead to a stronger reactivation of MEK in MEKi resistant cell lines after MEK inhibition. Model analysis suggested that combining MEK inhibition with IGF1R or RAF inhibition could be an effective treatment and we characterised this combination using phosphoproteomics by mass-spectrometry and growth assays. Our study confirms the importance of quantitative understanding of signalling and may help plan future clinical trials involving MEK inhibition for the treatment of neuroblastoma.
format	article
author	Mathurin Dorel Bertram Klinger Tommaso Mari Joern Toedling Eric Blanc Clemens Messerschmidt Michal Nadler-Holly Matthias Ziehm Anja Sieber Falk Hertwig Dieter Beule Angelika Eggert Johannes H. Schulte Matthias Selbach Nils Blüthgen
author_facet	Mathurin Dorel Bertram Klinger Tommaso Mari Joern Toedling Eric Blanc Clemens Messerschmidt Michal Nadler-Holly Matthias Ziehm Anja Sieber Falk Hertwig Dieter Beule Angelika Eggert Johannes H. Schulte Matthias Selbach Nils Blüthgen
author_sort	Mathurin Dorel
title	Neuroblastoma signalling models unveil combination therapies targeting feedback-mediated resistance
title_short	Neuroblastoma signalling models unveil combination therapies targeting feedback-mediated resistance
title_full	Neuroblastoma signalling models unveil combination therapies targeting feedback-mediated resistance
title_fullStr	Neuroblastoma signalling models unveil combination therapies targeting feedback-mediated resistance
title_full_unstemmed	Neuroblastoma signalling models unveil combination therapies targeting feedback-mediated resistance
title_sort	neuroblastoma signalling models unveil combination therapies targeting feedback-mediated resistance
publisher	Public Library of Science (PLoS)
publishDate	2021
url	https://doaj.org/article/eb0d4b5da0ad4179bece23442265192b
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Neuroblastoma signalling models unveil combination therapies targeting feedback-mediated resistance

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