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Clinical responses to ERK inhibition in BRAF(V600E)-mutant colorectal cancer predicted using a computational model

Approximately 10% of colorectal cancers harbor BRAF (V600E) mutations, which constitutively activate the MAPK signaling pathway. We sought to determine whether ERK inhibitor (GDC-0994)-containing regimens may be of clinical benefit to these patients based on data from in vitro (cell line) and in viv...

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Autores principales: Kirouac, Daniel C., Schaefer, Gabriele, Chan, Jocelyn, Merchant, Mark, Orr, Christine, Huang, Shih-Min A., Moffat, John, Liu, Lichuan, Gadkar, Kapil, Ramanujan, Saroja
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2017
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5460205/
https://www.ncbi.nlm.nih.gov/pubmed/28649441
http://dx.doi.org/10.1038/s41540-017-0016-1
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author Kirouac, Daniel C.
Schaefer, Gabriele
Chan, Jocelyn
Merchant, Mark
Orr, Christine
Huang, Shih-Min A.
Moffat, John
Liu, Lichuan
Gadkar, Kapil
Ramanujan, Saroja
author_facet Kirouac, Daniel C.
Schaefer, Gabriele
Chan, Jocelyn
Merchant, Mark
Orr, Christine
Huang, Shih-Min A.
Moffat, John
Liu, Lichuan
Gadkar, Kapil
Ramanujan, Saroja
author_sort Kirouac, Daniel C.
collection PubMed
description Approximately 10% of colorectal cancers harbor BRAF (V600E) mutations, which constitutively activate the MAPK signaling pathway. We sought to determine whether ERK inhibitor (GDC-0994)-containing regimens may be of clinical benefit to these patients based on data from in vitro (cell line) and in vivo (cell- and patient-derived xenograft) studies of cetuximab (EGFR), vemurafenib (BRAF), cobimetinib (MEK), and GDC-0994 (ERK) combinations. Preclinical data was used to develop a mechanism-based computational model linking cell surface receptor (EGFR) activation, the MAPK signaling pathway, and tumor growth. Clinical predictions of anti-tumor activity were enabled by the use of tumor response data from three Phase 1 clinical trials testing combinations of EGFR, BRAF, and MEK inhibitors. Simulated responses to GDC-0994 monotherapy (overall response rate = 17%) accurately predicted results from a Phase 1 clinical trial regarding the number of responding patients (2/18) and the distribution of tumor size changes (“waterfall plot”). Prospective simulations were then used to evaluate potential drug combinations and predictive biomarkers for increasing responsiveness to MEK/ERK inhibitors in these patients.
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spelling pubmed-54602052017-06-23 Clinical responses to ERK inhibition in BRAF(V600E)-mutant colorectal cancer predicted using a computational model Kirouac, Daniel C. Schaefer, Gabriele Chan, Jocelyn Merchant, Mark Orr, Christine Huang, Shih-Min A. Moffat, John Liu, Lichuan Gadkar, Kapil Ramanujan, Saroja NPJ Syst Biol Appl Article Approximately 10% of colorectal cancers harbor BRAF (V600E) mutations, which constitutively activate the MAPK signaling pathway. We sought to determine whether ERK inhibitor (GDC-0994)-containing regimens may be of clinical benefit to these patients based on data from in vitro (cell line) and in vivo (cell- and patient-derived xenograft) studies of cetuximab (EGFR), vemurafenib (BRAF), cobimetinib (MEK), and GDC-0994 (ERK) combinations. Preclinical data was used to develop a mechanism-based computational model linking cell surface receptor (EGFR) activation, the MAPK signaling pathway, and tumor growth. Clinical predictions of anti-tumor activity were enabled by the use of tumor response data from three Phase 1 clinical trials testing combinations of EGFR, BRAF, and MEK inhibitors. Simulated responses to GDC-0994 monotherapy (overall response rate = 17%) accurately predicted results from a Phase 1 clinical trial regarding the number of responding patients (2/18) and the distribution of tumor size changes (“waterfall plot”). Prospective simulations were then used to evaluate potential drug combinations and predictive biomarkers for increasing responsiveness to MEK/ERK inhibitors in these patients. Nature Publishing Group UK 2017-06-02 /pmc/articles/PMC5460205/ /pubmed/28649441 http://dx.doi.org/10.1038/s41540-017-0016-1 Text en © The Author(s) 2017 Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/.
spellingShingle Article
Kirouac, Daniel C.
Schaefer, Gabriele
Chan, Jocelyn
Merchant, Mark
Orr, Christine
Huang, Shih-Min A.
Moffat, John
Liu, Lichuan
Gadkar, Kapil
Ramanujan, Saroja
Clinical responses to ERK inhibition in BRAF(V600E)-mutant colorectal cancer predicted using a computational model
title Clinical responses to ERK inhibition in BRAF(V600E)-mutant colorectal cancer predicted using a computational model
title_full Clinical responses to ERK inhibition in BRAF(V600E)-mutant colorectal cancer predicted using a computational model
title_fullStr Clinical responses to ERK inhibition in BRAF(V600E)-mutant colorectal cancer predicted using a computational model
title_full_unstemmed Clinical responses to ERK inhibition in BRAF(V600E)-mutant colorectal cancer predicted using a computational model
title_short Clinical responses to ERK inhibition in BRAF(V600E)-mutant colorectal cancer predicted using a computational model
title_sort clinical responses to erk inhibition in braf(v600e)-mutant colorectal cancer predicted using a computational model
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5460205/
https://www.ncbi.nlm.nih.gov/pubmed/28649441
http://dx.doi.org/10.1038/s41540-017-0016-1
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