eLife
(May 2015)
A distinct p53 target gene set predicts for response to the selective p53–HDM2 inhibitor NVP-CGM097
Sébastien Jeay,
Swann Gaulis,
Stéphane Ferretti,
Hans Bitter,
Moriko Ito,
Thérèse Valat,
Masato Murakami,
Stephan Ruetz,
Daniel A Guthy,
Caroline Rynn,
Michael R Jensen,
Marion Wiesmann,
Joerg Kallen,
Pascal Furet,
François Gessier,
Philipp Holzer,
Keiichi Masuya,
Jens Würthner,
Ensar Halilovic,
Francesco Hofmann,
William R Sellers,
Diana Graus Porta
Affiliations
Sébastien Jeay
Disease Area Oncology, Novartis Institutes for BioMedical Research, Basel, Switzerland
Swann Gaulis
Disease Area Oncology, Novartis Institutes for BioMedical Research, Basel, Switzerland
Stéphane Ferretti
Disease Area Oncology, Novartis Institutes for BioMedical Research, Basel, Switzerland
Hans Bitter
Disease Area Oncology, Novartis Institutes for BioMedical Research, Cambridge, United States
Moriko Ito
Disease Area Oncology, Novartis Institutes for BioMedical Research, Basel, Switzerland
Thérèse Valat
Disease Area Oncology, Novartis Institutes for BioMedical Research, Basel, Switzerland
Masato Murakami
Disease Area Oncology, Novartis Institutes for BioMedical Research, Basel, Switzerland
Stephan Ruetz
Disease Area Oncology, Novartis Institutes for BioMedical Research, Basel, Switzerland
Daniel A Guthy
Disease Area Oncology, Novartis Institutes for BioMedical Research, Basel, Switzerland
Caroline Rynn
Metabolism and Pharmacokinetics, Novartis Institutes for BioMedical Research, Basel, Switzerland
Michael R Jensen
Disease Area Oncology, Novartis Institutes for BioMedical Research, Basel, Switzerland
Marion Wiesmann
Disease Area Oncology, Novartis Institutes for BioMedical Research, Basel, Switzerland
Joerg Kallen
Center of Proteomic Chemistry, Novartis Institutes for BioMedical Research, Basel, Switzerland
Pascal Furet
Global Discovery Chemistry, Novartis Institutes for BioMedical Research, Basel, Switzerland
François Gessier
Global Discovery Chemistry, Novartis Institutes for BioMedical Research, Basel, Switzerland
Philipp Holzer
Global Discovery Chemistry, Novartis Institutes for BioMedical Research, Basel, Switzerland
Keiichi Masuya
Global Discovery Chemistry, Novartis Institutes for BioMedical Research, Basel, Switzerland
Jens Würthner
Translational Clinical Oncology, Novartis Institutes for BioMedical Research, Basel, Switzerland
Ensar Halilovic
Translational Clinical Oncology, Novartis Institutes for BioMedical Research, Cambridge, United States
Francesco Hofmann
Disease Area Oncology, Novartis Institutes for BioMedical Research, Basel, Switzerland
William R Sellers
Disease Area Oncology, Novartis Institutes for BioMedical Research, Cambridge, United States
Diana Graus Porta
Disease Area Oncology, Novartis Institutes for BioMedical Research, Basel, Switzerland
DOI
https://doi.org/10.7554/eLife.06498
Journal volume & issue
Vol. 4
Abstract
Read online
Biomarkers for patient selection are essential for the successful and rapid development of emerging targeted anti-cancer therapeutics. In this study, we report the discovery of a novel patient selection strategy for the p53–HDM2 inhibitor NVP-CGM097, currently under evaluation in clinical trials. By intersecting high-throughput cell line sensitivity data with genomic data, we have identified a gene expression signature consisting of 13 up-regulated genes that predicts for sensitivity to NVP-CGM097 in both cell lines and in patient-derived tumor xenograft models. Interestingly, these 13 genes are known p53 downstream target genes, suggesting that the identified gene signature reflects the presence of at least a partially activated p53 pathway in NVP-CGM097-sensitive tumors. Together, our findings provide evidence for the use of this newly identified predictive gene signature to refine the selection of patients with wild-type p53 tumors and increase the likelihood of response to treatment with p53–HDM2 inhibitors, such as NVP-CGM097.
Keywords
Published in eLife
ISSN
2050-084X (Online)
Publisher
eLife Sciences Publications Ltd
Country of publisher
United Kingdom
LCC subjects
Medicine
Science: Biology (General)
Website
https://elifesciences.org
About the journal
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