TY - JOUR TI - A distinct p53 target gene set predicts for response to the selective p53–HDM2 inhibitor NVP-CGM097 AU - Jeay, Sébastien AU - Gaulis, Swann AU - Ferretti, Stéphane AU - Bitter, Hans AU - Ito, Moriko AU - Valat, Thérèse AU - Murakami, Masato AU - Ruetz, Stephan AU - Guthy, Daniel A AU - Rynn, Caroline AU - Jensen, Michael R AU - Wiesmann, Marion AU - Kallen, Joerg AU - Furet, Pascal AU - Gessier, François AU - Holzer, Philipp AU - Masuya, Keiichi AU - Würthner, Jens AU - Halilovic, Ensar AU - Hofmann, Francesco AU - Sellers, William R AU - Graus Porta, Diana A2 - Espinosa, Joaquin M VL - 4 PY - 2015 DA - 2015/05/12 SP - e06498 C1 - eLife 2015;4:e06498 DO - 10.7554/eLife.06498 UR - https://doi.org/10.7554/eLife.06498 AB - 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. KW - translational oncology KW - predictive signature KW - p53 KW - HDM2 JF - eLife SN - 2050-084X PB - eLife Sciences Publications, Ltd ER -