Radia M Johnson1, Heidi S Phillips1, Carlos Bais2, Cameron W Brennan3, Timothy F Cloughesy4, Anneleen Daemen5, Ulrich Herrlinger6, Robert B Jenkins7, Albert Lai4, Christoph Mancao8, Michael Weller9, Wolfgang Wick10, Richard Bourgon1, Josep Garcia11. 1. Department of Bioinformatics and Computational Biology, Genentech Inc, South San Francisco, California, USA. 2. Oncology Biomarker Development, Genentech Inc., South San Francisco, California, USA. 3. Department of Neurosurgery, Memorial Sloan Kettering Cancer Center, New York, New York, USA. 4. Department of Neurology, University of California Los Angeles (UCLA), Los Angeles, California, USA. 5. Department of Translational Medicine, ORIC Pharmaceuticals Inc, South San Francisco, California, USA. 6. Division of Clinical Neurooncology, Department of Neurology, University Hospital Bonn, Bonn, Germany. 7. Department of Laboratory Medicine and Pathology, Mayo Clinic College of Medicine, Rochester, Minnesota, USA. 8. Oncology Biomarker Development, Genentech Inc., Basel, Switzerland. 9. Department of Neurology, University Hospital and University of Zurich, Zurich, Switzerland. 10. Department of Neurology, Ruprecht-Karls University Heidelberg and German Cancer Research Center, Heidelberg, Germany. 11. Global Clinical Development, F. Hoffmann-La Roche Ltd, Basel, Switzerland.
Abstract
BACKGROUND: We aimed to develop a gene expression-based prognostic signature for isocitrate dehydrogenase (IDH) wild-type glioblastoma using clinical trial datasets representative of glioblastoma clinical trial populations. METHODS: Samples were collected from newly diagnosed patients with IDH wild-type glioblastoma in the ARTE, TAMIGA, EORTC 26101 (referred to as "ATE"), AVAglio, and GLARIUS trials, or treated at UCLA. Transcriptional profiling was achieved with the NanoString gene expression platform. To identify genes prognostic for overall survival (OS), we built an elastic net penalized Cox proportional hazards regression model using the discovery ATE dataset. For validation in independent datasets (AVAglio, GLARIUS, UCLA), we combined elastic net-selected genes into a robust z-score signature (ATE score) to overcome gene expression platform differences between discovery and validation cohorts. RESULTS: NanoString data were available from 512 patients in the ATE dataset. Elastic net identified a prognostic signature of 9 genes (CHEK1, GPR17, IGF2BP3, MGMT, MTHFD1L, PTRH2, SOX11, S100A9, and TFRC). Translating weighted elastic net scores to the ATE score conserved the prognostic value of the genes. The ATE score was prognostic for OS in the ATE dataset (P < 0.0001), as expected, and in the validation cohorts (AVAglio, P < 0.0001; GLARIUS, P = 0.02; UCLA, P = 0.004). The ATE score remained prognostic following adjustment for O6-methylguanine-DNA methyltransferase (MGMT) promoter methylation status and corticosteroid use at baseline. A positive correlation between ATE score and proneural/proliferative subtypes was observed in patients with MGMT non-methylated promoter status. CONCLUSIONS: The ATE score showed prognostic value and may enable clinical trial stratification for IDH wild-type glioblastoma.
BACKGROUND: We aimed to develop a gene expression-based prognostic signature for isocitrate dehydrogenase (IDH) wild-type glioblastoma using clinical trial datasets representative of glioblastoma clinical trial populations. METHODS: Samples were collected from newly diagnosed patients with IDH wild-type glioblastoma in the ARTE, TAMIGA, EORTC 26101 (referred to as "ATE"), AVAglio, and GLARIUS trials, or treated at UCLA. Transcriptional profiling was achieved with the NanoString gene expression platform. To identify genes prognostic for overall survival (OS), we built an elastic net penalized Cox proportional hazards regression model using the discovery ATE dataset. For validation in independent datasets (AVAglio, GLARIUS, UCLA), we combined elastic net-selected genes into a robust z-score signature (ATE score) to overcome gene expression platform differences between discovery and validation cohorts. RESULTS: NanoString data were available from 512 patients in the ATE dataset. Elastic net identified a prognostic signature of 9 genes (CHEK1, GPR17, IGF2BP3, MGMT, MTHFD1L, PTRH2, SOX11, S100A9, and TFRC). Translating weighted elastic net scores to the ATE score conserved the prognostic value of the genes. The ATE score was prognostic for OS in the ATE dataset (P < 0.0001), as expected, and in the validation cohorts (AVAglio, P < 0.0001; GLARIUS, P = 0.02; UCLA, P = 0.004). The ATE score remained prognostic following adjustment for O6-methylguanine-DNA methyltransferase (MGMT) promoter methylation status and corticosteroid use at baseline. A positive correlation between ATE score and proneural/proliferative subtypes was observed in patients with MGMT non-methylated promoter status. CONCLUSIONS: The ATE score showed prognostic value and may enable clinical trial stratification for IDH wild-type glioblastoma.
Authors: Monika E Hegi; Els Genbrugge; Thierry Gorlia; Roger Stupp; Mark R Gilbert; Olivier L Chinot; L Burt Nabors; Greg Jones; Wim Van Criekinge; Josef Straub; Michael Weller Journal: Clin Cancer Res Date: 2018-12-04 Impact factor: 12.531
Authors: Shideng Bao; Qiulian Wu; Roger E McLendon; Yueling Hao; Qing Shi; Anita B Hjelmeland; Mark W Dewhirst; Darell D Bigner; Jeremy N Rich Journal: Nature Date: 2006-10-18 Impact factor: 49.962
Authors: David N Louis; Arie Perry; Guido Reifenberger; Andreas von Deimling; Dominique Figarella-Branger; Webster K Cavenee; Hiroko Ohgaki; Otmar D Wiestler; Paul Kleihues; David W Ellison Journal: Acta Neuropathol Date: 2016-05-09 Impact factor: 17.088
Authors: Yong-Wan Kim; Dimpy Koul; Se Hoon Kim; Agda Karina Lucio-Eterovic; Pablo R Freire; Jun Yao; Jing Wang; Jonas S Almeida; Ken Aldape; W K Alfred Yung Journal: Neuro Oncol Date: 2013-03-15 Impact factor: 12.300
Authors: Stephen J Bagley; Shawn Kothari; Rifaquat Rahman; Eudocia Q Lee; Gavin P Dunn; Evanthia Galanis; Susan M Chang; Louis Burt Nabors; Manmeet S Ahluwalia; Roger Stupp; Minesh P Mehta; David A Reardon; Stuart A Grossman; Erik P Sulman; John H Sampson; Simon Khagi; Michael Weller; Timothy F Cloughesy; Patrick Y Wen; Mustafa Khasraw Journal: Clin Cancer Res Date: 2022-02-15 Impact factor: 13.801
Authors: Stephen J Bagley; Jacob Till; Aseel Abdalla; Hareena K Sangha; Stephanie S Yee; Jake Freedman; Taylor A Black; Jasmin Hussain; Zev A Binder; Steven Brem; Arati S Desai; Donald M O'Rourke; Qi Long; Seyed Ali Nabavizadeh; Erica L Carpenter Journal: Neurooncol Adv Date: 2021-01-16