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. 2019 Mar 22;120(8):806–814. doi: 10.1038/s41416-019-0404-y

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© The Author(s) 2019

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/.

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Fig. 2 — A new classification based on glioblastoma (GBM) cell lines. a Representation of the 129 cell lines samples on the two first dimensions of the principal components analysis. Three clusters were built by the hierarchical classification on principle components (HCPC) method. b, c Graph bar representing the quantities of cell lines groups the patients’ tumours. The patients were clustered based on these estimations using hierarchical clustering on the TCGA cohort (b) and Rembrandt’s cohort (c). d, e Kaplan–Meier estimates for overall survival (OS); patients from TCGA cohort (d) and Rembrandt cohort (e) were stratified according to the classical GBM classification. f, g Kaplan–Meier estimates for OS; patients from TCGA cohort (d) and Rembrandt cohort (e) were stratified according to the cell lines classification. **p < 0.01. ns not significant, TCGA the Cancer Genome Atlas