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. Author manuscript; available in PMC: 2017 Oct 4.
Published in final edited form as: Nat Genet. 2016 Jun 6;48(7):768–776. doi: 10.1038/ng.3590

Figure 5. Expression-based Subtyping of Recurrent GBM. (A) Expression based GBM subtyping.

Figure 5

ssGSEA was performed to cluster each sample into four subtypes (proneural, neural, classical, and mesenchymal). “*” indicates subtypes with maximal enrichment score (ES). If the optimal subtype in initial and that in recurrent tumor is different, a patient was labeled as switched. P-value was calculated by Fisher’s exact test. (B) Association between expression-based subtype switching and genetic/clinic features. The same analysis as in Figure 1C had been performed. (C) The stochastic matrix of GBM subtypes. The large cohort of longitudinal GBM samples allows the construction of probability transition matrix between four subtypes. The arrows indicate the frequency of a patient to stay a subtype or to be switched from one subtype to another. A stationary distribution was calculated based on this stochastic matrix, indicating the proportion of these four subtypes after treatment.