Box 1.

The main outcomes and impact of TCGA large-scale gene expression studies

Main outcomes of TCGA consortium in glioma	Impact and weaknesses
In general
TCGA offered a huge amount of publically-available data for >1000 glioma samples characterizing the genetic and epigenetic background of these tumours, performing pathway analysis and suggesting biomarkers for future therapy. Several other studies used TCGA data to identify potential target therapy and group of patients with better response to specific treatment.	The inability to map genetic and protein changes to single cells or distinct cell populations within the tumour (Singh et al., 2012).
Key findings
Characterizing the inter-patient heterogeneity in GBM at the molecular level through subtyping GBM patients into three subtypes: proneural, mesenchymal, and classical, characterized with PDGFRA/IDH mutation, NF1 mutation and EGFR amplification respectively (Verhaak et al., 2010; Wang et al., 2017b).	Most of the samples were taken from one single random spot of the tumour bulk, assuming that GBMs are homogenous tumours, and recently it was shown that GBM is highly heterogeneous, and anatomical location affects the subtype. The single cell analysis showed that a GBM sample contain different cell populations that belong to three different subtypes (Patel et al., 2014). Around 8% of GBM samples score for more than one subtype. In Phillips et al., EGFR is marker for proliferation and mesenchymal subtypes. There was no significant association between subtypes and longer survival among patients. The tendency of better survival was observed only by restricting the analysis to patients with lowest simplicity score that represent 20% of the analysed GBM samples (Wang et al., 2017).
Characterization of G-CIMP+ tumours with younger age at the time of diagnosis, better overall survival, more common in lower grade than GBM, and most patients with G-CIMP+ belong to the proneural subtype and are IDH mutant. Identifying the correlation between genetic mutations and MGMT+ in recurrent GBM after temozolomide treatment. The recurrent GBM in these patients that lost MGMT methylation, harboured much higher genetic alteration compared to untreated patients, which might contribute to the aggressive and therapeutic resistant nature of the tumour (Brennan et al., 2013; Noushmehr et al., 2010).	Abnormal methylation of MGMT and its favourable clinical outcomes in GBM after temozolomide treatment was discovered in 2000 (Esteller et al., 2000).
In lower grade glioma, three subtypes that correlated with patient survival were identified: IDH-mutant with 1p/19q co-deletion (which have the most favourable survival), IDH-mutant without 1p19q deletion, and IDH wild-type (with worst survival that tends to be similar to GBM) (Cancer Genome Atlas Research et al., 2015).	The favourable clinical outcome of IDH-mutant was discovered by others (Parsons et al., 2008; Jiao et al., 2012). Oligodendroglioma, which often harbour 1p/19q deletion were known to have a better response to radio- and chemotherapy and have better survival (van den Bent et al., 2013; Cairncross et al., 2014). The MGMT-methylation status was not considered here and this might have affected the results.
Confirmed that RB, p53, and RTK/RAS/PI3K pathways are activated in all GBM (Cancer Genome Atlas Research, 2008).	These were already known oncogenic pathways (Furnari et al., 2007).
Identifying EGFR-TACC fusion in a small subset of GBMs (3/97, 3.1%) (Singh et al., 2012).	The clinical significance of this finding needs to be described.
NF1-deficiency drives macrophage/microglia recruitment.	The role of NF1-deficiency in recruiting macrophages/microglia was reported in other studies (Daginakatte and Gutmann, 2007; Rutledge et al., 2013; Solga et al., 2015).
TCGA suggested a biological meaning of the subtypes by correlating the GBM subtypes to three cell types in the CNS. The proneural subtype enriched for the oligodendrocytic signature, classical enriched for astrocytic signature, and mesenchymal enriched for genes expressed in cultured astrocytes (Cahoy et al., 2008; Verhaak et al., 2010).	The cultured astrocytes were mouse derived astrocytes (Cahoy et al., 2008). The gene expression profile of the mesenchymal subtype showed similarity to human MSCs derived from bone marrow, adipose, and brain (epileptic patient), which weakened the belief of the astrocytic origin of the mesenchymal subtype depending on its similarity to cultured mouse astrocytes. (Behnan et al., 2017). In Phillips et al. (2006) the mesenchymal subtype samples were enriched for genes expressed in bone, synovium tissue, smooth muscle, endothelial, and dendritic cells, as well as cultured human foetal astrocytes.
Differential activation of immune microenvironment by different subtypes. MES subtype has lowest purity and simplicity score indicating the heterogeneity and complexity of this subtype comparing to non- mesenchymal tumours (Wang et al., 2017). Hypermutated primary and recurrent GBMs after temozolomide treatment were associated with increased CD8+ T-cell infiltration, suggesting that these patients might benefit from checkpoint inhibitors (Wang et al., 2017).	Limited sample size of hypermutated primary and recurrent GBMs, five to seven samples hypermutated compared to 238 non-hypermutated.
Aggressively treated patients demonstrated a survival benefit in the classical and mesenchymal subtypes, but not in the proneuralsubtype (Verhaak et al., 2010).	Preliminary data need to be validated in clinical settings.
Frequent subtype switch upon tumour recurrence (45% in IDH-wild-type samples). The mesenchymal subtype seemed to be the most stable subtype (65%) upon recurrence (Wang et al., 2017).	The change of the subtypes upon tumour recurrence, shift toward the mesenchymal subtype, and induced a shift in experimental set-up have been reported previously (Phillips et al., 2006; Bhat et al., 2013; Halliday et al., 2014). Although the mesenchymal subtype is the most common subtype in recurrent GBM, the proneural?mesenchymal shift was not significant (Wang et al., 2017).