Lonneke Gravendeel

Intrinsic Gene Expression Profiles of Gliomas Are a Better Predictor of Survival than Histology

Gliomas are the most common primary brain tumors with heterogeneous morphology and variable prognosis. Treatment decisions in patients rely mainly on histologic classification and clinical parameters. However, differences between histologic subclasses and grades are subtle, and classifying gliomas is subject to a large interobserver variability. To improve current classification standards, we have performed gene expression profiling on a large cohort of glioma samples of all histologic subtypes and grades. We identified seven distinct molecular subgroups that correlate with survival. These include two favorable prognostic subgroups (median survival, >4.7 years), two with intermediate prognosis (median survival, 1-4 years), two with poor prognosis (median survival, <1 year), and one control group. The intrinsic molecular subtypes of glioma are different from histologic subgroups and correlate better to patient survival. The prognostic value of molecular subgroups was validated on five independent sample cohorts (The Cancer Genome Atlas, Repository for Molecular Brain Neoplasia Data, GSE12907, GSE4271, and Li and colleagues). The power of intrinsic subtyping is shown by its ability to identify a subset of prognostically favorable tumors within an external data set that contains only histologically confirmed glioblastomas (GBM). Specific genetic changes (epidermal growth factor receptor amplification, IDH1 mutation, and 1p/19q loss of heterozygosity) segregate in distinct molecular subgroups. We identified a subgroup with molecular features associated with secondary GBM, suggesting that different genetic changes drive gene expression profiles. Finally, we assessed response to treatment in molecular subgroups. Our data provide compelling evidence that expression profiling is a more accurate and objective method to classify gliomas than histologic classification. Molecular classification therefore may aid diagnosis and can guide clinical decision making.

A Hypermethylated Phenotype Is a Better Predictor of Survival than MGMT Methylation in Anaplastic Oligodendroglial Brain Tumors: A Report from EORTC Study 26951

Purpose: The MGMT promoter methylation status has been suggested to be predictive for outcome to temozolomide chemotherapy in patients with glioblastoma (GBM). Subsequent studies indicated that MGMT promoter methylation is a prognostic marker even in patients treated with radiotherapy alone, both in GBMs and in grade III gliomas. Experimental Design: To help determine the molecular mechanism behind this prognostic effect, we have conducted genome-wide methylation profiling and determined the MGMT promoter methylation status, 1p19q LOH, IDH1 mutation status, and expression profile on a series of oligodendroglial tumors [anaplastic oligodendrogliomas (AOD) and anaplastic oligoastrocytomas (AOA)] within EORTC study 26951. The series was expanded with tumors of the same histology and treatment from our own archive. Results: Methylation profiling identified two main subgroups of oligodendroglial brain tumors of which survival in the CpG island hypermethylation phenotype (CIMP+) subgroup was markedly better than the survival of the unmethylated (CIMP−) subgroup (5.62 vs. 1.24 years; P < 0.0001). CIMP status correlated with survival, MGMT promoter methylation, 1p19q LOH, and IDH1 mutation status. CIMP status strongly increases the predictive accuracy of survival in a model including known clinical prognostic factors such as age and performance score. We validated our results on an independent data set from the Cancer Genome Atlas (TCGA). Conclusion: The strong association between CIMP status and MGMT promoter methylation suggests that the MGMT promoter methylation status is part of a more general, prognostically favorable genome-wide methylation profile. Methylation profiling therefore may help identify AODs and AOAs with improved prognosis. Clin Cancer Res; 17(22); 7148–55. ©2011 AACR.

Segregation of Non-p.R132H Mutations in IDH1 in Distinct Molecular Subtypes of Glioma

Mutations in the gene encoding the isocitrate dehydrogenase 1 gene (IDH1) occur at a high frequency (up to 80%) in many different subtypes of glioma. In this study, we have screened for IDH1 mutations in a cohort of 496 gliomas. IDH1 mutations were most frequently observed in low grade gliomas with c.395G>A (p.R132H) representing >90% of all IDH1 mutations. Interestingly, non‐p.R132H mutations segregate in distinct histological and molecular subtypes of glioma. Histologically, they occur sporadically in classic oligodendrogliomas and at significantly higher frequency in other grade II and III gliomas. Genetically, non‐p.R132H mutations occur in tumors with TP53 mutation, are virtually absent in tumors with loss of heterozygosity on 1p and 19q and accumulate in distinct (gene‐expression profiling based) intrinsic molecular subtypes. The IDH1 mutation type does not affect patient survival. Our results were validated on an independent sample cohort, indicating that the IDH1 mutation spectrum may aid glioma subtype classification. Functional differences between p.R132H and non‐p.R132H mutated IDH1 may explain the segregation in distinct glioma subtypes.

Intrinsic Molecular Subtypes of Glioma Are Prognostic and Predict Benefit From Adjuvant Procarbazine, Lomustine, and Vincristine Chemotherapy in Combination With Other Prognostic Factors in Anaplastic Oligodendroglial Brain Tumors: A Report From EORTC Study 26951

PURPOSE Intrinsic glioma subtypes (IGSs) are molecularly similar tumors that can be identified based on unsupervised gene expression analysis. Here, we have evaluated the clinical relevance of these subtypes within European Organisation for Research and Treatment of Cancer (EORTC) 26951, a randomized phase III clinical trial investigating adjuvant procarbazine, lomustine, and vincristine (PCV) chemotherapy in anaplastic oligodendroglial tumors. Our study includes gene expression profiles of formalin-fixed, paraffin-embedded (FFPE) clinical trial samples. PATIENTS AND METHODS Gene expression profiling was performed in 140 samples, 47 fresh frozen samples and 93 FFPE samples, on HU133_Plus_2.0 and HuEx_1.0_st arrays, respectively. RESULTS All previously identified six IGSs are present in EORTC 26951. This confirms that different molecular subtypes are present within a well-defined histologic subtype. Intrinsic subtypes are highly prognostic for overall survival (OS) and progression-free survival (PFS). They are prognostic for PFS independent of clinical (age, performance status, and tumor location), molecular (1p/19q loss of heterozygosity [LOH], IDH1 mutation, and MGMT methylation), and histologic parameters. Combining known molecular (1p/19q LOH, IDH1) prognostic parameters with intrinsic subtypes improves outcome prediction (proportion of explained variation, 30% v 23% for each individual group of factors). Specific genetic changes (IDH1, 1p/19q LOH, and EGFR amplification) segregate into different subtypes. We identified one subtype, IGS-9 (characterized by a high percentage of 1p/19q LOH and IDH1 mutations), that especially benefits from PCV chemotherapy. Median OS in this subtype was 5.5 years after radiotherapy (RT) alone versus 12.8 years after RT/PCV (P = .0349; hazard ratio, 2.18; 95% CI, 1.06 to 4.50). CONCLUSION Intrinsic subtypes are highly prognostic in EORTC 26951 and improve outcome prediction when combined with other prognostic factors. Tumors assigned to IGS-9 benefit from adjuvant PCV.

Integrated genomic profiling identifies candidate genes implicated in glioma-genesis and a novel LEO1-SLC12A1 fusion gene.

We performed genotyping and exon‐level expression profiling on 21 glioblastomas (GBMs) and 19 oligodendrogliomas (ODs) to identify genes involved in glioma initiation and/or progression. Low‐copy number amplifications (2.5 < n < 7) and high‐copy number amplifications (n > 7) were more frequently observed in GBMs; ODs generally have more heterozygous deletions per tumor. Four high‐copy amplicons were identified in more than one sample and resulted in overexpression of the known oncogenes EGFR, MDM2, and CDK4. In the fourth amplicon, RBBP5, a member of the RB pathway, may act as a novel oncogene in GBMs. Not all hCNAs contain known genes, which may suggest that other transcriptional and/or regulatory elements are the target for amplification. Regions with most frequent allelic loss, both in ODs and GBMs, resulted in a reduced expression of known tumor suppressor genes. We identified a homozygous deletion spanning the Pragmin gene in one sample, but direct sequencing of all coding exons in 20 other glioma samples failed to detect additional genetic changes. Finally, we screened for fusion genes by identifying aberrant 5′‐3′ expression of genes that lie over regions of a copy number change. A fusion gene between exon 11 of LEO1 and exon 10 of SLC12A1 was identified. Our data show that integrated genomic profiling can identify genes involved in tumor initiation, and/or progression and can be used as an approach to identify novel fusion genes.

Gene expression profiles of gliomas in formalin-fixed paraffin-embedded material

Background:We have recently demonstrated that expression profiling is a more accurate and objective method to classify gliomas than histology. Similar to most expression profiling studies, our experiments were performed using fresh frozen (FF) glioma samples whereas most archival samples are fixed in formalin and embedded in paraffin (FFPE). Identification of the same, expression-based intrinsic subtypes in FFPE-stored samples would enable validation of the prognostic value of these subtypes on these archival samples. In this study, we have therefore determined whether the intrinsic subtypes identified using FF material can be reproduced in FFPE-stored samples.Methods:We have performed expression profiling on 55 paired FF-FFPE glioma samples using HU133 plus 2.0 arrays (FF) and Exon 1.0 ST arrays (FFPE). The median time in paraffin of the FFPE samples was 14.1 years (range 6.6–26.4 years).Results:In general, the correlation between FF and FFPE expression in a single sample was poor. We then selected the most variable probe sets per gene (n=17 583), and of these, the 5000 most variable probe sets on FFPE expression profiles. This unsupervised selection resulted in a better concordance (R2=0.54) between expression of FF and FFPE samples. Importantly, this probe set selection resulted in a correct assignment of 87% of FFPE samples into one of seven intrinsic subtypes identified using FF samples. Assignment to the same molecular cluster as the paired FF tissue was not correlated to time in paraffin.Conclusion:We are the first to examine a large cohort of paired FF and FFPE samples. We show that expression data from FFPE material can be used to assign samples to intrinsic molecular subtypes identified using FF material. This assignment allows the use of archival material, including material derived from large-randomised clinical trials, to determine the predictive and/or prognostic value of ‘intrinsic glioma subtypes’ on Exon arrays. This would enable clinicians to provide patients with an objective and accurate diagnosis and prognosis, and a personalised treatment strategy.

Molecular Subtypes of Gliomas

Gliomas are the most common primary brain tumors with heterogeneous morphology and variable prognosis. However, differences between histological subclasses and grades are subtle, and classifying gliomas is subject to a large inter-observer variability. This variability can result in misdiagnosis of gliomas. As treatment decisions in patients rely mainly on histological classification and clinical parameters, there is an urgent need of developing a more accurate and objective classification model. The identification of specific molecular markers (LOH of 1p19q, IDH1 mutation, MGMT methylation status), as well as molecular clusters based on gene expression have been studied extensively. These specific molecular features within gliomas can help diagnosis, can give a more accurate prognosis, and may also be used to develop personalized targeted therapy in the future.

Abstract 2793: A hypermethylated phenotype in anaplastic oligodendroglial brain tumors is a better predictor of survival than MGMT methylation in the EORTC 26951 study

Proceedings: AACR 102nd Annual Meeting 2011‐‐ Apr 2‐6, 2011; Orlando, FL We have performed methylation profiling (Illumina Human Methylation 27 beadchip) on 69 anaplastic oligodendrogliomas (AOD) or anaplastic mixed oligoastrocytomas (MOA) and one non-diseased normal brain. Fifty-two of these samples were treated as part of the EORTC 26951 study, the primary objective of which was to compare the overall survival (OS) of patients with AOD or MOA treated with radiotherapy (59.4 Gy) vs. ± PCV chemotherapy. Remaining samples were also AOD or MOA and received similar treatment paradigms. Unsupervised clustering using hierarchical ordered partitioning and collapsing hybrid (Hopach) was performed using all or the 10,000, 5,000, 2,000, 1,000, 500, 200 or 100 most variably methylated CpG loci. In all analyses, we identified two main clusters that were highly stable (determined by Fuzzy clustering). In general, these clusters could be separated by predominantly methylated vs. unmethylated CpG loci. Survival (as determined from the date of resection) in the “hypermethylated” subgroup was markedly better than the survival of the unmethylated subgroup (5. 62 vs. 1.24 years, P<0.0001). In fact, methylation profiling was able to better separate long vs. short survivors than histology, MGMT promoter methylation status (as determined by MLPA), 1p/19q LOH (as determined by FISH) or IDH1 mutation status. Methylation phenotype remained an independent prognostic marker in a multivariate analysis that includes diagnosis, age, sex, 1p19q LOH and IDH1 mutation status. We validated our results on methylation profiling data from the cancer genome atlas (TCGA) by assigning TCGA samples to one of the molecular clusters identified in our dataset. 14/80 and 66/80 samples of were assigned to the “hypermethylated” and “unmethylated” cluster respectively. Similar to the initial “test” dataset, survival between the hypermethylated and unmethylated subgroups were significantly different (2.87 vs. 1.02 years, P<0.0001). In conclusion, methylation profiling has identified two main subgroups of oligodendroglial brain tumors. These methylation subgroups correlate better with survival than histology, MGMT promoter methylation, 1p19q LOH and IDH1 mutation status. We are currently integrating methylation data with expression data. Citation Format: {Authors}. {Abstract title} [abstract]. In: Proceedings of the 102nd Annual Meeting of the American Association for Cancer Research; 2011 Apr 2-6; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2011;71(8 Suppl):Abstract nr 2793. doi:10.1158/1538-7445.AM2011-2793

Abstract 3932: Tetraploid gliomas share molecular features with pilocytic astrocytomas

Proceedings: AACR 102nd Annual Meeting 2011‐‐ Apr 2‐6, 2011; Orlando, FL We have performed expression profiling on 276 glioma samples of all histological subtypes, which resulted in the identification of seven distinct molecular subgroups. Interestingly, pilocytic astrocytomas (PAs) (n=6; adults) were assigned to one specific molecular cluster, together with four other, more malignant, gliomas. All the non-PAs were histologically diagnosed as higher grade gliomas with pilocytic features. Interestingly, there was a dramatic difference between survival of PAs and gliomas of other histological subtypes in this molecular cluster (>10.6 years vs. 3.4 (avg.) years; p = 0.03). Validation with an external dataset containing only PAs ([GSE12907][1]) showed that PAs are virtually always assigned to this molecular cluster, confirming the stability of the cluster. However, similar to our dataset, a subset of samples of both the REMBRANDT (8%) and TCGA (1%) datasets was also assigned to this molecular cluster. To further explore the differences between PAs and non-PAs in this molecular cluster, we performed genotyping using SNP 6.0 chip arrays. As reported previously, all PAs have only one larger genetic aberration; a focal amplification on locus 7q34, which is indicative for the presence of the tandem duplication KIAA1549-BRAF. One of the four samples of other histology also had this identical genetic aberration as PAs. The other (3/4) non-PA gliomas showed more genetic aberrations than the PAs. All patients harboring the KIAA1549-BRAF duplication were still alive (“survivors”) at the moment of writing this abstract (survival 10.6-19.6 years), whereas the remaining patients (“non-survivors”) all died within 0.44-2.7 years. High copy EGFR amplification was seen in none of the survivors but all of the other tumors. None of the samples in this cluster showed an IDH1-132H mutation. Closer inspection of the SNP arrays indicated that all non-survivors are tetraploid, whilst tumors of all survivors are near diploid (except for 3n on 7q34). The ploidy of all samples is currently validated using Fluorescence In Situ Hybridization (FISH). Polyploidy was not observed in any of the other molecular clusters. Validation with the REMBRANDT and the TCGA datasets showed that non-PAs assigned to this molecular cluster had a poor survival, similar to the non-PAs in our dataset. Interestingly, tetraploidy and EGFR amplification were also seen in the GBM samples from the TCGA that were assigned to this cluster. Gliomas from other molecular subtypes did not show tetraploidy on SNP chip data. In conclusion, we have discovered and validated a glioma subtype that shares molecular (RNA expression profile) and histological features with PAs. In spite of these similarities (and in contrast to the PAs), such tumors have a relatively poor prognosis. They are characterized by EGFR amplification and a near tetraploid cytogenetic profile. Identification of this specific subtype may have important therapeutic consequences. Citation Format: {Authors}. {Abstract title} [abstract]. In: Proceedings of the 102nd Annual Meeting of the American Association for Cancer Research; 2011 Apr 2-6; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2011;71(8 Suppl):Abstract nr 3932. doi:10.1158/1538-7445.AM2011-3932 [1]: /lookup/external-ref?link_type=NCBIGEO&access_num=GSE12907&atom=%2Fcanres%2F71%2F8_Supplement%2F3932.atom

Abstract 3936: Identifying molecular subgroups of gliomas in formalin fixed paraffin embedded material

Proceedings: AACR 102nd Annual Meeting 2011‐‐ Apr 2‐6, 2011; Orlando, FL Gliomas are the most common primary brain tumors with heterogeneous morphology and variable prognosis. Histological classification, combined with the patients’ prognostic features, often guides treatment decisions. Unfortunately, differences in histology are subtle and therefore, diagnosis is subject to a large interobserver variability. To improve classification, we did expression profiling on fresh frozen tumor material of 276 glioma samples of all histological subtypes. This resulted in seven molecular subgroups, which correlated significantly better with survival than histology. When validated in prospective studies these molecular clusters could contribute to clinical decision making. However, there is a lack of fresh frozen glioma material, and until now clinical studies have been performed on formalin fixed paraffin embedded (FFPE) material. Therefore, we would like to see whether our molecular clusters are reproducible in FFPE material. Expression profiling was performed on 57 paired snap-frozen/FFPE glioma samples of all histological and molecular subtypes and three non-diseased brain samples. We collected FFPE material from the same patients that were included in our previous study (Gravendeel et al. Cancer Res 2009). FFPE expression profiling was performed using Hu\_Ex\_1.0_st “exon” arrays (Affymetrix) in combination with Nugen WT-Ovation technology (FFPE V2 and Exon modules). FFPE expression profiles were assigned to a molecular cluster based on its nearest centroid using the 20.000 most variably expressed exons. Preliminary analysis indicates that approximately 75% of all samples were assigned to the correct molecular cluster. Survival data confirmed that the molecular clusters identified using FFPE material retained significant prognostic value, similar to those obtained using fresh frozen material (p=0.0016). Our data indicate that exon arrays in combination with Nugen WT technology are a suitable platform to perform expression profiling on FFPE samples. We are currently expanding our dataset to include FFPE samples from a large phase III European trial. Citation Format: {Authors}. {Abstract title} [abstract]. In: Proceedings of the 102nd Annual Meeting of the American Association for Cancer Research; 2011 Apr 2-6; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2011;71(8 Suppl):Abstract nr 3936. doi:10.1158/1538-7445.AM2011-3936