- Open Access
Chromosome 7 gain and DNA hypermethylation at the HOXA10 locus are associated with expression of a stem cell related HOX-signature in glioblastoma
- Sebastian Kurscheid1, 2, 3, 16,
- Pierre Bady1, 2, 3, 4,
- Davide Sciuscio1, 2,
- Ivana Samarzija1, 2,
- Tal Shay5,
- Irene Vassallo1, 2,
- Wim V Criekinge6,
- Roy T Daniel1,
- Martin J van den Bent7,
- Christine Marosi8,
- Michael Weller9, 10,
- Warren P Mason11,
- Eytan Domany12,
- Roger Stupp1, 13,
- Mauro Delorenzi3, 14, 15 and
- Monika E Hegi1, 2Email author
© Kurscheid et al.; licensee BioMed Central. 2015
- Received: 16 September 2014
- Accepted: 8 January 2015
- Published: 27 January 2015
HOX genes are a family of developmental genes that are expressed neither in the developing forebrain nor in the normal brain. Aberrant expression of a HOX-gene dominated stem-cell signature in glioblastoma has been linked with increased resistance to chemo-radiotherapy and sustained proliferation of glioma initiating cells. Here we describe the epigenetic and genetic alterations and their interactions associated with the expression of this signature in glioblastoma.
We observe prominent hypermethylation of the HOXA locus 7p15.2 in glioblastoma in contrast to non-tumoral brain. Hypermethylation is associated with a gain of chromosome 7, a hallmark of glioblastoma, and may compensate for tumor-driven enhanced gene dosage as a rescue mechanism by preventing undue gene expression. We identify the CpG island of the HOXA10 alternative promoter that appears to escape hypermethylation in the HOX-high glioblastoma. An additive effect of gene copy gain at 7p15.2 and DNA methylation at key regulatory CpGs in HOXA10 is significantly associated with HOX-signature expression. Additionally, we show concordance between methylation status and presence of active or inactive chromatin marks in glioblastoma-derived spheres that are HOX-high or HOX-low, respectively.
Based on these findings, we propose co-evolution and interaction between gene copy gain, associated with a gain of chromosome 7, and additional epigenetic alterations as key mechanisms triggering a coordinated, but inappropriate, HOX transcriptional program in glioblastoma.
- Copy Number Alteration
- Increase Gene Dosage
- HOXA Locus
- HOXA10 Promoter
- Normalize Unscaled Standard Error
Glioblastoma (GBM) is an aggressive brain tumor with a median survival of only 15 months. Despite remarkable efforts targeting prominent pathogenetic biological features of GBM, efficacy of novel drugs has been disappointing and significant gains in overall survival have not been made since the introduction of combined radio-chemotherapy comprising TMZ . GBM are notorious for their treatment resistance. This has been attributed to the deregulation of major tumor suppressing and oncogenic pathways , tumor heterogeneity , and exhibition of stem cell-like properties by so called tumor stem cells, or glioma initiating cells (GICs) . GICs represent a subpopulation(s) of tumor cells and are believed to, first, give rise to tumor progeny due to their self-renewing capacities, and second, resist radio- and chemotherapy [5,6].
In line with the notion of GICs’ contribution to treatment resistance, we earlier reported a self-renewal-related, HOX-dominated gene expression signature in GBM associated with significantly worse outcome in patients homogenously treated in a clinical trial with combined chemo-radiotherapy comprising the alkylating agent temozolomide. This association was independent of the predictive effect of MGMT methylation or age . The abnormal expression of a HOX gene signature has been confirmed recently in GICs, where it has been functionally associated with their glioma initiating potential . The importance of HOX gene expression for gliomagenesis and treatment resistance to temozolomide has been emphasized in several studies [8-12]. In 2006, Krivtsov and colleagues first described the inappropriate expression of a HOX gene signature in acute myeloid leukemia (AML) . The authors showed in an elegant experimental mouse model that acquisition of this stem cell related HOX gene signature was associated with MLL-A9 fusion gene-induced leukemogenesis from committed progenitors of the granulocyte lineage, demonstrating for the first time that acquisition of stem cell properties in committed progenitor cells can lead to tumorigenesis.
HOX genes are a highly conserved family of genes encoding homeodomain transcription factors that provide anterior and posterior axial coordinates to vertebrate embryos during development . In mammals, there are four paralogous HOX gene clusters organized on different chromosomes (CHRs). These gene clusters represent loci with extremely high gene density. In humans they are located on CHR7 (HOXA), CHR17 (HOXB), CHR12 (HOXC), and CHR2 (HOXD). The spatial organization of HOX genes is reflected in a 5′-posterior to 3′-anterior expression along the embryonal axes, termed spatial colinearity. Hence, expression of HOXA9-13 is predominantly found in sites of the extremities, while HOXA1-2 expression has been confirmed in, for example, the hindbrain. Although HOX genes are involved in the development of the hindbrain, other non-HOX homeobox genes regulate the development of the mid- and forebrain . The forebrain comprises the ventricular and the subventricular zone, which harbors neural stem cells even in the adult brain, and has been proposed as origin of gliomas in the adult. Although this remains debated, mouse models have provided functional support .
Given that HOX genes are neither implicated in the developmental program of the brain nor expressed in the region of the adult brain that is thought to give rise to gliomas, we speculate that the HOX-signature is acquired during gliomagenesis, contributing stem cell properties. However, the mechanisms underlying the observed aberrant activation of HOX genes in GBM remain elusive. It has been proposed that the PI3K-pathway may be an important upstream regulator of HOXA9 expression that is part of the HOX-signature . A more recent report considered the involvement of MLL (KMT2A) in at least a subset of HOX-high expressing GBM. However, given the limited correlation reported, additional driver mechanisms triggering inappropriate HOX gene expression need to be considered . Previous works have described a remarkable correlation of gene expression levels with gene dosage modulated by pathogenic copy number changes in cancer . Most prominent among the HOX expression signature genes are HOXA genes, as corroborated by other labs [7,8,10]. The HOXA locus is located on CHR7 (7p15.2) that is affected by a copy number gain in up to 80% of GBM . Most interestingly, gain of CHR7 has been proposed recently as the evolutionary first driver event in the development of primary GBM together with loss of one copy of CHR10 . CHR7 harbors a number of potential driver genes, among many passengers that through CHR7 gain associated overexpression may drive/contribute to gliomagenesis. Of these, Ozawa et al. proposed PDGF as a driver gene for primary GBM, based on computational and experimental considerations. Previously we reported a low, but significant correlation between gene copy number of the HOXA cluster and expression of the HOX-signature . However, only 42% of this patient cohort was found to be HOX-high. We therefore hypothesized that additional regulatory mechanisms are required to explain the abnormal expression of HOXA genes, with downstream effects on other HOX-signature genes. Here we present a model explaining the aberrant expression of the HOX-signature in GBM integrating multidimensional molecular data, comprising gene expression, gene copy number, and DNA methylation.
Correlation between DNA methylation and gene expression in clinical GBM samples
Determination of the correlation signature in an independent GBM dataset
Likewise we calculated the correlation matrix between DNA methylation and gene expression in an independent dataset of 106 GBM from The Cancer Genome Atlas (TCGA; Additional file 1: Table S4; mean correlation Figure 1C) visualized in a heatmap in Additional file 1: Figure S3. The similarity of the structure of the correlation matrices was remarkable for these two independent GBM datasets, with an RV-coefficient of 0.84 (simulated P value <0.001 (9,999 permutations), Additional file 1: Figures S3 and S4). Of note, while DNA methylation data was also generated on the 450k platform (used as the common dimension), the expression data originated from different platforms. In the GBM TCGA Agilent data the HOX-signature genes are covered with 53 probes (Additional file 1: Table S5), with probes missing for the ncRNA genes MIR10B and HOTAIRM1.
In order to evaluate the relevance of our findings in the context of the whole CHR7, we tested whether the apparent local enrichment of negative correlation between HOXA gene expression and DNA methylation at the HOXA locus was statistically significant. We determined the negative correlations between 711 RefSeq annotated CHR7 genes and their respective Illumina Infinium 450k probes and plotted the values according to genomic location of the genes (Additional file 1: Figure S5A). Gene set enrichment analysis (GSEA) revealed that the 10 HOXA genes were significantly enriched when testing their positions in the ranked list of the observed correlation coefficients of the 711 CHR7 genes as visualized in Additional file 1: Figure S5B (P value <0.001, Additional file 1: Table S3). A similar result was obtained for the TCGA dataset (P value <0.001; Additional file 1: Figure S5C; Table S3).
The relationship DNA methylation/gene expression depends on CpG location
Next we were interested to evaluate the relationship of the mean correlation methylation/HOX-signature expression (Figure 1B and C) and the structural location of the respective CpGs using the Illumina annotation of the 450k probes (1st Exon, 3′UTR, 5′UTR, gene body, transcription start site (TSS) 1,500, TSS200). We observed that negative correlations between DNA methylation and the HOX-signature expression are primarily found for probes which are located either in the 1st exon of a gene, or within 200 bp of TSS, in line with canonical effects of promoter-CGI methylation on gene expression, while positive mean DNA methylation/gene expression correlations were found for probes located in the 3′UTR, 5′UTR, gene body and within 1,500 bp of TSS. This observation was consistent between the NCH_EORTC and the TCGA dataset (Additional file 1: Figure S6A and B, P value <0.01 and P value <0.05, one-way ANOVA).
DNA methylation at HOXA10 promoter CGI is lower in HOX-high than HOX-low GBM
The 59 GBM (NCH_EORTC) were classified into HOX-high (n = 25) or low (n = 34) based on iterative k-means clustering of the 22 Affymetrix probesets (Additional file 1: Figures S7 and S8). The average expression of the HOX-signature in the HOX-low group is not significantly different from respective measures in non-tumoral brain samples (P value = 0.9, all Welch’s Two-sample t-test) (Additional file 1: Figure S9A). In contrast, the higher mean expression levels of the HOX-signature in HOX-high samples are significantly different to both HOX-low (P value <0.01) and non-tumoral brain samples (P value <0.01). We observed significant differences in the degree of DNA methylation measured for probe cg05092861 between HOX-low and HOX-high samples, with a higher level of DNA methylation in HOX-low samples (P value <0.001). Both were different from non-tumoral brain (n = 4), which showed the lowest methylation levels (P value <0.001), although no expression is detected, while highest levels of DNA methylation were measured in HOX-low samples (non-tumoral brain < HOX-high < HOX-low, Additional file 1: Figure S9B). Similar differences were observed for the adjacent Infinium 450k probe cg01078824.
Correlation between expression and gene copy number
Gene dosage and DNA methylation impact HOX-signature expression
Coefficients of linear models for HOX-signature expression in GBM datasets
Std. Error a
t value b
Pr (>|t|) c
NCH_EORTC (Model 1)
CNA chr7p15.2 (BAC)
NCH_EORTC (Model 2)
CNA chr7p15.2 (BAC)
TCGA (Model 1)
CNA chr7p15.2 (SNP6)
TCGA (Model 2)
CNA chr7p15.2 (SNP6)
Transcriptome at the HOXA locus in GBM derived sphere (GS) lines
Histone marks and promoter methylation at the HOXA10/9 promoters
HOX-signature associated microRNAs
Correlation between microRNAs and mean HOX-signature expression in 106 GBM samples from TCGA, top 2 percentile positively and negatively correlated microRNAs
P value (two-sided)
hsa-miR-196b (HOXA locus)
hsa-miR-10b (HOXD locus)
hsa-miR-196a (HOXB/C locus)
Relationship of the HOX-signature and molecular GBM subtypes
Next we sought to address how the HOX-signature was related to three established molecular GBM classification schemes: (1) the four GBM expression subtypes neural, proneural, mesenchymal, and classical as proposed by Verhaak and colleagues ; (2) the glioma CpG island methylator phenotype (G-CIMP) present in a subgroup of proneural GBM ; or (3) distinction of MGMT promoter methylated vs. unmethylated that has been shown to be highly predictive for benefit from alkylating agent chemotherapy . Expression data from 473 GBM (TCGA, level 2 Agilent) were used to classify samples into either HOX-high (259) or low (214), based on k-means clustering (Additional file 1: Figure S13), and were annotated with the expression subtype classification, including G-CIMP, and MGMT promoter methylation status [2,24] (Additional file 1: Figure S14). We observed an enrichment of proneural GBM in the HOX-high group, while the proneural G-CIMP-positive GBM were under-represented (Additional file 1: Table S8, P value <0.001, Pearson’s Chi-squared test). No significant associations were found in the other three expression subtypes. No correlation was found with expression of PDGF that has been proposed as a gain of CHR7-associated driver gene for G-CIMP negative GBM . Finally, we confirmed our previous finding from the NCH_EORTC dataset  that the MGMT-promoter methylation frequency was not different between the HOX-high and low groups (Additional file 1: Table S9, P value >0.35, Pearson’s Chi-squared test).
In the present study we sought to elucidate underlying molecular mechanisms triggering the inappropriate expression of a HOX-signature. Such a HOX gene dominated expression signature has been associated by others, and us with resistance to temozolomide and conferring of glioma-initiating properties [7,8,11,12].
The hypermethylation of the HOXA locus was associated with gain of CHR7, which is reminiscent of compensation for increased gene dosage, known from X-chromosome inactivation [25-28]. This is further supported by the observation that a significant correlation between DNA methylation and expression was only observed for samples with gain of CHR7 as visualized for HOXA10. The involvement of gene dosage mediated induction of HOX-signature expression is compatible with the observation that HOX-high GBM are under-represented in G-CIMP positive GBM, which reportedly have a much lower frequency of CHR7 gain . The observed correlation between expression of the whole HOX-signature and DNA methylation suggested DNA methylation patterns permissive for expression. However, the regulatory effects leading to coordinated expression of HOXA, C, and D genes, and the other members of the signature, including the stem cell marker PROM1 that are located on other chromosomes, are not yet explained. With the exception of the developing forebrain where HOX genes are repressed , the coordinated expression and silencing of HOX genes is well known from embryonic development. It involves changes of higher chromatin organization and complex regulation implicating long-range control mechanisms which are only partly understood .
HOX genes are tightly regulated through polycomb-repressor complex 2 (PRC2)-mediated tri-methylation of H3K27 . Investigation of GS lines suggested loss of the repressive mark H3K27me3 and gain of the active mark H3K4me3 in the promoter of HOXA10 protein-coding transcript variant 1 in HOX-high GS lines, and was associated with an unmethylated CGI. This observation is in accordance with the detection of HOXA10 protein in HOX-high GS lines, as well as in a subset of GBM . In contrast, the HOX-low GS line lacked the active mark and displayed a methylated HOXA10 promoter. Interestingly, the histone marks in the HOXA9 promoter displayed enrichment of H3K36me3 in the HOX-high GS lines in conjunction with the fully methylated CGI suggested transcriptional elongation. This pattern of histone marks would also be compatible with presence of a HOXA10/9 read-through transcript, as proposed by the RNA-Seq analysis and the respectively annotated HG-133Plus2.0 probes that are part of the HOX-signature. Little is known about the functional relevance of the putative long non-coding RNA gene HOXA10-HOXA9. It has been proposed as candidate for nonsense-mediated mRNA decay (NMD) [31-33].
Non-coding RNAs, like lincRNAs and microRNAs, can be involved in the regulation of HOX gene expression [34-36]. Our HOX-signature also includes several lincRNAs, which are transcribed from the different HOX loci: LOC400043 and HOTAIR from the HOXC locus, HOTAIRM1 from the HOXA locus, and LOC375295 from the HOXD locus. For the lincRNAs HOTAIR and HOTAIRM1 functions have been investigated. HOTAIRM1 can regulate the expression of HOXA genes through facilitating conformational changes to the chromatin, in proximal distal manner [35-38]. An initial suspicion that HOTAIRM1 and other ncRNAs could be directly involved in the regulation of the HOX-signature genes was tantalizing. However, their expression pattern, and the observation that the top three correlated microRNAs are actually transcribed from the HOXA/B/C/D loci, rather suggested that these small and long ncRNAs are more likely ‘caught in the storm’ of a coordinated, but inappropriate HOX transcriptional program.
In conclusion, our results suggest that the aberrant expression of the HOX-signature, which confers stem-cell related properties and resistance to therapy, may be acquired through gene copy gain associated with CHR7 gain. Hypermethylation appears to compensate for gene copy gain at this locus in the HOX-low GBM, preventing CHR7 gain driven increase of expression, while in HOX-high GBM key CpGs in the HOXA locus escape hypermethylation. Gene copy gain and methylation at key CpGs in the promoter of HOXA10 putative non-coding transcript variant 2 are strongly associated with the expression of the whole HOX-signature. These findings are remarkably reproducible in an independent GBM dataset from TCGA. The observed mechanism of escape from DNA hypermethylation may explain overexpression of other gliomagenesis relevant proto-oncogenes located on CHR7 and other loci affected by tumor-related increased gene dosage. Hence, further studies are warranted to investigate the co-evolution of gene copy number changes and epigenetic changes, including tumorigenesis-associated DNA methylation, to identify tumor relevant deregulated genes. Finally, the observation of compensatory DNA methylation at genes with potential proto-oncogenic function should be taken into account when considering epigenetic drugs.
GBM datasets and GBM derived sphere lines
Our patient cohort of 59 GBM patients (NCH_EORTC), for whom Affymetrix HG-133Plus2.0 gene expression and Illumina Infinium 450k DNA methylation data were available, has been treated within clinical trials [39,40]. Patients treated within EORTC 26981 had consented for translational research of their tumor tissues as part of the study protocol. All other patients gave informed consent according to the protocol approved by the local ethics committee (protocol F25/99) and the respective competent Swiss federal authorities (No 1.05.01.10-48). The study protocols conform to the World Medical Association Declaration of Helsinki . Analysis of non-tumoral brain samples and the establishment of the GBM derived sphere lines (GS lines) LN-2207GS, LN-2540GS, LN-2669GS, and LN-2683GS, respective authentication, and the description of the respective original tumors have been published previously [7,42,43]. Briefly, GS lines were cultured under stem cell conditions using DMEM-F12 medium (Invitrogen, 10565–018) supplemented with human recombinant EGF and human recombinant basic FGF (Peprotech, AF-100-15 and 100-18B), 20 ng/mL each, and 2% B27 (Invitrogen, 17504); 50% of the medium was substituted twice weekly.
Bisulfite treatment and methylation-specific (MS) clone sequencing, and DNA methylation profiling
DNA isolated from frozen tissues or cells was treated with bi-sulfite, and methylation profiling was performed using Infinium HumanMethylation450 BeadChip (Illumina). MS clone sequencing was performed as previously described . See also Extended Experimental Procedures.
RNA-Seq of glioma sphere transcriptomes and data analysis
Total RNA isolated from GS cells was depleted from ribosomal RNA and sequencing libraries were prepared using TruSeq Stranded Total RNA with Ribo-Zero Gold (Epicentre, Illumina), followed by paired-end sequencing on Illumina Hiseq (PE 2x50 bp; NXTGNT, University of Gent, Belgium). Details on read-alignment, transcriptome reconstruction and data visualization can be found in the Extended Experimental Procedures.
Chromatin immunoprecipitation followed by quantitative PCR (ChIP-qPCR)
Chromatin was prepared using the MAGnify Chromatin Immunoprecipitation System (Invitrogen), precipitated with antibodies targeting the interrogated histone marks, and DNA quantified using qPCR as previously described . See Extended Experimental Procedures for details on the procedure and antibodies used for immunoprecipitation.
For the NCH_EORTC samples, the Bacterial Artificial Chromosome (BAC) aCGH data were acquired by UCSF Humarray 2.0 and 3.0 platforms containing 2,428 BACs, each spotted in triplicate, distributed over the human genome with an average resolution of 1.4 Mb [18,44]. Details on data processing and analysis are presented in the Extended Experimental Procedures.
Selection of TCGA samples included in the analysis and data processing
We applied two criteria to select samples from TCGA for our validation dataset: First, the gene expression platform should have sufficient coverage of the HOX-signature in terms of probes measuring expression levels of all 21 genes. Second, DNA methylation should be measured with the Illumina Infinium 450k platform, as this provided us a common dimension necessary to assess the similarity between the two datasets. Details on the sample selection are presented in the Extended Experimental Procedures.
Unless otherwise stated, all data processing, analysis, and visualization were performed in R version 3.1.0 . Packages for specific data types and tasks are listed in the relevant sections.
Processing and normalization of Illumina Infinium 450k DNA methylation data
The methylation array data of samples was loaded into R and processed using the BioConductor package ‘minfi’. The detection P-values, probabilities that the target sequence signal was distinguishable from the background, were used to exclude probes with poor quality. The probes that are unsuccessfully measured (p-detection >0.01) in more than 1% of samples were dropped from the dataset. The DNA methylation data from the 450k BeadChip were preprocessed as in Genome Studio (software provided by Illumina) and they were summarized by M-values as recommended by Du et al. .
Processing and normalization of Affymetrix gene expression data
The expression intensities for all probe sets from Affymetrix CEL-files were estimated using robust multiarray average (RMA) with probe-level quantile normalization and the Normalized Unscaled Standard Errors values (NUSE) were used to assess the relative quality of arrays. The R packages affy and affyPLM from BioConductor  were used to establish normalization and NUSE values.
Normalization of Agilent gene expression data
Level 1 Agilent gene expression data were downloaded from the TCGA for 106 samples for which Infinium 450k DNA methylation data were available. The intensities within array were normalized using Loess normalization, followed by quantile normalization between arrays. Missing values were imputed using nearest neighbor averaging method. In a last step, average intensities were calculated for probes, which are present more than once.
HOX classification of samples
We used the scaled and centered gene expression data for the 22 and 53 probes measuring levels of HOX-signature genes in the NCH_EORTC and TCGA samples, respectively. These data were used as input for an iterative k-means clustering procedures. Parameters were chosen to search for the most stable cluster consisting of two to eight groups of samples, and 10,000 iterations were performed. The number of groups was selected based on which number of clusters had the maximum Calinksi-Harabasz criterion value , thus representing the most stable partitioning of samples into groups/clusters. The mean HOX-signature expression levels were then calculated for the different groups and ‘high’ and ‘low’ classes were assigned based on the observed mean population-wide expression levels (means of the HOX-high/-low sample means).
Selection of Illumina Infinium 450k probes
Probes measuring DNA methylation of the promoters of 21 HOX signature genes were selected based on their annotated location, resulting in a list of 400 probes. To reduce the dimensionality of the DNA methylation data, principle component analysis was performed and only the 100 probes with the highest cumulative contribution retained. Further details on the procedure are presented in the Extended Experimental Procedures.
Correlation between gene copy number and expression
Expression data and aCGH profiling were available for 64 GBM samples of the NCH_EORTC cohort. For each of those samples, the median aCGH value and the median gene expression value (after each gene was mean centered and divided by the standard deviation of its expression across those samples) were calculated for each of the 39 autosomal chromosome arms. Pearson correlation coefficients between the median aCGH values and median expression values of all chromosomal arms were calculated per sample as described .
Correlation between DNA methylation and expression
Pearson cross-correlation matrices were computed separately to investigate relationship between the filtered methylation data and HOX expression signature datasets for both NCH_EORTC and TCGA samples. A description of the detailed statistical procedure can be found in the Extended Experimental Procedures.
Correlation of TCGA GBM Agilent gene and microRNA expression data
The correlation between mean HOX-signature gene expression levels and microRNA expression levels were calculated using Spearman’s rho statistic to estimate rank-based measure of association, for 96 of the 106 TCGA GBM samples. The top 2 percentile positively and negatively correlated microRNAs were selected for further inspection.
Additive effect of CNA and DNA methylation on mean HOX-signature expression levels
Gene expression profiles, DNA copy number alteration data (array comparative genomic hybridization (aCGH)) and DNA methylation profiles have in part been previously published [7,24,49], and are available in the Gene Expression Omnibus (GEO) database at  (accession-number: GSE7696; GSE60507; GSE60274). Due to patient privacy concerns, the RNA-Seq data in the form of raw sequencing data will be made available upon request to the corresponding author, MEH. The molecular profiles of GBM from The Cancer Genome Atlas project (TCGA) were downloaded from [2,51,52].
This work was supported by the Swiss National Science Foundation (3100A-138116), the National Center of Competence in Research Molecular Oncology, and the Swiss Cancer League (KFS-29-02-2012). The work of TS and ED was supported in part by a grant from the Leir Charitable Foundation. The results published here are in part based upon data generated by The Cancer TCGA Genome Atlas pilot project established by the NCI and NHGRI. Information about TCGA and the investigators and institutions who constitute the TCGA research network can be found at http://cancergenome.nih.gov/publications/publicationguidelines.
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