DNA methylation analysis of paediatric low-grade astrocytomas identifies a tumour-specific hypomethylation signature in pilocytic astrocytomas
- Jennie N. Jeyapalan1,
- Gabriel T. Doctor1,
- Tania A. Jones1,
- Samuel N. Alberman1,
- Alexander Tep1,
- Chirag M. Haria1,
- Edward C. Schwalbe2, 3,
- Isabel C. F. Morley1,
- Alfred A. Hill1,
- Magdalena LeCain1,
- Diego Ottaviani1,
- Steven C. Clifford2,
- Ibrahim Qaddoumi4,
- Ruth G. Tatevossian5,
- David W. Ellison5Email author and
- Denise Sheer1Email author
© Jeyapalan et al. 2016
Received: 12 February 2016
Accepted: 4 May 2016
Published: 27 May 2016
Low-grade gliomas (LGGs) account for about a third of all brain tumours in children. We conducted a detailed study of DNA methylation and gene expression to improve our understanding of the biology of pilocytic and diffuse astrocytomas. Pilocytic astrocytomas were found to have a distinctive signature at 315 CpG sites, of which 312 were hypomethylated and 3 were hypermethylated. Genomic analysis revealed that 182 of these sites are within annotated enhancers. The signature was not present in diffuse astrocytomas, or in published profiles of other brain tumours and normal brain tissue. The AP-1 transcription factor was predicted to bind within 200 bp of a subset of the 315 differentially methylated CpG sites; the AP-1 factors, FOS and FOSL1 were found to be up-regulated in pilocytic astrocytomas. We also analysed splice variants of the AP-1 target gene, CCND1, which encodes cell cycle regulator cyclin D1. CCND1a was found to be highly expressed in both pilocytic and diffuse astrocytomas, but diffuse astrocytomas have far higher expression of the oncogenic variant, CCND1b. These findings highlight novel genetic and epigenetic differences between pilocytic and diffuse astrocytoma, in addition to well-described alterations involving BRAF, MYB and FGFR1.
Pilocytic astrocytomas (WHO grade I) constitute the majority of paediatric low-grade gliomas (LGGs). They usually arise in the cerebellum but are also found in other sites such as the optic pathways and cerebral hemispheres. Pilocytic astrocytomas typically contain a BRAF fusion but occasionally a BRAF V600E mutation, RAF1 fusion, intragenic duplication of FGFR1, or other rarer alterations are present [21, 65]. Diffuse astrocytomas (WHO grade II) usually occur in the cerebral hemispheres, but are also found in the brainstem and spinal cord. Various genetic alterations have been identified in diffuse astrocytomas, including BRAF V600E mutations, intragenic duplication of FGFR1, structural alterations of the MYB oncogene and gene fusions involving FGFR1, FGFR3, MYB and MYBL1 . Virtually all the key genetic alterations in pilocytic and diffuse astrocytomas give rise to constitutive activation of the ERK/MAPK pathway [10, 20, 43, 65], but these tumour types exhibit significant biological and clinical heterogeneity. While pilocytic astrocytomas are well-circumscribed, non-invasive tumours, diffuse astrocytomas invade surrounding tissue and thus have a worse outcome. It is therefore likely that other factors, such as epigenetics and regulating RNAs, as well as the cell of origin and the developing brain environment, influence the divergent phenotypic behaviour [1, 22]. DNA methylation is altered in both cancer  and during brain development . However, its contribution to paediatric low-grade glioma tumorigenesis has not been extensively studied.
We have conducted a comprehensive analysis of DNA methylation together with gene expression in pilocytic and diffuse astrocytomas from two independent tumour sets (test set n = 27 and validation set n = 59) using the Illumina HumanMethylation450 BeadChip (450K). Comparison between the tumour types and normal brain controls identified tumour-specific differences in the DNA methylation patterns. We identified a hypomethylation signature specific to pilocytic astrocytomas, characterised by differentially methylated CpG sites predominantly in annotated enhancers. Additionally, we were able to show that the AP-1 transcription factor complex is predicted to bind at a number of the differentially methylated CpG sites. The AP-1 complex is formed by dimerisation of the FOS and JUN family of transcription factors and is activated by the MAPK pathway [9, 40]. In this study, the FOS family of transcription factors was found to be up-regulated in pilocytic astrocytomas. The AP-1 gene target CCND1a was also up-regulated in both pilocytic and diffuse astrocytomas, with higher levels of the oncogenic CCND1b transcript expressed in the diffuse astrocytomas.
Materials and methods
Low-grade astrocytoma cohort
The test tumour set consisted of 17 pilocytic astrocytomas and 10 diffuse astrocytomas (Additional file 1: Table S1). Validation tumour set 1 consisted of 23 pilocytic astrocytomas and 8 diffuse astrocytomas and validation tumour set 2 consisted of 45 pilocytic astrocytomas; 6 diffuse astrocytomas and 8 oligoastrocytomas (Additional file 1: Table S1). All tumours were obtained as surgical specimens. Ages of the patients at diagnosis ranged from 3 to 20 years. Access to tumours and linked clinical data was given in accordance with Institutional Review Board and MREC regulations: St Jude Children’s Research Hospital (USA) XPD07-107/IRB; Newcastle (UK) REC ref No 2002/112; Blizard Institute (UK) ICMS/PR/09/77. The controls were human neural progenitor cells (ReN VM cell-line), adult brain, foetal cerebellum, foetal frontal lobe and foetal brain (normal brain, BioChain).
Infinium HumanMethylation450 BeadChip processing
Sample DNA (1 μg) was bisulphite-converted using the EZ DNA methylation kit (Zymo Research) and analysed using the Infinium HumanMethylation450 BeadChip (Illumina Inc.). The samples and 450K BeadChips were processed according to the manufacturer’s protocol at Barts and The London Genome Centre, UK. Pre-processing of the 450K dataset was performed using Genome studio software v.2011.1 (Illumina Inc.). Quality control of bisulphite conversion was performed by calculating the ratio of unmethylated probe to methylated probe. Samples that had incomplete conversion (a ratio >0.2) were removed. Methylation status for each probe is given as a Beta value (β-value). The β-value is the ratio of the methylated probe intensity and the overall intensity (sum of the methylated and unmethylated probe intensities). Pre-processing of the data was then performed using R (version 2.15.0). Peak correction was performed  and probes that contained a minor allele frequency of >5 % within 50 bp of the target site were removed . The Illumina annotation  and an enhanced annotation ( were added to the peak-corrected datasets (Additional file 2: Table S2). We excluded probes located on the X- and Y- chromosomes from further analysis. The dataset generated in this study has been deposited in the Gene Expression Omnibus (GEO) under accession GSE77241.
Differential methylation analysis
Differential methylation analysis was performed using the MethLAB R-based programme  (R version 2.15.0). The programme enables us to identify significantly differentially methylated CpGs from the corrected β-values. The linear model with the factor of interest (tumour type – pilocytic, diffuse, control) was computed, with other varying factors: bead chip number (1–5), BRAF status (fusion, V600E mutation, WT), sample location (infratentorial/supratentorial), age group (foetal/HNSC, <3 years, > = 3 years, >16 years) and gender included. A class covariance and FDR correction (Benjamini-Hochberg) were performed. In this analysis the dependent variable is the β-value for each probe, and the independent variables are phenotypic factors such as tumour type. Further details for each analysis are shown in Additional file 3: Supplementary Methods. The differentially methylated CpG sites of interest had a differential change (delta Beta value) of ≥0.3 with FDR-corrected p-value <0.05. A list of the comparisons performed is shown in Additional file 4: Table S3.
Expression analysis was performed on 8 pilocytic astrocytomas and 10 diffuse astrocytomas from the test tumour set, using Affymetrix Human U133_plus2 arrays . The data were analysed using GeneSpring software (Agilent). Analysis was performed using the RMM model, with median baseline correction and data log2 transformation (Additional file 5: Table S4). For differential expression analysis, the tumour groups were averaged and the difference between the two groups was taken. Differentially expressed genes had a fold change of >2(differential log2 transformed values >1).
Pathway analysis and transcription factor binding motif analysis
Ingenuity pathway analysis (Ingenuity Systems Inc.) was used to identify key signalling and biological pathways from the genes identified as differentially methylated. For the top biological functions and canonical pathways, the log p-value was calculated by Fisher exact Test, with a threshold set at a p-value <0.05. The TFsearch software which utilises the TRANSFAC database  was used to predict transcription factor binding sites 100 bp either side of the differentially methylated CpG sites.
Marmal-aid database analysis
To analyse the differentially methylated CpG sites in published profiles for other brain tumours, we used the Marmal-aid database . Hierarchical clustering and heatmaps were produced using the R-programme fastcluster on R version 2.15.0. The database was used to assess 450K methylation datasets for adult low-grade gliomas (TCGA), adult and paediatric glioblastomas (GSE36278 ) and pilocytic astrocytomas (GSE41826, ). Heatmaps were also produced for validation tumour set 2 and for medulloblastomas .
Bisulphite converted DNA and PCR for pyrosequencing
Quantitative DNA methylation analysis was performed at 7 selected genes using pyrosequencing in the test tumour set and in validation set 2 (Additional file 6: Table S5). Amplification of 50 ng of bisulphite-converted DNA was performed using 0.03 U/μl Platinum Taq polymerase (Life Technologies), 1 x PCR buffer, 3 mM MgCl2, 0.8 mM dNTP, 200 nM forward primer, 200 nM reverse primer, 0.5 M Betaine (Sigma Aldrich) and nuclease-free water. PCR cycling at 92 °C for 10 mins, then 44 cycles at 92 °C for 30 s, 50 °C for 1 min and 72 °C for 40 s, with a final extension step of 72 °C for 5 mins. Strand separation and pyrosequencing were performed at Barts and The London Genome Centre, UK.
Methylation analysis of 11 CpG sites in the CCND1 gene and analysis of the G870A SNP were performed by amplification of 50 ng of bisulphite converted DNA as stated above. The primers amplified a region of 362 bp encompassing exon 4 and the intron boundary (Primers, forward 5′-GTTTTAGATGTGAAGTTTATTTTTAA-3′ and reverse 5′-TATAAAAACCTCCCAACCAATC-3′). The amplicons were Sanger sequenced in both directions to obtain CpG and SNP status.
CCND1 qPCR assay
Conversion of 500 ng of RNA into cDNA was performed using the SuperScript II reverse transcriptase (Life Technologies) following the manufacturer’s protocol. Amplification was performed in duplicate with a technical replicate (n = 2 for cDNA conversion). PCR reactions consisted of SYBR® Green Jumpstart Taq ReadyMix TM (1x; Sigma‐Aldrich), forward and reverse primers (10 μM each), made up to 20 μl with nuclease-free water. Primer sequences for CCND1a (forward – 5′-CTCTCCAGAGTGATCAAGTGTGACCC-3′, reverse – 5′-TGTGCAAGCCAGGTCCACC-3′;; CCND1b (forward- 5′-AACAGATCATCCGCAAACACGC-3′, reverse – 5′-CATGAGTCCTTCCACGATACC-3′; ; GAPDH (forward- 5′‐GTGAACCATGAGAAGTATGACAAC‐3′, reverse- 5′‐ CATGAGTCCTTCCACGATACC‐3′) and TBP (forward - 5′‐CACGAACCACGGCACTGATT‐3′, reverse 5′‐TTTTCTTGCTGCCAGTCTGGAC‐3′). The cycling conditions were 50 °C for 2 min, 95 °C for 10 min, followed by cycles of 95 °C for 15 s, 60 °C for 40 s and 72 °C for 40 s, for 40 cycles. A dissociation stage of 95 °C for 15 s, 60 °C for 1 min, 95 °C for 15 s and 60 °C for 15 s, was included. PCRs were performed on the 7500 Real-Time PCR system (Applied Biosystems®). The fold change was calculated using the ΔΔCT relative quantification method .
MicroRNA Taqman assays
Conversion of 10 ng of RNA into cDNA was performed using the Taqman® MicroRNA Reverse Transcription (RT) kit (Life Technologies) following the manufacturer’s protocol. RT-reaction conditions were 1 x Reverse Transcription buffer, 1 mM dNTP, 3.3 U/μl MultiScribe™ Reverse Transcriptase, 0.25 U/μl RNase Inhibitor, 10 ng RNA sample, 1 x RT microRNA-specific primer and nuclease-free water. RT-reaction was incubated at 16 °C for 30 mins, 42 °C for 30 mins and 85 °C for 5 mins. TaqMan® miRNA assays (Life Technologies) were used to analyse expression levels of microRNAs miR-21* and miR-155, with all samples normalised to control microRNA, miR-423-3p. PCR reaction conditions were 1 ng/μl RT-product, 1x Taqman® Universal PCR master mix II (no UNG), 1 x Taqman® probe and nuclease-free water. PCR cycling conditions were 95 °C for 10 mins, followed by 40 cycles of 95 °C for 15 s and 60 °C for 1 min. Fold changes were calculated relative to the average expression in adult and foetal cerebellum and frontal lobe (n = 7).
Identification of a hypomethylation signature specific to pilocytic astrocytomas
DNA methylation profiles were identified for the test tumour set (11 infratentorial pilocytic astrocytomas; 6 supratentorial pilocytic astrocytomas and 10 diffuse astrocytomas), 4 normal brain control samples and the ReN VM neural stem cell-line using the Illumina Infinium HumanMethylation450 BeadChip [3, 8]. Profiles were then subjected to extensive comparisons, as summarised in Additional file 4: Table S3.
We confirmed our findings by showing good correlation between the 450K BeadChip values with pyrosequencing methylation values for 5 CpG sites (Additional file 3: Figure S1). We also validated the methylation status at selected genes using pyrosequencing on the test tumour set and validation tumour set 1. The genes chosen for validation showed differential methylation between pilocytic astrocytomas and normal brain controls or between pilocytic astrocytomas and diffuse astrocytomas. The genes of interest were the RAS-RAF inhibitor, SPRED2 (Additional file 3: Figure S2; [60, 61]); miR-21, an AP-1 target which is involved in gliomagenesis (Additional file 3: Figures S3 and S5; [11, 55, 56]); miR-155, which is involved in inflammation and the mTOR pathway (Additional file 3: Figures S4 and S5 [37, 62]), and two genes involved in drug resistance, ABCC3 (Additional file 3: Figure S6 [4, 67]) and SELENBP1 (Additional file 3: Figure S7; [18, 47, 66]).
The 315 CpG sites which were predominately hypomethylated in pilocytic astrocytomas were validated in a second set of paediatric low-grade astrocytomas, which were analysed independently with the Illumina 450K system (validation set 2, n = 59; Additional file 3: Figure S8). Additionally, the differences were confirmed to be irrespective of tumour location, as the hypomethylation signature was also present in pilocytic astrocytomas located in the brain stem, diencephalon and optic nerve (Fig. 2b; published pilocytic astrocytoma validation set 3, n = 61; GSE44684 ). To confirm that the distinctive signature was specific for pilocytic astrocytomas, the 315 sites were then examined in published findings of DNA methylation in other brain tumours, using the Marmal-aid database . The hypomethylation signature was not present in other low-grade astrocytomas (adult gliomas –TCGA), paediatric and adult glioblastomas (GSE36278 ), medulloblastomas  or ependymomas (GSE45353 ; Additional file 3: Figures S9 and S10; Additional file 9: Table S8). The signature was also absent in tissue from foetal brain tissue (GSE58885 ; Additional file 3: Figure S11).
We then examined the genomic features of the 315 differentially methylated sites and found that 235 sites (75 %) were in regions of low CpG density, and 182 sites (58 %) were in enhancer regions (Illumina annotated, statistically significant - Chi-square p-value <0.01; 149/182 sites were in regions of low CpG density; (Additional file 10: Table S9). Ingenuity Pathway Analysis of the 185 genes that were directly linked to 217/315 sites showed significant association with Cancer (Additional file 11: Table S10). The remaining 98 CpG sites were located in intergenic regions. We assigned 82 genes to these intergenic sites by finding the closest transcription start sites (TSS) (Additional file 10: Table S9). Differential gene expression of ≥ 2-fold between pilocytic and diffuse astrocytomas was found for 56/267 genes (185 annotated genes and 82 closest TSS-assigned genes; Additional file 12: Table S11).
Functions of genes which show a significant correlation between DNA methylation and gene expression. The majority of genes were hypomethylated and up-regulated in pilocytic astrocytomas compared to diffuse astrocytomas, except the three genes highlighted in bold
MAPK pathway and downstream targets:
Receptors and channels:
Cell morphology, motility and interactions:
Identification of AP-1 binding sites at the differentially methylated CpG sites and up-regulation of AP-1 targets in pilocytic astrocytomas
Comparison of low-grade astrocytomas with normal brain tissue from tumour matched locations
We then examined DNA methylation profiles for infratentorial and supratentorial pilocytic astrocytomas and diffuse astrocytomas, as separate groups, with control tissue appropriate to their respective locations. Published control profiles for cerebellum and cerebral cortex were included [12, 27]. Comparison of infratentorial pilocytic astrocytomas with all cerebellar controls identified 11,671 differentially methylated CpG sites (FDR-corrected p-value <0.05, Δβ > 0.3) (Additional file 17: Table S16; Additional file 4: Table S3, Panel B). The large number of differentially methylated CpG sites could be due to normal cerebellum having a greater neuronal component (3:1 neuronal to non-neuronal) than the tumours, which would contain mainly glial cells. Of the 11,671 differentially methylated sites, 8,108 were associated with 3,925 genes (Additional file 17: Table S16). The distribution of these differentially methylated CpG sites across gene regions is shown in Additional file 3: Figure S14. Analysis of gene expression profiles in these tumours showed that 146 (3.3 %) of the genes had ≥2 fold differences compared to all the cerebellum controls as a single group. Ingenuity Pathway Analysis revealed that the top five pathways associated with the 146 deregulated genes are cellular movement, cancer, amino acid metabolism, cellular growth and proliferation, with the functions including neuritogenesis and neuron development (Additional file 18: Table S17). This was in agreement with previous findings .
Comparison of supratentorial pilocytic astrocytomas and diffuse astrocytomas with all cerebral cortex controls identified 382 and 58 CpG sites (43 sites in common), respectively, that were differentially methylated (Additional file 4: Table S3, Panel C and D; Additional file 19: Table S18 and Additional file 20: Table S19). Comparison of supratentorial pilocytic astrocytomas and diffuse astrocytomas with glial and neuronal components of cerebral cortex  showed that the tumours were more closely related to the glial component, as expected (Additional file 19: Table S18 and Additional file 20: Table S19, Additional file 4: Table S3, Panel E; Additional file 9: Table S8). Hierarchical clustering of the 397 CpG sites clustered all the controls, with two major branches for the majority of the pilocytic astrocytomas and diffuse astrocytomas (Additional file 3: Figure S15). Of the genes that have differential methylation, expression of the down-regulated genes in the pilocytic astrocytomas are involved in neuronal differentiation and brain function, with the up-regulated genes involved in the inflammatory response, apoptosis, metabolic processes and MAPK pathway (Additional file 19: Table S18).
Finally, comparison of infratentorial and supratentorial pilocytic astrocytomas identified only 72 differentially methylated sites, most of which were relatively hypomethylated in infratentorial tumours (Additional file 4: Table S3, Panel F; Additional file 21: Table S20). All 72 CpG sites were also hypomethylated in the infratentorial pilocytic astrocytomas compared to the diffuse astrocytomas. CpG sites included in this group were associated with 28 genes, including NR2E1 and EMX2OS, which had 9 and 3 differentially methylated sites, respectively (Additional file 3: Figure S16 and Additional file 3: Figure S17). A further 21 genes were associated with the intergenic CpG sites, identifying 49 genes as being differentially methylated. From the 49 genes, six genes showed differential expression between the two tumour groups (SHH and NR2E1 up-regulated in supratentorial astrocytomas; IRX2, IRX1, HS3ST1 and LNX1 up-regulated in infratentorial astrocytomas).
We have found that pilocytic astrocytomas have a hypomethylation signature that is independent of tumour location and is absent in other types of paediatric and adult gliomas and normal brain tissue. A subset of the CpG sites is located at intragenic distal enhancer regions of low CpG density, as identified in other malignancies including medulloblastoma [17, 25, 54]. Furthermore, tissue-specific hypomethylation has been found at distal regulatory regions of genes . In a subset of cancer-related genes that are associated with the distinctive signature in pilocytic astrocytomas, the affected sites within the gene body showed greater correlation with expression than the promoter region. Additionally, we identified consensus AP-1 binding sites located at a subset of the affected enhancers in pilocytic astrocytomas and an up-regulation of AP-1 factors and target genes in pilocytic astrocytomas compared to diffuse astrocytomas and normal brain. A high proportion of consensus AP-1 binding sites are reported to be located within introns and intergenic regions, but their function at these locations is not clear .
On further examination of the AP-1 target gene CCND1, we identified up-regulation of CCND1a in both pilocytic and diffuse astrocytomas compared to normal brain control. Interestingly, a truncated transcript, CCND1b has been shown to have oncogenic effects by transforming NIH-3 T3 cells [34, 48] and is expressed in other cancers . CCND1b was expressed at higher levels in diffuse astrocytomas compared to pilocytic astrocytomas. In the low-grade astrocytomas, expression of CCND1b was not linked to SNP status at the splice site or DNA methylation at this exon-intron boundary. High expression of the oncogenic variant CCND1b may therefore be critical for tumorigenesis in diffuse astrocytomas, and suggests that defective splicing mechanisms may be present in these tumours, as shown for other malignancies [38, 64].
Previous studies have shown that the cerebellum contains more hypomethylated genes than the cerebral cortex [26, 63]. Furthermore, DNA methylation patterns are distinct in neuronal and non-neuronal cells, particularly at enhancers and non-CpG sites . The differences in methylation patterns between brain regions could therefore, at least in part, reflect variation in the neuronal:non-neuronal cell ratio [12, 24]. These factors were reflected in our findings when we performed comparisons between the low-grade astrocytomas and normal brain from the tumour location.
Comparison between the infratentorial and supratentorial pilocytic astrocytomas identified 49 genes as being differentially methylated, of which 6 had been identified previously . Our findings may vary due to our supratentorial tumours being located predominately in the cerebral cortex, whereas the tumours in the previous study came from varied supratentorial regions. A key gene identified was NR2E1, which is important in the regulation of neural stem cell expansion and gliomagenesis [31, 68]. It is one of the genes reported to distinguish infratentorial and supratentorial pilocytic astrocytomas by their expression and/or DNA methylation profiles [27, 46]. We also identified other homeobox genes EMX2OS, MEIS1 and PBX3 that play a role in brain development [2, 13, 44, 52, 58].
It remains to be established whether the differences that we have observed arise from the specific genetic changes in pilocytic and diffuse astrocytomas, or whether the profiles reflect the methylation pattern in the cell of origin [9, 36, 41]. Distinct outputs of the MAPK pathway have been identified in melanoma and other malignancies with BRAF V600E and receptor tyrosine kinase mutations. Additionally, genetic alterations in mouse models of brain tumours often interfere with normal differentiation processes and give rise to tumours in a manner that is dependent on the tumour cell of origin, as reviewed recently . Pilocytic astrocytomas in the optic pathway are believed to derive from radial glia cells that are distinct from those giving rise to cerebellar pilocytic astrocytomas [28, 57]. The identity of the tumour precursor cells in non-optic pathway pilocytic astrocytomas, however, remains elusive, even in mouse models . The discovery of a unique methylation signature at a small number of sites may facilitate the identification of tumour precursor cells and in time enable the very earliest stages of tumorigenesis to be better understood.
In summary, pilocytic astrocytomas contain a hypomethylation signature characterised by CpG sites which are located predominantly in annotated enhancers. This signature is specific to pilocytic astrocytomas and is not present in diffuse astrocytomas, other brain tumours or normal brain tissue. The AP-1 transcription factor complex, activated by the MAPK pathway, is predicted to bind at a number of these CpG sites, and FOS transcription factors are up-regulated in pilocytic astrocytomas. Our findings highlight epigenetic differences between pilocytic and diffuse astrocytoma, in addition to the well-documented genomic alterations.
We thank Professor Vardhman Rakyan and Dr Robert Lowe for expertise with the Marmal-aid database, Christopher Matthews for support with 450K quality control, Dr Paul Scotting for the kind donation of hNSCs, and Barts and The London Genome Centre for hybridisation of the Illumina 450 K methylation arrays and the pyrosequencing. This research was supported by Astro Brain Tumour Fund, Brain Tumour Action, Rosetrees Trust, A Kid’s Brain Tumor Cure (The PLGA Foundation), The Brain Tumour Charity, and The American Lebanese Syrian Associated Charities (ALSAC) of St. Jude Children’s Research Hospital.
JNJ, RGT, DWE and DS conceived and designed the experiments. JNJ, GTD, TAJ, CMH and RGT performed the experiments. JNJ, GTD, TAJ, SNA, AT, CMH, ECS, ICFM, AAH, ML, DO and SCC analyseddata. RGT, IQ and DWE provided clinical samples and data. DWE undertook all pathological evaluations. JNJ, GTD, TAJ, CMH and DS provided additional scientific input. JNJ and DS wrote the paper. JNJ, TAJ, RGT, DWE and DS revised the manuscript. All authors read and approved the final manuscript.
The authors declare that they have no competing interests.
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