EXPLORING THE NEUROBLASTOMA EPIGENOME: PERSPECTIVES FOR THE DISCOVERY OF PROGNOSISTIC BIOMARKERS
M. Ongenaert, A. Decock, J. Vandesompele, F. Speleman
Center for Medical Genetics, Ghent University, Ghent, Belgium (mate.ongenaert@ugent.be)
Neuroblastoma (NB) is a childhood tumor originating from sympathetic nervous system cells. Although recently new insights into genes involved in NB have emerged, the molecular basis of neuroblastoma development and progression still remains poorly understood. The best-characterized genetic alterations include amplification of the proto-oncogene MYCN, ALK activating mutations or amplification, gain of chromosome arm 17q and losses of 1p, 3p, and 11q. Epigenetic alterations have been described as well: caspase-8 (CASP8) and RAS-association domain family 1 isoform A (RASSF1A) DNA-methylation are important events for the development and progression of neuroblastoma. In total, there are about 75 genes described as epigenetically affected in NB cell lines and/or NB primary samples.
Most of these methylation markers are found using ‘candidate gene’ approaches and the methylation frequencies are usually very low. In order to find novel methylation markers that can be used for improved prognosis, we applied a whole-genome methylation screen. This technique relies on capturing with the MBD2 protein, containing a methyl-binding domain (MBD), with a very high affinity towards methylated genomic regions. In an initial phase, MBD2-seq was performed on 8 NB cell lines (where we also had micro-array data of, before and after treatment with DAC). As these results are promising, we will explore the complete methylomes of 45 primary NB tumors.
Based on an integrative analysis (re-expression results, expression micro-arrays, MBD2-sequencing on cell lines), 48 MSP (Methylation Specific PCR) assays were tested on 89 primary neuroblastoma patients of different risk categories. The results of this validation study demonstrate the power of epigenetic biomarkers as several assays are informative for prognosis and survival.
Exploring the neuroblastoma epigenome: perspectives for improved prognosis
1. Exploring the neuroblastoma epigenome:
perspectives for the discovery of prognostic biomarkers
Cytometry 2011, Paris
26/10/2011
Maté Ongenaert
Center for Medical Genetics
Ghent University Hospital, Belgium
2. Overview
Epigenetics - introduction
Introduction
DNA-methylation and histone modifications
The interplay between epigenetics
Applications of epigentics
Mapping the neuroblastoma epigenome
Sequencing the neuroblastoma epigenome
Integrated data analysis
Real-time methylation-assays for improved
prognosis
3. Epigenetics > Introduction
-genetics
Heritable changes to the DNA or histones without
affecting the DNA sequence
A whole range of changes are described
• DNA-methylation
• Histone tail modifications
– Methylation
– Acetylation
– Phosphorylation
– ….
Epigenetic changes are interconnected
6. Epigenetics > DNA-methylation
Isolated CG dinucleotides are in most
cases methylated
Some regions are CG-rich: “CpG islands”
More than half of the promoter regions have a
CpG island
Are not methylated in most cases
7. Epigenetics > DNA-methylation
Is a normal phenomenon
Development, differentiation
• Genes, active only during specific stages of the embryonic development
Genomic imprinting
• Only one of the parental copies is active
Silencing large chromosomal domains, e.g. X-
chromosome
• Mosaic X-chromosome in females
Protection against intra-genomic parasites:
retrotransposons and other junk in the genome
8. Epigenetics > DNA-methylation
Is a normal phenomenon
Development, differentiation
• Genes, active only during specific stages of the embryonic development
10. Epigenetics > DNA-methylation
Dense methylation in promoter regions
causes transcriptional silencing
Blocked binding of transcription machinery
(physical blockage)
In reality, shows to be more complex
Link between DNA methylation and histone
modifications
15. Epigenetics > Detection
Detection of histone modifications
Affinity-based
• Antibodies against modifications
• Enrichment of fragments, bound by antibody
Platforms:
• Chip (ChIP-chip)
• Seq (ChIP-seq)
16. Epigenetics > Detection / Prognosis / Prediction
Detection / Prognosis / Prediction
Require ‘biomarkers’
• Easy to detect using molecular techniques
• Often an ‘early event’
• Suitable biomarker for detection / screening
• Can be detected in blood, urine, sputum (non-invasive sampling)
• Biomarkers in various cancer types
Beyond tumor detection
• Stratification of patient groups
• Stage/grading classification
• Prognosis (survival, disease-free survival >)
• Chemotherapy respons (MGMT in brain cancer – temozolomide >)
• Personalized medicine
17. Epigenetics > Detection / Prognosis / Prediction
Detection / Prognosis / Prediction
DNA-methylation is not random
Can be more frequent than mutations
31. Mapping the neuroblastoma epigenome
Neuroblastoma
Risk factors:
- Age at diagnosis
- MYCN amplification
- INSS Stage
Under- and overtreatment
- Molecular biomarkers - 59 gene signature (qPCR)
- Methylation biomarkers for improved prognosis
32. Mapping the neuroblastoma epigenome
Neuroblastoma
8 neuroblastoma cell lines
• CHP902R, CLBGA, IMR32, LAN2, N206, SHSY5Y, SJNB1, SKNAS
Re-activation after DAC-treatment
• Expression: micro-array Affymetrix HGU-133plus2.0
Sequencing
• Capture with MBD2 antibody – MBD2 has the highest affinity towards
methylated DNA
• Multiplex library preparation (MID tags to identify sample) and
sequencing
• Illumina GAIIx, paired-end sequencing (2x45bp)
33. Mapping the neuroblastoma epigenome
Sequencing
Control of fragment sizes with high sensitivity DNA chips
Concentration determination of the fragmented DNA with Fluostar Optima plate reader
MBD2 immunoprecipitation reaction (MethylCollector Kit)
34. Mapping the neuroblastoma epigenome
Sequencing data analysis
Mapping on the human reference genome
• Input: 45 bp ‘sequence tags’
• Output: mapped sequence reads: chromosome-location
• Coverage: number of tags at a certain genomic location
• In this case: coverage ~ captured DNA fragments ~ MBD2 binding ~
methylation
Peak detection
• Compared to the ‘background’, how unusual is the signal I see in a specific
region
Peak annotation
• Genomic location > Genes / functions / …
Visualisation
38. Mapping the neuroblastoma epigenome
Neuroblastoma methylation
Combine several data sources to filter the most
relevant biomarkers out: integrated data analysis
Very specific for biological question
Purpose: prognostic DNA-methylation biomarker
(risk groups)
Expression results
• High stage vs. low stage
• MYCN amplified vs. MYCN non-amplified
• High risk vs. low risk
Re-expression results
Methylation capture results
39. Mapping the neuroblastoma epigenome
Integrated data analysis
Expression results
• Public expression data from a total of 380 primary NB samples
• Three different arrays, two different platforms
• Uniform scoring scheme (RankProd analysis - ranking statistics)
Re-expression results
• Expression array before and after DAC treatment, 8 NB cell lines
• Score assigned (RankProd)
Methylation capture results
• MBD2 sequencing in 8 NB cell lines
• Score assigned (TSS, p-value peaks, tags/length, FE)