Outcome prediction and risk assessment by quantitative pyrosequencing methylation analysis of the SFN gene advanced stage, high-risk, neuroblastic tumor patients

Laboratory of Tumor Genetics, Istituto Nazionale per la Ricerca sul Cancro, IST, Genova, Italy.
International Journal of Cancer (Impact Factor: 5.09). 08/2009; 126(3):656-68. DOI: 10.1002/ijc.24768
Source: PubMed
ABSTRACT
The aim of our study was to identify threshold levels of DNA methylation predictive of the outcome to better define the risk group of stage 4 neuroblastic tumor patients. Quantitative pyrosequencing analysis was applied to a training set of 50 stage 4, high risk patients and to a validation cohort of 72 consecutive patients. Stage 4 patients at lower risk and ganglioneuroma patients were included as control groups. Predictive thresholds of methylation were identified by ROC curve analysis. The prognostic end points of the study were the overall and progression-free survival at 60 months. Data were analyzed with the Cox proportional hazard model. In a multivariate model the methylation threshold identified for the SFN gene (14.3.3sigma) distinguished the patients presenting favorable outcome from those with progressing disease, independently from all known predictors (Training set: Overall Survival HR 8.53, p = 0.001; Validation set: HR 4.07, p = 0.008). The level of methylation in the tumors of high-risk patients surviving more than 60 months was comparable to that of tumors derived from lower risk patients and to that of benign ganglioneuroma. Methylation above the threshold level was associated with reduced SFN expression in comparison with samples below the threshold. Quantitative methylation is a promising tool to predict survival in neuroblastic tumor patients. Our results lead to the hypothesis that a subset of patients considered at high risk-but displaying low levels of methylation-could be assigned at a lower risk group.

Full-text

Available from: Stefano Bonassi, Sep 05, 2014
Outcome prediction and risk assessment by quantitative
pyrosequencing methylation analysis of the SFN gene in
advanced stage, high-risk, neuroblastic tumor patients
Barbara Banelli
1
, Stefano Bonassi
2
, Ida Casciano
1
, Katia Mazzocco
3
, Angela Di Vinci
1
, Paola Scaruffi
4
, Claudio Brigati
1
,
Giorgio Allemanni
1
, Luana Borzı
`
1
, Gian Paolo Tonini
4
and Massimo Romani
1
1
Laboratory of Tumor Genetics, Istituto Nazionale per la Ricerca sul Cancro, IST, Genova, Italy
2
Laboratory of Molecular Epidemiology, Istituto Nazionale per la Ricerca sul Cancro, IST, Genova, Italy
3
Laboratory of Neuroblastoma Research, Italian Neuroblastoma Foundation, c/o Istituto Nazionale per la Ricerca sul Cancro, IST, Genova, Italy
4
Laboratory of Translational Pediatric Oncology, Istituto Nazionale per la Ricerca sul Cancro, IST, Genova, Italy
The aim of our study was to identify threshold levels of DNA methylation predictive of the outcome to better define the risk
group of stage 4 neuroblastic tumor patients. Quantitative pyrosequencing analysis was applied to a training set of 50 stage
4, high risk patients and to a validation cohort of 72 consecutive patients. Stage 4 patients at lower risk and ganglioneuroma
patients were included as control groups. Predictive thresholds of methylation were identified by ROC curve analysis. The
prognostic end points of the study were the overall and progression-free survival at 60 months. Data were analyzed with the
Cox proportional hazard model. In a multivariate model the methylation threshold identified for the SFN gene (14.3.3r)
distinguished the patients presenting favorable outcome from those with progressing disease, independently from all known
predictors (Training set: Overall Survival HR 8.53, p 5 0.001; Validation set: HR 4.07, p 5 0.008). The level of methylation in
the tumors of high-risk patients surviving more than 60 months was comparable to that of tumors derived from lower risk
patients and to that of benign ganglioneuroma. Methylation above the threshold level was associated with reduced SFN
expression in comparison with samples below the threshold. Quantitative methylation is a promising tool to predict survival
in neuroblastic tumor patients. Our results lead to the hypothesis that a subset of patients considered at high risk—but
displaying low levels of methylation—could be assigned at a lower risk group.
Neuroblastic tumors (NTs) are the second most common
childhood neoplasia and include two malignant histotypes,
neuroblastoma (NB) and ganglioneu roblastoma (GNB), and
the benign ganglioneuroma (GN).
1
In the last years several clinical and biological criteria
have been identified and are utilized to classify NTs patients
into four ‘‘risk groups’’ (high, intermediate, low and very
low) and this stratification has a direct impact on the clinical
management of the patients and on the choice of the treat-
ment regimen.
2–6
Approximately 50% of the children with malignant NTs
have metastatic disease at diagnosis, a condition that
according to the International Neuroblastoma Staging Sys-
tem (INSS)
5
classifies the patients as stage 4. The recent
consensus approach for risk stratification established by the
International Neuroblastoma Risk Group (INRG) task
force,
6
in agreement with other previous results,
2–5
identi-
fied the INSS stage as the most significant prognostic vari-
able and stage 4 patients are considered as a distinct group.
Importantly, the distinction between stage 4 and stage 1, 2,
3 and 4S patients in the new INRG classification is at the
top of the clinical decisional tree. Stage 4 patients are subdi-
vided into three risk categories (high, intermediate and low)
depending from their age at diagnosis, and, for the children
younger than 18 months, from the MYCN amplification sta-
tus and ploidy.
2,3,6
Intermediate and low risk stage 4 patients generally per-
form well and their life expectancy at 60 months is higher
than 70–80%.
6–8
On the contrary, the majority of the high
risk, stage 4 patients experience rapid and fatal disease pro-
gression and only 20–30% of them show progression free
Key words: neuroblastoma, DNA methylation, pyrosequencing,
predictive oncology, epigenetics
Additional Supporting Information may be found in the online
version of this article.
Grant sponsors: Fondazione Italiana per la Lotta al Neuroblastoma,
Associazione Italiana per la Ricerca sul Cancro (AIRC), Regione
Liguria (Progetto Diagnostica Avanzata), Italian Ministry of Health
and Ministero dell’Universita
`
e della Ricerca Scientifica e
Tecnologica (MURST), Italy
DOI: 10.1002/ijc.24768
History: Received 2 Mar 2009; Accepted 7 Jul 2009; Online 22 Jul
2009
Correspondence to: Massimo Romani, Laboratory of Tumor
Genetics, Istituto Nazionale per la Ricerca sul Cancro (IST-Genova).
Largo Rosanna Benzi 10, Genova 16132, Italy, Fax:
þ39-010-573-7230, E-mail: massimo.romani@istge.it
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and overall survival longer than 60 months despite the intro-
duction of novel multimodal therapeutic protocols. The
favorable outcome observed in a subgroup of patients at high
risk indicates that additional prognostic markers must be
identified and validated to assign the patients to the most
appropriate risk category and, ideally, to identify the most
effective and less toxic treatment plan.
4,9,10
In this respect, the aberrant hyper- or hypomethylation of
gene promoter regions is considered a promising biomarker
of outcome or response to treatment, and the potential clini-
cal application of DNA methylation analysis is actively
investigated.
11,12
In neuroblastic tumors, methylation profiles have been
associated with well known predictors of clinical outcome
13–18
and the observed hypermethylation of mult iple CpG islands
suggested the existence, in analogy with colorectal cancer,
19
of a ‘‘CpG island methylator phenotype’’ (CIMP) associated
with MYCN amplification and disease progression.
15–18
These studies included highly heterogeneous cohorts of
patients at various stages and assigned at different risk cat-
egories. Therefore, the presence of multiple and independ-
ent risk factors made it difficult to determine the full
potential of DNA methylation analysis for the patients’
evaluation and prognostication.
Most of the methylation studies on tumor samples were
conducted by qualitative techniques and the results were gen-
erally expressed as dichotomous data (methylated or unme-
thylated).
20,21
However, this representation does not take into
account the continuous variable nature of this epigenetic
modification that is revealed by quantitative sequence-based
techniques.
22
Furthermore, the Methylation Specific PCR
(MSP) analysis of tumor samples, even from microdissected
material, often shows the concomitant presence of methylated
and unmethylated alleles, whose presence cannot be attrib-
uted merely to infiltrating non cancer cells, confirming the
heterogeneity of methylation in tumors.
23
The significance of the ‘‘partial methylation’’ status
observed in many studies has been generally overlooked.
Quantitative changes of the methylation levels present indi-
vidual variations in normal tissues,
24
and, most importantly,
in cancer tissues and during tumor progression
25,26
suggest-
ing that the simple information of the presence or absence of
methylated alleles may be inadequate to disclose important
clinical and pathological features.
Along this line, the aim of our study was to establish if
the quantitative analysis of DNA methylation, could identify
threshold levels discriminating within the stage 4 high risk
patients, those likely to have a favorable outcome from those
presenting rapidly progressing and fatal disease and, in turn,
if quantitative methylation analysis could be utilized to better
define the risk group of these patients. This study was con-
ducted utilizing a ‘‘class discrimination’’ strategy to determine
the predictive value on the outcome at 60 months of different
levels of methylation in a clinically homogeneous group of
high-risk patients at stage 4.
Material and methods
Ethics statement
The Ethics Committee of the Giannina Gaslini Children
Hospital of Genoa approved the collection, the storage in the
Neuroblastoma Tissue Bank and the utilization of this
material. Informed consent was obtained for all patients.
Genes selection, patients and planning of the study
The genes included in this study were selected on the basis
of previous independent studies conducted on cohorts of
patients at all stages and assigned at different risk groups,
demonstrating that their hypermethylation could be a novel
candidate prognostic marker.
15,16
SFN acts as a cancer suppressor by inhibiting the cell-
cycle progression,
27
RASSF1A is a RAS effector that mediates
cell proliferation and apoptosis,
28
CYP26C1 is a CYP26 family
member involved in the metabolism of retinoids
29
and DCR2
is a decoy member of the TRAIL receptor family.
30
The clinical endpoints examined were the Overall Survival
(OS) at 60 months and the Progression Free Survival (PFS)
in relation with the level of methylation of the genes
examined.
As the INSS stage is the major predictor of outcome in
malignant NT patients,
2,6
to minimize the effect of this prog-
nostic factor we determined the impact of the level of meth-
ylation on OS and PFS only in high risk patients at stage 4,
that is the most common and aggressive mode of presenta-
tion of this disease.
The schematic representation of the study groups is
reported in the Supporting Information Figure 1. The risk
stratification criteria utilized were those of the International
Neuroblastoma Risk Group (INRG) Classification System.
6
Accordingly, stage 4 patients were considered at ‘‘high risk’’
if older than 18 months, irrespectively of other clinical and
biological characteristics or, if you nger than 18 months,
when their tumor presented MYCN amplification. Patients
below 18 months with MYCN-single copy tumors, were col-
lectively considered as a control group at low or intermediate
risk depending from the DNA index of the tumor.
6
The study was initially conducted on a trainin g cohort of
50 high- risk patients that were diagnosed between 1990 and
2003 with neuroblastoma (N ¼ 37; range OS: 1–140 months)
or ganglioneuroblastoma (N ¼ 6; range O S: 14–164 months)
or with malignant NT without further histological classifica-
tion (N ¼ 7; range OS: 7–72 months), and referred to the
Giannina Gaslini Children Hospital, Genov a, Italy (Table 1).
Criteria of inclusion of these patients were that they should
have presented progressive and fatal disease within 60
months from the diagnosis (‘‘short survivors’’) or they should
have had a minimum follow up time of 60 months and
should be alive at the last control (‘‘long survivors’’). Within
this first set, 37 patients were included in the ‘‘short survi-
vors’’ group (median OS: 28 months, range 1–56 months),
and 13 were considered as ‘‘long survivors’’ (median OS: 89
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months, range 61–165 months). MYCN amplification was not
detected in the tumors of these latter patients. Ten long sur-
viving patients were free of disease and 3 had stable disease
at the last control (follow up time of 111, 126 and 131
months, respectively).
As control grou ps we included 16 stage 4 patients at inter-
mediate and low risk. This group was composed by 13 neu-
roblastoma (range OS: 60–149 months), 2 ganglioneuroblas-
toma (OS: 87 and 111 months) and one NT tumor without
further histological classification (OS 72 months). Ten of
these patients were at low risk (DNA index > 1, range OS:
60–149 months); 4 were at intermediate risk (DNA index ¼
1, range OS: 87–129 months). DNA index was not deter-
mined in 2 patients (OS: 63 and 76 months). All these
patients were alive and disease-free after a median follow up
time of 89.6 months. As additional control group we
included 10 patients with benign ganglioneuroma. These
patients were diagnosed between 1994 and 2001, their me-
dian age at diagnosis was 92.8 months (SD: 41.5) and were
all alive and free of disease at the last follow up (median fol-
low up: 62.5 months, range: 14–134 months). None of these
patients presented MYCN amplification or chromosome 1p
alterations, DNA index was 1 in all samples.
We validated the methylation threshold risk-prediction
model on an independent cohort of 72 consecutive patients,
diagnosed between 1992 and 2004. This set of patients
included 65 neuroblastoma (range OS: 5–151 months), 3 gan-
glioneuroblastoma (range OS: 19–66 months) and 4 malignant
NT (range OS: 26–105 months) with no further histological
classification (Table 1). The size of the validation set was
defined according to a calculation based on 90% probability to
detect a treatment difference at a two-sided 5.0% significance
level if the true hazard ratio is 3.0. According to this calcula-
tion a minimum number of 47 patients was required. All the
patients of the validation set were at stage 4 and at high risk;
55 of them were ‘‘short survivors’’ (median OS: 30 months)
and 17 were ‘‘long survivors’’ (median OS: 105 months). How-
ever, differently from the training set, the validation cohort
included 3 patients that died of disease 66, 68 and 89 months
after diagnosis and that were thus classified as ‘‘long survi-
vors’’. Amplification of the MYCN oncogene was present in 5
of the long surviving patients of the validation set.
Table 1. Characteristics of the 138 malignant neuroblastic tumor patients included in the study
Group
1
Training set Validation set
Short survivors Long survivors Long survivors Short survivors Long survivors
Risk group
2
High High Intermediate and low High High
N 37 13 16 55 17
Age at diagnosis
Months. Mean (SD) 46.6 (22.7) 54.8 (44.5) 7.9 (2.8) 56.8 (36.4) 44.1 (28.5)
Histology N%
3
NB 29 (78.4) 8 (61.5) 13 (81.2) 50 (90.9) 15 (88.2)
GNB 2 (5.54) 4 (30.8) 2 (12.5) 2 (3.6) 1 (5.9)
NS 6 (16.2) 1 (7.7) 1 (6.3) 3 (5.5) 1 (5.9)
MYCN amplification N (%) 15 (40.5) 0 (0) 0 (0) 19 (35.2) 5 (29.4)
Chromosome 1p deletion
4
N (%) 11 (33.3) 0 (0) 0 (0) 10 (34.5) 4 (57.1)
Ferritin levels
5
<92 ng/ml (%) 6 (17.1) 7 (53.8) 9 (56.3) 6 (13.3) 3 (20.0)
>92 ng/ml (%) 29 (82.9) 6 (46.7) 7 (43.7) 39 (86.7) 12 (80.0)
PFS median (months) 16.0 74.0 84.0 21.0 104.0
OS median (months) 28.0 89.0 88.5 29.0 104.0
Treatment protocols
Nb97/Nb92
6
(N) 22/10 4/8 3/10 23/17 6/11
Clinical response PR(%)/CR(%)
7,8
16 (50.0)/16 (50.0) 43 (20.8)/9 (69.2) 5 (31.3)/11 (68.7) 30 (62.5)/18 (37.5) 8 (47.1)/9 (52.9)
1
Short survivors: <60 months; long survivors: 60 months.
2
High risk patients (HR): age >18 months or age <18 months and MYCN amplification.
Intermediate risk patients (IR): age <18 months, MYCN not amplified, DNA index ¼ 1: low risk patients (LR): age <18 months, MYCN not amplified,
DNA index >1.
3
NB, neuroblastoma; GNB, ganglioneuroblastoma; NS, not specified neuroblastic tumor.
4
Chromosome 1p deletion was not
determined or was not informative in 69 patients (50%).
5
Ferritin level was not available in 15 patients (10.9%).
6
24 patients (17.3%) were treated
with other protocols (Cojecs, Infant, Nb89, Nb AR-01).
7
36 patients (26%) did not experience tumor recurrence. Clinical response data for 12
patients are missing.
8
PR, partial remission; CR, complete remission.
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Patients that were alive but had a follow up time shorter
than 60 months were excluded from the study.
Tumor samples and DNA isolation
The tumor DNA was retrieved from the Italian Neuroblas-
toma Tissue Bank.
31
A pathologist examined the tumor tissue
utilized for nucleic acid extraction to verify the identity and
homogeneity of the samples. The specimens were collected at
the onset of the disease, before therapy, and tumor cell con-
tent was at least 80%.
DNA was isolated by proteinase K digestion and phenol/
phenol-chloroform extraction.
Methylation analysis
DNA Methylation was determined by pyrosequencing,
32
a
sequence-by-synthesis technique that allows the quantitative
determination of the level of methylation of each of the CpG
doublets within a target sequence.
DNA (1 lg) was modified by sodium bisulfite treatment
as described by Frommer et al.
22
and was subjected to pyro-
sequencing analysis. In a subset of patients, MSP
21
and pyro-
sequencing were conducted in parallel. Experimental condi-
tions and primers for MSP were previously described.
15,16
To
verify the reproducibility of the bisulfite reaction, DNA
derived from at least two different modifications was ana-
lyzed in the same MSP and pyrosequencing reaction.
For pyrosequencing analysis the modified DNA was first
amplified by PCR to generate amplicons that included CpG
sites in the regions previously studied by MSP by us and
other groups.
14–17
Blank reactions (for PCR and pyrose-
quencing) were included in each assay to exclude cross con-
tamination. The amplicons were subjected to pyrosequencing
in a Biotage PSQ 96MA system (Biotage, Uppsala, SW) uti-
lizing the sets of reagents suggested by the supplier of the
instrument. Primers were designed with the Pyrosequencing
Assay Design software (Biotage, Uppsala, SW).
The specificity of the primers was determined in PCR
reactions conducted on unmodified DNA to ensure that only
the modified DNA was amplified.
The comparison between different pyrosequencing runs
was conducted by inserting in random positions of the plates,
control samples whose level of methylation was previously
determined.
The sequence of the primers utilized for pyrosequencing,
the target sequences and the PCR conditions are reported in
the Supporting Information Table I. Each target sequence
included 4 to 7 CpG doublets. MSP primers and reaction
conditions were previously described.
16
Expression analysis
To determine the effect of DNA methylation on the expres-
sion of the SFN gene in neuroblastoma, we cultivated the
LAN1 cell line in the presence of 5 lM 5-Aza-dC (MP Bio-
medicals, LLC. Heide lberg, GER) for 3 days. DNA was
isolated from the cell by proteinase K digestion and phenol/
phenol-chloroform extraction. Total RNA was extracted with
Tryzol (Invitrogen, San Donato Milanese, IT). The level of
methylation of SFN was evaluated by MSP and pyrosequenc-
ing. Induction of SFN expression by demethylation was deter-
mined by qPCR as described by Akahira et al.
33
following
the MIQE guidelines
34
(Supporting Information Table II).
The expression of SFN in primary neuroblastic tumors was
determined in 18 samples belonging to the training and to the
validation cohort by qPCR according to the MIQE guidelines
34
as described in the Supporting Information Tables II and III.
Because of the limited amount of available material, the
tumor RNA was retrotranscribed and amplified utilizing the
WT-Ovation
TM
RNA Amplification System kit (NuGEN
Technologies, San Carlos, CA) according to the Manufac-
turer’s instructions. Retrotranscription and amplification was
conducted in parallel with positive and negative control RNA
(total human reference RNA and LAN1 RNA, respectively).
Statistical analysis
The mean methylation value of the CpG doublets included in
the target se quence was measured for each gene in all sub-
jects, and this value was considered for the statistical analysis
All univariate comparisons between study groups were
performed by ANOVA using the pairwise multiple compari-
sons test. An adjusted significance level of p < 0.05 was used
to test hypotheses after Bonferroni correction. All significance
tests were two tailed and CI was 95% in all cases.
Methylation values, as measured by pyrosequencing, were
dichotomized according to the Receiver Operating Character-
istic (ROC) curves, which identified those values providing
the best separation between long and short survivors.
35
The
threshold values identified with this procedure (85% for SFN,
65% for DCR2, 60% for RASSF1A and 50% for CYP26C1)
were utiliz ed in all subsequent analyses.
Overall Survival is defined as the time elapsed from diag-
nosis to death. Only cancer-related deaths were considered.
Patients that survived were censored at the last date they
were reported to be alive. Progression Free Survival is calcu-
lated from the day of diagnosis to the date of relapse, as
reported in the clinical records. Survival curves were com-
puted according to the Kaplan-Meier method
36
and were
compared by means of the log-rank test.
The Cox proportional-hazards regression model was used
to study in a multivariate setting the effect of DNA methyla-
tion on the overall and progression free survival. The follow-
ing actual confounders: treatment protocol (Nb92, Nb97,
other), clinical response (partial response, complete response,
other), histology (neuroblastoma or ganglioneuroblastoma),
and MYCN amplification (yes; no), age at diagnosis were
included in all models. Although serum ferritin level (<92 or
>92 ng/ml) does not provide clinically relevant information,
it is of prognostic value in high risk, stage 4 patients and was
included in the model.
6
The association between technical repeats of methylation
measures was estimated with the Pearson’s correlation
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coefficient. Statistical analysis was carried out with SPSS for
Windows Version 14.0 (SPSS, Chicago, IL), and STATA sta-
tistical software release 8 (StataCorp, College Station, TX).
Statistical analysis for expression data was performed with
the non parametric Mann-Whitney test (two tailed).
Results
Comparison between MSP and pyrosequencing results and
reproducibility of the assay system
In preliminary experiments we performed MSP and pyrose-
quencing analysis in a subset of 18 high-risk NT patients. In
Figure 1 and in the Supporting Information Figure 2 we
report three representative MSP and the Pyrosequencing
results obtained for each of the four genes considered in our
study. In 57 out of 72 determinations (79%), MSP analysis
revealed the concomitant presence of methylated and unme-
thylated alleles independently from the patients’ outcome. In
these samples, the quantitative pyrosequencing showed meth-
ylation levels ranging from 25.6 to 90.3% for the four genes
confirming the ‘‘partial methylation’’ status that was assigned
by MSP.
The different intensity of the DNA amplification bands
obtained by MSP in the reactions for the methylated and for
the unmethylated alleles only partially reflects the absolute
levels of methylation and likely depends also from the differ-
ent efficie ncy of the two PCR reactions.
Pyrosequencing analysis showed that the CpG doublets,
within the selected target sequences, had a homogeneous
level of methylation (Supporting Information Fig. 2). To
assess the reproducibility of the pyrosequencing determina-
tions we compared the methylation levels of the SFN and
RASSF1A genes in independent experiments and we observed
a strong correlation (>95%) among the different repetitions
(Supporting Information Fig. 3).
Given the consistency of this approach, and the absence
of hot spots of hypermethylation in the CpG doublets consid-
ered, we used for the statistical analysis of each gene the
mean value of methylation.
Quantitative methylation analysis in
neuroblastoma patients
The comparison of the methylation status between short and
long survivors, in the training cohort of patients at high risk,
showed significantly higher levels of methylation for all genes
in the patients that died of disease within 60 months (Table
2). We did not observe statistically significant differences in
the level of methylation between the high-risk long survivors
and the intermediate and low risk patients for the RASSF1A,
CYP26C1 and DCR2 genes (p values comprised between
0.398 and 0.210), whereas a significant difference between
Figure 1. Comparison between MSP and Pyrosequencing results in
a subset on NT patients. In each panel is reported the MSP result
for the primers set detecting the methylated (M) and the
unmethylated (U) target, along with the sample ID number and the
percentage of methylation determined by Pyrosequencing.
Table 2. Methylation level of the SFN, RASSF1A, CYP26C1, and DCR2 genes in NT patients subdivided according to their status
Group (age cut-off)
SFN RASSF1A CYP26C1 DCR2
N
Mean 6 Std.
Error pN
Mean 6 Std.
Error pN
Mean 6 Std.
Error pN
Mean 6 Std.
Error p
Training set
HR short survivors 35 88.78 6 0.81 <0.001 33 80.59 6 3.4 <0.001 37 33.63 6 3.62 <0.001 37 35.47 6 5.25 0.048
HR long survivors 12 71.22 6 2.88 0.039 10 31.49 6 6.41 0.210 13 13.69 6 2.89 0.398 13 19.61 6 5.65 0.326
IR-LR long survivors 14 78.17 6 0.99 15 41.64 6 4.79 16 17.16 6 2.78 16 12.66 6 4.27
Validation set
HR Short Survivors 55 88.00 6 1.05 0.033 50 68.72 6 3.48 0.211
HR Long Survivors 17 80.62 6 3.04 13 56.37 6 8.82
HR, high risk; IR, intermediate risk; LR, low risk.
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Early Detection and Diagnosis
Figure 2. Kaplan-Meier O.S. and P.F.S. estimates in the High Risk group of neuroblastic tumor patients according to the methylation
thresholds. Panel (a) training cohort, panel (b) validation cohort, C.I. was 95% in all cases.
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these two groups of patients was observed for SFN (p ¼
0.039) (Table 2).
The predictive value of DNA methylation levels on the
patients’ outcome was analyzed in univariate and multivariate
models utilizing the thresholds defined by the ROC curves
(85% for SFN, 65% for DCR2 , 60% for RASSF1A and 50%
for CYP26C1).
AsshowninFigure2,PanelA,theKaplan-Meiercurvesfor
OS and PFS estimates showed that the methylation levels of
SFN, RASSF1A and CYP26C1 above the thresholds were
strongly associated to a poorer outcome in the group of high
risk patients (p values for the long-rank tests for OS and PFS
were <0.001 for the three genes). Also the methylation of DCR2
above the threshold level was associated with reduced OS and
PFS although at a lower statistical significance (p < 0.01).
The Cox regression analysis (Table 3), after the adjust-
ment for the effect of know predictors of outcome (age at
diagnosis, MYCN amplification, treatment protocol, ferritin,
histology and clinical response), confirmed the strong predic-
tive value on OS and PFS of methylation above the threshold
for SFN and RASSF1A but not for CY26C1 and DCR2. The
predictive value of hypermethylation of CYP26C1, observed
in univariate analysis, was not confirmed in the multivariate
model likely because the strong association between MYCN
amplification and high levels of methylati on of this gene
(data not shown) made impossible to determine the inde-
pendent contribution of these two markers to poor outcome.
Validation of the threshold levels of methylation
To validate the information provided by the training set of
patients and to assess the robustness of our approach, we
performed a similar analysis in an independent, cohort of 72
consecutive patients at stage 4.
Clinical and demographic variables were sim ilar in case
patients, both in the training and in the validation set, and
no statistically significant differences in OS and PFS were
observed between the two groups (OS p ¼ 0.722; PFS p ¼
0.835) (Supporting Information Fig. 4). All the patients were
diagnosed between 1990 and 2004 and the treatment proto-
cols administered were comparable in the training and vali-
dation sets.
The major differences between the two cohorts were that
the validation set included also patients that, although could
be defined as ‘‘long survivors’’, have died of disease prog res-
sion after 60 months and that the tumors of 5 long surviving
patients in the validation set, and none in the training set,
were MYCN amplified.
The analysis of the validation set was restricted to SFN
and RASSF1A as these were the only genes whose methyla-
tion thresholds significantly differentiated long and short sur-
vivors in a multivariate model.
As shown in Table 2, the difference between the mean of
the methylation in the long and short survivors groups
remained significant only for SFN. Similarly, the Kaplan Maier
estimates for OS and PFS in the validation set and the
Early Detection and Diagnosis
Figure 2. (Continued)
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Int. J. Cancer: 126 , 656–668 (2010)
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multivariate analysis showed that SFN retained its predictive
value as a biomarker of outcome (Fig. 2, Panel B, and Table
3).
The predictive significance of the methylation of RASSF1A
above the threshold of 60% was not confirmed in the valida-
tion set. The stepwise analysis of the Cox regression model
showed that several confounding factors, including MYCN
amplification, contributed at a different extent to this result
whereas no influence of any of the predictors was observed
for SFN.
Furthermore, the quantitative methylation analysis of the
SFN gene conducted on a set of benign ganglioneuroma
showed that the level of methylation of these samples was
not significantly different from that of the patients at inter-
mediate and low risk and, most importantly, also from that
of the long surviving patients at high risk from both the
training and the validation cohorts (Table 4).
Distribution of DNA methylation in NT patients
Previous independent studies have shown that the level of
methylation of some of the genes that define the CIMP phe-
notype in NT follows a bimodal distribution.
15,18
We have
determined the distribution of DNA methylation in our casis-
tic (combining the patients of the training and validation set
for SFN and RASSF1A) and we have observed a trend toward
bimodal distribution only for RASSF1A but not for SFN,
CYP26C1 and DCR2 (Fig. 3).
Interestingly, the cut off methylation values discriminating
between patients with a poor prognosis and long surviving
Table 3. Cox regression analysis in high risk nt patients subdivided according to the threshold of methylation
Gene and methylation
Overall survival Progression free survival
N HR (95% CI) p HR (95% CI) p
Training set
SFN
85% 17 1.00 (–) 1.00 (–)
>85% 30 8.57 (2.29-32.10) 0.001 4.76 (1.64–13.83) 0.004
RASSF1A
60% 16 1.00 (–) 1.00 (–)
>60% 27 5.95 (1.58-22.37) 0.008 4.31 (1.48–12.51) 0.007
CYP26C1
50% 38 1.00 (–) 1.00 (–)
>50% 12 1.60 (0.65–3.92) 0.307 1.25 (0.55–2.86) 0.590
DCR2
65% 40 1.00 (–) 1.00 (–)
>65% 10 1.61 (0.76–3.41) 0.220 1.27 (0.31–5.34) 0.744
Validation set
SFN
85% 17 1.00 (–) 1.00 (–)
>85% 41 4.07 (1.44-11.49) 0.008 4.97 (1.80–13.75) 0.002
RASSF1A
60% 11 1.00 (–) 1.00 (–)
>60% 40 1.63 (0.54–4.93) 0.385 1.92 (0.56–7.05) 0.291
HR’s adjusted for age at diagnosis, MYCN amplification, treatment protocol, ferritin, histology and clinical response.
Early Detection and Diagnosis
Table 4. Comparison of the methylation level of the SFN gene between high and intermediate risk long survivor nt and ganglioneuroma
patients
Group
SFN SFN
N Mean 6 Std. Error p Group N Mean 6 Std. Error p
HR long survivors
(training cohort)
12 71.22 6 2.88 0.121 HR Long Survivors
(Validation Cohort)
17 80.62 6 3.04 0.728
Ganglioneuroma 10 77.88 6 1.14 0.806 Ganglioneuroma 10 77.88 6 1.14
IR–LR long survivors 14 78.17 6 0.99
HR, high risk; IR, intermediate risk; LR, low risk.
Banelli et al. 663
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patients determined with the distribution analysis, was essen-
tially identical to that determined by ROC (data not shown).
Effects of DNA methylation on SFN expression in NT
Hypermethylation is a well-established mechanism for the
control of gene transcription. The genes analyzed in this
study are all down-modulated by methylation in a variety of
tumors and methylation-dependent silencing of CYP26C1,
DCR2 and RASSF1A, but not of SFN, has been already dem-
onstrated in neuroblastic tumors.
14,17,37
To determine if hypermethylation of the SFN promoter
has a functional consequence also in NTs, we cultivated the
neuroblastoma cell line LAN1, which bears a hypermethy-
lated SFN gene (Fig. 4, Panel A), in the presence of the
DNMT inhibitor 5-Aza-dC and we determined the level of
expression of this gene by quantitative PCR analysis. The
result of this experiment is reported in Figure 4, Panels A
and B, and show that the reduction of the methylation level
of the SFN promoter is accompanied by the16-fold increase
of the expression level of the gene.
To determine if epigenetic mechanisms regulate SFN also
in vivo, we have determined its level of expression in a subset
of 18 NT mRNA samples derived from the training and
from the validation cohorts. Within this subset, 11 samples
had a methylation level above the discriminating threshold
and the remaining 7 were below the threshold.
The relative quantification was performed utilizing ßactin
as reference gene and as positive and negative controls, total
human reference RNA and RNA from the neuroblastoma cell
line LAN1, respectively. The result of this analysis, reported
in Figure 4, Panel C, show that in 17/18 tumor samples SFN
expression was absent or strongly reduced using as calibrator
total human reference RNA. Overall, the expression of the
samples whose methylation level was below 85% was signifi-
cantly higher than that of the samples presenting a methyla-
tion level above the threshold (nonparametric Mann- Whitney
test: p ¼ 0.042). In 6 out of the 11 samples above the thresh-
old, but only in 1 out of the 7 samples below the threshold,
the level of expression of SFN was comparable or lower than
that of the fully methylated LAN1 cell line. Overall this find-
ing suggests the existence of a relation between the cut off
value of methylation identified in the present study and the
transcriptional activity of the SFN gene.
Discussion
The stratification of NT patients into ‘‘risk groups’’ is an
essential step for the selection of the most appropriate treat-
ment plan and to impro ve outcome.
2–4,6,38
Nevertheless, even
with the most aggressive multimodal therapies, the treatment
of high risk, advanced stage NT patients remains a major
challenge for the oncologist since only 20 to 30% of these
patients have a life expectancy higher than 60 months.
Figure 3. Distribution of DNA methylation in high risk tumor samples. Histogram of number of cases according to the percentage of
methylation. The gray and black parts of the bars represent the ‘‘long’’ and the ‘‘short survivors,’’ respectively.
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Int. J. Cancer: 126 , 656–668 (2010)
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In an attempt to define novel and stringent criteria for the
more precise stratification of NT patients into risk groups
and, in perspective, to help the design of optimized therapies,
we have utilized the quantitative pyrosequencing methylation
analysis technique, to detect epigenetic alterations predictive
of outcome in high-risk patients at stage 4, that is the most
common form of presentation of this disease.
In the last 5 years the interest for the utilization of epige-
netic signatures for the molecular diagnostics and for the early
detection of cancer has steadily increased.
11,12,39,40
In this
respect, many qualitative or semiquantitative studies have
shown that hypermethylation is a characteristic of the most
aggressive NTs.
13–17
However, the dichoto mization of methyl-
ation data provided by the qualitative or semiquantitative tech-
niques that were utilized in those studies and the heterogeneity
of the patients enrolled, likely has masked major clinical differ-
ences. Indeed the MS P analysis in a subset of the homogeneous
cohort of stage 4, high risk patients analyzed in our study,
showed the concomitant presence of the methylated and of the
unmethylated target in 79% of the samples independently
from the patients’ outcome. This finding suggests that the sim-
ple determination of the presence or absence of methylated
targets might be a reductive approach that cannot disclose the
full potential of epigenetic analysis. Indeed, methylation is a
dynamic process and methylation levels may change during tu-
mor progression,
25,26
suggesting that the quantitative analysis
might identify novel and potentially highly informative prog-
nostic biomarkers in NTs and other tumors.
Bisulfite sequencing
22
of cloned PCR products is consid-
ered the ‘‘gold standard’’ for quantitative methylation analysis
since it can generate the precise methylation map of the tar-
get region. This time-consuming procedure is now being
superseded by qPCR-based procedures, like MethyLight,
41
and by pyrosequencing,
32
two faster techniques, still based on
Figure 4. Methylation and expression analysis of the SFN gene in the neuroblastoma cell line LAN1 and in primary neuroblastic tumors.
a) Demethylation of the neuroblastoma cell line LAN1 by 5-Aza-dC. Control and Control Day 3: LAN1 DNA at Day 0 and after 3 days in
culture with medium alone. 5-Aza-dC Day 3: DNA extracted from LAN1 cells cultivated for three days in the presence of 5 lM 5-Aza-dC.
b) Expression analysis in the LAN1 cell line before and after demethylation with 5-Aza dC; mRNA content was normalized utilizing bActin.
The RNA from control cells at day 0 was utilized as calibrator. Number in parentheses indicate the percentage of methylation of the SFN
gene in the sample. c) Expression analysis of SFN in NT; mRNA content was normalized utilizing bActin. The internal calibrator of
expression was total human RNA. Number in parentheses indicate the percentage of methylation of the SFN gene in the sample.
Early Detection and Diagnosis
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the bisulfite conversion of the unmethylated C into T. These
novel methodologies can detect minimal amount of DNA
methylation and, between the two, we chose pyrosequencing
because it allows to directly measur e the methylation level of
each CpG in the target sequence and to exclude methylation
heterogeneity in the analyzed region.
Our retrospective study was conducted initially on a clini-
cally homogeneous training set of patients at stage 4 that
were all classified at high risk and subdivided into ‘‘long’’
and ‘‘short survivors’’ according to their survival time (> 60
months or < 60 months, respectively). The results obtained
with this set were then validated on an independent cohort
of consecutive patients. Differently from other studies, pyro-
sequencing enabled us to consider methylation as a continu-
ous variable and to apply a standard ROC curves approach
to determine the values which best discriminate the patients
according to their outcome.
The distribution of DNA methylation observed in our cas-
istic confirmed, for RASSF1 A, the trend toward a bimodal
distribution already described in other studies for different
genes
15,18
whereas bimodality was not as well defined or
absent for the other genes. Considering the type of casistic
analyzed in our study (only stage 4 patients at high risk), this
finding was not surprising. Indeed, the studies where the bi-
modal distribution of methylation levels was described
15,18
included patients at all stages and high levels of methylation
were prevalent in advanced stage patients like the casistic
analyzed in this report.
The result of our study showed that the methylation of
the SFN gene above a defined threshold is a strong and reli-
able predictor of adverse outcome independently from other
prognostic factors. Interestingly, we have previously reported
that the SFN gene is partially or fully methylated in benign
and malignant neuroblastic tumors.
16
However, in that early
study, the limits of the qualitative analysis utilized did not
allow to detect the predictive value of SFN methylation on
outcome that was instead fully disclosed by the quantitative
determination herein reported.
The strong predic tive value on outcome of RASSF1A
methylation above the threshold level of 60% that was
observed in the training cohort was not confirmed in the val-
idation set because of the contribution of the other predictors
of advers e outcome in the unselected patients’ population.
The ‘‘methylator phenotype,’’ determined by quantification
of the methylation level of multiple genes,
15
was recently vali-
dated as a significant predictor of PFS in neuroblastoma
patients.
18
One of the questions that remain to be answered is
how the prognostic power of SFN methylation compares to that
of CIMP. In this respect we have confirmed that the level of
methylation of CYP26C1, one of the genes included in the origi-
nal set that defined the CIMP phenotype, is significantly higher
in short surviving as compared to long surviving patients. How-
ever, this gene was excluded from the validation analysis since,
in multivariate analysis, its predictive value was lost likely
because the strong association between MYCN amplification
and high levels of CYP26C1 methylation made impossible to
determine the independent contribution of these two markers to
poor outcome (Ref. 15 and our data not shown).
The quantitative PCR analysis conducted on a subset of
patients demonstrated that the overall expression of SFN is
significantly lower in the samples with a methylation level
above 85% as compared to that of the tumors presenting
lower methylation. This finding indicates that the methyla-
tion threshold identified in our study has a direct functional
consequence and suggests that SFN is a novel candidate gene
involved in neuroblastic tumors.
SFN belongs to the evolutionary highly conserved 14.3.3
gene family that participates to many crucial functions and
pathways like the maintenance of the G2 cell cycle check-
points, DNA repair, apoptosis, cellular senescence and cell
adhesion and motility.
27
SFN is a downstream effector of p53
activated in response to DNA damage and has been impli-
cated in many epithelial tumors.
27
Although SFN expression
traditionally was considered restricted to epithelial cells, the
qPCR analysis herein reported in addition to other our
unpublished observations and to data retrieved from expres-
sion microarray databases (http://www.ncbi.nlm.nih.gov/geo/),
showed that SFN could be detected in a variety of normal and
tumor tissues of different species and in a subset of neuroblas-
toma cell lines and tumors.
Although additional work will be obviously necessary to
determine if SFN has a specific role in NT pathogenesis, it is
of interest to observe that the overexpression of SFN inhibits
AKT, an oncogene involved in cell survival and a down-
stream target of TRK, a gene implicated in NT pathogenesis
and in its clinical behavior.
42,43
Furthermore, it has been demonstrated that the p53
homologue p73 is a more efficient activator of SNF than p53
itself
44
and that the transactivation-deficient variant of the
third member of the p53 family, DNp63, acts as a strong
repressor of SNF transcription.
45
It will be of interest to
determine if also the transactivation-deficient and oncogenic
p73 variant DNp73, that when overexpressed is a molecular
marker of adverse outcome in NT,
46
acts as a repressor of
SNF transcription.
Neuroblastoma and ganglioneuroblastoma are among the
first tumors where biological factors like MYCN amplifica-
tion, ploidy, and expression of selected genes or chromo-
somal rearrangements and deletions, were recognized as criti-
cal determinant s of the patients’ outcome
38
and some of
them are utilized to define risk categories and to optimize
therapeutic strategies.
2–4,6
In this respect, our result s lead us
to hypothesize that low levels of methylation of the SFN gene
could identify a subset of NT patients that by standard crite-
ria are considered at high risk but that instead could be
assigned at a lower risk group either because their disease is
less aggressive or is more responsive to treatment. It can be
foreseen that microarray techniques, capable to detect multi-
ple targets of aberrant methylation, could be coupled with
quantitative methylation analysis to develop new generation
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Int. J. Cancer: 126 , 656–668 (2010)
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platforms for a more accurate prediction of the patients’ out-
come and, ideally for their assignment to the most appropri-
ate risk category and to the optimal treatment plan.
In conclusion, our data demonstrate the power of quanti-
tative DNA methylation analysis in risk assessment and to
the best of our knowledge, define for the first time a thresh-
old level of methylation associated with the clinical character-
istics and survival of advanced stage, high risk NT patients.
Furthermore, the observation that survival is tightly linked
to the extent of methylation provides a strong rationale to
the exploitation of the epigenome as a target for innovative
experimental therapies in neuroblastic tumors.
Acknowledgements
The authors thank the patients and their families for the constant co-opera-
tion. They also thank the physicians of the Giannina Gaslini Children Hos-
pital, Genova, that have provided clinical records and Prof. Riccardo Rosso
(IST-Genova) and Dr. Bruno De Bernardi (G. Gaslini Children Hospital,
Genova) for their suggestions, advice and support. Dr. Barbara Banelli and
Dr. Katia Mazzocco are fellows of the Fondazione Italiana Per la Lotta al
Neuroblastoma.
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    • "Stratifin (SFN, 14-3-3 sigma) is a member of the 14-3-3 family that interacts with p53, to initiate cell cycle checkpoints after DNA damage [17]. In a small study of neuroblastomas (n=47 (test); n=58 (validation)), hypermethylation of the SFN promoter in tumour DNA was associated with poorer progression-free and overall survival [18]. However, in our study we have not examined methylation of the promoter region, but rather an intragenic CpG site previously demonstrated to show DNA methylation variability between individuals [8]. "
    [Show abstract] [Hide abstract] ABSTRACT: We have addressed whether inter-individual methylation variation in somatic (white blood cells, WBCs) DNA of ovarian cancer patients provides potential for prognostic and/or pharmacoepigenetic stratification. WBC DNA methylation was analysed by bisulphite pyrosequencing at ataxia telangiectasia mutated (ATM), estrogen receptor 1 (ESR1), progesterone receptor (PGR), mutL homologue 1 (MLH1), breast cancer susceptibility gene (BRCA1), secreted frizzled-related protein 1 (SFRP1), stratifin (SFN), retinoic acid receptor beta (RARB) loci and the repetitive element LINE1 in 880 SCOTROC1 trial patients [paclitaxel (Taxol)-carboplatin versus docetaxel (Taxotere)-carboplatin as primary chemotherapy for stage Ic-IV epithelial ovarian cancer]. We observed no significant associations (P < 0.005, after correction for multiple testing) for progression-free survival (PFS) using test and validation sets. However, we did identify mean SFN methylation associated with PFS (hazard ratio, HR = 1.01 per 1% increase in methylation, q = 0.028); particularly in the paclitaxel (HR = 1.01, q = 0.006), but not in the docetaxel arm in stratified analyses. Furthermore, higher methylation within the ESR1 gene was associated with CA125 response (odds ratio, OR = 1.06, q = 0.04) and with neuropathy (HR = 0.95, q = 0.002), but only in the paclitaxel arm of the trial. This is the first study linking DNA methylation variability in WBC to clinical outcomes for any tumour type; the data generated on novel prognostic and pharmacoepigenetic DNA methylation biomarkers in the circulation now need independent further evaluation.
    No preview · Article · Oct 2013 · Annals of Oncology
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    • "Similarly to what we have observed for the SFN gene [10], the overall distribution of the PCDHB methylation levels observed in our series of high risk stage 4 patients did not follow the bimodal distribution described by Abe et al [14] for a population of patients with neuroblastoma representative of all stages of the disease ( Figure S1). "
    [Show abstract] [Hide abstract] ABSTRACT: Approximately 20% of stage 4 high-risk neuroblastoma patients are alive and disease-free 5 years after disease onset while the remaining experience rapid and fatal progression. Numerous findings underline the prognostic role of methylation of defined target genes in neuroblastoma without taking into account the clinical and biological heterogeneity of this disease. In this report we have investigated the methylation of the PCDHB cluster, the most informative member of the "Methylator Phenotype" in neuroblastoma, hypothesizing that if this epigenetic mark can predict overall and progression free survival in high-risk stage 4 neuroblastoma, it could be utilized to improve the risk stratification of the patients, alone or in conjunction with the previously identified methylation of the SFN gene (14.3.3sigma) that can accurately predict outcome in these patients. We have utilized univariate and multivariate models to compare the prognostic power of PCDHB methylation in terms of overall and progression free survival, quantitatively determined by pyrosequencing, with that of other markers utilized for the patients' stratification utilizing methylation thresholds calculated on neuroblastoma at stage 1-4 and only on stage 4, high-risk patients. Our results indicate that PCDHB accurately distinguishes between high- and intermediate/low risk stage 4 neuroblastoma in agreement with the established risk stratification criteria. However PCDHB cannot predict outcome in the subgroup of stage 4 patients at high-risk whereas methylation levels of SFN are suggestive of a "methylation gradient" associated with tumor aggressiveness as suggested by the finding of a higher threshold that defines a subset of patients with an extremely severe disease (OS <24 months). Because of the heterogeneity of neuroblastoma we believe that clinically relevant methylation markers should be selected and tested on homogeneous groups of patients rather than on patients at all stages.
    Full-text · Article · May 2013 · PLoS ONE
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    • "These candidate genes were selected based either on prior knowledge of NB tumor biology or on the fact of being methylated in other tumor types. As a consequence, only few DNA methylation biomarkers, such as KRT19, TNFRSF10D, CASP8, ZMYND10 and RASSF1A, were previously related with NB risk factors or survival [11,13141518,3738394041. In order to identify new DNA methylation biomarkers in NB, we applied a multilevel experimental approach. "
    [Show abstract] [Hide abstract] ABSTRACT: Background Accurate outcome prediction in neuroblastoma, which is necessary to enable the optimal choice of risk-related therapy, remains a challenge. To improve neuroblastoma patient stratification, this study aimed to identify prognostic tumor DNA methylation biomarkers. Results To identify genes silenced by promoter methylation, we first applied two independent genome-wide methylation screening methodologies to eight neuroblastoma cell lines. Specifically, we used re-expression profiling upon 5-aza-2'-deoxycytidine (DAC) treatment and massively parallel sequencing after capturing with a methyl-CpG-binding domain (MBD-seq). Putative methylation markers were selected from DAC-upregulated genes through a literature search and an upfront methylation-specific PCR on 20 primary neuroblastoma tumors, as well as through MBD- seq in combination with publicly available neuroblastoma tumor gene expression data. This yielded 43 candidate biomarkers that were subsequently tested by high-throughput methylation-specific PCR on an independent cohort of 89 primary neuroblastoma tumors that had been selected for risk classification and survival. Based on this analysis, methylation of KRT19, FAS, PRPH, CNR1, QPCT, HIST1H3C, ACSS3 and GRB10 was found to be associated with at least one of the classical risk factors, namely age, stage or MYCN status. Importantly, HIST1H3C and GNAS methylation was associated with overall and/or event-free survival. Conclusions This study combines two genome-wide methylation discovery methodologies and is the most extensive validation study in neuroblastoma performed thus far. We identified several novel prognostic DNA methylation markers and provide a basis for the development of a DNA methylation-based prognostic classifier in neuroblastoma.
    Full-text · Article · Oct 2012 · Genome biology
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