Genome-wide methylation analysis shows similar patterns in Barrett’s esophagus and esophageal adenocarcinoma
Advance Access publication August
Genome-wide methylation analysis shows similar patterns in Barrett's esophagus and esophageal adenocarcinoma
EnpingXu 1 2 3 4
JianGu 1 3 4
Ernest T.Hawk 0 1 3
Kenneth K.Wang 1 3 6
MaodeLai 1 2 3
MaoshengHuang 1 3 4
JafferAjani 1 3 5
XifengWu 1 3 4
0 Division of Cancer Prevention and Population Sciences, The University of Texas MD Anderson Cancer Center , Houston, TX 77030 , USA
1 Abbreviations: ADAM, A Disintegrin And Metalloproteinase; BE , Barrett's esophagus; EAC, esophageal adenocarcinoma; NE, normal esophageal; ROC, receiver operating characteristic
2 Department of Pathology, School of Medicine, Zhejiang University , Hangzhou, Zhejiang 310058 , China
3 Epidemiology, Unit 1340, The University of Texas MD Anderson Cancer Center , 1155 Pressler Street, Houston, TX 77030 , USA. Tel:
4 Department of Epidemiology, The University of Texas MD Anderson Cancer Center , Houston, TX 77030 , USA
5 Department of Gastrointestinal Medical Oncology, Division of Cancer Prevention and Population Sciences, The University of Texas MD Anderson Cancer Center , Houston, TX 77030 , USA
6 Division of Gastroenterology and Hepatology, Mayo Clinic , Rochester, MN 55905 , USA
Barrett's esophagus (BE) is a precursor of esophageal adenocarcinoma (EAC). To identify novel tumor suppressors involved in esophageal carcinogenesis and potential biomarkers for the malignant progression of BE, we performed a genome-wide methylation profiling of BE and EAC tissues. Using Illumina's Infinium HumanMethylation27 BeadChip microarray, we examined the methylation status of 27578 CpG sites in 94 normal esophageal (NE), 77 BE and 117 EAC tissue samples. The overall methylation of CpG sites within the CpG islands was higher, but outside of the CpG islands was lower in BE and EAC tissues than in NE tissues. Hierarchical clustering analysis showed an excellent separation of NE tissues from BE and EAC tissues; however, the clustering of BE and EAC tissues was less clear, suggesting that methylation occurs early during the progression of EAC. We confirmed many previously reported hypermethylated genes and identified a large number of novel hypermethylated genes in BE and EAC tissues, particularly genes encoding ADAM (A Disintegrin And Metalloproteinase) peptidase proteins, cadherins and protocadherins, and potassium voltage-gated channels. Pathway analysis showed that a number of channel and transporter activities were enriched for hypermethylated genes. We used pyrosequencing to validate selected candidate genes and found high correlations between the array and pyrosequencing data (rho > 0.8 for each validated gene). The differentially methylated genes and pathways may provide biological insights into the development and progression of BE and become potential biomarkers for the prediction and early detection of EAC.
Esophageal cancer is a highly aggressive malignancy. In the USA,
there will be an estimated 17 990 new cases and 15 210 deaths in
2013 (1). Despite advances in treatment for patients with esophageal
cancer, the 5 year overall survival rate remains <20% because most
patients are diagnosed with advanced stage disease (2). Survival rates
for patients with esophageal cancer could be improved if more patients
were diagnosed at an early and potentially curable stage. Therefore, it
is critical to identify clinically applicable biomarkers that can be used
for the early detection and targeted prevention of esophageal cancer.
These authors are co-last authors of this study.
The two major histological types of esophageal cancer, esophageal
squamous cell carcinoma and esophageal adenocarcinoma (EAC),
have striking geographic differences in their incidences: esophageal
squamous cell carcinoma is predominant in Asian countries, whereas
EAC is the most rapidly increasing solid tumor in the Western world
and currently accounts for ~80% of new esophageal cancer cases in
the USA (3,4). Barretts esophagus (BE) is the precursor lesion of
EAC in which the squamous epithelial cells in the esophageal mucosa
are replaced by premalignant columnar epithelial cells. BE is the most
important risk factor for the development of EAC. The incidence of
EAC in patients with BE is 30100 times higher than in the general
population (57). However, a recent large population-based cohort
study estimated that the risk of malignant progression in BE patients
is 0.22% per year (8). This low absolute risk of progression calls for
more accurate risk stratification in BE patients for better informed
preventive and/or therapeutic interventions. Independent objective
biomarkers are needed to complement and enhance risk stratification
of BE patients based on pathological grading.
It is now widely recognized that epigenetic alterations are associated
with the process of neoplastic transformation (9). DNA methylation is
one of the most important epigenetic alterations and plays a critical
role in the development of human malignancies (10). Promoter regions
are usually enriched with CpG dinucleotides, known as CpG islands
(11,12); hypermethylation of these islands is associated with
transcriptional repression of tumor suppressor genes, whereas
hypomethylation is associated with increased expression of oncogenes (1316). The
identification of specific DNA methylation sites could not only provide
significant biological insights into the development and progression of
cancer but also discover novel biomarkers for early detection,
diagnosis and prognosis of cancer (17,18). To identify novel biomarkers
during the malignant progression of BE, in this study, we performed
a genome-wide methylation profiling in a large series of BE and EAC
tissues in comparison with normal esophageal (NE) tissues.
Materials and methods
Human tissue samples
A total of 117 EAC tissue samples, 77 BE tissue samples and 94 samples
of adjacent NE tissue from the surrounding esophagus were included in this
study. The EAC, BE and NE tissues were collected as described previously
(1921). All tissues were snap frozen at the time of diagnostic or therapeutic
endoscopic biopsies using a tissue collection protocol approved by the
institutional review board. Experienced pathologists performed histologic readings
of the corresponding juxtaposed paraffin-fixed specimens. Only those with
>70% tumor cells (for EAC tissue) or metaplasia/dysplasia (for BE tissue)
were included in this study. All tissues were from patients diagnosed as having
EAC. Acorresponding normal squamous tissue sample was collected from a
healthy appearing mucosa at least 3 cm from the edge of the apparent tumor
from each patient by a gastroenterologist. All tumors were staged according to
the criteria in the sixth edition of the American Joint Commission on Cancer
DNA extraction and bisulfite conversion
Genomic DNA was extracted using a QIAamp DNeasy Blood and Tissue Kit
(Qiagen, Valencia, CA) according to the manufacturers instructions. DNA
concentration was assessed with an ND-1000 spectrophotometer (NanoDrop
Technologies, Wilmington, DE) and the average fragment length was assessed
by gel electrophoresis. Bisulfite conversion of genomic DNA from each
sample was done using the EZ DNA Methylation Kit (Zymo Research, Orange,
CA), which converts unmethylated cytosines to uracil but leaves methylated
Bisulfite-converted genomic DNA was analyzed using Illuminas Infinium
Human Methylation27 BeadChip Kit (San Diego, CA). This array targets
27 578 unique CpG sites located within the proximal promoter regions of
the transcription start sites of 14 495 genes. The methylation profiling was
performed according to the manufacturers protocol. Briefly, ~200ng of
bisulfite-converted DNA was applied per chip. During hybridization, the DNA
molecules were annealed to two different bead types with locus-specific DNA
oligomersone for the methylated locus and another for the unmethylated
locus. The single-base extension of the probes incorporated a labeled
dideoxynucleoside triphosphate, which was subsequently stained with a
fluorescence reagent. The methylation status of each interrogated CpG site was then
calculated as the value, defined as ratio of the fluorescent signals from the
methylated allele to the sum of the methylated and unmethylated alleles. The
value is a quantitative measure of DNA methylation levels of specific CpGs
and ranges from 0 (completely unmethylated) to 1 (completely methylated).
Validation of Infinium methylation platform by pyrosequencing
The methylation change of the five differentially methylated genes between
NE and BE samples were validated by pyrosequencing, a
sequencing-bysynthesis method that quantitatively monitors the real-time incorporation of
nucleotides through the enzymatic conversion of released pyrophosphate into
a proportional light signal. After bisulfite treatment and PCR, the degree of
methylation of each CpG position in a sequence was determined from the
ratio of thymine to cytosine. We used the Vacuum Prep Tool (Qiagen) to
prepare single-stranded PCR products according to manufacturers instructions.
Pyrosequencing was performed using a PyroMark Q96 System (Qiagen)
according to manufacturers protocol.
We used Bead Studio Methylation Module software (Illumina) to assess the
differences in methylation levels for different samples and groups. The results
from pyrosequencing and the values from the methylation assay were
correlated using the Spearman rank correlation. Asupervised hierarchical cluster
analysis was performed using the average linkage method. All statistical tests
were two-sided. For all tests, P < 0.05 was used as the level of significance. The
DAVID bioinformatics tool (23,24) was used to determine the enrichment of
individual gene ontology terms and to map genes onto the Kyoto Encyclopedia
of Genes and Genomes pathway maps. The enriched gene ontology terms were
reported as clusters to reduce redundancy. The P value for each cluster is the
geometric mean of the P value for all the gene ontology categories in the
cluster. BenjaminiHochberg multiple testing correction was used to control false
Overall methylation profiles of NE, BE and EAC tissues
We assessed the methylation status of 27 587 CpG sites across 14 495
genes in a total of 288 esophageal tissues (94 NE, 77 BE and 117
EAC). Prior to determining differential methylation, we removed
probes that failed in any one of the samples (n = 68) and probes in
chromosomes X and Y (n = 1092). As described previously (25,26),
we also removed those probes with values in all samples being 0.8
or 0.2 to reduce the number of non-variable sites from subsequent
analyses (n = 8689). This resulted in a final data set of 17729 probes
for further analysis. Within this probe set, 10 836 CpG were within
CpG islands and 6893 CpG were outside CpG islands. Comparison of
mean values revealed no differences in overall CpG methylation in
the NE, BE and EAC tissue samples (Table I). However, when CpG
island and non-CpG island sites were analyzed separately, we found
significant differences between the distributions of methylation
profiling in the NE, BE and EAC tissue samples. Within the CpG islands,
the overall methylation (mean values of all sites) in NE tissue was
significantly lower than the BE and EAC tissues. In contrast, outside
CpG islands, the overall methylation in NE tissue was significantly
higher than the BE and EAC tissues.
Hierarchical clustering of NE, BE and EAC tissues
We performed a supervised hierarchical clustering to differentiate
these tissues (Figure1). We first randomly split all the samples into
a discovery and a validation set. We selected the top 10 differentially
methylated CpG sites with the smallest P values of mean value
difference between each pair-wise comparison of tissues (i.e. BE versus
NE, EAC versus NE and EAC versus BE) and used them to cluster
corresponding tissues. The clustering of NE tissues from BE and EAC
tissues was excellent; however, the clustering of BE and EAC tissues
was much less clear (Figure1AC). When we used the same 10 CpG
sites to cluster tissues in the validation set, there was again excellent
clustering of NE from BE or EAC tissues, but the BE and EAC tissues
were interspersed (Figure1DF).
Receiver operating characteristic curve
To further evaluate the value of the methylated CpG sites in
discriminating BE and EAC from normal tissues, we constructed a
receiver operating characteristic (ROC) curve by plotting
sensitivity versus specificity (Figure 2) using the top 10 differentially
methylated CpG sites. The area under the ROC curve, a commonly
used indicator for estimating the diagnostic efficacy of a potential
biomarker, was calculated. For discriminating BE from NE tissues,
the area under the ROC curve was 0.965 (sensitivity: 94.81%,
specificity: 91.49%), and for discriminating EAC from NE tissues, the
area under the ROC curve was 0.973 (sensitivity: 94.87%,
specificity: 93.62%), suggesting the excellent value of these differentially
methylated CpG sites in discriminating BE or EAC tissues from
All CpG sites
CpG sites inside
CpG sites outside
SD, standard deviation.
*P values for the difference between NE tissue and BE tissue.
**P values for the difference between NE tissue and EAC tissue.
***P values for the difference between BE tissue and EAC tissue.
Differentially methylated CpG sites and host genes
in BE/EAC tissues
There were a large number of differentially methylated individual
CpG sites between NE and BE/EA tissues. Of particular interest
are those sites within CpG islands that had low methylation ( <
0.2) in NE tissues but showed significant hypermethylation ( >
0.5) in BE/EA tissues. The host genes of these hypermethylated
CpG sites are potential tumor suppressors. Tables II and III showed
the top 20 hypermethylated CpG sites and host genes from
pairwise comparison of BE versus NE and EAC versus NE,
respectively. All these CpG sites showed consistent hypermethylation in
both BE and EAC tissues, among which SFRP1 (27), GBX2 (28),
ADAM12 (29), PTGDR (30), DMRT1 (31), PTPRT (32), SH3GL3
(33), LAMA1 (34), COL15A1 (35) and AJAP1 (36,37) have been
reported previously to be hypermethylated in various cancers. In
addition to these top 20 CpG sites, a complete examination of
those differentially methylated CpG sites found several
interesting gene families: ADAM (A Disintegrin And Metalloproteinase)
and ADAMTS (ADAM with Thrombospondin Motifs) peptidase
family, cadherins and protocadherins, and potassium voltage-gated
channels (Supplementary Table 1, available at Carcinogenesis
We also compared the methylation status of EAC tissues with that
of BE tissues (Supplementary Table 2, available at Carcinogenesis
Online). There were no CpG sites that fit the same criteria set
previously (i.e. < 0.2 in BE tissues but > 0.5 in EAC tissues).
There were also many hypomethylated CpG sites in pair-wise
comparison of BE versus NE, EAC versus NE and EAC versus BE
(Supplementary Tables 35, available at Carcinogenesis Online),
most of which were likely resulted from global hypomethylation in
Validation of differentially methylated CpG sites by pyrosequencing
The methylation of the five differentially methylated CpG sites
between NE and BE tissues in the discovery set (SLC18A3, CACNB2,
SH3GL3, CHRNA3 and SFRP1; Table II) was validated by
pyrosequencing after bisulfite conversion. There was a strong correlation
between the methylation levels of each CpG site as assayed by these
two methods (rho > 0.8 for each one; Table IV), demonstrating
technical reproducibility of the Illumina array method. Pyrosequencing
is a highly specific method with little non-specific noise. Therefore,
the methylation level detected by pyrosequencing was generally lower
than that detected by the Illuminaarray.
Pathway analysis of hypermethylatedgenes
We then used the DAVID bioinformatics tool to explore the potential
pathways involved in EAC development using 107 hypermethylated
genes ( < 0.2 in NE tissues and > 0.5 in BE/EA tissues). The
hypermethylated genes were enriched for genes involved in cell adhesion,
cell motion, cell surface receptor-linked signal transduction, cell
cell signaling, regulation of transcription and so on (Supplementary
Table 6, available at Carcinogenesis Online). The top significant
Kyoto Encyclopedia of Genes and Genomes pathways included
transcriptional activity, sequence-specific DNA binding, and a number of
channel and transporter activities.
Fig.2. ROC curve analysis of the diagnostic efficacy of 10 common
differentially methylated CpG sites in BE and EAC in all samples. (A)
ROC curve for discriminating NE tissues from BE. (B) ROC curve for
discriminating NE tissues from EAC. AUC, area under the ROC curve.
Carcinogenesis of EAC involves a multistep process from intestinal
metaplasia to low- and high-grade dysplasia and finally to
adenocarcinoma (38). It is well known that epigenetic events are involved in this
process. Two distinct DNA methylation alterations play fundamental
roles in cancer development: global hypomethylation and regional
hypermethylation of tumor suppressor genes (9,10,15). In this study,
we found that within the CpG islands, the overall methylation in BE
and EAC tissues was significantly higher than that in normal tissues.
The CpG islands are considered the most relevant for expression of
the corresponding gene, and hypermethylation of these islands is
associated with transcriptional repression of tumor suppressor genes.
The similar findings in the other tumor type have been reported
(34,39). On the other hand, we found that the overall methylation
outside CpG islands in BE and EA tissues was significantly lower than
that in normal tissues. Unlikely CpG sites inside CpG islands, CpG
sites outside CpG islands are usually not involved in regulating gene
expression. The methylation level outside CpG islands reflects more
of global methylation than specific gene promoter methylation. These
data are consistent with literature that global hypomethylation and
promoter hypermethylation of specific tumor suppressor genes are
both involved in the development of BE and EAC (4042).
Our hierarchical clustering analysis showed an excellent separation
of NE tissues from BE and EAC tissues; however, the clustering of BE
and EAC tissues was less clear. In addition, we could find numerous
individual CpG sites that showed low methylation ( < 0.2) in normal
tissues but were hypermethylated ( < 0.5) in BE and EAC tissues;
however, there was not a single CpG site that had low methylation
( < 0.2) in BE tissues but was hypermethylated ( < 0.5) in EAC
tissues. None of the hypomethylated CpG sites in EAC compared with
BE had a decreased value of >0.2 (Supplementary Table5, available
at Carcinogenesis Online). These observations suggest that
hypermethylation occurs early during the progression of EAC and plays
a more prominent role in driving metaplasia and dysplasia formation
than carcinoma development. Similar to our results, Smith etal. (43)
compared the methylation of nine known hypermethylated genes in
NE, BE and EAC tissue samples and demonstrated high similarity of
aberrant DNA methylation in BE and EAC. Taken together, these data
support that BE is a pre-cancerous lesion with profound molecular
alterations that are similar to carcinoma.
The identified individual hypermethylated CpG sites and host genes
are of particular interests because these genes are candidate tumor
suppressor genes for BE and EAC development. Among the top
differentially hypermethylated genes in BE/EAC tissues (Tables II and III),
several genes have been reported previously to be hypermethylated in
BE/EAC tissues and other cancers, such as SFRP1 (27), whereas many
others, including GBX2 (28), ADAM12 (29), PTGDR (30), DMRT1
(31), PTPRT (32), SH3GL3 (33), LAMA1 (34), COL15A1 (35) and
AJAP1 (36,37), were reported in other cancers. For new
hypermethylated genes, membrane transporter and ion channel genes were
unusually frequent, including genes encoding SLC18A3 (a vesicular
amine transporter), CACNB2 (a voltage-dependent calcium channel),
CHRNA3 (a ligand-gated ion channel), SLC6A2 (a multipass
membrane transporter of sodium and neurotransmitter; Table II) and the
simultaneous hypermethylation of a large number of potassium-gated
channels (Supplementary Table1, available at Carcinogenesis Online).
It is also interesting that many channel and transporter pathways were
enriched for hypermethylated genes (Supplementary Table 7,
available at Carcinogenesis Online). It is tempting to speculate that chronic
exposure to bile acid may cause physiological and pathological changes
of the membrane transporters and channels, which may contribute to
metaplasia. Another notable observation was the high frequent
simultaneous hypermethylation of genes encoding cell matrix and cell
adhesion proteins, such as COL5A1 (collagens), AJAP1 (an adherens
junction-associated protein), LAMA1 (a laminin; Tables II and III)
and a large number ADAM, ADAMTS, cadherins and
protocadherins (Supplementary Table1, available at Carcinogenesis Online). The
hypermethylation of some of these genes is likely involved in cellular
histology and morphology changes because the BE tissues are
columnar compared with the squamous nature of normal tissues.
Among the newly identified hypermethylated genes, IRX4 is
a homeobox transcription factor, and a recent study showed that it
can suppress prostate cancer cell growth through the interaction with
vitamin D receptor and there was a significant interaction between
IRX4 and vitamin D receptor in their reciprocal transcriptional
regulation (44). PTPRT is the most frequently mutated protein tyrosine
phosphatase in human cancers and can suppress colorectal cancer cell
The Illumina methylation array constitutes a robust platform that
produces reliable and highly reproducible data. It has been compared
with other platforms by previous studies and has shown consistent
results, with correlations ranging consistently >0.8 (46). Our
correlation study of the five differentially methylated CpG sites between
Illuminas array data and pyrosequencing data supports the
technical reliability of Illuminas array platform. The recapitulation of most
previously reported hypermethylated genes further support the
reproducibility of this technology. Illuminas Methylation27 assay detects
the methylation status of ~2 CpG sites per gene for most genes. For
genes with multiple CpG loci on the array, we found all the loci to be
differentially methylated in the same direction. One recent study that
used the same platform to analyze DNA methylation changes during
long-term culture of mesenchymal stromal cells found that closely
positioned CpGs on the microarray revealed very similar methylation
patterns (47). These observations suggest that aberrant methylations
are not restricted to an individual CpG site but rather affect nearby
CpG sites and the entire CpG islands.
SD, standard deviation.
SD, standard deviation.
The major strength of this study was the large sample size of
samples. There were 288 tissue samples included in this study, making
this study one of the largest whole-genome methylation array studies.
There are a few limitations to this study. First, this is a cross-sectional
study to compare one time collection of tissues from different
individuals. All the BE tissues in this study were obtained from patients who
have developed EAC. It is possible that these BE tissues may have
more rampant methylation aberrations than tissues from BE patients
in the general population who would never develop EAC. Future
prospective studies are warranted to compare methylation in BE patients
who develop and those who do not develop EAC to identify predictive
biomarkers for BE progression.
In conclusion, this large-scale study provides strong evidence that
DNA methylation plays an important role in the development of BE
and EAC. The methylation pattern of BE and EAC is remarkably
similar. The differentially methylated genes identified in this study
may provide biological insights into the development and progression
of BE and become potential biomarkers for the prediction and early
detection of EAC.
Supplementary Tables 17 can be found at http://carcin.oxfordjour
Pyrosequencing (%of methylated C)
SD, standard deviation.
National Institutes of Health (CA111922 and CA138671); the
Premalignant Genome Atlas Program of the Duncan Family Institute
for Cancer Prevention and Risk Assessment at The University of
Texas MD Anderson Cancer Center; MD Anderson Cancer Center
Start-up Fund (to J.G.).
Conflict of Interest Statement: None declared.
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Received March 15 , 2013 ; revised July 15 , 2013 ; accepted August 16, 2013