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RESEARCH ARTICLE
Aberrant DNMT3B7 expression correlates to
tissue type, stage, and survival across cancers
Safia Siddiqui, Michael W. White, Aimee M. Schroeder, Nicholas V. DeLuca, Andrew
L. Leszczynski, Stacey L. Raimondi*
Department of Biology, Elmhurst College, Elmhurst, Illinois, United States of America
*raimondis@elmhurst.edu
Abstract
Cancer cells are known for aberrant methylation patterns leading to altered gene expression
and tumor progression. DNA methyltransferases (DNMTs) are responsible for regulating
DNA methylation in normal cells. However, many aberrant versions of DNMTs have been
identified to date and their role in cancer continues to be elucidated. It has been previously
shown that an aberrant version of a de novo methylase, DNMT3B7, is expressed in many
cancer cell lines and has a functional role in the progression of breast cancer, neuroblas-
toma, and lymphoma. It is clear that DNMT3B7 is important to tumor development in vitro
and in vivo, but it is unknown if expression of the transcript in all of these cell lines translates
to relevant clinical results. In this study, a bioinformatics approach was utilized to test the
hypothesis that DNMT3B7 expression corresponds to tumor progression in patient samples
across cancer types. Gene expression and clinical data were obtained from the Genomic
Data Commons for the 33 cancer types available and analyzed for DNMT3B7 expression
with relation to tissue type in matched and unmatched samples, staging of tumors, and
patient survival. Here we present the results of this analysis indicating a role for DNMT3B7
in tumor progression of many additional cancer types. Based on these data, future in vitro
and in vivo studies can be prioritized to examine DNMT3B7 in cancer and, hopefully,
develop novel therapeutics to target this aberrant transcript across multiple tumor types.
Introduction
The American Cancer Society estimates that nearly 1 out of every 3 people will be diagnosed
with cancer in their lifetime [1]. While treatments have significantly improved and patient sur-
vival has increased in the last decade, cancer continues to be a global health issue and
improved targeted therapies are needed. However, due to the heterogeneity of tumors, it has
been difficult to identify one gene or protein that could be targeted to improve treatments
across multiple cancer types.
It has been well-documented that cancer cells are characterized by abnormal DNA methyla-
tion patterns that alter gene expression and function [2,3]. Tumor suppressor genes are often
hypermethylated and transcriptionally inactive while oncogenes are hypomethylated and
active. Normal methylation is regulated by three DNA methyltransferases (DNMTs)–
PLOS ONE | https://doi.org/10.1371/journal.pone.0201522 August 2, 2018 1 / 10
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OPEN ACCESS
Citation: Siddiqui S, White MW, Schroeder AM,
DeLuca NV, Leszczynski AL, Raimondi SL (2018)
Aberrant DNMT3B7 expression correlates to tissue
type, stage, and survival across cancers. PLoS
ONE 13(8): e0201522. https://doi.org/10.1371/
journal.pone.0201522
Editor: Aamir Ahmad, University of South Alabama
Mitchell Cancer Institute, UNITED STATES
Received: June 4, 2018
Accepted: July 17, 2018
Published: August 2, 2018
Copyright: ©2018 Siddiqui et al. This is an open
access article distributed under the terms of the
Creative Commons Attribution License, which
permits unrestricted use, distribution, and
reproduction in any medium, provided the original
author and source are credited.
Data Availability Statement: RNAseqV2 and
clinical data were obtained from the Genomic Data
Commons (GDC) Legacy Archives data portal
(https://portal.gdc.cancer.gov/legacy-archive/
search/f) and all relevant analysis and results are
within the paper.
Funding: This work was supported by the Ellen
Marks Cancer Foundation (SLR). The funders had
no role in study design, data collection and
analysis, decision to publish, or preparation of the
manuscript.
DNMT1, DNMT3A, and DNMT3B [4–6]. DNMT1 is a maintenance methylase that is active
throughout life while DNMT3A and DNMT3B are de novo methylases that are normally active
in early development.
Recently, it has been shown that aberrant versions of DNMT3B are expressed in cancer
cells, but not normal cells, and their functional role is still being elucidated [7–11]. Specifically,
one of these aberrant transcripts, DNMT3B7, is expressed in 21 out of 25 cancer cell lines
tested, including both solid and hematopoietic malignancies, making it a novel target that
could potentially be used to treat many cancers at once [7]. DNMT3B7 retains 94bp of intron
10 sequence leading to an early stop codon and truncated protein. Furthermore, this truncated
protein retains functional activity as observed by the fact that cell lines stably expressing
DNMT3B7 show altered methylation patterns [7]. Shah and colleagues were the first to show
that increased DNMT3B7 expression promotes lymphomagenesis in mice and alters methyla-
tion patterns in vivo as well as in vitro [9]. Subsequently, our laboratory has shown that expres-
sion of DNMT3B7 promotes tumor progression in breast cancer cells leading to
hypermethylation of E-cadherin and corresponding changes in cell adhesion, proliferation,
and anchorage-independent growth [10]. Interestingly, expression of DNMT3B7 in neuroblas-
toma showed an opposing effect in that lower levels of the transcript corresponded to tumor
progression as measured by increased cell proliferation, angiogenesis, and tumor formation
[11]. It is possible that differences in DNMT3B7 function may be related to cell type, such as
changes between epithelial and mesenchymal cells, but additional studies are needed.
Because DNMT3B7 is expressed in so many different cancer cell types, and retains an intron
sequence not found in other genes, it is an attractive target for novel targeted therapies. How-
ever, while we know that DNMT3B7 is expressed in multiple cancer cell lines, it is unknown
whether this altered expression is observed in clinical samples. Furthermore, in order to eluci-
date the role of DNMT3B7 across all cancer types, in vitro and in vivo studies are required.
Studies of this size and nature are both time-consuming and costly, therefore our laboratory
utilized a bioinformatics approach to test the hypothesis that DNMT3B7 expression promotes
tumor progression across cancers as measured by expression in normal versus tumor tissues,
staging, and patient survival. The results of this study provide useful information on which
cancer types should be further examined in vivo with the ultimate goal of developing novel
therapeutics to target this aberrant transcript and potentially treat many different cancer types.
Materials & methods
Collection of data from Genomic Data Commons
RNAseqV2 and clinical data were obtained from the Genomic Data Commons (GDC) Legacy
data portal (https://portal.gdc.cancer.gov/legacy-archive/search/f) [12]. Data were organized
and processed using a custom C# script and Microsoft Excel (Redmond, Washington) to analyze
expression of the retained 94bp sequence of intron 10 that is specific to DNMT3B7. Analyses
were conducted on all available patient data for every cancer type available. Clinical staging was
measured as stage I (combination of stage I, stage IA, and stage IB), stage II (combination of
stage II, stage IIA, stage IIB, and stage IIC), stage III (combination of stage IIIA, stage IIIB, and
stage IIIC), or stage IV. In order to determine survival rates, the median of DNMT3B7 expres-
sion across all tumor samples at a given site was determined. The samples were then divided in
half, based on the median, into “low” and “high” expression groups and compared [13].
Statistical analysis
All statistical analysis was performed using SigmaStat software (Systat, Chicago, IL). Tumor
versus normal tissue expression was compared using a Student’s T-test while matched tissues
Aberrant DNMT3B7 expression correlates to tissue type, stage, and survival across cancers
PLOS ONE | https://doi.org/10.1371/journal.pone.0201522 August 2, 2018 2 / 10
Competing interests: The authors have declared
that no competing interests exist.
were compared with a Pairwise T-Test. Comparisons among groups for staging were analyzed
with a one-way ANOVA with Dunn’s multiple comparisons. Finally, Survival LogRank analy-
sis was utilized to generate a Kaplan-Meier curve and compare survival rates among low and
high DNMT3B7 expression groups.
Results
DNMT3B7 expression is up-regulated in a majority of patient tumor
samples
In order to determine the role of DNMT3B7 in tumor progression across 33 cancer types, all
available data from the GDC were downloaded and analyzed for expression of the 94bp intron
sequence specific to DNMT3B7.Table 1 shows the complete results of our analysis, with statis-
tical significance indicated where appropriate.
Of the 21 samples in which both normal and tumor tissues were available, 14 (67%) showed
increased expression of DNMT3B7 in tumor samples compared to normal tissue, while two—
KICH and THCA—showed decreased expression in tumor samples compared to normal (Fig
1A–1C). Of the 16 tumor types that showed significant differences in expression between nor-
mal and tumor tissue, 11 had similar patterns in matched patient samples, indicating that
these results were not due to outliers in the group but rather genetic changes occurring in
patients as their tumor developed and progressed (Fig 1D and 1E). Finally, while 12 of the
tumor types did not have normal tissues available for analysis, three of these—GBM, LGG, and
OV—did have primary and recurrent tissue samples which were utilized for comparison. Of
these three tumor types, LGG showed increased expression in recurrent tumors compared to
primary tumors (Fig 1F).
DNMT3B7 expression correlates to increased stage in some cancers
In order to further assess the effects of DNMT3B7 expression on clinical tumor progression, an
analysis of expression based on diagnostic staging was completed. Of the 22 tumor samples for
which data were available, 7 (32%) showed changes in expression relative to stage. In almost all
cases, DNMT3B7 expression increased as clinical stage advanced indicating that DNMT3B7
expression correlates with tumor progression as measured by stage. Fig 2 shows the results of
every cancer type with significant results except for BRCA, for which these data were published
previously by our laboratory [10].
High expression of DNMT3B7 correlates with poorer survival in six tumor
types
A final analysis was completed to determine the effect of high DNMT3B7 expression on
patient survival. While survival is not a direct measure of tumor progression, due to the
availability of therapeutics for specific malignancies, ability to diagnose some tumors at early
stages, etc., we thought it was important to determine if there was any relationship between
DNMT3B7 and survival as part of this analysis. Therefore, patients in each cancer type were
divided into a “high” and “low” expression group based on the median DNMT3B7 expression
for that cancer. A Kaplan-Meier analysis was completed and significant results are shown in
Fig 3. Of the 33 cancers tested, only 6 (18%) showed a significant change in survival. In all
cases, patients with high expression of DNMT3B7 had lower survival rates than those with
low expression.
Aberrant DNMT3B7 expression correlates to tissue type, stage, and survival across cancers
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Table 1. Results of DNMT3B7 expression across all cancer types.
Cancer Name GDC
Name
Sample
Size
Normal vs. Tumor Matched
Normal vs. Tumor
Stage Survival
Adrenocortical Carcinoma ACC 79 NA NA No No
Bladder Urothelial Carcinoma BLCA 430 Yes (p<0.001) Yes (p<0.001) No No
Breast Invasive Carcinoma BRCA 1097 Yes (p<0.001) [10] Yes (p<0.001) [10] Yes (p = 0.01)
[10]
No
(p = 0.053)
Cervical Squamous Cell Carcinoma and
Endocervical Adenocarcinoma
CESC 309 Yes (p = 0.022) No NA Yes
(p = 0.025)
Cholangiocarcinoma CHOL 45 No NA No No
Colon Adenocarcinoma COAD 334 Yes (p<0.001) Yes (p<0.001) No No
Lymphoid Neoplasm Diffuse B cell Lymphoma DLBC 48 NA NA NA No
Esophageal Carcinoma ESCA 196 Yes (p<0.001) Yes (p = 0.001) Yes (p = 0.012) No
Glioblastoma Multiforme GBM 168 NA (No, primary vs
recurrent)
NA (No, primary vs
recurrent)
NA No
Head/Neck Squamous Cell Carcinoma HNSC 566 Yes (p<0.001) Yes (p<0.001) No No
Kidney Chromophobe KICH 91 Yes (p<0.001)^ No No No
Kidney Renal Clear Cell Carcinoma KIRC 612 Yes (p = 0.023) No Yes (p = 0.010) Yes
(p = 0.009)
Kidney Renal Papillary Cell Carcinoma KIRP 323 Yes (p<0.001) Yes (p<0.001) Yes (p = 0.02) No
Acute Myeloid Leukemia LAML 173 NA NA Yes (p<0.001) Yes
(p = 0.035)
Brain Lower Grade Glioma LGG 541 NA (Yes, primary vs
recurrent, p = 0.005)
NA (No, primary vs
recurrent)
NA No
(p = 0.054)
Liver Hepatocellular Carcinoma LIHC 424 Yes (p<0.001) Yes (p<0.001) No No
Lung Adenocarcinoma LUAD 576 Yes (p<0.001) Yes (p<0.001) No No
Lung Squamous Cell Carcinoma LUSC 553 Yes (p<0.001) Yes (p<0.001) Yes (p = 0.003) No
Mesothelioma MESO 87 NA NA No Yes
(p = 0.013)
Ovarian Serous Cystadenocarcinoma OV 309 NA (No, primary vs
recurrent)
NA (No, primary vs
recurrent)
NA No
Pancreatic Adenocarcinoma PAAD 183 No No No No
Pheochromocytoma and Paraganglioma PCPG 185 No No NA No
Prostate Adenocarcinoma PRAD 558 No No NA No
Rectum Adenocarcinoma READ 105 Yes (p<0.001) NA No No
Sarcoma SARC 266 No No NA Yes
(p = 0.003)
Skin Cutaneous Melanoma SKCM 473 NA NA No Yes
(p = 0.003)
Stomach Adenocarcinoma STAD 450 Yes (p<0.001) Yes (p<0.001) No No
Testicular Germ Cell Tumors TGCT 154 NA NA Yes (p<0.001) No
Thryoid Cancer THCA 572 Yes (p<0.001)^ Yes (p<0.001)^ No No
Thymoma THYM 122 NA NA NA No
Uterine Corpus Endometrial Carcinoma UCEC 198 Yes (p<0.001) Yes (p = 0.014) NA No
Uterine Carcinosarcoma UCS 57 NA NA NA No
Uveal Melanoma UVM 80 NA NA No No
Normal vs. Tumor includes all patient samples available while Matched Normal vs. Tumor only includes matched samples.
“Yes” indicates data are statistically significant with increased DNMT3B7 expression observed in tumor samples, higher stage, and/or poor survival groups.
“No” indicates data were not statistically significant.
“NA” indicates data were not available so analysis could not be completed.
^ indicates that the pattern was altered and DNMT3B7 expression was higher in normal samples compared to tumor tissues for that sample.
https://doi.org/10.1371/journal.pone.0201522.t001
Aberrant DNMT3B7 expression correlates to tissue type, stage, and survival across cancers
PLOS ONE | https://doi.org/10.1371/journal.pone.0201522 August 2, 2018 4 / 10
Fig 1. Expression of DNMT3B7 in normal and tumor patient samples. Representative graphs of 6 different tumor samples showing relative
DNMT3B7 expression, as measured by reads per kilobase per million (RPKM) or RNA-Seq by Expectation Maximization (RSEM), in
unmatched normal and tumor tissues in (A) HNSC, (B) UCEC, and (C) THCA. Expression of DNMT3B7 in matched patient samples is shown
in (D) LIHC and (E) LUAD. DNMT3B7 expression in primary and recurrent tissues in (F) LGG (p= 0.005) was assessed when normal samples
were not available. All samples shown here were significant, p<0.001, unless otherwise stated.
https://doi.org/10.1371/journal.pone.0201522.g001
Aberrant DNMT3B7 expression correlates to tissue type, stage, and survival across cancers
PLOS ONE | https://doi.org/10.1371/journal.pone.0201522 August 2, 2018 5 / 10
Fig 2. Relative DNMT3B7 expression correlates to clinical staging. DNMT3B7 expression was compared to clinical stage and shown to be
significantly different in (A) ESCA, p= 0.012; (B) KIRC, p= 0.010; (C) KIRP, p= 0.02; (D) LUSC, p= 0.003; (E) TGCT, p<0.001; and (F) LAML,
p<0.001. For (E) TGCT, there were no patient samples with a stage IV diagnosis. (F) LAML staging was measured using the French-American-
British (FAB) classifications.
https://doi.org/10.1371/journal.pone.0201522.g002
Aberrant DNMT3B7 expression correlates to tissue type, stage, and survival across cancers
PLOS ONE | https://doi.org/10.1371/journal.pone.0201522 August 2, 2018 6 / 10
Fig 3. Patients with high levels of DNMT3B7 expression have lower survival rates than those with low expression levels. The
median DNMT3B7 expression for each individual tumor was determined to divide patients with that tumor into “high” (gray, dotted
line) and “low” (black, solid line) expression groups. Kaplan-Meier curves were generated and statistical significance was determined
for (A) CESC, p= 0.025; (B) KIRC, p= 0.009; (C) LAML, p= 0.035; (D) MESO, p= 0.013; (E) SARC, p= 0.003; and (F) SKCM,
p= 0.003.
https://doi.org/10.1371/journal.pone.0201522.g003
Aberrant DNMT3B7 expression correlates to tissue type, stage, and survival across cancers
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Discussion
Due to the heterogeneity of tumors, it is rare to find one gene that is mutated across many can-
cer types that can be targeted by therapeutics. Furthermore, in the rare cases where a gene is
mutated in many cancers, (e.g. p53), the mutations are often in different parts of the gene mak-
ing it impossible to develop one therapeutic that is useful for all patients. However, the results
shown here indicate that DNMT3B7 may be a useful target across tumors in the future.
Because of the unique sequence it retains of 94bp of intron 10 leading to a premature stop
codon, there is a potential for specific targeting of this protein in cells. Our analysis here uti-
lized that unique sequence as a measure of DNMT3B7 expression in all available patient sam-
ples on the GDC and showed that this sequence is correlated to tumor progression across all
types of cancers—including carcinomas, sarcomas, and leukemias—as measured by tissue
type, clinical stage, and survival across many cancer types.
Of the 33 cancers with data available on GDC, 22 (67%) showed significant effects of
DNMT3B7 expression with relation to at least one of our measurements presented here. Of the
11 tumor types for which DNMT3B7 expression did not show any effect, five (DLBC, GBM,
OV, THYM, and UCS) had no data available to assess anything except survival (Table 1).
Therefore, it is possible that DNMT3B7 expression may have an effect in these cancers also,
but we are unable to determine that based on the data available at this time. Furthermore, 7
cancers had sample sizes under 100 patients which may have prevented statistical significance
from being achieved.
It is always important to determine if the experimental results previously shown in vitro
and in vivo match those seen in clinical samples. Overall, we observed that the results shown
by Ostler and colleagues [7] in which DNMT3B7 is expressed in virtually all (84%) cancer cell
lines tested is confirmed here to a similar degree. Based on the data available on GDC, we were
able to show altered expression of DNMT3B7 in 16 out of 21 samples (74%). Furthermore, we
see that the previously published in vitro work in breast cancer matches with our clinical analy-
sis (Table 1 and [10]). Shah and colleagues showed that DNMT3B7 expression led to lympho-
magenesis [9], however these results could not be recapitulated due to the lack of available data
on GDC. Finally, it may have been hypothesized that, based on the results of Ostler and col-
leagues in neuroblastoma [11], that the brain tumors examined here (GBM and LGG) would
have shown a flipped pattern of expression in which higher DNMT3B7 expression correlated
with normal samples compared to tumor samples. Unfortunately, normal samples were not
available for this analysis, so we are unable to confirm or deny that hypothesis. We did observe
that LGG showed increased expression of DNMT3B7 in recurrent tumors compared to pri-
mary tumors (Table 1 and Fig 1F) which would oppose the results seen in neuroblastoma.
However, this is not overly surprising since neuroblastoma is a pediatric cancer that is caused
by problems in early development and neurogenesis while LGG is diagnosed in adult brains
and, therefore, is caused by entirely different mechanisms [14].
Our analysis of differences in expression based on clinical stage, while providing some use-
ful data (Fig 2), was not as informative as hoped based on a few factors. First, we were unable
to analyze 33% of our total samples due to a lack of available clinical data for our patient sam-
ples. It is quite possible that significant changes in DNMT3B7 expression correlate with stage
in more cancers than shown here, but we cannot determine that based on the data available.
Next, because many of the cancers had relatively small sample sizes to begin with, this was
then further exacerbated by the fact that we had to subdivide these samples into smaller groups
in order to complete our analysis. Therefore, it is once again possible that DNMT3B7 may play
a larger role than observed here, but differences in sample size do not allow us to observe these
trends at this time. Additionally, analysis of the effects on clinical stage is dependent on having
Aberrant DNMT3B7 expression correlates to tissue type, stage, and survival across cancers
PLOS ONE | https://doi.org/10.1371/journal.pone.0201522 August 2, 2018 8 / 10
enough patient samples diagnosed at each stage, which was not always possible. As shown in
Fig 2E, some cancers did not have any patients diagnosed at one stage or another, which
affected our results. In other cases, such as PAAD, of the 183 patient samples available, 21 were
stage I, 151 were stage II, 3 were stage III, and 5 were stage IV. Small sample sizes in all but
stage II led to difficulties in achieving any sort of sound statistical analysis. LAML had to be
divided based on 8 FAB classifications which led to many more divisions than other tumor
types. While our results did obtain statistical significance (Fig 2F), there was no distinguishable
pattern except in the most advanced stages (6 and 7).
As stated previously, survival is not a direct measure of tumor progression and it can be
affected by many factors including ability to diagnose early and available treatments. However,
it is certainly the most important clinical outcome for patients and their families and, for that
reason, it was included as part of our analysis (Fig 3). We saw significant differences in survival
rates in LAML, which is the tumor type in which DNMT3B7 was originally identified [7]. Con-
versely, we did not see a significant difference in survival in BRCA (p= 0.053), even with a
large sample size and previous in vitro data indicating a role in tumor progression [10]. How-
ever, this could be due to the fact that breast cancer is typically diagnosed at an early stage and
has many good treatment options available, leading to increased survival rates compared to
other cancers.
Our results show that no one cancer had statistically significant results in all three categories
tested (normal versus tumor tissue, stage, and survival). However, 7 tumor types (BRCA,
CESC, ESCA, KIRC, KIRP, LAML, and LUSC; Table 1) had changes in two different catego-
ries, assuming expression in normal and tumor samples in matched and unmatched tissues
are considered one category. Because previous in vitro studies in LAML and BRCA have
already been completed and confirmed [7,10], these results suggest that the other 5 cancers
listed above should be prioritized for future studies involving DNMT3B7. Specifically, contin-
ued in vitro and in vivo work, matched with clinical samples, is imperative to elucidate the
functional role of DNMT3B7 in cancer and strengthen the likelihood of therapeutic targeting
of this aberrant protein across cancer types in the future. Taken together, the results presented
here demonstrate that DNMT3B7 has a role in tumor progression across cancers of all types
and is a promising target for future drug development.
Acknowledgments
The authors wish to thank Mark Raimondi for writing all of the code needed to produce our
data sets.
Author Contributions
Conceptualization: Stacey L. Raimondi.
Data curation: Safia Siddiqui, Michael W. White, Aimee M. Schroeder, Nicholas V. DeLuca,
Andrew L. Leszczynski, Stacey L. Raimondi.
Formal analysis: Safia Siddiqui, Michael W. White, Aimee M. Schroeder, Nicholas V. DeLuca,
Andrew L. Leszczynski, Stacey L. Raimondi.
Funding acquisition: Stacey L. Raimondi.
Methodology: Stacey L. Raimondi.
Project administration: Stacey L. Raimondi.
Supervision: Stacey L. Raimondi.
Aberrant DNMT3B7 expression correlates to tissue type, stage, and survival across cancers
PLOS ONE | https://doi.org/10.1371/journal.pone.0201522 August 2, 2018 9 / 10
Writing – original draft: Safia Siddiqui, Michael W. White, Aimee M. Schroeder.
Writing – review & editing: Safia Siddiqui, Michael W. White, Aimee M. Schroeder, Nicholas
V. DeLuca, Stacey L. Raimondi.
References
1. Lifetime Risk of Developing or Dying from Cancer [Internet]. Atlanta: American Cancer Society [cited 29
May 2018]. https://www.cancer.org/cancer/cancer-basics/lifetime-probability-of-developing-or-dying-
from-cancer.html
2. Robertson KD. DNA methylation and human disease. Nat Rev Genet. 2005; 6: 597–610. https://doi.
org/10.1038/nrg1655 PMID: 16136652
3. Esteller M. Epigenetic gene silencing in cancer: the DNA hypermethylome. Hum Mol Genet. 2007; 16
Spec No: R50–59.
4. Bestor TH. The DNA methyltransferases of mammals. Hum Mol Genet. 2000; 9: 2395–2402. PMID:
11005794
5. Okano M, Bell DW, Haber DA, Li E. DNA methyltransferases Dnmt3a and Dnmt3b are essential for de
novo methylation and mammalian development. Cell. 1999; 99: 247–257. PMID: 10555141
6. Reik W, Dean W, Walter J. Epigenetic reprogramming in mammalian development. Science. 2001;
293: 1089–1093. https://doi.org/10.1126/science.1063443 PMID: 11498579
7. Ostler KR, Davis EM, Payne SL, Gosalia BB, Expo
´sito-Ce
´spedes J, LeBeau MM, et al. Cancer cells
express aberrant DNMT3B transcripts encoding truncated proteins. Oncogene. 2007; 26: 5553–5563.
https://doi.org/10.1038/sj.onc.1210351 PMID: 17353906
8. Wang L, Wang J, Sun S, Rodriguez M, Yue P, Jang SJ, et al. A novel DNMT3B subfamily, Del-
taDNMT3B, is the predominant form of DNMT3B in non-small cell lung cancer. Intl J Onc. 2006; 29:
201–207.
9. Shah MY, Vasanthakumar A, Barnes NY, Figueroa ME, Kamp A, Hendrick C, et al. DNMT3B7, a trun-
cated DNMT3B isoform expressed in human tumors, disrupts embryonic development and accelerates
lymphomagenesis. Cancer Res. 2010; 70: 5840–5850. https://doi.org/10.1158/0008-5472.CAN-10-
0847 PMID: 20587527
10. Brambert PR, Kelpsch DJ, Hameed R, Desai CV, Calafiore G, Godley LA, et al. DNMT3B7 expression
promotes tumor progression to a more aggressive phenotype in breast cancer cells. PLoS ONE. 2015;
10(1):e0117310. https://doi.org/10.1371/journal.pone.0117310 PMID: 25607950
11. Ostler KR, Yang Q, Looney TJ, Zhang L, Vasanthakumar A, Tian Y, et al. Truncated DNMT3B isoform
DNMT3B7 suppresses growth, induces differentiation, and alters DNA methylation in human neuroblas-
toma. Cancer Res. 2012; 72: 4714–4723. https://doi.org/10.1158/0008-5472.CAN-12-0886 PMID:
22815530
12. Grossman RL, Heath AP, Ferretti V, Varmus HE, Lowy DR, Kibbe WA, et al. Toward a shared vision for
cancer genomic data. New Eng J Med. 2016; 375(12): 1109–1112. https://doi.org/10.1056/
NEJMp1607591 PMID: 27653561
13. Zhao H, Leppert JT, Peehl DM. A protective role for androgen receptor in clear cell renal cell carcinoma
based on mining TCGA data. PLoS ONE. 2016; 11(1): e0146505. https://doi.org/10.1371/journal.pone.
0146505 PMID: 26814892
14. de Weille J. On the Genesis of Neuroblastoma and Glioma. Intl J Brain Sci. 2014; 2014. https://doi.org/
10.1155/2014/217503
Aberrant DNMT3B7 expression correlates to tissue type, stage, and survival across cancers
PLOS ONE | https://doi.org/10.1371/journal.pone.0201522 August 2, 2018 10 / 10
