Introduction
MicroRNAs (miRNAs or miRs) are small non-coding
RNAs, comprising 19–25 nucleotides, that reduce the abundance and
translational efficiency of mRNAs and play a major role in
regulatory networks, influencing diverse biological processes
through the effects of individual miRNAs on the translation of
multiple mRNAs (1,2). Determining the roles of individual
miRNAs in cellular regulatory processes poses a major challenge
with the function of the majority of miRNAs that are currently
unknown; even for relatively well-studied miRNAs, only a handful of
targets have been rigorously characterized and these may differ by
tissue type.
miRNAs post-transcriptionally regulate the
expression of thousands of genes, including key genes in cell
differentiation and cancer pathogenesis (3). A growing number of studies have
highlighted the role of miRNAs in the development and progression
of cancer (4,5). In particular, the aberrant expression of
cancer-related proteins, such as oncogenes and tumor suppressors
has been shown to correlate with the modulation of the expression
specific miRNAs.
Non-Hodgkin's lymphomas (NHLs) are a heterogeneous
group of malignancies of the lymphoid system. NHLs are classified
based on cytology, immunophenotype and both genetic and clinical
characteristics (6). Genetic
aberration and molecular changes are used for a more appropriate
diagnostic profile. The most commonly associated genetic
abnormality in NHL is the translocation of t(14;18)(q32;q21)
(7), mostly detected in low-grade
lymphomas, such as follicular lymphoma; while molecular
rearrangements involving Bcl-6 or c-Myc are frequently observed in
diffuse large B-cell lymphoma (DLBCL) and Burkitt's lymphoma (BL),
respectively. Currently, a significant percentage of patients with
NHL are successfully cured; however, a fraction of these patients
may relapse following treatment due to the development of
chemoresitance (8,9).
It has been demonstrated that the transcription
factor, Yin Yang 1 (YY1), is involved in the regulation of
resistance to chemotherapy and immunotherapy in NHL cell lines. In
addition, the regulation of Fas resistance by nuclear factor
(NF)-κB is mediated via YY1 expression and activity (10). YY1 is known to play a critical role in
normal biological processes, such as embryogenesis,
differentiation, replication and cell proliferation. YY1 exerts its
effects on genes involved in these processes through its ability to
initiate, activate, or repress transcription, depending upon the
context in which it binds (11).
It has also been reported that YY1 is overexpressed
in several malignancies, including B-cell NHL (12,13), and
this overexpression is associated with aggressive behaviour in NHL
(14). Based on these findings, in
the current study, miRNAs potentially capable of targeting and
modulating YY1 were identified through in silico
approaches.
Data collection methods
In order to identify putative miRNAs that target YY1
mRNA, several publicly available miRNA target prediction tools were
used, including DIANA-microT (15),
miRanda (16), PicTar (17) and TargetScanS (18). Publicly available Gene Expression
Omnibus datasets of NHL specimens with the relative normal
counterparts were analyzed. Only datasets with both mRNA and miRNA
expression levels were considered for the analysis. According to
these criteria, the dataset GSE23026 was used in our study
(19). This dataset includes 12
samples of BL, 5 tonsil specimens, 7 lymph node specimens and 4
samples of CD19+CD10+ B-cells.
Statistical analysis
The differential analysis of YY1 expression levels
was performed using the ANOVA test. Correlation analysis between
the miRNA expression and YY1 expression levels was performed using
the Pearson correlation test.
Results
The analysis using the Diana-microT, miRanda,
PicTar, TargetScanS tools revealed a total of 57 predicted miRNAs
capable of targeting YY1 (Fig.
1).
The search of publicly available NHL datasets,
including paired mRNA and miRNA data (GSE23026) highlighted a
significant negative correlation (Pearson correlation coefficient
≤-0.5) between the YY1 expression levels and the expression of a
limited set of miRNAs, including miR-363, miR-200a, miR-23b,
miR-15a and miR-15b among the 57 predicted miRNAs capable of
targeting YY1 (Table I).
 | Table I.Pearson correlation analysis between
microRNAs targeting YY1 and YY1 expression levels. |
Table I.
Pearson correlation analysis between
microRNAs targeting YY1 and YY1 expression levels.
| miRNA | Pearson correlation
(r≤-0.5) | miRNA ID |
|---|
| ahsa-miR-363 | −0.611 | A_25_P00010953 |
| ahsa-miR-200a | −0.608 | A_25_P00010209 |
| hsa-miR-23b | −0.577 | A_25_P00010881 |
| hsa-miR-200a | −0.576 | A_25_P00010208 |
| hsa-miR-15a | −0.552 | A_25_P00010467 |
| ahsa-miR-363 | −0.549 | A_25_P00010954 |
| hsa-miR-15b | −0.517 | A_25_P00011101 |
As was expected, the transcript expression levels of
YY1 were found to be significantly higher in the BL samples
compared to the normal tissue samples (mean value expression for
BL=0.458, tonsil=−0.248, lymph node=0.049 and
CD19+CD10+ B-cells=0.197; ANOVA, P=0.007)
(Fig. 2). Intriguingly, both
hsa-miR-363 and hsa-miR-200a belong to the top 20 miRNAs that were
found to be downregulated in the BL samples compared to their
normal counterparts (Table II).
| Table II.Top 20 microRNAs downregulated in
Burkitt's lymphoma samples compared to normal tissue samples. |
Table II.
Top 20 microRNAs downregulated in
Burkitt's lymphoma samples compared to normal tissue samples.
| miRNA | P-value | FC (log) | miRNA ID |
|---|
| hsa-miR-150 | 2.32E-04 | −3.991 | A_25_P00010490 |
| hsa-miR-150 | 3.13E-04 | −3.869 | A_25_P00010489 |
| hsa-miR-363 | 1.71E-04 | −3.745 | A_25_P00010954 |
| hsa-miR-99a | 1.10E-06 | −3.686 | A_25_P00010471 |
|
hsa-miR-10b_v9.1 | 5.03E-05 | −3.657 | A_25_P00010136 |
|
hsa-miR-10b_v9.1 | 3.53E-05 | −3.607 | A_25_P00010135 |
|
hsa-miR-139_v9.1 | 2.73E-05 | −3.594 | A_25_P00010349 |
| hsa-miR-363 | 9.85E-05 | −3.547 | A_25_P00010953 |
|
hsa-let-7g_v9.1 | 7.09E-06 | −3.431 | A_25_P00010306 |
|
hsa-miR-31_v9.1 | 6.93E-05 | −3.426 | A_25_P00010510 |
|
hsa-let-7g_v9.1 | 5.21E-06 | −3.404 | A_25_P00010305 |
|
hsa-miR-200b_v9.1 | 1.01E-03 | −3.389 | A_25_P00010908 |
| hsa-let-7a | 7.41E-07 | −3.37 | A_25_P00011584 |
| hsa-let-7f | 1.59E-06 | −3.335 | A_25_P00010088 |
| hsa-miR-195 | 5.00E-06 | −3.25 | A_25_P00010769 |
| hsa-miR-133b | 7.41E-04 | −3.233 | A_25_P00010963 |
| hsa-miR-195 | 9.00E-06 | −3.198 | A_25_P00010770 |
|
hsa-let-7e_v9.1 | 1.04E-06 | −3.192 | A_25_P00010280 |
| hsa-miR-200a | 8.78E-04 | −3.184 | A_25_P00010209 |
|
hsa-let-7e_v9.1 | 6.81E-07 | −3.181 | A_25_P00010279 |
Discussion
A growing body of evidence has indicated that
deregulated miRNA expression is observed in a variety of human
diseases, including lymphomas, suggesting an important role in
their pathogenesis (20,21). The data from several experimental
studies have supported an important role for miRNAs in
lymphomagenesis through systematic miRNA profiling in lymphoma
samples using a variety of miRNA expression platforms (22–24).
YY1 is an activator and a repressor transcription
factor belonging to the Zinc-finger proteins (25). It is a positive regulator of several
oncogenes, such as c-Fos (26), c-Myc
(27) and Erb-B2 receptor tyrosine
kinase 2 (ERBB2) (28,29). However, it is also a negative
regulator of a fraction of tumor suppressor genes, including p27
(30), p16 (31), p73 (32)
and p53 (33). YY1 plays a role in
the malignant transformation of several diseases, including B-cell
lymphomas. Based on these findings, the aim of the present study
was to identify, through in silico approaches, which miRNAs
are potentially capable of targeting and modulating YY1.
Computational evaluation is an appropriate approach
for an initial screening to identify deregulated miRNAs. Based on
our results, we speculated that YY1 overexpression may be caused by
the downregulation of both hsa-miR-363 and hsa-miR-200a, at least
in BL. In fact, the overexpression of YY1 negatively correlated
with the expression of hsa-miR-363 and hsa-miR-200a. In turn, the
expression levels of hsa-miR-363 and hsa-miR-200a were lower in the
BL samples when compared with the normal tissue samples. The
increased transcript levels of YY1 in the BL samples is in
agreement with the observations of a previous study in which the
expression of YY1 was found to be associated with high-grade
lymphomas, suggesting that it is linked with post-germinal center
transit, where genetic alterations may occur, such as Bcl-6
mutations and/or Bcl-6 translocations (34). These findings may provide further
insight into the pathogenesis of BL, and YY1 may thus be considered
as a molecular signature of aggressiveness in high-grade
lymphomas.
Notably, it has been previously reported that the
overexpression of YY1 may promote p53 degradation or inhibit its
transcriptional activity (35).
Furthermore, the inhibition of YY1 in cancer cells, which lack
functional p53, also sensitizes them to cell death in response to
apoptotic stimuli (36,37). Although p53 is seldom mutated in NHL,
the p53 pathway has been reported to be attenuated in these tumors
(38). Among the targets of p53,
miR-34a has been found to be repressed as a consequence of promoter
methylation (39). These findings
support the notion that YY1 may directly control the expression of
genes involved in the apoptotic machinery independently of the p53
protein. However, certain drug-resistant hematopoietic disorders
that exhibit wild-type p53 may benefit from targeted therapy
(40).
In agreement with our results, the loss of miR-200a
expression in primary cutaneous melanoma is considered as an
additional indicator of aggressiveness, as it was associated with
increased thickness and disease progression (41).
Low levels of miR-200a have also been observed in
mucosa-associated lymphoid tissue lymphoma (MALT) lymphoma of the
conjunctiva. It was also found that cyclin E2 is a target of
miR-200a (42). Accordingly, the
putative role of YY1 in tumorigenesis is sustained by its
interaction with cell cycle regulation. The downregulated
expression of miR-363 can precisely differentiate the high-grade
lymphomas into ABC or GCB subtypes, and its expression has been
shown to correlate with the clinical outcome (43). Similarly, the downregulation of
miR-363 has also been detected in ovarian cancer and has been shown
to be associated with the drug-resistance phenomenon (44).
Although further validation studies are warranted,
the results of the present study indicate that the negative
correlation between miR-200a and miR-363 and YY1 expression, which
is observed in BL, may provide further insight into the
pathogenesis of BL and may have implications on treatment
strategies. Furthermore, our data suggest that miRNA expression
profiling provides a useful tool for a better understanding of
cancer development and progression and for the identification of
molecular predictors of response and outcome.
Acknowledgements
This study was supported in part by Lega Italiana
per la Lotta contro i Tumori and by the Jonsson Cancer Research
Center.
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