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Regulation of UHRF1 by dual-strand tumor-suppressor microRNA-145 (miR-145-5p and miR-145-3p): inhibition of bladder cancer cell aggressiveness

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Oncotarget. 2016; 7:28460-28487. https://doi.org/10.18632/oncotarget.8668

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Ryosuke Matsushita, Hirofumi Yoshino, Hideki Enokida, Yusuke Goto, Kazutaka Miyamoto, Masaya Yonemori, Satoru Inoguchi, Masayuki Nakagawa and Naohiko Seki _

Abstract

Ryosuke Matsushita1, Hirofumi Yoshino1, Hideki Enokida1, Yusuke Goto2, Kazutaka Miyamoto1, Masaya Yonemori1, Satoru Inoguchi1, Masayuki Nakagawa1, Naohiko Seki2

1Department of Urology, Graduate School of Medical and Dental Sciences, Kagoshima University, Kagoshima, Japan

2Department of Functional Genomics, Chiba University Graduate School of Medicine, Chuo-ku, Chiba, Japan

Correspondence to:

Naohiko Seki, e-mail: [email protected]

Keywords: miR-145-5p, miR-145-3p, tumor-suppressor, UHRF1, bladder cancer

Received: February 22, 2016     Accepted: March 28, 2016     Published: April 09, 2016

ABSTRACT

In microRNA (miRNA) biogenesis, the guide-strand of miRNA integrates into the RNA induced silencing complex (RISC), whereas the passenger-strand is inactivated through degradation. Analysis of our miRNA expression signature of bladder cancer (BC) by deep-sequencing revealed that microRNA (miR)-145-5p (guide-strand) and miR-145-3p (passenger-strand) were significantly downregulated in BC tissues. It is well known that miR-145-5p functions as a tumor suppressor in several types of cancer. However, the impact of miR-145-3p on cancer cells is still ambiguous. The aim of the present study was to investigate the functional significance of miR-145-3p and BC oncogenic pathways and targets regulated by miR-145-5p/miR-145-3p. Ectopic expression of either miR-145-5p or miR-145-3p in BC cells significantly suppressed cancer cell growth, migration and invasion and it also induced apoptosis. The gene encoding ubiquitin-like with PHD and ring finger domains 1 (UHRF1) was a direct target of these miRNAs. Silencing of UHRF1 induced apoptosis and inhibited cancer cell proliferation, migration, and invasion in BC cells. In addition, overexpressed UHRF1 was confirmed in BC clinical specimens, and the high UHRF1 expression group showed a significantly poorer cause specific survival rate in comparison with the low expression group. Taken together, our present data demonstrated that both strands of miR-145 (miR-145-5p: guide-strand and miR-145-3p: passenger-strand) play pivotal roles in BC cells by regulating UHRF1. The identification of the molecular target of a tumor suppressive miRNAs provides novel insights into the potential mechanisms of BC oncogenesis and suggests novel therapeutic strategies.


INTRODUCTION

In 2012, more than 400,000 new cases of bladder cancer (BC) were diagnosed and 165,000 patients died worldwide [1]. As for the prevalence of BC, men are three times more frequently diagnosed with BC than women [2]. The reasons for this disparity between sexes are not fully understood. BC is pathologically classified into two groups: non-muscle-invasive BC (NMIBC) and muscle-invasive BC (MIBC). Most BC patients (approximately 50%–80%) are diagnosed with NMIBC and this disease can be treated by removing the tumor by transurethral approaches [3]. In NMIBC, disease may recur, and some patients (approximately 25%) progress to MIBC [3]. Patients with advanced BC are generally treated with combination chemotherapy (gemcitabine and cisplatin), but progression-free survival is of limited duration [4]. Therefore, it is important to elucidate the molecular mechanisms of recurrence and invasiveness of BC cells to develop new treatment strategies.

The discovery of non-coding RNA in the human genome changed approaches in cancer research [5, 6]. Molecular mechanisms of post transcriptional gene regulation by protein-coding RNA/non-coding RNA networks are being studied on a genome-wide scale. MicroRNA (miRNA) is a class of small non-coding RNAs, and they are known to be involved in the repression or degradation of target RNA transcripts in a sequence-dependent manner [7]. A single miRNA can regulate thousands of target transcripts, and more than 60% of protein-coding genes may be influenced by miRNAs [8, 9]. Accumulating evidence indicates that aberrantly expressed miRNAs disturb normally regulated RNA networks, leading to pathologic responses in cancer cells [6]. Strategies to identify aberrant expression of miRNA-mediated cancer pathways are being developed as a new direction in cancer research in the post genome sequencing era.

To seek out differentially expressed miRNAs in BC cells, we used BC clinical specimens to establish deep sequencing-based miRNA expression signatures [10]. In general, the guide-strand RNA from duplex miRNA is retained to direct recruitment of the RNA induced silencing complex (RISC) to target messenger RNAs, whereas the passenger-strand RNA is degraded [1113]. Recently, we revealed that both strands of microRNA (miR)-144-5p and miR-144-3p derived from pre-miR-144 acted as tumor suppressors in BC cells [14]. Moreover, miR-144-5p (passenger-strand) directly targeted cyclin E1 and E2 in BC cells, suggesting that the passenger-strand of miRNA has a physiological role in cells [14].

In this study, we focused on miR-145-5p and miR-145-3p because these miRNAs were significantly downregulated in BC cells as determined in our deep sequencing signature [10]. It is well known that miR- 145- 5p functions as a tumor suppressor in several types of cancer, including BC [15]. However, the role of miR-145-3p on cancer cells is still ambiguous. The aims of the present study were to investigate the anti-tumor effects of miR-145-3p as well as miR-145-5p, and to determine the BC oncogenic pathways and target genes regulated by these miRNAs. The discovery that miR- 145- 5p and miR-145-3p coordinately regulate pathways and targets provides new insight into the mechanisms of BC progression and metastasis.

RESULTS

The expression levels of miR-145-5p and miR-145-3p in BC specimens and cell lines

We evaluated the expression levels of miR-145-5p and miR-145-3p in BC tissues (n = 69), normal bladder epithelia (NBE) (n = 12), and two BC cell lines (T24 and BOY). The expression levels of miR-145-5p and miR- 145- 3p were significantly lower in tumor tissues and BC cell lines compared with NBE (Figure 1A). Spearman’s rank test showed a positive correlation between the expression of these miRNAs (r = 0.986 and P < 0.0001) (Figure 1B). On the other hand, there were no significant relationships between any of the clinicopathological parameters (i.e., tumor grade, stage, metastasis, or survival rate) and the expression levels of miR-145-5p and miR-145-3p (data not shown).

The expression levels of miR-145-5p and miR-145-3p, and their effects in BC cells.

Figure 1: The expression levels of miR-145-5p and miR-145-3p, and their effects in BC cells. (A) Expression levels of miR- 145- 5p and miR-145-3p in clinical specimens and BC cell lines were determined by qRT-PCR. Data were normalized to RNU48 expression. (B) Correlation of miR-145-5p and miR-145-3p expression. (C) Cell growth was determined by XTT assays 72 hours after transfection with 10 nM miR-145-5p or miR-145-3p. *P < 0.0001. (D) Cell migration activity was determined by the wound-healing assays. *P < 0.0001. (E) Cell invasion activity was determined using Matrigel invasion assays. *P < 0.0001.

Effect of restoring miR-145-5p or miR-145- 3p expression on cell growth, migration, and invasion in BC cell lines

We performed gain-of-function studies using transfection of these miRNAs to investigate their functional roles. XTT, cell migration, and invasion assays demonstrated that cell proliferation, cell migration, and cell invasion were significantly inhibited in miR-145-5p and miR-145-3p transfectants in comparison with mock or miR-control transfectants (each P < 0.0001, Figure 1C, 1D, and 1E). These results suggested that miR-145-3p as well as miR-145-5p could have a tumor suppressive function in BC cells.

To investigate the synergistic effects of miR- 145- 5p and miR-145-3p, we performed proliferation, migration, and invasion assays with co-transfection of miR- 145-5p and miR-145-3p in BC cells (T24 and BOY), but they did not show synergistic effects of these miRNAs transfection (Supplementary Figure 1).

Effects of miR-145-5p and miR-145-3p transfection on apoptosis and cell cycle in BC cell lines

Because miR-145-5p and miR-145-3p transfection strongly inhibited cell proliferation in BC cell lines, we hypothesized that these miRNAs may induce apoptosis. Hence, we performed flow cytometric analyses to determine the number of apoptotic cells following restoration of miR- 145-5p or miR-145-3p expression.

The apoptotic cell numbers (apoptotic and early apoptotic cells) were significantly larger in miR-145-5p or miR-145-3p transfectants than in mock or miR-control transfectants (Figure 2A and 2C). Western blot analyses showed that cleaved PARP expression was significantly increased in miR-145-5p or miR-145-3p transfectants compared with mock or miR-control transfectants (Figure 2B and 2D).

Effects of miR-145-5p and miR-145-3p on apoptosis.

Figure 2: Effects of miR-145-5p and miR-145-3p on apoptosis. (A, C) Apoptosis assays were carried out using flow cytometry. Early apoptotic cells are in area R4 and apoptotic cells are in area R2. The normalized ratios of apoptotic cells are shown in the histograms. Cycloheximide (2 μg/mL) was used as positive control. *P = 0.0266 and **P < 0.0001. (B, D) Western blot analyses for apoptotic markers (cleaved PARP) in BC cell lines. GAPDH was used as a loading control.

We also investigated the cell cycle assays using miR-145-5p and miR-145-3p transfectants. The fraction of cells in the G2/M phase was significantly larger in miR-145-5p and miR-145-3p transfectants in T24 cells in comparison with mock or miR-control transfectants (Supplementary Figure 2). In contrast, miR-145-5p and miR-145-3p transfection induced cell cycle arrest at the G1 phase in BOY cells (Supplementary Figure 2). The reason why the cell cycle arrest (G2 arrest in T24 and G1 arrest in BOY) varies according to a cell types is a future problem.

Identification of common target genes regulated by miR-145-5p and miR-145-3p in BC cells

To gain further insight into the molecular mechanisms and pathways regulated by tumor suppressive miR-145-5p and miR-145-3p in BC cells, we used a combination of in silico analyses and gene expression analyses. Figure 3 shows our strategy to narrow down the common target genes of miR-145-5p and miR-145-3p.

Flow chart illustrates the strategy for analysis of miR-145-5p and miR-145-3p target genes.

Figure 3: Flow chart illustrates the strategy for analysis of miR-145-5p and miR-145-3p target genes. A total of 4,555 and 6,295 downregulated genes in expression analysis of miR-145-5p and miR-145-3p transfected BC cell lines, respectively, (T24 and BOY) were selected as putative target genes. Next we merged the data of those selected genes and the microRNA.org database. The analyses showed 398 common putative target genes between miR-145-5p and miR-145-3p. We then analyzed gene expression with available GEO data sets (GSE11783 + GSE31684). The analyses showed that 79 genes were significantly upregulated in BC specimens compared with NBE.

In gene expression analyses, a total of 4,555 and 6,295 genes were downregulated in miR-145-5p and miR- 145-3p transfectants, respectively, in comparison with control transfectants (Gene Expression Omnibus (GEO), accession number: GSE66498). Of those downregulated genes, 1,735 and 1,680 genes, respectively, had putative binding sites for miR-145-5p and miR-145- 3p in their 3′ untranslated regions (UTRs) according to the microRNA.org database. We found that there were 398 common genes targeted by both miRNAs, and among them, we ultimately identified 79 genes that were upregulated in the clinical BC samples from the GEO (accession numbers: GSE11783, GSE31684) (Table 1). We subsequently focused on the ubiquitin-like with PHD and ring finger domains 1 (UHRF1) gene because it was the top ranked gene in the list.

Table 1: Highly expressed genes putatively regulated by miR-145-5p and miR-145-3p

UHRF1 was a direct target of miR-145-5p and miR-145-3p in BC cells

We performed quantitative real-time RT-PCR (qRT-PCR) to validate that miR-145-5p and miR-145-3p repressed UHRF1 mRNA expression in BC cell lines, and we did indeed observe that it was significantly reduced in transfectants of these miRNAs in comparison with mock or miR-control transfectants (P < 0.0001 and P = 0.0036, Figure 4A). The protein expression levels of UHRF1 were also repressed in the miRNAs transfectants (Figure 4B).

Direct regulation of UHRF1 by miR-145-5p and miR-145-3p.

Figure 4: Direct regulation of UHRF1 by miR-145-5p and miR-145-3p. (A) UHRF1 mRNA expression was evaluated by qRT-PCR in T24 and BOY 72 hours after transfection with miR-145-5p and miR-145-3p. GUSB was used as an internal control. *P = 0.0036 and **P < 0.0001. (B) UHRF1 protein expression was evaluated by Western blot analyses in T24 and BOY 72–96 hours after transfection with miR-145-5p or miR-145-3p. GAPDH was used as a loading control. (C) miR-145-5p and miR-145-3p binding sites in the 3′ UTR of UHRF1 mRNA. Dual Luciferase reporter assays using vectors encoding putative miR-145-5p and miR-145-3p target sites of the UHRF 3′ UTR (positions 1,179–1,198 and 287–292, respectively) for both wild-type and deleted regions. Normalized data were calculated as ratios of Renilla/firefly luciferase activities. *P < 0.0001.

We carried out dual luciferase reporter assays in T24 and BOY cells to determine whether the UHRF1 gene was directly regulated by miR-145-5p/3p. The microRNA.org database predicted that there was one binding site for miR- 145-5p in the 3′ UTR of UHRF1 (position 1,179– 1,198); for miR-145-3p, there was a binding site in the 3′ UTR at position 287–292. We used vectors encoding the partial wild-type sequence of the 3′ UTR of the mRNA, including the predicted miR-145-5p or miR-145- 3p target sites. We found that the luminescence intensity was significantly reduced by co-transfection with these miRNAs and the vector carrying the wild-type 3′ UTR, whereas no reduction of luminescence was observed by transfection with the deletion vector (binding site had been removed) (P < 0.0001, Figure 4C). These suggested that either of miR-145-5p and miR-145-3p were directly bounded to specific sites in the 3′ UTR of UHRF1 mRNA.

Effects of silencing UHRF1 in BC cell lines

To investigate the functional role of UHRF1 in BC cells, we carried out loss-of-function studies by using si-UHRF1 transfectants. First, we evaluated the knockdown efficiency of si-UHRF1 transfection in BC cell lines. In the present study, we used two types of si- UHRF1 (si- UHRF1-1 and si-UHRF1-2). The qRT- PCR and Western blot analyses showed that both siRNAs effectively downregulated UHRF1 expression in both cell lines (Figure 5A and 5B).

UHRF1 mRNA and protein expression after si-UHRF1 transfection and effects of UHRF1 silencing in BC cell lines.

Figure 5: UHRF1 mRNA and protein expression after si-UHRF1 transfection and effects of UHRF1 silencing in BC cell lines. (A) UHRF1 mRNA expression was evaluated by qRT-PCR in T24 and BOY 72 hours after transfection with si-UHRF1-1 and si-UHRF1-2. GUSB was used as an internal control. (B) UHRF1 protein expression was evaluated by Western blot analysis in T24 and BOY 72 - 96 hours after transfection with miR-145-5p or miR-145-3p. GAPDH was used as a loading control. (C) Cell proliferation was determined with the XTT assays 72 hours after transfection with 10 nM si-UHRF1-1 or si-UHRF1-2. *P < 0.0001. (D) Cell migration activity was determined by wound-healing assays. *P < 0.0001. (E) Cell invasion activity was determined using Matrigel invasion assays. *P < 0.0001.

XTT, cell migration, and invasion assays demonstrated that cell proliferation, cell migration, and cell invasion were inhibited in si-UHRF1 transfectants in comparison with the mock or siRNA-control transfectant cells (each P < 0.0001, Figure 5C, 5D, and 5E).

In the apoptosis assays, the apoptotic cell numbers were significantly greater in si-UHRF1 transfectants than in mock or siRNA-control transfectants (Figure 6A and 6C). Western blot analyses showed that cleaved PARP expression was significantly increased in si-UHRF1 transfectants compared with mock or siRNA-control transfectants (Figure 6B and 6D).

Effects of silencing UHRF1 on apoptosis in BC cell lines.

Figure 6: Effects of silencing UHRF1 on apoptosis in BC cell lines. (A, C) Apoptosis assays were carried out using flow cytometry. Early apoptotic cells are in area R4 and apoptotic cells are in area R2. The normalized ratios of the apoptotic cells are shown in the histogram. Cycloheximide (2 μg/mL) was used as a positive control. *P < 0.0001 (B, D) Western blot analyses for apoptotic markers (cleaved PARP) in BC cell lines. GAPDH was used as a loading control.

Expression of UHRF1 in BC clinical specimens

The qRT-PCR analyses showed that the expression level of UHRF1 mRNA was significantly upregulated in 69 BC specimens and 2 BC cell lines compared with 12 NBE (P < 0.0001, Figure 7A). Spearman’s rank test showed negative correlations between miR-145-5p/miR-145-3p expression and UHRF1 mRNA expression (r = –0.324 and –0.298, P = 0.0024 and 0.0051, Figure 7B). As shown in Figure 7C, the expression level of UHRF1 was significantly greater in high grade clinical BCs (P = 0.0135), MIBCs (T2 ≤) (P = 0.0379), BCs with positive lymph node invasion (N1) (P = 0.00182), and in BCs with positive distant metastasis (M1) (P = 0.0307) than in their counterparts. Kaplan-Meier analysis showed that the high UHRF1 expression group had significantly lower cause specific survival probabilities compared to the low UHRF1 expression group (P = 0.0259, Figure 8).

The expression level of UHRF1 mRNA in BC clinical specimens and cell lines, and association of UHRF1 expression with clinicopathological parameters.

Figure 7: The expression level of UHRF1 mRNA in BC clinical specimens and cell lines, and association of UHRF1 expression with clinicopathological parameters. (A) Expression levels of UHRF1 in clinical specimens and BC cell lines were determined by qRT-PCR. Data were normalized to GUSB expression. (B) The correlated expression among miR-145-5p, miR-145-3p, and UHRF1. (C) Association of UHRF1 expression with clinicopathological parameters. Relationships between two variables were analyzed using the Mann-Whitney U test.

The association between the expression level of UHRF1 and cause specific survival rate.

Figure 8: The association between the expression level of UHRF1 and cause specific survival rate. Kaplan-Meier survival curves for cause specific survival rates based on UHRF1 expression in 57 BC patients. P-values were calculated using the log-rank test.

We validated the expression status of UHRF1 in BC clinical specimens using immunohistochemical staining. UHRF1 was expressed moderately or strongly in several cancer lesions, and normal bladder tissues stained weakly (Figure 9).

Immunohistochemical staining of UHRF1 in BC clinical specimens.

Figure 9: Immunohistochemical staining of UHRF1 in BC clinical specimens. UHRF1 was expressed more strongly in several cancer lesions than in noncancerous tissues. Left panel, original magnification ×40; Right panel, original magnification ×200. (A) Positively stained tumor lesion (High grade, T2bN0M0), (B) Positively stained tumor lesion (High grade, T1N0M0), (C) Positively stained tumor lesion (Low grade, T3N0M0), (D) Negative staining in normal bladder tissue.

Investigation of downstream genes regulated by UHRF1 in BC cells

To identify the downstream genes regulated by UHRF1, genome-wide gene expression analyses and in silico analyses were performed in two BC cell lines transfected with si-UHRF1. A total of 533 genes were downregulated (log2 FC < –1.5) by si-UHRF1 transfection, and a total of 704 genes were upregulated (log2 FC > 1.0) by si-UHRF1 transfection compared with negative control cells (GEO, accession number: GSE77790). Among the downregulated genes in the si-UHRF1 transfectants, 104 genes were upregulated in the BC clinical samples from GEO database (accession numbers: GSE11783, GSE31684), whereas among the upregulated genes, 62 genes were downregulated in the clinical BCs. These results imply that the 104 upregulated genes may act as oncogenes, and the 62 downregulated genes may act as tumor suppressors downstream from UHRF1 in BC (Tables 2 and 3).

Table 2: Significantly downregulated genes by si-UHRF1 in BC cell lines

Entrez Gene ID

Gene Symbol

Description

Genomic location

Gene Expression Omnibus
(GSE11783 + GSE31684)

Expression
in si-UHRF1
transfectant
(Log2 FC)

Expression

Log2FC

P-value

T24

BOY

7153

TOP2A

topoisomerase (DNA) II alpha 170kDa

17q21.2

up

6.312

1.049E-03

–1.880

–1.681

29128

UHRF1

ubiquitin-like with PHD and ring finger domains 1

19p13.3

up

4.984

1.049E-03

–3.213

–2.907

259266

ASPM

asp (abnormal spindle) homolog, microcephaly associated (Drosophila)

1q31.3

up

4.299

1.049E-03

–3.431

–3.444

332

BIRC5

baculoviral IAP repeat containing 5

17q25.3

up

4.110

1.049E-03

–2.258

–1.777

9928

KIF14

kinesin family member 14

1q32.1

up

3.866

1.049E-03

–3.294

–1.544

1063

CENPF

centromere protein F, 350/400kDa

1q41

up

3.576

1.049E-03

–2.613

–3.307

1894

ECT2

epithelial cell transforming 2

3q26.31

up

3.469

1.049E-03

–1.928

–1.813

55247

NEIL3

nei endonuclease VIII-like 3 (E. coli)

4q34.3

up

3.428

1.049E-03

–1.728

–2.065

9401

RECQL4

RecQ protein-like 4

8q24.3

up

3.414

1.049E-03

–1.751

–2.102

3832

KIF11

kinesin family member 11

10q23.33

up

3.356

1.049E-03

–2.299

–1.657

57082

CASC5

cancer susceptibility candidate 5

15q15.1

up

3.230

1.049E-03

–2.470

–2.188

151176

FAM132B

family with sequence similarity 132, member B

2q37.3

up

3.100

1.058E-03

–2.420

–2.184

151246

SGOL2

shugoshin-like 2 (S. pombe)

2q33.1

up

2.694

1.049E-03

–3.124

–2.407

1062

CENPE

centromere protein E, 312kDa

4q24

up

2.689

1.058E-03

–3.676

–3.218

23529

CLCF1

cardiotrophin-like cytokine factor 1

11q13.2

up

2.646

1.049E-03

–1.905

–2.363

81930

KIF18A

kinesin family member 18A

11p14.1

up

2.553

1.049E-03

–3.246

–2.128

7130

TNFAIP6

tumor necrosis factor, alpha-induced protein 6

2q23.3

up

2.531

2.835E-03

–1.795

–2.735

55502

HES6

hes family bHLH transcription factor 6

2q37.3

up

2.506

6.688E-03

–1.572

–1.508

5328

PLAU

plasminogen activator, urokinase

10q22.2

up

2.244

1.740E-03

–2.417

–1.791

9824

ARHGAP11A

Rho GTPase activating protein 11A

15q13.3

up

2.051

2.348E-03

–1.675

–1.613

23057

NMNAT2

nicotinamide nucleotide adenylyltransferase 2

1q25.3

up

2.050

1.247E-03

–1.707

–1.863

59285

CACNG6

calcium channel, voltage-dependent, gamma subunit 6

19q13.42

up

2.016

1.049E-03

–1.502

–1.763

675

BRCA2

breast cancer 2, early onset

13q13.1

up

2.015

1.049E-03

–1.764

–2.356

6524

SLC5A2

solute carrier family 5 (sodium/glucose cotransporter), member 2

16p11.2

up

1.900

1.214E-03

–1.855

–1.569

79412

KREMEN2

kringle containing transmembrane protein 2

16p13.3

up

1.893

1.348E-03

–2.309

–1.796

6274

S100A3

S100 calcium binding protein A3

1q21.3

up

1.825

8.102E-03

–2.215

–1.848

5331

PLCB3

phospholipase C, beta 3 (phosphatidylinositol-specific)

11q13.1

up

1.790

1.049E-03

–2.219

–1.735

55349

CHDH

choline dehydrogenase

3p21.1

up

1.743

1.049E-03

–1.926

–2.008

811

CALR

calreticulin

19p13.2

up

1.652

1.049E-03

–1.554

–1.500

4987

OPRL1

opiate receptor-like 1

20q13.33

up

1.627

2.626E-03

–1.927

–1.766

375248

ANKRD36

ankyrin repeat domain 36

2q11.2

up

1.530

8.102E-03

–3.873

–1.791

441054

C4orf47

chromosome 4 open reading frame 47

4q35.1

up

1.485

2.151E-02

–2.229

–2.522

201475

RAB12

RAB12, member RAS oncogene family

18p11.22

up

1.468

1.058E-03

–2.353

–2.947

286151

FBXO43

F-box protein 43

8q22.2

up

1.463

2.396E-02

–1.528

–2.082

9091

PIGQ

phosphatidylinositol glycan anchor biosynthesis, class Q

16p13.3

up

1.434

3.574E-03

–1.594

–1.693

81575

APOLD1

apolipoprotein L domain containing 1

12p13.1

up

1.354

1.808E-03

–2.237

–2.383

132320

SCLT1

sodium channel and clathrin linker 1

4q28.2

up

1.340

1.049E-03

–3.140

–3.098

100131211

TMEM194B

transmembrane protein 194B

2q32.2

up

1.325

1.049E-03

–1.573

–1.967

153642

ARSK

arylsulfatase family, member K

5q15

up

1.252

1.049E-03

–2.052

–1.875

21

ABCA3

ATP-binding cassette, sub-family A (ABC1), member 3

16p13.3

up

1.170

4.892E-02

–1.879

–1.831

55036

CCDC40

coiled-coil domain containing 40

17q25.3

up

1.160

1.049E-03

–1.562

–1.531

84259

DCUN1D5

DCN1, defective in cullin neddylation 1, domain containing 5

11q22.3

up

1.151

1.247E-03

–1.591

–1.993

80381

CD276

CD276 molecule

15q24.1

up

1.146

1.072E-03

–2.656

–2.096

6487

ST3GAL3

ST3 beta-galactoside alpha-2,3-sialyltransferase 3

1p34.1

up

1.139

1.049E-03

–1.828

–2.380

5351

PLOD1

procollagen-lysine, 2-oxoglutarate 5-dioxygenase 1

1p36.22

up

1.104

2.942E-03

–1.650

–1.570

343099

CCDC18

coiled-coil domain containing 18

1p22.1

up

1.075

1.578E-03

–3.521

–2.428

30818

KCNIP3

Kv channel interacting protein 3, calsenilin

2q11.1

up

1.069

2.723E-03

–3.678

–2.733

10051

SMC4

structural maintenance of chromosomes 4

3q25.33

up

1.066

1.578E-03

–2.612

–1.745

51427

ZNF107

zinc finger protein 107

7q11.21

up

1.040

1.316E-03

–2.527

–2.104

10592

SMC2

structural maintenance of chromosomes 2

9q31.1

up

1.032

6.688E-03

–3.520

–2.180

20

ABCA2

ATP-binding cassette, sub-family A (ABC1), member 2

9q34.3

up

0.965

1.372E-02

–1.511

–2.291

55183

RIF1

replication timing regulatory factor 1

2q23.3

up

0.960

1.058E-03

–1.712

–1.605

9898

UBAP2L

ubiquitin associated protein 2-like

1q21.3

up

0.952

1.049E-03

–1.587

–2.301

29780

PARVB

parvin, beta

22q13.31

up

0.952

1.096E-02

–3.288

–1.888

9585

KIF20B

kinesin family member 20B

10q23.31

up

0.933

5.720E-03

–2.282

–3.122

9534

ZNF254

zinc finger protein 254

19p12

up

0.920

3.863E-03

–2.072

–2.662

57520

HECW2

HECT, C2 and WW domain containing E3 ubiquitin protein ligase 2

2q32.3

up

0.884

3.179E-03

–1.838

–1.958

84083

ZRANB3

zinc finger, RAN-binding domain containing 3

2q21.3

up

0.873

1.578E-03

–1.987

–1.915

6498

SKIL

SKI-like proto-oncogene

3q26.2

up

0.859

1.808E-03

–2.709

–1.845

64770

CCDC14

coiled-coil domain containing 14

3q21.1

up

0.842

6.943E-03

–2.453

–1.711

254065

BRWD3

bromodomain and WD repeat domain containing 3

Xq21.1

up

0.808

1.393E-03

–1.852

–2.546

22973

LAMB2P1

laminin, beta 2 pseudogene 1

3p21.31

up

0.804

7.521E-03

–2.336

–2.311

7525

YES1

YES proto-oncogene 1, Src family tyrosine kinase

18p11.32

up

0.794

2.526E-03

–3.127

–2.099

1984

EIF5A

eukaryotic translation initiation factor 5A

17p13.1

up

0.793

5.486E-03

–2.297

–2.018

22852

ANKRD26

ankyrin repeat domain 26

10p12.1

up

0.787

3.303E-03

–2.798

–2.663

23322

RPGRIP1L

RPGRIP1-like

16q12.2

up

0.778

1.182E-02

–1.517

–1.806

79677

SMC6

structural maintenance of chromosomes 6

2p24.2

up

0.764

8.401E-03

–1.909

–2.083

84920

ALG10

ALG10, alpha-1,2-glucosyltransferase

12p11.1

up

0.763

6.688E-03

–1.828

–2.360

8570

KHSRP

KH-type splicing regulatory protein

19p13.3

up

0.762

3.303E-03

–1.767

–1.820

5819

PVRL2

poliovirus receptor-related 2 (herpesvirus entry mediator B)

19q13.32

up

0.757

9.078E-03

–3.014

–2.465

51575

ESF1

ESF1, nucleolar pre-rRNA processing protein, homolog (S. cerevisiae)

20p12.1

up

0.755

9.430E-03

–1.786

–1.732

51361

HOOK1

hook microtubule-tethering protein 1

1p32.1

up

0.689

3.067E-02

–2.156

–2.000

10198

MPHOSPH9

M-phase phosphoprotein 9

12q24.31

up

0.667

1.947E-03

–2.113

–1.502

4983

OPHN1

oligophrenin 1

Xq12

up

0.632

5.277E-03

–2.278

–1.747

4976

OPA1

optic atrophy 1 (autosomal dominant)

3q29

up

0.619

2.169E-03

–2.190

–1.526

168850

ZNF800

zinc finger protein 800

7q31.33

up

0.611

1.227E-02

–1.807

–1.867

26272

FBXO4

F-box protein 4

5p13.1

up

0.611

3.512E-02

–2.224

–2.445

7390

UROS

uroporphyrinogen III synthase

10q26.13

up

0.605

6.433E-03

–3.120

–2.062

4683

NBN

nibrin

8q21.3

up

0.590

5.720E-03

–2.986

–1.966

79670

ZCCHC6

zinc finger, CCHC domain containing 6

9q21.33

up

0.587

5.486E-03

–2.353

–1.839

79573

TTC13

tetratricopeptide repeat domain 13

1q42.2

up

0.587

6.943E-03

–1.740

–2.064

50840

TAS2R14

taste receptor, type 2, member 14

12p13.2

up

0.574

1.598E-02

–1.947

–1.509

79042

TSEN34

TSEN34 tRNA splicing endonuclease subunit

19q13.42

up

0.570

1.138E-02

–2.455

–1.761

6801

STRN

striatin, calmodulin binding protein

2p22.2

up

0.563

2.723E-03

–1.964

–2.434

3597

IL13RA1

interleukin 13 receptor, alpha 1

Xq24

up

0.552

2.075E-02

–2.460

–2.403

147657

ZNF480

zinc finger protein 480

19q13.41

up

0.547

3.893E-02

–3.434

–3.276

8683

SRSF9

serine/arginine-rich splicing factor 9

12q24.31

up

0.534

1.227E-02

–1.523

–2.098

252983

STXBP4

syntaxin binding protein 4

17q22

up

0.516

2.151E-02

–1.776

–1.599

284325

C19orf54

chromosome 19 open reading frame 54

19q13.2

up

0.510

4.734E-02

–1.614

–2.171

91147

TMEM67

transmembrane protein 67

8q22.1

up

0.509

9.799E-03

–1.647

–2.069

114799

ESCO1

establishment of sister chromatid cohesion N-acetyltransferase 1

18q11.2

up

0.495

4.873E-03

–2.173

–2.401

57670

KIAA1549

KIAA1549

7q34

up

0.480

4.582E-02

–2.127

–1.789

6103

RPGR

retinitis pigmentosa GTPase regulator

Xp11.4

up

0.467

3.290E-02

–1.583

–2.025

5700

PSMC1

proteasome (prosome, macropain) 26S subunit, ATPase, 1

14q32.11

up

0.449

1.274E-02

–1.639

–1.711

253260

RICTOR

RPTOR independent companion of MTOR, complex 2

5p13.1

up

0.442

2.666E-02

–2.458

–1.683

23241

PACS2

phosphofurin acidic cluster sorting protein 2

14q32.33

up

0.442

3.179E-03

–3.416

–2.028

27154

BRPF3

bromodomain and PHD finger containing, 3

6p21.31

up

0.440

5.720E-03

–1.772

–2.598

7703

PCGF2

polycomb group ring finger 2

17q12

up

0.439

2.865E-02

–1.828

–1.974

51105

PHF20L1

PHD finger protein 20-like 1

8q24.22

up

0.383

9.078E-03

–3.492

–2.007

57697

FANCM

Fanconi anemia, complementation group M

14q21.2

up

0.364

3.067E-02

–1.648

–1.627

9730

VPRBP

Vpr (HIV-1) binding protein

3p21.2

up

0.363

2.075E-02

–2.342

–1.568

5378

PMS1

PMS1 postmeiotic segregation increased 1 (S. cerevisiae)

2q32.2

up

0.350

4.734E-02

–2.701

–1.616

255520

ELMOD2

ELMO/CED-12 domain containing 2

4q31.1

up

0.334

4.582E-02

–2.360

–1.637

80124

VCPIP1

valosin containing protein (p97)/p47 complex interacting protein 1

8q13.1

up

0.304

3.893E-02

–3.107

–2.286

Table 3: Significantly upregulated genes by si-UHRF1 in BC cell lines

Entrez Gene ID

Gene Symbol

Description

Genomic location

Gene Expression Omnibus
(GSE11783 + GSE31684)

Expression
in si-UHRF1
transfectant
(Log2 FC)

Expression

Log2FC

P-value

T24

BOY

3043

HBB

hemoglobin, beta

11p15.4

down

–3.263

1.214E-03

1.204

2.109

137835

TMEM71

transmembrane protein 71

8q24.22

down

–2.428

4.873E-03

2.813

3.920

8639

AOC3

amine oxidase, copper containing 3

17q21.31

down

–2.188

1.434E-03

1.907

3.140

1408

CRY2

cryptochrome circadian clock 2

11p11.2

down

–2.141

1.058E-03

2.134

2.108

7644

ZNF91

zinc finger protein 91

19p12

down

–2.058

1.155E-03

1.435

2.063

197257

LDHD

lactate dehydrogenase D

16q23.1

down

–1.626

2.965E-02

1.844

1.362

316

AOX1

aldehyde oxidase 1

2q33.1

down

–1.601

2.169E-03

1.841

1.049

26051

PPP1R16B

protein phosphatase 1, regulatory subunit 16B

20q11.23

down

–1.547

6.688E-03

1.076

1.198

63976

PRDM16

PR domain containing 16

1p36.32

down

–1.439

2.075E-02

2.639

3.846

254827

NAALADL2

N-acetylated alpha-linked acidic dipeptidase-like 2

3q26.31

down

–1.313

4.873E-03

1.621

3.168

154

ADRB2

adrenoceptor beta 2, surface

5q32

down

–1.242

9.799E-03

2.384

2.302

10477

UBE2E3

ubiquitin-conjugating enzyme E2E 3

2q31.3

down

–1.117

1.135E-03

1.053

2.755

7099

TLR4

toll-like receptor 4

9q33.1

down

–1.053

6.943E-03

1.402

2.356

57478

USP31

ubiquitin specific peptidase 31

16p12.2

down

–1.037

4.169E-03

1.570

1.234

57185

NIPAL3

NIPA-like domain containing 3

1p36.11

down

–0.986

1.316E-03

1.329

1.189

30815

ST6GALNAC6

ST6 (alpha-N-acetyl-neuraminyl-2,3-beta-galactosyl-1,3)-N-acetylgalactosaminide alpha-2,6-sialyltransferase 6

9q34.11

down

–0.936

1.660E-02

1.093

2.348

29915

HCFC2

host cell factor C2

12q23.3

down

–0.928

1.393E-03

1.304

1.296

54741

LEPROT

leptin receptor overlapping transcript

1p31.3

down

–0.893

1.049E-03

1.280

2.248

7779

SLC30A1

solute carrier family 30 (zinc transporter), member 1

1q32.3

down

–0.879

8.736E-03

1.267

1.262

79027

ZNF655

zinc finger protein 655

7q22.1

down

–0.863

1.393E-03

1.570

1.589

64344

HIF3A

hypoxia inducible factor 3, alpha subunit

19q13.32

down

–0.845

1.016E-02

1.284

2.411

79844

ZDHHC11

zinc finger, DHHC-type containing 11

5p15.33

down

–0.834

3.176E-02

1.505

1.890

79815

NIPAL2

NIPA-like domain containing 2

8q22.2

down

–0.825

6.688E-03

1.929

1.259

7923

HSD17B8

hydroxysteroid (17-beta) dehydrogenase 8

6p21.32

down

–0.821

3.512E-02

2.657

3.759

8629

JRK

Jrk homolog (mouse)

8q24.3

down

–0.820

1.740E-03

1.358

2.076

79591

C10orf76

chromosome 10 open reading frame 76

10q24.32

down

–0.812

1.808E-03

1.099

1.917

599

BCL2L2

BCL2-like 2

14q11.2

down

–0.775

2.835E-03

1.384

1.730

412

STS

steroid sulfatase (microsomal), isozyme S

Xp22.31

down

–0.770

1.372E-02

1.440

1.471

56900

TMEM167B

transmembrane protein 167B

1p13.3

down

–0.755

2.626E-03

2.282

2.366

23509

POFUT1

protein O-fucosyltransferase 1

20q11.21

down

–0.747

1.274E-02

1.400

2.132

25923

ATL3

atlastin GTPase 3

11q12.3

down

–0.727

3.290E-02

1.179

1.907

79669

C3orf52

chromosome 3 open reading frame 52

3q13.2

down

–0.708

4.021E-02

1.200

1.482

55844

PPP2R2D

protein phosphatase 2, regulatory subunit B, delta

10q26.3

down

–0.691

2.666E-02

1.422

1.303

5939

RBMS2

RNA binding motif, single stranded interacting protein 2

12q13.3

down

–0.626

5.943E-03

1.193

1.438

6158

RPL28

ribosomal protein L28

19q13.42

down

–0.618

1.808E-03

2.026

3.427

2145

EZH1

enhancer of zeste 1 polycomb repressive complex 2 subunit

17q21.2

down

–0.618

1.393E-03

1.391

1.171

388969

C2orf68

chromosome 2 open reading frame 68

2p11.2

down

–0.611

3.435E-03

1.309

1.192

55422

ZNF331

zinc finger protein 331

19q13.42

down

–0.594

1.725E-02

2.855

2.230

92400

RBM18

RNA binding motif protein 18

9q33.2

down

–0.594

8.401E-03

1.172

2.001

80017

C14orf159

chromosome 14 open reading frame 159

14q32.11

down

–0.590

1.182E-02

1.072

1.748

7556

ZNF10

zinc finger protein 10

12q24.33

down

–0.563

1.480E-02

1.592

1.127

55957

LIN37

lin-37 DREAM MuvB core complex component

19q13.12

down

–0.543

1.857E-02

1.002

1.205

84267

C9orf64

chromosome 9 open reading frame 64

9q21.32

down

–0.543

5.720E-03

1.215

1.299

8799

PEX11B

peroxisomal biogenesis factor 11 beta

1q21.1

down

–0.535

4.679E-03

1.083

1.163

8790

FPGT

fucose-1-phosphate guanylyltransferase

1p31.1

down

–0.524

2.075E-02

1.680

1.222

6992

PPP1R11

protein phosphatase 1, regulatory (inhibitor) subunit 11

6p22.1

down

–0.517

6.433E-03

1.104

1.329

116224

FAM122A

family with sequence similarity 122A

9q21.11

down

–0.507

2.169E-03

1.231

1.549

51710

ZNF44

zinc finger protein 44

19p13.2

down

–0.499

1.372E-02

2.385

1.001

7265

TTC1

tetratricopeptide repeat domain 1

5q33.3

down

–0.487

1.182E-02

1.109

1.112

80213

TM2D3

TM2 domain containing 3

15q26.3

down

–0.485

1.182E-02

1.342

1.742

81631

MAP1LC3B

microtubule-associated protein 1 light chain 3 beta

16q24.2

down

–0.480

1.725E-02

1.210

2.109

6016

RIT1

Ras-like without CAAX 1

1q22

down

–0.473

2.666E-02

1.556

1.432

7247

TSN

translin

2q14.3

down

–0.467

4.582E-02

1.101

1.496

167227

DCP2

decapping mRNA 2

5q22.2

down

–0.447

1.016E-02

1.284

1.104

11046

SLC35D2

solute carrier family 35 (UDP-GlcNAc/UDP-glucose transporter), member D2

9q22.32

down

–0.431

1.227E-02

1.318

1.340

54946

SLC41A3

solute carrier family 41, member 3

3q21.2

down

–0.402

4.294E-02

1.526

1.988

7799

PRDM2

PR domain containing 2, with ZNF domain

1p36.21

down

–0.384

7.805E-03

1.438

1.294

6651

SON

SON DNA binding protein

21q22.11

down

–0.374

5.486E-03

1.126

1.155

80255

SLC35F5

solute carrier family 35, member F5

2q14.1

down

–0.369

4.441E-02

1.143

1.619

55197

RPRD1A

regulation of nuclear pre-mRNA domain containing 1A

18q12.2

down

–0.364

3.893E-02

1.480

1.761

91603

ZNF830

zinc finger protein 830

17q12

down

–0.358

2.075E-02

1.040

1.085

5094

PCBP2

poly(rC) binding protein 2

12q13.13

down

–0.286

4.734E-02

1.454

1.158

To further investigate the UHRF1 downstream genes, we performed the classification of these candidate genes to known molecular pathways by using DAVID program (https://david.ncifcrf.gov/). Classification strategy of downstream genes by si-UHRF1 transfectants is shown in Figure 10A and 10B. Significantly upregulated and downregulated pathways and their involved genes are indicated in Tables 4 and 5. Several genes were classified into biological process categories and a variety of biological pathways, “M phase”, “cell cycle”, and “cell cycle phase” were significantly downregulated by si- UHRF1 transfectants (Table 4).

Flow chart demonstrating the strategy for analysis of genes regulated by UHRF1.

Figure 10: Flow chart demonstrating the strategy for analysis of genes regulated by UHRF1. (A) A total of 2,222 and 1,512 downregulated genes in expression analyses of si-UHRF1 transfectants of BC cell lines (T24 and BOY, respectively) were selected. We then analyzed 533 common downregulated genes by using available GEO data sets (GSE11783 + GSE31684). The analyses showed that 104 genes were significantly upregulated in BC specimens compared with NBE. (B) A total of 2,665 and 2,434 upregulated genes in expression analysis of si-UHRF1 transfectants of BC cell lines (T24 and BOY, respectively) were selected. We then analyzed 704 common upregulated genes by using GEO data sets. The analyses showed that 62 genes were significantly downregulated in BC specimens compared with NBE.

Table 4: Downregulated genes by si-UHRF1 were classified by DAVID program

Biological process

Number of genes

P-Value

Genes

M phase

15

8.10E-09

ASPM, BIRC5, BRCA2, CENPE, CENPF, FBXO43, KIF11, KIF18A, KIF20B, MPHOSPH9, NBN, SGOL2, SMC2, SMC4, VCPIP1

cell cycle

20

1.10E-07

ASPM, BIRC5, BRCA2, CALR, CENPE, CENPF, ESCO1, FBXO43, KIF11, KIF18A, KIF20B, MPHOSPH9, NBN, PSMC1, RIF1, SGOL2, SMC2, SMC4, UHRF1, VCPIP1

cell cycle phase

15

1.40E-07

ASPM, BIRC5, BRCA2, CENPE, CENPF, FBXO43, KIF11, KIF18A, KIF20B, MPHOSPH9, NBN, SGOL2, SMC2, SMC4, VCPIP1

cell cycle process

17

1.90E-07

ASPM, BIRC5, BRCA2, CALR, CENPE, CENPF, FBXO43, KIF11, KIF18A, KIF20B, MPHOSPH9, NBN, PSMC1, SGOL2, SMC2, SMC4, VCPIP1

chromosome segregation

8

5.20E-07

BIRC5, CENPE, CENPF, KIF18A, SGOL2, SMC2, SMC4, TOP2A

M phase of mitotic cell cycle

11

8.50E-07

ASPM, BIRC5, CENPE, CENPF, KIF11, KIF18A, KIF20B, MPHOSPH9, SMC2, SMC4, VCPIP1

organelle fission

11

1.00E-06

ASPM, BIRC5, CENPE, CENPF, KIF11, KIF18A, KIF20B, OPA1, SMC2, SMC4, VCPIP1

mitosis

10

6.40E-06

ASPM, BIRC5, CENPE, CENPF, KIF11, KIF18A, KIF20B, SMC2, SMC4, VCPIP1

nuclear division

10

6.40E-06

ASPM, BIRC5, CENPE, CENPF, KIF11, KIF18A, KIF20B, SMC2, SMC4, VCPIP1

mitotic cell cycle

12

1.20E-05

ASPM, BIRC5, CENPE, CENPF, KIF11, KIF18A, KIF20B, MPHOSPH9, PSMC1, SMC2, SMC4, VCPIP1

DNA repair

10

4.90E-05

BRCA2, ESCO1, FANCM, NBN, NEIL3, PMS1, RECQL4, SMC6, TOP2A, UHRF1

cell division

10

6.50E-05

ASPM, BIRC5, BRCA2, CENPE, CENPF, KIF11, KIF20B, SGOL2, SMC2, SMC4

response to DNA damage stimulus

11

7.40E-05

BRCA2, ESCO1, FANCM, NBN, NEIL3, PMS1, RECQL4, RIF1, SMC6, TOP2A, UHRF1

establishment of chromosome localization

4

8.90E-05

BIRC5, CENPE, CENPF, KIF18A

chromosome localization

4

8.90E-05

BIRC5, CENPE, CENPF, KIF18A

chromosome organization

12

1.40E-04

BRCA2, BRPF3, CENPE, CENPF, FBXO4, KIF18A, NBN, PCGF2, SGOL2, SMC2, SMC4, TOP2A

DNA metabolic process

12

2.00E-04

BRCA2, CENPF, ESCO1, FANCM, FBXO4, NBN, NEIL3, PMS1, RECQL4, SMC6, TOP2A, UHRF1

microtubule-based movement

6

5.80E-04

CENPE, KIF11, KIF14, KIF18A, KIF20B, OPA1

regulation of cell cycle process

6

6.00E-04

BIRC5, BRCA2, CALR, CENPE, CENPF, KIF20B

microtubule-based process

8

7.90E-04

BRCA2, CENPE, HOOK1, KIF11, KIF14, KIF18A, KIF20B, OPA1

mitotic sister chromatid segregation

4

1.30E-03

CENPE, KIF18A, SMC2, SMC4

sister chromatid segregation

4

1.40E-03

CENPE, KIF18A, SMC2, SMC4

metaphase plate congression

3

1.90E-03

CENPE, CENPF, KIF18A

cellular response to stress

11

2.00E-03

BRCA2, ESCO1, FANCM, NBN, NEIL3, PMS1, RECQL4, RIF1, SMC6, TOP2A, UHRF1

regulation of mitotic cell cycle

6

2.20E-03

BIRC5, BRCA2, CENPE, CENPF, KIF20B, NBN

organelle localization

5

2.20E-03

ASPM, BIRC5, CENPE, CENPF, KIF18A

spindle checkpoint

3

2.20E-03

BIRC5, CENPE, CENPF

positive regulation of cell cycle

4

4.80E-03

BIRC5, BRCA2, CALR, CENPE

establishment of organelle localization

4

8.20E-03

BIRC5, CENPE, CENPF, KIF18A

chromosome condensation

3

9.70E-03

SMC2, SMC4, TOP2A

glucose transport

3

1.30E-02

SLC5A2, STXBP4, YES1

hexose transport

3

1.40E-02

SLC5A2, STXBP4, YES1

regulation of cell cycle

7

1.40E-02

BIRC5, BRCA2, CALR, CENPE, CENPF, KIF20B, NBN

monosaccharide transport

3

1.50E-02

SLC5A2, STXBP4, YES1

negative regulation of neuron differentiation

3

1.70E-02

ASPM, CALR, NBN

cell cycle checkpoint

4

1.70E-02

BIRC5, CENPE, CENPF, NBN

kinetochore assembly

2

1.80E-02

CENPE, CENPF

meiosis

4

2.10E-02

BRCA2, FBXO43, NBN, SGOL2

M phase of meiotic cell cycle

4

2.10E-02

BRCA2, FBXO43, NBN, SGOL2

meiotic cell cycle

4

2.20E-02

BRCA2, FBXO43, NBN, SGOL2

germ cell development

4

2.30E-02

BRCA2, CASC5, HOOK1, PVRL2

kinetochore organization

2

2.40E-02

CENPE, CENPF

DNA recombination

4

2.50E-02

BRCA2, NBN, RECQL4, SMC6

mitotic cell cycle checkpoint

3

2.70E-02

CENPE, CENPF, NBN

centromere complex assembly

2

3.50E-02

CENPE, CENPF

spermatid development

3

4.10E-02

CASC5, HOOK1, PVRL2

regulation of nuclear division

3

4.40E-02

CENPE, CENPF, KIF20B

regulation of mitosis

3

4.40E-02

CENPE, CENPF, KIF20B

negative regulation of macromolecule biosynthetic process

8

4.50E-02

BRCA2, CALR, CD276, CENPF, KCNIP3, PCGF2, SKIL, ZNF254

spermatid differentiation

3

4.60E-02

CASC5, HOOK1, PVRL2

cytoskeleton organization

7

4.60E-02

BRCA2, CALR, HOOK1, KIF11, KIF18A, OPHN1, RICTOR

negative regulation of cellular biosynthetic process

8

5.10E-02

BRCA2, CALR, CD276, CENPF, KCNIP3, PCGF2, SKIL, ZNF254

positive regulation of cellular protein metabolic process

5

5.10E-02

CLCF1, EIF5A, FBXO4, PSMC1, RICTOR

carbohydrate transport

3

5.20E-02

SLC5A2, STXBP4, YES1

mitotic metaphase plate congression

2

5.30E-02

CENPE, KIF18A

regulation of DNA replication

3

5.30E-02

BRCA2, CALR, NBN

double-strand break repair

3

5.30E-02

BRCA2, NBN, RECQL4

negative regulation of biosynthetic process

8

5.50E-02

BRCA2, CALR, CD276, CENPF, KCNIP3, PCGF2, SKIL, ZNF254

positive regulation of protein metabolic process

5

5.80E-02

CLCF1, EIF5A, FBXO4, PSMC1, RICTOR

microtubule cytoskeleton organization

4

5.80E-02

BRCA2, HOOK1, KIF11, KIF18A

negative regulation of mitotic metaphase/anaphase transition

2

6.40E-02

CENPE, CENPF

blastocyst growth

2

6.40E-02

BRCA2, NBN

mitotic cell cycle spindle assembly checkpoint

2

6.40E-02

CENPE, CENPF

positive regulation of mitotic cell cycle

2

7.00E-02

BIRC5, BRCA2

negative regulation of mitosis

2

7.00E-02

CENPE, CENPF

negative regulation of nuclear division

2

7.00E-02

CENPE, CENPF

negative regulation of macromolecule metabolic process

9

7.20E-02

BRCA2, CALR, CD276, CENPF, KCNIP3, PCGF2, PSMC1, SKIL, ZNF254

reproductive cellular process

4

7.30E-02

BRCA2, CASC5, HOOK1, PVRL2

mitotic chromosome condensation

2

7.50E-02

SMC2, SMC4

negative regulation of transcription from RNA polymerase II promoter

5

7.50E-02

CALR, KCNIP3, PCGF2, SKIL, ZNF254

protein localization

10

8.00E-02

CALR, CENPE, CENPF, EIF5A, HOOK1, KIF18A, RAB12, RPGR, SGOL2, STXBP4

negative regulation of nucleobase, nucleoside, nucleotide and nucleic acid metabolic process

7

8.60E-02

BRCA2, CALR, CENPF, KCNIP3, PCGF2, SKIL, ZNF254

establishment of protein localization

9

8.90E-02

CALR, CENPE, CENPF, EIF5A, HOOK1, KIF18A, RAB12, RPGR, STXBP4

in utero embryonic development

4

8.90E-02

BRCA2, NBN, PCGF2, RPGRIP1L

negative regulation of nitrogen compound metabolic process

7

9.10E-02

BRCA2, CALR, CENPF, KCNIP3, PCGF2, SKIL, ZNF254

positive regulation of cellular component organization

4

9.50E-02

CALR, CENPE, EIF5A, RICTOR

developmental growth

3

9.60E-02

BRCA2, NBN, PLAU

Table 5: Upregulated genes by si-UHRF1 were classified by DAVID program

Biological process

Number of genes

P-Value

Genes

regulation of transcription

15

1.40E-02

CRY2, ADRB2, EZH1, HCFC2, HIF3A, JRK, POFUT1, PRDM16, PRDM2, TLR4, ZNF10, ZNF331, ZNF44, ZNF655, ZNF91

regulation of transcription, DNA-dependent

10

7.00E-02

ADRB2, HCFC2, HIF3A, PRDM16, PRDM2, ZNF10, ZNF331, ZNF44, ZNF655, ZNF91

regulation of RNA metabolic process

10

7.90E-02

ADRB2, HCFC2, HIF3A, PRDM16, PRDM2, ZNF10, ZNF331, ZNF44, ZNF655, ZNF91

negative regulation of myeloid leukocyte differentiation

2

4.90E-02

PRDM16, TLR4

fucose metabolic process

2

5.20E-02

POFUT1, FPGT

brown fat cell differentiation

2

6.90E-02

ADRB2, PRDM16

negative regulation of myeloid cell differentiation

2

8.50E-02

PRDM16, TLR4

DISCUSSION

miRNAs are critical regulators of gene expression and they control many physiologic processes in mammalian cells [57]. There are abundant evidences that aberrantly expressed miRNAs can dysregulate otherwise well-controlled cellular RNA networks, thereby enhancing cancer cell development, progression, and metastasis [69]. The discovery of aberrantly expressed miRNAs and the resultant changes in RNA networks in cancer cells provide novel molecular explanations for cancer cell progression and metastasis. It is now apparent that dysregulated miRNAs play important roles in BC cell development [16]. Our past miRNA studies of BC cells showed that clustered miRNAs (including miR-1/133a (targeting TAGLN2), miR-23b/27b/24-1 (targeting EGFR, MET, and FOXM1), and miR-195/497 (targeting BIRC5 and WNT7A)) act as tumor-suppressive miRNAs through their regulation of several oncogenic genes and pathways [10, 1719].

Improved technological developments (next generation sequencing) have illuminated the role of miRNA networks in cancer cells. In this study, we examined the expression of miR-145-5p and miR-145 3p in BC cells because these miRNAs were significantly reduced in cancer cells as determined by deep sequencing. Our data demonstrated that miR-145-3p (the passenger-strand from pre-miR-145) had anti-tumor effects through targeting of UHRF1 in BC cells.

Downregulation of miR-145-5p (the guide-strand) is frequently observed in many types of cancer, and past studies have established the anti-tumor function of miR-145-5p through its regulation of several types of oncogenes in cancer cells [15]. Our group also identified the anti-tumor function of miR-145-5p in prostate cancer, renal cell carcinoma, bladder cancer, and esophageal squamous cell carcinoma [2023]. Importantly, p53 appears to transcriptionally regulate miR-145-5p by interaction with a potential p53 response element at the pre-miR-145 promoter region [24]. Moreover, c-MYC is directly repressed by miR-145-5p, indicating that it acts as a new member of the p53 regulatory network and contributes to the direct linkage between p53 and c-MYC in human cancer pathways [24]. In contrast to miR-145-5p, the functional significance of miR-145-3p in cancer cells has been obscure. This is the first report to evaluate the anti-tumor function of miR-145-3p in BC cells by gain-of-function assays.

miRNAs are often associated in clusters in the genome, and several studies have focused on the functional role of clustered miRNAs in human cancers [17, 18, 2023, 25]. In the human genome, 429 human miRNAs have been found to be clustered at 144 sites, with inter-miRNA distances of less than 5,000 base pair (miRBase, release 21). Both miR-143 and miR-145-5p are known to be located close together on human chromosome 5q32, where they form a cluster [26]. Based on our miRNA signatures, miR-143 and miR-145-5p are the most frequently downregulated miRNAs in various types of human cancers [26]. These two miRNAs have been reported as tumor suppressors and studied extensively for their role in oncogenic pathways in several cancers [15]. Our past studies demonstrated that hexokinase-2 (HK2) and Golgi membrane protein 1 (GOLM1) were directly regulated by miR-143 and miR-145-5p in renal carcinoma and prostate cancer, respectively [22, 23].

In this study, we speculated that miR-145-5p and miR-145-3p worked together to regulate pathways in BC cell progression and metastasis. Our present data showed that UHRF1 was directly regulated by both miR-145-5p and miR-145-3p in BC cells. In previous studies of miRNA regulation of UHRF1 in cancers, UHRF1 was regulated by miR-146a/146b in gastric cancer [27], miR-9 in colorectal cancer [28], and miR-124 in BC [29]. However, there have been no previous reports about the effects of miR-145-5p and miR-145-3p on UHRF1.

The UHRF1 gene was first cloned as a transcription factor that binds to the promoter region of the topoisomerase IIα (TOP2A) gene and controls its expression levels [30]. UHRF1 is involved in a wide range of physiological and pathological phenomena, including cancer development and metastasis [31]. UHRF1 plays a pivotal role in controlling gene expression through regulating epigenetic mechanisms, including DNA methylation, histone deacetylation, histone methylation, and histone ubiquitination [31]. Overexpression of UHRF1 occurs in many types of cancer, and aberrantly expressed UHRF1 causes cancer cell activation through hyper-methylation of tumor-suppressor genes such as BRCA1, CDKN2A, p73, and RASSF1 [32]. Expression of UHRF1 might be used as a progression marker in cancer [32]. For example, the expression of UHRF1 in MIBC was greater than in NMIBC, and upregulation was associated with an increased risk of progression after transurethral resection [33]. Our present data showed that knockdown of UHRF1 significantly induced apoptosis in BC cells and expression levels of the gene correlated with cause specific survival. Our data support the past studies of UHRF1 in cancer research, suggesting UHRF1 plays essential roles in BC cell progression and might be a molecular target for BC treatment.

In this study, we identified UHRF1-regulated BC pathways by using genome-wide gene expression analysis of si-UHRF1-transfected cells. Our expression data showed that UHRF1 and TOP2A were significantly reduced by si-UHRF1 transfection, indicating the usefulness of the present analytic approach. Our data showed that several anti-apoptosis genes and pro-proliferation genes were involved in pathways downstream of UHRF1, such as BIRC5 and CENPF. BIRC5 is a member of the inhibitor of apoptosis (IAP) family preferentially expressed by many cancers, including BC [10], and its mediated cellular networks are essential for cancer cell proliferation and viability [34]. CENPF is a master regulator of prostate cancer malignancy. Together, FOXM1 and CENPF regulate target gene expression and activation in cancer cells [35, 36]. The identification of these novel molecular pathways and targets mediated by the miR-145-5p/145-3p/UHRF1 axis may lead to a better understanding of BC cell progression and metastasis.

In conclusion, downregulation of dual-strand miR- 145-5p and miR-145-3p was validated in BC clinical specimens, and these miRNAs were shown to function as tumor suppressors in BC cells. To the best of our knowledge, this is the first report demonstrating that tumor suppressive miR-145-5p and miR-145-3p directly targeted UHRF1. Moreover, UHRF1 was upregulated in BC clinical specimens and contributed to anti-apoptotic effects through its regulation of several oncogenic genes. Expression of UHRF1 might be a useful prognostic marker for survival of BC patients. The identification of novel molecular pathways and targets regulated by the miR-145-5p/miR-145-3p/UHRF1 axis may lead to a better understanding of BC progression and aggressiveness.

MATERIALS AND METHODS

Clinical specimens and cell lines

Clinical tissue specimens were collected from BC patients (n = 69) who had undergone transurethral resection of their bladder tumors (TURBT, n = 59) or cystectomy (n = 10) at Kagoshima University Hospital between 2003 and 2013. NBE (n = 12) were derived from patients with noncancerous disease. The specimens were staged according to the American Joint Committee on Cancer-Union Internationale Contre le Cancer tumor-node-metastasis (TNM) classification and histologically graded [37]. Our study was approved by the Bioethics Committee of Kagoshima University; written prior informed consent and approval were obtained from all patients. Patient details and clinicopathological characteristics are listed in Table 6.

Table 6: Characteristic of patients

Bladder cancer (BC)

Total number

69

 

 

Median age (range)

73

(40–94)

years

Gender

 Male

53

76.8%

 

 Female

16

23.2%

 

Tumor grade

 Low grade

45

65.2%

 

 High grade

22

31.9%

 

 Unknown

2

2.9%

 

T stage

 Tis

2

2.9%

 

 Ta

7

10.1%

 

 T1

25

36.2%

 

 T2

27

39.1%

 

 T3

4

5.8%

 

 T4

4

5.8%

 

N stage

 N0

40

58.0%

 

 N1

8

11.6%

 

 Unknown

21

30.4%

 

M stage

 M0

58

84.1%

 

 M1

5

7.2%

 

 Unknown

6

8.7%

 

Operation method

 TURBT

59

85.5%

 

 Cystectomy

10

14.5%

 

Normal bladder epithelium

 Total number

12

 

 

 Median age (range)

61

(47–72)

 years

Abbreviation: TURBT = transurethral resection of bladder tumor

We used two human BC cell lines: T24, which was invasive and obtained from the American Type Culture Collection; and BOY, which was established in our laboratory from an Asian male patient, 66 years old, who was diagnosed with stage III BC and lung metastasis [38, 39]. These cell lines were maintained in minimum essential medium supplemented with 10% fetal bovine serum in a humidified atmosphere of 5% CO2 and 95% air at 37°C.

Tissue collection and RNA extraction

Tissues were immersed in RNAlater (Thermo Fisher Scientific; Waltham, MA, USA) and stored at –20°C until RNA extraction was conducted. Total RNA, including miRNA, was extracted using the mirVana miRNA isolation kit (Thermo Fisher Scientific) following the manufacturer’s protocol. The integrity of the RNA was checked with an RNA 6000 Nano Assay kit and a 2100 Bioanalyzer (Agilent Technologies, Santa Clara, CA, USA) following the manufacturer’s protocol.

Quantitative real-time reverse transcription polymerase chain reaction (qRT-PCR)

The procedure for qRT-PCR quantification was described previously [40, 41]. Stem-loop RT-PCR (TaqMan MicroRNA Assays; product ID: 002278 for miR-145-5p and product ID: 002149 for miR-145-3p; Thermo Fisher Scientific) was used to quantify miRNAs according to previously published conditions [4042]. TaqMan probes and primers for UHRF1 (product ID: Hs 01086727_m1; Thermo Fisher Scientific) were assay-on-demand gene expression products. We used human GUSB (product ID: Hs99999908_m1; Thermo Fisher Scientific) and RNU48 (product ID: 001006; Thermo Fisher Scientific), respectively, as internal controls.

Transfections with miRNA mimic and small interfering RNA (siRNA) into BC cell lines

Mature miRNA molecules, Pre-miR miRNA precursors (hsa-miR-145-5p; product ID: PM11480, hsa-miR-145-3p; product ID: PM13036, and negative control miRNA; product ID: AM 17111; Thermo Fisher Scientific) were used in the gain-of-function experiments, whereas UHRF1 siRNA (product ID: HSS120939 and HSS179006; Thermo Fisher Scientific) and negative control siRNA (product ID: D-001810-10; Thermo Fisher Scientific) were used in the loss-of-function experiments. The transfection procedures and transfection efficiencies of miRNA in T24 and BOY cells were reported previously [4042].

Cell proliferation, migration, and invasion assays

To investigate the functional significance of the miR-145-5p, miR-145-3p, and UHRF1, we performed cell proliferation, migration, and invasion assays using T24 and BOY cells. The experimental procedures were performed as described in our previous studies [40-42].

Apoptosis assays

BC cell lines were transiently transfected with reagent only (mock), miR-control, miR-145-5p, miR- 145- 3p, siRNA-control, or si-UHRF1 at 10 nM in 6 well tissue culture plates, as described previously [14, 1719]. Cells were harvested by trypsinization 72 hours after transfection and washed in cold phosphate-buffered saline. For apoptosis assays, double staining with FITC-Annexin V and propidium iodide was carried out using a FITC Annexin V Apoptosis Detection Kit (BD Biosciences, Bedford, MA, USA) according to the manufacturer’s recommendations and analysed within 1 hour by flow cytometry (CyAn ADP analyzer; Beckman Coulter, Brea, CA, USA). Cells were identified as viable cells, dead cells, early apoptotic cells, and apoptotic cells using Summit 4.3 software (Beckman Coulter), and the percentages of early apoptotic and apoptotic cells from each experiment were then compared. As a positive control, we used 2 μg/mL cycloheximide.

Cell cycle assays

For the cell cycle analyses, cells were stained with PI using the Cycletest PLUS DNA Reagent Kit (BD Biosciences) following the protocol and analyzed by CyAn ADP analyzer (Beckman Coulter). The percentages of the cells in the G0/G1, S, and G2/M phases were determined and compared. Experiments were performed in triplicate.

Western blot analyses

Immunoblotting was performed with rabbit anti-UHRF1 antibodies (1:500, PA5-29884; Thermo Fisher Scientific), anti-PARP antibodies (1:500 #9542; Cell Signaling Technology; Danvers, MA, USA), anti-cleaved PARP antibodies (1:500 #5625; Cell Signaling Technology), and anti-GAPDH antibodies (1:10000 MAB374; Chemicon, Temecula, CA, USA). Specific complexes were visualized with an echochemiluminescence detection system (GE Healthcare, Little Chalfont, UK).

Immunohistochemistry

A tissue microarray of 68 urothelial cancers and 20 normal bladder tissues was obtained from US Biomax, Inc. (Rockville, MD, USA) (product ID: BL1002). Detailed information on all tumor specimens can be found at http://www.biomax.us/index.php. The tissue microarray was immunostained following the manufacturer’s protocol with an Ultra Vision Detection System (Thermo Scientific). The primary rabbit polyclonal antibodies against UHRF1 (PA5-29884; Thermo Fisher Scientific) were diluted 1:300. Immunostaining was evaluated according to a scoring method as described previously [17].

Genome-wide gene expression and in silico analyses for the identification of genes regulated by miR-145-5p and miR-145-3p

To further investigate the specific genes affected by miR-145-5p and miR-145-3p, we performed a combination of in silico and genome-wide gene expression analyses. We attempted to identify target genes using a BC cell line transfected with these miRNAs. A Sure Print G3 Human GE 8 × 60K Microarray (Agilent Technologies) was used for expression profiling of miR-145-5p and miR-145-3p transfectants. The microarray data were deposited into GEO (http://www.ncbi.nlm.nih.gov/geo/) and were assigned GEO accession number GSE66498. Next, we selected putative miRNA target genes using the microRNA.org database (August, 2010 release, http://www.microrna.org). Finally, to identify upregulated genes in BC, we analyzed publicly available gene expression data sets in GEO (accession numbers: GSE11783, GSE31684). The data were normalized and analyzed with Gene Spring software (Agilent Technologies) as described previously [22, 23, 4042]. The strategy for investigation of the target genes is shown in Figure 3.

Plasmid construction and dual luciferase reporter assays

Partial wild-type sequences of the 3′ UTR of UHRF1 or those with a deleted miR-145-5p and miR- 145- 3p target site (positions 1,179–1,198 of UHRF1 3′ UTR for miR- 145-5p, and positions 287–292 of UHRF1 3′ UTR for miR-145-3p) were inserted between the XhoI and PmeI restriction sites in the 3′ UTR of the hRluc gene in the psiCHECK-2 vector (C8021; Promega, Madison, WI, USA). T24 and BOY cell lines were transfected with 50 ng of the vector and 10 nM miR-145-5p or miR-145-3p using Lipofectamine 2000 (Thermo Fisher Scientific) and Opti-MEM (Thermo Fisher Scientific). The activities of firefly and Renilla luciferases in cell lysates were determined with a dual luciferase reporter assay system according to the manufacturer’s protocol (E1960; Promega). Normalized data were calculated as the ratio of Renilla/firefly luciferase activities.

Identification of downstream targets regulated by UHRF1 in BC

To investigate molecular targets regulated by UHRF1 in BC cells, we carried out gene expression analyses using si-UHRF1-transfected BC cell lines. Microarray data were used for expression profiling of si-UHRF1 transfectants. The microarray data were deposited into GEO (accession number: GSE77790). We analyzed common down or upregulated genes using the GEO dataset. The flow chart outlining the investigation of UHRF1 downstream genes is shown in Figure 10A and 10B.

Statistical analysis

Relationships among two or three variables and numerical values were analysed using the Mann-Whitney U test or Bonferroni-adjusted Mann-Whitney U test. Spearman’s rank test was used to evaluate the correlation among the expressions of miR-145-5p, miR-145-3p, and UHRF1. We estimated cause specific survival of 57 BC patients by using the Kaplan-Meier method. Among the 69 BC patients, 12 died of other causes. Therefore, we analyzed cause specific survival of 57 BC patients. Patients were divided into two groups according to the median value of UHRF1 expression, and the differences between the two groups were evaluated by the log-rank tests. We used Expert Stat View software, version 5.0 (SAS Institute Inc., Cary, NC, USA), for these analyses.

ACKNOWLEDGMENTS AND FUNDING

This study was supported by JSPS KAKENHI Grant Numbers 26293354, 25462490, and 26462416.

CONFLICTS OF INTEREST

The authors indicated no potential conflicts of interest.

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