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Abstract

BACKGROUND:

Circular RNAs (circRNA)are involved in the progression of cancers, and previous study showed that hsa_circ_0001649 expression is down-regulated in hepatocellular carcinoma (HCC).

OBJECTIVE:

To explore whether hsa_circ_0001649 is a prognostic biomarker for HCC and to investigate the biological functions of hsa_circ_0001649 in HCC.

METHODS:

Hsa_circ_0001649 expression was measured in 77 pairs of HCC and adjacent no-tumor tissues by quantitative Real-Time polymerase chain reaction. Kaplan-Meier curve and Cox regression were used to analyze its prognostic significance for HCC patients. In addition, the hsa_circ_0001649 was over-expressed using a circRNA-forming plasmid in HCC cells, and the biological function of hsa_circ_0001649 was investigated in vitro.

RESULTS:

We verified that hsa_circ_0001649 was down-regulated in HCC tissues compared with adjacent non-tumor tissues. In addition, low hsa_circ_0001649 expression was associated with the poor overall survival of HCC patients, and Cox multivariate analysis showed that hsa_circ_0001649 is a novel independent prognostic factor for HCC patients. Furthermore, the in vitro experiments demonstrated that over-expressed hsa_circ_0001649 inhibits the proliferation, migration, and invasion and promotes the apoptosis of HCC cells.

CONCLUSIONS:

Hsa_circ_0001649 could act as a novel prognostic biomarker for HCC patients. In addition, hsa_circ_ 0001649 might be a potential therapeutic target for HCC.

Keywords

Hsa_circ_0001649 hepatocellular carcinoma prognosis biomarker

1. Background

Hepatocellular carcinoma (HCC) is one of the most common malignant tumors, and more than 750, 000 people suffer from this disease every year [1]. Though advances in diagnosis, surgical techniques, liver transplantation have been made, long-term survival of patients with HCC still remains poor [2]. Therefore, it is critical to explore novel biomarkers and therapeutic targets to improve the prognosis of HCC patients.

Circular RNAs (circRNAs) are a large class of endogenous non-coding RNAs, which covalently linked the 5’ and 3’ ends together and formed circular loops [3, 4, 5]. CircRNAs were deemed as low abundance splicing errors with no biological function for decades [6, 7, 8]. Recently, due to the development of RNA-sequencing technology and bioinformatics, studies revealed that circRNAs are abundant, conserved, stable and tissue specific expressed in mammalian cells [3, 4, 5, 9]. An increasing number of studies showed a close relationship between circRNAs and cancers [10, 11, 12]. For example, the circRNAMTO1 is significantly down-regulated in HCC tissues, and the deceased amount of circRNAMTO1 is a predictor for poor patient survival [13]. In this study, we focused our attention on the circRNAhsa_circ_0001649 (Circbase ID) in HCC, which is located in chr6:146209155-146216113 and is predicted to be associated with HCC in citc2Traits (circTraits ID: hsa_circ_001599). Previously, Conn et al. [14] found that hsa_circ_000 1649 expression was significantly increased during TGF- $\beta$ induced epithelial-to-mesenchymal transition. Qin et al. [15] then reported that hsa_circ_0001649 expression was down-regulated in HCC tissues and hsa_circ_0001649 might regulate the metastasis of HCC. However, the relationship between hsa_circ_000 1649 expression and clinical prognosis of HCC patients and the biological functions of hsa_circ_0001649 remain unclear.

In the present study, hsa_circ_0001649 expression was detected in 77 pairs of HCC and adjacent non-tumor tissues by quantitative Real-Time polymerase chain reaction (qRT-PCR). In addition, the relationship between hsa_circ_0001649 expression and patients’ prognosis was analyzed. Furthermore, the biological functions of hsa_circ_0001649 were explored in vitro.

2. Material and methods

2.1 Patients and samples

Seventy-seven pairs of HCC and adjacent non-tumor tissues were obtained from HCC patients (71 males and 6 females, mean age 57 $\pm$ 11) at the Zhongnan Hospital of Wuhan University from 2011 to 2014. The patients with preoperative chemotherapy or radiotherapy were excluded. Alanine aminotransferase (ALT) and aspartate aminotransferase (AST) was measured by Lactate dehydrogenase method using BECKMAN AU5800, $\alpha$ -fetoproteinï¼ˆAFPï¼‰ was measured by chemiluminescence using ARGHITECT i4000, and the HBV DNA copies were measured using qRT-PCR (Bio-Rad, USA). The study conforms with The Code of Ethics of the World Medical Association (Declaration of Helsinki), printed in the British Medical Journal (18 July 1964). In addition, the study was approved by the Ethics Committee of Zhongnan Hospital of Wuhan University and all patients signed the written informed consent.

2.2 RNA extraction and reverse transcription

Total RNA content of tissues were extracted using the Trizol reagent (Invitrogen, USA) according to the manufacturer’s instructions. The concentration and purity of the obtained RNA samples were measured using the NanoDrop ND2000 (Thermo, USA). The RNA samples were reverse-transcribed to cDNA using the PrimeScript ${}^{\rm TM}$ RT reagent Kit with gDNA Eraser (Takara, Japan) according to the manufacturer’s instructions.

2.3 qRT-PCR

qRT-PCR was performed with SYBR ${}^{\@setsize{\scriptsize}{8pt}{\viipt}{\@viipt}{\textregistered}}$ Premix Ex Taq ${}^{\rm TM}$ II (Takara, China) on the Bio-Rad CFX96 (Bio-Rad, USA) according to the manufacturer’s instructions. The reactions began with an initial denaturation at 95 ${}^{\circ}$ C for 5min, followed by denaturation at 95 ${}^{\circ}$ C for 30 s, annealing at 63.3 ${}^{\circ}$ C for 30 s and extension at 72 ${}^{\circ}$ C for 30 s. The denaturation, annealing, and extension steps were repeated for 40 cycles. The glyceraldehyde 3-phosphate dehydrogenase (GAPDH) gene was used as internal control. The specific primers used for the PCR reactions ofhsa_circ_0001649 were: forward, 5’-CCCATATTGAACCCTGCCCAT-3’; reverse, 5’-TTCTGACCACAGCTTCCACTT-3’). All the experiments were performed in duplicate.

2.4 Plasmid construction

We used the pcDNA3.1(+) circRNA mini vector (Addgene plasmid # 60648), which is a circRNA-forming plasmid obtained from Jeremy Wilusz [16], to subclone the hsa_circ_0001649 sequence for the transfection studies. The hsa_circ_0001649cDNA was amplified using PCR with specific primers. The obtained PCR fragments were subcloned into the EcoRV and SacII sites of the pcDNA3.1 (+) circRNA mini vectors. Afterwards, the reconstructed plasmidpcDNA3.1(+) circRNA-hsa_circ_0001649 was validated using DNA sequencing (TsingKe, China). Finally, more copies of the plasmid was produced and purified using the Mini Plasmid Preparation Kit (Axygen, China) according to the manufacturer’s instructions.

2.5 Cell culture and plasmid transfection

The HCC cell lines HepG2, HCCLM9, HCCLM3, and MHCC97L as well as the immortalized human hepatic cell line L02 were obtained from the Cell Bank of Type Culture Collection of Chinese Academy of Sciences (Shanghai, China). Cells were cultured in DMEM (Gibco, USA) with 10% fetal bovine serum (Gibco, USA) in a humidified incubator at 37 ${}^{\circ}$ C with 5% CO ${}_{2}$ . A six-well plate was seeded with 5 $\times$ 10 ${}^{5}$ cells and incubated for 24 h. The cells were then transfected with the related genes using Lipofectamine ${}^{\rm TM}$ 2000 (Invitrogen, USA) according to the manufacturer’s instructions.

2.6 Cell proliferation assay

Cell proliferation assays were conducted using the Cell Counting Kit-8 (CCK-8) (Dojindo, Japan). In brief, transfected cells were seeded into 96-well plates (2000 cells/well). Each well was added with 10 $\mu$ l of CCK8 solution, and the plates were then incubated at 37 ${}^{\circ}$ C for an additional 2 h. Finally, the solution was measured at 450 nm on the spectrophotometer (EnSpire, PerkinElmer, USA). The assay was repeated for three times.

2.7 Apoptosis analysis

The cell apoptosis was detected using propidium iodide (PI) and fluorescein isothiocyanate (FITC)-conjugated Annexin V staining. Briefly, transfected cells were harvested after transfection for 24 h, and stained using an Annexin V-FITC/PI Apoptosis Detection Kit (Beyotime, China) according to the manufacturer’s instructions. The cells were then analyzed using a Cytomics ${}^{\rm TM}$ FC500 flow cytometer (Beckman Coulter, USA). The assay was repeated for three times.

2.8 Transwell assays

Transfected cells were harvested after transfection for 24 h, and seeded into the upper chambers (20000 cells/chamber) of plates (Corning, USA) with 200 $\mu$ l of serum-free DMEM to quantify cell migration. Similarly, transfected cells were seeded into the upper chambers (40000 cells/chamber) of transwell plates with Matrigel-coated membranes (BD, USA) in 200 $\mu$ l serum-free DMEM to quantify cell invasion. The lower chambers were added with DMEM containing 10% FBS. After an incubation period of 24 h, the medium was removed, and cells were fixed with methanol for 20 min. The cells were stained with crystal violet for 20 min, air-dried, and photographed with a digital microscope. The number of cells was calculated from five random fields in each chamber. The assays were repeated for three times.

2.9 Statistical analyses

GraphPad Prism 5.0 and SPSS version 21.0 (SPSS Inc, USA) were used to do the statistical analyses. The numerical data are presented as mean $\pm$ standard error of the mean (M $\pm$ SEM). The - $\Delta$ Ct value was determined by subtracting the Ct value of circRNA from the Ct value of GAPDH. Results were considered statistically significant at $P<$ 0.05. Kaplan-Meier curves were constructed to analyze the relationship between hsa_circ_0001649 expression and the overall survival (OS) rate of HCC patients, and Cox regression models were performed to identify independent prognostic factors of OS.

3. Results

3.1 Down-regulation of hsa_circ_0001649 expression in HCC

To explore the expression profile of hsa_circ_000 1649, qRT-PCR was performed in 77 pairs of HCC and adjacent non-tumor tissues. As shown in Fig. 1, thehsa_circ_0001649 expression in HCC tissues was significantly down-regulated compared with the paired adjacent non-tumor tissues ( $P<$ 0.001). The correlations of hsa_circ_0001649 expression with clinicopathological parameters are presented in Table 1. No significant correlation was found between hsa_circ_00 01649 expression in HCC tissues and clinicopathological characteristics, including gender, age, smoking, alcoholism, tumor size, tumor foci, TNM stage, differentiation, ALT, AST, AFP, and HBV.

Table 1
Correlation between hsa_circ_0001649 expression (- $\Delta$ Ct) and clinical parameters in HCC

Characteristics	Patient number	Mean $\pm$ SEM	$P$
Gender			0.501
Female	6	$-$ 7.94 $\pm$ 1.12
Male	71	$-$ 8.65 $\pm$ 0.29
Age			0.504
$<$ 54	38	$-$ 8.79 $\pm$ 0.43
$\geqslant 4$	39	$-$ 8.41 $\pm$ 0.37
Smoking			0.149
Positive	50	$-$ 8.30 $\pm$ 0.38
Negative	27	$-$ 9.15 $\pm$ 0.38
Alcoholism			0.611
Positive	40	$-$ 8.45 $\pm$ 0.36
Negative	37	$-$ 8.75 $\pm$ 0.44
Tumor size			0.991
$<$ 5 cm	20	$-$ 8.60 $\pm$ 0.60
$\geqslant$ 5 cm	57	$-$ 8.60 $\pm$ 0.32
Tumor foci			0.788
1	52	$-$ 8.55 $\pm$ 0.34
$>$ 1	23	$-$ 8.71 $\pm$ 0.51
TNM stage			0.428
I/II	34	$-$ 8.85 $\pm$ 0.45
III/IV	43	$-$ 8.40 $\pm$ 0.36
Differentiation			0.472
High/moderate	62	$-$ 8.50 $\pm$ 0.30
Low	15	$-$ 9.01 $\pm$ 0.73
ALT (U/L)			0.648
$\geqslant$ 46	45	$-$ 8.48 $\pm$ 0.35
$<$ 46	32	$-$ 8.75 $\pm$ 0.48
AST (U/L)			0.327
$\geqslant$ 46	37	$-$ 8.31 $\pm$ 0.42
$<$ 46	40	$-$ 8.87 $\pm$ 0.38
AFP (ng/mL)			0.986
$\geqslant$ 200	38	$-$ 8.64 $\pm$ 0.41
$<$ 200	39	$-$ 8.56 $\pm$ 0.39
HBV			0.860
$\geqslant$ 500	47	$-$ 8.64 $\pm$ 0.40
$<$ 500	30	$-$ 8.53 $\pm$ 0.37

Figure 1.

The expression of hsa_circ_0001649 was down-regulated in HCC tissues compared with adjacent non-tumor tissues. The expression levels of circSMAD2 are represented by the $-\Delta$ Ct value of each sample. The $-\Delta$ Ct value was determined by subtracting the Ct value of circRNA from the Ct value of GAPDH. Data are presented as the mean $\pm$ SEM. **, $P<$ 0.01.

Figure 2.

The overall survival rate analysis in patients with HCC by Kaplan-Meier method.

3.2 Prognostic value of hsa_circ_0001649 expression in HCC patients

To assess the prognostic significance of hsa_circ_00 01649 expression in HCC, patients were divided into high and low expression groups based on the expression levels of hsa_circ_0001649 in HCC tissues. Survival analysis revealed that hsa_circ_0001649 expression was significantly associated with the survival time of HCC patients (Fig. 2). Moreover, compared to those with hsa_circ_0001649 high expression levels, OS time was remarkably reduced in HCC patients with hsa_circ_0001649 low expression levels ( $P=$ 0.007). The Cox univariate analysis showed that hsa_circ_0001649 ( $P=$ 0.015), TNM stage ( $P=$ 0.001), and AST ( $P=$ 0.017) had statistically prognostic influences on OS of HCC patients. Furthermore, the Cox multivariate analysis demonstrated that hsa_circ_0001649 ( $P=$ 0.011) and TNM stage ( $P=$ 0.004) were the independent prognostic factors for OS of HCC patients (Table 2).

Table 2
Prognostic factors for overall survival in univariate and multivariate analyses

Parameters	Univariate analysis		Multivariate analysis
	HR (95% CI)	$P$	HR (95% CI)	$P$
Hsa_circ_0001649	0.283 (0.097–0.826)	0.015 ${}^{*}$	0.191 (0.053–0.682)	0.011 ${}^{*}$
Gender	1.499 (0.185–12.075)	0.721	NA	NA
Age	0.939 (0.334–2.640)	0.905	NA	NA
Smoking	1.285 (0.404–4.089)	0.677	NA	NA
Alcoholism	0.647 (0.235–1.783)	0.393	NA	NA
HBV	0.551 (0.195–1.566)	0.273	NA	NA
Tumor size	3.181 (0.715–14.147)	0.083	2.681 (0.516–13.947)	0.241
Tumor focal	0.986 (0.340–2.855)	0.979	NA	NA
TNM stage	7.758 (1.735–34.695)	0.001 ${}^{*}$	11.206 (2.132–58.892)	0.004 ${}^{*}$
Differentiation	0.292 (0.037–2.287)	0.164	NA	NA
AFP (ng/mL)	0.989 (0.351–2.783)	0.983	NA	NA
ALT (U/L)	2.517 (0.933–6.789)	0.073	1.556 (0.434–5.583)	0.497
AST (U/L)	3.525 (1.236–10.048)	0.017 ${}^{*}$	2.283 (0.636–8.187)	0.205

NA, not available; *, $P<$ 0.05.

Figure 3.

Over-expressed hsa_circ_0001649 inhibited the proliferation and promoted the apoptosis of HCC cells. (A) Hsa_circ_0001649 expression in HCC cell lines HepG2, HCCLM9, HCC97L but not HCCLM3 was down-regulated compared with the hepatic cell line L02. (B) Hsa_circ_0001649 expression was significantly up-regulated in HCC cells which were transfected with pcDNA 3.1- hsa_circ_0001649. (C) The CCK-8 assay showed that over-expressed hsa_circ_0001649 inhibited the proliferation of HCC cells. (D) The apoptosis assays showed that over-expressed hsa_circ_0001649 promoted the apoptosis of HCC cells.NC, negative control. *, $P<$ 0.05.

3.3 Over-expressedhsa_circ_0001649 inhibited the proliferation, migration, and invasion and promoted the apoptosis of HCC cells

Next, the hsa_circ_0001649 expression in the HCC and hepatic cell lines was detected by qRT-PCR. The results showed that hsa_circ_0001649 expression in HCC cell lines HepG2, HCCLM9, HCC97L but not HCCLM3 was down-regulated compared with the hepatic cell line L02 (Fig. 3A). To investigate the biological functions of hsa_circ_0001649, we over-expressed hsa_circ_0001649 using a circRNA-forming plasmid in HCC cell lines HCCLM9 (Fig. 3B). The CCK-8 assays showed that over-expressed hsa_circ_0001649 inhibited the proliferation of HCCLM9 cells (Fig. 3C). The sequential apoptosis assays showed that over-expressed hsa_circ_0001649 promoted the apoptosis of the HCC cells (Fig. 3D). In addition, the transwell assays demonstrated that over-expressed hsa_circ_000 1649 impaired the migration and invasion abilities of HCC cells (Fig. 4A and B).

Figure 4.

Over-expressed hsa_circ_0001649 inhibited the migration and invasion of HCC cells. (A) Over-expressed hsa_circ_0001649 inhibited the migration of HCC cells. (B) Over-expressed hsa_circ_0001649 inhibited the invasion of HCC cells. NC, negative control. *, $P<$ 0.05.

4. Discussion

In this study, we verified that hsa_circ_0001649 expression is down-regulated in HCC tissues compared with adjacent non-tumor tissues. In addition, we found that hsa_circ_0001649 is an independent prognostic biomarker for OS of HCC patients. Furthermore, the in vitro assays demonstrated that over-expressed hsa_circ_0001649 inhibited the proliferation, migration, and invasion and promoted the apoptosis of HCC cells.

Increasing evidence revealed that circRNAs are involved in the progression and act as biomarkers of cancers. For example, the circRNA LARP4 inhibits cell proliferation and invasion of gastric cancer and serve as an prognostic factor for OS of gastric cancer patients [17]. The circRNA hsa_circ_0001649 was revealed to function as a tumor suppressor gene in HCC and gastric cancer [15, 18]. However, the prognostic significance of hsa_circ_0001649 for HCC patients reminded unclear. In this study, Kaplan-Meier analysis showed that HCC patients with low hsa_circ_0001649 expression had significantly reduced OS than those with high hsa_circ_0001649 expression. Moreover, both univariate and multivariate analyses demonstrated that hsa_circ_0001649 was an independent favorable predictor of OS in HCC patients.

Qin et al. [15] found that down-regulation of hsa_ circ_0001649 in HCC cells significantly increases the mRNA level of matrix metallopeptidases 9, 10, and 13, which promotes the metastasis of HCC, suggesting that low expression of hsa_circ_0001649 might promote the metastasis of HCC [19]. To further explore the potential biological function of hsa_circ_0001649 in HCC, we over-expressed it using a circRNA-forming plasmid in HCC-derived cells. The transwell assays verified that over-expression of hsa_circ_0001649 inhibited the migration and invasion abilities of HCC cells. In addition, we found that over-expression of hsa_circ_0001649 inhibited the proliferation and promoted the apoptosis of HCC cells. Altogether, these data suggest that hsa_circ_0001649 might regulate the progression of HCC and might be a potential therapeutic target for HCC. Recently, studies revealed that circRNAs could regulate the apoptosis of tumor cells by acting as miRNA sponges [20, 21]. For example, Zhong et al. found that circRNA-MYLK might function as competing endogenous RNA (ceRNA) for miR-29a to regulate the activating of VEGFA/VEGFR2 and downstream Ras/ERK signaling pathway and thus modulate the apoptosis of bladder cancer cells [22]. In addition, Holdt et al. demonstrated that CircANRIL bound to pescadillo homologue 1 and thus induced nucleolar stress and p53 activation, which resulted in the induction of apoptosis [23] . Increasing evidence showed that circRNAs might regulate the progression of cancers by sponging the target microRNAs or regulating the expression of parental gene [3, 24, 25, 26, 27, 28, 29, 30]. For example, Chen et al. [31] reported that circRNA_100290 functions as a competing endogenous RNA to regulate the development of human oral squamous cell carcinomas through sponging up microRNA-29b family members. Li et al. [28]reported that circITCH might increase the expression level of its parental gene ITCH to exert inhibitory effect on esophageal squamous cell carcinoma. However, the exactly underlying mechanism of hsa_circ_0001649 in regulating the progression of HCC remains to be further investigated.

There were several limitations in our study. First, our experiments were done in vitro, the biological functions of hsa_circ_0001649 we found in HCC cells remained to be validated in vivo. Second, the study has been carried out on small number of subjects. Therefore, our findings need to be validated by a large number of cases trial.

In summary, the present study demonstrated that hsa_circ_0001649 might act as an independent prognostic biomarker for HCC patients. In addition, our data support that hsa_circ_0001649 regulates the progression of HCC and might be a potential therapeutic target for HCC.

Footnotes

Acknowledgments

This study was supported by National Basic Research Program of China (973 Program) (2012CB7206 05).

Conflict of interest

None declared.

Abbreviations

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Down-regulation of hsa_circ_0001649 in hepatocellular carcinoma predicts a poor prognosis

Abstract

BACKGROUND:

OBJECTIVE:

METHODS:

RESULTS:

CONCLUSIONS:

Keywords

1. Background

2. Material and methods

2.1 Patients and samples

2.2 RNA extraction and reverse transcription

2.3 qRT-PCR

2.4 Plasmid construction

2.5 Cell culture and plasmid transfection

2.6 Cell proliferation assay

2.7 Apoptosis analysis

2.8 Transwell assays

2.9 Statistical analyses

3. Results

3.1 Down-regulation of hsa_circ_0001649 expression in HCC

Table 1 Correlation between hsa_circ_0001649 expression (- Δ Ct) and clinical parameters in HCC

Table 2 Prognostic factors for overall survival in univariate and multivariate analyses

Footnotes

Acknowledgments

Conflict of interest

Abbreviations

References

Table 1
Correlation between hsa_circ_0001649 expression (- $\Delta$ Ct) and clinical parameters in HCC

Table 2
Prognostic factors for overall survival in univariate and multivariate analyses