Role of microRNA-7 and selenoprotein P in hepatocellular carcinoma

Abstract

There is an obvious need to diagnose hepatocellular carcinoma using novel non-invasive and sensitive biomarkers. In this regard, the aim of this study was to evaluate and correlate both relative quantification of microRNA-7 using quantitative real time polymerase chain reaction and quantitative analysis of selenoprotein P using enzyme-linked immunosorbent assay in sera of hepatocellular carcinoma patients, chronic liver disease patients, as well as normal healthy subjects in order to establish a new diagnostic biomarker with a valid non-invasive technique. In addition, this study aimed to investigate whether changes in selenium supply affect microRNA-7 expression and selenoprotein P levels in human hepatocarcinoma cell line (HepG2). The results showed a highly significant decrease in serum microRNA-7 relative quantification values and selenoprotein P levels in malignant group in comparison with benign and control groups. The best cutoff for serum microRNA-7 and selenoprotein P to discriminate hepatocellular carcinoma group from benign and control groups was 0.06 and 4.30 mg/L, respectively. Furthermore, this study showed that changes in selenium supply to HepG2 cell line can alter the microRNA-7 profile and are paralleled by changes in the concentration of its target protein (selenoprotein P). Hence, serum microRNA-7 and selenoprotein P appear to be potential non-invasive diagnostic markers for hepatocellular carcinoma. Moreover, the results suggest that selenium could be used as an anticancer therapy for hepatocellular carcinoma by affecting both microRNA-7 and selenoprotein P.

Introduction

Hepatocellular carcinoma (HCC) represents the fifth most common cancer and the third most leading cause of cancer-related deaths worldwide.¹ High morbidity observed in HCC is majorly attributed to the lack of early detection markers and poor prognosis. Hence, exploration of novel frontiers in HCC diagnosis and therapeutics remains to be high priority research areas.^2,3 HCC represents a public health problem in Egypt. It constitutes 70.48% of all liver tumors among Egyptians, representing the second most common malignancy after bladder cancer in men and breast cancer in women and the second most common cause of death in men.^4,5

Alpha-fetoprotein (AFP) is the most widely used tumor biomarker for HCC diagnosis. However, it has low sensitivity and specificity. This highlights the need for other methods that would be minimally invasive, simple, and reliable.⁶

MicroRNAs (miRNAs) are a class of short non-coding RNAs, which play a central role in sequence specific post-transcriptional gene attenuation.⁷ They are involved in various fundamental cellular processes as well as carcinogenesis. Moreover, miRNAs are highly stable in serum due to their resistance to RNase, extreme pH, and temperature. Therefore, they have been identified as candidate biomarkers for detecting early stage pre-symptomatic diseases, including HCC.^3,8–10

The current work used scanning algorithms to search for miRNA specific to HCC through several miRNA public databases, namely, miRCancer and miRTarBase databases (available at http://mircancer.ecu.edu/browse.jsp/ and http://mirtarbase.mbc.nctu.edu.tw/index.php). MicroRNA-7 (miR-7) has been proven to play a substantial role in tumorigenesis and to progress by several signaling pathways in various tumors, but its functions in the context of HCC need further study and investigation.^11–14 The selected miR-7 was analyzed by miRcode database (available at http://www.mircode.org/?gene=sepp1&mirfam=miR-7%2F7ab&class=&cons=&trregion) and based on previous study of Dewing et al.,¹⁵ where selenoprotein P (SeP) was selected as miR-7 target pair. SeP was retrieved and confirmed as an associated gene with HCC from gene atlas database (available at http://genatlas.medecine.univ-paris5.fr/imagine/biblio.php?menu=biblio). SeP is an extracellular protein produced primarily by the liver. It transports selenium (Se) from the liver to extra-hepatic tissues and protects against oxidative injury. It has been suggested to be the most sensitive measure of Se nutritional status.^16,17

Experiments with human tumor cell lines are basic pre-clinical trials for anticancer drug permission.¹⁸ In fact, the use of dietary antioxidants and micronutrients has been proposed for successful HCC management.¹⁹ Due to the narrow concentration range between beneficial and toxic effects and a potential negative influence on healthy tissue, application of selenite in cancer treatment is still discussed quite controversially.^20,21

The aim of this study was to evaluate the clinical significance of serum miR-7 based on relative quantification (RQ) values and quantitative analysis of serum SeP using enzyme-linked immunosorbent assay (ELISA) in HCC. To the best of our knowledge, this study is the first to evaluate the role of miR-7 in the sera of HCC patients aiming to suggest a potential diagnostic biomarker with a valid non-invasive technique. In addition, this study aimed to investigate whether changes in Se supply (in the form of selenite) affect miR-7 expression and SeP levels in human hepatocarcinoma cell line (HepG2).

Subjects and methods

This case-control study was conducted in collaboration between Medical Biochemistry and Molecular Biology Department and Tropical Medicine Department, Faculty of Medicine, Ain Shams University. It included 90 subjects subdivided into three groups—group 1: a total of 30 newly diagnosed HCC patients according to American Association for the Study of Liver Diseases (AASLD) Practice Guidelines; group 2: a total of 30 patients with chronic liver disease (CLD) diagnosed on clinical, laboratory, and/or ultrasonographic basis; and control group: a total of 30 normal healthy subjects. Patients who aged below 18 years, had a history of cancer within the last 5 years other than HCC, had previous radiotherapy or systemic chemotherapy, had former liver transplantation, and complained of immunosuppression and/or autoimmune co-morbidities were excluded from the study. Patients were recruited from both the outpatient Hepatoma Clinic and inpatients at the Tropical Medicine Department at Ain Shams University Hospitals. This study was approved by the Institutional Ethics Committee and all the participants granted their consent to share in this study.

Sample collection and processing

Venous blood (5 mL) was withdrawn from each subject under complete aseptic conditions and was left to clot for 30 min. Serum was separated by centrifugation at 4000g for 15 min. All samples were kept at −80°C until use.

Relative expression of miR-7 using quantitative real time polymerase chain reaction

Total RNA including miRNA was extracted from sera using miRNeasy Mini Kit (Qiagen, Hilden, Germany), according to the manufacturer’s protocol. Then, the total RNA was reverse transcribed using miScript II RT Kit (Qiagen). Expression of miR-7 and its housekeeping gene SNORD68 (used as endogenous control) was measured by quantitative real time polymerase chain reaction (qRT-PCR) performed using target-specific miScript Primer Assay and miScript SYBR Green PCR Kit (Qiagen) according to the manufacturer’s protocol. Relative expression levels of the miR-7 were measured using 2^−ΔΔCt method²² with SNORD68 being used as the internal control to normalize the data.

Quantitative determination of serum SeP

The quantitative determination of serum SeP was done by ELISA using the commercially available ELISA Kit supplied by CUSABIO^® (USA) according to the manufacturer’s instructions.

Cell cultures

Potential cytotoxicity of sodium selenite (NaSe) on HepG2 cell lines was tested using the method of Skehan et al.²³ HepG2 cells were plated onto 96-multiwell plates (10⁴cells/well) for 24 h before treatment with NaSe to allow cell adhesion with the wall of the plate. Different concentrations of NaSe (1, 2, 4, and 8 µM) were added to the cell monolayer. Triplicate wells were prepared for each individual dose. Monolayer cells were incubated with NaSe for 48 and 72 h at 37°C and in an atmosphere of 5% CO₂. After incubation, the cells were fixed, washed, and stained with sulforhodamine B stain (Sigma). Excess stain was washed with acetic acid and attached stain was recovered with Tris-ethylenediaminetetraacetic acid (EDTA) buffer. Color intensity was measured in an ELISA reader. Cell viability (CV) was calculated by setting the cell viabilities of non-treated cells to 100%. The relation between surviving fraction and NaSe concentration was plotted to get the survival curve of HepG2 cell line after incubation with NaSe for 48 and 72 h. Calculation of the substance’s inhibitory concentration inducing 50% cell viability (IC₅₀) was done. To determine the effect of different Se concentrations on miR-7 expression and SeP concentration, six-well plates with HepG2 cells were cultured and incubated for 72 h with different concentrations of NaSe (0.75, 1.5, and 3.2 µM). miR-7 relative expression was determined after the extraction of RNA from HepG2 cells grown in either Se-deficient or Se-adequate medium. In addition, SeP levels were measured in culture medium.

Statistical analysis

All analyses were done using the Statistical Package for the Social Sciences (SPSS software version 20, Chicago, IL, USA) on a personal computer. Mann–Whitney and Kruskal–Wallis tests were used for statistical comparison of the non-parametric data variables between different groups. Chi-square analysis was used to find out the relation between various qualitative data. Variables were cross tabulated in all possible combinations against each other. The correlation coefficients (r) were calculated using the Spearman’s correlation. Receiver operating characteristic (ROC) curve determined the best value that gave maximum sensitivity and specificity. To determine independent predictors, the logistic regression analysis was used. p < 0.05 was considered significant and <0.01 was considered highly significant.

Results

Demographic, clinicopathological, and laboratory parameters of study subjects

Different demographic and laboratory parameters of subjects of the three groups are shown in Table 1. Moreover, the characteristics of HCC patients were investigated, including assessment of disease severity by Child–Pugh score, Barcelona-clinic liver cancer (BCLC) staging, tumor numbers, tumor size, lymph node enlargement, and extra-hepatic spread (Table 1).

Table 1.

Demographic, clinicopathological, and laboratory parameters in different study groups.

Demographic, clinicopathological, and laboratory parameters	HCC (n = 30)	CLD (n = 30)	Healthy control (n = 30)	p
Age (years)
≥57 (n = 50)	18 (60%)	15 (50%)	17 (56.7%)	>0.05a
<57 (n = 40)	12 (40%)	15 (50%)	13 (43.3%)
Sex
Male (n = 55)	23 (76.7%)	15 (50%)	17 (56.7%)	>0.05a
Female (n = 35)	7 (23.3%)	15 (50%)	13 (43.3%)
Smoking status
Smoker (n = 15)	7 (23.3%)	2 (6.7%)	6 (10%)	>0.05a
Non-smoker (n = 75)	23 (76.7%)	28 (93.3%)	24 (80%)
Bilharziasis antibody
Positive (n = 34)	19 (63.3%)	15 (50%)	0 (0%)	<0.01a,**
Negative (n = 56)	11 (36.7%)	15 (50%)	30 (100%)
HCV-Ab
Positive (n = 52)	26 (86.7%)	26 (86.7%)	0 (0%)	<0.01a,**
Negative (n = 38)	4 (13.3%)	4 (13.3%)	30 (100%)
HBVsAg
Positive (n = 5)	3 (10%)	2 (6.7%)	0 (0%)	>0.05a
Negative (n = 85)	27 (90%)	28 (93.3%)	30 (100%)
Cirrhosis
Cirrhotic (n = 26)	10 (33.3%)	16 (53.3%)	0 (0%)	<0.01a,**
Non-cirrhotic (n = 64)	20 (66.7%)	14 (46.7%)	30 (100%)
Total bilirubinb	62.05	56.33	18.12	<0.01c,**
Albuminb	33.03	29.82	73.65	<0.01c,**
ASTb	63.72	42.95	29.83	<0.01c,**
ALTb	60.70	37.92	37.88	<0.01c,**
ALPb	57.37	63.50	15.63	<0.01c,**
AFPb	70.18	48.03	18.27	<0.01c,**
Child–Pugh score
A	10 (33.3%)	–	–	–
B	8 (26.7%)
C	12 (40%)
BCLC stage
0	2 (6.7%)	–	–	–
A	8 (26.6%)
B	2 (6.7%)
C	6 (20%)
D	12 (40%)
Number of focal lesions
Single	24 (80%)	–	–	–
Multiple	6 (20%)
Tumor size
≥3	15 (50%)	–	–	–
<3	15 (50%)
Lymph node enlargement
Positive	2 (6.7%)	–	–	–
Negative	28 (93.3%)
Extra-hepatic spread
Positive	3 (10%)	–	–	–
Negative	27 (90%)

HCC: hepatocellular carcinoma; CLD: chronic liver disease; HCV-Ab: hepatitis C virus antibody; HBVsAg: hepatitis B virus surface antigen; AST: aspartate transaminase; ALT: alanine transaminase; ALP: alkaline phosphatase; AFP: alpha-fetoprotein; BCLC: Barcelona-clinic liver cancer.

a

Chi-square test.

b

Values are expressed as mean rank.

c

Kruskal–Wallis test.

p > 0.05, non-significant; **p < 0.01, highly significant.

Serum miR-7 RQ values and SeP levels in HCC patients

Results showed that serum miR-7 RQ values and SeP levels were significantly lower in HCC patients compared to both CLD patients and healthy controls (p < 0.01, Table 2). ROC curve was done to determine the best cutoff values for miR-7 and SeP discriminating the malignant group from benign and control groups (Figure 1). The positivity rates of serum miR-7 and SeP were estimated among the different groups of the study (p < 0.01, Table 2). Serum miR-7 and SeP positivity rates in relation to different demographic and clinicopathological variables in HCC group revealed no significant difference (p > 0.05, Table 3).

Table 2.

Serum miR-7 RQ values and serum levels of SeP among the different study groups.

Parameter	HCC (n = 30)	CLD (n = 30)	Healthy control (n = 30)	p
miR-7
Median	0.012	0.077	2.082	<0.01a,**
Mean rank	21.60	39.53	75.37
Positivity rate “number of cases ≤0.06 (%)”	23 (76.67)	9 (30)	0 (0)	<0.01b,**
SeP
Median (mg/L)	2.52	5.07	6.43	<0.01a,**
Mean rank	19.93	48.02	68.55
Positivity rate “number of cases ≤4.30 mg/L (%)”	26 (86.67)	9 (30)	2 (6.67)	<0.01b,**

miR-7: microRNA-7; RQ: relative quantification; SeP: selenoprotein P; HCC: hepatocellular carcinoma; CLD: chronic liver disease.

a

Kruskal–Wallis test.

b

Chi–square test.

**

p < 0.01, highly significant.

Figure 1.

ROC curve analysis for serum miR-7 and SeP to calculate the best cutoff value discriminating the HCC group from CLD and healthy control groups.

AUC: area under the curve; PPV: positive predictive value; NPV: negative predictive value.

[Figure omitted. See PDF]

Table 3.

Positivity rates of miR-7 RQ and SeP in relation to different demographic and clinicopathological variables in HCC group.

Demographic and clinicopathological variables	miR-7					SeP
	Median	Mean rank	p	Positivity raten (%)	pa	Median	Mean rank	p	Positivity raten (%)	pa
Age (years)
≥57 (n = 18)	0.005	13.81	>0.05b	15 (83.33)	>0.05	2.65	15.25	>0.05b	17 (94.44)	>0.05
<57 (n = 12)	0.016	18.04		8 (66.67)		2.34	15.88		9 (75)
Sex
Male (n = 23)	0.015	16.98	>0.05b	17 (73.91)	>0.05	2.43	16.43	>0.05b	19 (82.61)	>0.05
Female (n = 7)	0.005	10.64		6 (85.71)		2.60	12.43		7 (100)
Smoking status
Smoker (n = 7)	0.018	16.43	>0.05b	6 (85.71)	>0.05	2.82	18.93	>0.05b	6 (85.71)	>0.05
Non-smoker (n = 23)	0.012	15.22		17 (73.91)		2.43	14.46		20 (86.96)
Bilharziasis antibody
Positive (n = 19)	0.015	16.47	>0.05b	13 (68.42)	>0.05	2.70	16.39	>0.05b	17 (89.47)	>0.05
Negative (n = 11)	0.010	13.82		10 (90.91)		2.25	13.95		9 (81.82)
HCV-Ab
Positive (n = 26)	0.014	16.29	>0.05b	20 (76.92)	>0.05	2.40	15.10	>0.05b	22 (84.62)	>0.05
Negative (n = 4)	0.003	10.38		3 (75)		2.70	18.13		4 (100)
HBVsAg
Positive (n = 3)	0.004	7.33	>0.05b	3 (100)	>0.05	2.43	12.50	>0.05b	3 (100)	>0.05
Negative (n = 27)	0.015	16.41		20 (74.07)		2.60	15.83		23 (85.19)
Cirrhosis
Cirrhotic (n = 10)	0.019	15.70	>0.05b	6 (60)	>0.05	2.57	15.50	>0.05b	9 (90)	>0.05
Non-cirrhotic (n = 20)	0.012	15.40		17 (85)		2.49	15.50		17 (85)
Child–Pugh score
A (n = 10)	0.012	13.75	>0.05c	7 (70)	>0.05	2.48	15.75	>0.05c	8 (80)	>0.05
B (n = 8)	0.005	12		8 (100)		2.52	13.88		8 (100)
C (n = 12)	0.024	19.29		8 (66.67)		2.60	16.38		10 (83.33)
BCLC stage
0 (n = 2)	0.072	15	>0.05c	1 (50)	>0.05	2.17	12.75	>0.05c	2 (100)	>0.05
A (n = 8)	0.019	17.06		7 (87.5)		2.80	17.31		6 (75)
B (n = 2)	0.048	14		1 (50)		3.20	19.75		2 (100)
C (n = 6)	0.003	6.5		6 (100)		2.10	10.83		6 (100)
D (n = 12)	0.024	19.29		8 (66.67)		2.60	16.38		10 (83.33)
Number of focal lesions
Single (n = 24)	0.009	14.65	>0.05b	19 (79.17)	>0.05	2.52	15.44	>0.05b	21 (87.5)	>0.05
Multiple (n = 6)	0.024	18.92		4 (66.67)		2.90	15.75		5 (83.33)
Tumor size
≥3 (n = 15)	0.007	14.70	>0.05b	10 (66.67)	>0.05	2.43	16.47	>0.05b	13 (86.67)	>0.05
<3 (n = 15)	0.018	16.30		13 (86.67)		2.82	14.53		13 (86.67)
Lymph node enlargement
Positive (n = 2)	0.005	8	>0.05b	2 (100)	>0.05	3.46	20.75	>0.05b	1 (50)	>0.05
Negative (n = 28)	0.014	16.04		21 (75)		2.52	15.13		25 (89.29)
Extra-hepatic spread
Positive (n = 3)	0.010	13.83	>0.05b	3 (100)	>0.05	1.10	7.67	>0.05b	3 (100)	>0.05
Negative (n = 27)	0.015	15.69		20 (70.07)		2.70	16.37		23 (85.19)

miR-7: microRNA-7; RQ: relative quantification; SeP: selenoprotein P; HCC: hepatocellular carcinoma; HCV-Ab: hepatitis C virus antibody; HBVsAg: hepatitis B virus surface antigen; BCLC: Barcelona-clinic liver cancer.

a

Chi-square test.

b

Mann–Whitney test.

c

Kruskal–Wallis test.

p > 0.05, non-significant.

In addition, correlation analysis was performed between the three groups regarding both miR-7 RQ values and SeP levels, and different laboratory parameters (p < 0.05, Table 4). Regarding HCC group, there was a significant positive correlation between serum miR-7 RQ values and serum SeP levels (r = 0.372, p < 0.05). However, there was no significant correlation between serum miR-7 RQ or SeP and the different laboratory parameters in HCC group (p > 0.05).

Table 4.

Correlation between serum miR-7 RQ values, serum levels of SeP, and laboratory parameters in all study groups.

Spearman’s ρ	miR-7	SeP	Total bilirubin	Albumin	AST	ALT	ALP	AFP
miR-7
r	1.000	0.741	−0.611	0.582	−0.363	−0.239	−0.619	−0.698
p	–	<0.01**	<0.01**	<0.01**	<0.01**	<0.05*	<0.01**	<0.01**
SeP
r	0.741	1.000	−0.490	0.510	−0.434	−0.279	−0.487	−0.618
p	<0.01**	–	<0.01**	<0.01**	<0.01**	<0.01**	<0.01**	<0.01**

miR-7: microRNA-7; RQ: relative quantification; SeP: selenoprotein P; AST: aspartate transaminase; ALT: alanine transaminase; ALP: alkaline phosphatase; AFP: alpha-fetoprotein; r: correlation coefficient.

*

p < 0.05, significant; **p < 0.01, highly significant.

Furthermore, regression analysis revealed that serum AFP, miR-7 RQ, and SeP after identifying the cutoff were statistically significant independent predictors of HCC risk (p < 0.01, Table 5).

Table 5.

Predictive power of miR-7 RQ and SeP for the development of HCC by logistic regression analysis.

Parameter	B	Significance	Exp(B)	95% CI for Exp(B)
				Lower	Upper
Mean age	0.500	0.556	1.649	0.312	8.710
HCV-Ab	2.462	0.055	11.730	0.946	145.459
miR-7 RQ after cutoff	2.793	0.003	16.322	2.548	104.569
SeP after cutoff	4.026	0.000	56.042	6.464	485.849
AFP after cutoff (10 ng/mL)	2.626	0.008	13.825	1.981	96.463
Constant	−16.845	0.000	0.000

miR-7: microRNA-7; RQ: relative quantification; SeP: selenoprotein P; HCC: hepatocellular carcinoma; CI: confidence interval; HCV-Ab: hepatitis C virus antibody; AFP: alpha-fetoprotein.

Cytotoxicity of NaSe on HepG2 cell lines

The relation between surviving fraction of HepG2 cell lines and various concentrations of NaSe after incubation for 48 and 72 h is shown in Table 6 and Figure 2. The effect of NaSe on HepG2 cell line was dose and time dependent. The NaSe toxicity in HepG2 cells after 48 h of exposure was remarkably low with cell viabilities of >60% even at a concentration of 8 µM. The IC₅₀ was 3.2 µM after 72 h exposure.

Table 6.

Cytotoxicity of NaSe on HepG2 cell lines after incubation for 48 and 72 h.

NaSe (µM)	Surviving fraction (48 h)	Surviving fraction (72 h)
0.000	1.000	1.000
1.000	0.959	0.950
2.000	0.822	0.617
4.000	0.694	0.427
8.000	0.630	0.333

NaSe: sodium selenite.

Figure 2.

The survival curve of HepG2 cell line after incubation with various concentrations (1, 2, 4, and 8 µM) of NaSe: (a) for 48 h and (b) for 72 h. Values were of three independent experiments.

[Figure omitted. See PDF]

miR-7 relative expression and SeP analysis in HepG2 cell lines

The relative expression of miR-7 markedly increased in a dose-dependent fashion as detected by qRT-PCR in cells grown in Se-adequate medium (Figure 3(a)). As for SeP, its levels in the culture medium were markedly increased in a dose-dependent fashion as detected by ELISA. They were notably higher in Se-adequate medium (Figure 3(b)).

Figure 3.

(a) Relative expression of miR-7 measured by qRT-PCR from Se-adequate and Se-depleted HepG2 cells. (b) Influence of NaSe on the secretion of SeP by HepG2 cells.

[Figure omitted. See PDF]

Discussion

HCC is a major health problem worldwide and its diagnosis is still challenging. MiRNAs have emerged as a novel class of potential diagnostic biomarkers with high accuracy in cancer detection.²⁴

In this study, males constituted 76.7% of HCC patients. Accordingly, higher incidence of HCC was observed in males as reported by other studies.^24–27 Results showed no statistically significant differences between the subjects of the three groups concerning age, sex, and smoking status. This was in accordance with previous studies.^24,28

There was a highly significant difference between the three groups regarding necroinflammatory markers (aspartate transferase (AST), alanine transaminase (ALT)), liver synthetic function tests (albumin and bilirubin), and alkaline phosphatase (ALP; p < 0.01). These findings came in agreement with other reports.^24,28

Concerning serum level of AFP in all studied groups, the results of this study showed that HCC had the highest level compared to other groups with statistically significant difference (p < 0.01). These results were confirmed by previous studies.^24,28,29

Depending on their messenger RNA (mRNA) targets, miRNAs may act as oncogenes (onco-miRs) or tumor suppressors (TS-miRs). miR-7 has been considered as a double-edged sword where it may act either as an onco-miR or as a TS-miR in different tumor types through its participation in distinct pathways and regulation of discrete target genes in different cell types.^12,30–37 This study revealed that serum miR-7 RQ values were significantly lower in the HCC group compared to both CLD and healthy control groups (p < 0.01). In fact, most studies describing the role of miR-7 in HCC have been in vitro experiments with the exception of the study done by Fang et al.¹⁴ who analyzed the expression of miR-7 using qRT-PCR in 10 pairs of clinical HCC tissue samples and reported repression of miR-7 expression in 7 of 10 HCC cases compared to paired normal tissues. The findings of this study were consistent with other reports which confirmed that miR-7 is implicated in HCC, suggesting that it acts as a tumor suppressor, where miR-7 was found to be down-regulated in HCC tissues and inhibit proliferation and metastasis in HCC cells in vitro and in vivo, through different target genes and signaling pathway.^30,38,39

Moreover, the down-regulation of miR-7 detected in CLD patients in this study may suggest that miR-7 is involved in the process of inflammation. Thus, these cases should be followed up, as chronic inflammation is reported to play an important role in the pathogenesis of HCC. According to Forner et al.,⁴⁰ CLD is the major risk factor for the development of HCC and thus preventing or treating liver disease can decrease the risk of HCC.

Regarding SeP, its decreased expression and decreased serum/plasma level were reported in different types of cancer, including renal cell carcinoma, colorectal adenoma, gastric adenocarcinoma, prostate cancer, and lung cancer.^41–47

The quantitative analysis of serum SeP in this study using ELISA revealed a marked decrease in SeP levels in HCC group as compared to CLD and healthy control groups (p < 0.01). These results confirmed the findings of Li et al.⁴⁸ who reported that SeP mRNA expression was significantly lower in HCC tissues compared to that of normal liver and cirrhosis, suggesting that SeP might play a role in the occurrence and development of HCC.

Correlation analysis indicated that serum SeP level was reduced along with miR-7 down-regulation. Furthermore, there was significant correlation between both miR-7 and SeP, along with necroinflammatory markers (ALT, AST) and liver synthetic function tests (albumin and bilirubin) in all studied groups. This may suggest the use of serum miR-7 and SeP as new parameters for assessment of liver function.

As AFP is frequently used for the diagnosis of HCC, the relationship between AFP and both miR-7 RQ values and SeP levels was investigated, and the results showed that the expression of miR-7 and SeP levels in HCC patients was negatively associated with the corresponding AFP level. The correlation indicated that miR-7 and SeP might be potential biomarkers in the clinical diagnosis of HCC.

In cultured cell models, Se compounds have been shown to inhibit cancer cell growth by decreasing cell proliferation through cell cycle arrest and/or increasing the apoptosis.^49,50 A dose and time-dependent study was performed in the current work using different concentrations of NaSe which gave an IC₅₀ value of approximately 3.2 µM with an incubation period of 72 h.

In comparison with previous studies, Hinrichsen and Planer-Friedrich¹⁸ reported that especially at short exposure times, selenite toxicity to HepG2 cells was remarkably low and with longer exposure times, selenite toxicity increased. In Hinrichsen and Planer-Friedrich’s¹⁸ study, 5 µM selenite resulted in 87% CV after 24 h, while in the study of Zhang et al.,²⁰ 6 µM selenite resulted in 90% CV after 72 h. The difference in results could be attributed to different cell culture conditions. In addition, the results of this study showed that changes in Se supply to HepG2 cell line can alter the miRNA profile. Furthermore, the changes in the miR-7 profile were paralleled by changes in the concentration of its target protein (SeP).

Conclusion

In conclusion, this study suggests that both serum miR-7 and SeP could serve as potential diagnostic biomarkers for HCC. Measurement of these biomarkers in serum is easy, non-invasive, and more practical than determining them in tissue samples which can be obtained only by invasive procedures. Furthermore, our results suggest that Se could be used as an anticancer therapy for HCC by affecting both miR-7 and SeP.

All procedures performed in the studies involving human participants were in accordance with the ethical standards of the institutional and/or National Research Committee and with the 1964 Declaration of Helsinki and its later amendments or comparable ethical standards.

Declaration of conflicting interests

The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Funding

The author(s) disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: This work was supported by Ain Shams University Faculty of Medicine Grants Office, Grant No. 2016-38.