Abstract

Heart development protein with EGF-like domains 1 (HEG1) plays critical roles in embryo development and angiogenesis, which are closely related to tumor progression. However, the role of HEG1 in hepatocellular carcinoma (HCC) remains unknown. In the present study, we explored the clinical significance, biological function and regulatory mechanisms of HEG1 in HCC and found that HEG1 is significantly up-regulated in HCC cell lines and primary tumor samples. Additionally, high HEG1 expression is correlated with aggressive clinicopathological features. Patients with high HEG1 expression had shorter overall survival (OS) and disease-free survival (DFS) than those with low HEG1 expression, which indicated that HEG1 is an independent factor for poor prognosis. Lentivirus-mediated HEG1 overexpression significantly promotes HCC cell migration, invasion and epithelial–mesenchymal transition (EMT) in vitro and promotes intrahepatic metastasis, lung metastasis and EMT in vivo. Opposing results are observed when HEG1 is silenced. Mechanistically, HEG1 promotes β-catenin expression and maintains its stability, leading to intracellular β-catenin accumulation, β-catenin nuclear translocation and Wnt signaling activation. Loss- and gain-of-function assays further confirmed that β-catenin is essential for HEG1-mediated promotion of HCC invasion, metastasis and EMT. In conclusion, HEG1 indicates poor prognosis; plays important roles in HCC invasion, metastasis and EMT by activating Wnt/β-catenin signaling; and can serve as a potentially valuable prognostic biomarker and therapeutic target for HCC.

Introduction

Hepatocellular carcinoma (HCC) is the sixth most commonly diagnosed cancer (4.7%) and the fourth leading cause of cancer-related deaths (8.2%) worldwide [1]. Although treatments have greatly improved in recent decades, the long-term survival of HCC patients remains poor due to recurrence and metastasis [2–4]. Metastasis has become the major obstacle to improving the poor prognosis of HCC [5,6]. Recent studies have shown that many oncogenes (such as LEF1, 5-HT1D, TonEBP and others) are involved in HCC invasion and metastasis [7–9], thus enriching our understanding of the mechanism of HCC progression and providing a basis for precise and individualized treatment of HCC patients, but this information is still not complete. Therefore, it is necessary to further study the exact mechanisms of HCC invasion and metastasis to help improve current treatment strategies.

Heart development protein with EGF-like domains 1 (HEG1) has been shown to play important roles in embryo development [10] and angiogenesis [11], which are closely related to cancer progression. Researchers also found that HEG1 is involved in mesothelioma cell survival and proliferation [12]. However, the functions and mechanisms of HEG1 in the invasion and metastasis of tumors (including HCC) remain unclear. Interestingly, the results of previous studies have indicated that HEG1 is critical for Rap1-dependent recruitment of Rasip1 [13], which acts as an oncogene to promote cancer cell migration and invasion [14], MUC13 plays an important role in HCC metastasis, and HEG1 has the same genomic location as MUC13 (3q21.2) and contains similar domains. Therefore, HEG1 may also play an important role in tumor invasion and metastasis.

In the present study, we explored the novel functions of HEG1 in HCC and found that HEG1 is highly expressed in HCC tissues and cell lines and is closely correlated with poor prognosis in HCC patients. HEG1 promotes HCC invasion, metastasis and epithelial–mesenchymal transition (EMT) by activating Wnt/β-catenin signaling. Thus, HEG1 can serve as a potentially valuable prognostic biomarker and therapeutic target for HCC.

Materials and methods

HCC samples and patients

The present study was approved by the Ethics Committee of Xiangya Hospital at Central South University. All patients and their families provided written informed consent and agreed to the use of their tissue samples in the study in accordance with the Declaration of Helsinki. A total of 137 HCC specimens collected from January 2009 to December 2012 were randomly selected from the Department of Surgery, Xiangya Hospital of Central South University. Another 105 HCC specimens collected from January 2010 to December 2012 were randomly selected from the Department of Abdominal Surgical Oncology, Affiliated Cancer Hospital of Xiangya School of Medicine, Central South University. The details of the sample collections are shown in Supplementary Figure S1A. The patient demographics and clinicopathological variables of the two cohorts are described in Supplementary Table S1. Furthermore, 30 matched fresh HCC tissues and adjacent nontumor liver tissues (ANLTs) were collected from Xiangya Hospital from January to December 2016. The diagnosis of HCC in all patients was confirmed by two independent histopathologists.

Follow-up and prognostic study

Follow-up procedures were conducted as described in our previous study [15]. The complete clinicopathological features of these patients were collected and stored in our database. Research protocols followed the Reporting Recommendations for Tumor Marker Prognostic Studies (REMARK) recommendations for reporting prognostic biomarkers in cancer [16].

Cell lines and cell culture

Eight HCC cell lines and the Immortalized normal liver cell line L02 were used in the present study. Details regarding the culture of these cells were described in our previous study [17].

RNA extraction and quantitative real-time PCR

Total RNA was extracted from fresh-frozen HCC patient tissues or cultured cells with TRIzol reagent (Invitrogen, Carlsbad, CA) according to the manufacturer’s protocol. Reverse transcription was performed using an Advantage RT-for-PCR Kit (Takara, Dalian, China). quantitative real-time polymerase chain reaction (qRT-PCR) analysis was performed using FastStart Universal SYBR Green Master (ROX) (Roche, Shanghai, China) in a 7300 Real-Time PCR system (Applied Biosystems Inc., Foster City, CA). The detailed procedure was conducted as previously described [18]. Relative mRNA expression levels were calculated by the 2−ΔΔCt method and were normalized to the expression of the internal control GAPDH [19]. The experiments were performed in triplicate. The primers were all synthesized by and purchased from Sangon Biotech (China); the primer sequences are listed in Supplementary Table S4.

Protein extraction and Western blot

Total proteins were extracted with RIPA lysis buffer (Pierce, Rockford, U.S.A.), and nuclear extraction was prepared using an NE-PER Nuclear Cytoplasmic Extraction Reagent kit (Pierce, Rockford, U.S.A.) according to the manufacturer’s instructions. Then, after the protein concentrations were measured, the samples were separated by SDS/PAGE and transferred to a PVDF membrane (Millipore, Belford, MA). The membranes were blocked with 5% skim milk and incubated with the appropriate antibody. The antigen–-antibody complex on the membrane was detected using an enhanced chemiluminescence (ECL) kit (Pierce, Rockford, U.S.A.). The antibodies used are listed in Supplementary Table S5.

Immunohistochemistry

Immunohistochemical staining on formalin-fixed, paraffin-embedded tissue sections 4 µm in thickness was performed using the polymer HRP detection system (Zhongshan Goldenbridge Biotechnology, Beijing, China). Immunohistochemical experiments were conducted as previously described [15,17]. The antibodies used are listed in Supplementary Table S5. The immunohistochemical staining intensity was scored as negative (−,0), weak (+,1), moderate (++,2), or strong (+++,3), and the percentage of positive cells was scored as <5% (0), 6–25% (1), 26–75% (2), or >75% (3). The final scores were calculated by multiplying the intensity and percentage values (range: 0–9). The HCC specimens were divided based on protein expression into a low expression group (<4) and a high expression group (≥4) for further analysis [20,21].

Immunofluorescence

For assessment of immunofluorescence (IF) in cells, cells were grown on glass coverslips and then fixed with 4% paraformaldehyde in phosphate-buffered saline (PBS) with 0.2% Triton X-100. Cells were then blocked for an hour with 1% bovine serum albumin (BSA), followed by incubation with primary antibody overnight at 4°C. Cells were washed and incubated with the appropriate secondary antibody and DAPI (Vector Laboratories, Burlingame, CA) [22]. Finally, the slides were mounted, and images were captured using an inverted fluorescence microscope DMI4000-B (Leica, Wetzlar, Germany). The antibodies used are listed in Supplementary Tables S5 and S6.

Establishment of overexpressing and knockdown HCC cells

The ectopic expression and knockdown lentiviruses for HEG1, as well as the corresponding control lentivirus, were purchased from Vigene Bioscience (China). The ectopic expression and knockdown lentiviruses for catenin β 1 (CTNNB1), as well as the corresponding control lentivirus, were purchased from GeneChem (China). The knockdown lentiviruses for APC, as well as the corresponding control lentivirus, were also purchased from GeneChem (China). Transfection was performed according to the manufacturer’s instructions. Puromycin (final concentration: 2 μg/ml) was used to select clones with stable plasmid expression. The sequences of the shRNA and cDNA clones are listed in Supplementary Table S7.

Wound healing and transwell invasion assays

Wound healing and transwell invasion assays were performed and analyzed for the present study as described in our previous work [15].

HCC mouse model

Xenograft experiments were conducted with 6-week-old male BALB/c nude mice (six mice per group). A total of 5 × 106 of the indicated HCC cells were injected subcutaneously into the right upper flank regions of BALB/c nude mice. After 4 weeks, the mice were killed. The tumors were excised, cut into pieces approximately 1 mm3 in size, and implanted into the livers of BALB/c nude mice in each group to mimic primary HCC [15]. Tumor formation and metastatic progression were monitored and quantitated using a Xenogen In Vivo Imaging System (IVIS) 100 (Caliper Life Sciences, Hopkinton, MA) [23]. At 8 weeks after implantation, the mice were killed, and the livers and lungs were harvested, imaged and processed for histopathological examination. All animal studies were conducted at the Animal Institute of CSU according to the protocols approved by the Medical Experimental Animal Care Commission of CSU.

Kyoto Encyclopedia of Genes and Genomes pathway enrichment analysis

The median of 371 cancer samples from the The Cancer Genome Atlas (TCGA) database was accepted as an optimal cut-off value to divide into the high and the low expression subgroups for Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis [24]. EdgeR was used to analyze the expression levels in the cancer samples and to screen for differentially expressed genes that met the following criteria: FDR < 0.01 and fold-change > 2. Pearson correlation analysis between HEG1 and the differentially expressed genes was performed using R language, and the genes with P<0.01 were selected as differentially related genes. KEGG pathway enrichment analysis of these differentially related genes was performed using DAVID.

Cignal finder cancer 10-pathway reporter arrays

A Cignal Finder Cancer 10-Pathway Reporter Array (Qiagen, Valencia, CA) was performed to explore the signaling pathways that were regulated by HEG1 in HCC cells. The assay was conducted according to the manufacturer’s protocol. Relative firefly luciferase activity was calculated and normalized to constitutive Renilla luciferase activity. Experiments were repeated three times, and the data are presented as the mean ± SD.

qRT-PCR

Gene expression profiles were analyzed using the Human Targets of Wnt/β-catenin Signaling Related Gene qPCR Array (Wcgene Biotech, Shanghai, China) according to the manufacturer’s protocol. Data were analyzed using Wcgene Biotech software (http://www.wcgene.com). Genes with fold-changes greater than 2.0 or less than -2.0 were considered to be of biological significance [25]. The genes are listed in Supplementary Table S8.

Coimmunoprecipitation assay and cycloheximide chase assay

Coimmunoprecipitation (Co-IP) was performed using a Thermo Scientific Pierce Co-IP kit (Rockford, U.S.A.) following the manufacturer’s protocol. Briefly, primary antibody was first immobilized for 2 h using AminoLink Plus coupling resin, which was then washed and incubated with whole cell lysates overnight. After incubation, the resin was again washed, and the protein was eluted using elution buffer. A negative control that was provided in the IP kit to assess nonspecific binding received the same treatment as the Co-IP samples, including the primary antibody. In this control, the coupling resin was not amine-reactive, thus preventing covalent immobilization of the primary antibody on to the resin. Then, samples were analyzed by Western blot. A cycloheximide (CHX) chase assay was used to determine the half-lives of HEG1 and β-catenin. HCC cells with aberrant HEG1 expression were treated with CHX (10 μg/ml) for the indicated times, and Western blot was performed.

Statistical analysis

Statistical analyses were performed using SPSS 19.0 software (SPSS Inc., Chicago, IL) and GraphPad Prism 7. Data are presented as the mean ± SD from three repeated experiments. Quantitative data between groups were compared using Student’s t test. The chi-square test was applied to examine the associations between HEG1 expression and clinicopathological parameters. Spearman’s rank analysis was performed to determine the correlations between the different protein levels. Overall survival (OS) and disease-free survival (DFS) curves were obtained by the Kaplan–Meier method, and differences were compared by the log-rank test. Univariate and multivariate analyses were performed with the Cox proportional hazard regression model to verify the independent risk factors. All differences were deemed statistically significant at P<0.05.

Results

HEG1 is highly expressed in human HCC cell lines and tissues

First, we detected the expression levels of HEG1 in the L02 and HCC cell lines. Compared with L02 cells, HCC cell lines had higher expression levels of HEG1 mRNA and protein (Figure 1A). Interestingly, HEG1 expression levels in the cell lines with stronger metastatic potential (Hep3B, HCCLM3) were significantly higher than those with weaker metastatic potential (PLC/PRF5, SMMC7721) [15,26–28]. Then, we detected the mRNA and protein expression levels of HEG1 in fresh HCC tissues. Compared with ANLTs, HCC tissues (T) had significantly up-regulated levels of HEG1 expression (P<0.001, Figure 1B). Furthermore, HEG1 expression was detected by immunohistochemistry (IHC) and was found to be higher in HCC tissues and metastases than in the matched ANLTs (P<0.001, Figure 1C). We also analyzed public datasets from the Gene Expression Omnibus (GEO) (GSE45436, GSE57957, GSE60502 and GSE76427) and the TCGA database. The results also confirmed that the expression of HEG1 in HCC tissues was significantly higher than that in normal liver tissues and ANLTs (Supplementary Figure S1B; all P<0.002). Both our experimental results and public data analysis indicated that HEG1 is significantly up-regulated and thus may play an important role in HCC progression.

HEG1 expression is significantly up-regulated in HCC cell lines and tissues and is closely correlated with poor prognosis

Figure 1
HEG1 expression is significantly up-regulated in HCC cell lines and tissues and is closely correlated with poor prognosis

(A) qRT-PCR and Western blot identified the mRNA and protein expression levels, respectively, of HEG1 in eight HCC cell lines and L02 cells. (B) HEG1 mRNA and protein expression levels were detected in 30 paired fresh HCC tissues and ANLTs by qRT-PCR and Western blot. (C) Representative IHC images of HEG1 expression in HCC tumor, metastases and ANLT samples. (D) The OS and DFS of HCC patients with high or low HEG1 expression in the training cohort. (E) The OS and DFS of HCC patients with high or low HEG1 expression in the validation cohort. The survival curve was calculated with the log-rank test. Abbreviations: bp, base pair; T, HCC tissue. **, P<0.01; ***, P<0.001.

Figure 1
HEG1 expression is significantly up-regulated in HCC cell lines and tissues and is closely correlated with poor prognosis

(A) qRT-PCR and Western blot identified the mRNA and protein expression levels, respectively, of HEG1 in eight HCC cell lines and L02 cells. (B) HEG1 mRNA and protein expression levels were detected in 30 paired fresh HCC tissues and ANLTs by qRT-PCR and Western blot. (C) Representative IHC images of HEG1 expression in HCC tumor, metastases and ANLT samples. (D) The OS and DFS of HCC patients with high or low HEG1 expression in the training cohort. (E) The OS and DFS of HCC patients with high or low HEG1 expression in the validation cohort. The survival curve was calculated with the log-rank test. Abbreviations: bp, base pair; T, HCC tissue. **, P<0.01; ***, P<0.001.

HEG1 expression closely correlates with aggressive clinicopathological features and indicates poor prognosis in HCC patients

To explore the clinical significance of high HEG1 expression in HCC, we estimated the association of HEG1 expression with clinicopathological features and survival of HCC patients using training and validation cohorts. Patients were divided into high and low HEG1 expression groups according to the IHC results (Supplementary Figure S1C and Table S1). In the training cohort, a high expression level of HEG1 was closely correlated with high α-fetoprotein (AFP) level, large tumor size, vascular invasion, high Edmondson–Steiner grade, advanced tumor node metastasis stage (TNM) and Barcelona Clinic Liver Cancer (BCLC) stage, and tumor subtypes (all P<0.05, Table 1). In the tumor subtypes, the high expression rate of HEG1 in nodular HCC (NHCC, tumor nodules ≥ 2) was higher than that in solitary large HCC (SLHCC, only one nodule, and tumor diameter > 5 cm) (87.8 vs 57.4%, Supplementary Figure S1C) [29,30]. HCC patients with high HEG1 expression had shorter OS (1-, 3-, 5-year OS: 68, 32, 15% vs 89, 64, 44%, P<0.001, Figure 1D) and DFS (1-, 3-, 5-year DFS: 61, 22, 9% vs 89, 51, 36%, P<0.001, Figure 1D), and the multivariate analysis revealed that high HEG1 expression was an independent risk factor for both OS and DFS of HCC patients (all P<0.05, Table 2). Next, the correlation between high HEG1 expression and aggressive clinicopathological features and poor survival of HCC patients was further verified in the validation cohort (Figure 1E, Table 1 and Supplementary Table S2). Then, survival analysis for the overall cohort also demonstrated that high HEG1 expression patients had shorter OS and DFS (P<0.001, Supplementary Figure S1D). These results fully demonstrated that HEG1 closely correlated with poor survival and could be used as a novel and valuable independent prognostic biomarker for HCC.

Table 1
Correlations between HEG1 expression and clinicopathological characteristics of HCC in the training and validation cohorts
Clinicopathological variables Training cohort Validation cohort 
 Number HEG1 expression P-value Number HEG1 expression P-value 
  Low High   Low High  
Gender         
  Female 31 25 0.236 32 10 22 0.687 
  Male 106 32 74  73 20 53  
Age (years)         
  ≤60 92 26 66 0.845 67 19 48 0.949 
  >60 45 12 33  38 11 27  
AFP (ng/ml)         
  <20 62 25 37 0.003 37 18 19 0.001 
  ≥20 75 13 62  68 12 56  
HBsAg         
  Negative 42 14 28 0.331 31 22 0.946 
  Positive 95 24 71  74 21 53  
Liver cirrhosis         
  Absence 60 20 40 0.197 50 17 33 0.240 
  Presence 77 18 59  55 13 42  
Tumor size (cm)         
  ≤5 59 53 <0.001 47 41 0.001 
  >5 78 32 46  58 24 34  
Tumor nodule number         
  Solitary 86 28 58 0.102 62 17 45 0.754 
  Multiple (≥2) 51 10 41  43 13 30  
Capsular formation         
  Absence 72 17 55 0.256 65 18 47 0.799 
  Presence 65 21 44  40 12 28  
Macrovascular invasion (MAVI)         
  Absence 92 31 61 0.026 67 26 41 0.002 
  Presence 45 38  38 34  
Microvascular invasion (MVI)         
  Absence 79 30 49 0.002 59 23 36 0.007 
  Presence 58 50  46 39  
Edmondson–Steiner grade         
  I/II 72 35 37 <0.001 61 25 36 0.001 
  III/IV 65 62  44 39  
Child–Pugh         
  A 102 27 75 0.572 73 19 54 0.383 
  B 35 11 24  32 11 21  
TNM stage         
  I/II 78 29 49 0.005 59 21 25 0.001 
  III/IV 59 50  46 50  
BCLC stage         
  0/A 48 41 0.012 33 30 0.003 
  B/C 89 31 58  72 27 45  
Tumor subtypes         
  SHCC 41 12 29 0.036 34 13 21 0.022 
  SLHCC 47 20 27  32 15 17  
  NHCC 49 43  39 37  
Clinicopathological variables Training cohort Validation cohort 
 Number HEG1 expression P-value Number HEG1 expression P-value 
  Low High   Low High  
Gender         
  Female 31 25 0.236 32 10 22 0.687 
  Male 106 32 74  73 20 53  
Age (years)         
  ≤60 92 26 66 0.845 67 19 48 0.949 
  >60 45 12 33  38 11 27  
AFP (ng/ml)         
  <20 62 25 37 0.003 37 18 19 0.001 
  ≥20 75 13 62  68 12 56  
HBsAg         
  Negative 42 14 28 0.331 31 22 0.946 
  Positive 95 24 71  74 21 53  
Liver cirrhosis         
  Absence 60 20 40 0.197 50 17 33 0.240 
  Presence 77 18 59  55 13 42  
Tumor size (cm)         
  ≤5 59 53 <0.001 47 41 0.001 
  >5 78 32 46  58 24 34  
Tumor nodule number         
  Solitary 86 28 58 0.102 62 17 45 0.754 
  Multiple (≥2) 51 10 41  43 13 30  
Capsular formation         
  Absence 72 17 55 0.256 65 18 47 0.799 
  Presence 65 21 44  40 12 28  
Macrovascular invasion (MAVI)         
  Absence 92 31 61 0.026 67 26 41 0.002 
  Presence 45 38  38 34  
Microvascular invasion (MVI)         
  Absence 79 30 49 0.002 59 23 36 0.007 
  Presence 58 50  46 39  
Edmondson–Steiner grade         
  I/II 72 35 37 <0.001 61 25 36 0.001 
  III/IV 65 62  44 39  
Child–Pugh         
  A 102 27 75 0.572 73 19 54 0.383 
  B 35 11 24  32 11 21  
TNM stage         
  I/II 78 29 49 0.005 59 21 25 0.001 
  III/IV 59 50  46 50  
BCLC stage         
  0/A 48 41 0.012 33 30 0.003 
  B/C 89 31 58  72 27 45  
Tumor subtypes         
  SHCC 41 12 29 0.036 34 13 21 0.022 
  SLHCC 47 20 27  32 15 17  
  NHCC 49 43  39 37  

No patients with Child-Pugh C were included. Significant results (P<0.05) are shown in bold. HEG1 low expression: IHC score < 4; HEG1 high expression: IHC score 4–9. Abbreviations: HBsAg, hepatitis B surface antigen; SHCC, small HCC. Annotation: Macrovascular invasion (MAVI), invasion of the first- and second-order branches of the portal veins or hepatic arteries, or invasion of one or more of the three hepatic veins (right, middle, or left). Microvascular invasion (MVI), microscopic invasion of smaller intraparenchymal vascular structures identified by histopathologic examination (AJCC Cancer Staging Manual, 8th edition).

Table 2
Univariable and multivariable analyses of risk factors associated with OS and DFS of HCC patients in the training cohort
Clinicopathologic variables OS DFS 
 Univariable analysis Multivariable analysis Univariable analysis Multivariable analysis 
 HR (95% CI) P-value HR (95% CI) P-value HR (95% CI) P-value HR (95% CI) P-value 
Gender         
  Female       
  Male 0.819 (0.493–1.362) 0.442  NA 0.881 (0.552–1.406) 0.596  NA 
Age (years)         
  ≤60       
  >60 1.107 (0.715–1.712) 0.649  NA 1.062 (0.699–1.613) 0.778  NA 
AFP (ng/ml)         
  <20       
  ≥20 1.827 (1.194–2.796) 0.006  NS 1.882 (1.258–2.816) 0.002  NS 
HBsAg         
  Negative       
  Positive 1.061 (0.683–1.651) 0.791  NA 1.340 (0.864–2.080) 0.191  NA 
Liver cirrhosis         
  Absence     
  Presence 1.864 (1.203–2.889) 0.005 2.101 (1.273–3.470) 0.004 1.930 (1.278–2.915) 0.002 2.063 (1.283–3.319) 0.003 
Tumor size(cm)         
  ≤5 cm      
  >5 cm 1.624 (1.056–2.499) 0.027 1.755 (1.071–2.875) 0.026 1.633 (1.085–2.458) 0.019  NS 
Tumor nodule number         
  Solitary     
  Multiple (≥2) 2.351 (1.531–3.611) <0.001 2.752 (1.421–5.327) 0.003 2.135 (1.420–3.210) <0.001 2.094 (1.224–3.582) 0.007 
Capsular formation         
  Absence       
  Presence 1.362 (0.893–2.078) 0.151  NA 1.121 (0.755–1.664) 0.572  NA 
Macrovascular invasion         
  Absence      
  Presence 1.972 (1.279–3.039) 0.002 1.894 (1.160–3.091) 0.011 1.745 (1.152–2.644) 0.009  NS 
Microvascular invasion         
  Absence     
  Presence 1.892 (1.247–2.870) 0.003 2.046 (1.248–3.354) 0.005 2.832 (1.764–4.428) 0.002 1.838 (1.166–2.898) 0.009 
Edmondson–Steiner grade         
  I/II       
  III/IV 1.602 (1.052–2.439) 0.028  NS 1.641 (1.101–2.446) 0.015  NS 
Child–Pugh         
  A       
  B 1.358 (0.864–2.136) 0.185  NA 1.161 (0.741–1.819) 0.514  NA 
TNM stage         
  I/II     
  III/IV 2.706 (1.756–4.168) <0.001 1.744 (1.057–2.878) 0.030 3.010 (1.987–4.560) <0.001 2.095 (1.295–3.390) 0.003 
BCLC stage         
  0/A       
  B/C 1.783 (1.168–2.723) 0.007  NS 1.456 (0.965–2.196) 0.073  NA 
HEG1 expression         
  Low     
  High 2.606 (1.543–4.400) <0.001 1.965 (1.063–3.632) 0.031 2.600 (1.595–4.238) <0.001 2.064 (1.158–3.681) 0.014 
Clinicopathologic variables OS DFS 
 Univariable analysis Multivariable analysis Univariable analysis Multivariable analysis 
 HR (95% CI) P-value HR (95% CI) P-value HR (95% CI) P-value HR (95% CI) P-value 
Gender         
  Female       
  Male 0.819 (0.493–1.362) 0.442  NA 0.881 (0.552–1.406) 0.596  NA 
Age (years)         
  ≤60       
  >60 1.107 (0.715–1.712) 0.649  NA 1.062 (0.699–1.613) 0.778  NA 
AFP (ng/ml)         
  <20       
  ≥20 1.827 (1.194–2.796) 0.006  NS 1.882 (1.258–2.816) 0.002  NS 
HBsAg         
  Negative       
  Positive 1.061 (0.683–1.651) 0.791  NA 1.340 (0.864–2.080) 0.191  NA 
Liver cirrhosis         
  Absence     
  Presence 1.864 (1.203–2.889) 0.005 2.101 (1.273–3.470) 0.004 1.930 (1.278–2.915) 0.002 2.063 (1.283–3.319) 0.003 
Tumor size(cm)         
  ≤5 cm      
  >5 cm 1.624 (1.056–2.499) 0.027 1.755 (1.071–2.875) 0.026 1.633 (1.085–2.458) 0.019  NS 
Tumor nodule number         
  Solitary     
  Multiple (≥2) 2.351 (1.531–3.611) <0.001 2.752 (1.421–5.327) 0.003 2.135 (1.420–3.210) <0.001 2.094 (1.224–3.582) 0.007 
Capsular formation         
  Absence       
  Presence 1.362 (0.893–2.078) 0.151  NA 1.121 (0.755–1.664) 0.572  NA 
Macrovascular invasion         
  Absence      
  Presence 1.972 (1.279–3.039) 0.002 1.894 (1.160–3.091) 0.011 1.745 (1.152–2.644) 0.009  NS 
Microvascular invasion         
  Absence     
  Presence 1.892 (1.247–2.870) 0.003 2.046 (1.248–3.354) 0.005 2.832 (1.764–4.428) 0.002 1.838 (1.166–2.898) 0.009 
Edmondson–Steiner grade         
  I/II       
  III/IV 1.602 (1.052–2.439) 0.028  NS 1.641 (1.101–2.446) 0.015  NS 
Child–Pugh         
  A       
  B 1.358 (0.864–2.136) 0.185  NA 1.161 (0.741–1.819) 0.514  NA 
TNM stage         
  I/II     
  III/IV 2.706 (1.756–4.168) <0.001 1.744 (1.057–2.878) 0.030 3.010 (1.987–4.560) <0.001 2.095 (1.295–3.390) 0.003 
BCLC stage         
  0/A       
  B/C 1.783 (1.168–2.723) 0.007  NS 1.456 (0.965–2.196) 0.073  NA 
HEG1 expression         
  Low     
  High 2.606 (1.543–4.400) <0.001 1.965 (1.063–3.632) 0.031 2.600 (1.595–4.238) <0.001 2.064 (1.158–3.681) 0.014 

Significant results (P<0.05) are shown in bold. Abbreviations: CI, confidence interval; HR, hazard risk ratio; NA, not applicable; NS, not significant.

HEG1 promotes HCC invasion and metastasis in vitro and in vivo

To understand the function of HEG1 in HCC invasion and metastasis, we restored HEG1 expression by ectopically expressing HEG1 in the HCC cell line with the lowest HEG1 expression, PLC/PRF5 (named: PLC/PRF5–HEG1), and silenced HEG1 in the cell line with the highest HEG1 expression, Hep3B (named: Hep3B-shHEG1) (Supplementary Figure S2A(a,b,c)). First, wound healing and transwell assays were used to investigate the migratory and invasive capacities of these cells. The results showed that Hep3B-shHEG1 cells exhibited a slower wound closure rate and fewer invasive cells than Hep3B-shcontrol cells, while PLC/PRF5–HEG1 cells had significantly enhanced migratory and invasive capacities (all P<0.01, Figure 2A,B). Then, we established an orthotopic xenograft tumor model to investigate the role of HEG1 in vivo (Supplementary Figure S2B). Tumor formation and metastatic progress were monitored and quantitated using the IVIS. The results showed that PLC/PRF5–HEG1 cell-derived tumors had a higher metastatic rate than control cell-derived tumors (intrahepatic: 50 vs 0%; lung: 33 vs 0%), whereas the metastasis rate in Hep3B–shHEG1 cell-derived tumors was lower than that in Hep3B-shcontrol cell-derived tumors (intrahepatic: 17 vs 67%; lung: 17 vs 50%) (Figure 2C,D). Similarly, Hematoxylin and Eosin (H&E) staining showed that intrahepatic and lung metastatic nodules were detected in the HEG1 high expression groups (Figure 2E,F). Taken together, our data demonstrated that HEG1 could promote HCC invasion and metastasis in vitro and in vivo.

HEG1 promotes HCC invasion and metastasis in vitro and in vivo

Figure 2
HEG1 promotes HCC invasion and metastasis in vitro and in vivo

Wound healing assay (A) and transwell invasion assay (B) were used to detect the migratory and invasive capacities of cells with modified HEG1 expression. (C) Tumor formation and metastatic progression were monitored and quantitated using IVIS. Representative bioluminescent images of the orthotopic tumors (PLC/PRF5-HEG1, PLC/PRF5-control, Hep3B-shHEG1 and Hep3B-shcontrol groups; n=6 for each group, left panel) are shown. The colored region represents the fluorescence signal of HCC cells in nude mice, and the proportions of intrahepatic metastasis were calculated and compared. The right panel shows representative macroscopic intrahepatic metastatic nodules in orthotopic tumors. (D) Bioluminescent images of lung metastasis. The proportions of metastasis in the lungs were calculated and compared (n=6 for each group). (E) Representative H&E-stained sections of orthotopic primary liver tumors and their microsatellites. (F) Representative H&E staining of pulmonary metastatic nodules in the experimental and control groups. **, P<0.01.

Figure 2
HEG1 promotes HCC invasion and metastasis in vitro and in vivo

Wound healing assay (A) and transwell invasion assay (B) were used to detect the migratory and invasive capacities of cells with modified HEG1 expression. (C) Tumor formation and metastatic progression were monitored and quantitated using IVIS. Representative bioluminescent images of the orthotopic tumors (PLC/PRF5-HEG1, PLC/PRF5-control, Hep3B-shHEG1 and Hep3B-shcontrol groups; n=6 for each group, left panel) are shown. The colored region represents the fluorescence signal of HCC cells in nude mice, and the proportions of intrahepatic metastasis were calculated and compared. The right panel shows representative macroscopic intrahepatic metastatic nodules in orthotopic tumors. (D) Bioluminescent images of lung metastasis. The proportions of metastasis in the lungs were calculated and compared (n=6 for each group). (E) Representative H&E-stained sections of orthotopic primary liver tumors and their microsatellites. (F) Representative H&E staining of pulmonary metastatic nodules in the experimental and control groups. **, P<0.01.

HEG1 induces EMT

In the present study, we observed an interesting phenomenon in which PLC/PRF5-HEG1 and Hep3B-shcontrol cells exhibited spindle-like mesenchymal morphology and elongated F-actin fibers, while PLC/RPF5-control and Hep3B-shHEG1 cells exhibited cobblestone-like epithelial morphology and contracted F-actin fibers (Figure 3A,B). Considering the morphologic change in these cells and the function of HEG1, we speculated that HEG1 could induce EMT. To confirm our hypothesis, we first analyzed the relationship between HEG1 expression and hallmarks of EMT in HCC patients from the TCGA database with gene set enrichment analysis (GSEA). We found that high expression of HEG1 was significantly positively correlated with the hallmarks of EMT (NES = 2.01, FDR q<0.001, Figure 3C). Then, the expression relationship between HEG1 and EMT markers was analyzed in cytological and histological experiments. IF analysis showed that in PLC/PRF5-HEG1 cells, high expression of HEG1 reduced the expression of the epithelial marker E-cadherin and increased the expression of the mesenchymal marker vimentin, while HEG1 knockdown induced inverse results in Hep3B cells (Figure 3D). At the protein level, ectopic expression of HEG1 decreased the expression of E-cadherin and increased the expression of N-cadherin, vimentin and EMT-related transcriptional factors (snail, ZEB1) in PLC/PRF5-HEG1 cells, whereas HEG1 knockdown in Hep3B cells resulted in opposing results (Figure 3E). IHC staining also showed that ZEB1, snail and vimentin expression levels were up-regulated in high HEG1-expressing cell-derived tumors, whereas E-cadherin expression was reduced (Supplementary Figure S2C). Moreover, IHC of consecutive HCC sections revealed that HEG1 expression was negatively correlated with E-cadherin expression (training: P=0.006, r = −0.234; validation: P=0.001, r = −0.332) and positively correlated with vimentin expression (training: P<0.001, r = 0.317; validation: P=0.001, r = 0.308) (Figure 3F). These results indicated that HEG1 plays an important role in inducing EMT in HCC.

HEG1 promotes EMT in HCC

Figure 3
HEG1 promotes EMT in HCC

(A) Representative phase-contrast images of PLC/PRF5-HEG1, Hep3B-shHEG1, and their corresponding control cells. (B) Representative images of the cytoskeleton showed that HEG1 affected the cellular morphology. (C) GSEA of HEG1 expression in HCC patients from the TCGA database. GSEA plots indicated that the EMT signature is significantly positively associated with HEG1 expression (NES = 2.01, FDR q<0.001). (D) IF showed that HEG1 affected the expression of EMT markers. (E) HEG1-mediated expression levels of EMT markers and related transcriptional factors were detected by western blot. (F) Representative IHC images of HEG1, E-cadherin and vimentin expression in consecutive sections of HCC, and their expression correlations were analyzed by Spearman rank correlation tests in the training and validation cohorts.

Figure 3
HEG1 promotes EMT in HCC

(A) Representative phase-contrast images of PLC/PRF5-HEG1, Hep3B-shHEG1, and their corresponding control cells. (B) Representative images of the cytoskeleton showed that HEG1 affected the cellular morphology. (C) GSEA of HEG1 expression in HCC patients from the TCGA database. GSEA plots indicated that the EMT signature is significantly positively associated with HEG1 expression (NES = 2.01, FDR q<0.001). (D) IF showed that HEG1 affected the expression of EMT markers. (E) HEG1-mediated expression levels of EMT markers and related transcriptional factors were detected by western blot. (F) Representative IHC images of HEG1, E-cadherin and vimentin expression in consecutive sections of HCC, and their expression correlations were analyzed by Spearman rank correlation tests in the training and validation cohorts.

HEG1 activates Wnt signaling and its downstream effectors

To systemically screen the potential signaling pathways manipulated by HEG1 in HCC, we first analyzed the information of HCC patients from the TCGA database using KEGG pathway enrichment analysis. Wnt signaling was found to be the most significantly enriched pathway (Figure 4A; Supplementary Table S3; P<0.001). Then, a Cignal Finder Cancer 10-Pathway Reporter Array was performed in HCC cells with manipulated HEG1 expression to further screen and confirm the signaling pathway regulated by HEG1. The results showed that Wnt signaling was the most significantly altered pathway (Figure 4B). We further investigated the effect of HEG1 on the expression of key members of the Wnt signaling pathway [31] and observed that in HEG1-overexpressing cells, the protein levels of β-catenin, active-β-catenin, and glutamine synthetase (GS) were up-regulated, APC was down-regulated, and Axin and GSK-3β were almost unchanged (Figure 4C). Meanwhile, several genes related to cancer cell invasion, metastasis and EMT (which are controlled by Wnt signaling) [32–36] were analyzed. The data showed that snail, ZEB1, MMP7, and MMP2 were up-regulated in HEG1-overexpressing cells, whereas HEG1 knockdown cells showed opposing results (Figure 4C). Taken together, the public database analysis and our experimental results indicated that HEG1 could activate Wnt signaling and its downstream effectors in HCC.

HEG1 primarily activates Wnt signaling in HCC

Figure 4
HEG1 primarily activates Wnt signaling in HCC

(A) KEGG pathway enrichment analysis of 371 HCC patients from the TCGA database. KEGG pathway analysis was performed using DAVID. The differentially related genes (P<0.01) of HEG1 were enriched in 51 pathways. Among them, 26 pathways were significantly enriched (red, P<0.01). (B) A Cignal Finder Cancer 10-Pathway Reporter Array showing the signaling change in cells with HEG1 expression interference. (C) Key members of the Wnt signaling pathway and its downstream effectors were detected by Western blot.

Figure 4
HEG1 primarily activates Wnt signaling in HCC

(A) KEGG pathway enrichment analysis of 371 HCC patients from the TCGA database. KEGG pathway analysis was performed using DAVID. The differentially related genes (P<0.01) of HEG1 were enriched in 51 pathways. Among them, 26 pathways were significantly enriched (red, P<0.01). (B) A Cignal Finder Cancer 10-Pathway Reporter Array showing the signaling change in cells with HEG1 expression interference. (C) Key members of the Wnt signaling pathway and its downstream effectors were detected by Western blot.

HEG1 activates Wnt signaling via β-catenin and APC

To reveal how HEG1 activates Wnt signaling in HCC, we used the Human Targets of Wnt/β-catenin Signaling Related Gene qPCR Array for detection and analysis. Ectopic expression of HEG1 was found to increase CTNNB1 (β-catenin protein coding gene) expression and decrease APC expression in PLC/PRF5-HEG1 cells, while knockdown of HEG1 in Hep3B cells increased APC expression and decreased CTNNB1 expression (log2 fold change>1) (Figure 5A,B). Next, the detection of mRNA levels of the β-catenin transcriptional targets (GLUL, LGR5, AXIN-2, SP-5) confirmed that β-catenin was activated at the nuclear level (Supplementary Figure S2D). Then, we analyzed the correlations between HEG1 and both β-catenin and APC in HCC tissues. Similar to the array results above, HEG1 was negatively correlated with APC (training: P<0.001, r = −0.428; validation: P<0.001, r = −0.450) and positively correlated with β-catenin (training: P<0.001, r = 0.575; validation: P<0.001, r = 0.688) (Figure 5C). In addition, we reviewed the literature and found that HEG1 may interact with β-catenin [11,37]; therefore, a Co-IP assay was performed. The results showed that HEG1 could interact with β-catenin but not with APC in HCC cells (Figure 5D). It is well known that β-catenin stability is crucial for its entry into the nucleus and for its biological activity [31]. Therefore, we further studied the effect of HEG1 on the stability of β-catenin. The CHX chase assay showed that overexpression of HEG1 significantly prolonged the half-life of β-catenin, while silencing HEG1 dramatically reduced its half-life; similarly, the half-life of HEG1 was prolonged in PLC/PRF/5-HEG1 cells compared with the control group but was shortened in Hep3B-shHEG1 cells (Figure 5E). Moreover, the proteasome inhibitor MG132 rescued the reduction in β-catenin levels induced by HEG1 silencing (Supplementary Figure S2E). Consistent with the above results, Western blot showed that high HEG1 expression increased total β-catenin and cytoplastic β-catenin, decreased P-β-catenin and increased nuclear β-catenin (Figure 5F), eventually resulting in activation of Wnt signaling and its downstream effectors.

HEG1 activates Wnt signaling via β-catenin and APC

Figure 5
HEG1 activates Wnt signaling via β-catenin and APC

(A) The gene expression of HCC cells with HEG1 expression interference was detected by the Human Targets of Wnt/β-catenin Signaling Related Gene qPCR Array. HEG1 expression positively regulates the expression of CTNNB1 (red box) and negatively regulates the expression of APC (blue box) (log2 fold change > 1). (B) The protein expression levels of HEG1, APC and β-catenin were detected by Western blot. (C) Representative IHC images of HEG1, APC and β-catenin expression in consecutive sections of HCC, and their expression correlations were analyzed by Spearman rank correlation tests in the training and validation cohorts. (D) A Co-IP assay was performed to analyze the direct binding between HEG1, APC and β-catenin in HCC cells. (E) The protein half-lives of HEG1 and β-catenin in cells with HEG1 expression interference were determined by the CHX chase assay. (F) The protein expression levels of total β-catenin, cytoplasmic β-catenin, nuclear β-catenin and P-β-catenin were detected by Western blot.

Figure 5
HEG1 activates Wnt signaling via β-catenin and APC

(A) The gene expression of HCC cells with HEG1 expression interference was detected by the Human Targets of Wnt/β-catenin Signaling Related Gene qPCR Array. HEG1 expression positively regulates the expression of CTNNB1 (red box) and negatively regulates the expression of APC (blue box) (log2 fold change > 1). (B) The protein expression levels of HEG1, APC and β-catenin were detected by Western blot. (C) Representative IHC images of HEG1, APC and β-catenin expression in consecutive sections of HCC, and their expression correlations were analyzed by Spearman rank correlation tests in the training and validation cohorts. (D) A Co-IP assay was performed to analyze the direct binding between HEG1, APC and β-catenin in HCC cells. (E) The protein half-lives of HEG1 and β-catenin in cells with HEG1 expression interference were determined by the CHX chase assay. (F) The protein expression levels of total β-catenin, cytoplasmic β-catenin, nuclear β-catenin and P-β-catenin were detected by Western blot.

β-Catenin is indispensable for HEG1-mediated activation of Wnt signaling and promotion of HCC invasion, metastasis and EMT

To test whether β-catenin is indispensable for HEG1-mediated activation of Wnt signaling and promotion of HCC invasion, metastasis and EMT, we transfected CTNNB1-shRNAs into PLC/PRF5–HEG1 cells and the CTNNB1 ectopic expression plasmid into Hep3B-shHEG1 cells (Supplementary Figure S2F). We found that the promoting effects of HEG1 on the expression levels of snail, ZEB1, MMP7, MMP2 and MMP9 were significantly inhibited by CTNNB1 knockdown in PLC/PRF5–HEG1 cells, while overexpression of CTNNB1 reversed the down-regulation of the abovementioned proteins caused by HEG1 silencing in Hep3B-shHEG1 cells (Figure 6A,B). However, altering CTNNB1 expression had little effect on HEG1 mRNA and protein expression, further confirming that β-catenin is a downstream molecule of HEG1 (Figure 6A,B). These data indicated that β-catenin is necessary for the activation of Wnt signaling by HEG1. Then, loss- and gain-of-function assays were performed to verify whether β-catenin is indispensable for HEG1 promoting HCC invasion, metastasis and EMT in vitro and in vivo. Wound healing and transwell assay results revealed that knockdown of CTNNB1 in PLC/PRF5–HEG1 cells eliminated the promoting effect of HEG1 on migration and invasion, whereas overexpression of CTNNB1 in Hep3B-shHEG1 cells restored their migratory and invasive capacities (P<0.01, Figure 6C). Similarly, PLC/PRF5-HEG1 cells with knockdown of CTNNB1 presented a cobblestone-like morphology with shrinkable F-actin fibers, decreased vimentin expression and increased E-cadherin expression, whereas ectopic expression of CTNNB1 in Hep3B-shHEG1 cells resulted in the inverse effect (Figure 6D). In vivo, knockdown of CTNNB1 inhibited the metastasis of PLC/PRF5–HEG1 cell-derived tumors (intrahepatic: 33 vs 0%; lung: 17 vs 0%), whereas ectopic expression of CTNNB1 in Hep3B-shHEG1 cells resulted in the inverse effect (Figure 6E and Supplementary Figure S2G). H&E staining showed that intrahepatic and lung metastatic nodules were detected in PLC/PRF5–HEG1 and Hep3B–shHEG1+CTNNB1 groups, but not detected in their control groups (Figure 6F). IHC staining also confirmed that knockdown of CTNNB1 inhibited the EMT of PLC/PRF5–HEG1 cell-derived tumors, whereas ectopic expression of CTNNB1 resulted in the inverse effect (Supplementary Figure 2H). In addition, to verify whether the impact of HEG1 on β-catenin depends on the impact of HEG1 on APC, we transfected shAPCs into PLC/PRF5 cells and Hep3B-shHEG1 cells (Supplementary Figure S3A). The results showed that in shAPC-expressing cells, the protein levels of β-catenin and Act-β-catenin were up-regulated, while the changes in CTNNB1 mRNA expression were not significant (Supplementary Figure S3B). Then, functional assays were performed to verify the effects of APC knockdown on HCC invasion, metastasis and EMT. The results of wound healing and transwell assays indicated that APC knockdown in PLC/PRF5 cells and Hep3B-shHEG1 cells enhanced the migratory and invasive capacities of HCC cells (P<0.01, Supplementary Figure S3C). Similarly, APC knockdown increased vimentin expression and decreased E-cadherin expression (Supplementary Figure S3D). These data further indicated that the impact of HEG1 on the protein expression level and biological functions of β-catenin depend in part on the impact of HEG1 on APC. Altogether, these results demonstrate that β-catenin, as a downstream molecule of HEG1, is indispensable for HEG1-mediated Wnt signaling and promotes HCC invasion, metastasis and EMT.

β-catenin is indispensable for HEG1-mediated promotion of HCC proliferation, metastasis and EMT

Figure 6
β-catenin is indispensable for HEG1-mediated promotion of HCC proliferation, metastasis and EMT

(A) mRNA expression levels of HEG1 and CTNNB1 in HCC cells with HEG1 expression interference and knockdown or ectopic expression of CTNNB1. (B) The expression levels of key proteins in HCC cells with HEG1 expression interference and knockdown or ectopic expression of CTNNB1. (C) Wound healing and transwell invasion assays of HCC cells with HEG1 expression interference and knockdown or ectopic expression of CTNNB1. (D) Cytoskeleton and EMT marker expression assays of HCC cells with HEG1 expression interference and knockdown or ectopic expression of CTNNB1. (E) Representative bioluminescent images of the orthotopic xenograft tumors (PLC/PRF5–HEG1+shCTNNB1, Hep3B–shHEG1+CTNNB1, and their control groups; n=6 for each group, left panel) are shown, and the proportions of intrahepatic and lung metastasis were calculated and compared. (F) Representative H&E-stained sections of intrahepatic and lung metastasis of orthotopic xenograft tumors. (G) A working model of HEG1-mediated activation of Wnt signaling via β-catenin and APC and promotion of HCC invasion, metastasis and EMT. **, P<0.01; ***, P<0.001.

Figure 6
β-catenin is indispensable for HEG1-mediated promotion of HCC proliferation, metastasis and EMT

(A) mRNA expression levels of HEG1 and CTNNB1 in HCC cells with HEG1 expression interference and knockdown or ectopic expression of CTNNB1. (B) The expression levels of key proteins in HCC cells with HEG1 expression interference and knockdown or ectopic expression of CTNNB1. (C) Wound healing and transwell invasion assays of HCC cells with HEG1 expression interference and knockdown or ectopic expression of CTNNB1. (D) Cytoskeleton and EMT marker expression assays of HCC cells with HEG1 expression interference and knockdown or ectopic expression of CTNNB1. (E) Representative bioluminescent images of the orthotopic xenograft tumors (PLC/PRF5–HEG1+shCTNNB1, Hep3B–shHEG1+CTNNB1, and their control groups; n=6 for each group, left panel) are shown, and the proportions of intrahepatic and lung metastasis were calculated and compared. (F) Representative H&E-stained sections of intrahepatic and lung metastasis of orthotopic xenograft tumors. (G) A working model of HEG1-mediated activation of Wnt signaling via β-catenin and APC and promotion of HCC invasion, metastasis and EMT. **, P<0.01; ***, P<0.001.

Discussion

The high recurrence and metastasis rates after liver resection are the main cause of death in HCC patients [4]. In the present study, we provided the first evidence that HEG1 is highly expressed in HCC and is significantly correlated with aggressive clinicopathological features and poor prognosis of HCC patients. Moreover, we demonstrated that HEG1 plays important roles in HCC invasion, metastasis and EMT by activating Wnt signaling via β-catenin and APC in vitro and in vivo. Thus, HEG1 is a novel oncogene in HCC and could serve as a potentially valuable prognostic biomarker and therapeutic target for HCC.

HEG1 plays critical roles in embryo development [10], angiogenesis [11] and cell–cell junctions [13], suggesting its potential role in promoting tumor progression. As expected, HEG1 was highly expressed in HCC patients and correlated with aggressive clinicopathological features. Moreover, the percentage of NHCC cases with high expression of HEG1 is higher than that of SLHCC cases, indicating that HEG1 can be used to distinguish the clinical subtypes of HCCs. Interestingly, our previous studies confirmed that the metastatic potential of SLHCC was significantly lower than that of NHCC [29,38]. These results indicated that HEG1 may promote HCC metastasis. Previous studies have mentioned the potential role of HEG1 in tumor metastasis [13,14,32]. However, to date, the role of HEG1 in the metastasis of tumors (including HCC) has not been verified. Thus, we studied the role of HEG1 in HCC through functional experiments in vitro and in vivo. The results of functional assays revealed that HEG1 overexpression could significantly enhance the invasive and metastatic capacities of HCC, whereas HEG1 knockdown in HCC exerted opposing effects. During the study, we also observed that HEG1 ectopic expression changed the cell morphology from an epithelial to a mesenchymal phenotype, while HEG1 knockdown showed opposing results. This biological function is similar to EMT, which is the initial stage and a necessary step of the metastatic cascade of many cancers [36,39,40]. We further validated this observation by public database analysis and EMT marker detection. Therefore, our data are the first to illustrate that HEG1 could induce EMT in HCC. Our study also revealed the novel roles of HEG1 in promoting HCC progression and enriched the understanding of the biological function of HEG1.

In the present study, we further demonstrated that HEG1 facilitated HCC invasion, metastasis and EMT through Wnt signaling activation. Wnt signaling is critical for embryo development, angiogenesis and stem cell differentiation [41]; recent studies have also confirmed that Wnt signaling plays an important role in HCC progression [33,42]. However, how HEG1 activates Wnt signaling in HCC was unclear. In this study, we found by qPCR array that HEG1 could regulate the expression of APC and β-catenin in HCC. Further, we found that HEG1 may inhibit the formation of β-catenin degradation complexes by down-regulating APC expression. β-Catenin is a core component of the Wnt signaling pathway and is highly expressed in a variety of malignancies [31,34,43], including HCC [32]. It is well known that stable β-catenin levels play a key role in the Wnt signal output [44]. Previous studies have demonstrated that HEG1 can recruit and bind Krit1 to regulate cell–cell junctions [11], while Krit1 can bind β-catenin and regulate its localization [37], suggesting that HEG1 can also interact with β-catenin. In the present study, we showed that HEG1 could interact with β-catenin and maintain its stability, which not only supports the above viewpoint but also provides novel information regarding this pathway. Under these conditions, overexpression of HEG1 increased intracellular β-catenin accumulation and increased the localization of β-catenin to the nucleus. More importantly, our study also confirmed that nuclear β-catenin accumulation in HCC increased β-catenin-dependent gene expression and promoted HCC invasion, metastasis and EMT [32,35,45]. Based on these results, we demonstrated that HEG1 increased total β-catenin, decreased P-β-catenin and increased β-catenin in the nucleus, eventually activating Wnt signaling and its downstream effectors (Figure 6G). Our research enriches the understanding of HEG1 and Wnt signaling. However, more precise mechanisms need to be further explored.

In conclusion, our study first demonstrated that HEG1 is highly expressed and is significantly correlated with poor prognosis as an independent prognostic indicator for HCC patients. In addition, we verified that HEG1 promoted HCC invasion, metastasis and EMT in vitro and in vivo through the Wnt signaling pathway by increasing β-catenin expression and maintaining its stability. Thus, these studies reveal the novel function of HEG1 in HCC progression, provide new insights into how HEG1 can influence Wnt signaling, and suggest that HEG1 is a potential prognostic biomarker and a worthwhile therapeutic target for HCC.

Clinical perspectives

  • HCC is the sixth most commonly diagnosed cancer (4.7%) and the fourth leading cause of cancer-related deaths (8.2%) worldwide. Metastasis is the main cause of death in postoperative HCC patients. However, the mechanisms for HCC metastasis remain unclear.

  • We provide the first evidence that HEG1 is highly expressed and significantly correlated with aggressive clinicopathological features and poor postoperative prognosis in HCC patients.

  • HEG1 was found to promote HCC invasion, metastasis, and EMT through activating Wnt/β-catenin signaling in vitro and in vivo. β-Catenin, as a downstream molecule of HEG1, is essential for HEG1-mediated activation of Wnt/β-catenin signaling and promotion of HCC invasion, metastasis, and EMT.

  • The results of the present study reveal the role and regulatory mechanism of HEG1 in HCC and indicates that HEG1 may be a potentially valuable prognostic biomarker and therapeutic target for HCC patients.

Acknowledgments

The authors thank Prof. Qiong-qiong He and Prof. Geng-Qiu Luo (Department of Pathology, Xiangya Hospital of Central South University) for their help with pathological diagnoses and guidance.

Competing Interests

The authors declare that there are no competing interests associated with the manuscript.

Author Contribution

Y.-r.Z. and L.-y.Y. conceived the study and wrote the manuscript. Y.-r.Z., Y.-m.L. and B.S. conducted the experiments and contributed to the data analysis. Y.-r.Z., J.-l.W., C.X., Y.-m.L., B.S. and L.-y.Y. collected clinical samples and corresponding clinical data. Y.-r.Z., J.-l.W. and L.-y.Y. revised the manuscript. All authors read and approved the final manuscript.

Funding

This work was supported by the Key Project of the National Natural Science Foundation of China [grant number 81330057]; the National Natural Science Foundation of China [grant number 81773139]; the National Science and Technology Major Project [grant number 2017ZX10203207-002-003]; the National Key R&D Program of China [grant number 2016YFC0902400]; the Specialized Research Fund for Doctoral Program of Higher Education of China [grant number 20130162130007]; and the Key Project of Science and Technology Plan of Science and Technology Department of Hunan Province [grant number 2014CK2003].

Abbreviations

     
  • ANLT

    adjacent nontumor liver tissue

  •  
  • CHX

    cycloheximide

  •  
  • Co-IP

    coimmunoprecipitation

  •  
  • CTNNB1

    catenin β 1

  •  
  • DFS

    disease-free survival

  •  
  • EMT

    epithelial–mesenchymal transition

  •  
  • HCC

    hepatocellular carcinoma

  •  
  • HEG1

    heart development protein with EGF-like domain 1

  •  
  • H&E

    Hematoxylin and Eosin

  •  
  • IF

    immunofluorescence

  •  
  • IHC

    immunohistochemistry

  •  
  • IVIS

    In Vivo Imaging System

  •  
  • KEGG

    Kyoto Encyclopedia of Genes and Genomes

  •  
  • NHCC

    nodular HCC

  •  
  • OS

    overall survival

  •  
  • SLHCC

    solitary large HCC

  •  
  • TCGA

    The Cancer Genome Atlas

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