Polymorphism in asparagine synthetase is associated with overall survival of hepatocellular carcinoma patients

The subjects enrolled in this study were constituted of 2 independent groups of patients.

The first was constituted of 90 HCC patients, 77 CHB patients and 70 non-HBV controls which were enrolled from the Weifang People’s Hospital from Jan 2011 to Nov 2014. The second was constituted of 337 HCC patients and 310 CHB patients enrolled from the same hospital from May 2005 to Jan 2010. Among the 337 HCC patients, clinical outcomes of 146 patients that had undergone surgical resection of a HCC tumor were recorded until October 2015, with a median follow-up time of 39.5 months (range 5.0–76.5 months).

HCC patients, CHB patients and non-HBV controls were defined as previously reported [3]. The main features of the subjects were summarized in Table 1. The study was carried out in accordance with the guidelines of the Helsinki Declaration after obtaining written informed consent from all the subjects and was approved by the ethics committee of the Weifang People’s Hospital. All patients consented to participate this study.

HepG2, HepG2. 2.15, and SMMC-7721 cells were were kindly gifts from professor Xiaopan Wu (National Laboratory of Medical Molecular Biology, Institute of Basic Medical Sciences, Chinese Academy of Medical Sciences, Beijing, China). The cells were propagated in MEM/NEAA or RPMI-1640 medium with 10% fetal calf serum. All cells were maintained with 5% CO2 at 37 °C. We seeded 2 × 10⁵ HepG2, HepG2. 2.15, or SMMC-7721 cells each well in 24-well plates. The ATF6 expression plasmid was constructed as previous reported [3]. Half Wells were transfected with ATF6 expression plasmid by Lipofectamine™ 2000 (Invitrogen, Carlsbad, CA). The rest half were non-transfected cells regarded as controls. All transfections were repeated 3 times. The primers used for qPCR and detailed qPCR methods were according to previously reported [2, 3]. Total RNA was extracted from the peripheral blood of 90 HCC patients, 77 CHB patients and 70 non-HBV controls and mRNA levels of ATF6 and ASNS were tested. The detailed qPCR methods were the same as above mentioned.

We constructed a pGL3-Basic (Promega, Madison, WI) reporter plasmid encompassing −395 to +145 bp of ASNS promoter. The ATF6 eukaryotic expression plasmid and FLAG control plasmid were gifts from Dr. Wu (Institute of Basic Medical Sciences, Chinese Academy of Medical Sciences). The luciferase assay was performed as previously reported [3] in HepG2 cells.

Genomic DNA were extracted from peripheral blood using the salting-out protocol. Using the NCBI dbSNP database (http://​www.​ncbi.​nlm.​nih.​gov/​snp/​), potential functional SNPs (SNPs in promoter region and mRNA sequence) with minor allele frequency (MAF) greater than 0.05 for the Han Chinese Beijing population were selected. Only 2 SNPs were found, namely rs1049674 (nonsynonymous coding) and rs34050735 (5’UTR). These 2 SNPs were genotyped using TaqMan method (Applied Biosystems, Foster City, CA), according to the manufacture’s protocols. All the samples were successfully genotyped.

ANOVA was used to examine the differences in mRNA expression levels between different groups. By using the χ2 test, we tested whether the genotype distributions of SNP were in the Hardy–Weinberg equilibrium (HWE). We used 2 × 2 or 2 × 3 contingency tables for comparing allele and genotype frequencies between different groups. We calculated the linkage disequilibrium values (r2, D’) and the haplotype estimation using the SHEsis online software [12]. The associations between overall survival and demographic characteristics, and rs1049674 and rs34050735 were estimated using the Kaplan–Meier method. A survival curve was drawn with the Kaplan–Meier method for each genotype. P < 10.05 was the criterion for statistical significance. All statistical analyses were performed using the Statistical Package for the Social Sciences (SPSS), version 15.0 (SPSS Inc., Chicago, Illinois).

We transiently transfected HepG2, HepG2.2.15, and SMMC-7721 cells with ATF6 expression plasmid, and then examined the mRNA expression of ASNS. Final abundance figures were adjusted to yield an arbitrary value of 1 for non-transfected cells. The result showed that when ATF6 was over expressed, the mRNA level of ASNS was elevated by 1.86-fold, 1.95-fold and 1.65-fold in HepG2, HepG2.2.15, and SMMC-7721 cells, respectively (P < 0.001) (Fig. 1).

We then examined levels of total ATF6 and ASNS mRNA using quantitative realtime PCR. The mRNA levels of ATF6 and ASNS were measured. As shown in Table 1, the 3 groups of subjects had similar age and sex distribution, but CHB and HCC groups had higher smoking and drinking ratio than non-HBV controls. Final abundance figures were adjusted to yield an arbitrary value of 1 for ATF6 expression level in HCC patients (Figs. 2 and 3). The result showed that non-HBV controls and CHB patients had 2.67-fold and 2.08-fold higher ATF6 mRNA levels than HCC patients (P = 5.38E-79), and 2.78-fold and 2.16-fold higher ASNS mRNA levels than HCC patients (P = 9.05E-82). We also found that ASNS expression level was positively correlated with ATF6 level (r2 = 0.98).

To further confirm whether ATF6 regulated ASNS promoter, we transiently transfected HepG2 cells with pGL3-ASNS promoter together with ATF6 expressing plasmid or FLAG control plasmid. The result showed that the ATF6 expressing plasmid group had 1.59-fold higher luciferase activity compared with FLAG control group (P = 0.002). This result indicated that ATF6 could indeed positively regulate the promoter region of ASNS gene.

We next conducted genotyping experiments for the 2 ASNS polymorphisms in the case–control samples. Genotype distributions of the studied SNPs were in HWE in both cases and controls. The genotype distributions and allelic frequencies of ASNS polymorphisms in CHB and HCC patients were represented in Table 2. The frequency of T allele of rs34050735 was 16.5% in HCC patients vs. 10.8% in CHB patients (P = 0.003, OR = 1.63, 95%CI = 1.18–2.25). The Cochran-Armitage trend test (assuming an additive model for T allele) revealed an allele dose-dependent association of rs34050735 with HCC (P = 0.005), with decreased OR of 0.71 and 0.44 for GT and GG genotypes, respectively.

We then used binary logistic regression to adjust for confounding factors as age, gender, smoking drinking and family history under additive model, and the results showed that rs34050735 was still independently associated with HCC (P = 0.005, OR = 1.59, 95%CI = 1.15–2.20). While the other SNP rs1049674 was not associated with HCC under any model. We analyzed the degree of LD for these 2 SNPs, and found there was no apparent LD (D’ ≤ 0.05, r² ≤ 0.002). Table 3 shows 4 haplotypes constructed by these 2 SNPs. The A-T haplotype was associated with HCC (P = 0.02).

Finally, we asked the question whether these 2 SNPs influencing overall survival of HCC patients. Among the 146 HCC patients with clinical outcomes, 127 patients were died and were included in the final analysis. As shown in Table 4 and Fig. 4, SNP rs34050735 was significantly associated with overall survival (P = 0.001). Patients who carried the TT genotype had a significantly shorter survival time compared to those with the GT or GG genotypes. We used Receiver Operating Characteristic (ROC) curve to establish the prognosis of HCC patients. According to the ROC curve, patients whose survival time more than or equal to 38 months were defined as the better group, survival time less than 38 months were defined as the poor group (P = 0.025).