Role of PVT1 polymorphisms in the glioma susceptibility and prognosis

Background Genetic factors play a crucial role in the glioma risk and prognosis of glioma patients. To explore the role of plasmacytoma variant translocation 1 (PVT1) polymorphism in the susceptibility and survival of glioma in the Chinese Han population, we conducted a case-control study. Methods The three single-nucleotide polymorphisms (SNPs) in PVT1 were genotyped using Agena MassARRAY from 575 patients with glioma and 500 healthy controls. We used the χ2 test to analyze the differences in distribution of allele and genotype between the cases and controls. Odds ratio and 95% confidence interval (CI) were calculated by logistic regression analysis to evaluate the association SNPs with glioma risk. The effects of polymorphisms and clinical features on survival of glioma patients were evaluated using the log-rank test, Kaplan–Meier and Cox regression analysis. Results We found that rs13255292 was associated with a decreased risk of glioma in the recessive model in overall or male; and rs4410871 was significantly associated with an increased the risk of glioma in age ≤40 years old or female. Moreover, the extent of resection and chemotherapy were found to be key prognostic factors in survival of glioma patients. However, the gender, age, tumor grade, radiotherapy and PVT1 polymorphisms have no effect on prognosis of glioma patients. Conclusions Our results indicated that PVT1 polymorphisms (rs13255292 and rs4410871) were associated with glioma susceptibility, but have no effect on prognosis of glioma patients. Further studies with large samples are required to confirm the results.


Introduction
Glioma is the most common intracranial malignant tumor in the central nervous system (CNS) and has a poor prognosis and high mortality (Reni et al., 2017). The incidence of glioma has been sharply increasing worldwide. The statistics of incidence and mortality worldwide for 36 cancers in 185 countries showed that there were 296 851 newly diagnosed cases and 241 037 individuals died from brain and CNS tumor in 2018 (Bray et al., 2018). According to the data of the National Office for Cancer Prevention and Control in China, the estimated numbers of newly brain and CNS tumor cases and deaths were 101 600 and 61 000, respectively (Chen et al., 2016). Despite diagnosis and treatments (surgery, radiotherapy and chemotherapy) have been continuously improving, the outcomes of patients with glioma remain poor. To date, many risk factors have been identified as potential contributors to gliomas risk, such as smoking, ionizing radiation exposure, occupational exposure, environmental carcinogens, higher socioeconomic status and education level (Ohgaki and Kleihues 2005). The age, gender, extent of resection, radiotherapy, chemotherapy, and histological grade, tumor size and range have been identified as potential contributors to the prognosis of glioma patients (Hayashi et al., 2017;Guo et al., 2019). Moreover, many genetic polymorphisms have been identified to be associated with the susceptibility to gliomas and as well as the prognosis of glioma patients (Li et al., 2013;Du et al., 2014;Jin et al., 2016). Therefore, it is critical to identify new glioma therapeutic targets and new diagnostic and prognostic biomarkers.
The human plasmacytoma variant translocation 1 (PVT1) gene at the 8q24.21 chromosomal region represents a long noncoding RNA locus that has been identified as a candidate oncogene (Colombo et al., 2015). Zou et al. (2017) found that diffuse glioma patients with high PVT1 expression had poor survival outcomes; aberrantly expressed PVT1 could be the independent prognosis biomarkers for glioma patients. The overexpression of PVT1 increased the expression of Atg7 and Beclin1 by targeting miR-186, which induced protective autophagy, thus promoting glioma vascular endothelial cell proliferation, migration and angiogenesis (Ma et al., 2017). Several polymorphisms in PVT1 have been reported to be associated with cancer risk and prognosis. The rs1561927 in PVT1 was found to be associated with poor overall survival (OS) in pancreatic ductal adenocarcinoma cases patients (Moschovis et al., 2019). The GG genotype of rs13281615 in PVT1 was associated with an increased risk of breast cancer likely by influencing PVT1 expression (Zhang et al., 2014). The presence of polymorphisms rs13281615 in PVT1 and rs2910164 in miR-146a contribute to a favorable prognosis in colon cancer patients by regulating COX2 expression and cell apoptosis .
However, the influence of PVT1 polymorphisms on the risk of glioma, as well as the prognosis of glioma patients in the Chinese Han population, has not been reported yet. Given the role of PVT1 in tumorigenesis and progression of glioma and prognosis of glioma patients, we hypothesized that the genetic polymorphisms in the PVT1 gene may also influence the risk of glioma and prognosis of glioma patients. To investigate this hypothesis, we recruited 575 patients with glioma and 500 healthy controls to investigate the role of the three single-nucleotide polymorphisms (SNPs) (rs4410871, rs4733789 and rs13255292) in the PVT1 gene in glioma susceptibility and prognosis of glioma patients in the Chinese Han population.

Study subjects
We randomly recruited a total of 1075 subjects, including 575 patients with glioma and 500 healthy controls from the department of neurosurgery at Tangdu Hospital of The Fourth Military Medical University. All patients had newly diagnosed and histologically confirmed glioma by at least two senior neuropathologists according to the WHO classification in 2007. All controls were selected from the general health examinations in this hospital during the same period. The controls with a history of cancer or brain and CNS-related diseases and previously receiving radiotherapy and chemotherapy for certain diseases were excluded. All subjects were unrelated individuals of the Chinese Han.

Follow-up
The clinical follow-up of patients was performed in a single-blind fashion with the endpoint of cardiac death. Patients were followed up through telephone calls, outpatient visits and writing communication with patients or their families by the professional medical staff every month. OS was measured from the date of diagnosis with glioma to the date of death or last follow-up. Progression-free survival (PFS) was calculated from the date of the pathologically confirmed to the progression of the disease, death without progression or last clinical follow-up.

Demographic and clinical data collection
The demographic and clinical characteristics of patients with glioma were collected and regularly updated from medical records, questionnaires and follow-up, such as age, gender, histology types, tumor grade, surgical methods, the extent of resection, treatment with radiotherapy and chemotherapy, date of the last follow-up and status of patients (living/deceased).

DNA extraction and genotyping
The peripheral blood sample (5 mL) was collected from each patient with glioma and control subject into the EDTA-containing vacutainers and stored at −20°C until use. We use the GoldMag-Mini Whole Blood Genomic DNA Purification Kit (GoldMag. Co. Ltd., Xi'an, China) to extract the genomic DNA of the samples according to the instructions. We performed a quality analysis of the extracted DNA by measuring its concentration and purity using a spectrophotometer (NanoDrop 2000; Thermo Fisher Scientific, Waltham, Massachusetts, USA).
The three SNPs (rs4410871, rs4733789 and rs13255292) in PVT1 were selected with minor allele frequency (MAF) >5% in the global population from the HapMap database. The Agena Bioscience Assay Design Suite V2.0 software (https://agenacx.com/online-tools/) was used to design PCR amplification and extension primers of the three SNPs. The PVT1 polymorphisms were genotyped using the Agena MassARRAY platform with iPLEX gold chemistry (Agena Bioscience, San Diego, California, USA) according to the protocol described. The Agena Bioscience TYPER software (version 4.0) was used to manage and analyze data.

Statistical analysis
The basic descriptive statistical analysis of demographic and clinical data was conducted using SPSS 20.0 statistical package (SPSS, Chicago, Illinois, USA). Pearson's χ 2 test and Student's t-test were used to analyze the differences in the distribution of gender and age between the case and control groups, respectively. The χ 2 test was used to examine whether the genotype frequencies of SNPs among control was consistent with Hardy-Weinberg equilibrium (HWE). The association between PVT1 polymorphisms and glioma risk was assessed under the genetic models by PLINK software (version 1.07). Odds ratios (ORs) and 95% confidence intervals (CIs) were calculated using logistic regression analysis. Kaplan-Meier method was used to evaluate the survival, and log-rank test to assess the difference between these two groups. Hazard ratio and 95% CI were calculated from the univariate Cox regression analysis to estimate the association between clinical factors, PVT1 polymorphisms with PFS and OS in glioma patients. Multivariate Cox models were performed to compute hazard ratio and 95% CI, after adjustment potential risk factors. All P values were two-sided, and P < 0.05 was considered statistically significant.

PVT1 polymorphisms and glioma risk
This study selected three SNPs in PVT1, which were successfully genotyped (call rate >95%). The detailed information, including chromosome ID, position, role, allele and potential function predicted, MAF for the SNPs in cases and controls and HWE of these variants is listed in Table 2. The genotype frequencies of the three SNPs among the controls were in agreement with the HWE (P > 0.05). However, there were no significant differences in the allelic frequency distribution of the three SNPs between the case group and the control group (P > 0.05). No significant association of the three SNPs in PVT1 with glioma risk.
To further explore the relationship between PVT1 polymorphisms and glioma risk, we performed a genetic model analysis, as shown in Table 3. The results showed that individuals with the TT genotype of rs13255292 were associated with a decreased risk of glioma compared with those with the CC/CT genotype in the recessive model before and after adjusted with age and gender (OR = 0.53; 95% CI, 0.29-0.99; P = 0.046). However, no significant association was found between the SNPs (rs4410871 and rs4733789) and the risk of glioma.
In order to reduce the impact of age and gender on the results of statistical analysis, we conducted a stratification analysis (Table 4). Our results found that individuals with the TT genotype of rs4410871 were associated with an increased risk of glioma compared with those with the CC genotype in age ≤40 years old (OR = 2.05; 95% CI, 1.12-3.75; P = 0.020]. Meanwhile, rs4410871 was found to be associated with an increased risk of glioma in the recessive model in age ≤40 years old (TT vs. CC/CT: OR = 2.33; 95% CI, 1.31-4.15; P = 0.004).

Clinical factors and prognosis of glioma patients
We also investigated the impact of clinical factors on the OS and PFS of glioma patients (Table 5). The univariate and Cox regression analysis results that the glioma patients with GTR was also associated with a reduced risk of death on OS (log-rank P < 0.001; hazard ratio = 0.63; 95% CI, 0.52-0.76; P < 0.001) and PFS (log-rank P < 0.001; hazard ratio = 0.59; 95% CI, 0.49-0.71; P < 0.001), compared with the glioma patients with NTR or STR. In addition, we also found that the glioma patients with the chemotherapy treatment had a longer OS (log-rank P < 0.001) and PFS (log-rank P = 0.012), and had a better prognosis of glioma patients (OS: hazard ratio = 0.67; 95% CI, 0.56-0.81; P < 0.001; PFS: hazard ratio = 0.81; 95% CI, 0.67-0.97; P = 0.025), compared with the no chemotherapy treatment. The Kaplan-Meier survival curve described the survival rates of glioma patients with the extent of resection (Fig. 1) and chemotherapy (Fig. 2) treatments, respectively. However, no significant associations were found between the age, gender, WHO grade, radiotherapy and the prognosis of glioma patients as measured by OS and PFS.

PVT1 polymorphisms and prognosis of glioma patients
We used the log-rank tests, Cox regression analysis (univariate and multivariate) and Kaplan-Meier analysis to evaluate the effect of the four PVT1 polymorphisms on the glioma patients with OS and PFS (Tables 5 and 6). However, there were no significant associations were found between the polymorphisms of PVT1 and the prognosis of glioma patients.

Discussion
To our knowledge, this case-control study is firstly to investigate the role of PVT1 polymorphisms (rs4410871, rs4733789 and rs13255292) in the susceptibility and survival of glioma in the Chinese Han population. We found that rs13255292 was associated with a decreased risk of glioma in the recessive model in overall or male; rs4410871 was significantly associated with an increased  Adjust OR (95% CI) were calculated by logistic regression analysis with adjustments for age and gender. P < 0.05 indicates statistical significance. CI, confidence interval; OR, odds ratio; SNP, single-nucleotide polymorphism.
risk of glioma in age ≤40 years old or female. Moreover, the extent of resection and chemotherapy were found to be key prognostic factors in the survival of glioma patients. However, no effects were found between PVT1 polymorphisms on the prognosis of glioma patients.
PVT1 is one of the transcribed lncRNAs located at the 8q24 human chromosomal region susceptibility locus.
LncRNAs are key mediators of pathways involved in tumor suppression and oncogenesis affecting important cellular processes, such as chromatin reprogramming, cis-and trans-regulation of gene expression and mRNA processing (Gibb et al., 2011;Guttman and Rinn, 2012;Zeng et al., 2015). PVT1, located downstream of MYC, has been proven to play an important role in cancer, and PVT1 dependence in cancer with MYC copy-number increases (Tseng et al., 2014). The upregulation of PVT1 has been found to be involved in poor prognosis in colorectal cancer (Takahashi et al., 2014), gastric cancer (Kong et al., 2015), pancreatic cancer (Huang et al., 2015), and glioma . PVT1 modulated GREM1 and BMP downstream signaling proteins through sponging miR-128-3p, thereby promoting tumorigenesis and progression of glioma (Fu et al., 2018). The overexpression of PVT1 in glioma tissue and cells and promotes glioma cell proliferation and invasion by targeting miR-200a . PVT1 knockdown could negatively regulate miR-424 to inhibit human glioma cell activity, migration and invasiveness (Han et al., 2019).
The rs4410871 and rs13255292 in PVT1 were found to be significantly associated with the risk of glioma in the Chinese Han population. However, no association was found between rs4733789 and glioma risk. These PVT1 polymorphisms have been reported to be associated with disease susceptibility. A Meta-analysis of genome-wide association studies (GWAS) identified that rs4410871 influenced allergic sensitization (Bonnelykke et al., 2013). The rs4410871 was found to be associated with susceptibility to multiple sclerosis (Gourraud et al., 2012;Beecham et al., 2013). A previous meta-analysis of GWAS identified that rs4733789 was associated with adult height in an East Asian population (He et al., 2015). The men with the minor allele T in rs4476972 and with the major allele C in rs4733789 tend to have a lower risk of developing prostate cancer in the African American population (Lin et al., 2019). A GWAS and a pooled study of three Eastern Asian populations observed a significant association between rs13255292 (PVT1) and diffuse large B-cell lymphoma risk (Cerhan et al., 2014;Bassig et al., 2015). The rs13255292 was also found to be associated with ovarian cancer (Kim et al., 2019). However, this study was first to investigate the association between the Kaplan-Meier curves for overall survival and progression-free survival of extent of resection in glioma patients.

Fig. 2
Kaplan-Meier curves for overall survival and progression-free survival of chemotherapy in glioma patients.
three PVT1 polymorphisms and glioma risk. Therefore, the results need to be confirmed in a multi-ethnic population with a larger scale.
This study also explored the impact of clinical features and PVT1 polymorphisms on the prognosis of glioma patients. Our results found that extent of resection and chemotherapy were key prognostic factors in the survival of glioma patients. However, gender, age, WHO grade, radiotherapy and PVT1 polymorphisms have no effects on the survival of glioma patients. Wang et al., indicated that degree of resection and pathological grade were independent prognostic factors for patients with malignant gliomas, but age and gender have no effect on glioma survival outcome . The extent of resection and sex was found to be as prognostic factors for OS in pediatric high-grade glioma (McCrea et al., 2015). This comprehensive analysis of multicentric glioma patients revealed that age >54 years old, surgical resection and radiotherapy were significantly associated with improved survival and were independent prognostic factors for OS. Radiotherapy and radiotherapy combined with chemotherapy were independent prognostic factors for surgical patients' OS as well (Wang et al., 2018). There are many reasons for conflicting results, such as differences in sample size, ethnicity, tumor grade and experiment method. Therefore, further study is needed to confirm the results.
There were several limitations in the present study. First, only three SNPs in PVT1 were selected in this study, which may not represent a comprehensive view of PVT1 variation. Further studies on variation in susceptible regions of PVT1 are needed. Second, data were not available for some risk factors (e.g. cigarette smoking and  alcohol consumption); therefore, these factors should be taken into account in future studies. Third, since this is a very preliminary study, further functional studies are also required to explore the mechanisms of the PVT1 polymorphisms affected the risk and prognosis in a glioma patient.

Conclusion
In conclusion, the results indicated that PVT1 polymorphisms (rs13255292 and rs4410871) were significantly associated with the risk of glioma. The extent of resection and chemotherapy were found to be key prognostic factors in the survival of glioma patients. However, the PVT1 polymorphisms have no effects on the prognosis of glioma patients. Further study with large samples on the role of PVT1 polymorphisms in the susceptibility and survival of glioma is warranted to obtain more conclusive outcomes.