Evaluation of rs1982073 polymorphism of transforming growth factor-β1 in glioblastoma

INTRODUCTION

Glioblastoma (GBM) is the most common form of malignant brain tumors with an incidence rate of 3.19/100,000 persons in the United States and survival rate of about 1 year. Risk factors include prior radiotherapy, decreased susceptibility to allergy, immune factors and immune genes, as well as some single-nucleotide polymorphisms (SNPs) detected by genomic analysis.[1,2] The most frequent location of GBM is cerebral hemispheres; with 95% of these tumors arise in the supratentorial region, while only few percent of tumors occur in the cerebellum, brain stem, and spinal cord. Low survival rates have led to creation of treatment method in order to tumor removal or increase survival in GBM[3,4] and unlike the current treatment regimens, GBM survival of 5 years has still been reported to be <10%;[3,5] this cancer has a poor prognostic[6] as well as its molecular mechanisms that are less known.[7] The transforming growth factor-β (TGF-β) superfamily encompasses around 40 secreted cytokines, including TGF-β, bone morphogenetic proteins, activins, nodal, lefty, myostatin, anti-Müllerian hormone, and growth differentiation factors. These cytokines regulate a plethora of biological functions such as cell proliferation and apoptosis, embryonic patterning, stem cell maintenance, cell differentiation, migration, and immune surveillance. TGF-β plays a very important role in tissue homeostasis and cancers.[8,9,10] This group of cytokines consists of three factors such as TGF-β1, TGF-β2, and TGF-β3, which TGF-β1 is more important.[11,12] While activating the TGF-β pathway, TGF-β was attached to its receptor that induced phosphorylation and activation of SMAD2/3 and then SMAD4, which in the following the agent would be transferred to the nucleus and regulated the expression of genes involved in cell division, migration, invasiveness, angiogenesis, and epithelial–mesenchymal transition.[9,10,13,14] In addition, TGF-β also plays a noticeable role in progression of tumors on independent paths of the SMAD.[14,15]

The role of TGF B in cancer can be considered as the both initially cell division and tumor suppressor but it may also cause tumor invasion and metastasis.[16,17] The above discussion suggests that TGF-β is a very good target for many cancer studies and has been yet evaluated in several ways.[7,10,11,12,16,17,18] Many cancer cells, such as GBM, are dependent on the TGF-β pathway,[14] and recent studies have reported the increased expression of this cytokine in GBM with less survival.[19,20,21,22] TGF-β secretion in GBM has also enhanced tumor cells.[9,10]

Malignant cancers, such as GBM, have lost selectively TGF-β capabilities in inhibiting proliferation, while other functions of this route remain intact. The TGF-β pathway plays many roles in the carcinogenesis. For example, it has effect on important activities in GBM aggressiveness such as stemness, immunosuppression, angiogenesis, and invasion/migration as well as drug-/radioresistance.[10]

MATERIALS AND METHODS

This case–control study was approved by the Research and Ethics Committee of Isfahan University of Medical Sciences. After providing sufficient information, written consent was obtained from all patients or their legal guardians before involvement in the project. This study was conducted on 100 cases of histopathologically confirmed GBM according to tumor-node-metastasis classification system of the American Joint Committee on Cancer 2010, 7^th edition, including 47 paraffin-embedded brain tissue samples that was taken from the Pathology Department of Al Zahra University Hospital and 53 blood samples from another GBM patients, who was under therapy for this disease from Milad Hospital, and 150 sex- and age-adjusted controls from population of Isfahan, Iran, from 2013 to 2015. In cases, the extension of disease, if the disease progression was defined or in the case of local recurrence or metastasis was detected (mainly in the lung, bone, and liver or combined), they were excluded.

DNA was extracted from the brain tissue samples using PFET-DNA extraction kit (Yektatajhiz Inc., Tehran, Iran) and from blood samples using Blood-DNA extraction kit (Yektatajhiz Inc., Tehran, Iran) according to the manufacturer's protocol.

The Pro10Leu, rs1982073 or rs1800470 SNP in TGF-β1 SNP were identified by the NCBI, and ensemble databases and primers were designed by Beacon Designer 8.1 (PREMIER Biosoft International, USA) and synthesized by Bioneer (Bioneer, Korea). The forward primer was 5′-sequence-3′ and reverse primer was 5′-sequence-3′. Genotyping was performed by high-resolution melt (HRM polymerase chain reaction [PCR]) assay using a Rotor-Gene 6000 instrument (Corbett Life Science, Australia).

PCR reactions were carried out in triplicate in 10 μL of final volume using HRM kit (Qiagen, Germany) according to manufacturer protocol. The PCR program consisted of an initial denaturation – activation step at 95°C for 10 min, followed by a 40-cycle program (denaturation at 95°C for 15 s, annealing conditions 60°C for 20 s, 72°C for 20 s; an HRM step from 75°C to 95°C rising at 0.1°C/s). Curves for each triplicate were checked on the shape, melting pattern, and Tm to meet reproducibility.

Melt curves from HRM which suspected to SNP were selected and subjected to direct sequencing.

The Hardy–Weinberg equilibrium (HWE) was tested to compare the observed genotype frequencies with the expected frequencies among samples so that the genotype distribution of TGF-β1 rs1982073 was compatible with the HWE in our patients.

Finally, the collected data were entered into the SPSS (version 20; SPSS Inc., Chicago, Ill., USA) and mean ± standard deviation or n (%) was used to show the data. Moreover, Fisher's exact test and independent t-test were applied for statistical analysis of frequency distribution of gender and mean age. To show the relationship between the genotype, TGF-β1 rs1982073 allele and GBM disease, logistic regression was used and odds ratio (OR) was reported. Furthermore, to increase the precision of the study, variables such as age and gender were taken under control as the confounding variables. In all the analyses, P < 0.05 was considered statistically significant.

RESULTS

In this study, a total of 150 healthy individuals included 80 (53.3%) males and 70 (46.7%) females with the mean age of 49.67 ± 15.12-year-old were used in the control group. Furthermore, 100 patients with GBM included 55 (55%) males and 45 (45%) females with the mean age of 51.63 ± 13.27-year-old were assigned to the case group. The two groups were statistically matched in terms of age and gender (P > 0.05) [Table 1].

On the other hand, the frequency distribution of TGF-β1 allele G in GBM patients was 41.5% more than healthy individuals with 30.7% (OR [95% confidence interval (CI) ]: 1.604 [1.104–2.330]; P = 0.013). Furthermore, the distribution of AG genotype in patients with GBM was 37% and in healthy individuals were 33.3%, which was not statistically significant with the incidence of GBM disease (P = 0.192). In contrast, a significant correlation was found between GG genotype and GBM disease (OR [95% CI]: 2.163 [1.071–4.370]; P = 0.032). In addition, by controlling the age and gender, the obtained results remained valid; in fact, age and gender did not play any confounding role on the results [Table 2].

DISCUSSION

Considering the multiple roles of TGB-β in cancer suppressing or progressing, and the importance of GBM among high-mortality brain tumors, in this study, we evaluated the effect of T29C (rs1982073) polymorphism of TGF-β1 gene in GBM. We analyzed the DNA sequence of the TGF-β1 gene from blood samples taken from 100 GBM patients and 150 noncancerous controls who were adjusted for sex and age.

It is to be noted that the prevalence of GBM was higher in men and its mean age was 51.63 ± 13.27 years. Thus, it can be concluded by adding other epidemiologic results that generally, the GBM is more prevalent in men and it mostly occurs in elderlies rather than the youth. According to the National Database of Central Brain Tumor Registry of the United States, the age-adjusted GBM incidence rate is 3.97 cases/100,000 for men and 2.53 cases/100,000 for women.[30]

Moreover, the analysis of association of allele and genotype of TGB-β gene with the occurrence of GBM showed that the frequency of GG genotype was significantly higher in GBM patients, but although the frequency of AG genotype was higher in GBM group, it was not statistically significant. Furthermore, the presence of G allele was significantly more frequent than A allele in GBM patients. These results remained valid by adjusting sex and age, so we may conclude that sex or age did not have a role in the presence of these alleles of genotype in these patients.

Accordingly, in the study of Pooja et al. who worked on 1222 samples of the Indian population, they analyzed 29C>T (Pro10Leu, rs1982073 or rs1800470) and 74G>C (Arg25Pro, rs1800471) polymorphisms in the TGF-β1 gene. They found that these polymorphisms in the TGF-β1 gene significantly affect breast cancer risk, which might be related to higher TGF-β1 levels. They showed that TGF-β1 level was significantly higher in breast cancer as compared to the control group. This higher TGF-β1 level might be due to a higher frequency of these genotypes in breast cancer cases.[11]

In the study of Watanabe et al., they found 106 SNPs and 11 other types of variations in TGF-β11 and six other genes. These genes were TGF-β1 receptor gene (TGF-β1R1), TGF-β2 receptor gene (TGF-β1R2), SMAD2, SMAD3, SMAD4, and all of which compose the TGF-β1 signaling pathway. A total of 11 SNPs were identified in TGF-β1. The only SNP (TGF-Β11-2, 29C>T) identified in the coding region (exon 1) was nonsynonymous and resulted in proline to leucine change (P10Leu). Hence, they suggested further evaluations of these genes in cancerous cases in order to find probable associations.[28]

In contrast, there was a study by Krippl et al. on 500 breast cancer cases and 500 sex- and age-adjusted controls that showed no significant association in the presence of TGF-Β11, L10P polymorphism, and breast cancer. On the other hand, they found higher lymph node metastasis in patients carrying this allele.[31]

Finally, it might be necessary to say that, one of the limitations of this study was difficulties in gathering GBM samples, because larger sample size may lead to more reliable results. Furthermore, another weakness of our study was the lack of other clinical features and comorbid disease of these patients. Thus, the duration of disease, family history of GBM, and other comorbid diseases might affect the distribution of mentioned allele or genotypes in these patients. Hence, further study noticing these factors in a wider sample size is recommended.

CONCLUSION

In conclusion, and to the best of our knowledge, the results of the present study support that the Pro10Leu, rs1982073, or rs1800470 SNP in TGF-Β1 is found to be expressed significantly more in GBM patients as it was found in the breast cancer. Thus, further evaluation regarding the effects of this polymorphism on susceptibility to other types of neoplasms and their outcome is recommended.