| BackgroundProstate cancer is the most common malignancy affecting men’s health. It occurs in men over the age of60. There were679,000new cases of cancer in2002and was the second most common cancer in male. The incidence of prostate cancer is different due to the diversity of geographic and ethnic.North America and Scandinavia has the highest incidence of prostate cancer, but most of the Asian countries are low incidence areas. African Americans which has the highest incidence of prostate cancer is85.7/100,000. American Caucasians’incidence rate is107.8/100,000and other Western developed countries are50-103/100,000. In European countries, there are around190,000new cases and about80,000patients died of prostate cancer. The incidence of China and Japan are lower than in other countries Among Asian countries. Japan has the incidence rate of9/100,000and China has the incidence rate of2.3/100,000(7.7/100,000in Shanghai region). Whether in the areas of high incidence or low incidence, the incidence of prostate cancer is increasing year by year from1973to1992. Therefore, the relevant factors for prostate cancer risk and early prevention of prostate cancer is important.At present the cause of prostate cancer is not fully understood. The known risk factors are age, race, family history. Difference in incidence between ethnic and region may due to the genetic background, environment, lifestyle and other factors. Studies have confirmed that genetic susceptibility and environmental factors will have an impact on the incidence of prostate cancer. Single nucleotide polymorphism is one of the important fields in genetic susceptibility.Single Nucleotide Polymorphisms (SNPs) are DNA sequence polymorphisms at the genomic level which were caused by a single nucleotide mutation. Wherein the rate of variation of less than1%is referred to the mutant and the rate greater than1%is called single nucleotide polymorphism. SNPs which is widespread human genetic variation in the human genome may be the most common type, accounting for over90%of all known polymorphisms. Each of about1000bp in the human genome is SNP and total number of SNPs is about3×106.Because SNPs involves only a single base mutation, it can be converted by transition or transversion caused, may also be caused by insertion or deletion of single nucleotides. SNPs are commonly caused by transitions and transversions. Most SNPs is meaningless and does not affect protein function or gene expression (such as non-coding region SNPs).According to the location of SNPs in the genome and the change of gene encoding, the SNPs can be divided into several categories. Approximately95%of the SNPs in the non-coding region, which is located in a small portion of the gene regulatory region, were referred to as gene control region SNPs (rSNPs). which is located in the coding region of the gene coding SNPs called SNPs (cSNPs). Furthermore, if cSNPs does not change the amino acid sequence encoded, it could be called synonymous SNPs (sSNPs). But if it change the amino acid sequence, it could be called non-synonymous SNPs or missense SNPs (nsSNPs). SNPs can affect the function of genes through a variety of ways. Some SNPs have been shown related to prostate cancer development and prognosis.Due to SNPs are widely distributed in the population and this genetic marker is relatively stable existing from birth to death, so that genetic analysis can be carried out before the onset of decades.Therefore, SNPs and only able to provide proof of the genetic etiology of tumorigenesis, but also provides an effective means of common cancer screening.Not only SNPs can be able to provide proof of the genetic etiology of tumorigenesis, but also provides an effective means of common cancer screening.As the third generation of SNP genetic markers, only have two allelic type which is less than microsatellite variability. Because of the huge number of frequency distribution in total genome, it is more stable than microsatellite genetic markers. SNPs in the genomic screening process generally only need to analysis positive or negative (+/-), so it is easy to conduct genotyping analysis automatically. Compared to the first and second generation of genetic markers are more suitable for exploring population-based genetic condition and other aspects of the study in complex genetic diseases. It has been replaced microsatellite marker technology in the field of genetic research. SNPs were used to explain the phenotypic differences between individuals, different complex diseases susceptibility of different groups or individuals, drug and environmental factors response. It has been widely used in clinical diagnosis, forensics, pathogen detection, genetic diseases, new drug development and other aspects.Common methods of analysis of SNPs can be divided into three categories. The first category is association analysis based genetic epidemiology method, including the research of SNPs in disease susceptibility, drug reactions and other phenotypic differences.The second category is about the analysis in cellular and biochemical levels including enzyme activity and other aspects in cell signaling pathways to illustrate the impact of SNPs on gene function. The third category focus on SNPs impacting on molecular mechanisms of gene expression. Through the role of SNPs in the gene transcription, translation and protein expression to explore the mechanism of SNPs affecting gene function.Zheng SL et al. have published an article in the New England Journal of Medicine. They found high-risk SNPs in five loci (three in8q24,17q12and the other two SNPs located in17q24.3). They choose a highest hazard ratio SNPs in each loci to analysis totally. Each of these five SNPs has the prostate cancer risk odds ratio (OR) between1.22to1.53. However, with four to five SNPs occured at the same time, the OR value will reach to4.47. If also defined family history of prostate cancer as a risk factor, OR value was2.22. Then combined five or even more risk factors, the OR values could be up to9.46(P=1.29×10-8). The study results showed that the joint analysis of multiple SNPs can improve the effectiveness of prediction in the risk of prostate cancer.The research group in Okayama University had screened48missense SNPs (non-synonymous SNPs) in cancer-related genes. They found12SNPs in10genes and these SNPs have a significant impact on the incidence of prostate cancer. This10genes include five tumor suppressor genes, two DNA repair genes, a metabolic enzyme gene, a chromosome segregation gene and an apoptosis-related gene. Nine SNPs which are correlated with prostate cancer were first discovered. This12SNPs in prediction of prostate cancer risk also has a cumulative effect. The highest risk group’s OR value can be up to47.4comparing with the low-risk group. The highest risk group the incidence of prostate cancer in the next30years was29%, while the low-risk group was0.6%and the lowest risk group was only about0.2%. Thus, through the integration of multiple tumor-associated SNPs risk to conduct tumor genetics evaluation, can further improve the accuracy and efficiency of prostate cancer screening in high-risk populations. It also can improve the prevention or early diagnosis of prostate cancer.Because of similar geographic and ethnic origin, Chinese population and Japanese population have great similarity in genetic background. These prostate cancer risk SNPs obtained by large-scale screening of the Japanese population may also apply to the Chinese population. In order to test this hypothesis and further expand this research results from Japan into China and other Asian countries, China, Japan, South Korea and Singapore jointly launched an international multi-center study. This study was designed to test the effectiveness of these prostate cancer risk SNPs in other Asian populations. The selected SNPs in this article is derived from the achievement of Okayama University research group and is consistent with multi-center study.Purpose1. To investigate the association between SNPs and the risk of prostate cancer in Guangzhou Han population, positive sites to guidance for prostate cancer prevention and early diagnosis. Using positive SNP for prostate cancer prevention and early diagnosis.2. Try to establish a risk model with number of positive single-nucleotide polymorphisms in predicting the risk of prostate cancer among Guangzhou Han population.MethodFrom June2012to July2013, recruited112cases of prostate cancer (Pca) patients and104cases of non-prostate cancer patients and healthy volunteers (control group) from Southern Medical University Zhujiang Hospital and Guangdong Province People’s Hospital.Case group included biopsy or pathologic diagnosis of prostate cancer patients, the initial onset or referral. Control group included patients with prostate cancer and other malignancies with age matched patients maintained. The could be in the same patient hospitalization or outpatient medical units during the same period. Recorded clinical data such as age at onset, PSA, Gleason score, TNM stage, treatment, and treatment effects and distributed questionnaires to patients. The questionnaires included smoking history, drinking history, family history, diet habit and so on.A2mL blood sample was obtained from each participant, and it remained at room temperature for no more than six hours. Genomic DNA was extracted using a TIANamp Blood DNA Kit (TIANGEN Biotech, Beijing, China) according to the manufacturer’s instructions, and was stored at-20℃. We analyzed the Axin2SNP (rs2240308) and seven SNPs of the other genes (not shown in this paper) using these samples. The genetic analyses were performed using the ABI SNaPshot multiplex system (Life Technologies Corporation, Carlsbad, CA, USA).Statistical analysisWe compared the proportion (percentage) of the each genotype and allele of the SNP [rs2240308:G/A] and other seven SNPs in the controls and prostate cancer cases. The association between the SNP and incidence of prostate cancer was analyzed using a logistic regression model. The odds ratio (OR),95%confidence interval (CI) and corresponding p values for the association between the prostate cancer risk and the genotypes or alleles were calculated. The data for each genotype or allele was compared with that of the common homozygote or allele as the reference group. We also stratified our analyses by the age of the patient at diagnosis (≤72or≥72years) and by the aggressiveness of the disease (localized or advanced prostate cancer). Localized prostate cancer inclusion criteria are T1-2, N0, M0, Gleason score2-7, and PSA levels≤50ng/mL. Advanced prostate cancer inclusion criteria are T3/4or N+or M+or Gleason score8-10or PSA levels>50ng/mL.In these analyses, the data were adjusted for the age, smoking status and drinking status. The data are shown as the means±standard deviation (SD). The Chi-square test was used to compare the distribution of the control males and prostate cancer patients or of the clinical characteristics. The Mann-Whitney U test was also performed to analyze the statistical significance of differences in the age and PSA level at diagnosis. All statistical analyses were conducted using the SPSS software program, version20.0. The differences were considered to be significant for values of p<0.05.Results1. Eight SNPs genotypes (or allele) distribution and prostate cancer risk association analysis:Whether or not adjusted for age, smoking history, drinking history and other confounding factors, the p value of these six SNPs (including SMARCAD1SNP, CASP9SNP, PSMD8BP1SNP, DCLRE1B SNP, MMP27SNP and BARD1SNP) was greater than0.05individually. And this suggested that the case group and the control group genotype (or equivalent differences in allele) has not statistically significant association in these SNPs except RAD17SNP and AXIN2SNP.RAD17SNP and AXIN2SNP [rs2240308] were associated with prostate cancer risk. Due to the result of Hardy-Weinberg equilibrium test with RAD17SNP genotypes in the control group is p=0.0324, it might affect its population representativeness. So this study only focused on AXIN2SNP [rs2240308] with further statistical analysis. AXIN2SNP [rs2240308] GG genotype frequencies in case group (59.2%) was significantly higher than control group (39.0%) and GA genotype frequencies in the case group (30.1%) was higher than the control group (52.0%).G allele frequency (74.3%) is higher than control group (65.0%) in the case group, on the other hand, A allele frequency in the control group (35.0%) was higher than the case group (25.7%). GA genotype compared with the GG genotype (as a reference) carriers was statistically significant and adjusted OR was0.377(95%CI:0.206-0.688, p=0.001). AA genotype compared with the GG genotype was no statistically significant and adjusted OR was0.830(95%CI:0.309-2.232, p=0.712). G allele (as a reference) and the A allele differences between cases and controls remained statistically significant (p=0.048) and adjusted OR was0.649,95%CI:0.422-0.996.2. Further stratified analysis AXIN2SNP [rs2240308] by age:Compared to the GG genotype (as a reference), GA genotype carriers in≤72years group (adjusted OR=0.419,95%CI:0.181-0.969, p=0.042). and>72years group (adjusted OR=0.364,95%CI:0.150-0.879, p=0.025) both showed the lower risk of prostate cancer. A allele in≤72years group showed the lower risk of prostate cancer (adjusted OR=0.514,95%CI:0.281-0.940; p=0.031), but in the age>72group did not find statistically significant (p=0.646).3. Further stratified analysis AXIN2SNP [rs2240308] by tumor progression:Compared to the GG genotype (as a reference) GA genotype carriers in localized group (adjusted OR=0.246,95%CI:0.100-0.607, p=0.002) and progressive group (adjusted OR=0.446,95%CI:0.228-0.873, p=0.018) both showed lower risk of prostate cancer. A allele carriers in localized group showed lower risk of prostate cancer (adjusted OR=0.408;95%CI:0.206-0.807, p=0.010), but not found statistically significant in advanced group (p=0.271). On the other hand, the allele [A] was associated with a reduced incidence of prostate cancer in younger patients and in the patients with localized cancer.4. Association between AXIN2SNP [rs2240308] genotype and clinical characteristics (cancer aggressiveness, Gleason score, PSA level, age at diagnosis, smoking and drinking status, hypertension):Among clinical indicators, we found no significant difference between the GG genotype and non-GG genotype.ConclusionIn conclusion, our study demonstrates that there is a significant association between the SNP [rs2240308:G/A] of the Axin2gene and prostate cancer risk. This is, to our knowledge, the first study showing the possible involvement of the Axin2polymorphism in prostate cancer development. Although additional studies with larger and more diverse populations and a functional analysis of the polymorphism are necessary to confirm and extend our findings, we believe that the Axin2SNP [rs2240308] could be a useful biomarker for the predisposition to prostate and for the early diagnosis of the disease. |
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