| Background and Objection:Breast cancer is one of the most common cancers among women. Compared with western countries, China has lower incidence of breast cancer. With the development of industry and the change of lifestyle, however, the incidence of Breast cancer in China is increasing, and patients with breast cancer are being much younger now than in the past. According to the investigation in2005, the incidence of breast cancer in cities of China has been ranked as1st. Moreover, the incidence of breast cancer among Chinese women is expected to reach85.3/100,000in2021. Therefore, taking effective measures to control the incidence of breast cancer is becoming more and more important in our country. It is necessary for us to screen out high risk population by some efficient assessment based on the risk factors of breast cancer to facilitate the individualized treatment and the first-grade prevention.As we know, the development of breast cancer is a complicated process with interactions of multiple factors and stages. Its associated risk factors can be divided into two groups, endogenous and exogenous, in term of their sources, characteristics and functional ways. Endogenous factors mainly include the immune status, genetic background, the level of hormone and so on. Of these factors, different genetic background could explain, to a certain extent, that not all of women suffered from breast cancer when they live in the same environment. A lot of susceptibility genes that are closely associated with various cancers have been found so far. Except well-known breast cancer genes, BRCA1and2, other genes, such as HER-2/neu、CyclinD1、COX、 FGFR-2, have been identified as breast cancer susceptibility genes. In addition, another important reason for the development of breast cancer is single nucleotide polymorphism (SNP) which is the third generation of genetic marker following RFLP, SSCP, and defined as base changes (transition, transversion, insertion and deletion) in gene sequence with a higher density of once every300-1000bases. Additionally, a large amount of studies have found that SNP is a crucial genetic basis for individual differences in many biological traits such as disease susceptibility and drug sensitivity etc. Therefore, the studies based on SNPs will provide theoretical evidences and data bases for individualized medicine including disease diagnosis, treatment and precaution. Exogenous factors also have close relationship with environment and lifestyle. At present, it is admitted that exogenous risk factors of breast cancer involve breast feeding history, oral contraceptive, living environment, diet, etc.In some western countries with high incidence of breast cancer, more and more breast cancer risk assessment tools have been built based on these risk factors mentioned above. In America, for example, the first breast cancer risk assessment tool-Gail Model was developed in1898, and then BRCAPRO Model, Claus Model, Tyrer-Cuzick Model, BOADICE Model, and some online assessment tools appeared gradually. In some Asian countries, Japan and Korea, for examples, have built appropriate breast cancer risk assessment tools as well. However, China is still in the stage of exploration. Besides, it is fortunate that more and more people are turning their eyes on the use of breast cancer susceptive SNPs for population risk prediction and subsequently this kind of detection has its own market recently. Therefore, there is no doubt that an ideal assessment tool will be beneficial for us to find high risk individuals earlier and make reasonable strategy to use medical resource.With the incidence of breast cancer is increasing recently in our country, it is necessary and vital to develop a breast cancer assessment model fit to Chinese women, which will be useful for screening high risk population and taking more reasonable measures to control breast cancer. Currently, we are still in the exploratory stage in this matter, and related studies and SNP data are limited compared to foreign countries.We first conducted the first phase selecting SNP loci in Chinese population to provide the data and lay a solid theoretical foundation for breast cancer risk assessment model. In order to increase the effectiveness of inspection, based on the existing domestic and international research results, we selected SNPs which are positive loci in GWAS to verify in Chinese Han women. Genome-wide association studies(GWAS) is a method of searching the genome for small variations, called single nucleotide polymorphisms or SNPs, that occur more frequently in people with a particular disease than in people without the disease. GWAS represent a promising way to study complex diseases, detect the SNP among patients and controls in the range of genome-wide and campare the frequency distribution between the two groups. This way identifys all of the variant allele frequency, unlike candidate gene strategies, which needs to pre-suppose some gene as a candidate gene. And GWAS studies have found a number of genes and chromosomal regions not previously found, and provided more clues to the pathogenesis of complex diseases.Its basic idea is the same with the classic case-control design, that is, assuming that a SNP is associated with the disease, in theory, SNP allele frequencies of the cases should be higher than that of the controls. Then test the hypothesis by hypothesis testing.All of these known genes,such as BRCA1/BRCA2, account for only25%of the familial aggregation cases, suggesting that most of the familial risk of BC can plausibly involve a combination of multiple low-penetrance susceptibility alleles, each conferring a small effect on BC risk. According to this model defined ’polygenic’, proposed to explain the genetic susceptibility to BC, a large number of low-risk variants occur with high frequency in populations, therefore, it may have a multiplicative effect in determining the overall risk of disease. A significant part of polygenic contribute to low-penetrance susceptibility may rise by non-conservative missense mutations in evolutionarily conserved domains. In recent years the research of low-penetrance allelic variants was conducted mainly through GWAS. These studies use a large number of common genetic single nucleotide polymorphisms (SNPs) to identify associations with disease that rely upon patterns of linkage disequilibrium (LD) in the human genome. The power of GWAS is to evaluate the association of genetic variants at different loci on different chromosomes (LD) in large series of cases versus controls, analyzing a panel of hundred thousand SNPs simultaneously, to identify new alleles of susceptibility to BC. These GWA studies therefore provide a powerful tool to identify novel markers for susceptibility and prognosis of disease. In the GWA studies the accumulation of a large number of data is crucial. Houlston and Peto,(2004) have estimated the number of cases required to identify low-penetrance alleles conferring a relative risk of two both in an unselected population and in families with first-degree relatives affected. In an unselected population the identification of a susceptibility allele with a frequency of5%requires over800cases. In the same population, the identification of a susceptibility allele with a frequency of1%requires over3700unselected cases, whereas about700would be enough if three affected families are selected.Therefore, GWAS needs a large number of samples, genotyping costly, the task of the genetic statistical analysis is not only to identify SNPs related to several complex conditions from the hundreds of thousands of SNPs,but also strictly control errors,such as potential false-positive probably as a result of mixed population, type I error expansion caused by multiple comparion the expansion and many other issues, screening out real disease-related sequence variation within the genome from mass positive SNPs loci. High-quality repeat research can help us make the right judgments. Duplication of a research is necessary guarantees to ensure that we find what real association with the disease is. when the association with a desease has not been repeated, there were three possibilities in theory:firstly, a true false-positive association was correctly not repeated; secondly, a real association has not been replicated in follow-up study of low detection performance; Thirdly, a true association exists in a crowd, due to the genetic heterogeneity of complex diseases,that is, because of genetic and environmental factors association can not be repeated back in another crowd. For these reasons, high-quality repeat can help us make the right judgments. One way to repeat the study is to directly analyze the joint of two or several research groups, so through a multitude of samples researchers can improve test performance and the probability of the SNP related to diseases.This study tested and verified43SNPs of GWAS in Guangdong,Nanchang and Chongqing han women, and we analyzed four parts data:The first part, according to case-control design, we analyzed the joint of Guangdong, Nanchang and Chongqing samples, and6SNPs were statistical significance; the second part, we performed the analysis whether there are differences between cases and controls in Guangdong Han women, and received eight SNP loci whose genotype frequencies are differently scattered between case and control groups; statistical analysis was done in Nanchang Han women, and wo obtained one protective SNP and one dangerous; We picked out two SNPs associated with breast cancer suitable to Chongqing Han women. Wiped out two SNPS rs7895676and rs2981575not conforming to Hardy-Weinberg equilibrium,linkage disequilibrium (LD) and haplotype analyses were performed with SNPs rs1078806, rs2981579, rs1219648, rs2420946, rs2981582in FGFR2. What we did is to lay a foundation for building breast cancer assessment model.We seleted the positive points and negative SNPs on the genes closely related to the incidence of breast cance to test and verify these locis in Shandong Han women. The data analysis is divided into two parts:First, the Shandong Han women were analyzed; Second, two large samples two populations Shandong and Guangdong data were analyzed together.Methods:Preliminary validation1. Collection of study subjects Blood samples from Breast cancer female patients and healthy females in three areas Guangdong, Nanchang and Chongqing were collected according to case-control design. Meanwhile, clinical data were organized. We extracted DNA from blood samples with BloodDNA kit (Tiangen) before storage at-70℃。2. Selection of SNPs SNPs were picked out from some published genome-wide association studies.3. Assay design and synthesis4. Detection of SNPs We genotyped the selected SNPs on genomic DNA of the DNA storage at-70℃before using primer extension on Sequenom MassARRAY-IPLEX platform.5. Analysis of SNPs Statistical analysis was done with online website http://bioinfo.iconcologia.net/SNPstats in four parts.6. LD and haplotype analyses linkage disequilibrium (LD) and haplotype analyses were performed with the software hapioview.Further validation of susceptibility locis1. According to reports,select genes strongly associated with breast cancer, we refer to the results above and pick out several SNPs to test and verify in Shandong Han women.2. Data analysis First, the Shandong Han women were analyzed; Second, two large samples two populations Shandong and Guangdong data were analyzed together, excluding the impact of the small sample size.Results43SNPs were picked out at last. After the test and statistical analysis of these SNPs in Chinese Han women, we found that rs999737had no polymorphism; its basic genotype is CC. Firstly, we selected11SNPs that may be associated with Chinese Han women:1) six SNPs show statistically significant differences between case and contros groups when studied the joint, including rs2981579(P=0.029), rs4784227CP=0.0069), rs4973768(P=0.038),rs2046210(P=0.0001), rs8051542(P=0.039) and rs3734805(P=0.0006);2) in Guangdong Han women, Statistical analysis was done and eight SNPs are associated with breast cancer, and they are SNPS not completely different from these in the the joint rs4784227(P=0.0003), rs16886165(P=0.024), rs3757318(P<0.0001), rs2046210(P=0.0008), rs8051542(P=0.017), rs13387042(P=0.04), rs1978503(P=0.032), rs3734805(P=0.0041);3) one protective SNP and one dangerous SNP were identified in Nanchang population;4) that rs4973768(P=0.041) and rs2046210(P=0.023) are relevant to breast cancer is fit in Chongqing Han women. Among these results, we found that the association between rs2046210and breast cancer is strongest. LD analysisi shows that rs2981579and rs1078806exhibited strong LD (D’=0.997, r2=0.453) and that rs2420946and rs2981582also exhibited strong LD (D’=0.958, r2=0.701). The frequencies of the TTACC and TTGTC haplotype of rs2981579, rs1078806, rs1219648, rs2420946and rs2981582differed significantly between the two groups, and P value were0.02and0.0066respectivly. Further,we verify that:1) in the Shandong population, the locus rs2046210(P=0.05), rs3734805(P=0.037), rs3803662(P=0.033), rs4784227(P=10-4) and rs12443621(P<0.0001) are statistically significantly different between cases and control group;2) to exclude the impact of small sample size, Guangdong and Shandong unite analysis find that the locus rs889312(P=0.018), rs16886165(P=0.012), rs3734805(P=6×10-4), rs4784227(P<0.0001) and rs2046210(P=2×10-4) are potential breast cancer susceptibility locis.Conclusion43SNPs were picked out at last. Fourteen of these SNPs were validated as SNPs possibly associated breast cancer in Han Chinese women. Rs3734805and rs2046210located on the gene ESR1and rs4784227located on the gene TOX3are closely related to risk of breast cancer in Chinese Han women, what association between rs2046210and breast cancer is the most obvious.And we also found out that genetic polymorphism, frequency distribution and disease susceptibility loci are different in different races or in different populations of one race. |
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