1.Association Study Of Single Nucleotide Variants With The Risk Of Prostate Cancer 2.Identification Of Novel Fusion Genes Of Prostate Cancer In Chinese

Part 1 Association Study of Single Nucleotide Variants with the Risk of Prostate CancerSection 1 Systematic meta-analyses of gene-specific genetic association studies in prostate cancerObjectives To access the correlation between gene-specific single nucleotide variants (SNVs) and prostate cancer (PCa) risk using meta-analysis method.Materials and methods Journal articles on the association between single nucleotide variants (SNVs) and PCa risk were identified from PubMed、EMBASE and Cochrane Library databases published between August 1,1990 and August 1,2015.Articles were selected with inclusion/exclusion criteria. Information from all available studies was extracted blindly and independently by two authors. Comprehensive meta-analysis version 2.0 software was used for the meta-analysis. Q statistic was performed and subgroup analysis was conducted to expore the source of heterogeneity. Effect size was pooled using Mantel-Haenszel fixed-effect model or DerSimonian and Laird random-effects model, and the risk of PCa was assessed by calculating the pooled odd ratio (OR) and the 95% confidence interval (95% CI). Ethnicity was stratified for the subgroup analysis. Sensitivity and cumulative analysis were conducted to evaluate the quality and consistency of the results. The potential publication bias was measured using the Egger’s regression procedure and funnel plot were performed. If publication bias existed, Duval and Tweedie’s trim and fill procedure was used to adjust for it. Enriched signaling pathways and biological processes were performed by Gene set enrichment analysis software.Results After screening over 40,000 titles and abstracts,560 papers which reported 66 SNVs in 51 different genes were finally included for the meta-analyses. The total of sample size involved in these meta-analyses was 1,002,493.The number of independent studies ranged from 3 to 33.Across 66 meta-analyses, a total of 20 genetic variants involving 584,100 subjects in 19 different genes (KLK3, IGFBP3, ESR1, SOD2, CAT, CYP1B1, VDR, RFX6, HNF1B, SRD5A2, FGFR4, LEP, HOXB13, FAS, FOXP4, SLC22A3, LMTK2, EHBP1 and MSMB) exhibited significant association with prostate cancer. The average summary OR was 1.33 (ranging from:1.016-3.788) for risk alleles and 0.838 (ranging from 0.757-0.896) for protective alleles. Of these positive variants, FOXP4 rs1983891, LMTK2 rs6465657 and RFX6 rs339331 had not been previously meta-analyzed.Conclusions This study have performed a comprehensive estimation of the genetic association between population-based gene-specific SNVs and PCa using currently available data. All meta-analyses yielded twenty significant associations, but the bulk of their genetic effects were small or modest. Thus, the interpretation of these positive results should be cautious. Further analyses with sufficient power and investigations of the potential biological roles of these genetic variants are needed.Section 2 Association between single nucleotide variants and the risk of prostate cancer among Chinese Han populations:A case-control studyObjectives To explore associations between three single nucleotide variants (SNVs) and prostate cancer (PCa) risk among Chinese Han populations.Materials and methods 826 PCa patients and 975 age-matched healthy men were analysed retrospectively.Clinical records of the subjects were collected and genomic DNA was extracted from peripheral blood leucocytes by phenol chloroform method. The fragment containing variants was amplified by PCR with fluorescent-labeled primers. Genotyping of the SNVs was performed using high-resolution melt (HRM) and the results were verified by Sanger sequencing method. The genotype frequencies for SNVs between PCa group and control group was compared.The associations between risk allele and age, PSA, Gleason score, TNM of PCa patients were also evaluated by Logistic Regression. Pearson chi-square test was used to compare genotype frequencies between the two groups. The odd ratios (OR) corresponding to 95% confidence interval (95% CI) were calculated. A P value<0.05 was considered statistically significant. Statistical analysis was carried out using the PLINK V1.02 and SPSS 16.0. Comprehensive meta-analysis version 2.0 software was used for the meta-analysis of association studies.Result A total of 1445 subjects with full data were included in the final analysis,504 in the PCa group and 941 in the control group. There was no significant difference of age between PCa group and control group (P>0.05). The genotype frequencies for SOD2 rs4880 between PCa group and control group were exhibited significantly in recessive model (OR=2.929,95%CI=1.56-5.51, P=0.0005). The genotype frequencies for MPO rs2333227 between PCa group and control group were revealed significantly in Dominant model, (OR=1.286,95%CI=1.03-1.61, P=0.029), The allele frequencies for MPO rs2333227 between PCa group and control group were significant in Allelic model, (OR=1.268,95%CI=1.04-1.55, P=0.019), There was no statistical difference in the frequency distribution of allele and genotype for LEP rs2167270. However, no significant associations were detected between SNVs and age, PSA and tumor stage within PCa group (P>0.05).Conclusions The SOD2 rs4880 C>T SNVs were associated with PCa risk among Chinese Han populations. T allele may contribute to increase the susceptibility of PCa. the protection of T allele for MPO rs2333227 is still need to be confirmed in Chinese prostate cancerPart 2 Identification of Novel Fusion Genes of Prostate Cancer in ChineseObjectives To screen and identify new fusion genes of prostate cancer in Chinese preliminary.Materials and methods Total RNA of 9 paired prostate cancer tissues and adjacent normal tissues from Northern Chinese Han men were extracted and reverse transcription were performed to obtain the cDNAand establish RNA-Seq library. Candidate fusion genes of prostate cancer were screened by HiSeq 2000 and Soap bioinformatics analysis software. At last, novel fusion genes and forms were identified by RT-PCR and Sanger Sequencing.Result Fifth eight fusion genes were found through RNA-Seq in 9 paired prostate cancer tissues and adjacent normal tissues. About 57%(33/58) fusion genes only showed in prostate cancer tissues were treated by Soap bioinformatics analysis software. Three of four novel fusion genes(ETV3-CRBl, GTF2I-LIMK1 and REPS2-TXLNG) were identified by RT-PCR and Sanger Sequencing in TMPRSS2-ERG absent tissues.Conclusions Three novel fusion genes of prostate cancer were identified in Chinese.