Chapter1Current Status Of Molecular Mechanisms Of Multidrug Resistance In Epithelial Ovarian Cancer

The treatment of epithelial ovarian cancer is largely based on cytoreductive surgery plusplatinum-based combination chemotharapy.The majority of advanced patients respond well tothe combination chemotharapy,but often progress to be resistant and even multidrugresistant(MDR) finally,leading to treatment failure and even death for them.Numorous studies have evidenced clinicopathological factors includinghistology,residual diameter(RD),cell grade and FIGO stage may lead to differentialchemotherapy afficacy.However the5-year overall survival(OS) of the patients treated bythe protocol based on these clinicopathological factors has basically lingered behind since the90s of last century.Molecular studies have evidenced epithelial ovarian cancer belongs to a heterogeneousdisease.Significant classical pathways such as increased drug efflux, enhanced metabolicdetoxification and aberrent damage repair,and other pathways such as second mutation ofcertain genes and changed cellular microenvironment have implicated in the mechanisms ofMDR,and involved abrrent genetic variation,protein expression and network regulation ofmany genes such as MDR related super family,cytochrome p450family.Predicting anddiagnosing chemotherapy response of ovarian cancer patients using the differential geneticvariation and protein expression profiles has made success in some studies,but application inclincal practice has yet not arrived,and more researches are warranted in the future.Single nucleotide polymorphisms(SNPs) make up of more than90%of geneticvariations in genomic DNA,and associated with individual differential responses tochemotherapy in the past studies including MDR mechanism of epithelial ovarian cancer,though relative small samples and few SNPs have largely made inconsistent results and negative results in independent replication studies in the latter.Some authors suggestedincreasing samples and detecting more SNPs to overcome the dillema. High-throughput,rapiddetection and cost effective whole-genome SNP arrays applied in detecting new cancersusceptibility locuses have made big success in large tumor samples and certein degree ofsuccess in drug response/toxic profiling researches of relative small samples in the past years.There are many reasons that bininformatic ways need be applied in the large dataprodouced by the high-throuput SNP arrays.Firstly,on one hand the demands foe processinglarge data and calculating speed dwarf the performance of common softwares such as SPSS orSAS.On the other hand analytic ways from diffrent perspectives may significantly influencethe final statistic results.With the development of bioinformation more and more softwaresand analytic methods can be implemented in genome-wide association study(GWAS),and it isvery important to select appropriate tools for use in our research.Seondly,functinal SNPs suchas those affecting splicing sites or can lead to amino-acids substitution are the key parts offuther replication studies,and also are needed be selected by the help of bioinformatictools.Finally,meta-analysis and bioinformatic analyses to the data from other researches alikemay compliment and cross-validate our statistic results. Objectivity This study aims to detect SNPs using genomic DNA from multiple groupsof ovarian tissues by high throughout whole genome-wide SNP arrays and explore significantmultidrug resistance related biological pathways and functional SNPs in epithelial ovariancancer(EOC) by gene-set enrichment pathway analysis(GSEA).Methods normal ovariantissue,benign ovarian cysadenoma,sensitive and resistant ovarian cancer consisting of50ineach group were used to extract genomic DNA.After determining concentrations andagarose gel electrophoresis,the DNA samples were used to genotype with The HumanOmniZhongHua-8SNP arrays by the protocol suggested by Illumina company.The rawintensity signals were converted to specific genotypes by the software of GenomeStudio.Thenthe genotyping data was preprocessed and filtered by different parameters to pass qualitycontrol with PLINK software.Allelic test was applied to get significant SNPs(p<0.05) fromthe statistical comparisons of four groups,i.e,normal group vs benign group,normal group vsmalignant group(sensitive plus resistant),benign group vs malignant group and sensitivegroup vs resistant group.After discarding the common SNPs in the first3comparisons,the restsignificant SNPs and their p values from sensitive group vs resistant were analyzed withgene-set enrichment pathway analysis (GESA) in the online website WebGestalt.Then thetransformed genes in WebGestalt were further used by DAVID for pathway analysis. Afterempirically keeping MDR related significant pathways(adjusted p<0.05by BH andFDR<0.05,respectively),12biological pathways were reserved.Next,these12pathways andthe included SNPs were cross-validated by the text mining tool of SciMiner and functionalSNPs were predicted by the online website SNPFUNC.Then the Selectome database was usedto predict base positions under positive selection for those MDR related genes.The PLINKsoftware was further used to calculate epistatic effect between SNPs and conduct multivariateanalysis and stratified analyses with clinicopathological parameters.Finally ROC were used toestablish SNP diagnosing model for predicting MDR in EOC.Results Twelve significantpathways such as focal adhesion were identified pertaining to multidrug resistance in EOC.Abatch of functional SNPs including rs2293347of the EFGR gene might affect the functions oftheir according genes through aberrant splicing or coding nonsynonymous amino acids,etc.Three SNPs including MRP1(rs4148356)、 TP53(rs1042522)and PDGFC（rs1425486）and ABC transporters plus focal adhesion were cross-validated by text miningand pathway analysis. SNPs such as rs111878422and rs2274223might play pivotal role inMDR through epistatic effect. The Selectome database demonstrated the base positions ofNo.237、291、296and298of the FYN gene were under positive selection.In the stratifiedanalyses many SNPs were shown to be related with MDR in different clinicopathologicalparameters.Finally we failed to establish a SNP-based diagnosing model for predictingMDR,however, the sensitivity of ROC showed the trend of increasing with the increase ofSNPs.Conclusion Through high through-out SNP arrays and bioinformatic analyses we haveobtained a number of multidrug resistance related biolgical pathways and functionalSNPs,which may be used to establish a SNP-based diagnosing model for predicting MDR ifconfirmed in further studies with more homogeneous samples. Objective To explore MDR related biological pathways and functional SNPs usinggene-set enrichment pathway analysis.Methods The SNP array data (No. GSE13813) fromGEO(Gene Expression omnibus) was corrected for population stratification with the principle component analysis (PCA) after quality control, and then analyzed by linear regression usingthe PLINK software to get significant single nucleotide polymorphisms (SNPs)(p<0.05)between multidrug resistant and sensitive advanced epithelial ovarian cancer (EOC) patientstreated with platinum plus paclitaxel chemotherapy. The differential SNPs were then used forpathway analysis according to the same protocol in chapter2.Results3pathways includingGap junction, Tight junction and Phosphatidylinositol signaling system might be associatedwith drug resistance in EOC. Besides,4functional SNPs(rs1013986、rs2672734、rs5008332and rs700626)which were in linkage disequilibrium with the SNPs in the3pathways might bealso in relation to drug resistance in EOC.Conclusion Theses pathways and functional SNPscould be included for further analysis,which might help establish SNP-based diagnosingmodel if confirmed. Objective This paper aims to explore the relationship between the excision repaircross-complementation group1(ERCC1)19007C/T polymorphism and response ofplatinum-based combination chemotherapy in epithelial ovarian cancer(EOC) through pooledanalysis.Methods After searching the electronic databases of Pubmed,Embase and Wanfang,7 eligible papers including total879EOC patients were retrieved for meta-analysis according toinclusion and exclusion criteria. The Stata software(11.0version) was used to explore therelationships between different genotypes of19007C/T polymorphism and chemotherapyresponse.Funnel plots plus Begg test and Egger test were applied to assess possiblepublication bias.Results Pooled analysis of subgroups according to different sample sourcesdemonstrated that patients with CT genotype might respond better to chemotherapy than thosewith TT genotype by genotyping with blood sample source(OR=6.52，95%CI1.74-24.42).Funnel plots plus Begg test and Egger test（PBegg=0.089; PEgger=0.296） didn’tshow significant publication bias.Conclusion The ERCC119007C/T polymorphism could beincluded in further validation experiment,and might help establish SNP-based diagnosingmodel for predicting MDR in EOC cancer patients.