Sequenom Massarray iPLEX single nucleotide polymorphism genotyping

2.6.1. Study population

The study was performed on 871 DNA samples isolated from blood of women who entered the SCOTROC I clinical trial (provided by the Scottish Gynaecological Clinical Trials Group), 1473 samples from postmenopausal Danish women aged 60-84 without cancer (provided by Professor

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Philippe Froguel, Imperial College London) and DNA samples isolated from ovarian cancer cell lines. All participating women signed an approved consent form, and the study was carried out in accordance with the Helsinki Declaration II and the European Standards for Good Clinical Practice. The demographic characteristic of the populations are presented in Chapters 3 and 4.

2.6.2. SNP selection and assay design

HapMap Phase II database and HaploView 3.32 software were used to generate a list of 77 tagging SNPs selected across the region covering predicted promoter and all WWOX exons (including their flanking intronic sequences) corresponding to the only observed protein isoform with minor allele frequency (MAF) of >0.02 (or MAF of >0.01 in the regions, where previous associations with ovarian cancer clinicopathological features were observed) and linkage disequilibrium (LD) of r2>0.8 with other SNPs in the LD bin. The list was further supplemented with a list of 6 non-tagging candidate SNPs including coding non-synonymous polymorphisms or SNPs previously associated with ovarian cancer clinicopathological features (described in Chapter 3). Full rationale for SNP selection is presented in Chapter 3. For each of the SNPs 200 bp genomic sequence centred on the polymorphism was downloaded from the Ensembl Genome Browser website (www.ensembl.org/biomart) and MassArray Assay Design Software was used to design multiplex Sequenom MassArray assays (reported additional variation within the 200bp sequences adjacent to the assay SNPs was marked and excluded from the primer design). Four SNPs failed in the assay design because there was too high primer potential for dimer or hairpin formation or interference with other primers. Low multiplicity assay (4 SNPs) were not run to minimise the costs. Because of assay design issues, 69 tagging SNPs and 6 extra candidate SNPs were eventually run. I appreciate the help of Stephen Clark from Section of Genomic Medicine, Imperial College London, with running the primer design software.

2.6.3. Genotyping

SNP analysis was carried out using Sequenom MALDI-TOF mass spectrometer. 28-, 25-, and 22- plex PCR reactions were carried out in 384-well plates according to Sequenom protocols. The PCR and extension reaction primers (Appendix 3) were obtained from Sigma-Genosys and Invitrogen, based on output from Sequenom assay design software. PCR was carried out using 1.25 x Qiagen

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HotStar buffer, 3.5 mM Mg2+, 0.5 mM dNTPs, 100 nM primer, and 0.5 U Qiagen HotStar Taq polymerase (Qiagen #203205) (1 U for 28-plex PCR reaction) with 5 ng DNA in a 5-µl reaction. The concentration of the extension primers added to the extension reaction cocktail were adjusted according to Sequenom High iPlex Gold protocol. The plate was further processed (single nucleotide extension reaction and MALDI–TOF <matrix-assisted laser desorption/ionization time-of-flight> mass spectroscopy) at the Section of Genomic Medicine laboratory, Imperial College London, by Marlene Attard. The spectra were analyzed using MassArray Typer 3.4 Analyzer software. Assays with call rates lower than 90% were not carried forward to further analysis. Three SNPs (rs442608, rs383362 and rs441004) were genotyped in duplicate in around 300 samples each as a technical replicate and the average reproducibility was 99.8%.

2.6.4. Scotroc1 and Danish women population genotyping studies: statistical analysis

All analyses were performed with PASW Statistics 18.0 (formerly SPSS) and Microsoft Excel. Presented p values are 2-sided where applicable.

2.6.4.1. Statistical analysis for the validation of the SNPs from the original study in the Scotroc1 population

SNPs were tested for Hardy-Weinberg equilibrium by Fisher’s Exact tests. Univariate test for independence from genotype were performed for rs4887937 versus histology (chi-squared test), rs4887937 and rs2303191 versus grade (Fisher’s exact test) and rs11545028 versus age (1-way Anova). Assessment of rs383362 as prognostic factor independent of the clinical factors for progression-free survival was performed using a multivariate Cox proportional hazards regression model. The progression free survival analysis was conducted by Manuela Zucknick (Imperial College) and Jim Paul (University of Glasgow).

2.6.4.2. Statistical analysis of the associations between WWOX variation and ovarian cancer phenotypes in Scotroc1 clinical trial patient population

SNPs were tested for Hardy-Weinberg equilibrium by Fisher’s Exact tests. Univariate tests for independence from genotype (Fisher’s exact) were performed for histology, grade (1 and 2 versus 3), stage (1 and 2 versus 3 and 4), CA125 response and clinical/radiological response (complete and

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partial reponse versus stable and progressive disease) and chemotoxicity: neurotoxicity (grade 1 versus 2-4), serious hematologic toxicity (docetaxel patients) and gastrointestinal toxicity. Markers with strongest evidence of association for each trait where re-assessed with chi-square linear-by- linear association test, an approximation of Cochrane-Armitage test for trend in PASW/SPSS software. Univariate overall and progression-free survival analysis was performed with log-rank test.

2.6.4.3. Statistical analysis of the associations between WWOX variation and bone metabolism parameters in the population of Danish postmenopausal women

SNPs were tested for Hardy-Weinberg equilibrium by Fisher’s Exact tests. Assessment of the contribution of covariates (BMI, number of years from menopause) and factors (current and ever smoking status, hormone replacement therapy and osteoporosis treatment), to the phenotypes of interest was carried out using multivariate ANCOVA. Subsequently, for univariate ANCOVA analysis of each phenotype in turn, only those covariates and factors with p-values of less than 0.1 were included with the genotypes for analysis. The analysis strategy was proposed and the analysis subsequently supervised by Dr Andrew Walley (Section of Genomic Medicine, Imperial College London).

2.6.4.4. Statistical analysis of the associations between WWOX variation and BMI as well as height in the population of Danish postmenopausal women

Assessment of the contribution of a covariates (number of years from menopause) and factors (current and ever smoking status, hormone replacement therapy and osteoporosis treatment), to BMI (body mass index) and height was carried out using multivariate ANCOVA. Subsequently, for univariate ANCOVA analysis of BMI and height, only those covariates and factors with p-values of less than 0.1 were included with the genotypes for analysis.

2.7. Evaluation of putative splice site variation in an in vitro assay with pSpL3 exon trapping