Additional file 2: Table S1. of Health care professionals’ attitudes towards population-based genetic testing and risk-stratification for ovarian cancer: a cross-sectional survey

Comparisons between healthcare specialists’ ovarian cancer and genetics knowledge and self-efficacy to conduct a cancer risk consultation. Table S2. Comparisons between healthcare specialists willingness to offer all adult female patients genetic testing for ovarian cancer risk. Table S3. Willingness to discuss risk stratified interventions with patients. Table S4. Reasons for lack of willingness to discuss suggested interventions. Table S5. Reasons for lack of willingness to discuss suggested interventions (DOCX 31 kb

Additional file 3: of Awareness, knowledge, perceptions, and attitudes towards genetic testing for cancer risk among ethnic minority groups: a systematic review

Rank order of included studies based on quality assessment. The table presents the quality assessments for each study and comments on why studies were marked down. (DOCX 19 kb

Additional file 2: Table S1. of Impact of a decision aid about stratified ovarian cancer risk-management on women’s knowledge and intentions: a randomised online experimental survey study

Factor loadings for decisional conflict and anticipated decisional regret items; Table S2. Participants’ knowledge about genetics (‘genetic literacy’); Table S3. Participants’ knowledge about ovarian cancer and the PROMISE study in the sample overall. (DOCX 16 kb

Figure 1

<p><b>A.</b> Mutant read frequency in different samples. The patient's blood samples were all taken around the time of neuroblastoma diagnosis. Numbers of sequencing reads per sample are displayed in the top level. * p = 0.01, comparing mutant read count frequencies between samples PD9058b3 and PD9058b with Fisher's exact test. Differences between PD9058b2 and sample b/b3 are not significant (p>0.05). <b>B.</b> Capillary sequencing of control germline DNA (Reference sequence) and patient's blood samples extracted at three time points, showing very low level of adenine (black arrow). The guanine (black peak) dropped approximately between 8–17% relative to control, as given by the software, which would not usually be classed as significant when looking for heterozygous germline mutations. <b>C and D.</b> Immunohistochemistry to show strong nuclear staining p53 in neuroblastoma (C) and sarcoma NOS (D).</p

p-values of association (−log10 scale) with breast cancer risk in <i>BRCA2</i> carriers for genotyped and imputed SNPs in the <i>NEIL2</i> gene.

<p>SNP rs1466785 is indicated with a purple arrow and the best causal imputed SNPs, rs804276 and rs804271 are indicated with a red arrow. Colors represent the pariwise r². Plot generated with LocusZoom <a href="http://www.plosgenetics.org/article/info:doi/10.1371/journal.pgen.1004256#pgen.1004256-Pruim1" target="_blank">[42]</a> (<a href="http://csg.sph.umich.edu/locuszoom/" target="_blank">http://csg.sph.umich.edu/locuszoom/</a>).</p

Associations with breast and ovarian cancer risk for SNPs observed at p-trend<0.05 in stage II of the experiment.

a<p>Hazard Ratio per allele (1 df) estimated from the retrospective likelihood analysis.</p>b<p>Hazard Ratio under the genotype specific models (2df) estimated from the retrospective likelihood analysis.</p>c<p>p-values were based on the score test.</p>d<p>HR per allele of 1.69 and p-trend of 1×10⁻⁴ for <i>BRCA2</i> mutation carriers in stage I of the study.</p>e<p>HR per allele of 1.43 and p-trend of 0.01 for <i>BRCA1</i> mutation carriers in stage I of the study.</p>f<p>HR per allele of 1.30 and p-trend of 0.03 for <i>BRCA1</i> mutation carriers in stage I of the study.</p>g<p>HR per allele of 0.64 and p-trend of 0.057 for <i>BRCA2</i> mutation carriers in stage I of the study.</p>h<p>HR per allele of 1.25 and p-trend of 0.04 for <i>BRCA1</i> mutation carriers in stage I of the study.</p>i<p>HR per allele of 1.25 and p-trend of 0.058 for <i>BRCA2</i> mutation carriers in stage I of the study.</p>j<p>rs3093926 did not yield results under the genotype specific model due to the low minor allele frequency.</p><p>Complete description of results from stage I are included in Supplementary <a href="http://www.plosgenetics.org/article/info:doi/10.1371/journal.pgen.1004256#pgen.1004256.s002" target="_blank">Table S1</a>.</p><p>Highlighted in bold are those SNPs showing strongest associations with breast or ovarian cancer risk (p<0.01).</p