Additional file 1: Table S1. of Identification of coding and non-coding mutational hotspots in cancer genomes

The number of samples with 1000 or more valid mutations included in our final analysis, as well as information about tumour type and original publication for each sample. For the ICGC samples we give ICGC project codes and use this to categorise tumour type throughout this work. Although some project codes imply the same tumour type (e.g. LICA-FR and LINC-JP are both liver cancers) we treat these separately in case these cohorts might have different properties, either technical or biological. Table S2: Top ten non-coding, non-hypermutated regions in terms of recurrence score within each cancer type. Table S3: Top ten non-coding, non-hypermutated regions in terms of combined score within each cancer type. (PDF 196 kb

Additional file 2: Figure S1. of Identification of coding and non-coding mutational hotspots in cancer genomes

Log10 of total mutations per genome, ordered by median mutations within each tumour type. Figure S2: For comparison, we show the location of mutations (black arrows) within a recurrent CTCF binding site that was highlighted in a previous analysis [28]. Figure S3: We show recurrence score (plotted as log(score + 2)) plotted against GC content. Regions with mutations per patient > 1.2 are in orange, with recurrence score > 10 and mutations per patient < = 1.2 in black, and all others in purple. Figure S4: Recurrent TERT promoter mutations identified in our data set. The mutations occur at one of the previously identified bases, generating a de novo ETS binding site. Figure S5: PLEKHS1 recurrently mutated region that has previously been identified. We identify mutations at the same base position as previous analyses. Figure S6: UCSC browser image depicting a recurrently mutated region identified by our method. Mutations are depicted by black arrows. This region is flanked on the left by the gene MED16. Figure S7: Sequence logo depicting the MEF2A motif. Text above the logo is the reference sequence observed within the recurrently mutated region in the MED16 promoter. Mutated positions are depicted in red. Figure S8: UCSC browser image of a second recurrently mutated region identified by our method. Mutations are depicted by black arrows. Figure S9: Recurrently mutated region overlapping the miRNA MIR142. The region is highly conserved, as suggested by its inclusion among the top non-coding regions based on combined score. Figure S10: MIR142 reference aligned with the sequence of mature microRNA has-miR142-5p. Mutated positions are depicted in red. Figure S11: Recurrently mutation overlapping an intron of the gene MSRA. The mutations occur primarily at two neighbouring bases. Figure S12: UCSC browser image of a recurrently mutated region overlapping an intron of the gene PRIM2. Figure S13: Sequence logo depicting the FOXP2 motif. Text above the logo is the reference sequence observed within the recurrently mutated region in the PRIM2 intron. Mutated positions are depicted in red. Figure S14: UCSC browser image depicting a recurrently mutated region in an intron of the DNA repair gene RAD51B. This region is mutated specifically in breast cancer. (PDF 4081 kb

Germline single nucleotide polymorphisms in <i>ERBB3</i> and <i>BARD1</i> genes result in a worse relapse free survival response for HER2-positive breast cancer patients treated with adjuvant based docetaxel, carboplatin and trastuzumab (TCH) - Fig 3

<p>Reverse Phase Protein array analysis correlating differential expression and phosphorylation of proteins involved in either the A) AKT or B) MAPK pathway versus the presence or absence of the minor allele of the ERBB3 rs2229046 SNP. p-values <0.05 included on the graph demonstrate significantly differential protein expression between the presence of the reference allele or the presence of the minor allele and are corrected for multiple testing.</p

Germline single nucleotide polymorphisms in <i>ERBB3</i> and <i>BARD1</i> genes result in a worse relapse free survival response for HER2-positive breast cancer patients treated with adjuvant based docetaxel, carboplatin and trastuzumab (TCH)

<div><p>Breast cancer is the leading cause of cancer related deaths in women worldwide and is classified into subtypes based on the cancer’s receptor status. Of these subtypes, those expressing the human epidermal growth factor receptor 2 (HER2) receptor were traditionally associated with poor prognosis. Several advances have been made in the treatment of HER2-positive breast cancer, yet issues of resistance and poor response to therapy remains prevalent. In this study we explored the impact of HER-family and homologous recombination deficiency SNPs on response to patients who received TCH-based (docetaxel (T), carboplatin (C), and trastuzumab (H)) treatment versus those who received other treatment regimens. Using Cox regression analysis, we identified 6 SNPs that correlate with recurrence free survival in our patients and supported our findings using support vector machines. We also used reverse phase protein array analysis to examine the impact ERBB3 SNPs may have on both the PI3K/AKT and MAPK/ERK signaling pathways. Finally, using cell line models, we correlated SNP status with sensitivity to platinum based drugs and docetaxel. We found that patients on a TCH based regimen with the minor allele of the ERBB3 (rs2229046 and rs773123) and BARD1 (rs2070096) SNPs, were significantly more likely to relapse than those women who were not. Additionally, we observed that patients with these ERBB3 SNPs had shown elevated protein expression/phosphorylation of Src kinase, c-MET (Y1234/1235), GSK-3β (S9) and p27, indicating that these SNPs are associated with non-PI3K/AKT signaling. Finally, using cell line models, we demonstrate that the BARD1 SNP (rs2229571) is associated with greater sensitivity to both carboplatin and cisplatin. The BARD1 and ERBB3 SNPs can potentially be used to determine those patients that will have a worse response to TCH based treatment, an effect that may arise from the SNPs impact on altered cellular signaling.</p></div

The prognostic role of RNF8-T448T SNP in TCH versus non-TCH treated primary tumours (n = 157).

<p>The blue, red and green lines represent the samples with the wild type (reference), heterozygous and minor alleles respectively. Kaplan Meier estimates where RFS is the survival endpoint (HR = 12.42 (2.00–77.19) p = 0.01) in non-TCH treated patients versus no-significant impact in TCH treated patients.</p

List of SNPs including Gene ID, accession number, mutant allele frequency and haplotype details which were detected by high depth next generation sequencing and selected for further analysis.

<p>List of SNPs including Gene ID, accession number, mutant allele frequency and haplotype details which were detected by high depth next generation sequencing and selected for further analysis.</p

Impact of HER-family and HRD SNPs on relapse free and overall survival of HER2-positive BC patients who have received either TCH based regimen or a non-TCH based regimen as part of their therapeutic regimen (n = 157).

<p>Impact of HER-family and HRD SNPs on relapse free and overall survival of HER2-positive BC patients who have received either TCH based regimen or a non-TCH based regimen as part of their therapeutic regimen (n = 157).</p

Metrics from the Support Vector Machine trained on the patient cohort using cross validation.

<p>Metrics from the Support Vector Machine trained on the patient cohort using cross validation.</p

Summary of patient characteristics used in the RPPA analysis (<i>n</i> = 60).

<p>Summary of patient characteristics used in the RPPA analysis (<i>n</i> = 60).</p

Analysis of the differential sensitivity of HER2-positive breast cancer cell lines to the platinum drugs cisplatin and carboplatin.

<p>We correlated the presence or absence of the minor allele of HER-family or BARD1 versus the GD₅₀ to either drug. GD₅₀ values were taken from the GDSC cell line analysis database [<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0200996#pone.0200996.ref021" target="_blank">21</a>]. p-value of <0.05 indicates a significant p-value after multiple testing correction.</p