Supplemental Figure legends

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1 Supplemental Figure legends Supplemental Figure S1 Frequently mutated genes. Frequently mutated genes (mutated in at least four patients) with information about mutation frequency, RNA-expression and copy-number. Tumors from NPD patients are shown to the left and tumors from PD patients to the right. Supplemental Figure S2 Analysis of differences and changes in mutations types. Only patients having paired tumors were included in the analysis (14 NPD and 15 PD patients). (A-D), Diagrams showing the proportions of the six mutation types in the first and last tumors for the NPD patients (A), the PD patients (B), the smokers only (C) and the combined former and non-smokers (D). In cases where more than two tumors were available from one patient the first resected and last resected tumors were used. The bars represent lowest, highest and median proportions across patients. (E) Differences in intra patient mutation type proportions. Proportions are calculated as the mean of absolute change across NPD and PD patients. (F) Differences in intra patient mutation type proportions. Change is calculated as the mean of Tumor2-Tumor1 across NPD and PD patients. In cases where more than two tumors were available from one patient, the change in proportion was calculated between tumors having highest difference in stage. Supplemental Figure S3 Mutational signatures based on trinucleotide contexts The mutational context is represented for each sample and each patient. Each bar represents the relative ratio of a given mutation in a given trinucleotide context (dark color when including only cat 1 SNVs and light colors when including all SNVs called). Supplemental Figure S4 Contributions and comparison of most prevalent mutational signatures across samples Contributions of signatures 1A, 1B, 2, 6, 12, 13 and 2+13 across all samples. Samples from NPD patients are shown in green and samples of the PD patients are shown in blue. Signatures 2 and 13 are a hallmark of APOBEC enzyme activity and a plot of signature 2+13 is included to represent the combined APOBEC effect. 13

2 Supplemental Figure S5 Comparisons of contributions of most prevalent mutational signatures from initial tumor to most recent tumor in NPD and PD patients Signatures 1A, 1B, 2, 6, 12, 13, 2+13 plotted against Tumor 1(initial tumor) and Tumor 2 (most recent tumor) are shown as bar plots. For patients having more than two tumor samples, the tumor with the highest stage is selected as tumor 2. Samples from NPD patients are shown in light green (tumor 1) and dark green (tumor 2). Samples from PD patients are shown in light red (tumor 1) and dark red (tumor 2). Supplemental Figure S6 Comparison of mutation rate and APOBEC score. (A) Correlation plot of APOBEC score (Cat 1-2) versus the mutation rate (cat1+2 SNV/Mb) for all samples. (B) Relationship between APOBEC score (Bars, primary Y-axis; Cat 1-2) and the mutation rate (Black lines, secondary y-axis) for tumors from NPD patients (green) and PD patients (red). Supplemental Figure S7 APOBEC enzymes expression Bar plots displaying gene expression of Apobec1, Apobec2, Apobec3a, Apobec3b, Apobec3b-as1, Apobec3c, Apobec3d, Apobec3f, Apobec3g, Apobec3h and Apobec4 for the initial Ta tumors from NPD patients (green bars) and PD patients (blue bars). Supplemental Figure S8 Comparison of deleterious mutations in different sub-groups. (A) Comparison of the initial Ta tumors from each group (omitting patients with primary invasive tumors) identified ten early drivers of progression (LRP1B, RYR3, PCDHGA12, TLN1, RP1L1, BBX, ZNF717, ADAMTS18, TENM1 and SSPO) only mutated in Ta tumors from the PD group. Of these LRP1B and RYR3, both related to cancer cell migration, were mutated in 26% (4/15) of the PD patients (P<0.05). The LRP1B gene is often deleted in bladder cancer and is thought to be a tumor suppressor gene (13). Recently, LRP1B was found to be a possible cancer driver gene in clear cell kidney carcinoma, present as a subclonal mutation (9). (B) Comparison of the initial Ta tumors from NPD patients versus the T1 or T2 tumors from PD patients (most recent tumor) identified 14 genes that were only mutated in the PD group. The most frequently mutated gene, TRRAP, was mutated in four (24%) of the PD samples and is involved in MYC signaling (14). TRRAP encodes a kinase that is part of several histone acetyltransferase (HAT) complexes e.g. the TIP60 complex (14), which is involved in bladder cancer (15). Loss of TRRAP activates the WNT pathway and is frequently seen in melanomas (15). (C) A comparison of paired Ta tumors from NPD patients revealed frequent mutations in PIK3CA, RBM10, KDM6A, RANBP2 and FGFR3 were early events present in the initial Ta, whereas mutations in MKI67, CCDC168, MIA3 and OPN1LW primarily occurred late in tumorigenesis of recurrent Ta tumors. (D) Finally, we compared metachronous tumors from PD patients and we found that genes like RYR3, RP1L1, KDM6A, FGFR3, PIK3CA and ZNF717 were frequently mutated in the initial tumor. Interestingly only 35% (7/20) of the mutations in these genes seemed to be retained in the progressed samples. However, visual inspection (SNVs only) resulted in detection of additional recurrent low frequency SNVs (marked by gray) in early (n=7) and late PD samples (n=8), increasing the retained mutations to 50% (10/20) in 14

3 these genes. In contrast, mutations in ADRA2B and TRRAP are predominantly present in the progressed samples. However, after visual inspection, 100% (3/3) of ADRA2B and 33% (1/3) of TRRAP mutations were observed in the initial tumor, at very low frequency (marked by an orange box). Supplemental Figure S9 Disease evolution inferred by phylogenetic tree analysis for patients with two tumors analyzed. The total number of mutations and the percentages of SNVs belonging to each of the branches are shown. Tumor suppressor genes, oncogenes and bladder intogen genes with Tier 0-1 SNVs are highlighted on the right side (ancestral: black font; sample-specific: green font for the first tumor and blue font for the second) together with their clonal status as defined in (9) (red: clonal, blue: subclonal and grey: not defined). Genes potentially actionable using FDA approved drugs are marked with an asterisk. The time-scale indicates the time between the tumor removals. Supplemental Figure S10 Mutational heat maps for patients with three or more tumor samples analyzed For each patient with three or more tumor sample analyzed, a heat map of presence (green) or absence (white) of mutations (left) and a heat map of allele frequencies (right) are shown. Supplemental Figure S11 Clonality status of all Cat 1 Tier 0-1 mutations found in NPD patients. For each sample, the cancer cell fraction (CCF) was estimated using information about the number of reads for the reference and alternate alleles, an estimation of the cellularity and the copy number status of the region harboring the mutation. The mean and confidence intervals from all mutations called in Cat1 Tier 0-1 are plotted. A mutation was called clonal and colored in red if the upper limit of the confidence interval was above If not, it was called sub-clonal and colored in blue. Supplemental Figure S12 Clonality status of all Cat 1 Tier 0-1 mutations found in PD patients. For each sample, the cancer cell fraction (CCF) was estimated using information about the number of reads for the reference and alternate alleles, an estimation of the cellularity and the copy number status of the region harboring the mutation. The mean and confidence intervals from all mutations called in Cat1 Tier 0-1 are plotted. A mutation was called clonal and colored in red if the upper limit of the confidence interval was above If not, it was called sub-clonal and colored in blue. Supplemental Figure S13 List of genes with their clonality status in all samples from NPD patients. For NPD patients with two tumor samples analyzed, we show all Cat 1 Tier 0-1 mutations (defined by the gene they are affecting) in the phylogenetic tree context (Fig. 3). The genes in the ancestral branches are defined by a black font, the genes in the first sample branch by a green font and the genes in the second branch by a blue font. The clonal status is defined in the first column for the first tumor and in the second column for the last tumor: red for clonal, blue for sub-clonal and grey for not defined. 15

4 Supplemental Figure S14 List of genes with their clonality status in all samples from PD patients. For PD patients with two tumor samples analyzed, we show all Cat 1 Tier 0-1 mutations (defined by the gene they are affecting) in the phylogenetic tree context (Fig. 3). The genes in the ancestral branches are defined by a black font, the genes in the first sample branch by a green font and the genes in the second branch by a blue font. The clonal status is defined in the first column for the first tumor and in the second column for the last tumor: red for clonal, blue for sub-clonal and grey for not defined. Supplemental Figure S15 Correlation between allele frequencies estimated from exome-seq versus ampliconseq. All SNVs used to infer the subclonal populations are plotted. Overall we observed a very good correlation (correlation = 0.91) between the frequencies estimated in the ampliconseq data (x-axis) and in the exome-seq data (y-axis). The overall density is indicated by the red shading. Supplemental Figure S16 Subclonal populations inferred by PyClone in patients with two samples analyzed. For 17 patients with two tumor samples analyzed, the cellular prevalence of a selection of SNVs was inferred by PyClone and plotted (black dots). The overall density is indicated by the red shading and the name of driver genes (oncogenes, tumor suppressor genes or intogen genes) is written next to their cluster. Supplemental Figure S17 Subclonal populations inferred by PyClone in patients with three samples analyzed. For four patients with three tumor samples analyzed, the cellular prevalence of a selection of SNVs was inferred by PyClone and plotted (black dots). The overall density is indicated by the red shading and the name of driver genes (oncogenes, tumor suppressor genes or intogen genes) is written next to their cluster. Supplemental Figure S18 Subclonal populations inferred by PyClone in the patient with five samples analyzed. For one patient with five tumor samples analyzed, the cellular prevalence of a selection of SNVs was inferred by PyClone and plotted (black dots). The overall density is indicated by the red shading and the name of driver genes (oncogenes, tumor suppressor genes or intogen genes) is written next to their cluster. Supplemental Figure S19 APOBEC enzymes expression in tumor samples from patients with three or more metachronous tumor samples. Bar plots displaying gene expression of APOBEC1, APOBEC2, APOBEC3A, APOBEC3B, APOBEC3B-AS1, APOBEC3C, APOBEC3D, APOBEC3F, APOBEC3G, APOBEC3H and APOBEC4 for all samples from the six patients with three or more tumor samples analyzed. 16

5 Supplemental Table legends Supplemental Table 1 Clinical and histopathological information together with information on exome and RNA sequencing (A) Overview of clinical data for the 75 tumor samples included in the paired-whole exome sequencing set. (B) Summary of samples and clinical data. (C) Summary statistics on Paired-WES data set. (D) Summary statistics of RNA sequencing data. Supplemental Table 2 Mutations called by MuTect The table displays all mutations called by MuTect for all the samples annotated by SnpEff and associated categories, Cat 1 and Cat 2. Supplemental Table 3 Allele specific expression (ASE) (A) Differences in ASE between cancerous and normal bladder cells as a function of gene class. (B) Significant genes with a different ASE between cancerous and normal bladder cells. (C) Differences in ASE between initial Ta tumors from NPD versus PD patients as a function of gene class. (D) Significant genes with a different ASE between initial Ta tumors from NPD versus PD patients. Supplemental Table 4 Heat maps of mutations and gene expression for patients with three or more tumor sample analyzed. For each of the six patients with more than two metachronous tumors analyzed, we show a heat map of presence (green) or absence (white), a heat map with allele frequencies information and the gene expression values for the corresponding mutations. Supplemental Table 5 Mutations included in the 1530 amplicons target panel. (A) The 1800 SNVs included in the 1530 amplicons target panel. For each sample, information about the category of the call is given if the mutation has been called in this sample. (B) Summary statistic for the 1800 SNVs included in the 1536 amplicons target panel for all analyzed patients samples. The table includes alternative and reference call for both the amplicon sequencing and exome sequencing. (C) Comparison of SNV calls from WES and deep amplicon sequencing for patient 11. The table displays heat map, allele frequency of alterations for patient 19 calculated from the WES data. The reference and alternate allele counts from the SNV positions that were included on the targeted deep sequencing panel for this patient are shown to the right. This demonstrates that we can fully trust a negative SNV in the WES data as the ultra-deep sequencing do not pick up low frequency SNV not detected in the WES data. (D) All primer/probe position and sequence for 1530 amplicons. Supplemental Table 6 Potential therapeutic targets. All altered genes that are potential targets identified by search in the Drug-Gene Interaction database (DGIdb), the Target database, and the IntOGen database are listed 17

6 for each patient. The genes altered, the observed alterations, and the samples affected are shown. Additionally, IntOGen genes, oncogenes, or tumor suppressor genes are highlighted in green, red, and blue font, respectively. All FDA approved drugs for the given target are listed (identified by the DrugBank database). 18