Somatic mutation profiles as molecular classifiers of ulcerative colitis‐associated colorectal cancer

This is a self-archived version of an original article. This version may differ from the original in pagination and typographic details. Author(s): Title: Year: Version: Copyright: Rights: Rights url: Please cite the original version: CC BY 4.0 https://creativecommons.org/licenses/by/4.0/ Somatic mutation profiles as molecular classifiers of ulcerative colitis‐associated colorectal cancer © 2021 The Authors. International Journal of Cancer published by John Wiley & Sons Ltd on behalf of UICC. Published version Mäki‐Nevala, Satu; Ukwattage, Sanjeevi; Olkinuora, Alisa; Almusa, Henrikki; Ahtiainen, Maarit; Ristimäki, Ari; Seppälä, Toni; Lepistö, Anna; Mecklin, Jukka‐ Pekka; Peltomäki, Päivi Mäki‐Nevala, S., Ukwattage, S., Olkinuora, A., Almusa, H., Ahtiainen, M., Ristimäki, A., Seppälä, T., Lepistö, A., Mecklin, J., & Peltomäki, P. (2021). Somatic mutation profiles as molecular classifiers of ulcerative colitis‐associated colorectal cancer. International Journal of Cancer, 148(12), 2997-3007. https://doi.org/10.1002/ijc.33492 2021 CANCER GENETICS AND EPIGENETICS Somatic mutation profiles as molecular classifiers of ulcerative colitis-associated colorectal cancer Satu Mäki-Nevala 1 | Sanjeevi Ukwattage 1 | Alisa Olkinuora 1 | Henrikki Almusa 2 | Maarit Ahtiainen 3 | Ari Ristimäki 4,5 | Toni Seppälä 6 | Anna Lepistö 6 | Jukka-Pekka Mecklin 7 | Päivi Peltomäki 1 1 Department of Medical and Clinical Genetics, University of Helsinki, Helsinki, Finland 2 Institute for Molecular Medicine Finland (FIMM), University of Helsinki, Helsinki, Finland 3 Department of Education and Research, Central Finland Central Hospital, Jyväskylä, Finland 4 Department of Pathology, HUSLAB, University of Helsinki and Helsinki University Hospital, Helsinki, Finland 5 Applied Tumor Genomics Research Program, Research Programs Unit, University of Helsinki, Helsinki, Finland 6 Department of Gastrointestinal Surgery, Helsinki University Hospital and Helsinki University, Helsinki, Finland 7 Department of Sport and Health Sciences, University of Jyväskylä and Jyväskylä Central Hospital, Jyväskylä, Finland Correspondence Satu Mäki-Nevala, Department of Medical and Clinical Genetics, University of Helsinki, Helsinki, Finland. Email: [email protected] Funding information Academy of Finland, Grant/Award Numbers: 294643, 330606, 331284; HiLIFE Fellows; Jane ja Aatos Erkon Säätiö; Sigrid Juséliuksen Säätiö; Syöpäsäätiö Abstract Ulcerative colitis increases colorectal cancer risk by mechanisms that remain incompletely understood. We approached this question by determining the genetic and epigenetic profiles of colitis-associated colorectal carcinomas (CA-CRC). The findings were compared to Lynch syndrome (LS), a different form of cancer predisposition that shares the importance of immunological factors in tumorigenesis. CA-CRCs (n = 27) were investigated for microsatellite instability, CpG island methylator phenotype and somatic mutations of 999 cancer-relevant genes (“Pan-cancer”panel). A subpanel of “Pan-cancer”design (578 genes) was used for LS colorectal tumors (n = 28). Mutational loads and signatures stratified CA- CRCs into three subgroups: hypermutated microsatellite-unstable (Group 1, n = 1), hypermutated microsatellite-stable (Group 2, n = 9) and nonhypermutated microsatellite-stable (Group 3, n = 17). The Group 1 tumor was the only one with MLH1 promoter hypermethylation and exhibited the mismatch repair deficiency-associated Signatures 21 and 15. Signatures 30 and 32 characterized Group 2, whereas no prominent single signature existed in Group 3. TP53, the most common mutational target in CA-CRC (16/27, 59%), was similarly affected in Groups 2 and 3, but DNA repair genes and Wnt signaling genes were mutated significantly more ofteninGroup2.InLStumors,thedegreeof hypermutability exceeded that of the hypermutated CA-CRC Groups 1 and 2, and somatic mutational profiles and signatures were different. In conclusion, Groups 1 (4%) and 3 (63%) comply with published studies, whereas Group 2 (33%) is novel. The existence of molecularly distinct subgroups within CA-CRC may guide clinical management, such as therapy options. KEYWORDS colorectal cancer, Lynch syndrome, microsatellite instability, somatic mutation, Ulcerative colitis 1|BACKGROUND Inflammatory bowel disease, comprising ulcerative colitis (UC) and Crohn's disease, is associated with an increased risk of colorectal Abbreviations: CA-CRC, colitis-associated colorectal carcinoma; CCP, Comprehensive Cancer Panel; CIMP, CpG island methylator phenotype; CRC, colorectal carcinoma; LS, Lynch syndrome; MMR, DNA mismatch repair; MSI, microsatellite instability; MSI-H, high-degree microsatellite instability; MS-MLPA, methylation-specific multiplex ligation-dependent probe amplification; MSS, microsatellite-stable; UC, ulcerative colitis; VAF, variant allele frequency. Received: 2 November 2020 Revised: 15 January 2021 Accepted: 20 January 2021 DOI: 10.1002/ijc.33492 This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited. ©2021 The Authors. International Journal of Cancer published by John Wiley & Sons Ltd on behalf of UICC. Int. J. Cancer. 2021;148:2997–3007. wileyonlinelibrary.com/journal/ijc 2997 carcinoma (CRC). 1 UC-associated CRC (CA-CRC) develops in a multifactorial manner involving a complex imbalance of regulation and coordination of the human immune system, gut microbial composition and epithelial regeneration during the persistent inflammatory period. 1,2 Inflammation together with no mucosal healing predisposes to CA-CRC via inflammation-dysplasia-carcinoma sequence. 2 During inflammation-associated tumorigenesis, active inflammatory cells produce reactive oxygen species and reactive nitrogen intermediates, which induce mutations leading to genetic instability. 3 Cytokine production further enhances intracellular reactive oxygen species and reactive nitrogen intermediates in a malignant cell; moreover, it promotes epigenetic modifications that can accelerate tumor initiation by silencing DNA repair genes, for example. 3 Up to 35% of CRC risk can be attributed to genetic factors, and some 5% of CRC cases represent hereditary single-gene disorders. 4 Germline defects in DNA mismatch repair (MMR) genes MLH1,MSH2, MSH6 and PMS2, 5 or more rarely deletions in the 30end of EPCAM gene leading to hypermethylation of MSH2 gene promoter, 6 cause Lynch syndrome (LS), the most prevalent form of hereditary CRC. Heterozygous germline defects lead to reduced levels of functional MMR proteins, which increases the risk for early-onset cancers, primarily CRC and endometrial cancer. 7 CRC in LS often, but not always, develops via the adenoma-carcinoma sequence. 8 The emergence of de novo somatic mutations contributes to high levels of neoantigens, which are thought to result in immune activation and later, immune evasion. 9 Thus, in analogy to CA-CRC, immunological alterations and inflammation accompany LS-associated colorectal tumorigenesis from the outset. Recently, genomic analyses on cancers have revealed details of mutational processes and their timing in various cancers. Characterization of such events can be useful to understand molecular mechanisms of cancers and can help to determine plausible biomarkers for diagnostic and therapeutic use. In our study, we aim to determine the somatic mutational profiles and signatures for CA-CRC and compare the findings to LS-associated colorectal tumors, thereby covering two forms of earlyonset colorectal cancer with different etiologies, but with a strong immunological component as a common denominator. 2|MATERIALS AND METHODS 2.1 |Patients and samples The study material consisted of formalin-fixed, paraffin-embedded tissue specimens from UC patients developing CRC (CA-CRC, n = 27) and LS patients (verified carriers of pathogenic or likely pathogenic germline variants of MMR genes) developing colorectal tumors (adenomas with highgrade dysplasia, n = 10, and CRCs, n = 18). Besides tumor material, we had the patients' normal colon tissue or blood specimens available. All theLSpatientswererepresentedinthenationwideLynchSyndrome Registry of Finland. DNA was extracted using the nonenzymatic protocols, modified extraction protocol of the phenyl-chlorophorm method 10 and protocol described in Lahiri and Nurnberger 11 for formalin-fixed, paraffin-embedded and blood samples, respectively. 2.2 |Microsatellite instability analysis Microsatellite instability (MSI) was assayed using mononucleotide repeat markers BAT25 and BAT26 that are sensitive and specific markers of high-degree MSI (MSI-H). 12,13 Unstable BAT25 and/or BAT26 indicated MSI (specifically, MSI-H), whereas tumors in which both markers were stable were considered microsatellite-stable (MSS). 2.3 |CpG island methylator phenotype analysis CpG island methylator phenotype (CIMP) status was assessed with commercial SALSA methylation-specific multiplex ligation-dependent probe amplification (MS-MLPA) ME042-B2 (LS samples) and ME042-C1 (UC samples) probemixes (MRC Holland, Amsterdam, the Netherlands) according to the manufacturer's protocol, and as described in Valo et al. 14 CIMP status was defined according to the Weisenberger panel 15 : a sample was considered CIMP positive when at least three out of five genes (CACNA1G,IGF2,NEUROG1,RUNX3 and SOCS1) were methylated. A set of corresponding normal samples were examined to determine a threshold of hypermethylation for each probe with a stringency level II, details described in Valo et al 14 and values presented in Supplementary Table 1. 2.4 |Parallel sequencing Sequencing was performed on 27 CA-CRC patients' paired tumor-normal samples (n = 54) and 28 LS tumors including adenomas with high-grade dysplasia and carcinomas, paired with the patients' normal tissue samples (n = 56). Prior to sequencing, the core facility (FIMM) conducted a LabChip gDNA analysis to evaluate the quality of each sample. CA-CRC samples were sequenced as follows: sequencing libraries were prepared using the Twist EF library kit and Twist custom capture kit (Twist What's new? Ulcerative colitis-associated colorectal carcinoma (CA-CRC) is a complex disease involving inflammation-associated tumorigenesis and genetic mutation. Despite extensive knowledge of germline defects linked to CA-CRC, however, molecular pathogenesis of the disease remains poorly defined. In this study, using tumor profiling, the authors describe three genetic and epigenetic CA-CRC subgroups, two of which are previously known and one that is novel. The novel subgroup consisted of hypermutated microsatellite-stable tumors, which displayed distinct mutational signatures compared to the remaining CA-CRC subgroups and Lynch syndrome tumors, suggesting pathophysiologic differences. The existence of molecular subgroups within CA-CRCs may inform treatment decisions. 2998 MÄKI-NEVALA ET AL. Bioscience, San Francisco, CA). The custom kit called Pan-cancer panel included probes (n = 17 314) in the regions of 999 cancer-associated genes totaling a 6.4 Mb design (Supplementary Table 2). The libraries were sequenced using a S4 cell and run on the NovaSeq platform (Illumina, San Diego, CA). Average data per sample was 6.4 Gb, and the average depth of targeted areas was 286. Detailed performance characteristics are given in Supplementary Table 3. LS samples were sequenced as part of our earlier investigation. 16 Briefly, the Nimblegen Comprehensive Cancer Panel (CCP; Roche Diagnostics, Basel, Switzerland), a 4 Mb design with 578 cancerrelated genes, was used together with ThruPLEX DNA-seq Kit (Rubicon Genomics, Ann Arbor, MI) for library preparation. Sequencing was done on the Illumina HiSeq 2500 platform. The mean target coverage of 41-fold was reached. Details of performance characteristics are described in Porkka et al. 16 For both data sets, raw data were processed using an in-house pipeline called variant calling pipeline version 3.7, 17 and data were aligned to the human genome GRCh38. First, the adapters were trimmed from the reads as well as any bad quality nucleotides from the beginning or the end of the reads, removing any pair having read(s) smaller than 36 bp. Reads were then aligned to the GRCh38 reference genome with the BWA (version 0.6.2). Nonunique read pairs and nonunique single reads were removed and GATK (version 3.7) BaseRecalibrator was used to clean the alignment. Any potential PCR duplicates were removed using Picard (version 2.9.0). MarkDuplicates and GATK IndelRealigner were used for indel sites. 2.5 |Somatic mutation analysis Paired tumor-normal data were compared and nonsynonymous somatic mutations (missense, nonsense, frameshift, in-frame coding deletion/insertion and splice site mutations) were extracted using the VarScan2 version 2.3.2. The following parameters and thresholds were applied: strand-filter 1, min-coverage-normal 8, min-coverage- tumor 6, somatic-P-value 1, normal-purity 1 and min-var-freq 0.05. Mutations were annotated using SnpEff version 4.0 with the Ensembl v86 annotation database. Misclassified germline variants were filtered out using the Database of Single Nucleotide Polymorphisms and common population variants were removed. Mutational signatures were extracted from somatic nonsynonymous mutation data using the MutationalPatterns package 18 in R. Mutation signatures were compared to sixty available single base substitution signatures of the Catalogue of Somatic Mutations in Cancer (https://cancer.sanger.ac.uk/ cosmic/signatures/SBS/). 19 2.6 |Statistical analysis Statistical analyses were conducted using the SPSS software, version 25.0 (IBM SPSS Inc. Chicago, IL). Fisher's exact test was used to study pairwise comparisons of categorical variables. Normal distribution of continuous data was tested using the Shapiro-Wilk test. As data were largely not normally distributed and sample sizes were small, continuous variables were analyzed using the nonparametric Mann-Whitney Utest. Correlation analyses were calculated with Spearman's or Pearson's correlation test. Exact two-sided Pvalues were calculated. Pvalues <.05 were considered statistically significant. 3|RESULTS 3.1 |Study design This investigation was undertaken to define the molecular pathogenesis of colorectal tumorigenesis in UC, an idiopathic chronic inflammatory bowel disease with accelerated tumor development by a “landscaper”mechanism. 20 The results were compared to LS, where impaired “caretaker”function due to inherited (and acquired) MMR gene defects is known to induce immunological/inflammatory alterations and result in rapid tumor development. Basic characteristics of the study series are described in Table 1. 3.2 |MSI and CIMP in CA-CRC Only one CA-CRC tumor showed MSI-H (1/27, 4%). MLH1 promoter methylation analysis was possible as part of the CIMP MS-MLPA protocol (see Materials and Methods). The tumor with MSI-H revealed hypermethylation of the proximal promoter region “C,”which has been shown to be associated with a loss of MLH1 protein expression. 21 No other CA-CRC tumors had MLH1 promoter methylation, consistent with stable microsatellites. The Weisenberger criteria 15 classified 11/27 (41%) of CA-CRCs as CIMP(+), which corresponds to the CIMP(+) frequency seen among LS tumors (Table 2). The CIMP MS-MLPA panel also includes probes for the BRAF Val600Glu mutation, and two CA-CRC tumors (7%) were mutation-positive, compared to none among LS tumors (Table 2); subsequent panel sequencing confirmed the results. The single MSI-H CA-CRC tumor did not harbor BRAF Val600Glu mutation, but it had KRAS Gly12Asp mutation (Supplementary Table 4). 3.3 |Somatic mutations in CA-CRC By Pan-cancer panel sequencing, the average rate of nonsynonymous somatic mutations (VarScan2 somatic Pvalue <.01) was 16.1 mutations/Mb (median 6.3, range 2.8-118.2/Mb) in CA-CRC tumors. Ten of 27 CA-CRC tumors (37%) were found to be hypermutated (>10 mutations/Mb). These included the single MSI tumor (84.8 mutations/ Mb) and nine MSS tumors (average 29.5 mutations/Mb). Figure 1 shows the most commonly mutated genes in CA-CRC by focusing either on genes affected by high-frequency mutations (variant allele frequency [VAF] at least 25%, which is characteristic of MÄKI-NEVALA ET AL.2999 colon cancer driver genes), 22 or genes involved in at least 30% of tumors (a cutoff we have used in our previous studies on LS). 16 TP53 was the most prominent mutational target in CA-CRC, being affected with high-frequency mutations in 14 samples out of 27 (52%) (Figure 1A) and in 18 samples (67%) if any VAF was considered (Figure 1B). Our VarScan2 annotations were based on the longest transcript and two TP53 mutations included in Figure 1B were outside the primary transcript (ENST00000445888.6); 16/27 (59%) samples had TP53 mutations involving the primary transcript. When VAF ≥25% and involvement in at least 30% of tumors were both required, only TP53 fulfilled this criterion. Figure 2 provides a detailed overview of exonic TP53 mutations present in our CA-CRC tumors. The results are compared to mutations reported in recent investigations on UC or inflammatory bowel disease 23-27 (Figure 2A), and with TP53 mutations detected in our LS tumors in this investigation (Figure 2B). Our CA-CRC tumors harbored 15 different mutations, mostly located in positions shown to be associated with impaired functionality when affected. 28 The most frequent mutation was p.Arg248Trp/Gln occurring in three samples with VAFs above 25% in all of them. Overall, the vast majority, 73% (11/15) of TP53 mutations present in CA-CRC were high-frequency somatic mutations. One was a truncating mutation (p.Tyr205*) found in one sample (Figure 2A). For comparison, of TP53 mutations present in LS-associated tumors, only 3/19 (16%) occurred with VAF of 25% or higher (P= .0013) (Figure 2B). The total number of nonsynonymous somatic mutations (VarScan2 P< .01) per CA-CRC tumor did not significantly correlate with the number of methylated CIMP genes or probes. MMR deficiency explained hypermutability in a single tumor (the one with MSI described above). To identify possible molecular contributors for hypermutability in those CA-CRC tumors that were MSS, we investigated the prevalence of mutations in DNA repair pathway genes (n = 86) identified by Gene Ontology analysis (www.ebi.ac. uk/QuickGO). Mutations of DNA repair genes were significantly enriched in the nine hypermutated MSS cases compared to the 17 nonhypermutated MSS cases of CA-CRC: 142/189 (75%) of mutations were found in the hypermutant tumors (P= .00001) (Supplementary Table 5a). By a similar comparison, mutations in TABLE 1 Characteristics of the patient samples CA-CRC LS tumors combined a LS HGD adenomas LS carcinomas Pvalue CA-CRC vs LS tumors No. of patients 27 24 10 15 NA Male sex b 18 (66.7%) 11 (45.8%) 4 (40%) 8 (53.3%) .164 Age at diagnosis, years (mean ± SD) b 51.1 (±10.6) 50.1 (±12.9) c 50.4 (±14) c 50.8 (±12.2) .962 Years of colitis before CRC (mean ± SD) b 22.2 (±10.5) d ———NA Gene mutated in the germline b MLH1 —19 (79.2%) 9 (90%) 11 (73.3%) NA MSH2 —3 (12.5%) 1 (10%) 2 (13.3%) NA MSH6 —2 (8.3%) 0 2 (13.3%) NA No. of tumors 27 28 10 18 NA Tumor location Proximal e 12 (44.4%) 15 (53.6%) 2 (20.0%) 13 (72.2%) .380 Distal 12 (44.4%) 12 (42.9%) 8 (100.0%) 4 (22.2%) NA 3 (11.1%) 1 (3.6%) 0 1 (5.6%) Stage of carcinomas I 12 (44.4%) 11 (61.1%) —11 (61.1%) .354 II 5 (18.5%) 4 (22.2%) —4 (22.2%) III 7 (25.9%) 2 (11.1%) —2 (11.1%) IV 3 (11.1%) 0 —0 NA 0 1 (5.6%) —1 (5.6%) Note: Note regarding LS samples: Multiple samples were available from three LS patients (three carcinomas, two carcinomas, and a carcinoma plus adenoma from one patient each). If sampling took place at different time points (metachronous neoplasia), different ages were included in the calculation of age at diagnosis. Abbreviations: HGD, high-grade dysplasia; NA, not available or applicable. a LS-associated adenomas and carcinomas combined. b Calculated per patients. c Information for one case not available. d Information for eight cases not available. e From caecum to splenic flexure (included). 3000 MÄKI-NEVALA ET AL. TABLE 2 Comparison of central molecular features between CA-CRC and LS tumors CA-CRC a LS tumors Pvalue CA-CRC (all) vs LS (all)Group 1 Group 2 Group 3 All HGD-adenomas CRCs All No. of tumors 1 9 17 27 10 18 28 NA MSI-H tumors 1 (100%) 0 0 1 (3.7%) 10 (100%) 16 (100%) b 26 (100%) b <.00001 CIMP(+) tumors 0 3 (33.3%) 8 (47.1%) 11 (40.7%) 2 (20%) 9 (50%) 11 (39.3%) .782 Average no. of somatic nonsynonymous mutations/Mb (P< .01) Pan-cancer panel 84.8 29.5 4.9 16.1 NA NA NA NA CCP 69.8 26.8 4.6 14.4 278.1 169.9 208.5 2.3E-12 No. of tumors with high-frequency c mutations BRAF Val600Glu (CCP) 0 0 2 (12%) 2 (7.4%) 0 0 0 .236 TP53 (CCP) 0 5 (55.6%) 9 (52.9%) 14 (51.9%) 1 (10%) 2 (11.1%) 3 (10.7%) .0013 APC (CCP) 1 (100%) 2 (22.2%) 0 3 (11.1%) 6 (60%) 10 (35.7%) 16 (57.1%) .0005 Predominant mutational signatures d 21, 46, 15 30, 32 (32) 30, 32 1, 46, 4, 10b, 6 1, 46, 6, 4, 10b 1, 46, 4, 10b, 6 NA Abbreviations: HGD, high-grade dysplasia; NA, not available or applicable. a Subdivision based on our molecular data as follows: Group 1, hypermutated MSI; Group 2, hypermutated MSS; and Group 3, nonhypermutated MSS tumors. Tumors with over 10 nonsynonymous somatic mutations/Mb were considered hypermutated. b MSI information was unavailable for two cases, but immunohistochemical analysis suggested MMR defects in both samples. c VAF 25% or higher. d In decreasing order of contribution per tumor group (signatures were based on the entire Pan-Cancer panel in CA-CRC and the CCP subpanel in LS tumors). MÄKI-NEVALA ET AL.3001 Wnt pathway genes (n = 44 genes) were mostly found in the hypermutated tumors: 115/134 (86%) (P= .00002) (Supplementary Table 5b). Detailed somatic mutation data for the CA-CRC samples can be found in Supplementary Table 6. 3.4 |Mutation signatures of CA-CRC tumors Mutation signature analysis was performed on somatic mutation data (VarScan2 P< .01), and signatures were compared to known 60 single 0 10 20 30 40 50 60 % tumors 0 10 20 30 40 50 60 70 80 90 % tumors (A) (B) FIGURE 1 Top mutant genes in CA-CRC (n = 27 tumors), based on Pan-cancer panel (n = 999 genes) and VarScan2 annotations utilizing the longest RefSeq transcript. A, Selection criteria were variant allele frequency (VAF) 25% or higher, and at least 10% of tumors affected. B, Selection criterion was at least 30% of tumors affected (any VAF was considered). Asterisk indicates genes that fulfilled both (A) and (B)-specific criteria FIGURE 2 Number and distribution of exonic nonsynonymous TP53 mutations along the protein domains (transcript ENST00000445888.6; any VAF was considered). A, Mutations found in our CA-CRC sample set are presented above the bar visualizing the protein domains. Mutations from recent studies on CA-CRC 23-27 are presented below the bar. B, Mutations found in our LS tumor material (n = 28) by CCP sequencing. White circles indicate nontruncating mutations and black circles refer to truncating mutations. TAD, transactivation domain [Color figure can be viewed at wileyonlinelibrary.com] 3002 MÄKI-NEVALA ET AL. base substitution COSMIC signatures (v3). As evident from Figure 3, hypermutated and nonhypermutated CA-CRC tumors formed separate clusters. The single hypermutated MSI tumor clearly represented a different signature profile compared to other CA-CRC tumors. The MSI tumor showed a strong Signature 21 and a notable Signature 15 (Figure 3A), and cosine similarity additionally pinpointed Signature 26 (Figure 3B); all these three signatures are known to be associated with MSI. 29 Hypermutated MSS tumors revealed prominent Signatures 30 and 32 (Figure 3A,B). Additionally, cosine similarity to Signatures 7a and b, 11, 19 and 23 was high (Figure 3B). No single signature stood out among the nonhypermutated MSS tumors (Figure 3A,B). In group-wise analysis (Figure 4), comparison of the relative contributions of mutational signatures between hypermutated and nonhypermutated MSS CA-CRCs highlighted the predominance of Signatures 30 and 32 in the former group (relative contributions 36% and 20%, respectively) and the absence of a single dominant signature in the latter group (with the possible exception of Signature 32 that accounted for 16% of all signature contributions in this group) (Figure 4A). 3.5 |Molecular comparison of CA-CRC vs LS tumors A study protocol analogous to CA-CRCs was applied to LS tumors, and Table 2 provides a comparative summary of the essential findings. All LS adenomas had high-grade dysplasia and did not significantly differ from LS-CRCs with respect to MSI, CIMP or somatic mutational load (Table 2); therefore, LS adenomas and carcinomas were combined to a single group (“LS tumors”) throughout this article, unless Muta�on rate 3.4 5.5 4.1 2.8 4.7 6.3 4.7 3.4 3.4 6.6 4.7 6.1 6.1 14.7 118.0 14.7 35.9 10.9 84.8 6.3 3.8 15.8 22.8 13.8 8.6 18.9 3.3 Muta� on rate 6.3 4.7 4.7 6.1 6.1 3.4 4.1 3.4 3.4 2.8 6.6 5.5 4.7 3.3 84.8 8.6 3.8 10.9 13.8 15.8 6.3 22.8 14.7 18.9 14.7 35.9 118.0 Mutation rate Mutation rate (A) (B) FIGURE 3 COSMIC signatures (v3) of all CA-CRC samples. A, Relative contribution heatmap. B, Cosine similarity heatmap. Mutation rate over 10/Mb identifies hypermutated samples [Color figure can be viewed at wileyonlinelibrary.com] MÄKI-NEVALA ET AL.3003 specified otherwise. For LS tumors, raw sequence data based on CCP panel (n = 578 genes) was available from a previous investigation 16 and was reanalyzed by the same protocol used for the Pan-cancer data (see Materials and Methods) to enable comparison with CA-CRC results. For CA-CRC, CCP panel targets were extracted from the Pancancer sequencing data for the purposes of comparison. All LS tumors showed MSI-high and were hypermutated (>10 nonsynonymous somatic mutations/Mb). The overall mutation rate (VarScan2 somatic Pvalue <.01) was significantly higher in LS-associated tumors than in CA-CRC, with averages of 208.5 mutations/Mb (median 175.6/Mb, range 15.8-528.8/Mb) and 14.4 mutations/Mb (median 5.5/Mb, range 2.8-108.8/Mb), respectively (P= 2.3E-12; Table 2). The same applied to high-frequency mutations (VAF 25% or higher), with the average and median numbers of 17.4 mutations/Mb and 12.4 mutations/Mb in LS tumors vs 2.1 mutations/ Mb and 0.75 mutations/Mb in CA-CRC tumors (P= 5.6E-12). Among genes most often affected by high-frequency somatic mutations (Supplementary Figure 1), TP53 showed significantly higher mutation rates in CA-CRC than LS tumors (14/27, 52% vs 3/28, 11%, P= .0013; Supplementary Figure 1A; Table 2). Conversely, mutations of APC were significantly more common in LS tumors compared to CA-CRC (16/28, 57% vs 3/27, 11%, P= .0005; Table 2). By mutation type (truncating vs nontruncating), truncating (ie, nonsense or frameshift) mutations were clearly more common in LS-associated tumors (Supplementary Figure 1C) compared to CA-CRC (Supplementary Figure 1B), consistent with MSI statuses (100% of LS and 4% of CA-CRC tumors had MSI; Table 2). Somatic mutational signatures for the individual LS tumors are depicted in Supplementary Figure 2. LS tumors clustered into two major groups; signature profiles were evidently more uniform than between the subgroups of CA-CRC samples. In LS, the overall number of nonsynonymous mutations (below vs above 100 mutations/Mb) appeared to contribute to the pattern of sample clustering. The CIMP status seemed randomly distributed across the LS clusters (the same applied to CA-CRC tumors; Figure 3). Mutation signatures of LS-associated adenomas and carcinomas were very similar. Signatures 1 (aging-associated, “clock-like”), 4 (tobacco smoking-associated), 6 (MMR deficiency-associated), 10b (POLE-proofreading domain mutation-associated) and 46 19,29,30 (see also https://cancer.sanger.ac. uk/cosmic/signatures/SBS/) were well represented in the LS tumors (Figure 4B; Supplementary Figure 2). When compared to hypermutated MSS CA-CRCs (n = 9), LS tumors (n = 28, all hypermutated) showed clearly distinctive mutation signatures (Figure 4B; Supplementary Figure 3–A-C), compatible with different disease etiologies. 4|DISCUSSION Patients with UC like those with LS are predisposed to early onset CRC. Severity, 31 duration 32 and extent 33,34 of inflammation increase (A) (B) FIGURE 4 Relative contribution of mutational signatures, comparing the five largest contributors selected from each group. A, Top five signatures in hypermutated MSS CA-CRC (n = 9) and nonhypermutated MSS CA-CRC (n = 17) totaling eight signatures. B, Top five signatures in LS tumors (hypermutated MSI) (n = 28) and hypermutated MSS CA-CRC (n = 9) totaling nine signatures [Color figure can be viewed at wileyonlinelibrary.com] 3004 MÄKI-NEVALA ET AL.