IJC International Journal of Cancer Quantitative analysis of somatically acquired and constitutive uniparental disomy in gastrointestinal cancers Keyvan Torabi1,2, Pau Erola3,4, Maria Isabel Alvarez-Mora5, Marcos Díaz-Gay1, Queralt Ferrer1, Antoni Castells1, Sergi Castellví-Bel1, Montserrat Milà5, Juan José Lozano3, Rosa Miró2,6, Thomas Ried 7, Immaculada Ponsa2,6 and Jordi Camps 1,2 1 Gastrointestinal and Pancreatic Oncology Group, Institut D’Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), Centro de Investigación Biomédica en Red de Enfermedades Hepáticas y Digestivas (CIBEREHD), Barcelona, Catalonia, Spain 2 Unitat de Biologia Cellular i Genètica Mèdica, Departament de Biologia Cellular, Fisiologia i Immunologia, Facultat de Medicina, Universitat Autònoma de Barcelona, Bellaterra, Catalonia, Spain 3 Bioinformatics Unit, CIBEREHD, Barcelona, Catalonia, Spain 4 Roslin Institute, University of Edinburgh, Midlothian, Scotland, United Kingdom 5 Biochemistry and Molecular Genetics Department, Hospital Clínic, IDIBAPS, Centro de Investigación Biomédica en Red de Enfermedades Raras (CIBERER), Barcelona, Catalonia, Spain Cancer Genetics and Epigenetics 6 Institut de Biotecnologia i Biomedicina, Universitat Autònoma de Barcelona, Bellaterra, Catalonia, Spain 7 Genetics Branch, Center for Cancer Research, National Cancer Institute, National Institutes of Health, Bethesda, MD, USA Somatically acquired uniparental disomies (aUPDs) are frequent events in solid tumors and have been associated with cancer- related genes. Studies assessing their functional consequences across several cancer types are therefore necessary. Here, we aimed at integrating aUPD profiles with the mutational status of cancer-related genes in a tumor-type specific manner. Using TCGA datasets for 1,032 gastrointestinal cancers, including colon (COAD), rectum (READ), stomach (STAD), esophageal Key words: uniparental disomy, copy-number alterations, gastrointestinal cancers, single nucleotide variants, ploidy, mosaicism Abbreviations: ASCAT: Allele-Specific Copy Number Analysis of Tumors; aUPD: somatically acquired uniparental disomy; BAF: B allele fre- quency; CEP: Centromeric FISH probes; CIN: chromosome instability; CNAs: copy number alterations; cnLOH: copy-number neutral loss of heterozygosity; COAD: colon adenocarcinoma; CRC: colorectal cancer; EAC: esophageal adenocarcinoma; ESCA: esophageal carcinoma; ESCC: esophageal squamous cell carcinoma; FISH: Fluorescence in situ hybridization; GI: gastrointestinal; IBD: identical-by-descent; INDELs: short insertions and deletions; LOH: loss of heterozygosity; LRR: Log R Ratio; MAD: Mosaic Alteration Detection; MAF: Mutation Annotation For- mat; MLPA: Multiplex Ligation-dependent Probe Amplification; PSCBS: Parent-Specific Circular Binary Segmentation; READ: rectum adeno- carcinoma; RNAi: RNA interference.; SNP: single nucleotide polymorphism; SNV: single nucleotide variant; STAD: stomach adenocarcinoma; TCGA: The Cancer Genome Atlas; TMA: tissue microarray; TSGs: tumor suppressor genes; UPD: (constitutive) uniparental disomy Additional Supporting Information may be found in the online version of this article. Conflict of interest: The authors declare that they have no conflict of interest. K.T. and P.E. contributed equally to this work. I.P. and J.C. contributed equally to this work. Grant sponsor: The European Commission (COLONGEVA to J.C.); Grant sponsor: The Instituto de Salud Carlos III and cofunded by the European Regional Development Fund (ERDF); Grant numbers: CP13/00160, PI14/00783 (J.C.); Grant sponsor: The CIBEREHD program; Grant sponsor: The Agència de Gestió d’Ajuts Universitaris i de Recerca, Generalitat de Catalunya; Grant numbers: 2017 SGR 1035, 2017 SGR 1134, 2017 SGR 1796, 2017 SGR 21; Grant sponsor: Fundación Científica de la Asociación Española Contra el Cáncer; Grant numbers: GCB13131592CAST; Grant sponsor: PERIS (SLT002/16/00398, Generalitat de Catalunya); Grant sponsor: CERCA Programme (Generalitat de Catalunya); Grant sponsor: PIF-fellowship from Universitat Autònoma de Barcelona; Grant numbers: 456-01-02/2013 (K.T.); Grant sponsor: Roslin Institute Strategic Programme funding from the BBSRC; Grant numbers: BB/P013732/1 (P.E.); Grant sponsor: A contract from AGAUR (Generalitat de Catalunya); Grant numbers: 2017 FI_B 00619 (M.D.G.) DOI: 10.1002/ijc.31936 This is an open access article under the terms of the Creative Commons Attribution-NonCommercial License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited and is not used for commercial purposes. History: Received 7 Mar 2018; Accepted 2 Oct 2018; Online 23 Oct 2018 Correspondence to: Jordi Camps, Ph.D. Gastrointestinal and Pancreatic Oncology Group Institut D’Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS) c/Rosselló 149-153, 4th floor, 08036 Barcelona, Spain, E-mail: jcamps@clinic.cat; Tel.: +34-93-2275400 ext. 4560; Fax: +34-93-3129405 Int. J. Cancer: 144, 513–524 (2019) © 2018 The Authors. International Journal of Cancer published by John Wiley & Sons Ltd on behalf of UICC. 514 Genomic integration of aUPD and mutational status adenocarcinoma (EAC) and esophageal squamous cell carcinoma (ESCC), we show a non-random distribution of aUPD, suggesting the existence of a cancer-specific landscape of aUPD events. Our analysis indicates that aUPD acts as a “second hit” in Knudson’s model in order to achieve biallelic inactivation of tumor suppressor genes. In particular, APC, ARID1A and NOTCH1 were recurrently inactivated by the presence of homozygous mutation as a consequence of aUPD in COAD and READ, STAD and ESCC, respectively. Furthermore, while TP53 showed inactivation caused by aUPD at chromosome arm 17p across all tumor types, copy number losses at this genomic position were also frequent. By experimental and computationally inferring genome ploidy, we demonstrate that an increased number of aUPD events, both affecting the whole chromosome or segments of it, were present in highly aneuploid genomes compared to near-diploid tumors. Finally, the presence of mosaic UPD was detected at a higher frequency in DNA extracted from peripheral blood lymphocytes of patients with colorectal cancer compared to healthy individuals. In summary, our study defines specific profiles of aUPD in gastrointestinal cancers and provides unequivocal evidence of their relevance in cancer. What’s new? Cancer Genetics and Epigenetics Somatically acquired uniparental disomies (aUPDs), in which two copies of a chromosome originate from the same parent, have been documented in various human cancers. Here, the authors examined the frequency of aUPDs in different gastrointestinal cancer types. Events involving aUPDs were found to occur at high incidence in gastrointestinal cancers and at increased frequency particularly in highly aneuploid genomes. The data also reveal a nonrandom distribution of aUPDs, with evidence of biallelic inactivation of tumor suppressor genes and activation of oncogenes in a tumor type-specific manner. The findings suggest that aUPDs are functionally relevant in gastrointestinal malignancies. Introduction involved in genomic imbalances has become essential in order Copy number alterations (CNAs) are the hallmark of human to identify functional inactivation of genes.10 In this context, cancers, including gastrointestinal (GI) cancers; these CNAs aUPD can arise as an alternative mechanism to act as the “sec- result in a recurrent, tumor-type specific landscape of DNA ond hit” in the “two-hit” Knudson’s model. Similar to genomic gains and losses.1 The application of SNP arrays has allowed losses, the mutational status of genes located at recurring the identification of loss of heterozygosity (LOH) and copy- regions of aUPD can provide evidence to determine the extent number neutral LOH (cnLOH), defined as LOH not affected to which a certain aUPD event is a driver alteration if biallelic by a reduction in copy number, which typically appears as a inactivation is achieved. In fact, UPD events have been already consequence of somatically acquired uniparental disomies associated with driver genes in several cancer types.11–19 (hereafter referred to as aUPDs).2–4 UPD was first described Moreover, some authors have also reported gain-of-function of as a constitutional event, consisting in the inheritance of two homozygous mutations affecting oncogenes in regions of copies of chromosomes from the same parental origin caused aUPD.20,21 Yet, only few studies have focused on profiling such by a meiotic error which may lead to developmental disor- events in a genome-wide tumor-type specific manner. ders.5 Lately, mosaic UPD has been also associated with aging Additionally, whole genome duplication, giving rise to highly and cancer.6 Furthermore, aUPDs have been recurrently unstable tetraploid genomes, has been accepted as a common observed in several human malignancies, including both event in several tumor types, and has been postulated as a driver hematological neoplasms and solid tumors.3,7 event in the progression of cancer.22 The consequence of a An important challenge in genome-wide cancer studies is to genome tetraploidization includes the acquisition of numerical distinguish driver CNAs, which lead to the development, pro- chromosome instability, which is defined by the increasing rate gression and maintenance of tumors, from those considered of mitotic segregation errors.23 Recently, the use of bioinfor- passenger events, resulting as a consequence of high rates of matic tools has allowed the assessment of allele-specific copy chromosome instability (CIN).8 Thus, several efforts have been number and, consequently, the identification of the tumor made in order to identify oncogenes and tumor suppressor ploidy.24,25 Therefore, it has been systematically established that genes (TSGs) in recurrently gained and deleted regions, respec- highly aneuploid genomes resulting from whole genome tively, which could provide insight into driver CNAs. In the duplications (i.e., tetraploidization) are common in cancer, in “two-hit” Knudson’s hypothesis, one copy of a TSG is inacti- particular in epithelial tumors.8 In such a polyploid scenario, it vated by a non-synonymous mutation, while the other copy is is feasible to hypothesize that genomic gains and losses of the inactivated by a similar mutation or by a loss of heterozygosity same parental chromosome could result in recurrent aUPDs. (LOH), acting as the “second hit.”9 Therefore, the integration In the present study, we aimed at integrating patterns of of the mutational status of genes with regions frequently aUPD of GI tumors with the mutational status of genes located at Int. J. Cancer: 144, 513–524 (2019) © 2018 The Authors. International Journal of Cancer published by John Wiley & Sons Ltd on behalf of UICC. Torabi et al. 515 these regions. Moreover, by inferring tumor ploidy, we also deter- Specific Copy Number Analysis of Tumors (ASCAT) method.24 mined the extent to which highly aneuploid genomes displayed Affymetrix CEL files were preprocessed using PennCNV-Affy increased frequency of aUPD and, finally, interrogated the pres- to generate Log R Ratio (LRR) and B Allele Frequency (BAF) ence of constitutive UPD in colorectal cancer (CRC) patients. matrices, which were used as input files in ASCAT. Previously published Affymetrix SNP 6.0 genotyping data Materials and Methods from genome-wide association studies of the EPICOLON Clinical samples cohort were used to infer mosaic CNAs and UPDs by applying Level 1 data from the five major GI tumor-types were the Mosaic Alteration Detection (MAD) method.28,29 This obtained from The Cancer Genome Atlas (TCGA) project algorithm detects the deviation of the B allele frequency (BAF) through the NCI Genomic Data Commons (GDC) portal signal from the expected values typical for non-altered homozy- (https://portal.gdc.cancer.gov/). TCGA cohorts included sam- gous (1 or 0) or non-altered heterozygous (0.5) probes. BAF ples for each tumor-type and their matched normal paired values for heterozygous SNPs were used to estimate the per- samples, which consisted of 434 colon adenocarcinomas centage of cells with the rearrangement.30 Unless specifically (COAD), 155 rectum adenocarcinomas (READ), 325 stomach mentioned, segments smaller than 2 Mb and pericentromeric adenocarcinomas (STAD) and 118 esophageal (ESCA) carci- regions were not included in the analysis. In order to discrimi- nomas, including 58 esophageal adenocarcinoma (EAC) and nate identical-by-descent regions (also known as IBD alleles), Cancer Genetics and Epigenetics 60 esophageal squamous cell carcinoma (ESCC) samples. which may mimic UPD alleles, from constitutive mosaic UPD, Additionally, genotyping data from genome-wide association segments with BAF value of 1 (complete LOH) were discarded. studies of the EPICOLON cohort, which comprised 747 CRC patients and 503 controls ascertained through a prospective, Whole exome sequencing data analysis multicenter, nationwide study in Spain, were used.26 For a sub- When available, whole exome sequencing data were extracted set of individuals of the EPICOLON cohort, DNA from from all cohorts from the GDC portal. For this analysis, single paraffin-embedded primary tumors and their associated normal nucleotide variants (SNVs) and short insertions and deletions mucosa were obtained using standard DNA extraction kits (INDELs) were considered. According to GATK Best Practices, (Qiagen, Hilden, Germany) to perform validation experiments. MuTect2 was selected as somatic variant caller.31 Annotated Finally, 20 colorectal adenocarcinomas provided by the variants were downloaded using the Mutation Annotation For- Hospital Clínic of Barcelona/IDIBAPS Biobank were included mat (MAF) as tab-delimited text files. Regarding pathogenicity, in a tissue microarray (TMA). Clinical features of each patient truncating variants (nonsense, frameshift and those affecting were previously described.18 All patients signed the corre- splicing variants) were directly considered. Additionally, mis- sponding informed consent and the sample collection was sense variants were assessed with six different prediction tools: approved by the institutional review board of the hospital. PhyloP (deleteriousness threshold of phyloP46way_placental score ≥ 1.6), SIFT (prediction of damaging), PolyPhen2 SNP-array data analysis (HumVar prediction of probably damaging or possibly damag- TCGA tumor and normal-matched Affymetrix SNP 6.0 array ing), MutationTaster (prediction of disease-causing or disease- data were used for this analysis. To identify CNAs and LOH, causing-automatic), LRT (prediction of deleterious) and CADD segmentation was performed using the Paired Parent-Specific (Phred score ≥ 15). Only those missense variants predicted as Circular Binary Segmentation (Paired PSCBS) method imple- pathogenic by at least three algorithms were considered for mented in the PSCBS package.27 PSCBS uses a parametric further analysis. In order to allow an accurate annotation of bootstrapping technique to estimate the different allelic mean missense variants with Oncotator (http://portals.broadinstitute. levels. Somatically acquired UPD calls are tested on the seg- org/oncotator/), genomic coordinates were switched from ments that are not in allelic balance, and is positive on those genome build GRCh38 (hg38) to GRCh37 (hg19) using the cases where the allelic CNA is under a certain threshold, NCBI Genome Remapping Service (https://www.ncbi.nlm.nih. derived from data considered background signal. Unfortu- gov/genome/tools/remap). Only variants showing at least a nately, the background signal estimation may fail on tumors 20% of alternative allele frequency and a coverage of 20× were that do not present LOH, so we discarded those samples with a considered for analysis. Comparison with PSCBS results was background signal ΔLOH >0.75. After the segmentation, seg- performed through an in-house R pipeline.32 ments smaller than 2.5 Mb were discarded. Two segments were considered the same if the gap between them was shorter than Fluorescence in situ hybridization 2.5 Mb. Out of all paired samples examined in our study, only Centromeric Fluorescence in situ hybridization (FISH) probes those that presented less than 300 segments were considered (CEP) for chromosomes 7 and 15 labeled in green and for chro- for further analyses. Details on data analysis have been previ- mosomes 18 and 20 labeled in orange were used according the ously published.18 Moreover, in order to identify the global manufacturer’s recommendations (Vysis Inc., Downers Grove, ploidy of a previously reported dataset (GSE64114) and TCGA IL). FISH analyses were performed in 4–5 μm thickness sections samples, we used the recommended pipeline of the Allele- of the TMA containing two replicates of both tumor and normal Int. J. Cancer: 144, 513–524 (2019) © 2018 The Authors. International Journal of Cancer published by John Wiley & Sons Ltd on behalf of UICC. 516 Genomic integration of aUPD and mutational status adjacent mucosa for each sample. Pretreatment included three multiplied by the fraction of the genome with copy-number xylene incubations, increasing concentration of ethanol series, aberrations in each patient. The mutation probability was permeabilization with EDTA and treatment with pepsin. Next, calculated based on the size of each gene and the number of slides were incubated in 1× PBS with MgCl2 and fixed with 1% mutations in each patient. We performed 109 tests for all paraformaldehyde. Denaturation was performed in a Thermo genes that showed more than one “second hit” event in our Brite (Vysis) at 78  C during 6 min for panel one (CEP7 and dataset. The resulting p values were adjusted for multiple 18) and 85  C during 3 min for panel two (CEP15 and 20). testing using Benjamini-Hochberg’s method. Only genes with Hybridization was performed at 37  C overnight. Post- q values <0.1 were considered. hybridization washes were performed in 0.4× SSC/0.3% NP40 at The Mann–Whitney sum-rank test was used in order to 74  C for 2 min and 2× SSC/0.1% NP40 at room temperature compare the number of aUPD events between tumor-types during 1 min. A minimum of 100 cells were imaged with a and also between highly aneuploid and near-diploid genomes. Nikon Eclipse 50i fluorescence microscope using the Isis Correlation analysis was applied when comparing ploidy Fluorescence Imaging System (MetaSystems, Altlussheim, values extracted from FISH and ASCAT methods. The Germany). In order to infer ploidy, the weighted mean copy software GraphPad Prism 6.0 (GraphPad) was used to assess number of all chromosomes analyzed in each sample was calcu- statistical significance and to plot graphs. Cancer Genetics and Epigenetics lated. A threshold for considering a highly aneuploid genome was set at 2.5, which corresponded to a hypotriploid genome Results (i.e., 57 chromosomes). aUPD profiling in GI cancers Genome-wide aUPD analysis was performed in 265 colon Multiplex ligation-dependent probe amplification (MLPA) (COAD), 105 rectum (READ), 121 stomach (STAD) and MLPA analysis was performed using Salsa MLPA probemix 57 esophageal (ESCA, including 18 EAC and 39 ESCC) tumors P043-D1 and Salsa MLPA probemix P037-B1 CLL-1 accord- and their corresponding normal-matched samples extracted ing to manufacturer’s recommendations (MRC-Holland, from level 1 TCGA data portal by applying the algorithm Amsterdam, Netherlands). Electrophoresis was performed PSCBS. Most of the samples showed at least one genomic using the ABI 3100 genetic analyzer (Applied Biosystems, region affected by aUPD (96.49% in ESCA, 91.74% in STAD, Foster City, CA) with GeneScan 500 ROX dye Size Standard. 88.89% in READ and 85.38% in COAD cohorts). Specifically, Results were evaluated using the SeqPilot software version ESCA showed the highest number of regions with aUPD, with 4.0.1 (JSI Medical Systems GmbH, Kippenheim, Germany). a median of five events per sample (p < 0.05). In contrast, COAD showed a median of three aUPD events per sample Microsatellite analysis being the tumor type with statistically significant lowest number Multiplexed PCR amplification of polymorphic short tandem of aUPD (p < 0.05) (Supporting Information Fig. S1A). We repeat (STR) loci was performed using commercial STR then classified aUPD in two types of events: whole chromosome marker panels for chromosomes 11 and 17 (ABI PRISM® and segmental aUPDs, the last including both telomeric and Linkage Mapping Set, Version 2.5, Applied Biosystems). For interstitial fragments. Overall, segmental aUPDs were the most chromosome 11, a total of seven STRs were selected, three frequent alterations with a mean of 3.39 events per sample within the region of interest (D11S4046, D11S1338, across all cohorts compared to 0.87 whole chromosome aUPD D11S902), and four outside this region used as normal control events (p < 0.0001). Moreover, we observed a higher amount of region (D11S935, D11S904, D11S987, D11S937). For chromo- segmental aUPD in the upper compared to the lower GI tract some 17, eight STRs were selected, including four within the (mean of 4.65 for ESCA and STAD vs. mean of 2.84 for COAD LOH region (D17S831, D17S938, D17S1852, D17S799) and and READ; p < 0.0001) (Supporting Information Fig. S1B). four outside this region (D17S798, D17S1868, D17S944, In order to establish an overview of the overlap between D17S785). All forward primers were fluorescently labeled with regions recurrently affected by aUPD and CNA in a tumor- different fluorochromes (FAM, VIC and NED). The PCR type specific manner, genome-wide circos plots were gener- amplification was performed under standard conditions using ated for each individual cohort (Supporting Information fluorescently labeled primers. The PCR products were run on Fig. S2A-E). Significant positive correlations between the an ABI3100 Genetic Analyzer (ABI, Foster City, CA), and the frequency of regions with aUPD and copy number losses were results were analyzed with the GeneMapper v3.5 software. identified (0.253 in COAD, 0.334 in READ, 0.285 in EAC, Single peaks were considered uninformative. 0.105 in ESCC and 0.304 in STAD; p < 0.0001); however, the correlations between the frequency of regions with aUPD and Statistical analysis copy number gains were all negative (−0.206 in COAD, A permutation test was implemented to assess the statistical −0.223 in READ, −0.072 in EAC, −0.029 in ESCC and − 0.156 significance of “second hit” events. For each gene and patient in STAD; p < 0.0001). The most frequently genomic regions we defined the probability of having a “second hit” event as affected by aUPD in at least 10% of the samples for each the probability of having one or more mutations in a gene cohort are listed in Supporting Information Table 1. Our Int. J. Cancer: 144, 513–524 (2019) © 2018 The Authors. International Journal of Cancer published by John Wiley & Sons Ltd on behalf of UICC. Torabi et al. 517 Cancer Genetics and Epigenetics Figure 1. Genomic profiles of aUPDs in GI cancers. Frequency plots showing the distribution of aUPDs along the whole genome in esophageal squamous cell carcinoma, esophageal adenocarcinoma, stomach adenocarcinoma, colon adenocarcinoma, and rectum adenocarcinomas. In blue are indicated the most frequently mutated genes affected by aUPD in each tumor type. [Color figure can be viewed at wileyonlinelibrary.com] analysis indicated that the chromosome region 17p13.3-p13.1 arm 17p also showed high frequencies of copy number losses was affected across all GI tumor types (Fig. 1). In particular, in all cohorts, thus becoming the most altered genomic region the highest frequency of aUPD events affecting this region throughout all tumor types. The second most prevalent geno- was observed in EAC (up to 55.56%), and it was the second mic region affected by aUPD was the chromosome arm 9q. most frequently affected region in ESCC, READ and COAD, Specifically, aUPDs affecting 9q21.11-q34.3 were present in with frequencies up to 53.85%, 26.67% and 17.36%, respec- 64.10%, 27.78% and 21.48% of ESCC, EAC and STAD tively. When including CNAs in the analysis, chromosome samples, respectively. Notably, the region at 9q22.32-q34.3 in Int. J. Cancer: 144, 513–524 (2019) © 2018 The Authors. International Journal of Cancer published by John Wiley & Sons Ltd on behalf of UICC. 518 Genomic integration of aUPD and mutational status Table 1. Most frequently mutated genes accompanied by aUPD or copy number losses in GI cancers Cohort Gene Cytoband “1st hit” mutation1 % “2nd hit” aUPD2,3 % (qval) “2nd hit” CN Loss3 % (qval) COAD APC 5q22.2 74.47 22.29 (< 10−9) 20.57 (< 10−9) −9 TP53 17p13.1 53.19 20 (< 10 ) 73.6 (< 10−9) −9 KRAS 12p12.1 39.57 15.05 (< 10 ) 3.23 (0.0061) FBXW7 4q31.3 13.62 12.5 (0.0098) 12.5 (0.0772) SMAD4 18q21.2 10.64 12 (0.00061) 68 (< 10−9) −9 SOX9 17q24.3 10.21 16.67 (< 10 ) 8.33 (0.000087) READ APC 5q22.2 80.77 34.92 (< 10−9) 15.87 (< 10−9) TP53 17p13.1 73.08 31.58 (< 10−9) 57.89 (< 10−9) −9 KRAS 12p12.1 39.74 19.35 (< 10 ) 3.23 (0.004) FBXW7 4q31.3 14.10 18.18 (0.0036) 9.09 (0.031) NRAS 1p13.2 11.54 22.22 (8.4 × 10−6) 0 STAD TP53 17p13.1 45.00 31.48 (< 10−9) 59.26 (< 10−9) ARID1A 1p36.11 22.50 14.81 (0.019) 3.70 (n.s.) Cancer Genetics and Epigenetics PIK3CA 3q26.32 11.67 21.43 (0.0728) 0 APC 5q22.2 7.50 22.22 (n.s.) 44.44 (0.0073) ESCC TP53 17p13.1 71.79 53.57 (< 10−9) 21.43 (< 10−6) NOTCH1 9q34.3 10.26 75 (5.5 × 10−9) 0 PTCH1 9q22.32 10.26 100 (< 10−9) 0 ZNF750 17q25.3 7.69 66.67 (1.64 × 10−8) 33.33 (0.000048) EAC TP53 17p13.1 72.22 69.23 (< 10−9) 23.08 (< 10−9) −8 MYH2 17p13.1 11.11 100 (1.41 × 10 ) 0 n.s., not significant. 1 Only genes that reached a 7% threshold of mutation by cohort have been considered. 2 Only genes that reached a 10% threshold of “second hit” driven by an aUPD event have been considered. 3 Genomic events detected in only one sample were not considered for this analysis. ESCC showed the highest frequency of aUPD across all (N = 235), READ (N = 78), EAC (N = 18) and ESCC cohorts (Fig. 1). Finally, UPD at 5q12.1-q35.3 was the most (N = 39) cohorts was 123.64, 72.1, 45.83 and 37.03, respec- common event in READ and COAD, affecting up to 32.38% tively. We then evaluated which of these variants were located and 20.38% of the samples, respectively. While this alteration in regions of aUPD. Our analysis indicated that ESCA showed was also present in a maximum frequency of 22.22% in EAC, the highest average percentage of mutations per patient in it was rarely detected in ESCC and STAD, showing a regions affected by aUPDs (11.79% in EAC and 10.75% in frequency of 10.26% and 9.09%, respectively (Fig. 1). In con- ESCC), while STAD, READ and COAD cohorts presented trast, these two latest cohorts showed high frequencies of copy 10.60%, 8.15% and 6.74% of mutated genes simultaneously number losses at this region of chromosome 5q (61.54% in affected by aUPD, respectively. ESCC and 38.84% in STAD) (Supporting Information Subsequently, we integrated the mutational status of genes Fig. S2A and C). Additional regions of interest were those that with CNA and aUPD profiles for each tumor type (Table 1, showed high frequency of aUPD but rarely involved any Fig. 1 and Supporting Information Figures S3-S7). To do this chromosome loss, such as 6p25.3-p21.1 (15.09%) and analysis, only genes with mutational frequencies over 7% in 17q21.32-q25.3 (19.05%) in COAD and READ, respectively each specific tumor type and a minimum threshold of aUPD (Supporting Information Table 1). was set at 10% were considered. In addition, an adjusted p value was calculated to statistically assess the association of Functional consequences of aUPDs on cancer-related genes each mutated gene with its presence at the site of aUPD or In order to explore whether aUPDs contributed to the inacti- CNA. Our results indicated that TP53 was simultaneously vation of TSGs and the activation of oncogenes, we assessed mutated and affected by aUPD across all GI cancers. For whole exome sequencing data from all five tumor types. Only example, 69.23% of the EAC samples which showed a muta- high-impact variants (i.e., protein truncating and damaging tion at TP53 also presented aUPD affecting 17p13.1 (q value < missense mutations) were considered in this analysis. Our 10−9). Moreover, a mutation in this TSG accompanied by a results indicated that the STAD cohort (N = 120) displayed copy number loss was also detected in all GI cancers. In con- the highest amount of mutations, including SNVs and trast to the aforementioned example in EAC, 73.6% of COAD INDELs, per sample (average of 173.33). The average number samples with a mutation at TP53 also displayed simultaneous of mutations per sample corresponding to the COAD copy number loss at 17p13.1 (q value <10−9). Therefore, our Int. J. Cancer: 144, 513–524 (2019) © 2018 The Authors. International Journal of Cancer published by John Wiley & Sons Ltd on behalf of UICC. Torabi et al. 519 Cancer Genetics and Epigenetics Figure 2. Quantification of aUPDs in highly aneuploid and near-diploid tumors. Box-plots showing significant differences between highly aneuploid and near-diploid genomes for (a) all aUPD events in the FISH-validated ploidy assessment CRC sample set, (b) all aUPD events in TCGA cohorts, (c) whole-chromosome aUPDs in TCGA cohorts and (d) segmental aUPDs in TCGA cohorts. The Mann–Whitney sum-rank test was used to compare number of aUPD events between the two groups of genome ploidies. analysis suggested that tumor samples with mutated TP53 statistically significant for KRAS in COAD and READ showed either aUPD or genomic losses as “second hit” events (15.05% and 19.35%, respectively, q value <10−9) and for ranging from 75% to 93.6% across all GI cancers. Addition- NRAS in READ (22.22%, q value = 8.4 × 10−6), and showed a ally, our analysis also revealed several examples of aUPD- tendency for PIK3CA in STAD (21.43%, q value = 0.0728). mediated inactivation of TSGs in a tumor-type dependent manner. Of note, 34.92% of rectum and 22.29% of colon ade- aUPD is frequently detected in highly aneuploid genomes nocarcinomas showing an inactivating mutation at APC also Aneuploid genomes are common in cancer; we therefore displayed aUPD events at 5q22.2 (q value <10−9). In contrast, assessed to which extent the total DNA content contributes to 15.86% and 20.57% of samples with mutated APC displayed the generation of aUPD events. First, we sought to infer the copy number losses in READ and COAD, respectively ploidy by performing FISH analysis in a set of 20 colorectal (q value <10−9). Besides TP53, NOTCH1 and PTCH1 were the adenocarcinomas from Hospital Clínic of Barcelona/IDIBAPS most frequently mutated genes involved in regions of aUPD Biobank. We quantified copy numbers of chromosomes 7, 15, in ESCC. While 75% of the samples showing an inactivating 18 and 20 using centromere specific probes. Our results mutation in NOTCH1 also presented aUPD at 9q34.3 showed that chromosomes 7 and 20 were recurrently gained (q value = 5.5 × 10−9), aUPD events at 9q22.32 were affecting with a median of 3.48 copies for chromosome 7 (range from all samples with mutated PTCH1 (q value <10−9). No samples 2.02 to 5.07) and 3.24 copies for chromosome 20 (range from with copy number losses affecting either of these two genes 1.88 to 6.01). On the other hand, chromosome 18 was mostly when mutated were detected. Finally, the second most lost showing a median of 1.49 copies (range from 1.09 to frequently inactivated gene in STAD was ARID1A. The chro- 3.45). Chromosome 15 showed a median of 1.91 copies (range mosome region containing ARID1A, 1p35.3, was rarely from 1.18 to 3.16) (Supporting Information Fig. S8A). In affected by copy number losses (3.70%, n.s.), but often affected order to infer the genome ploidy based on the FISH counts, by aUPD (14.81%, q value = 0.019). Although APC was also we used the weighted mean copy number of all chromosomes mutated in STAD (7.76%), the frequency of aUPD was lower analyzed in each sample. By applying this, we detected that than genomic copy number losses (22.22%, n.s. vs. 44.44%, 60% of samples showed highly aneuploid genomes, which q value = 0.0073) in this cancer type. were defined by ploidy values higher than 2.5 (Table 2). Like- Despite the high prevalence of TSGs in regions of aUPD, wise, applying ASCAT to this sample set, we identified 50% of our analysis also unveiled that several well-known oncogenes cases with a highly aneuploid genome. The correlation were affected by aUPD. This was the example of KRAS in between FISH data and DNA ploidy provided by ASCAT was COAD and READ, NRAS in READ and PIK3CA in STAD statistically tested (r = 0.6; p < 0.01) (Supporting Information (Table 1). Indeed, the frequency of aUPD as “second hit” was Fig. S8B). Out of 20 cases, only four showed discrepancy Int. J. Cancer: 144, 513–524 (2019) © 2018 The Authors. International Journal of Cancer published by John Wiley & Sons Ltd on behalf of UICC. 520 Genomic integration of aUPD and mutational status Table 2. FISH assessment and ASCAT ploidy Sample Chr. 71 Chr. 151 Chr. 181 Chr. 201 FISH ploidy2 ASCAT ploidy 2T 3.21 n.a. 1.61 n.a. 2.41 2.24 5T 4.42 1.79 1.63 2.30 2.53 1.93 6T 3.73 3.16 1.53 4.39 3.20 3.87 8T 3.38 1.18 1.16 2.83 2.14 2.89 9T 3.56 1.48 1.56 3.75 2.59 2.14 10T 2.95 1.90 1.09 1.99 1.98 1.98 11T 3.92 2.24 1.49 5.39 3.26 3.59 12T 2.38 n.a. 3.45 n.a. 2.92 4.04 13T 3.76 1.81 1.45 4.37 2.85 4.29 33T 3.12 1.83 1.19 1.88 2.01 2.10 37T 3.59 n.a. 1.62 n.a. 2.61 3.29 40T 2.68 1.80 1.48 2.07 2.01 1.97 41T 5.07 2.10 1.32 6.01 3.63 2.37 Cancer Genetics and Epigenetics 42T 4.63 1.46 1.67 3.24 2.75 3.33 43T 3.21 2.11 1.19 2.90 2.35 2.37 44T 2.22 3.01 1.74 3.69 2.67 2.68 45T 3.99 2.16 1.47 4.95 3.14 4.24 46T 3.39 2.15 1.35 2.69 2.39 2.15 47T 2.02 n.a. 1.96 n.a. 1.99 2.45 50T 3.81 n.a. 1.41 n.a. 2.61 3.31 n.a., not available. 1 Values indicated are weighted means of copy number for the corresponding chromosome. 2 Average of chromosomes 7, 15, 18 and 20. between the two approaches. We then aimed at comparing events, four corresponding to healthy controls (0.795%) and the frequency of aUPD events in highly aneuploid genomes nine to CRC patients (1.204%) (Table 3). By performing the versus near-diploid samples. We could show that aUPD events same analysis in the colon and rectum adenocarcinoma data- were more frequently observed in highly aneuploidy genomes sets from TCGA, frequencies of mosaic structural rearrange- (p < 0.01) (Fig. 2a). ments were 0.88 and 1.89, respectively. No significant Next, we explored the ploidy computed by ASCAT in differences were observed after adjusting for gender and age TCGA cohorts. We observed that COAD and STAD samples groups, most likely due to the small sample size. With the showed the lowest genome ploidy, with a median of 2.44 and exception of a focal, 1.07 Mb deletion at 13q14, only alterations 2.60, respectively. On the other hand, READ showed a median larger than 2 Mb were considered. In the EPICOLON cohort of 2.96, and ESCA showed a median of 3.07. When comparing we detected five UPDs (four patients and one control), six the frequency of aUPD events in highly aneuploid versus genomic losses (four patients and two controls), one duplica- near-diploid genomes, our results confirmed that highly aneu- tion (one control) and one trisomy (one patient). The most ploid tumors displayed a significantly higher amount of aUPD clonal event was the loss of chromosome region 5q14.1-q33.1 events than near-diploid tumors (p < 0.001) (Fig. 2b). In addi- in a control individual, which appeared in 59% of cells tion, when aUPD events were classified in whole chromosome (Fig. 3a). Chromosome arms affected by UPD included 5q, 9p, and segmental aUPDs, we also detected that the number 11p and 17p in CRC patients, and 20q in a healthy control. On of these events was greater in highly aneuploid tumors the other hand, mosaic deletions were identified at chromo- (p < 0.001 for whole chromosome aUPDs and p < 0.0001 for some arms 1q, 18p, 10q and 13q in patients with CRC segmental aUPDs) (Fig. 2c and D). (Fig. 3b), and 5q and 2p in healthy controls. When material was available, we attempted to validate the rearrangements, Mosaic UPD events are present in CRC patients either by MLPA or microsatellite markers (Table 3). For exam- Constitutive UPD was assessed using DNA extracted from ple, UPD events at 11p15.5-p15.1 and at 17p13.3-p11.2 were peripheral blood lymphocytes of the EPICOLON cohort, which confirmed by microsatellite analysis in the peripheral blood consisted of 1,250 individuals, including 503 healthy controls DNA (Fig. 3c and d). Similarly, a deletion at 10q22.3-q23.2 was and 747 CRC patients. By estimating LRR and BAF values validated by MLPA in the peripheral blood DNA, and identi- from genome-wide association studies SNP 6.0-array data, our fied in both the normal colon mucosa and in the correspond- analysis resulted in the identification of 13 clonal mosaic ing primary tumor of the same patient. Genes reported in the Int. J. Cancer: 144, 513–524 (2019) © 2018 The Authors. International Journal of Cancer published by John Wiley & Sons Ltd on behalf of UICC. Torabi et al. 521 Table 3. Summary of mosaic rearrangements Case/control Rearrangement Cytoband1 Chr Start Stop Size (Mb) Clonality Validation Control Deletion 5q14.1-q33.1 5 82,926,332 151,852,840 68.93 59% MLPA Control UPD 20q11.23-q13.33 20 36,224,534 62,912,463 26.69 17% n.d. Control Duplication 20q11.21-q13.13 20 30,691,943 49,777,691 19.09 29% n.d. Control Deletion 2p24.1-p23.3 2 23,298,851 25,421,803 2.12 57% n.d. Case Trisomy 12p13.33-q24.33 12 0 133,851,895 133.85 15% n.d. Case UPD 17p13.3-p11.2 17 6,689 17,344,122 17.34 36% MS Case UPD 11p15.5-p15.1 11 198,510 21,002,580 20.80 30% MS Case Deletion 13q14.2-q14.3 13 50,394,625 51,461,086 1.07 40% MLPA Case Deletion 10q22.3-q23.2 10 81,685,024 89,167,880 7.48 49% MLPA Case UPD 5q14.3-q23.1 5 89,863,279 120,267,945 30.40 12% n.d. Case UPD 9p24.3-p24.1 9 46,587 5,731,315 5.68 14% n.d. Case Deletion 1q21.1-q21.2 1 144,988,936 147,823,776 2.83 28% n.d. Case Deletion 18p11.21 18 12,033,735 14,920,039 2.89 23% n.d. Cancer Genetics and Epigenetics 1 Cytobands and genomic coordinates according to genome build GRCh37/hg19. Abbreviations: MLPA, multiplex ligation-dependent probe amplification analysis; MS, microsatellite analysis; n.d., not determined. COSMIC Cancer Gene Census (https://cancer.sanger.ac.uk/ to result from postzygotic mitotic recombination at the sites of census) catalog that are located at genomic regions affected by high sequence homology.39 In fact, the positioning of chromo- mosaic rearrangements are displayed in Supporting some breakpoints at 5q involving segmental aUPDs in the Information Table 2. COAD and READ cohorts were located at 70–80 Mb (Supporting Information Fig. S9), which coincided with sites of Discussion meiotic recombination (data not shown). This association is in In the present study, we have performed the largest systematic agreement with previous findings in familial adenomatous integrative analysis of somatically acquired UPD with the polyposis patients, were similar genomic breakpoints were mutational status of genes located at regions affected by aUPD detected and were also associated with mitotic recombination in the five most frequent GI cancers, including esophageal ade- events.40 Therefore, it might be plausible to rationalize that in nocarcinomas, esophageal squamous cell carcinomas, stomach, highly aneuploid genomes, nonrandom nuclear topology of colon and rectum adenocarcinomas. Our results uncovered homologous chromosomes enables higher chances of mitotic that GI cancers exhibit a high incidence of aUPD events. In recombination events. particular, we could show that STAD, EAC and ESCC carried The integrative analysis of regions affected by aUPD and the significantly different patterns of aUPD compared to COAD mutational status of genes within these regions revealed evi- and READ, thus suggesting the existence of cancer-specific dence that aUPD acts as a “second hit” to inactivate TSGs. Spe- landscapes of aUPD across GI cancers. As observed for CNAs, cifically, our results confirmed that aUPD events represent an aUPD profiles in the COAD cohort matched with those identi- important mechanism to functionally inactivate APC in colon fied in READ samples, which is in agreement with previous and rectum adenocarcinomas.11,18,34,41–43 Therefore, these reports.11,18,33–35 Remarkably, the high rate of segmental aUPD results further strengthen the hypothesis that colorectal tumor in STAD and ESCA suggests higher levels of structural CIN in cells strive to maintain a disomy for chromosome 5 despite the these cancer types compared to COAD and READ, which benefit of inactivating APC. In contrast to CRC, the loss of 5q in agrees with a previous study showing more focal amplification STAD is twice as high as the frequency of aUPD, suggesting dif- events in the upper than in the lower GI tract.36 Furthermore, ferent mechanisms to achieve the biallelic inactivation of APC. most GI cancers contain aneuploid genomes.37 Our experi- Moreover, we also identified inactivation of NOTCH1 driven by mental and computational assessment of the genome ploidy aUPD at chromosome arm 9q as the “second hit” in ESCC. confirmed that highly aneuploid tumors display an increased Although aUPD at chromosome arm 9q was also detected at number of aUPD compared to near-diploid tumors, affecting high frequency in EAC, mutations in NOCTH1 were not both whole chromosomes and segments of chromosomes. In observed in this tumor type, suggesting that mutations in other fact, whole chromosome UPD may originate from pre- or post- genes might contribute to the positive selection of this event in zygotic chromosome segregation defects.3 A recent report has EAC. While SNVs affecting NOTCH1 have been previously speculated that inappropriate activation of RNA interference reported in ESCC, they have not been widely described in (RNAi) machinery and meiotic gene expression might induce EAC.44 Copy-number neutral LOH affecting NOTCH1 has been UPD in fission yeast.38 Whether dysfunctional meiotic cohe- described in head and neck squamous cell carcinoma; however, sins or genes involved in RNAi in cancer cells induce aUPD no association between aUPD and gene mutation has been pre- remains elusive. On the other hand, segmental aUPD appears viously established.45 In fact, the inactivation of NOTCH1 has Int. J. Cancer: 144, 513–524 (2019) © 2018 The Authors. International Journal of Cancer published by John Wiley & Sons Ltd on behalf of UICC. 522 Genomic integration of aUPD and mutational status Cancer Genetics and Epigenetics Figure 3. Representative mosaic rearrangements further validated by MLPA or microsatellite analysis. Plots resulting from the MAD method showing the signal intensity Log R ratio (LRR) as black dots (left Y-axis) and the B allele frequency (BAF) as red dots (right Y-axis) in the EPICOLON cohort. In the X-axis are displayed the Mb position according to the Human GRCh37/hg19 genome assembly. (a) Mosaic deletion at 5q in a healthy control validated by MLPA SALSA P043-D1 probemix in the peripheral blood DNA. (b) Focal deletion at 13q in a CRC patient validated by MLPA SALSA P037-B1 probemix in the peripheral blood DNA. (c) Mosaic UPD at 11p in a CRC patient validated by microsatellite analysis in the peripheral blood DNA. The figure shows electrophoretograms of two STR markers, D11S1338-VIC within the region of UPD at chromosome 11 and D11S935-FAM in a normal region of this chromosome. (d) Mosaic UPD at 17p in a CRC patient validated by microsatellite analysis in the peripheral blood DNA. Electrophoretograms of two STR markers, D17S1852-FAM within the region of UPD at chromosome 17 and D17S798-VIC in a normal region of this chromosome, are indicated. In both panels, the X-axis shows the length of the PCR products (bp) determined using the GeneScan 500 ROX dye Size Standard, and the Y-axis shows fluorescence intensity in relative fluorescence units (RFU). [Color figure can be viewed at wileyonlinelibrary.com] Int. J. Cancer: 144, 513–524 (2019) © 2018 The Authors. International Journal of Cancer published by John Wiley & Sons Ltd on behalf of UICC. Torabi et al. 523 been reported in about 10% of patients with tumors of squa- there is the need to perform integrative analysis of aUPD with mous origin, including skin, oral cavity, esophageal and lung, methylation profiling and gene expression to unveil their suggesting that Notch signaling regulates these cancers.46 Other functional consequences. genes at 9q affected by aUPD in ESCC involved Patched In addition to aUPD in tumor cells, we also observed con- 1 (PTCH1), a gene that has been previously found mutated in a stitutive UPD events in the peripheral blood lymphocytes of region with aUPD in basal cell carcinomas.47 Furthermore, our CRC patients and healthy individuals. This finding is in agree- results indicated that ARID1A is the second most frequently ment with previously published data suggesting that large inactivated TSG in the STAD cohort, and is frequently affected structural genetic mosaicism was associated with aging and by aUPD as the “second hit”. ARID1A is a subunit of the various types of solid tumors.6,56,57 In fact, chromosomal SWI/SNF chromatin remodeling family, regulating the tran- mosaic events have been recently described in patients with scription of MYC and other genes.48 Inactivating mutations of cancer predisposing disorders, such as Fanconi anemia.58 this TSG have been previously described, especially in gastric Here, we show a possible relationship between clonal mosai- cancer.49 Despite the fact that we identified aUPD events in cism and CRC. Using the EPICOLON cohort, we identified chromosome arms 11q and 12q in STAD, mutated genes were mosaic UPD in CRC patients affecting genomic regions not present in these regions.50 Finally, we detected that TP53 5q14.3-q23.1, 11p15.5-p15.1, 17p13.3-p11.2 with known CRC- was ubiquitously inactivated by aUPD across all GI cancers. related genes such as APC, IGF2 and TP53, respectively, and a Cancer Genetics and Epigenetics Previous reports assessing LOH at the TP53 locus in ESCC have copy number loss at 13q14.2-q14.3 involving the putative already shown copy-number neutral LOH in TP53 mutant TSGs DLEU7, DLEU1, DLEU2 and the microRNAs mir-15a tumors.15 aUPD events at 17p have been identified in other can- and miR-16-1, implicated in B-cell chronic lymphocytic leuke- cer types such as glioblastoma,51 pediatric adrenocortical mia.59 Lastly, a previously identified ~7.4 Mb mosaic deletion tumors,52 diffuse large B cell lymphoma,53 and in patients with at 10q22.3- q23.2 in a patient with early onset CRC involving newly diagnosed myelodysplastic syndromes.54 Interestingly, the BMPR1A gene has been validated and confirmed in the aUPD may also play a crucial role in activating cancer-related normal colon mucosa and in the primary tumor.60 Whether genes. In our analysis, the well-known oncogenes KRAS, NRAS these mosaic structural alterations identified in the peripheral and PIK3CA were frequently affected by aUPD. Copy number blood lymphocytes play a causative role in the cancer etiology gains for KRAS and PIK3CA are common in COAD, READ and requires further exploration. STAD; however, NRAS is barely gained in READ, suggesting that aUPD is the main genetic mechanism to achieve homozy- Acknowledgements gous activation of this gene.55 Altogether, even though we can- The authors would like to thank Dr. Javier del Rey for technical assistance, and Dr. Eva Hernández-Illán for critical reading of the study. 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