REGULAR ARTICLE Detectable clonal mosaicism in blood as a biomarker of cancer risk in Fanconi anemia Judith Reina-Castillón,1-3 Roser Pujol,3,4 Marcos López-Sánchez,1,2,5 Benjamı́n Rodrı́guez-Santiago,1,2,6 Miriam Aza-Carmona,3,4 Juan Ramón González,1,5,7 José Antonio Casado,3,8,9 Juan Antonio Bueren,3,8,9 Julián Sevilla,10 Isabel Badel,11 Albert Català,12 Cristina Beléndez,13 Marı́a Ángeles Dası́,14 Cristina Dı́az de Heredia,15 Jean Soulier,16-18 Detlev Schindler,19 Luis Alberto Pérez-Jurado,1-3 and Jordi Surrallés3,4,20 1 Department of Experimental and Health Sciences, Universitat Pompeu Fabra, Barcelona, Spain; 2Hospital del Mar Research Institute, Barcelona, Spain; 3Centro de Investigación Biomédica en Red de Enfermedades Raras, Barcelona, Spain; 4Department of Genetics and Microbiology, Universitat Autònoma de Barcelona, Bellaterra, Spain; 5Centre for Research in Environmental Epidemiology, ISGlobal, Barcelona, Spain, 6qGenomics Laboratory, Esplugues de Llobregat, Spain; 7Centro de Investigación Biomédica en Red de Epidemiologı́a y Salud Pública, Barcelona, Spain, 8Division of Hematopoietic Innovative Therapies, Centro de Investigaciones Energéticas, Medioambientales y Tecnológicas, Madrid, Spain; 9Instituto de Investigación Sanitaria Fundación Jiménez Dı́az, Madrid, Spain; 10Hematology Service, Hospital Niño Jesús, Madrid, Spain; 11Pediatrics Service, Hospital de la Santa Creu i Sant Pau, Barcelona, Spain; 12Hematology Service, Hospital Sant Joan de Déu, Esplugues de Llobregat, Spain; 13Oncohematology Service, Hospital Gregorio Marañón, Madrid, Spain; 14Hematology Service, Hospital Universitario la Fe, Valencia, Spain, 15Hemato-Oncology Service, Hospital Maternoinfantil Vall d’Hebron, Barcelona, Spain; 16Institute of Hematology, Université Paris-Diderot, Sorbonne Paris Cité, Paris, France; 17INSERM, Unité Mixte de Recherche 944, and 18Centre National de la Recherche Scientifique, Unité Mixte de Recherche 7212, Saint-Louis Hospital, Paris, France; 19Department of Human Genetics, University of Würzburg, Würzburg, Germany; and 20Genetics Department, Hospital de la Santa Creu i Sant Pau, Barcelona, Spain Detectable clonal mosaicism for large chromosomal events has been associated with aging and an Key Points increased risk of hematological and some solid cancers. We hypothesized that genetic cancer • Fanconi anemia pa- predisposition disorders, such as Fanconi anemia (FA), could manifest a high rate of tients have exacerbated chromosomal mosaic events (CMEs) in peripheral blood, which could be used as early biomarkers cytogenetic clonal mo- of cancer risk. We studied the prevalence of CMEs by single-nucleotide polymorphism (SNP) array saicism as detected by in 130 FA patients’ blood DNA and their impact on cancer risk. We detected 51 CMEs (4.4-159 Mb molecular karyotyping in size) in 16 out of 130 patients (12.3%), of which 9 had multiple CMEs. The most frequent events of blood DNA with SNP were gains at 3q (n 5 6) and 1q (n 5 5), both previously associated with leukemia, as well as assays. rearrangements with breakpoint clustering within the major histocompatibility complex locus • Bone marrow clonal (P 5 7.3 3 1029). Compared with 15 743 age-matched population controls, FA patients had a 126 abnormalities can be to 140 times higher risk of detectable CMEs in blood (P , 2.2 3 10216). Prevalent and incident detected in blood DNA hematologic and solid cancers were more common in CME carriers (odds ratio [OR] 5 11.6, 95% and used as biomarkers confidence interval [CI] 5 3.4-39.3, P 5 2.8 3 1025), leading to poorer prognosis. The age-adjusted of cancer risk and poor prognosis. hazard risk (HR) of having cancer was almost 5 times higher in FA individuals with CMEs than in those without CMEs. Regarding survival, the HR of dying was 4 times higher in FA individuals having CMEs (HR 5 4.0, 95% CI 5 2.0-7.9, P 5 5.7 3 1025). Therefore, our data suggest that molecular karyotyping with SNP arrays in easy-to-obtain blood samples could be used for better monitoring of bone marrow clonal events, cancer risk, and overall survival of FA patients. Introduction Mosaicism is the coexistence of cells with different genetic composition within an individual, caused by postzygotic mutations during development that are propagated to a subset of adult cells.1 The frequency Submitted 29 August 2016; accepted 11 December 2016. DOI 10.1182/ The full-text version of this article contains a data supplement. bloodadvances.2016000943. © 2017 by The American Society of Hematology The SNP array analyses reported in this article have been deposited in the Gene Expression Omnibus data repository (https://www.ncbi.nlm.nih.gov/geo/, accession numbers GSE93692 and GPL22924). 24 JANUARY 2017 x VOLUME 1, NUMBER 5 319 of mosaicism is likely underestimated because somatic events may other complementation groups, and 8.5% not yet classified). DNA of a not be associated with phenotypic effects or may be negatively paraffin-embedded sample of FA013 (anal SCC) was extracted by using the selected.2-4 However, mosaicism can contribute to tumor develop- QIAamp DNA FFPE Tissue Kit (Qiagen, Inc). Reverse mosaicism was ment resulting from the accumulation of events, which can serve as studied by the quantification of chromosome fragility in FA cells following diepoxybuthane or mitomycin C assays. Reverse mosaicism was considered tumor markers during clonal evolution or arise as a consequence of when chromosomal aberrations were observed in ,50% of the cells after the malignancy itself.2,3,5 Although the identification of mosaic diepoxybuthane treatment.13 Studies were all performed under institutional events will greatly benefit from single-cell analyses, chromosomal review board–approved protocols by the involved research centers. rearrangements .1 to 2Mb can also be inferred from studies of DNA from cell populations by genome-wide single-nucleotide SNP array analyses polymorphism (SNP) genotypes when the proportion of clonally DNA samples were analyzed with the SNP arrays Illumina Human1M-Duo v3 affected cells is larger than a certain threshold, that is, 7% to 18% (;1 000 000 SNP probes, 17 samples), HumanOmniExpressExome-8 v1.2 depending on the type of rearrangement and the quality of the (;960 000 SNP probes, 1 sample), HumanOmniExpress-12 v1-BeadChip array.6 In this context, the term “detectable clonal mosaicism” refers (;730 000 SNP probes, 96 samples), or InfiniumHumanCore-12 v1 (;250 000 to chromosomal mosaic events (CMEs) that occur in a proportion of SNP probes, 16 samples), at the Spanish National Center for Genotyping. A total of 9 samples from FA patients with CMEs were also analyzed with cells sufficient for their detection. This operational term underes- Illumina InfiniumHumanCore-12 v1 (;250 000 SNP probes). The detection timates the true rate of CMEs. The frequency of detectable CMEs in of mosaic rearrangements was based on the assessment of allelic imbalance autosomes is low in individuals ,50 years (,0.5%), but it has been and copy number changes using the Mosaic Alteration Detection (MAD) shown to increase with age and to be strongly associated with a algorithm implemented in R Genomic Alteration Detection Analysis software.6 higher risk of hematological cancer (OR 5 22-30) and slightly We defined the breakpoint interval for each CME as the region located related to some solid tumors (OR 5 4).2,3,7 The frequency of CMEs between 2 informative SNP probes (the first probe within and outside the is also higher in conditions of accelerated aging, such as type 2 event). We restricted the search to breakpoints mapped to intervals diabetes, with a higher prevalence of cardiovascular complications ,200 Kb in order to compare our results with reported data generated with among individuals with CMEs.8 SNP arrays of lower probe density. Then, we analyzed putative enrichment We hypothesized that genome instability disorders with impaired on genomic features at these regions by calculating the percentage of total breakpoint interval length overlapping with each genomic feature (segmental DNA repair, such as FA, could show a higher rate of CMEs at an duplications [SD], copy number variants [CNV], genes, and meiotic early age and that CME detection could herald the high risk of recombination hotspots [MRH]), and comparing these values with the hematological and mucosal cancers in these patients. FA is a rare, established distribution of each genomic feature in the human genome genetic tumor predisposition disease characterized by impaired (University of California, Santa Cruz genome browser [http://genome.ucsc.edu/ DNA interstrand crosslink repair and secondary genomic and cgi-bin/hgGateway] and HapMap database [http://hapmap.ncbi.nlm.nih.gov/]). chromosomal instability.9 The diagnostic hallmark of FA is increased The cellular proportion with a specific rearrangement was calculated by chromosomal breakage when patients’ cells are cultured with using the b allele frequency (BAF) split in the altered region. The formulae diepoxybuthane or mitomycin C. There are at least 21 FA and FA- used to obtain the cellular proportion for each event type (gain, loss, like genetic subtypes, each one resulting from mutations in distinct uniparental disomy [UPD]) was reported elsewhere.4 To calculate the FA genes.9,10 FA patients clinically present with some congenital proportion of cells for mosaic multicopy gains with allelic imbalance malformations, progressive bone marrow failure (BMF), and cancer (genotypes AAA/B and A/B), we adjusted the previous formulae (G2 susceptibility,11 particularly hematologic malignancies and typical [proportion of cells with a 2-copy gain] 5 Bdev/[0.5 – Bdev]), where Bdev is solid tumors, including head, neck, esophageal, and gynecological the deviation from the expected BAF value of 0.5 for heterozygous SNPs, squamous cell carcinomas (SCC) and treatment-related liver and also included the dosage values estimated by the average log R ratio tumors. Given the extraordinary risk of hematological and mucosal (LRR) signal in the region. In some tetrasomies without allelic imbalance (genotypes AA/BB and A/B), there is not a BAF split, and the proportion of cancers at early ages, stringent follow-up protocols are recom- cells cannot be calculated by using BAF values. In these cases, we only used mended for FA patients, including periodic bone marrow biopsies, the median-adjusted LRR signal of the region to obtain the cellular proportion. starting in the first decade of life.12 Because of the invasiveness of The LRR signal in detected events was adjusted by the autosomal average these control tests, clinical follow-up of some patients is difficult. LRR in samples with only 1 CME. In samples with multiple events, the LRR Thus, less invasive but equally effective screening approaches signal was adjusted by the average LRR in a region of the same chromosome would be useful to improve the quality of life of FA patients during without structural variants. Considering that nonmosaic simple gain (AA/B) their medical follow-up. In this study, we investigated the detection has the same genetic dosage as a mosaic tetrasomy in a 0.5 proportion of of cytogenetic events in blood DNA by molecular karyotyping and cells (genotypes AA/BB or AAA/B and A/B), we can define the function whether the presence of such abnormal events is a prognostic between the LRR and cellular proportion as half the function in simple gains. biomarker for leukemia, solid cancer, and survival in FA. Control datasets In order to estimate the frequency of CMEs in the population of patients ,18 Methods years old and between 19 and 50 years old, we analyzed SNP array data obtained from blood DNA of unaffected individuals (siblings and parents) Patient cohort and samples from several datasets: (1) the Simons Simplex Collection (https://sfari.org/),14 Total genomic DNA was extracted from peripheral blood samples from 130 a characterized sample consisting of 2644 families of autistic probands that FA patients by using a standard phenol–chloroform extraction method or the includes nonaffected parents and siblings; we analyzed SNP array data Puregene DNA Isolation Kit (Qiagen, Inc). There was no cell fractionation (Illumina Human 1MDuo and Omni2.5) of 2209 children (siblings) and 4354 other than red cell lysis before DNA extraction. All patients (mean age: 14.4 parents; (2) the Autism Genome Project (https://www.autismspeaks.org/ years old, range: 0-50 years old) had been diagnosed with FA based on science/initiatives/autism-genome-project),15 which consists of 2611 fam- clinical criteria and a positive chromosome fragility test followed by genetic ilies, each one with a child affected by an autism spectrum disorder and complementation and mutational analysis (67.4% with FANCA, 24.1% from nonaffected parents; we analyzed SNP array data (Illumina Human 1M) of 320 REINA-CASTILL ÓN et al 24 JANUARY 2017 x VOLUME 1, NUMBER 5 A Y B X 1 MultiGain; R 2=0.98; Adj–R 2=0.99 22 0.5 21 2 Gain; R 2=0.94; Adj–R 2=0.95 20 UPD; R 2=–0.03; Adj–R 2=0.14 0.4 Loss; R 2=0.96; Adj–R 2=0.96 19 0.3 18 3 log2 intensity ratio (LRR) 0.2 17 0.1 16 4 0.0 15 –0.1 14 –0.2 5 –0.3 13 –0.4 6 12 –0.5 11 7 0 10 20 30 40 50 60 70 80 90 100 10 8 9 Cell fraction of abnormal cells (%) Figure 1. Genomic distribution of CMEs in FA patients. (A) Genomic distribution of the 51 CMEs detected in blood DNA of 16 of 130 FA patients. The circular plot shows the chromosomal location of each of the 51 mosaic events detected (red bars: losses; blue bars: gains; orange bars: multicopy gains; green bars: copy-neutral events or UPDs). (B) Ratios of the dosage values (LRR) as a function of the type of rearrangement and the estimated fraction of cells. LRR signals follow a linear correlation with the percentage of cells with mosaicism for each type of rearrangement (losses, copy-neutral events or UPDs, gains, and multicopy gains). 4086 parents (between 19 and 50 years old); and (3) we added the between the year of diagnosis of the first cancer after blood sample published data also generated with the MAD algorithm as described above collection and the year of blood sample collection in individuals with cancer from the Avon Longitudinal Study of Parents and Children (http://www. development; in those cancer-free FA patients, cancer-free time was bristol.ac.uk/alspac/) (N 5 3290 children) and the Twins Early Development calculated as the difference between the year of the last clinical examination Studies (http://www.teds.ac.uk/) (N 5 1804 children).16 or the year of exitus (when it occurred) and the year when the blood sample was obtained. A total of 6 out of 130 FA patients were excluded from the Microsatellite analyses cancer-free time analysis due to incomplete information. In addition, in order Microsatellites were amplified from blood and tumor DNA by standard to evaluate the real incidence of cancer after sample collection, 15 out of polymerase chain reaction protocols, and the products were analyzed on an 124 FA patients were excluded from the cancer-free time reanalysis ABI PRISM 3100 genetic analyzer according to the manufacturer’s instructions. because of having cancer (n 5 14) or dying (n 5 1) at the time of sample For relative allelic peak quantitative analysis, trace data were retrieved by using collection. Age-adjusted cancer risk was computed by using a Cox the accompanying software (GeneScan, Applied Biosystems). proportional hazard model, including CMEs and age as covariates. Overall survival was also analyzed using Cox proportional hazard models. Multiplex ligation-dependent probe amplification Approximately 100 ng of genomic DNA from each sample was subjected Results to multiplex ligation-depended probe amplification (MLPA) using 2 com- mercial panels with multiple subtelomeric probes (P036-E1 and P070-B2) Exacerbated clonal mosaicism in FA blood samples according to the manufacturer’s instructions (MRC-Holland, Amsterdam, We evaluated the presence of CMEs in peripheral blood DNA of The Netherlands). Each MLPA signal was normalized and compared with the 130 FA patients (mean age: 14.5 years old, range: 0-50 years old), corresponding mean peak height obtained from 2 control DNA samples. previously collected for the purpose of genetic diagnosis. SNP Statistical analyses arrays were used to build molecular karyotypes that were analyzed with the MAD software.6 In total, 16 out of 130 FA patients (12.3%) Statistical tests for 2 3 2 tables comparing CME prevalence for FA had detectable CMEs that were 4.4 to 159 Mb in size (Figure 1, individuals and controls were based on Fisher’s exact test due to the small Table 1; supplemental Table 1). Five of the CME carriers (5/91, numbers. P values, odds ratios (ORs) and 95% confidence intervals at were computed using the Fisher’s test R function.17 Binomial or Bernoulli 5.5%) were children or adolescents ,18 years old, whereas distribution was used to compute the probability of observing a number 11 (11/39, 28.2%) were in the 19- to 50-years-old range. The mean of chromosomal breakpoints in a defined genomic region, for example, age at the time of sample collection was 23.2 years for the group n the MHC region, by chance. The formula was pðX 5 kÞ 5 k pk ×qn 2 k ; Æ æ with CMEs and 13.3 years for the group without CMEs. Although Æ æ n k 5 k!ðn 2 kÞ!, where n was the number of experiments (breakpoint intervals), n! there is information from multiple case-control studies of cancer,7 k was the number of succeeds (breakpoint intervals overlapping with the we analyzed an age-matched, healthy population of 15 743 controls MHC region), p was the probability of succeeding (size of the MHC region with SNP arrays of similar density and used the same methods to versus the whole genome), and q was the probability of failure (1 – p). establish unbiased risks in FA. The frequency of detectable CMEs in To estimate the survival function from lifetime data, we used the Kaplan- the general population of individuals ,18 years old was 0.04% Meier estimator.18 Here, cancer-free time was calculated as the difference (3/7,303) and was 0.3% (26/8,440) in individuals between 19 and 24 JANUARY 2017 x VOLUME 1, NUMBER 5 CLONAL MOSAICISM AND CANCER IN FANCONI ANEMIA 321 322 Table 1. Features of the 16 FA individuals with CMEs Years from DNA Genetic CMEs (size Start End Cell fraction Age at DNA Clinical features sampling Evolution Sample group in Mb) (Mb) (Mb) (%) sampling (y) (age at BMF in y) to cancer Cancer diagnosis (age in y) (age in y) Cause of death FA466 A UPD 4p (6.6) pter 6.6 9 0.7 BRH, CaLS, BMF (0.7) — None Alive (8) — REINA-CASTILL ÓN et al FA106 A UPD 6p (26.1) pter 26.1 13 15 BMF (8) — None Exitus (22) H1N1 viral infection FA117 A UPD 10q (70.4) 65.1 qter 17 30 BMF (8) 6 AML (36) Exitus (36) BM transplant complications FA648 A Gain 1q (104.3)* cen qter 29 32 BRH, ID, KM, BMF (32) 0 Lymphoma (32) Exitus (32) Lymphoma 041607 A Monosomy 7 pter qter 59 50 GR, BMF (23) 0 Breast (37,45), AML (50) Exitus (50) AML (159.1) FA647 A Gain 3q (36.3)† 161.5 qter 30 4 GIM, BMF (4) 1 MDS (5) Exitus (5) BMF Loss 5q (49.3)† 131.4 qter 32 EGF058 A Gain 1q (76.7) cen 222.8 59 23 GR, BMF (23) 8 HNSCC (31) Exitus (31) Cancer treatment toxicity Gain 3q (64.7) 133.1 qter 27 FA013 A UPD 6p (32.7) pter 32.7 28 24 BRH, CaLS, BMF (7) 10 Anal SCC (34) Exitus (35) Metastatic Anal SCC Gain 6p (22.8) 32.7 55.5 27 FA360 A Gain 1q (102.7)† cen qter 76 30 BMF (13) 0 AML (30) Exitus (30) Multiorganic failure after HSCT Loss 11q (30.4)† 104.5 qter 87 Trisomy 8 (146.1) pter qter 26 Trisomy 9 (141.0) pter qter 27 041869 A Gain 1p (33.5) 18.5 52.0 45 39 GR, BRH, CaLS, KM, BMF (8) 5 Vulvar SCC (27), Exitus (44) Esophagus SCC esophagus SCC (44) Gain 1q (105.9)* cen qter 45 Loss 7q (11.1) 148.0 qter 48 Loss 8p (4.4) pter 4.4 32 FA178 A Loss 1p (29.6) pter 29.6 41 19 CaLS, UHM, BMF (9) 0 AML (19) Exitus (19) AML therapy complications (sepsis) Gain 1p (25.8) 29.6 55.4 39 Gain 3q (63.1)* 134.7 qter 51 Loss 5q (98.7) 82.0 qter 38 Loss 18q (8.8) 69.2 qter 42 Columns contain information about patient, genetic group, detected CMEs including genomic location and type, start and end of each rearrangement and the estimated proportion of affected cells, the age at DNA sampling and BMF, the 24 JANUARY 2017 x VOLUME 1, NUMBER 5 main clinical features, the years from sampling to the first cancer diagnosis, the type of cancer and the evolution including cause of death. (1) A single case with CMEs, 000644, presented reverse mosaicism of the FA mutation in blood. The rearrangements detected by SNP array in blood also found by cytogenetic analysis of BM aspirates are shown in bold and italic letters. AML, acute myeloid leukemia; BM, bone marrow; BMF, bone marrow failure; BRH, bilateral radial hypoaplasia; CaLS: café-au-lait spot; cen, centromere; CM, cardiac malformation; GIM, gastrointestinal malformation; GR, growth restriction; HL, hearing loss; HNSCC, head and neck squamous cell carcinoma; HSCT, hematopoietic stem cells transplantation; ID, intellectual disability; KM, kidney malformation; MDS, myeloid dysplastic syndrome; NoM: no relevant malformation; pter, p terminal; qter: q terminal; UHM, unilateral hand malformation. *Gains of .1 extra copy (triplication-tetrasomy). †Possible unbalanced translocation. ‡Complex rearrangements. Table 1. (continued) Years from DNA Genetic CMEs (size Start End Cell fraction Age at DNA Clinical features sampling Evolution Sample group in Mb) (Mb) (Mb) (%) sampling (y) (age at BMF in y) to cancer Cancer diagnosis (age in y) (age in y) Cause of death FA351 C Loss 3p (4.1) pter 4.1 29 2.7 BMF (2.7) 0.3 AML (3) Exitus (3) AML therapy complications (multiorganic failure) Gain 3q (18.5) 159.7 178.7 69 Gain 3q (18.9)* 178.8 qter 62 Loss 4p (12.3) pter 12.3 50 Loss 6p (28.6) pter 28.6 16 Loss 6q (63.8) 107.1 qter 80 Loss 7p (57.5) pter 57.5 42 Loss 7q (15.3) 143.8 qter 75 Gain 8q (20.6) 56.1 76.7 26 Gain 8q (16.9) 76.7 94.1 56 Gain 8q (52.0) 94.2 qter 32 Gain 13q (93.4) 21.7 qter 19 24 JANUARY 2017 x VOLUME 1, NUMBER 5 UPD 16p (29.7) pter 29.7 73 Loss 18q (20.7) 57.4 qter 36 Gain 21q (12.0) 36.1 qter 29 Gain Xp (42.7) pter 42.7 40 110243 D2 UPD 3p (53.6) pter 53.6 27 22 GR, BRH, HL, ID, KM, BMF (9) — None Alive (27) — FA531 D2 Loss 1p (21.2) pter 21.2 14 26 GR, BRH — None Alive (28) — 000644 D2 Monosomy 7 pter qter 27 27 GR, BRH 0 Vulvar SCC (23), oral premalignant Alive (37) — (1) (159.1) findings (24), AML (27) Loss 12p (27.1)‡ pter 27.1 27 Gain 20p (30.8)‡ pter 30.8 27 Loss 20q (20.6)‡ 30.8 51.4 27 Gain 20q (11.5)‡ 51.4 qter 27 FA072 J Gain 1q (105.8)* cen qter 66 28 CaLS, CM, BMF (20) 2 AML (30) Exitus (31) AML therapy complications (pneumonia) Gain 3q (33.6)* 164.2 qter 98 Loss 6p (29.9)† pter 29.9 51 Gain 16p (22.6)† pter 22.6 44 Columns contain information about patient, genetic group, detected CMEs including genomic location and type, start and end of each rearrangement and the estimated proportion of affected cells, the age at DNA sampling and BMF, the main clinical features, the years from sampling to the first cancer diagnosis, the type of cancer and the evolution including cause of death. (1) A single case with CMEs, 000644, presented reverse mosaicism of the FA mutation in blood. The rearrangements detected by SNP array in blood also found by cytogenetic analysis of BM aspirates are shown in bold and italic letters. AML, acute myeloid leukemia; BM, bone marrow; BMF, bone marrow failure; BRH, bilateral radial hypoaplasia; CaLS: café-au-lait spot; cen, centromere; CM, cardiac malformation; GIM, gastrointestinal malformation; GR, growth restriction; HL, hearing loss; HNSCC, head and neck squamous cell carcinoma; HSCT, hematopoietic stem cells transplantation; ID, intellectual disability; KM, kidney malformation; MDS, myeloid dysplastic syndrome; NoM: no relevant malformation; pter, p terminal; qter: q terminal; UHM, unilateral hand malformation. *Gains of .1 extra copy (triplication-tetrasomy). †Possible unbalanced translocation. CLONAL MOSAICISM AND CANCER IN FANCONI ANEMIA ‡Complex rearrangements. 323 A B Chromosome 6 Chromosome 6 2.0 1.0 2.0 1.0 0.8 0.8 1.0 1.0 0.6 0.6 LRR LRR BAF BAF 0.0 0.0 0.4 0.4 –1.0 –1.0 0.2 0.2 –2.0 0.0 –2.0 0.0 0 25 50 75 100 125 150 0 25 50 75 100 125 150 Position (Mb) Position (Mb) Figure 2. SNP array plots detecting CMEs in a FA patient. Illustrative example of the chromosome 6 plot (black dots represent total intensity values, LRR; red dots represent BAF values) from 1 individual (FA013) whose CMEs (terminal 6p UPD and proximal 6p gain) were both detected by high-density (730 000) (A) and lower-density (250 000) SNP arrays (B). Additional examples are shown in the supplemental annex (supplemental Figures 1 and 2). 50 years old (supplemental Table 2). Thus, the risk of having analyzed by MLPA, whereas different microsatellites were used to detectable mosaicism in FA patients ,18 years was almost 140 quantify allelic balance at heterozygous sites (supplemental Figure 1; times higher than in control individuals (OR 5 139.9, 95% CI 5 supplemental Table 1). Some rearrangements could not be studied 26.8-897.9, P 5 1.37 3 1028), whereas the risk was slightly lower due to sample unavailability. There was a single event discrepant on in FA patients between 19 and 50 years of age (OR 5 126.3, 95% reanalysis likely due to a failure of the validation method. CI 5 51.1-297.9, P , 2.2 3 10216). Out of the 16 FA patients with In addition, we also used lower resolution (;250 000) SNP arrays CMEs, 9 had .1 event with a total of 51 rearrangements, with 1 in 9 samples to further validate the CMEs and check for the clinical patient harboring 16 CMEs (FA351). The chromosomal distribution validity of this type of low-cost molecular karyotype. All CMEs of the 51 CMEs detected in FA is shown in Figure 1A. We detected detected with higher resolution arrays were also detectable with all types of CMEs, including segmental copy-neutral losses of lower resolution (Figure 2; supplemental Figure 2). heterozygosity due to uniparental isodisomies (n 5 6), segmental losses (n 5 18), segmental single (n 5 17) or multicopy gains Mapping of chromosomal breakpoints and (n 5 6), entire chromosome monosomies (n 5 2), and trisomies (n 5 2) (Figure 1B). Most CMEs included the telomeres (80.4%), recurrent rearrangements 7.8% spanned centromeres, and only 19.6% were interstitial. CMEs To further investigate the mutational mechanisms generating CMEs were observed in different FA genetic subtypes (11 FA-A, 1 FA-C, 3 in FA somatic cells, we determined the breakpoint interval for each FA-D2, and 1 FA-J), suggesting that CMEs do not preferentially CME. We detected significant gene enrichment in the FA break- affect a specific complementation group. We validated 41 out of 42 point intervals because the odds of having genes in that region were CMEs (97.6%) by independent experimental methods using the 4.5 times higher than in the whole genome (OR 5 4.5, 95% CI 5 same DNA source. Dosage at the subtelomeric regions was 2.4-8.7, P 5 5.2 3 1027). However, there was no difference in the Table 2. Genomic features at the chromosomal breakpoint regions in FA somatic rearrangements GF % of BPi overlapping with the GF % of the genome overlapping with the GF Ratio BPi/genome P SDs 8.2 519 1.6 .56 CNVs 65.1 77.9 (DGV) 0.8 .059 Genes 64.3 27.520 2.3 5.2 3 1027 MRH 7.5 6.3 (HapMap database) 1.1 .78 From left to right, this table shows genomic features whose overlap was studied in FA BPis. The total length of the defined BPis was obtained in order to calculate the global percentage overlapping with each feature. The proportion (%) of BPis overlapping with each genomic feature (column 2) was compared with the genomic proportion of the feature reported in the literature (column 3) to detect an increased or decreased overlapping with respect to the expected rate (column 4). We detected a statistically significant enrichment of genes in FA BPis. BPi, breakpoint interval; GF, genomic feature; DGV, Database of Genomic Variants (http://dgv.tcag.ca/dgv/app/home). 324 REINA-CASTILL ÓN et al 24 JANUARY 2017 x VOLUME 1, NUMBER 5 A Chr 6 6p22.3 21.1 12.3 6q12 6q13 6q14.1 q15 q16.1 16.3 6q21 q22.31 25.3 26 6q27 Scale 50 Mb hg19 chr6: 50,000,000 100,000,000 150,000,000 FA_rearrangement FA351_a FA106 FA072 FA013 FA013 FA351_b Machiela etal HLA region Chr 6 6p22.3 21.1 12.3 6q12 6q13 6q14.1 q15 q16.1 16.3 6q21 q22.31 25.3 26 6q27 Scale 10 Mb hg19 chr6: 20,000,000 25,000,000 30,000,000 35,000,000 40,000,000 45,000,000 FA_rearrangement FA351_a FA106 FA072 FA013 FA013 Machiela_etal HLA region B Chr 3 p24.3 14.1 13 12.3 23 q24 q26.1 28 q29 Scale 50 Mb hg19 chr3: 50,000,000 100,000,000 150,000,000 FA_rearrangement 110243 FA351_a EGF058 FA178 FA351_b FA647 FA072 FA351_c Machiela_etal C Chr 1 31.3 1p31.1 1q12 32.1 1q41 q43 44 Scale 100 Mb hg19 chr1: 50,000,000 100,000,000 150,000,000 200,000,000 FA_rearrangement FA531 FA178_a 041869_a FA178_b FA072 041869_b FA648 EGF058 FA360 Machiela_etal Figure 3. Clustering of somatic chromosomal rearrangements in FA patients at the MHC locus (6p21) and chromosome arms 1q and 3q. (A) Out of 51 CMEs in FA patients, 5 (9.8%) had breakpoints within or near the MHC–HLA locus at 6p21 (P 5 7.3 3 1029 [2 terminal 6p losses in FA351 and FA072, 2 terminal 6p UPD in FA013 and FA106, and an interstitial gain in FA013]), suggesting that this region is a hotspot for somatic chromosomal rearrangements. Dashed lines delimitate the CIs for the specific breakpoints, spanning as much as 11 Mb in 6p UPD in FA013. (B) A total of 6 CMEs (11.7%) involved 3q in 5 FA individuals (EGF058, FA072, FA178, FA351, and FA647), all of them genomic gains. (C) Five additional gain-type CMEs (9.8%) in 5 individuals (FA072, 041869_b; FA648; EGF058; FA360) were located in 1q as shown. The plots, generated with the University of California, Santa Cruz genomic browser (http://genome.ucsc.edu/), show the distribution of rearrangements in FA patients along with those previously reported in the population, based on multiple case-control studies of cancer.7 Purple: gains; red: losses; green: neutral; gray: complex rearrangements. 24 JANUARY 2017 x VOLUME 1, NUMBER 5 CLONAL MOSAICISM AND CANCER IN FANCONI ANEMIA 325 A B 1.0 1.0 0.8 0.8 Cancer free survival probability Cancer free survival probability 0.6 0.6 0.4 0.4 0.2 0.2 No clonal mosaicism No clonal mosaicism 0.0 Clonal mosaicism 0.0 Clonal mosaicism 0 2 4 6 8 10 12 14 0 2 4 6 8 10 12 14 Years Years Figure 4. Reduced cancer-free time in FA patients with CMEs compared with patients without CMEs. (A) We calculated cancer-free time (years) for 124 FA patients (incomplete information for the remaining 6 cases), 16 with CMEs and 108 without CMEs, from the time of blood collection until the first cancer diagnosis or the last follow-up (if cancer-free); correction by exitus year was done when required. A significantly abridged cancer-free time was observed in FA patients with CMEs using Kaplan-Meier statistical analysis (HR 5 5.1, 95% CI 5 2.5-10.3, P 5 6.78 3 1026). The age-adjusted HR of having cancer was 4.2 times higher in CME carriers than noncarriers (age-adjusted HR 5 4.2, 95% CI 5 2.0-8.7, P 5 1.2 3 1024). (B) In order to consider the incident cancer after blood sample collection, we performed a Kaplan-Meier reanalysis discarding 14 cases with cancer diagnosis at the same time of sample collection and 1 case of exitus at the same year of sampling out of the 124 FA patients included in the initial analysis. A significantly shortened cancer-free time was detected again in FA patients with CMEs compared with those without CMEs (HR 5 5.8, 95% CI 5 2.3-14.5, P 5 1.8 3 1024). As shown in the figure, we obtained the same results when adjusting by age (age-adjusted HR 5 4.9, 95% CI 5 1.9-12.7; P 5 1.1 3 1023). content of SD, polymorphic CNV, or previously defined MRH cancer) or during follow-up (mouth, anal, or esophagus SCC). Of (Table 2).19,20 Interestingly, the breakpoints of 5 CMEs (2 terminal note, the 6p gain and 6p UPD detected in the peripheral blood of losses, 1 interstitial gain, and 2 terminal UPDs) occurred at or near FA013 were also found by microsatellite assays in the anal the MHC region (chr6:29570005-33377657, hg19) (Figure 3A). SCC developed 10 years later (supplemental Figure 3), indicating Given the very low probability for the occurrence of 5 of 51 that these CMEs, which were present in 2 tissues of different breakpoints in this genomic region by chance (P 5 7.3 3 1029), the ontogenetic origin, probably arose very early during embryonic MHC locus seems to be a hotspot for somatic rearrangements development. Globally, we observed that 12 of 16 (75%) FA in FA. Other recurrent CMEs in FA were gains at 3q (n 5 6) and 1q individuals with CMEs versus 23 of 112 (20.5%, 2 cases departed (n 5 5), with both rearrangements strongly associated with hema- from medical follow-up) without CMEs developed a malignancy 0 to tologic cancer development and poor prognosis21-23 (Figure 3B,C). 10 years after DNA sampling, revealing a significantly increased risk On this direction, we were able to detect CMEs that are typically of cancer in FA patients with CMEs (OR 5 11.6, 95% CI 5 associated with hematologic malignancy (1q/3q gains and chro- 3.4-39.3, P 5 2.8 3 1025). Additionally, the diagnosis of prevalent mosome 7 monosomy) in 10 out of 15 FA patients with both CMEs or incident cancer was clearly increased in FA patients with .1 and hematologic problems (bone marrow failure, hematologic CME (9/9 individuals) compared with those with a single CME (3/7 premalignancy or malignancy) (Table 1). individuals) (Fisher’s exact test, P 5 .019) (Table 1). Using the Kaplan-Meier algorithm,18 we observed that the FA patients with Increased cancer risk and poor prognosis associated CMEs in blood had a shortened cancer-free time after sampling with clonal mosaicism in FA compared with the FA patients without CMEs (hazard risk [HR] 5 Among the FA individuals with CMEs, 5 were diagnosed with 5.1, 95% CI 52.5-10.3, P 5 6.78 3 1026) (Figure 4A). Given that hematologic malignancies at the time of sampling, whereas 4 more the mean age was different between both groups of FA patients patients were diagnosed 3 months to 6 years later (Table 1). (with and without CMEs), we obtained an age-adjusted HR of Common chromosomal rearrangements associated with leukemia having cancer, which was 4.2 times higher in individuals with CMEs (1q gain, 3q gain, and/or chromosome 7 monosomy) were detected than in individuals without CMEs (age-adjusted HR 5 4.2, 95% by SNP array in blood DNA of 8 of the FA cases with hematologic CI 5 2.0-8.7, P 5 1.2 3 1024). Importantly, we also observed malignancies.21-24 We compared findings by conventional cytoge- shortened cancer-free time in FA patients with CMEs when netic testing in bone marrow aspirates in 5 patients with our findings repeating the analysis by excluding FA patients with cancer detected by SNP arrays in peripheral blood DNA, and, generally, we (n 5 14) or exitus (n 5 1) at the time of sample collection observed that the SNP array of blood DNA detected all CMEs (HR 5 5.8, 95% CI 5 2.3-14.5, P 5 1.8 3 1024). In this case, the present in the bone marrow along with extra findings (Table 1). age-adjusted HR of having cancer was almost 5 times higher in Other types of cancer were also diagnosed in FA patients with CME individuals than in individuals without CMEs (age-adjusted CMEs, either before sampling (mouth or vulvar SCC and breast HR 5 4.9, 95% CI 5 1.9-12.7, P 5 1.1 3 1023) (Figure 4B). We 326 REINA-CASTILL ÓN et al 24 JANUARY 2017 x VOLUME 1, NUMBER 5 detected 11 individuals with CMEs who did not have any type of patients with CMEs after blood sample collection, showing a tendency cancer at the time of sample collection. Seven of these cases of more diagnosis of cancer after mosaicism detection. As somehow developed cancer (4 hematologic tumors and 3 SCC) during an expected, a significant proportion of the CMEs detected in blood DNA average follow-up of 4.61 years (0.3-10 years) (Table 1). On the other has been clearly associated with hematologic malignancies (1q gains, side, among the 98 FA patients without CMEs who did not have 3q gains, and chromosome 7 monosomy), representing two-thirds of cancer at the time of sample collection, 14 developed a malignancy FA patients with both CMEs and hematologic complications. These during an average follow-up of 3.85 years (1-9 years) (7 individuals data, together with the fact that 2 mosaic rearrangements (6p gain and with hematologic malignancies, 3 cases of SCC, 1 patient with both 6p UPD) were found both in blood and solid tumor samples in a FA myelodysplastic syndrome and SCC, and 3 patients with other patient, reinforce the idea that CMEs can lead to tumor development tumors) (supplemental Table 3). Accordingly, there is an increased or arise as a consequence of tumor clonal expansion. risk of developing cancer after mosaicism detection that is statistically Cancer development in FA patients has been traditionally associated significant (OR 5 10.5, 95% CI 5 2.71-40.6, P 5 7.6 3 1024). with chromosome copy gains and losses, as previously mentioned. Regarding survival, the HR of dying was 4 times higher in individ- With this work, we have discovered that copy-neutral changes could uals having CMEs than those without CMEs (HR 5 4.0, 95% CI 5 play an important role in FA malignancies, because 11.8% of CMEs 2.0-7.9, P 5 5.7 3 1025). Although the main causes of death were detected in FA patients were UPDs. We have also contributed to cancer or related complications in both groups, the proportion increasing the knowledge regarding hotspots for CMEs in FA, because of cancer-related deaths was much higher in individuals with we discovered that the MHC locus is a hotspot for somatic CMEs (11/12) than in those without CMEs (12/29, 1 case with rearrangements in FA, in addition to the already known 1q and 3q no information about the exitus’ cause) (OR 5 15.5, 95% CI 5 regions. Because structural variation at the MHC locus is a likely 1.7-137.7, P 5 4.7 3 1023). substrate for somatic rearrangements in cells of the immune system, derogated repair of MHC rearrangements may facilitate their clonal Clonal mosaicism is related to FA functional proliferation in FA cells. Interestingly, copy-neutral loss of heterozygosity in 6p by UDP involving the MHC locus has been reported in acquired deficiency aplastic anemia27 and primary nervous system lymphoma.28 Loss of the It is widely known that, in about 20% to 25% of FA patients, reverse mismatched HLA haplotype by UPD has also been found after mosaicism can arise in vivo from site-specific reversion of a germ haploidentical hematopoietic stem cell transplantation and infusion of line mutation to wild-type sequence either in stem cells or in more donor T cells in leukemic patients, leading to relapse through the committed lineage-specific hematopoietic progenitor cells, usually escape of leukemic cells from the donor’s antileukemic T cells.29-31 resulting in a less severe hematologic phenotype. However, the reverted clone rarely repopulates the entire bone marrow, and a Elucidating the genomic features of breakpoint intervals of CMEs proportion of mutated cells remains.25,26 Reverse mosaicism, revealed can provide information about the mechanisms underlying these by a diepoxybutane test resulting in ,50% of the cells with chromosomal rearrangements as well as the phenotypic consequences for the aberrations,13 was detected a few years after initial sample collection in patient. The enrichment of coding genes in FA breakpoint intervals 27 of the 130 studied FA patients. Only 1 case with reverse mosaicism reinforces the growing evidence coupling transcriptional activity with presented with CMEs in blood along with a diagnosis of vulvar SCC, DNA repair,32,33 which is perturbed in FA patients. Importantly, we and none developed hematopoietic cancer. Thus, clonal mosaicism detected 2 CMEs in both blood and tumor (anal SCC) samples in 1 appears clearly related to the functional impairment of DNA FA patient. Although we cannot completely rule out the possibility interstrand crosslink repair and secondary chromosomal instability of some blood or cell free DNA contamination or the presence that occurs in cells with biallelic mutations in FA genes. of lymphocytes in the tumor sample, the different allelic imbalance, indicative of a different proportion of cells with each of the aberrant Discussion rearrangements in the tumor with respect to the blood, would suggest a common embryonic origin with different progression in different cells. CMEs are rare in young, healthy individuals, but have been strongly Although the evidence establishing a mechanistic link between CME associated with aging and an increased risk of hematological detection and solid tumor development is still weak, it is also supported cancer and also slightly related to some solid cancers in the general by previous data showing a similar proportion of cells carrying CMEs in population. Importantly, these studies estimate that the risk of the blood and bladder mucosa of 4 individuals with bladder cancer.4 hematological cancer is 10-fold higher for mosaic than for nonmosaic individuals.2,3,5 Thus, in this article, we hypothesized Regarding reverse mosaicism, which is described in up to a quarter of that cancer predisposition disorders, such as FA,9,10 could manifest FA patients, we detected CMEs in the blood of a single individual a high rate of CMEs, even at an early age, and that CMEs could be who was also diagnosed with vulvar SCC. Importantly, none of the indicative of a higher risk of cancer in the coming years. Our study, 27 patients with reverse mosaicism was diagnosed with hematologic based on high-resolution SNP array analysis of 130 patients and malignancy, reinforcing the idea that reversion of a germ line mutation 15 743 age-matched controls, revealed an exacerbated risk of in hematopoietic cells protects against genomic instability, leading to detectable mosaicism in FA individuals, indicating that proper DNA CMEs and hematopoietic cancer. In fact, the reversion of FA mutation repair suppresses genomic heterogeneity of the soma in vivo in could become visible following the same clonal process as any CME. healthy people. We also observed an increased risk of cancer and a A preexisting reverted wild-type clone, which initially contributes to shortened survival due to cancer after DNA sampling in FA patients the somatic genomic heterogeneity, could undergo progressive with CMEs when compared with FA patients without CMEs. monoclonal expansion until repopulating an important fraction of the Interestingly, considering only the incident cases of cancer after bone marrow in a similar way in which a clone with a chromosomal blood sampling, we detected a reduced cancer-free time in FA event is positively selected and leads to a mosaicism. 24 JANUARY 2017 x VOLUME 1, NUMBER 5 CLONAL MOSAICISM AND CANCER IN FANCONI ANEMIA 327 Given the high prevalence of CMEs in blood samples of FA patients and Innovation (projects CB06/07/0023, SAF2012-31881, and and the documented association of detectable CMEs with SAF2015-64152-R), the European Commission (EUROFANCOLEN hematologic and, to a lesser extent, solid cancer, it is logical to project HEALTH-F5-2012-305421 and FANCODRUG project propose that early detection of CMEs could help in clinical decision- H2020-703521), the Fanconi Anemia Research Fund, Inc, and the making. It is well known that strict follow-up according to the clinical European Regional Development (FEDER). L.A.P.-J.’s team is funded guidelines recommending annual bone marrow sampling for FA by the Spanish Ministry of Health (FIS-PI1302481 cofunded by patients is very difficult for patients and families, especially when the FEDER), the Generalitat de Catalunya (SRG1468-2014), and the patient’s hematology remains stable. Although prospective data on ICREA-Academia program, and also acknowledges support from the sequential sampling of a large cohort are required to better define Spanish Ministry of Economy and Competiveness Programa de the sensitivity, specificity, and most appropriate sampling intervals, Excelencia Maria de Maeztu (MDM-2014-0370). CIBERER is an we propose that SNP arrays of DNA from easy-to-obtain samples, initiative of the Instituto de Salud Carlos III (Madrid, Spain). D.S. was such as blood cells, should be included in the regular follow-up of supported by the Schroeder-Kurth Fund. patients with FA, with the goal of identifying individuals at higher risk of cancer in order to better direct additional exams and treatments. Authorship The possibility of studying additional samples that might better Contribution: L.A.P.-J. and J. Surrallés designed the study, super- detect nonhematological tumors, such as plasma-free DNA or vised the data, and wrote the manuscript; J.R.-C. performed the saliva, should also be evaluated in future studies, as well as the utility validation studies and contributed to writing the manuscript; J.R.-C., of these tools in other chromosome instability and bone marrow M.L.-S., and B.R.-S. performed the CME detection and associ- failure syndromes. ated analyses; M.L.-S. and J.R.G. contributed to the population Acknowledgments control data and statistical analyses; R.P. and M.A.-C. contributed to the patient characterization, classification, and clinical data; the The authors thank the FA families and FA parent organizations, namely rest of the coauthors (J.A.C., J.A.B., J.S., I.B., A.C., C.B., M.A.D., Asociación Española de Anemia de Fanconi and Ralf Dietrich, for C.D.d.H., J. Soulier, and D.S.) provided blood and tumor samples their collaboration and continuous support, as well as the Spanish and clinical and genetic data; and all authors approved and FA Clinical Network for their contributions in taking care of these commented on the manuscript. patients (supplemental Table 4). The authors would also like to thank Francisco X. Real for his critical review of the manuscript and Tania Conflict-of-interest disclosure: B.R.-S. is an employee of, and Lobato for technical support in DNA extraction of tumor samples. L.A.P.-J. is a scientific advisor for, qGenomics, SL. The remaining J.R.-C. was supported by a fellowship from the Spanish Ministry of authors declare no competing financial interests. Education (FPU13/00782) and M.A.-C. was supported by a Juan de Correspondence: Luis Alberto Pérez-Jurado, Genetics Unit, De- la Cierva postdoctoral fellowship (JCI-2011-10660). J. Surrallés’ partment of Experimental and Health Sciences, Universitat Pompeu team is funded by the Generalitat de Catalunya (SGR0489-2009, Fabra, 88 Dr. Aiguader St, PRBB Building, 08003 Barcelona, Spain; SGR317-2014), the ICREA-Academia program, Marató de TV3 and Jordi Surrallés, Genetics Department, Hospital de Sant Pau, (project 464/C/2012), the Spanish Ministry of Health (projects Laboratories floor-2, 89 Sant Quintı́ St, 08041 Barcelona, Spain; FANCOSTEM and FANCOLEN), the Spanish Ministry of Science e-mail: jsurralles@santpau.cat. References 1. Fernández LC, Torres M, Real FX. Somatic mosaicism: on the road to cancer. Nat Rev Cancer. 2016;16(1):43-55. 2. Jacobs KB, Yeager M, Zhou W, et al. Detectable clonal mosaicism and its relationship to aging and cancer. Nat Genet. 2012;44(6):651-658. 3. Laurie CC, Laurie CA, Rice K, et al. Detectable clonal mosaicism from birth to old age and its relationship to cancer. Nat Genet. 2012;44(6):642-650. 4. Rodrı́guez-Santiago B, Malats N, Rothman N, et al. Mosaic uniparental disomies and aneuploidies as large structural variants of the human genome. Am J Hum Genet. 2010;87(1):129-138. 5. Schick UM, McDavid A, Crane PK, et al. Confirmation of the reported association of clonal chromosomal mosaicism with an increased risk of incident hematologic cancer. PLoS One. 2013;8(3):e59823. 6. González JR, Rodrı́guez-Santiago B, Cáceres A, et al. A fast and accurate method to detect allelic genomic imbalances underlying mosaic rearrangements using SNP array data. BMC Bioinformatics. 2011;12(1):166. 7. Machiela MJ, Zhou W, Sampson JN, et al. Characterization of large structural genetic mosaicism in human autosomes. Am J Hum Genet. 2015;96(3): 487-497. 8. Bonnefond A, Skrobek B, Lobbens S, et al. Association between large detectable clonal mosaicism and type 2 diabetes with vascular complications. Nat Genet. 2013;45(9):1040-1043. 9. Bogliolo M, Surralles J. Fanconi anemia: a model disease for studies on human genetics and advanced therapeutics. Curr Opin Genet Dev. 2015;33: 32-40 10. Wang AT, Smogorzewska A. SnapShot: Fanconi anemia and associated proteins. Cell. 2015;160(1-2):354-354.e1. 11. Kutler DI, Wreesmann VB, Goberdhan A, et al. Human papillomavirus DNA and p53 polymorphisms in squamous cell carcinomas from Fanconi anemia patients. J Natl Cancer Inst. 2003;95(22):1718-1721. 328 REINA-CASTILL ÓN et al 24 JANUARY 2017 x VOLUME 1, NUMBER 5 12. Hays L, ed. Fanconi Anemia: Guidelines for Diagnosis and Management. 4th ed. Eugene, OR: Fanconi Anemia Research Fund, Inc; 2014:421. 13. Castella M, Pujol R, Callén E, et al. Chromosome fragility in patients with Fanconi anaemia: diagnostic implications and clinical impact. J Med Genet. 2011;48(4):242-250. 14. Fischbach GD, Lord C. The Simons Simplex Collection: a resource for identification of autism genetic risk factors. Neuron. 2010;68(2):192-195. 15. Pinto D, Delaby E, Merico D, et al. Convergence of genes and cellular pathways dysregulated in autism spectrum disorders. Am J Hum Genet. 2014; 94(5):677-694. 16. King DA, Jones WD, Crow YJ, et al; Deciphering Developmental Disorders Study. Mosaic structural variation in children with developmental disorders. Hum Mol Genet. 2015;24(10):2733-2745. 17. R Core Team. R: A language and environment for statistical computing. Vienna, Austria: R Foundation for Statistical Computing; 2015. 18. Kaplan EL, Meier P. Nonparametric estimation from incomplete observations. J Am Stat Assoc. 1958;53(282):457-481. 19. Sharp AJ, Locke DP, McGrath SD, et al. Segmental duplications and copy-number variation in the human genome. Am J Hum Genet. 2005;77(1):78-88. 20. Gregory TR. Synergy between sequence and size in large-scale genomics. Nat Rev Genet. 2005;6(9):699-708. 21. Tönnies H, Huber S, Kühl JS, Gerlach A, Ebell W, Neitzel H. Clonal chromosomal aberrations in bone marrow cells of Fanconi anemia patients: gains of the chromosomal segment 3q26q29 as an adverse risk factor. Blood. 2003;101(10):3872-3874. 22. Quentin S, Cuccuini W, Ceccaldi R, et al. Myelodysplasia and leukemia of Fanconi anemia are associated with a specific pattern of genomic abnormalities that includes cryptic RUNX1/AML1 lesions. Blood. 2011;117(15):e161-e170. 23. Meyer S, Bristow C, Wappett M, et al. Fanconi anemia (FA)-associated 3q gains in leukemic transformation consistently target EVI1, but do not affect low TERC expression in FA. Blood. 2011;117(22):6047-6050. 24. Mehta PA, Harris RE, Davies SM, et al. Numerical chromosomal changes and risk of development of myelodysplastic syndrome–acute myeloid leukemia in patients with Fanconi anemia. Cancer Genet Cytogenet. 2010;203(2):180-186. 25. Lo Ten Foe JR, Kwee ML, Rooimans MA, et al. Somatic mosaicism in Fanconi anemia: molecular basis and clinical significance. Eur J Hum Genet. 1997; 5(3):137-148. 26. Waisfisz Q, Morgan NV, Savino M, et al. Spontaneous functional correction of homozygous fanconi anaemia alleles reveals novel mechanistic basis for reverse mosaicism. Nat Genet. 1999;22(4):379-383. 27. Ogawa S. Clonal hematopoiesis in acquired aplastic anemia. Blood. 2016;128(3):337-347. 28. Schwindt H, Vater I, Kreuz M, et al. Chromosomal imbalances and partial uniparental disomies in primary central nervous system lymphoma. Leukemia. 2009;23(10):1875-1884. 29. Vago L, Perna SK, Zanussi M, et al. Loss of mismatched HLA in leukemia after stem-cell transplantation. N Engl J Med. 2009;361(5):478-488. 30. Villalobos IB, Takahashi Y, Akatsuka Y, et al. Relapse of leukemia with loss of mismatched HLA resulting from uniparental disomy after haploidentical hematopoietic stem cell transplantation. Blood. 2010;115(15):3158-3161. 31. Dubois V, Sloan-Béna F, Cesbron A, et al. Pretransplant HLA mistyping in diagnostic samples of acute myeloid leukemia patients due to acquired uniparental disomy. Leukemia. 2012;26(9):2079-2085. 32. Garcı́a-Rubio ML, Pérez-Calero C, Barroso SI, et al. The Fanconi anemia pathway protects genome integrity from R-loops. PLoS Genet. 2015;11(11): e1005674. 33. Schwab RA, Nieminuszczy J, Shah F, et al. The Fanconi anemia pathway maintains genome stability by coordinating replication and transcription. Mol Cell. 2015;60(3):351-361. 24 JANUARY 2017 x VOLUME 1, NUMBER 5 CLONAL MOSAICISM AND CANCER IN FANCONI ANEMIA 329