Rapid and accurate remethylation of DNA in Dnmt3a-deficient hematopoietic cells with restoration of DNMT3A activity.

Here, we characterize the DNA methylation phenotypes of bone marrow cells from mice with hematopoietic deficiency of Dnmt3a or Dnmt3b (or both enzymes) or expressing the dominant-negative Dnmt3aR878H mutation [R882H in humans; the most common DNMT3A mutation found in acute myeloid leukemia (AML)]. Using these cells as substrates, we defined DNA remethylation after overexpressing wild-type (WT) DNMT3A1, DNMT3B1, DNMT3B3 (an inactive splice isoform of DNMT3B), or DNMT3L (a catalytically inactive "chaperone" for DNMT3A and DNMT3B in early embryogenesis). Overexpression of DNMT3A for 2 weeks reverses the hypomethylation phenotype of Dnmt3a-deficient cells or cells expressing the R878H mutation. Overexpression of DNMT3L (which is minimally expressed in AML cells) also corrects the hypomethylation phenotype of Dnmt3aR878H/+ marrow, probably by augmenting the activity of WT DNMT3A encoded by the residual WT allele. DNMT3L reactivation may represent a previously unidentified approach for restoring DNMT3A activity in hematopoietic cells with reduced DNMT3A function.

Ultra-Deep Sequencing Reveals the Mutational Landscape of Classical Hodgkin Lymphoma.

The malignant Hodgkin and Reed Sternberg (HRS) cells of classical Hodgkin lymphoma (cHL) are scarce in affected lymph nodes, creating a challenge to detect driver somatic mutations. As an alternative to cell purification techniques, we hypothesized that ultra-deep exome sequencing would allow genomic study of HRS cells, thereby streamlining analysis and avoiding technical pitfalls. To test this, 31 cHL tumor/normal pairs were exome sequenced to approximately 1,000× median depth of coverage. An orthogonal error-corrected sequencing approach verified >95% of the discovered mutations. We identified mutations in genes novel to cHL including: CDH5 and PCDH7, novel stop gain mutations in IL4R, and a novel pattern of recurrent mutations in pathways regulating Hippo signaling. As a further application of our exome sequencing, we attempted to identify expressed somatic single-nucleotide variants (SNV) in single-nuclei RNA sequencing (snRNA-seq) data generated from a patient in our cohort. Our snRNA analysis identified a clear cluster of cells containing a somatic SNV identified in our deep exome data. This cluster has differentially expressed genes that are consistent with genes known to be dysregulated in HRS cells (e.g., PIM1 and PIM3). The cluster also contains cells with an expanded B-cell clonotype further supporting a malignant phenotype. This study provides proof-of-principle that ultra-deep exome sequencing can be utilized to identify recurrent mutations in HRS cells and demonstrates the feasibility of snRNA-seq in the context of cHL. These studies provide the foundation for the further analysis of genomic variants in large cohorts of patients with cHL. SIGNIFICANCE: Our data demonstrate the utility of ultra-deep exome sequencing in uncovering somatic variants in Hodgkin lymphoma, creating new opportunities to define the genes that are recurrently mutated in this disease. We also show for the first time the successful application of snRNA-seq in Hodgkin lymphoma and describe the expression profile of a putative cluster of HRS cells in a single patient.

Genomic landscape of TP53-mutated myeloid malignancies.

TP53-mutated myeloid malignancies are associated with complex cytogenetics and extensive structural variants, which complicates detailed genomic analysis by conventional clinical techniques. We performed whole-genome sequencing (WGS) of 42 acute myeloid leukemia (AML)/myelodysplastic syndromes (MDS) cases with paired normal tissue to better characterize the genomic landscape of TP53-mutated AML/MDS. WGS accurately determines TP53 allele status, a key prognostic factor, resulting in the reclassification of 12% of cases from monoallelic to multihit. Although aneuploidy and chromothripsis are shared with most TP53-mutated cancers, the specific chromosome abnormalities are distinct to each cancer type, suggesting a dependence on the tissue of origin. ETV6 expression is reduced in nearly all cases of TP53-mutated AML/MDS, either through gene deletion or presumed epigenetic silencing. Within the AML cohort, mutations of NF1 are highly enriched, with deletions of 1 copy of NF1 present in 45% of cases and biallelic mutations in 17%. Telomere content is increased in TP53-mutated AMLs compared with other AML subtypes, and abnormal telomeric sequences were detected in the interstitial regions of chromosomes. These data highlight the unique features of TP53-mutated myeloid malignancies, including the high frequency of chromothripsis and structural variation, the frequent involvement of unique genes (including NF1 and ETV6) as cooperating events, and evidence for altered telomere maintenance.

A draft human pangenome reference.

Here the Human Pangenome Reference Consortium presents a first draft of the human pangenome reference. The pangenome contains 47 phased, diploid assemblies from a cohort of genetically diverse individuals1. These assemblies cover more than 99% of the expected sequence in each genome and are more than 99% accurate at the structural and base pair levels. Based on alignments of the assemblies, we generate a draft pangenome that captures known variants and haplotypes and reveals new alleles at structurally complex loci. We also add 119 million base pairs of euchromatic polymorphic sequences and 1,115 gene duplications relative to the existing reference GRCh38. Roughly 90 million of the additional base pairs are derived from structural variation. Using our draft pangenome to analyse short-read data reduced small variant discovery errors by 34% and increased the number of structural variants detected per haplotype by 104% compared with GRCh38-based workflows, which enabled the typing of the vast majority of structural variant alleles per sample.

Persistent Molecular Disease in Adult Patients With AML Evaluated With Whole-Exome and Targeted Error-Corrected DNA Sequencing.

PURPOSE: Persistent molecular disease (PMD) after induction chemotherapy predicts relapse in AML. In this study, we used whole-exome sequencing (WES) and targeted error-corrected sequencing to assess the frequency and mutational patterns of PMD in 30 patients with AML. MATERIALS AND METHODS: The study cohort included 30 patients with adult AML younger than 65 years who were uniformly treated with standard induction chemotherapy. Tumor/normal WES was performed for all patients at presentation. PMD analysis was evaluated in bone marrow samples obtained during clinicopathologic remission using repeat WES and analysis of patient-specific mutations and error-corrected sequencing of 40 recurrently mutated AML genes (MyeloSeq). RESULTS: WES for patient-specific mutations detected PMD in 63% of patients (19/30) using a minimum variant allele fraction (VAF) of 2.5%. In comparison, MyeloSeq identified persistent mutations above 0.1% VAF in 77% of patients (23/30). PMD was usually present at relatively high levels (>2.5% VAFs), such that WES and MyeloSeq agreed for 73% of patients despite differences in detection limits. Mutations in DNMT3A, ASXL1, and TET2 (ie, DTA mutations) were persistent in 16 of 17 patients, but WES also detected non-DTA mutations in 14 of these patients, which for some patients distinguished residual AML cells from clonal hematopoiesis. Surprisingly, MyeloSeq detected additional variants not identified at presentation in 73% of patients that were consistent with new clonal cell populations after chemotherapy. CONCLUSION: PMD and clonal hematopoiesis are both common in patients with AML in first remission. These findings demonstrate the importance of baseline testing for accurate interpretation of mutation-based tumor monitoring assays for patients with AML and highlight the need for clinical trials to determine whether these complex mutation patterns correlate with clinical outcomes in AML.

Genomic landscape of TP53 -mutated myeloid malignancies.

TP53 -mutated myeloid malignancies are most frequently associated with complex cytogenetics. The presence of complex and extensive structural variants complicates detailed genomic analysis by conventional clinical techniques. We performed whole genome sequencing of 42 AML/MDS cases with paired normal tissue to characterize the genomic landscape of TP53 -mutated myeloid malignancies. The vast majority of cases had multi-hit involvement at the TP53 genetic locus (94%), as well as aneuploidy and chromothripsis. Chromosomal patterns of aneuploidy differed significantly from TP53 -mutated cancers arising in other tissues. Recurrent structural variants affected regions that include ETV6 on chr12p, RUNX1 on chr21, and NF1 on chr17q. Most notably for ETV6 , transcript expression was low in cases of TP53 -mutated myeloid malignancies both with and without structural rearrangements involving chromosome 12p. Telomeric content is increased in TP53 -mutated AML/MDS compared other AML subtypes, and telomeric content was detected adjacent to interstitial regions of chromosomes. The genomic landscape of TP53 -mutated myeloid malignancies reveals recurrent structural variants affecting key hematopoietic transcription factors and telomeric repeats that are generally not detected by panel sequencing or conventional cytogenetic analyses. Key Points: WGS comprehensively determines TP53 mutation status, resulting in the reclassification of 12% of cases from mono-allelic to multi-hit Chromothripsis is more frequent than previously appreciated, with a preference for specific chromosomes ETV6 is deleted in 45% of cases, with evidence for epigenetic suppression in non-deleted cases NF1 is mutated in 48% of cases, with multi-hit mutations in 17% of these cases TP53 -mutated AML/MDS is associated with altered telomere content compared with other AMLs.

High-coverage whole-genome sequencing of the expanded 1000 Genomes Project cohort including 602 trios.

The 1000 Genomes Project (1kGP) is the largest fully open resource of whole-genome sequencing (WGS) data consented for public distribution without access or use restrictions. The final, phase 3 release of the 1kGP included 2,504 unrelated samples from 26 populations and was based primarily on low-coverage WGS. Here, we present a high-coverage 3,202-sample WGS 1kGP resource, which now includes 602 complete trios, sequenced to a depth of 30X using Illumina. We performed single-nucleotide variant (SNV) and short insertion and deletion (INDEL) discovery and generated a comprehensive set of structural variants (SVs) by integrating multiple analytic methods through a machine learning model. We show gains in sensitivity and precision of variant calls compared to phase 3, especially among rare SNVs as well as INDELs and SVs spanning frequency spectrum. We also generated an improved reference imputation panel, making variants discovered here accessible for association studies.

Genome-wide association studies of metabolites in Finnish men identify disease-relevant loci.

Few studies have explored the impact of rare variants (minor allele frequency < 1%) on highly heritable plasma metabolites identified in metabolomic screens. The Finnish population provides an ideal opportunity for such explorations, given the multiple bottlenecks and expansions that have shaped its history, and the enrichment for many otherwise rare alleles that has resulted. Here, we report genetic associations for 1391 plasma metabolites in 6136 men from the late-settlement region of Finland. We identify 303 novel association signals, more than one third at variants rare or enriched in Finns. Many of these signals identify genes not previously implicated in metabolite genome-wide association studies and suggest mechanisms for diseases and disease-related traits.

Somatic Dnmt3a inactivation leads to slow, canonical DNA methylation loss in murine hematopoietic cells.

Mutations in the gene encoding DNA methyltransferase 3A (DNMT3A) are the most common cause of clonal hematopoiesis and are among the most common initiating events of acute myeloid leukemia (AML). Studies in germline and somatic Dnmt3a knockout mice have identified focal, canonical hypomethylation phenotypes in hematopoietic cells; however, the kinetics of methylation loss following acquired DNMT3A inactivation in hematopoietic cells is essentially unknown. Therefore, we evaluated a somatic, inducible model of hematopoietic Dnmt3a loss, and show that inactivation of Dnmt3a in murine hematopoietic cells results in a relatively slow loss of methylation at canonical sites throughout the genome; in contrast, remethylation of Dnmt3a deficient genomes in hematopoietic cells occurs much more quickly. This data suggests that slow methylation loss may contribute, at least in part, to the long latent period that characterizes clonal expansion and leukemia development in individuals with acquired DNMT3A mutations in hematopoietic stem cells.

Functional and epigenetic phenotypes of humans and mice with DNMT3A Overgrowth Syndrome.

Germline pathogenic variants in DNMT3A were recently described in patients with overgrowth, obesity, behavioral, and learning difficulties (DNMT3A Overgrowth Syndrome/DOS). Somatic mutations in the DNMT3A gene are also the most common cause of clonal hematopoiesis, and can initiate acute myeloid leukemia (AML). Using whole genome bisulfite sequencing, we studied DNA methylation in peripheral blood cells of 11 DOS patients and found a focal, canonical hypomethylation phenotype, which is most severe with the dominant negative DNMT3AR882H mutation. A germline mouse model expressing the homologous Dnmt3aR878H mutation phenocopies most aspects of the human DOS syndrome, including the methylation phenotype and an increased incidence of spontaneous hematopoietic malignancies, suggesting that all aspects of this syndrome are caused by this mutation.

Mitochondrial genome copy number measured by DNA sequencing in human blood is strongly associated with metabolic traits via cell-type composition differences.

BACKGROUND: Mitochondrial genome copy number (MT-CN) varies among humans and across tissues and is highly heritable, but its causes and consequences are not well understood. When measured by bulk DNA sequencing in blood, MT-CN may reflect a combination of the number of mitochondria per cell and cell-type composition. Here, we studied MT-CN variation in blood-derived DNA from 19184 Finnish individuals using a combination of genome (N = 4163) and exome sequencing (N = 19034) data as well as imputed genotypes (N = 17718). RESULTS: We identified two loci significantly associated with MT-CN variation: a common variant at the MYB-HBS1L locus (P = 1.6 × 10-8), which has previously been associated with numerous hematological parameters; and a burden of rare variants in the TMBIM1 gene (P = 3.0 × 10-8), which has been reported to protect against non-alcoholic fatty liver disease. We also found that MT-CN is strongly associated with insulin levels (P = 2.0 × 10-21) and other metabolic syndrome (metS)-related traits. Using a Mendelian randomization framework, we show evidence that MT-CN measured in blood is causally related to insulin levels. We then applied an MT-CN polygenic risk score (PRS) derived from Finnish data to the UK Biobank, where the association between the PRS and metS traits was replicated. Adjusting for cell counts largely eliminated these signals, suggesting that MT-CN affects metS via cell-type composition. CONCLUSION: These results suggest that measurements of MT-CN in blood-derived DNA partially reflect differences in cell-type composition and that these differences are causally linked to insulin and related traits.

Association of structural variation with cardiometabolic traits in Finns.

The contribution of genome structural variation (SV) to quantitative traits associated with cardiometabolic diseases remains largely unknown. Here, we present the results of a study examining genetic association between SVs and cardiometabolic traits in the Finnish population. We used sensitive methods to identify and genotype 129,166 high-confidence SVs from deep whole-genome sequencing (WGS) data of 4,848 individuals. We tested the 64,572 common and low-frequency SVs for association with 116 quantitative traits and tested candidate associations using exome sequencing and array genotype data from an additional 15,205 individuals. We discovered 31 genome-wide significant associations at 15 loci, including 2 loci at which SVs have strong phenotypic effects: (1) a deletion of the ALB promoter that is greatly enriched in the Finnish population and causes decreased serum albumin level in carriers (p = 1.47 × 10-54) and is also associated with increased levels of total cholesterol (p = 1.22 × 10-28) and 14 additional cholesterol-related traits, and (2) a multi-allelic copy number variant (CNV) at PDPR that is strongly associated with pyruvate (p = 4.81 × 10-21) and alanine (p = 6.14 × 10-12) levels and resides within a structurally complex genomic region that has accumulated many rearrangements over evolutionary time. We also confirmed six previously reported associations, including five led by stronger signals in single nucleotide variants (SNVs) and one linking recurrent HP gene deletion and cholesterol levels (p = 6.24 × 10-10), which was also found to be strongly associated with increased glycoprotein level (p = 3.53 × 10-35). Our study confirms that integrating SVs in trait-mapping studies will expand our knowledge of genetic factors underlying disease risk.

Haplotype-resolved diverse human genomes and integrated analysis of structural variation.

Long-read and strand-specific sequencing technologies together facilitate the de novo assembly of high-quality haplotype-resolved human genomes without parent-child trio data. We present 64 assembled haplotypes from 32 diverse human genomes. These highly contiguous haplotype assemblies (average minimum contig length needed to cover 50% of the genome: 26 million base pairs) integrate all forms of genetic variation, even across complex loci. We identified 107,590 structural variants (SVs), of which 68% were not discovered with short-read sequencing, and 278 SV hotspots (spanning megabases of gene-rich sequence). We characterized 130 of the most active mobile element source elements and found that 63% of all SVs arise through homology-mediated mechanisms. This resource enables reliable graph-based genotyping from short reads of up to 50,340 SVs, resulting in the identification of 1526 expression quantitative trait loci as well as SV candidates for adaptive selection within the human population.

Mapping and characterization of structural variation in 17,795 human genomes.

A key goal of whole-genome sequencing for studies of human genetics is to interrogate all forms of variation, including single-nucleotide variants, small insertion or deletion (indel) variants and structural variants. However, tools and resources for the study of structural variants have lagged behind those for smaller variants. Here we used a scalable pipeline1 to map and characterize structural variants in 17,795 deeply sequenced human genomes. We publicly release site-frequency data to create the largest, to our knowledge, whole-genome-sequencing-based structural variant resource so far. On average, individuals carry 2.9 rare structural variants that alter coding regions; these variants affect the dosage or structure of 4.2 genes and account for 4.0-11.2% of rare high-impact coding alleles. Using a computational model, we estimate that structural variants account for 17.2% of rare alleles genome-wide, with predicted deleterious effects that are equivalent to loss-of-function coding alleles; approximately 90% of such structural variants are noncoding deletions (mean 19.1 per genome). We report 158,991 ultra-rare structural variants and show that 2% of individuals carry ultra-rare megabase-scale structural variants, nearly half of which are balanced or complex rearrangements. Finally, we infer the dosage sensitivity of genes and noncoding elements, and reveal trends that relate to element class and conservation. This work will help to guide the analysis and interpretation of structural variants in the era of whole-genome sequencing.

Author Correction: Exome sequencing of Finnish isolates enhances rare-variant association power.

An Amendment to this paper has been published and can be accessed via a link at the top of the paper.

Exome sequencing of Finnish isolates enhances rare-variant association power.

Exome-sequencing studies have generally been underpowered to identify deleterious alleles with a large effect on complex traits as such alleles are mostly rare. Because the population of northern and eastern Finland has expanded considerably and in isolation following a series of bottlenecks, individuals of these populations have numerous deleterious alleles at a relatively high frequency. Here, using exome sequencing of nearly 20,000 individuals from these regions, we investigate the role of rare coding variants in clinically relevant quantitative cardiometabolic traits. Exome-wide association studies for 64 quantitative traits identified 26 newly associated deleterious alleles. Of these 26 alleles, 19 are either unique to or more than 20 times more frequent in Finnish individuals than in other Europeans and show geographical clustering comparable to Mendelian disease mutations that are characteristic of the Finnish population. We estimate that sequencing studies of populations without this unique history would require hundreds of thousands to millions of participants to achieve comparable association power.

svtools: population-scale analysis of structural variation.

SUMMARY: Large-scale human genetics studies are now employing whole genome sequencing with the goal of conducting comprehensive trait mapping analyses of all forms of genome variation. However, methods for structural variation (SV) analysis have lagged far behind those for smaller scale variants, and there is an urgent need to develop more efficient tools that scale to the size of human populations. Here, we present a fast and highly scalable software toolkit (svtools) and cloud-based pipeline for assembling high quality SV maps-including deletions, duplications, mobile element insertions, inversions and other rearrangements-in many thousands of human genomes. We show that this pipeline achieves similar variant detection performance to established per-sample methods (e.g. LUMPY), while providing fast and affordable joint analysis at the scale of ≥100 000 genomes. These tools will help enable the next generation of human genetics studies. AVAILABILITY AND IMPLEMENTATION: svtools is implemented in Python and freely available (MIT) from https://github.com/hall-lab/svtools. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Mutation Clearance after Transplantation for Myelodysplastic Syndrome.

BACKGROUND: Allogeneic hematopoietic stem-cell transplantation is the only curative treatment for patients with myelodysplastic syndrome (MDS). The molecular predictors of disease progression after transplantation are unclear. METHODS: We sequenced bone marrow and skin samples from 90 adults with MDS who underwent allogeneic hematopoietic stem-cell transplantation after a myeloablative or reduced-intensity conditioning regimen. We detected mutations before transplantation using enhanced exome sequencing, and we evaluated mutation clearance by using error-corrected sequencing to genotype mutations in bone marrow samples obtained 30 days after transplantation. In this exploratory study, we evaluated the association of a mutation detected after transplantation with disease progression and survival. RESULTS: Sequencing identified at least one validated somatic mutation before transplantation in 86 of 90 patients (96%); 32 of these patients (37%) had at least one mutation with a maximum variant allele frequency of at least 0.5% (equivalent to 1 heterozygous mutant cell in 100 cells) 30 days after transplantation. Patients with disease progression had mutations with a higher maximum variant allele frequency at 30 days than those who did not (median maximum variant allele frequency, 0.9% vs. 0%; P<0.001). The presence of at least one mutation with a variant allele frequency of at least 0.5% at day 30 was associated with a higher risk of progression (53.1% vs. 13.0%; conditioning regimen-adjusted hazard ratio, 3.86; 95% confidence interval [CI], 1.96 to 7.62; P<0.001) and a lower 1-year rate of progression-free survival than the absence of such a mutation (31.3% vs. 59.3%; conditioning regimen-adjusted hazard ratio for progression or death, 2.22; 95% CI, 1.32 to 3.73; P=0.005). The rate of progression-free survival was lower among patients who had received a reduced-intensity conditioning regimen and had at least one persistent mutation with a variant allele frequency of at least 0.5% at day 30 than among patients with other combinations of conditioning regimen and mutation status (P≤0.001). Multivariate analysis confirmed that patients who had a mutation with a variant allele frequency of at least 0.5% detected at day 30 had a higher risk of progression (hazard ratio, 4.48; 95% CI, 2.21 to 9.08; P<0.001) and a lower 1-year rate of progression-free survival than those who did not (hazard ratio for progression or death, 2.39; 95% CI, 1.40 to 4.09; P=0.002). CONCLUSIONS: The risk of disease progression was higher among patients with MDS in whom persistent disease-associated mutations were detected in the bone marrow 30 days after transplantation than among those in whom these mutations were not detected. (Funded by the Leukemia and Lymphoma Society and others.).

Genomic heterogeneity of ALK fusion breakpoints in non-small-cell lung cancer.

In lung adenocarcinoma, canonical EML4-ALK inversion results in a fusion protein with a constitutively active ALK kinase domain. Evidence of ALK rearrangement occurs in a minority (2-7%) of lung adenocarcinoma, and only ~60% of these patients will respond to targeted ALK inhibition by drugs such as crizotinib and ceritinib. Clinically, targeted anti-ALK therapy is often initiated based on evidence of an ALK genomic rearrangement detected by fluorescence in situ hybridization (FISH) of interphase cells in formalin-fixed, paraffin-embedded tissue sections. At the genomic level, however, ALK rearrangements are heterogeneous, with multiple potential breakpoints in EML4, and alternate fusion partners. Using next-generation sequencing of DNA and RNA together with ALK immunohistochemistry, we comprehensively characterized genomic breakpoints in 33 FISH-positive lung adenocarcinomas. Of these 33 cases, 29 (88%) had detectable DNA level ALK rearrangements involving EML4, KIF5B, or non-canonical partners including ASXL2, ATP6V1B1, PRKAR1A, and SPDYA. A subset of 12 cases had material available for RNA-Seq. Of these, eight of eight (100%) cases with DNA rearrangements showed ALK fusion transcripts from RNA-Seq; three of four cases (75%) without detectable DNA rearrangements were similarly negative by RNA-Seq, and one case was positive by RNA-Seq but negative by DNA next-generation sequencing. By immunohistochemistry, 17 of 19 (89%) tested cases were clearly positive for ALK protein expression; the remaining cases had no detectable DNA level rearrangement or had a non-canonical rearrangement not predicted to form a fusion protein. Survival analysis of patients treated with targeted ALK inhibitors demonstrates a significant difference in mean survival between patients with next-generation sequencing confirmed EML4-ALK rearrangements, and those without (20.6 months vs 5.4 months, P<0.01). Together, these data demonstrate abundant genomic heterogeneity among ALK-rearranged lung adenocarcinoma, which may account for differences in treatment response with targeted ALK inhibitors.

Spectrum of mutations in leiomyosarcomas identified by clinical targeted next-generation sequencing.

Recurrent genomic mutations in uterine and non-uterine leiomyosarcomas have not been well established. Using a next generation sequencing (NGS) panel of common cancer-associated genes, 25 leiomyosarcomas arising from multiple sites were examined to explore genetic alterations, including single nucleotide variants (SNV), small insertions/deletions (indels), and copy number alterations (CNA). Sequencing showed 86 non-synonymous, coding region somatic variants within 151 gene targets in 21 cases, with a mean of 4.1 variants per case; 4 cases had no putative mutations in the panel of genes assayed. The most frequently altered genes were TP53 (36%), ATM and ATRX (16%), and EGFR and RB1 (12%). CNA were identified in 85% of cases, with the most frequent copy number losses observed in chromosomes 10 and 13 including PTEN and RB1; the most frequent gains were seen in chromosomes 7 and 17. Our data show that deletions in canonical cancer-related genes are common in leiomyosarcomas. Further, the spectrum of gene mutations observed shows that defects in DNA repair and chromosomal maintenance are central to the biology of leiomyosarcomas, and that activating mutations observed in other common cancer types are rare in leiomyosarcomas.