Integrated paired-end enhancer profiling and whole-genome sequencing reveals recurrent CCNE1 and IGF2 enhancer hijacking in primary gastric adenocarcinoma

Gut ◽  
2019 ◽  
Vol 69 (6) ◽  
pp. 1039-1052 ◽  
Author(s):  
Wen Fong Ooi ◽  
Amrita M Nargund ◽  
Kevin Junliang Lim ◽  
Shenli Zhang ◽  
Manjie Xing ◽  
...  
Keyword(s):  
Whole Genome Sequencing ◽  
Genome Sequencing ◽  
Therapy Resistance ◽  
Regulatory Elements ◽  
Genomic Rearrangements ◽  
Common Mechanism ◽  
Whole Genome ◽  
Structural Variations ◽  
Chromosome Conformation ◽  
Chip Sequencing

ObjectiveGenomic structural variations (SVs) causing rewiring of cis-regulatory elements remain largely unexplored in gastric cancer (GC). To identify SVs affecting enhancer elements in GC (enhancer-based SVs), we integrated epigenomic enhancer profiles revealed by paired-end H3K27ac ChIP-sequencing from primary GCs with tumour whole-genome sequencing (WGS) data (PeNChIP-seq/WGS).DesignWe applied PeNChIP-seq to 11 primary GCs and matched normal tissues combined with WGS profiles of >200 GCs. Epigenome profiles were analysed alongside matched RNA-seq data to identify tumour-associated enhancer-based SVs with altered cancer transcription. Functional validation of candidate enhancer-based SVs was performed using CRISPR/Cas9 genome editing, chromosome conformation capture assays (4C-seq, Capture-C) and Hi-C analysis of primary GCs.ResultsPeNChIP-seq/WGS revealed ~150 enhancer-based SVs in GC. The majority (63%) of SVs linked to target gene deregulation were associated with increased tumour expression. Enhancer-based SVs targeting CCNE1, a key driver of therapy resistance, occurred in 8% of patients frequently juxtaposing diverse distal enhancers to CCNE1 proximal regions. CCNE1-rearranged GCs were associated with high CCNE1 expression, disrupted CCNE1 topologically associating domain (TAD) boundaries, and novel TAD interactions in CCNE1-rearranged primary tumours. We also observed IGF2 enhancer-based SVs, previously noted in colorectal cancer, highlighting a common non-coding genetic driver alteration in gastric and colorectal malignancies.ConclusionIntegrated paired-end NanoChIP-seq and WGS of gastric tumours reveals tumour-associated regulatory SV in regions associated with both simple and complex genomic rearrangements. Genomic rearrangements may thus exploit enhancer-hijacking as a common mechanism to drive oncogene expression in GC.

scholarly journals Allele-Specific Quantification of Structural Variations in Cancer Genomes

2016 ◽  
Author(s):  
Yang Li ◽  
Shiguo Zhou ◽  
David C. Schwartz ◽  
Jian Ma
Keyword(s):  
Whole Genome Sequencing ◽  
Genome Sequencing ◽  
Copy Number ◽  
Graphical Model ◽  
Genome Structure ◽  
Cancer Genome ◽  
Whole Genome ◽  
Structural Variations ◽  
Cancer Genomes ◽  
Allele Specific

AbstractOne of the hallmarks of cancer genome is aneuploidy, resulting in abnormal copy numbers of alleles. Structural variations (SVs) can further modify the aneuploid cancer genomes into a mixture of rearranged genomic segments with extensive range of somatic copy number alterations (CNAs). Indeed, aneuploid cancer genomes have significantly higher rate of CNAs and SVs. However, although methods have been developed to identify SVs and allele-specific copy number of genome (ASCNG) separately, no existing algorithm can simultaneously analyze SVs and ASCNG. Such integrated approach is particularly important to fully understand the complexity of cancer genomes. Here we introduce a new algorithm called Weaver to provide allele-specific quantification of SVs and CNAs in aneuploid cancer genomes. Weaver uses a probabilistic graphical model by utilizing cancer whole genome sequencing data to simultaneously estimate the digital copy number and inter-connectivity of SVs. Our simulation evaluation, comparison with single-molecule Optical Mapping analysis, and real data applications (including MCF-7, HeLa, and TCGA whole genome sequencing samples) demonstrated that Weaver is highly accurate and can greatly refine the analysis of complex cancer genome structure.

scholarly journals Linked-read whole-genome sequencing resolves common and private structural variants in multiple myeloma

2021 ◽  
Author(s):  
Lucía Peña Pérez ◽  
Nicolai Frengen ◽  
Julia Hauenstein ◽  
Charlotte Gran ◽  
Charlotte Gustafsson ◽  
...  
Keyword(s):  
Multiple Myeloma ◽  
Whole Genome Sequencing ◽  
Genome Sequencing ◽  
Cohort Analysis ◽  
Genomic Medicine ◽  
Molecular Classification ◽  
Regulatory Elements ◽  
Copy Number Variations ◽  
Whole Genome ◽  
Structural Variants

Multiple myeloma (MM) is an incurable and aggressive plasma cell malignancy characterized by a complex karyotype with multiple structural variants (SVs) and copy number variations (CNVs). Linked-read whole-genome sequencing (lrWGS) allows for refined detection and reconstruction of SVs by providing long-range genetic information from standard short-read sequencing. This makes lrWGS an attractive solution for capturing the full genomic complexity of MM. Here we show that high-quality lrWGS data can be generated from low numbers of FACS sorted cells without DNA purification. Using this protocol, we analyzed FACS sorted MM cells from 37 MM patients with lrWGS. We found high concordance between lrWGS and FISH for the detection of recurrent translocations and CNVs. Outside of the regions investigated by FISH, we identified >150 additional SVs and CNVs across the cohort. Analysis of the lrWGS data allowed for resolving the structure of diverse SVs affecting the MYC and t(11;14) loci causing the duplication of genes and gene regulatory elements. In addition, we identified private SVs causing the dysregulation of genes recurrently involved in translocations with the IGH locus and show that these can alter the molecular classification of the MM. Overall, we conclude that lrWGS allows for the detection of aberrations critical for MM prognostics and provides a feasible route for providing comprehensive genetics. Implementing lrWGS could provide more accurate clinical prognostics, facilitate genomic medicine initiatives, and greatly improve the stratification of patients included in clinical trials.

scholarly journals Genome-Wide Analysis of Non-Coding Alterations in Pan-Myeloid Cancers Using Whole Genome Sequencing

Blood ◽  
2018 ◽  
Vol 132 (Supplement 1) ◽  
pp. 103-103
Author(s):  
Yasuhito Nannya ◽  
Kenichi Yoshida ◽  
Lanying Zhao ◽  
June Takeda ◽  
Hiroo Ueno ◽  
...  
Keyword(s):  
Whole Genome Sequencing ◽  
Genome Sequencing ◽  
Research Funding ◽  
Large Cohort ◽  
Whole Genome ◽  
Structural Variations ◽  
Driver Genes ◽  
Complex Structural ◽  
Short Indels ◽  
Tandem Duplications

Abstract Background Intensive efforts of genome sequencing studies during the past decade identified >100 driver genes recurrently mutated in one or more subtypes of myeloid neoplasms, which collectively account for the pathogenesis of >90% of the cases. However, approximately 10% of the cases have no alterations in known drivers and their pathogenesis is still unclear. A possible explanation might be the presence of alterations in non-coding regions that are not detected by conventional exome/panel sequencing; mutations and complex structural variations (SVs) affecting these regions have been shown to deregulate expression of relevant genes in a variety of solid cancers. Unfortunately, however, no large studies have ever been performed, in which a large cohort of myeloid malignancies were analyzed using whole genome sequencing (WGS) in an attempt to identify a full spectrum of non-coding alterations, even though its efficacy have been demonstrated in many solid cancers. In this study, we performed WGS in a large cohort of pan-myeloid cancers, in which both coding and non-coding lesions were comprehensively analyzed. Patients and methods A total of 338 cases of myeloid malignancies, including 212 with MDS, 70 with AML, 17 with MDS/MPN, 23 with t-AML/MDS, and 16 with MPN were analyzed with WGS, of which 173 were also analyzed by transcriptome sequencing. Tumor samples were obtained from patients' bone marrow (N=269) or peripheral blood (N=69), while normal controls were derived from buccal smear (N=263) or peripheral T cells (N=75). Sequencing of target panel of 86 genes were performed for all samples. Sequencing data were processed using in-house pipelines, which were optimized for detection of complex structural variations (SVs) and abnormalities in non-coding sequences. Results WGS identified a median of 586,612 single nucleotide variants (SNVs) and 124,863 short indels per genome. NMF-based decomposition of the variants disclosed three major mutational signatures, which were characterized by age-related C>T transitions at CpG sites (Sig. A), C>T transitions at CpT sites (Sig. B), and T>C transitions at ApTpN context (Sig. C). Among these, Sig. C showed a prominent strand bias and corresponds to COSMIC signature 16, which has recently been implicated in alcohol drinking. Significant clustering of SNVs and short indels were interrogated across the genome divided into different window sizes (1Kbp, 10Kbp, 100Kbp) or confining the targets to coding exons and known regulatory regions, such as promoters, enhancers/super enhances, and DNase I hypersensitive sites. Recapitulating previous findings, SNVs in the coding exons were significantly enriched in known drivers, including TP53, TET2, ASXL1, DNMT3A, SF3B1, RUNX1, EZH2, and STAG2. We detected significant enrichment of SNVs in CpG islands, and promoters/enhancers. We also detected a total of 8,242 SVs with a median of 15 SVs/sample, which is more prevalent than expected from conventional karyotype analysis. Focal clusters of complex rearrangements compatible with chromothripsis were found in 8 cases, of which 7 carried biallelic TP53 alterations. NMF-based signature analysis of SVs revealed that large (>1Mb) deletions, inversions, and tandem duplications and translocations are clustered together and were strongly associated with TP53 mutations, while smaller deletions and tandem duplications, but not inversions, constitute another cluster. As expected, FLT3-ITD (N=15) and MLL-PTD (N=12) were among the most frequent SVs. Unexpectedly, in addition to known SVs associated with t(8;21) (RUNX1-RUNX1T1) (N=6) and t(3;21) (RUNX1-MECOM) (n=1) as well as non-synonymous SNVs within the coding exons (N=30), we detected frequent non-coding alterations affecting RUNX1, including SVs (N=15) and SNVs around splicing acceptor sites (N=5), suggesting that RUNX1 was affected by multiple mechanism, where as many as 38% of RUNX1 lesions were explained by non-coding alterations. Other recurrent targets of non-coding lesions included ASXL1, NF1, and ETV6. Conclusions WGS was successfully used to reveal a comprehensive registry of genetic alterations in pan-myeloid cancers. Non-coding alterations affecting known driver genes were more common than expected, suggesting the importance of detecting non-coding abnormalities in diagnostic sequencing. Disclosures Nakagawa: Sumitomo Dainippon Pharma Co., Ltd.: Research Funding. Usuki:Mochida Pharmaceutical: Speakers Bureau; Astellas Pharma Inc.: Research Funding; Sanofi K.K.: Research Funding; GlaxoSmithKline K.K.: Research Funding; Otsuka Pharmaceutical Co., Ltd.: Research Funding; Kyowa Hakko Kirin Co., Ltd.: Research Funding; Daiichi Sankyo: Research Funding; Celgene Corporation: Research Funding, Speakers Bureau; SymBio Pharmaceuticals Limited.: Research Funding; Shire Japan: Research Funding; Janssen Pharmaceutical K.K: Research Funding; Boehringer-Ingelheim Japan: Research Funding; Sumitomo Dainippon Pharma: Research Funding, Speakers Bureau; Pfizer Japan: Research Funding, Speakers Bureau; Novartis: Speakers Bureau; Nippon Shinyaku: Speakers Bureau; Chugai Pharmaceutical: Speakers Bureau; Takeda Pharmaceutical: Speakers Bureau; Ono Pharmaceutical: Speakers Bureau; MSD K.K.: Speakers Bureau. Chiba:Bristol Myers Squibb, Astellas Pharma, Kyowa Hakko Kirin: Research Funding. Miyawaki:Otsuka Pharmaceutical Co., Ltd.: Consultancy; Novartis Pharma KK: Consultancy; Astellas Pharma Inc.: Consultancy.

scholarly journals Whole genome sequencing identifies common and rare structural variants contributing to hematologic traits in the NHLBI TOPMed program

2021 ◽  
Author(s):  
Marsha M. Wheeler ◽  
Adrienne M Stilp ◽  
Shuquan Rao ◽  
Bjarni V Halldorsson ◽  
Doruk V Beyter ◽  
...  
Keyword(s):  
Blood Cell ◽  
Whole Genome Sequencing ◽  
Genome Sequencing ◽  
Association Studies ◽  
Regulatory Elements ◽  
Chromatin Domain ◽  
Genome Wide Association Studies ◽  
Whole Genome ◽  
Structural Variants ◽  
Genome Wide

Genome-wide association studies (GWAS) have identified thousands of single nucleotide variants and small indels that contribute to the genetic architecture of hematologic traits. While structural variants (SVs) are known to cause rare blood or hematopoietic disorders, the genome-wide contribution of SVs to quantitative blood cell trait variation is unknown. Here we utilized SVs detected from whole genome sequencing (WGS) in ancestrally diverse participants of the NHLBI TOPMed program (N=50,675). Using single variant tests, we assessed the association of common and rare SVs with red cell-, white cell-, and platelet-related quantitative traits. The results show 33 independent SVs (23 common and 10 rare) reaching genome-wide significance. The majority of significant association signals (N=27) replicated in independent datasets from deCODE genetics and the UK BioBank. Moreover, most trait-associated SVs (N=24) are within 1Mb of previously-reported GWAS loci. SV analyses additionally discovered an association between a complex structural variant on 17p11.2 and white blood cell-related phenotypes. Based on functional annotation, the majority of significant SVs are located in non-coding regions (N=26) and predicted to impact regulatory elements and/or local chromatin domain boundaries in blood cells. We predict that several trait-associated SVs represent the causal variant. This is supported by genome-editing experiments which provide evidence that a deletion associated with lower monocyte counts leads to disruption of an S1PR3 monocyte enhancer and decreased S1PR3 expression.

scholarly journals Evaluation of Single-Molecule Sequencing Technologies for Structural Variant Detection in Two Swedish Human Genomes

Genes ◽  
2020 ◽  
Vol 11 (12) ◽  
pp. 1444
Author(s):  
Nazeefa Fatima ◽  
Anna Petri ◽  
Ulf Gyllensten ◽  
Lars Feuk ◽  
Adam Ameur
Keyword(s):  
Whole Genome Sequencing ◽  
Genome Sequencing ◽  
Single Molecule ◽  
Large Scale ◽  
Whole Genome Sequencing Data ◽  
Whole Genome ◽  
Sequencing Data ◽  
Structural Variations ◽  
Single Molecule Sequencing ◽  
Human Samples

Long-read single molecule sequencing is increasingly used in human genomics research, as it allows to accurately detect large-scale DNA rearrangements such as structural variations (SVs) at high resolution. However, few studies have evaluated the performance of different single molecule sequencing platforms for SV detection in human samples. Here we performed Oxford Nanopore Technologies (ONT) whole-genome sequencing of two Swedish human samples (average 32× coverage) and compared the results to previously generated Pacific Biosciences (PacBio) data for the same individuals (average 66× coverage). Our analysis inferred an average of 17k and 23k SVs from the ONT and PacBio data, respectively, with a majority of them overlapping with an available multi-platform SV dataset. When comparing the SV calls in the two Swedish individuals, we find a higher concordance between ONT and PacBio SVs detected in the same individual as compared to SVs detected by the same technology in different individuals. Downsampling of PacBio reads, performed to obtain similar coverage levels for all datasets, resulted in 17k SVs per individual and improved overlap with the ONT SVs. Our results suggest that ONT and PacBio have a similar performance for SV detection in human whole genome sequencing data, and that both technologies are feasible for population-scale studies.

scholarly journals One substance to rule them all and in the darkness bind them: whole-genome sequencing illuminates multifaceted targets of humic adaptation in Eurasian perch

2021 ◽  
Author(s):  
Mikhail Ozerov ◽  
Kristina Noreikiene ◽  
Siim Kahar ◽  
Magnus Huss ◽  
Ari Huusko ◽  
...  
Keyword(s):  
Whole Genome Sequencing ◽  
Genome Sequencing ◽  
Extreme Environments ◽  
Gene Families ◽  
Regulatory Elements ◽  
Phenotypic Traits ◽  
Whole Genome ◽  
Humic Lakes ◽  
Whole Genome Analysis ◽  
Eurasian Perch

Extreme environments are inhospitable to the majority of species, but some organisms are able to survive in such hostile conditions due to evolutionary adaptations. For example, modern bony fishes have colonized various aquatic environments, including perpetually dark, hypoxic, hypersaline and toxic habitats. Eurasian perch (Perca fluviatilis) is among the few fish species of northern latitudes that is able to live in extremely acidic humic lakes. Such lakes represent almost “nocturnal” environments; they contain high levels of dissolved organic matter, which in addition to creating a challenging visual environment, also affects a large number of other habitat parameters and biotic interactions. To reveal the genomic targets of humic-associated selection, we performed whole-genome sequencing of perch originating from 16 humic and 16 clear-water lakes in northern Europe. We identified over 800,000 SNPs, of which >10,000 were identified as potential candidates under selection (associated with >3,000 genes) using multiple outlier approaches. Our findings suggest that adaptation to the humic environment involves hundreds of regions scattered across the genome. Putative signals of adaptation were detected in genes and gene families with diverse functions, including organism development and ion transportation. The observed excess of variants under selection in regulatory regions highlights the importance of adaptive evolution via regulatory elements, rather than via protein sequence modification. Our study demonstrates the power of whole-genome analysis to illuminate multifaceted nature of humic adaptation and highlights the next challenge moving from high-throughput outlier identification towards functional validation of causal mutations underlying phenotypic traits of ecological and evolutionary importance.

scholarly journals Evaluation of the Molecular Pathogenesis of Adrenocortical Tumors by Whole-Genome Sequencing

2021 ◽  
Vol 5 (Supplement_1) ◽  
pp. A68-A68
Author(s):  
Kerstin Neininger ◽  
Patrick May ◽  
Barbara Altieri ◽  
Juliane L Lippert ◽  
Kirsten Roomp ◽  
...  
Keyword(s):  
Whole Genome Sequencing ◽  
Genome Sequencing ◽  
Genetic Alterations ◽  
Driver Mutations ◽  
Whole Genome ◽  
Cortisol Secretion ◽  
Structural Variations ◽  
Driver Genes ◽  
Pathogenic Variants ◽  
Autonomous Cortisol Secretion

Abstract Pathogenesis of autonomous steroid secretion and adrenocortical tumorigenesis remains partially obscure. Our aim was to identify novel genetic alterations in adrenocortical adenomas (ACA) without somatic mutations in known driver genes. Whole-genome sequencing was performed on 26 ACA/blood-derived DNA pairs without driver mutations in PRKACA, GNAS and CTNNB1 genes at previous WES (ENSAT study JCEM 2016). These included 12 cortisol-producing adenomas with Cushing syndrome (CS-CPAs), 7 with mild autonomous cortisol secretion (MACS-CPAs), and 7 endocrine-inactive ACAs (EIAs). Seven adrenocortical carcinomas (ACC) were added to the cohort. We developed a bioinformatics pipeline for a comprehensive genome analysis and to reveal differences in variant distribution. Strelka, VarScan2 and ANNOVAR software and an in-house confidence score were used for variant calling and functional annotation. Combined Annotation-Dependent-Depletion (CADD) values were used to prioritize pathogenic variants. Additional focus relied on variants in pathogenically known pathways (Wnt/β-catenin, cAMP/PKA pathway). NovoBreak algorithm was applied to discover structural variations. Two hypermutated CS-CPA samples were excluded from further analysis. Using different filters, we detected variants in driver genes not observed at WES (one p.S45P in CTNNB1 and one p.R206L in PRKACA in two different CS-CPAs). In total, we report 179,830 variations (179,598 SNVs; 232 indels) throughout all samples, being more abundant in ACC (88,954) compared to ACA (CS-CPAs: 31,821; MACS-CPAs: 35,008; EIAs: 29,963). Most alterations were in intergenic (>50%), followed by intronic and ncRNA intronic regions. A total of 32 predicted pathogenic variants were found in both coding (CADD values ≥ 15) and non-coding (CADD values ≥ 5) regions. We found 3,301 possibly damaging and recurrent variants (intergenic mutations removed) (CS-CPAs: 1,463; MACS-CPAs: 1,549; EIAs: 1,268; ACC: 1,660), mostly accumulated in intronic regions. Some of these were detected in members of the Wnt/β-catenin (CS-CPAs: 6; MACS-CPAs: 2; EIA: 1) and cAMP/PKA (CS-CPAs: 6; MACS-CPAs: 7; EIA: 4) pathways (e.g. ADCY1, ADCY2, GNA13, PDE11A). We also found a slightly higher number of structural variations in EIA (3,620) and ACC (3,486) compared to CS-CPAs (977) and MACS-CPAs (2,119). In conclusion, still unrevealed genetic alterations, especially in intronic regions, may accompany early adrenal tumorigenesis and/or autonomous cortisol secretion.

scholarly journals Characterization of intermediate-sized insertions using whole genome sequencing data and analysis of their functional impacts on gene expression

2021 ◽  
Author(s):  
Saeideh Ashouri ◽  
Jing Hao Wong ◽  
Hidewaki Nakagawa ◽  
Mihoko Shimada ◽  
Katsushi Tokunaga ◽  
...  
Keyword(s):  
Gene Expression ◽  
Whole Genome Sequencing ◽  
Genome Sequencing ◽  
Gene Expression Regulation ◽  
Regulatory Elements ◽  
Expression Regulation ◽  
Ctcf Binding ◽  
Whole Genome Sequencing Data ◽  
Whole Genome ◽  
Sequencing Data

Abstract Intermediate-sized insertions are one of the structural variants contributing to genome diversity. However, due to technical difficulties in identifying them, their importance in disease pathogenicity and gene expression regulation remains unclear. We used whole-genome sequencing data of 174 Japanese samples to characterize intermediate-sized insertions using a highly-accurate insertion calling method (IMSindel software and joint-call recovery) and obtained a catalogue of 4,254 insertions. We constructed an imputation panel comprising of insertions and SNVs from all samples, and conducted imputation of intermediate-sized insertions for 82 publicly-available Japanese samples. Imputation accuracy, evaluated using Nanopore long-read sequencing data, was 97%. Subsequent eQTL analysis predicted 128 (~ 3.0%) insertions as causative for gene expression level changes. Enrichment analysis of causal insertions for genome regulatory elements showed significant associations with CTCF-binding sites, super-enhancers, and promoters. Among 17 causal insertions found in the same causal set with GWAS hits, there were insertions associated with changes in expression of cancer-related genes such as BRCA1, ZNF222, and ABCB10. Analysis of insertions sequences revealed that 461 insertions were short tandem duplications frequently found in early replicating regions of genome. Furthermore, comparison of functional importance of intermediate-sized insertions with that of intermediate-sized deletions detected in the same sample set in our previous study showed that insertions were more frequent in genic regions, and proportion of functional candidates was smaller in insertions. Here, we characterize a high-confidence set of intermediate-sized insertions and indicate their importance in gene expression regulation. Our results emphasize the importance of considering intermediate-sized insertions in trait association studies.

Integrated Molecular Analysis of Myelodysplastic Syndromes Using Whole Genome Sequencing

Blood ◽  
2016 ◽  
Vol 128 (22) ◽  
pp. 5512-5512
Author(s):  
Yasuito Nannya ◽  
Yoshida Kenichi ◽  
Keisuke Kataoka ◽  
Yasunobu Nagata ◽  
Tetsuichi Yoshizato ◽  
...  
Keyword(s):  
Whole Genome Sequencing ◽  
Genome Sequencing ◽  
Research Funding ◽  
Genetic Alterations ◽  
Whole Genome ◽  
Structural Variations ◽  
Coding Regions ◽  
Molecular Events ◽  
Targeted Capture ◽  
Capture Sequencing

Abstract Background Myelodysplastic syndromes (MDS) are a heterogeneous group of myeloid malignancies characterized by refractory cytopenias with marrow dysplasia, which frequently progress to acute myeloid leukemia (AML). Although poorly understood in the previous era, the molecular events that underlie the pathogenesis of MDS have been intensively studied using advanced genomics in the past decade and are now fully catalogued into an array of well-defined functional pathways. However, mostly obtained through exome/targeted-capture sequencing, our knowledge about these molecular events is largely confined to those of single nucleotide variations (SNVs) and short indels, as well as arm-level copy number lesions, mostly within the coding sequences. Alterations in the non-coding regions, particularly a diversity of structural variations, in MDS genomes remain to be investigated in most part, even though the relevance of such lesions has recently been unequivocally demonstrated for other cancer types through large-scale whole genome sequencing (WGS) studies. Unfortunately, however, only a small number of MDS samples have been fully analyzes and inspected for genetic alterations using WGS. Patients and Methods In the present study, we performed an integrated, unbiased molecular study of 60 MDS cases, using whole genome sequencing (WGS) in combination with exome and transcriptome sequencing as well as methylome analysis. Paired tumor/germline DNA were obtained from patients' bone marrow and buccal smear samples. Sequencing data were analyzed using novel in-house pipelines, which were tuned to optimize detection of complex structural variations (SVs) and abnormalities in non-coding sequences. For some patients, multiple longitudinal materials were obtained along with their clinical course. Results WGS identified SNVs across the entire genome with a mean of 5.7/Mb/genome with a clear predominance of age-related C to T transitions, followed by other signatures. The spectrum of major targets of somatic mutations successfully recapitulated the previously reported one in MDS, including those involving splicing factors (SRSF2, SF3B1, U2AF1, and ZRSR2), epigenetic regulators (DNMT3A, ASXL1, TET2, BCOR, and EZH2), transcription factors (RUNX1, ETV6, and CUX1), signal transducing molecules (NRAS, KRAS, FLT3, PTPN11, CBL), and other critical molecules (TP53, NPM1, and STAG2). Moreover, other somatic variants within the coding regions were also identified that had already been reported in other human cancers but not in MDS, such as NCOR2X, MUC6, and TIAM2. The analysis of SVs unexpectedly revealed the complexity of MDS genomes. Most of the MDS genomes analyzed had a heavy burden of SVs including tandem duplications, deletions, translocations, and inversions, with a mean of 7.2/genome, which was far more than expected from conventional cytogenetics and array-based karyotyping. Complex rearrangements were common, frequently converging into particular chromosomes, suggesting multiple genetic events at a single genetic insult. Known targets of SNVs and indels were often affected by SVs, which largely escaped from conventional exome and targeted-capture sequencing, including RUNX1, TET2, FHITand other genes, suggesting that conventional platforms may substantially underestimate the frequency of alterations for some genes. Concomitant transcriptome analysis allowed to correlated abnormal splicing with somatic intronic events otherwise undetectable. Furthermore, comprehensive analysis of genomic aberrations in longitudinal samples enabled us to delineate the clonal architecture of the cellular population in MDS and their dynamics during the AML progression or clonal changes caused by AZA treatment. Conclusions Integrated molecular analysis using WGS and other platforms revealed the complexity of MDS genomes previously unexpected and reveal novel genetic alterations. Our results should help to extend our knowledge about the genomic landscape of MDS and provide novel insights into the molecular pathogenesis and clonal dynamics of MDS. Disclosures Kataoka: Kyowa Hakko Kirin: Honoraria; Boehringer Ingelheim: Honoraria; Yakult: Honoraria. Naoe:Pfizer Inc.: Research Funding; CMIC Co., Ltd.: Research Funding; Kyowa-Hakko Kirin Co.,Ltd.: Honoraria, Patents & Royalties, Research Funding; Otsuka Pharmaceutical Co.,Ltd.: Honoraria, Research Funding; Nippon Boehringer Ingelheim Co., Ltd.: Honoraria, Research Funding; Amgen Astellas BioPharma K.K.: Honoraria; TOYAMA CHEMICAL CO.,LTD.: Research Funding; Chugai Pharmaceutical Co.,LTD.: Honoraria, Patents & Royalties; Celgene K.K.: Honoraria, Research Funding; Sumitomo Dainippon Pharma Co.,Ltd.: Honoraria, Research Funding; Fujifilm Corporation: Honoraria, Patents & Royalties, Research Funding; Bristol-Myers Squibb: Honoraria; Astellas Pharma Inc.: Research Funding. Kiyoi:Celgene Corporation: Consultancy; MSD K.K.: Research Funding; Mochida Pharmaceutical Co., Ltd.: Research Funding; Nippon Boehringer Ingelheim Co., Ltd.: Research Funding; Kyowa-Hakko Kirin Co.LTD.: Research Funding; Fujifilm Corporation: Patents & Royalties, Research Funding; JCR Pharmaceutlcals Co.,Ltd.: Research Funding; Alexion Pharmaceuticals: Research Funding; Yakult Honsha Co.,Ltd.: Research Funding; Eisai Co., Ltd.: Research Funding; Chugai Pharmaceutical Co. LTD.: Research Funding; Toyama Chemikal Co.,Ltd.: Research Funding; Astellas Pharma Inc.: Consultancy, Research Funding; Phizer Japan Inc.: Research Funding; Novartis Pharma K.K.: Research Funding; Nippon Shinyaku Co., Ltd.: Research Funding; Takeda Pharmaceutical Co., Ltd.: Research Funding; Sumitomo Dainippon Pharma Co., Ltd.: Research Funding; Zenyaku Kogyo Co.LTD.: Research Funding; AlexionpharmaLLC.: Research Funding. Ogawa:Kan research institute: Consultancy, Research Funding; Takeda Pharmaceuticals: Consultancy, Research Funding; Sumitomo Dainippon Pharma: Research Funding.

Sign in / Sign up

Export Citation Format

Share Document