Kooperativer Bibliotheksverbund

In: International Journal of Cancer, Wiley, Vol. 139, No. 11 ( 2016-12), p. 2512-2518

Abstract: What's new? While the number of patients with virus‐related hepatocellular carcinoma (HCC) is expected to decline thanks to advanced anti‐virus therapy, the number of patients with nonalcoholic fatty liver disease‐derived HCC (NAFLD‐HCC) has been raising worldwide due to increased prevalence of metabolic syndrome. The molecular features of NAFLD‐HCC remain to be fully determined. Here, the authors analyzed genetic aberrations in NAFLD‐HCC tumor samples by whole‐exome sequencing, targeted sequencing, and copy number variation studies. Although NAFLD‐HCC shared similar genetic aberration profiles with HCC from other etiologies, TERT promoter mutations and chromosome 8p loss emerged as potentially essential factors in NAFLD‐derived liver carcinogenesis.

Type of Medium: Online Resource

ISSN: 0020-7136 , 1097-0215

URL: Issue

URL: Article

DOI: 10.1002/ijc.v139.11

DOI: 10.1002/ijc.30379

Language: English

Publisher: Wiley

Publication Date: 2016

detail.hit.zdb_id: 218257-9

detail.hit.zdb_id: 1474822-8

In: Blood, American Society of Hematology, Vol. 138, No. Supplement 1 ( 2021-11-05), p. 610-610

Abstract: Background: Acute erythroid leukemia (AEL) is a rare subtype of AML characterized by erythroid predominant proliferation and classified into two subtypes with pure erythroid (PEL) and myeloid/erythroid (MEL) phenotypes. Although several reports described gene mutations in AEL, genotype phenotype correlations have not fully been elucidated with little knowledge about feasible molecular targets for therapy. Methods: To understand the mechanism of the erythroid dominant phenotype of AEL and identify potential therapeutic targets for AEL, we analyzed a total of 121 adult AEL cases with the median age of 60 (23-87), using whole genome/exome sequencing of 35 cases, followed by targeted-capture sequencing of 387 genes together with 1,279 SNP loci for copy number measurements in all cases. Among these, 21 were also analyzed by RNA sequencing. Genetic profiles of these AEL cases were compared to those of 409 cases with non-erythroid AML (non-AEL) including 195 cases from The Cancer Genome Atlas. Six patient-derived xenografts (PDX) were established from AEL with JAK2 and/or EPOR focal gain/amplification/mutation. PDX cells were inoculated into immune-deficient mice and tested for their response to JAK1/2 inhibitor. Results: According to unique genetic alterations, AEL was classified into 4 genomic groups (A-D). Characterized by TP53 mutations and complex karyotype, Group A was the most common subtype (48/121; 40%) and showed very poor prognosis. Remarkably, almost all the PEL cases (12/13; 92%) were categorized into Group A. Conspicuously, 75% of PEL cases with TP53 mutation had focal gain/amplifications/mutations of JAK2 (5/12; 42%), EPOR (7/12; 58%), and ERG/ETS2 (1/12; 8%) loci on chromosomes 9p, 19q, and 21q, respectively, while 34% of MEL cases with TP53 mutation had focal gain/amplifications/mutations of JAK2 (2/29; 7%), EPOR (7/29;24%), and ERG/ETS2 (7/29;24%) loci, frequently in combination. Group B was characterized by frequent NPM1 mutations, in contrast to the frequent co-mutation of FLT3 in the corresponding subgroup of NPM1-mutated cases in non-AEL, whereas NPM1-mutated patents in this group lacked FLT3 mutations but had frequent PTPN11 mutations (8/16; 50%), which were much less common in non-AEL (15/101; 15%). All cases in Group C (n=22, 18%), another prevalent form of AEL, had STAG2 mutations and classified in MEL. Prominently, 68% (17/25) of STAG2-mutated AEL cases had KMT2A-PTD, which was rarely found in non-AEL cases. The remaining cases were categorized into Group D, which was enriched for mutations in ASXL1, BCOR, PHF6, RUNX1 and TET2. We also identified recurrent loss-of-function USP9X mutations in this group, which were previously reported in ALL with an upregulated JAK-STAT pathway. In RNA sequencing analysis, AEL cases exhibited gene expression profiles implicated in an upregulated STAT5 signaling pathway, which was seen not only in those cases with JAK2 or EPOR focal gain/amplification/mutation, but also in AEL without these amplifications, suggesting that aberrantly upregulated STAT5 activation might represent a common molecular signature of AEL. Survival analysis revealed that TP53 mutation is a poor prognostic factor in AEL and non-AEL and no statistically significant difference between AEL and non-AEL with TP53 mutation. Intriguingly, 19p gains/amplifications were associated with a significantly poor prognostic prognosis in TP53-mutated AEL cases. Based on this finding, we evaluated the effect of a JAK inhibitor, ruxolitinib, on 6 PDX models established from AEL having TP53 mutations and JAK2 and EPOR mutation/amplification. Of interest , ruxolitinib significantly suppressed cell growth and prolonged overall survival in mice engrafted with 4 PDX models with STAT5 downregulation, although the other 2 models were resistant to JAK2 inhibition with persistent STAT5 activation. Conclusion: AEL is a heterogeneous group of AML, of which PEL is characterized by frequent amplifications/mutations in JAK2 and/or EPOR. Frequent involvement of EPOR/JAK/STAT pathway is a common feature of AEL, in which a therapeutic role of JAK inhibition was suggested. Disclosures Nakagawa: Sumitomo Dainippon Pharma Oncology, Inc.: Research Funding. Yoda: Chordia Therapeutics Inc.: Research Funding. Morishita: Chordia Therapeutics Inc.: Current Employment, Current equity holder in publicly-traded company. Miyazaki: Sumitomo-Dainippon: Honoraria, Research Funding; Astellas: Honoraria; Chugai: Honoraria; Abbvie: Honoraria; Novartis: Honoraria; Nippon-Shinyaku: Honoraria; Bristol-Myers Squibb: Honoraria; Takeda: Honoraria; Daiichi-Sankyo: Honoraria; Kyowa-Kirin: Honoraria; Eisai: Honoraria; Janssen: Honoraria; Pfizer: Honoraria; Sanofi: Honoraria. Usuki: Alexion: Speakers Bureau; Eisai: Speakers Bureau; MSD: Speakers Bureau; PharmaEssentia: Speakers Bureau; Yakult: Speakers Bureau; Mundipharma: Research Funding; Astellas-Amgen-Biopharma: Research Funding; Nippon Boehringer Ingelheim: Research Funding; Takeda: Research Funding, Speakers Bureau; Celgene: Research Funding, Speakers Bureau; Janssen: Research Funding; Ono: Research Funding, Speakers Bureau; Otsuka: Research Funding, Speakers Bureau; Sumitomo Dainippon: Research Funding; Daiichi Sankyo: Research Funding, Speakers Bureau; Symbio: Research Funding, Speakers Bureau; Gilead: Research Funding; Abbvie: Research Funding; Nippon shinyaku: Research Funding, Speakers Bureau; Novartis: Research Funding, Speakers Bureau; Pfizer: Research Funding; Kyowa Kirin: Research Funding, Speakers Bureau; Brisol-Myers Squibb: Research Funding, Speakers Bureau; Astellas: Research Funding, Speakers Bureau. Maciejewski: Bristol Myers Squibb/Celgene: Consultancy; Regeneron: Consultancy; Novartis: Consultancy; Alexion: Consultancy. Ohyashiki: Novartis Pharma: Other: chief clinical trial; Bristol Myers Squibb: Membership on an entity's Board of Directors or advisory committees. Ganser: Celgene: Honoraria; Novartis: Honoraria; Jazz Pharmaceuticals: Honoraria. Heuser: Roche: Membership on an entity's Board of Directors or advisory committees, Research Funding; Bayer Pharma AG: Research Funding; Karyopharm: Research Funding; Daiichi Sankyo: Membership on an entity's Board of Directors or advisory committees, Research Funding; BergenBio: Research Funding; Janssen: Honoraria; Novartis: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding; Astellas: Research Funding; AbbVie: Membership on an entity's Board of Directors or advisory committees, Research Funding; Tolremo: Membership on an entity's Board of Directors or advisory committees; Jazz: Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding; BMS/Celgene: Membership on an entity's Board of Directors or advisory committees, Research Funding; Pfizer: Membership on an entity's Board of Directors or advisory committees, Research Funding. Thol: Astellas: Honoraria; Abbvie: Honoraria; Novartis: Honoraria; Jazz: Honoraria; BMS/Celgene: Honoraria, Research Funding; Pfizer: Honoraria. Shih: PharmaEssentia Co: Consultancy, Membership on an entity's Board of Directors or advisory committees; Celgene Ltd: Research Funding; Ltd: Research Funding; Novartis: Research Funding. Takaori-Kondo: Celgene: Research Funding; Bristol-Myers K.K.: Honoraria; ONO PHARMACEUTICAL CO., LTD.: Research Funding. Ogawa: Otsuka Pharmaceutical Co., Ltd.: Research Funding; Eisai Co., Ltd.: Research Funding; Kan Research Laboratory, Inc.: Consultancy, Research Funding; Dainippon-Sumitomo Pharmaceutical, Inc.: Research Funding; ChordiaTherapeutics, Inc.: Consultancy, Research Funding; Ashahi Genomics: Current holder of individual stocks in a privately-held company.

Type of Medium: Online Resource

ISSN: 0006-4971 , 1528-0020

URL: Article

DOI: 10.1182/blood-2021-152800

Language: English

Publisher: American Society of Hematology

Publication Date: 2021

detail.hit.zdb_id: 1468538-3

detail.hit.zdb_id: 80069-7

In: Blood, American Society of Hematology, Vol. 134, No. Supplement_1 ( 2019-11-13), p. 4216-4216

Abstract: Background Copy-number alterations (CNAs) and gene mutations are hallmarks of cancer genomes, and they are implicated in the development of myeloid neoplasm. However, their relationships have not been fully examined. To address this issue, we have recently developed a novel, next-generation sequencing-based platform for copy-number analysis, which enabled us to detect mutations and CNAs simultaneously. We applied this platform to around 2,000 cases with myeloid neoplasms. Aims We aimed at delineating the landscape of CNAs and their relationships with gene mutations in myeloid neoplasms. Methods We examined 2,101 cases with myeloid neoplasms by whole-exome sequencing (WES) or targeted deep sequencing. Excluding 116 samples showing low qualities of copy-number signals, we performed subsequent analysis on the remaining 1,985 cases with myelodysplastic syndromes (MDS, n = 1,102), myelodysplastic/myeloproliferative neoplasms (MDS/MPN, n = 140), de novo acute myeloid leukemia (de novo AML, n = 448), and secondary AML (sAML, n = 295). In copy-number analysis, total copy numbers and allele-specific copy numbers (ASCNs) were quantified based on sequencing depths and allelic ratios on genome-wide probes. Copy-number signals were corrected for multiple biases (e.g. GC content, ASCN, and fragment length). We also validated the performance of this platform through comparison with SNP-array karyotyping data in 115 de novo AML cases. CNAs longer than 5 Mb were regarded as arm-level CNAs, and those shorter than 5 Mb were regarded as focal CNAs. Results In total, we identified 4,141 CNAs (52.9 % of cases with at least one CNA), and 3,863 mutations (73.9 % of cases with at least one mutation). Most frequent alterations included -7/del(7q) (13.2 %), del(5q) (11.4 %), trisomy 8 (7.2 %), and del(20q) (5.2 %), and mutations of TET2 (12 .3 %), TP53 (11.3 %), ASXL1 (10.1%), and DNMT3A (9.9 %). To evaluate the difference of copy-number landscapes between de novo AML and myelodysplasia (MDS, MDS/MPN, and sAML), we compared the frequencies of CNAs between them. Uni-parental disomy (UPD) of 13q (FLT3) and 11p (WT1), and amplifications of 11q, 13q, and 21q (ERG) were more enriched in de novo AML, while der(1;7), UPD of 11q (CBL), and del(20q) were enriched in myelodysplasia, suggesting differential involvements of CNAs. We next analyzed the correlations between CNA profiles and prognosis in cases with myelodysplasia. Since TP53 status implies a large impact on both patients' prognosis and CNA profiles, we separately analyzed TP53-positive (n = 53) and negative (n = 686) cases with available survival data. In TP53-negative cases, -7/7qLOH (Hazard ratio(HR): 2.28, q 〈 0.001), and UPD of 11q (CBL) (HR: 2.60, q = 0.0034) significantly correlated with shorter overall survivals (OS), while, in TP53-positive cases, amp(11q), +19, and amp(21q) were marginally associated with shorter OS. To delineate the relationships between CNAs and mutations, we interrogated correlations between both lesions among MDS cases without TP53 alterations (n = 937). A number of significant correlations were detected, such as those between trisomy 8 and del(20q) with U2AF1 mutations (q 〈 0.05, for each), and monosomy 7 and amp(21q) with mutations of RUNX1 and NRAS (q 〈 0.01, for each). These correlations were also revealed in clustering analysis based on CNA and mutation profiles, which identified 5 unique clusters: Cluster 1 (n = 171) with trisomy 8, del(20q), and mutations of U2AF1 and ETV6, Cluster 2 (n = 43) with monosomy 7, amp(21q), and mutations of NRAS, SETBP1, and RUNX1, Cluster 3 (n = 19) with amp(1q) and amp(3q), Cluster 4 (n = 127) with those of SF3B1, TET2, and DNMT3A, and Cluster 5 (n = 50) with those of SRSF2, STAG2, ASXL1, and RUNX1. The remaining 527 cases were not assigned into any cluster due to lack of significantly correlated alterations. Finally, the temporal relationships of coexisting alterations were estimated based on their cell fractions; monosomy 7 had significantly greater cell fractions (P = 0.031) and is predicted to precede NRAS mutations, while the cell fractions of U2AF1 mutations tended to be greater than those of trisomy 8 (P = 0.063), suggesting their implications in different stages of disease progression. Conclusion An integrated analysis of CNAs and mutations in 〉 2,000 cases revealed the impacts of CNAs on disease characteristics and provided novel insight into the interplay between CNAs and mutations in the pathogenesis of MDS. Figure Disclosures Atsuta: CHUGAI PHARMACEUTICAL CO., LTD.: Honoraria; Kyowa Kirin Co., Ltd: Honoraria. Kanda:Celgene: Consultancy, Research Funding; Novartis: Research Funding; Shionogi: Consultancy, Honoraria, Research Funding; Nippon-Shinyaku: Research Funding; Taiho: Research Funding; Asahi-Kasei: Research Funding; Bristol-Myers Squibb: Consultancy, Honoraria; Takeda: Consultancy, Honoraria, Research Funding; Eisai: Consultancy, Honoraria, Research Funding; Eisai: Consultancy, Honoraria, Research Funding; Dainippon Sumitomo: Consultancy, Honoraria, Research Funding; Otsuka: Research Funding; Kyowa-Hakko Kirin: Consultancy, Honoraria, Research Funding; Ono: Consultancy, Honoraria, Research Funding; MSD: Research Funding; Chugai: Consultancy, Honoraria, Research Funding; CSL Behring: Research Funding; Taisho-Toyama: Research Funding; Tanabe Mitsubishi: Research Funding; Dainippon Sumitomo: Consultancy, Honoraria, Research Funding; Takeda: Consultancy, Honoraria, Research Funding; Kyowa-Hakko Kirin: Consultancy, Honoraria, Research Funding; Bristol-Myers Squibb: Consultancy, Honoraria; Astellas: Consultancy, Honoraria, Research Funding; Takara-bio: Consultancy, Honoraria; Novartis: Research Funding; Astellas: Consultancy, Honoraria, Research Funding; Sanofi: Research Funding; Pfizer: Research Funding; Asahi-Kasei: Research Funding; Alexion: Consultancy, Honoraria; CSL Behring: Research Funding; Takara-bio: Consultancy, Honoraria; Mochida: Consultancy, Honoraria; Taiho: Research Funding; Celgene: Consultancy, Research Funding; Tanabe Mitsubishi: Research Funding; Taisho-Toyama: Research Funding; Pfizer: Research Funding; Sanofi: Research Funding; Mochida: Consultancy, Honoraria; Alexion: Consultancy, Honoraria; Otsuka: Research Funding. Sekeres:Celgene: Membership on an entity's Board of Directors or advisory committees; Millenium: Membership on an entity's Board of Directors or advisory committees; Syros: Membership on an entity's Board of Directors or advisory committees. Saunthararajah:EpiDestiny: Consultancy, Equity Ownership, Patents & Royalties; Novo Nordisk: Consultancy. Miyazaki:Chugai: Research Funding; Otsuka: Honoraria; Novartis: Honoraria; Nippon-Shinyaku: Honoraria; Dainippon-Sumitomo: Honoraria; Kyowa-Kirin: Honoraria. Usuki:Boehringer-Ingelheim Japan: Other: Received Research ; Daiichi Sankyo: Other: Received Research ; SymBio Pharmaceuticals Limited.,: Other: Received Research ; Novartis: Speakers Bureau; Ono Pharmaceutical: Speakers Bureau; Takeda Pharmaceutica: Speakers Bureau; Chugai Pharmaceutical: Speakers Bureau; Nippon Shinyaku: Speakers Bureau; Mochida Pharmaceutical: Speakers Bureau; MSD K.K.: Speakers Bureau; Celgene Corporation: Other: Received Research , Speakers Bureau; Sumitomo Dainippon Pharma: Other: Received Research , Speakers Bureau; Pfizer Japan: Other: Received Research ; Stellas Pharma: Other: Received Research ; Otsuka: Other: Received Research ; Kyowa Kirin: Other: Received Research ; GlaxoSmithKline K.K.: Other: Received Research ; Sanofi K.K.: Other: Received Research ; Shire Japan: Other: Received Research ; Janssen Pharmaceutical K.K: Other: Received Research . Imada:Bristol-Meyer Squibb K.K.: Honoraria; Celgene K.K.: Honoraria; Chugai Pharmaceutical Co., Ltd.: Honoraria; Kyowa Hakko Kirin Co., Ltd.: Honoraria; Ono Pharmaceutical Co., Ltd.: Honoraria; Otsuka Pharmaceutical Co., Ltd.: Honoraria; Astellas Pharma Inc.: Honoraria; Novartis Pharma K.K.: Honoraria; Takeda Pharmaceutical Co.,LTD.: Honoraria; Nippon Shinyaku Co.,Ltd.: Honoraria. Takaori-Kondo:Kyowa Kirin: Research Funding; Pfizer: Honoraria; Janssen: Honoraria; Chugai: Research Funding; Takeda: Research Funding; Ono: Research Funding; Bristol-Myers Squibb: Honoraria, Research Funding; Novartis: Honoraria; Celgene: Honoraria, Research Funding. Kiguchi:Celltrion, Inc.: Research Funding; Astellas Pharmaceutical Co., Ltd.: Research Funding; Nippon Shinyaku Co., Ltd.: Research Funding; Otsuka Pharmaceutical Co., Ltd.: Research Funding; Kyowa Hakko Kirin Co., Ltd.: Research Funding; MSD CO., Ltd.: Research Funding; Novartis Pharmaceutical Co., Ltd.: Research Funding; Sumitomo Dainippon Pharmaceutical Co., Ltd.: Research Funding; Bristol-Myeres Squibb Co., Ltd.: Research Funding; Janssen Pharmaceutical Co., Ltd.: Research Funding; Celgene Co., Ltd.: Research Funding; SymBio Pharmaceutical Co., Ltd.: Research Funding; Taiho Pharmaceutical Co., Ltd.: Research Funding; Tejin Co., Ltd.: Research Funding; Sanofi K.K., Ltd.: Research Funding. Maciejewski:Alexion: Consultancy; Novartis: Consultancy. Ogawa:Asahi Genomics: Equity Ownership; Qiagen Corporation: Patents & Royalties; Dainippon-Sumitomo Pharmaceutical, Inc.: Research Funding; RegCell Corporation: Equity Ownership; ChordiaTherapeutics, Inc.: Consultancy, Equity Ownership; Kan Research Laboratory, Inc.: Consultancy.

Type of Medium: Online Resource

ISSN: 0006-4971 , 1528-0020

URL: Article

DOI: 10.1182/blood-2019-132174

Language: English

Publisher: American Society of Hematology

Publication Date: 2019

detail.hit.zdb_id: 1468538-3

detail.hit.zdb_id: 80069-7

In: Blood, American Society of Hematology, Vol. 122, No. 21 ( 2013-11-15), p. 3000-3000

Abstract: Angioimmunoblastic T-cell lymphoma (AITL) is a distinct subtype of T-cell lymphoma, characterized by generalized lymphadenopathy and frequent autoimmune-like manifestations. The diagnosis of AITL is sometimes challenging for hematopathologists, because the tumor cell content is generally low and relatively large reactive lymphocytes are confused as tumor cells. Possibly because of the low tumor cell frequency, clonal rearrangement of T-cell receptor gene is undetectable in 30% of the cases. We identified recurrent mutations in RHOA at c.G50T, predicting to generate p.G17V in 70% of AITL and PTCL-NOS harboring AITL features, which implies diagnostic properties for AITL (M S-Y and SC, unpublished). Purpose To establish a novel cost-effective method to diagnose AITL, we performed allele-specific realtime PCR to detect RHOA G17V mutation. Methods Genomic DNA was extracted from 119 AITL and PTCL-NOS samples, which include 47 periodate-lysine-paraformaldehyde (PLP)-fixed, 12 formalin-fixed-paraffin- embedded (FFPE) and 60 frozen tissues. Forty-one out of 60 genomic DNA samples, purified from frozen tissue, were amplified by RepliG kit (QIAGEN). Allele-specific primers for RHOA G17V mutant and wild-type sequences were designed by Wangkumhang's algorithm. The [mut] and [WT] values were individually measured by realtime PCR using each primer set, and the [mut]/([mut] +[WT]) values were calculated. Mutant allele frequencies were determined by amplicon-based deep sequencing using MiSeq. Results The [mut] values were distributed from 1.5×10-7 to 7.6×10-2, and the [WT] values were from 7.9×10-5 to 1.3×10-2. The [mut]/[mut] +[WT] values were distributed from 1.9×10-4 to 8.5×10-1. We set a cut-off value to determine existence of mutation as 2% for MiSeq, and 1.3×10-2 for the [mut] /([mut]+[WT] ) value. Then we compared these two methods to detect RHOA G17V mutation. Forty-three cases were positive for the RHOA mutation in this study cohort by MiSeq, including 32 AITL and 11 PTCL-NOS cases. The [mut]/([mut] +[WT]) values of DNA from FFPE samples tend to be lower than those from other samples, and 4 out of 12 FFPE samples determined as mutation-positive by MiSeq were not detected by our allele-specific realtime PCR. We therefore excluded the FFPE samples and analyzed the data of 107 DNA samples, purified from PLP-fixed and frozen tissues. Rank correlation coefficient was 0.753. Sensitivity was 97.4%, and specificity was 97.1%. Positive concordance rate was 94.9%, and negative concordance rate was 98.6%. Conclusions We established a method to detect RHOA G17V hotspot mutation for AITL. It is expected to be highly accurate and cost effective. Disclosures: No relevant conflicts of interest to declare.

Type of Medium: Online Resource

ISSN: 0006-4971 , 1528-0020

URL: Article

DOI: 10.1182/blood.V122.21.3000.3000

Language: English

Publisher: American Society of Hematology

Publication Date: 2013

detail.hit.zdb_id: 1468538-3

detail.hit.zdb_id: 80069-7

In: Blood, American Society of Hematology, Vol. 124, No. 21 ( 2014-12-06), p. 823-823

Abstract: Somatic mutations constitute key pathogenetic elements in MDS. Unbiased whole exome sequencing (WES) and deep NGS led to discovery of new somatic mutations and also to the recognition of i) tremendous diversity of mutations and their combinations; ii) individual intra-tumor heterogeneity and clonal hierarchy. Chromosomal lesions further increase the complexity of molecular defects. While in MDS molecular defects are acquired in order, observations made in AML highlight the importance of ancestral events; e.g., t(8;21), inv16 or t(15;17) and other lesions that are used as the basis for nosological sub-classification. Thus, it is the identity of individual ancestral events or their classes rather than the spectrum of secondary events or the distribution of mutations, that will allow for molecular, functionally-relevant and diagnostically useful classification within MDS. This would explain why only a few somatic mutations have been found to be prognostically important, as their position in the clonal hierarchy has not been accounted for. With this in mind, we applied WES (N=206) and targeted deep NGS (N=836) and studied 100 samples serially with analyses focused on ancestral events. Globally, through WES we identified and validated 2386 mutational events in 1458 genes. Of these, 112 genes were mutated at significant frequencies (q 〈 0.05); groups of affected genes involved in splicing, transcription, DNA methylation, histone modification, and others were distinguished. On average, 9 somatic events per MDS case, 10.7 in secondary AML, and 12.5 in MDS/MPN were found. Resequencing in combination with SNP-array karyotyping provided information on variant allelic frequency (VAF) adjusted for corresponding zygosity of mutations; 99% of cases displayed clear intra-tumor heterogeneity due to multiple clones defined by hierarchically acquired somatic mutational patterns. Using cross-sectional analyses, the highest mean VAF could be interpreted as consistent with the ancestral nature of the mutations, as seen for instance in a proportion of TET2 and SF3B1 mutant cases. In contrast, the lowest mean VAF indicated secondary events, as occur in NPM1 and RAS pathway mutations. Similar conclusions were made based on cross-sectional analyses showing a similar distribution of ancestral but not secondary events in MDS and sAML. All gene mutations were categorized into those that are predominantly ancestral and those that are facultatively secondary. The most frequent founder mutations were identified (TET2, DNMT3A, SF3B1, ASXL1, TP53, U2AF1, RUNX1, SRSF2) and used to sub-classify approximately 80% of patients, with the remainder containing more infrequent ancestral mutations. While in a combined fashion (as both founder and secondary events) many of these mutations were not predictive of prognosis, they gained relevance when only cases affected by ancestral mutations were used for prognostication. Thus some of the mutations, when present as secondary events may not be predictive. Founding mutations may determine subsequent clinical and molecular features. While other frequently affected genes, SF3B1 or ASXL1, are not associated with a significant increase in the number of concomitant mutations, cases with TET2 mutations showed significantly more frequent mutations per case than those with wild-type TET2 (14.6 vs. 9.1; p=0.001). Moreover, ancestral TET2 mutations were associated with concomitant mutations due to high C-to-T transitions, possibly because reduced 5-hydroxymethylcytosine might create the specific mutator milieu. Most important is the association not of any type, but of ancestral mutations with certain pathomorphologic features and outcomes. Founding TET2 mutations are associated with MPN/MDS while secondary TET2 mutations are present in MDS. Ancestral DNMT3A mutations determine a rapid progression to AML, whereas subclonal DNMT3A mutations are also found in high-risk MDS. RAS pathway mutations are ancestral in CMML and also secondarily positive in the late stage of MDS (sAML). Specific ancestral events may determine subsequent mutational events, and while both types of mutation may affect the clinical phenotype, the initial events are less diverse and more subtype-specific. In conclusion, WES clarified the distinct landscape and ordering of the somatic mutational spectrum in MDS. Disclosures No relevant conflicts of interest to declare.

Type of Medium: Online Resource

ISSN: 0006-4971 , 1528-0020

URL: Article

DOI: 10.1182/blood.V124.21.823.823

Language: English

Publisher: American Society of Hematology

Publication Date: 2014

detail.hit.zdb_id: 1468538-3

detail.hit.zdb_id: 80069-7

In: Blood, American Society of Hematology, Vol. 126, No. 23 ( 2015-12-03), p. 709-709

Abstract: MDS and related disorders, including MDS/MPN and sAML that evolved from these conditions constitute disease continuum characterized by a wide spectrum of molecular lesions which often overlap. Here, we defined general mutational spectrum and clonal architecture in a large cohort (n=718) of MDS studied by whole exome sequencing (WES) and target deep sequencing. Within this cohort 97 cases were studied at multiple time points to clarify the clinical impact of clonal dynamics on phenotype commitment or outcomes. All samples were obtained after informed consent, according to protocols approved by the respective ethics boards of the participating institutions. When mean and maximum variant allele frequency (VAF) for whole mutations were at one time-point evaluated in disease phenotypes, significantly higher averaged values suggested their larger clones in sAML and CMML compared to MDS. Clustering analysis of multiple mutational events by Pyclone software discriminated the cases with multiple mutational clones (positive heterogeneity) and those with a single expansion of MDS clone (no heterogeneity detected). Over 80% of low-risk MDS and all the sAML harbored multiple clusters of mutations. These results suggest that intra-tumor heterogeneity of MDS is most likely due to various sizes of clonal and subclonal mutations, likely impacting clinical behavior. To delineate clonal dynamics in MDS, we assessed mutational burden and their temporal changes in serially collected samples (n=97). Among these, Pyclone analysis was applied to exome sequencing at two time points (n=11 pairs). All cases showed various mutational clusters with individual expansions and declines, including initially present, newly acquired or disappearing during clinical course. Initial subclones were identified at disease presentation in 55% of cases, of which in 86% the subclones expanded to occupy whole MDS population with clonal sweep. New subclones acquired during clinical course were identified in 91%, in which 60% cases harbored clonal sweep. Disappearing clones were observed in 55% of cases. Next, we applied clustering analysis on clonal size of driver mutations evaluated at multiple time points (n=97 cases) to categorize the most frequently mutated genes into 3 subtypes. Mutational burden of PTPN11 most frequently increased and were associated with leukemic evolution (an example of type I gene). Similarly, CBL, NRAS, STAG2, RUNX1, and IDH1 were categorized into the type I genes, demonstrating increased clonal size resulting in the evolutions into high-risk phenotypes. Although JAK2 mutations were related to the stable clinical course when the mutational burden decreased, cases with highly expanded JAK2 mutations resulted in leukemic evolution (occasional evolution or expansions; type II gene). DNMT3A, SRSF2, TP53, U2AF1, and ASXL1 mutations were also categorized into such type II consequences with occasional progression. The last category (type III) included clonal/founder genes EZH2, TET2, SF3B1 and PRPF8, demonstrating random shifts of clonal size and lack of association with leukemic evolution. The proposed hierarchical categorization correlates with clinical parameters. Cases with the increasing burden of type I gene mutations showed most significant increases in myeloblasts. Overall survival measured from second sampling time points in the cases with increasing type I mutations was significantly shorter in the whole cohort (HR=2.05, 95%CI; 1.14-3.79, P=0.016) and in the cases solely with IPSS INT-1 (HR=2.37, 95%CI; 1.01-5.97, P=0.048). Subcohorts classified according to the presence or absence of increasing type I mutations did not differ with regard to the IPSS categories. In contrast, increased mutational burden of type II and III genes did not correlated with any of the clinical parameters examined, even though some gene mutations including TP53, EZH2, and U2AF1 represented poor prognostic factors at disease presentation. In conclusion, this work demonstrates that detailed understanding of clonal dynamics allows for new insights into clinical significance of somatic mutations, made possible only by serial sample sequencing at multiple time points. Increasing clonal burden of extracted genes associated with predictive prognostic impact should be prospectively validated in more uniform and larger cohort of MDS. Disclosures Sekeres: TetraLogic: Membership on an entity's Board of Directors or advisory committees; Celgene Corporation: Membership on an entity's Board of Directors or advisory committees; Amgen: Membership on an entity's Board of Directors or advisory committees. Shih:Novartis: Research Funding.

Type of Medium: Online Resource

ISSN: 0006-4971 , 1528-0020

URL: Article

DOI: 10.1182/blood.V126.23.709.709

Language: English

Publisher: American Society of Hematology

Publication Date: 2015

detail.hit.zdb_id: 1468538-3

detail.hit.zdb_id: 80069-7

In: Blood, American Society of Hematology, Vol. 122, No. 21 ( 2013-11-15), p. 815-815

Abstract: Angioimmunoblastic T-cell lymphoma (AITL) is a distinct subtype of peripheral T-cell lymphoma (PTCL) characterized by generalized lymphadenopathy, hyperglobulinemia, and autoimmune-like manifestations. Frequent mutations in TET2, IDH2, and DNMT3A have been described in AITL, which are commonly found in myeloid malignancies. However, the molecular pathogenesis specific to AITL is still unknown. Methods To clarify the molecular pathogenesis of AITL, we performed comprehensive gene-mutation analysis. Somatic mutations in 3 AITL and 3 PTCL-NOS specimens were explored using whole-exome sequencing (WES). Targeted resequencing for genes identified by WES was also performed in a cohort of 157 patients with AITL/PTCL-NOS. Results We identified a novel recurrent mutation in RHOA (c.G50T/p.G17V) in 3 AITL and one PTCL-NOS samples by WES. Validation in an extended cohort revealed an extremely high frequency of the identical G17V RHOA mutation in AITL (50/72 [69.4%]), together with mutations in TET2 (39/47 [83.0%] ), IDH2 (14/47 [29.8%]), and DNMT3A(12/47 [25.5%] ). The G17V RHOA mutation was also found in PTCL-NOS samples at a lower frequency (14/85 [16.5%]), especially in those harboring AITL features (PTCL-NOS with AITL features vs PTCL-NOS w/o AITL features: 13/21 [61.9%] vs 0/38 [0%]). Remarkably, mutations in RHOA, TET2, and IDH2 showed striking correlations. All RHOA-mutated samples were accompanied by TET2 mutations. IDH2 mutations were confined to the samples having simultaneous mutations of RHOA and TET2. Mutations in DNMT3A largely overlapped to TET2 mutations, but its correlation with RHOA or IDH2 mutations was much less clear. TET2 mutations showed a consistently higher allelic burden than RHOA mutations. Gene-mutation analysis of tumor cells and infiltrated cells demonstrated that the G17V RHOA mutation specifically existed in tumor cells, but not in non-tumor cells, while TET2 mutations were identified both in tumor and non-tumor cells. RHOA encodes a small GTPase, which operates as a molecular switch that regulates a wide variety of biological processes through cycling between an active (GTP-bound) and an inactive (GDP-bound) state. We demonstrated that the G17V RHOA mutant did not bind GTP and also inhibited GTP-binding of the wild-type RHOA protein. Accordingly, unlike wild-type RHOA, the G17V mutant was not able to activate transcription from the serum response factor-responsive element (SRF-RE). Conclusions Our data suggests that combination of preceding mutations in TET2 and subsequent tumor-specific G17V RHOA mutation determines distinct disease properties of AITL. Disclosures: No relevant conflicts of interest to declare.

Type of Medium: Online Resource

ISSN: 0006-4971 , 1528-0020

URL: Article

DOI: 10.1182/blood.V122.21.815.815

Language: English

Publisher: American Society of Hematology

Publication Date: 2013

detail.hit.zdb_id: 1468538-3

detail.hit.zdb_id: 80069-7

In: Blood, American Society of Hematology, Vol. 126, No. 23 ( 2015-12-03), p. 2841-2841

Abstract: Myelodysplastic syndromes (MDS) and related disorders are a heterogeneous group of chronic myeloid neoplasms with a high propensity to acute myeloid leukemia. A cardinal feature of MDS, as revealed by the recent genetic studies, is a high frequency of mutations and copy number variations (CNVs) affecting epigenetic regulators, such as TET2, IDH1/2, DNMT3A, ASXL1, EZH2, and other genes, underscoring a major role of deregulated epigenetic regulation in MDS pathogenesis. Meanwhile, these mutations/deletions have different impacts on the phenotype and the clinical outcome of MDS, suggesting that it should be important to understand the underlying mechanism for abnormal epigenetic regulation for better classification and management of MDS. SETD2 and ASH1L are structurally related proteins that belong to the histone methyltransferase family of proteins commonly engaged in methylation of histone H3K36. Both genes have been reported to undergo frequent somatic mutations and copy number alterations, and also show abnormal gene expression in a variety of non-hematological cancers. Moreover, germline mutation of SETD2 has been implicated in overgrowth syndromes susceptible to various cancers. However, the role of alterations in these genes has not been examined in hematological malignancies including myelodysplasia. In this study, we interrogated somatic mutations and copy number variations, among a total of 1116 cases with MDS and myelodysplastic/myeloproliferative neoplasms (MDS/MPN), who had been analyzed by target deep sequencing (n=944), and single nucleotide polymorphism-array karyotyping (SNP-A) (n=222). Gene expression was analyzed in MDS cases and healthy controls, using publically available gene expression datasets. SETD2 mutations were found in 6 cases, including 2 with nonsense and 4 with missense mutations, and an additional 10 cases had gene deletions spanning 1.8-176 Mb regions commonly affecting the SETD2 locus in chromosome 3p21.31, where SETD2 represented the most frequently deleted gene within the commonly deleted region. SETD2 deletion significantly correlated with reduced SETD2 expression. Moreover, MDS cases showed a significantly higher SETD2 expression than healthy controls. In total, 16 cases had either mutations or deletions of the SETD2 gene, of which 70% (7 out of 10 cases with detailed diagnostic information) were RAEB-1/2 cases. SETD2 -mutated/deleted cases had frequent mutations in TP53 (n=4), SRSF2 (n=3), and ASXL1 (n=3) and showed a significantly poor prognosis compared to those without mutations/deletions (HR=3.82, 95%CI; 1.42-10.32, P=0.004). ASH1L, on the other hand, was mutated and amplified in 7 and 13 cases, respectively, of which a single case carried both mutation and amplification with the mutated allele being selectively amplified. All the mutations were missense variants, of which 3 were clustered between S1201 and S1209. MDS cases showed significantly higher expression of ASH1L compared to healthy controls, suggesting the role of ASH1L overexpression in MDS development. Frequent mutations in TET2 (n=8) and SF3B1 (n=6) were noted among the 19 cases with ASH1L lesions. RAEB-1/2 cases were less frequent (n=11) compared to SETD2-mutated/deleted cases. ASH1L mutations did not significantly affect overall survival compared to ASH1L-intact cases. Gene Set Expression Analysis (Broad Institute) on suppressed SETD2 and accelerated ASH1L demonstrated 2 distinct expression signatures most likely due to the differentially methylated H3K36. We described recurrent mutations and CNVs affecting two histone methyltransferase genes, which are thought to represent novel driver genes in MDS involved in epigenetic regulations. Given that SETD2 overexpression and reduced ASH1L expression are found in as many as 89% of MDS cases, deregulation of both genes might play a more role than expected from the incidence of mutations and CNVs alone. Although commonly involved in histone H3K36 methylation, both methyltransferases have distinct impacts on the pathogenesis and clinical outcome of MDS in terms of the mode of genetic alterations and their functional consequences: SETD2 was frequently affected by truncating mutations and gene deletions, whereas ASH1L underwent gene amplification without no truncating mutations, suggesting different gene targets for both methyltransferases, which should be further clarified through functional studies. Disclosures Alpermann: MLL Munich Leukemia Laboratory: Employment. Nadarajah:MLL Munich Leukemia Laboratory: Employment. Haferlach:MLL Munich Leukemia Laboratory: Employment, Equity Ownership. Kern:MLL Munich Leukemia Laboratory: Employment, Equity Ownership. Shih:Novartis: Research Funding.

Type of Medium: Online Resource

ISSN: 0006-4971 , 1528-0020

URL: Article

DOI: 10.1182/blood.V126.23.2841.2841

Language: English

Publisher: American Society of Hematology

Publication Date: 2015

detail.hit.zdb_id: 1468538-3

detail.hit.zdb_id: 80069-7

In: Blood, American Society of Hematology, Vol. 120, No. 21 ( 2012-11-16), p. 782-782

Abstract: Abstract 782 Recent genetic studies have revealed a number of novel gene mutations in myeloid malignancies, unmasking an unexpected role of deregulated histone modification and DNA methylation in both acute and chronic myeloid neoplasms. However, our knowledge about the spectrum of gene mutations in myeloid neoplasms is still incomplete. In the previous study, we analyzed 29 paired tumor-normal samples with chronic myeloid neoplasms with myelodysplastic features using whole exome sequencing (Yoshida et al., Nature 2011). Although the major discovery was frequent spliceosome mutations tightly associated with myelodysplasia phenotypes, hundreds of unreported gene mutations were also identified, among which we identified recurrent mutations involving STAG2, a core cohesin component, and also two other cohesin components, including STAG1 and PDS5B. Cohesin is a multimeric protein complex conserved across species and is composed of four core subunits, i.e., SMC1, SMC3, RAD21 and STAG proteins, together with several regulatory proteins. Forming a ring-like structure, cohesin is engaged in cohesion of sister chromatids in mitosis, post-replicative DNA repair and regulation of gene expression. To investigate a possible role of cohesin mutations in myeloid leukemogenesis, an additional 534 primary specimens of various myeloid neoplasms was examined for mutations in a total of 9 components of the cohesin and related complexes, using high-throughput sequencing. Copy number alterations in cohesin loci were also interrogated by SNP arrays. In total, 58 mutations and 19 deletions were confirmed by Sanger sequencing in 73 out of 563 primary myeloid neoplasms (13%). Mutations/deletions were found in a variety of myeloid neoplasms, including AML (22/131), CMML (15/86), MDS (26/205) and CML (8/65), with much lower mutation frequencies in MPN (2/76), largely in a mutually exclusive manner. In MDS, mutations were more frequent in RCMD and RAEB (19.5%) but rare in RA, RARS, RCMD-RS and 5q- syndrome (3.4%). Cohesin mutations were significantly associated with poor prognosis in CMML, but not in MDS cases. Cohesin mutations frequently coexisted with other common mutations in myeloid neoplasms, significantly associated with spliceosome mutations. Deep sequencing of these mutant alleles was performed in 19 cases with cohesin mutations. Majority of the cohesin mutations (16/19) existed in the major tumor populations, indicating their early origin during leukemogenesis. Next, we investigated a possible impact of mutations on cohesin functions, where 17 myeloid leukemia cell lines with or without cohesin mutations were examined for expression of each cohesin component and their chromatin-bound fractions. Interestingly, the chromatin-bound fraction of one or more components of cohesin was substantially reduced in cell lines having mutated or defective cohesin components, suggesting substantial loss of cohesin-bound sites on chromatin. Finally, we examined the effect of forced expression of wild-type cohesin on cell proliferation of cohesin-defective cells. Introduction of the wild-type RAD21 and STAG2 suppressed the cell growth of RAD21- (Kasumi-1 and MOLM13) and STAG2-defective (MOLM13) cell lines, respectively, supporting a leukemogenic role of compromised cohesin functions. Less frequent mutations of cohesin components have been described in other cancers, where impaired cohesion and consequent aneuploidy were implicated in oncogenic action. However, 23 cohesin-mutated cases of our cohort had completely normal karyotypes, suggesting that cohesin-mutated cells were not clonally selected because of aneuploidy. Alternatively, a growing body of evidence suggests that cohesin regulate gene expression, arguing for the possibility that cohesin mutations might participate in leukemogenesis through deregulated gene expression. Of additional note, the number of non-silent mutations determined by our whole exome analysis was significantly higher in 6 cohesin-mutated cases compared to non-mutated cases. Since cohesin also participates in post-replicative DNA repair, this may suggest that compromised cohesin function could induce DNA hypermutability and contribute to leukemogenesis. In conclusion, we report a new class of common genetic targets in myeloid malignancies, the cohesin complex. Our findings highlight a possible role of compromised cohesin functions in myeloid leukemogenesis. Disclosures: Haferlach: MLL Munich Leukemia Laboratory: Equity Ownership. Alpermann:MLL Munich Leukemia Laboratory: Employment. Haferlach:MLL Munich Leukemia Laboratory: Equity Ownership.

Type of Medium: Online Resource

ISSN: 0006-4971 , 1528-0020

URL: Article

DOI: 10.1182/blood.V120.21.782.782

Language: English

Publisher: American Society of Hematology

Publication Date: 2012

detail.hit.zdb_id: 1468538-3

detail.hit.zdb_id: 80069-7

In: Cancer Research, American Association for Cancer Research (AACR), Vol. 76, No. 14_Supplement ( 2016-07-15), p. 164-164

Abstract: Background Esophageal squamous cell carcinoma (ESCC) represents the most common form of esophageal cancer worldwide, especially in East Asia, where alcohol drinking and smoking have been implicated in the field carcinogenesis of ESCC. However, the oncogenic process therein has been poorly understood in terms of gene mutations. Patients & Methods A total of 100 samples, including cancer, dysplastic, and non-dysplastic esophageal tissues, were obtained from 24 individual with (N = 14) or without (N = 10) ESCC (a median of 2.5 samples per case: 1−29) either by endoscopy or surgery and were subjected to whole exome sequencing (WES). An additional paired cancer/non-caner samples from 32 patients was analyzed by targeted sequencing (TS). All samples were analyzed for copy number alterations (CNAs) using SNP array- and/or digital sequencing-based karyotyping. Results In WES, clonal evolution in esophageal epithelia, as determined by the presence of somatic mutations, was detected in 21 of 21 cancer, 12 of 12 dysplastic, and 63 of 67 non-dysplastic samples, where the mean number of mutation per sample showed a significant trend to increase in cancer (65) and dysplastic samples (50) compared to non-dysplastic samples (13) (P = 2.1×10-11). CNAs, especially those involving CDKN2A, CCND1, YAP1, and EGFR, were frequently affected in cancer samples, but rarely so in non-dysplastic samples. Non-dysplastic samples tended to have smaller allelic burden and therefore, clone size, compared to dysplastic and cancer samples (P = 2.2×10-16). Mutations had a predominant age-related signature in non-dysplastic samples but increasing APOBEC3A/3B patterns was observed in cancer and dysplastic samples. Shared mutations were found only within cancer tissues but never among dysplastic or non-dysplastic samples, suggesting the latter lesions are clonally independent from each other. In accordance with previous reports, TP53 mutations were found in 21/21 cancer samples and also found in dysplastic (11/12) and non-dysplastic samples at a lower frequency (26/67). Strikingly, non-dysplastic samples harbored a very high frequency of NOTCH1 mutations (51/67), which were also found in cancer (3/21) and non-dysplastic (8/12) samples but at much lower frequencies (P = 6.6×10-7). TS of validation samples confirmed the trend of higher NOTCH1 (84% vs. 25%) and lower TP53 mutation rates (38% vs. 100%) in non-dysplastic samples compared to cancer samples. The number of mutations in non-dysplastic samples was higher in drinkers than non-drinkers. Multiple NOTCH1 mutations were more common in cancer patients and drinkers than non-drinkers. Conclusion Clonal proliferation in non-cancer esophageal epithelia is common even in non-ESCC cases and extensive in ESCC cases. NOTCH1 and TP53 mutations play major roles in clonal evolution in common but may have differential impacts on esophageal carcinogenesis, which is likely to be shaped by APOBEC-induced mutations and CNAs. Citation Format: Akira Yokoyama, Hiromichi Suzuki, Tetsuichi Yoshizato, Kosuke Aoki, Yusuke Shiozawa, Youichi Fujii, Yusuke Sato, Nobuyuki Kakiuchi, Sugi Kin, Keisuke Kataoka, Kenichi Yoshida, Hideki Makishima, Yusuke Amanuma, Shinya Oohashi, Yuichi Shiraishi, Kenichi Chiba, Hiroko Tanaka, Brown J.B., Masashi Sanada, Shigeru Tsunoda, Sachiko Minamiguchi, Yoshiharu Sakai, Hironori Haga, Tsutome Chiba, Satoru Miyano, Manabu Muto, Seishi Ogawa. Clonal evolution in noncancerous esophageal mucosa in normal and cancer-bearing individuals. [abstract]. In: Proceedings of the 107th Annual Meeting of the American Association for Cancer Research; 2016 Apr 16-20; New Orleans, LA. Philadelphia (PA): AACR; Cancer Res 2016;76(14 Suppl):Abstract nr 164.

Type of Medium: Online Resource

ISSN: 0008-5472 , 1538-7445

URL: Article

DOI: 10.1158/1538-7445.AM2016-164

Language: English

Publisher: American Association for Cancer Research (AACR)

Publication Date: 2016

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detail.hit.zdb_id: 1432-1

detail.hit.zdb_id: 410466-3