Profiling the Genomic Landscape at the Early Stages of CLL: Low Genomic Complexity and Paucity of Driver Mutations in MBL and Indolent CLL

Blood ◽  
2016 ◽  
Vol 128 (22) ◽  
pp. 3214-3214 ◽  
Author(s):  
Andreas Agathangelidis ◽  
Viktor Ljungström ◽  
Lydia Scarfò ◽  
Claudia Fazi ◽  
Maria Gounari ◽  
...  
Keyword(s):  
Deep Sequencing ◽  
Research Funding ◽  
Somatic Mutations ◽  
Driver Mutations ◽  
Whole Genome ◽  
Sequencing Analysis ◽  
Driver Genes ◽  
Hematopoietic Stem ◽  
Genomic Complexity ◽  
Targeted Deep Sequencing

Abstract Chronic lymphocytic leukemia (CLL) is preceded by monoclonal B cell lymphocytosis (MBL), characterized by the presence of monoclonal CLL-like B cells in the peripheral blood, yet at lower numbers than those required for the diagnosis of CLL. MBL is distinguished into low-count (LC-MBL) and high-count (HC-MBL), based on the number of circulating CLL-like cells. While the former does not virtually progress into a clinically relevant disease, the latter may evolve into CLL at a rate of 1% per year. In CLL, genomic studies have led to the discovery of recurrent gene mutations that drive disease progression. These driver mutations may be detected in HC-MBL and even in multipotent hematopoietic progenitor cells from CLL patients, suggesting that they may be essential for CLL onset. Using whole-genome sequencing (WGS) we profiled LC-MBL and HC-MBL cases but also CLL patients with stable lymphocytosis (range: 39.8-81.8*109 CLL cells/l) for >10 years (hereafter termed indolent CLL). This would refine our understanding of the type of genetic aberrations that may be involved in the initial transformation rather than linked to clinical progression as is the case for most, if not all, CLL driver mutations. To this end, we whole-genome sequenced CD19+CD5+CD20dim cells from 6 LC-MBL, 5 HC-MBL and 5 indolent CLL cases; buccal control DNA and polymorphonuclear (PMN) cells were analysed in all cases. We also performed targeted deep-sequencing on 11 known driver genes (ATM, BIRC3, MYD88, NOTCH1, SF3B1, TP53, EGR2, POT1, NFKBIE, XPO1, FBXW7) in 8 LC-MBL, 13 HC-MBL and 7 indolent CLL cases and paired PMN samples. Overall similar mutation signatures/frequencies were observed for LC/HC-MBL and CLL concerning i) the entire genome; with an average of 2040 somatic mutations observed for LC-MBL, 2558 for HC-MBL and 2400 for CLL (186 for PMN samples), as well as ii) in the exome; with an average of non-synonymous mutations of 8.9 for LC-MBL, 14.6 for HC-MBL, 11.6 for indolent CLL (0.9 for PMN samples). Regarding putative CLL driver genes, WGS analysis revealed only 2 somatic mutations within NOTCH1, and FBXW7 in one HC-MBL case each. After stringent filtering, 106 non-coding variants (NCVs) of potential relevance to CLL were identified in all MBL/CLL samples and 4 NCVs in 2/24 PMN samples. Seventy-two of 110 NCVs (65.5%) caused a potential breaking event in transcription factor binding motifs (TFBM). Of these, 29 concerned cancer-associated genes, including BTG2, BCL6 and BIRC3 (4, 2 and 2 samples, respectively), while 16 concerned genes implicated in pathways critical for CLL e.g. the NF-κB and spliceosome pathways. Shared mutations between MBL/CLL and their paired PMN samples were identified in all cases: 2 mutations were located within exons, whereas an average of 15.8 mutations/case for LC-MBL, 8.2 for HC-MBL and 9 for CLL, respectively, concerned the non-coding part. Finally, 16 sCNAs were identified in 9 MBL/CLL samples; of the Döhner model aberrations, only del(13q) was detected in 7/9 cases bearing sCNAs (2 LC-MBL, 3 HC-MBL, 2 indolent CLL). Targeted deep-sequencing analysis (coverage 3000x) confirmed the 2 variants detected by WGS, i.e. in NOTCH1 (n=1) and FBXW7 (n=1), while 4 subclonal likely damaging variants were detected with a VAF <10% in POT1 (n=2), TP53 (n=1), and SF3B1 (n=1) in 4 HC-MBL samples. In conclusion, LC-MBL and CLL with stable lymphocytosis for >10 years display similar low genomic complexity and absence of exonic driver mutations, assessed both with WGS and deep-sequencing, underscoring their common low propensity to progress. On the other hand, HC-MBL comprising cases that may ultimately evolve into clinically relevant CLL can acquire exonic driver mutations associated with more dismal prognosis, as exemplified by subclonal driver mutations detected by deep-sequenicng. The existence of NCVs in TFBMs targeting pathways critical for CLL prompts further investigation into their actual relevance to the clinical behavior. Shared mutations between CLL and PMN cells indicate that some somatic mutations may occur before CLL onset, likely at the hematopoietic stem-cell level. Their potential oncogenic role likely depends on the cellular context and/or microenvironmental stimuli to which the affected cells are exposed. Disclosures Stamatopoulos: Novartis: Honoraria, Research Funding; Janssen: Honoraria, Other: Travel expenses, Research Funding; Gilead: Consultancy, Honoraria, Research Funding; Abbvie: Honoraria, Other: Travel expenses. Ghia:Adaptive: Consultancy; Gilead: Consultancy, Honoraria, Research Funding, Speakers Bureau; Abbvie: Consultancy, Honoraria; Janssen: Consultancy, Honoraria, Speakers Bureau; Roche: Honoraria, Research Funding.

Whole-Exome Sequencing and Targeted Deep Sequencing of cfDNA Enables a Comprehensive Mutational Profiling of Multiple Myeloma

Blood ◽  
2016 ◽  
Vol 128 (22) ◽  
pp. 197-197 ◽  
Author(s):  
Salomon Manier ◽  
Jihye Park ◽  
Samuel Freeman ◽  
Gavin Ha ◽  
Marzia Capelletti ◽  
...  
Keyword(s):  
Deep Sequencing ◽  
Research Funding ◽  
Clonal Evolution ◽  
Target Coverage ◽  
Whole Genome ◽  
Driver Genes ◽  
Whole Exome ◽  
Low Pass ◽  
Targeted Deep Sequencing ◽  
Tumor Dna

Abstract Background . Cell-free DNA (cfDNA) sequencing enables serial temporal sampling, which offers the possibility of following the dynamics of biomarkers and clonal evolution in Multiple Myeloma (MM) over time. The use of cfDNA in clinical practice as a molecular biomarker and for monitoring response/resistance is dependent on a comprehensive profile of matched cfDNA and tumor DNA (tDNA) samples. Here we performed Ultra-Low Pass Whole Genome Sequencing (ULP-WGS) followed by whole-exome sequencing (WES) and targeted deep sequencing of matched cfDNA/tDNA samples from MM patients. Methods. We performed next generation sequencing of matched cfDNA/tDNA samples for 63 patients with newly diagnosed or relapsed MM, SMM, or MGUS. Libraries were constructed using the Kappa Hyper kit and sequenced by ultra-low-pass whole-genome sequencing (ULP-WGS, 0.1x coverage) to quantify tumor fraction within cfDNA. WES was performed on 30 matched samples cfDNA/tDNA/germline DNA from 10 patients with more than 5% of tumor fraction. Libraries were hybridized to the Nextera Rapid Capture Exome kit (Illumina) and then sequenced on HiSeq 4000 (Illumina). Targeted deep sequencing was performed on 32 matched cfDNA/tDNA samples from 16 patients using the HaloPlex HS technology (Agilent), allowing for molecular barcoding. Libraries were constructed according to the manufacturer's instructions and sequenced on HiSeq 2500 (Illumina). Sequencing data were analyzed using the Firehose pipelines, including MuTect, ABSOLUTE, ReCapSeg, GISTIC and MutSig. Results. We first used a cost-effective approach to establish the tumor content of cfDNA in a large-scale manner by ULP-WGS. Among 63 tested samples (53 MM, 6 SMM and 4 MGUS patient samples), the tumor fraction within cfDNA ranged from 0 to 81% with a mean of 10%. About 43% of these samples had tumor fraction greater than 5% within cfDNA. To assess whether cfDNA can capture the genetic diversity of MM and inform clinical management, we performed WES of matched cfDNA/tDNA/germline DNA samples for 10 patients (mean target coverage 194x). Copy number alterations (CNAs) assessed by WES (ReCapSeg) were consistent between cfDNA and tumor DNA. Similarly, focal CNAs assessed by GISTIC were consistent between tDNA and cfDNA. We then examined the overlap of somatic single nucleotide variants (SSNVs) between WES of cfDNA and matched tDNA. We found, on average, 100% of the clonal and 96% of the subclonal (range 54-100%) SSNVs that were detected in the tumor were confirmed to be present in cfDNA. Similarly, for mutations detected in the cfDNA, we found, on average, 100% of the clonal and 99% of the subclonal (range 98-100%) SSNVs were confirmed in the tumor. To assess whether targeted deep sequencing of cfDNA could be a good proxy for tumor biopsy we used a targeted deep sequencing approach of known MM driver genes. Libraries were prepared using unique molecular barcodes to avoid duplication rates, for 32 matched cfDNA/tDNA samples from 16 patients with MM. The mean target coverage was 596x. We found similar frequencies of altered MM driver genes in both cfDNA and tDNA, including KRAS, NRAS, and TP53, indicating that cfDNA can be used for precision medicine. Conclusions. Our study demonstrates that both WES and targeted deep sequencing of cfDNA are consistently representative of tumor DNA alterations in terms of CNAs, focal CNAs and SSNVs. This approach could therefore be used to longitudinally follow clonal evolution across the course of the disease and precision medicine in patients with MM. Disclosures Palumbo: Takeda: Employment, Honoraria; Janssen Cilag: Honoraria. Kumar:Noxxon Pharma: Consultancy, Research Funding; Celgene: Consultancy, Research Funding; Millennium: Consultancy, Research Funding; Skyline: Honoraria, Membership on an entity's Board of Directors or advisory committees; Janssen: Consultancy, Research Funding; Kesios: Consultancy; Glycomimetics: Consultancy; BMS: Consultancy; Array BioPharma: Consultancy, Research Funding; Sanofi: Consultancy, Research Funding; AbbVie: Research Funding; Onyx: Consultancy, Research Funding. Roccaro:Takeda Pharmaceutical Company Limited: Honoraria. Facon:Amgen: Consultancy, Speakers Bureau; Novartis: Consultancy; Janssen: Consultancy, Speakers Bureau; Bristol: Consultancy; Millenium/Takeda: Consultancy; Celgene: Consultancy, Speakers Bureau; Karyopharm: Consultancy. Ghobrial:Celgene: Honoraria, Research Funding; BMS: Honoraria, Research Funding; Noxxon: Honoraria; Novartis: Honoraria; Takeda: Honoraria; Amgen: Honoraria.

scholarly journals Concomitant Occurrence of Polyclonal Hematopoiesis and Cell-Autonomous Megakaryopoiesis in Triple-Negative Essential Thrombocythemia

Blood ◽  
2020 ◽  
Vol 136 (Supplement 1) ◽  
pp. 27-28
Author(s):  
Tadaaki Inano ◽  
Marito Araki ◽  
Soji Morishita ◽  
Misa Imai ◽  
Yoshihiko Kihara ◽  
...  
Keyword(s):  
Stem Cells ◽  
Bone Marrow ◽  
Genomic Dna ◽  
Research Funding ◽  
Somatic Mutations ◽  
Triple Negative ◽  
Jak2 V617f ◽  
Sequencing Analysis ◽  
Hematopoietic Stem ◽  
Otsuka Pharmaceutical

Somatic mutations in JAK2, MPL, and CALR are found in approximately 80% of patients with essential thrombocythemia (ET), whereas the remaining patients are negative for disease-defining mutations and are defined as triple-negative (TN). Studies have shown that some patients with TN-ET harbor non-canonical mutations in JAK2 and MPL; however, the failure to identify recurrent mutations in most patients has made the pathogenesis of TN-ET ambiguous (Milosevic Feenstra et al. Blood 2016, Cabagnols et al. Blood 2016). In this study, we screened 483 patients suspected as having ET in a single center, performed mutation analysis for JAK2 V617F, CALR exon 9, and MPL exon 10, and centrally reviewed bone marrow specimens. We identified 23 patients with TN-ET based on the WHO 2016 criteria. Sequencing analysis of these patients revealed non-canonical mutations in JAK2 and MPL in 4 cases. Whole exome-sequencing analysis of genomic DNA from peripheral blood and CD3-positive cells from 9 patients revealed that 2 patients harbored somatic mutations in other genes; 7 patients showed no detectable somatic mutation. A STAT5 reporter assay revealed that unlike JAK2 V617F and MPL W515L, all non-canonical mutants of JAK2 or MPL activated STAT5 similar to wild-type proteins, suggesting that these mutations did not drive the disease. Statistical analysis of clinical records revealed that patients with TN-ET were mostly young (median age of 36.0 years), female (18/23, 78.3%), and had neither a history of thrombosis nor progression to secondary myelofibrosis and leukemia, demonstrating the unique characteristics of TN-ET. The presence of clonal hematopoiesis, analyzed using genomic DNA purified from granulocytes of peripheral blood from female patients in a human androgen receptor assay, revealed that only 1 out of 15 patients was clonal. Hypothesizing that TN-ET was reactive thrombocytosis, the concentrations of cytokines promoting platelet production such as thrombopoietin (TPO) and interleukin-6 (IL-6) in the serum were analyzed. However, no significant differences in concentrations were observed among ET with driver mutations, TN-ET, and healthy individuals. We next examined the capacity of hematopoietic stem cells from patients with TN-ET to form megakaryocytic colonies. CD34-positive cells purified from cryopreserved bone marrow cells were cultured in the absence or presence of TPO. CD34-positive cells derived from patients with TN-ET exhibited an equivalent capacity to form megakaryocytic colonies compared to those from patients with ET harboring a driver mutation, even in the absence of TPO (Figure 1). Thus, in TN-ET, megakaryopoiesis may have been induced in a cell-autonomous manner. In 10 patients with TN-ET with available blood count data, no sign of thrombocytosis was observed before ET development, indicating that thrombocytosis was not hereditary but rather occurred via an alternate mechanism, such as aberrations in epigenomic regulation that induced cellular transformation (Ohnishi et al, Cell 2015). Taken together, TN-ET is a distinctive disease entity associated with polyclonal hematopoiesis and paradoxically caused by hematopoietic stem cells harboring a capacity for cell-autonomous megakaryopoiesis. Figure 1 Disclosures Komatsu: Takeda Pharmaceutical Co., Ltd, Novartis Pharma KK, Shire Japan KK: Speakers Bureau; PPMX: Consultancy, Research Funding; Meiji Seika Pharma Co., Ltd.: Patents & Royalties: PCT/JP2020/008434, Research Funding; AbbVie: Other: member of safety assessment committee in M13-834 clinical trial.; Otsuka Pharmaceutical Co., Ltd., Shire Japan KK, Novartis Pharma KK, PharmaEssentia Japan KK, Fuso Pharmaceutical Industries, Ltd., Fujifilm Wako Pure Chemical Corporation, Chugai Pharmaceutical Co., Ltd., Kyowa Hakko Kirin Co., Ltd., Takeda Pharmaceutica: Research Funding; Otsuka Pharmaceutical Co., Ltd., PharmaEssentia Japan KK, AbbVie GK, Celgene KK, Novartis Pharma KK, Shire Japan KK, Japan Tobacco Inc: Consultancy.

scholarly journals Monosomy 7 As the Initial Hit Followed By Sequential Acquisition of SETBP1 and ASXL1 Driver Mutations in Childhood Myelodysplastic Syndromes

Blood ◽  
2018 ◽  
Vol 132 (Supplement 1) ◽  
pp. 105-105 ◽  
Author(s):  
Victor Pastor Loyola ◽  
Pritam Kumar Panda ◽  
Sushree Sangita Sahoo ◽  
Enikoe Amina Szvetnik ◽  
Emilia J. Kozyra ◽  
...  
Keyword(s):  
Deep Sequencing ◽  
Myelodysplastic Syndromes ◽  
Somatic Mutations ◽  
Clonal Evolution ◽  
Driver Mutations ◽  
Common Denominator ◽  
Hematopoietic Stem ◽  
Monosomy 7 ◽  
Clonal Architecture ◽  
Over Time

Abstract Childhood myelodysplastic syndromes (MDS) account for less than 5% of pediatric hematologic malignancies and differ from their adult counterpart in terms of biology, genetics, and cure rates. Complete (-7) or partial loss (del7q) of chromosome 7 constitutes the most common cytogenetic abnormality and is associated with more advanced disease typically requiring timely hematopoietic stem cell transplantation (HSCT). Previously, we and others established a link between -7 and germline GATA2 mutations in pediatric MDS (37% of MDS/-7 cases are GATA2-deficient) as well as constitutional SAMD9/9L disorders where -7 is utilized as an escape mechanism from the growth-restrictive effect of SAMD9/9L mutations. To date, comprehensive sequencing studies have been performed in 96 children with primary MDS, as reported by Pastor et al, Leukemia 2017 and Schwartz et al, Nature Comm 2017. This work established mutations in SETBP1, ASXL1, PTPN11, RUNX1 and RAS pathway genes as common somatic drivers. However, little is known about the clonal development of -7 and the role of additional somatic mutations. The knowledge about clonal hierarchies is essential for the understanding of disease progression on molecular level and for mapping potential drug targets. The rationale for the current study was to i) define the most common somatic drivers in a large cohort of patients with childhood MDS, ii) identify clonal/subclonal mutations, iii) infer clonal architecture of monosomy 7 and track the changes over time. We studied a cohort of 576 children and adolescents with primary MDS diagnosed between 1998 and 2016 in Germany, consisting of 482 (83%) patients with refractory cytopenia of childhood (RCC) and 94 (17%) MDS with excess blasts (EB). All patients underwent deep sequencing for 30 genes relevant to pediatric MDS and additional WES was performed in 150/576 patients. Using 20 computational predictors (including CADD and REVEL), population databases and germline testing, we identified the most likely pathogenic mutations. First, we excluded germline predisposing mutations in GATA2, SAMD9/SAMD9L and RUNX1 detected in 7% (38/576), 8% (43 of 548 evaluable) and 0.7% (4/576) of patients, respectively. Then we focused on the exploration of somatic aberrations. Most common karyotype abnormalities were monosomy 7 (13%, 77/576) and trisomy 8 (3%, 17/576). A total of 104 patients carried somatic mutations, expectedly more prevalent in the MDS-EB group as compared to RCC (56%, 53/94 vs 10.6%, 51/482; p<0.0001). The most recurrent somatic hits (≥ 1% frequency within 576 cases) were in SETBP1 (4.2%), ASXL1 (3.8%), RUNX1 (3.3%), NRAS (2.9%), KRAS (1.6%), PTPN11 (1.4%) and STAG2 (1%). We next focused on the -7 karyotype as a common denominator for the mutated group. Mutations were found in 54% (43/79), and the mutational load was significantly higher in -7 vs. non-7 (1.1 vs. 0.1 mutations per patient; p<0.001). In 11 patients with -7 and concomitant SETBP1/ASXL1 driver mutations, SETBP1 surpassed ASXL1 hits (median allelic frequency: 38% vs. 24%, p<0.05), while mutations in other genes were subclonal. Notably, these clonal patterns were independent of the underlying hereditary predisposition (4/11 GATA2; 3/11 SAMD9L). To explore the clonal hierarchy in MDS/-7 we performed targeted sequencing of several hundreds of single bone marrow derived colony forming cells (CFC) in 7 patients with MDS/-7. In all cases, the -7 clone was the founding clone followed by stepwise acquisition of mutations (i.e. -7>SETBP1>ASXL1; -7>SETBP1>ASXL1>PTPN11; -7>SETBP1>ASXL1>CBL, -7>EZH2>PTPN11). Finally, we tracked clonal evolution over time in 12 cases with 2-12 available serial samples using deep sequencing complemented by serial CFC-analysis. This confirmed that SETBP1 clones are rapidly expanding, while ASXL1 subclones exhibit an unstable pattern with clonal sweeping, while additional minor clones are acquired as late events. In 2 of 11 transplanted patients who experienced relapse, the original clonal architecture reappeared after HSCT. In summary, the hierarchy of clonal evolution in pediatric MDS with -7 follows a defined pattern with -7 aberrations arising as ancestral event followed by the acquisition of somatic hits. SETBP1 mutations are the dominant driver while co-dominant ASXL1 mutations are unstable. The functional interdependence and potential pharmacologic targetability of such somatic lesions warrants further studies. Disclosures Niemeyer: Celgene: Consultancy, Membership on an entity's Board of Directors or advisory committees.

Somatic PHF6 Mutations In Myeloid Malignancies

Blood ◽  
2013 ◽  
Vol 122 (21) ◽  
pp. 2514-2514
Author(s):  
Wenyi Shen ◽  
Bartlomiej P Przychodzen ◽  
Chantana Polprasert ◽  
Naoko Hosono ◽  
Brittney Dienes ◽  
...  
Keyword(s):  
Deep Sequencing ◽  
Research Funding ◽  
Somatic Mutations ◽  
Snp Array ◽  
Illustrative Case ◽  
Sequencing Analysis ◽  
Data Set ◽  
Myeloid Malignancies ◽  
Dysmorphic Features ◽  
Myeloid Neoplasms

Abstract X chromosome genomics is an important area of hematologic malignancy research because of frequent acquired X-abnormalities, location of important genes on this chromosome, and issues surrounding Lyonization (X-inactivation). For example, we previously described somatic mutations of UTX (KDM6A), a H3K27 demethylase located on chromosome Xp11.3, in aggressive myeloid neoplasms. In a companion abstract to the the results here, we also report loss of function somatic mutations of BRCC3 (Xq28), encoding a subunit of the BRCA1-BRCA2-containing complex. In an index young female case of a proliferative CMML with dysmorphic features, we have identified PHF6 mutation mosaisism (p.K44fs), confirmed by deep sequencing of bone marrow, skin and spleen tissues. Subsequently, we screened our MDS exome project data set, involving 206 patients with MDS and related neoplasms, and have detected and confirmed additional somatic PHF6mutations. Plant homeodomain finger protein 6 (PHF6) is a ubiquitously expressed 41 kDa protein that is conserved and vertebrate-specific. Human PHF6 is located on chrXq26.3. Germline mutations of PHF6 cause Borjeson−Forssman−Lehmann syndrome (BFLS), an X-linked mental retardation disorder characterized by truncal obesity, gynaecomastia, hypogonadism and other dysmorphic features. BFLS patients have been reported to develop leukemias. More recently, rare somatic PHF6mutations were detected in patients with T-ALL, but rarely also in AML. To assess the clinical associations and significance of PHF6 mutations, we analyzed NGS results in a total of 809 patients with MDS, MDS/MPN, MPN and AML. In addition we also investigated for the presence of PHF6 mutation in the TCGA AML data sets (n=199). All mutations in our patients were confirmed by Sanger sequencing and targeted deep NGS. In total, we identified 19/809 cases with PHF6 mutations; they were located throughout the gene including 15 SNVs and 4 indels. In addition TCGA pAML NGS results revealed PHF6 mutations in 6/199 cases, including 4 SNVs and 2 indels. Thus, PHF6 mutation occurs at a frequency of 2.5% in myeloid neoplasm and are most frequently observed in pAML (36%) together with sAML (32%) phenotypes. Gender distribution showed male predominance (84%), likely related to PHF6 locus on chrXq26.3. SNP-array karyotyping showed that deletions of Xq, involving PHF6locus (Xq26) were present in about 2% of myeloid neoplasms. Chromosome 7 abnormalities, including del(7q), were the most frequent lesions seen in conjunction with PHF6 mutations. Most commonly coinciding mutations were in RUNX1 (n=8), TET2 (n=4), ASXL1 (n=3) and U2AF1 (n=3) and unbiased statistical analysis confirmed the significant association between PHF6 and RUNX1 mutations (P=.002). Interestingly, all of 8 cases with concomitant RUNX1 and PHF6 mutations were diagnosed as high-risk diseases; 1 RAEB-2 and 7 AMLs. Deep sequencing analysis of 5 cases with coexisting PHF6 and RUNX1 mutations showed that PHF6 mutated clones were always significantly larger than RUNX1 mutated clones. Such a serial clonal acquisition pattern of ancestral PHF6 and secondary RUNX1 mutations was also observed clearly in an illustrative case with evolution from aplastic anemia (AA) to sAML, in which small clone of PHF6 was detected in AA sample and expanded during MDS stage, followed by secondary driver RUNX1 mutations at the stage. These findings suggest that RUNX1 mutations were acquired as a subclone of the main population with primary driver PHF6mutations. In conclusion, our results indicate that PHF6 mutations, as a recurrent genetic abnormality, were frequently mutated in more aggressive types of myeloid malignancies. Newly identified ancestral nature of PHF6 mutations specifically favor being followed by secondary driver RUNX1 mutations during leukemic evolution. Disclosures: Polprasert: MDS foundation: Research Funding. Maciejewski:Aplastic anemia&MDS International Foundation: Research Funding; NIH: Research Funding. Makishima:Scott Hamilton CARES grant: Research Funding; AA & MDS international foundation: Research Funding.

scholarly journals Application of Trusight Myeloid Panel on Whole Genome Amplified DNA in Myelodysplastic Syndrome Patients

Blood ◽  
2016 ◽  
Vol 128 (22) ◽  
pp. 5519-5519
Author(s):  
Laura Palomo ◽  
Daniel Alvira ◽  
Francisco Fuster-Tormo ◽  
Vera Ademà ◽  
Maria Pilar Armengol ◽  
...  
Keyword(s):  
Deep Sequencing ◽  
Low Frequency ◽  
Targeted Sequencing ◽  
Target Coverage ◽  
Whole Genome ◽  
Common Variants ◽  
Sequencing Data ◽  
Hematopoietic Stem ◽  
Paired Samples ◽  
Targeted Deep Sequencing

Abstract Background: Whole genome amplification (WGA) has become an invaluable method for working with small amounts of starting DNA and for preserving limited samples of precious stock material. Next-Generation Sequencing (NGS) techniques can benefit from WGA, but due to their high sensitivity, WGA reliability needs to be certified to ensure an unbiased and accurate amplification of whole genomes. Myelodysplastic Syndromes (MDS) are a group of clonal hematopoietic stem cell disorders characterized by presenting somatic mutations in several myeloid-related genes. We have performed whole exome sequencing (WES) and targeted deep sequencing in tumoral samples from MDS patients. With the aim to determine if Multiple Displacement Amplification-based WGA can be applied to perform NGS in these type of samples and to obtain valuable results, targeted deep sequencing was performed on both fresh-DNA and WGA-DNA from the same patients. Mehtods: Whole bone marrow samples from four MDS patients were included in the study. WGA was performed in tumoral DNA samples with REPLI-g (Qiagen). WES libraries were generated in tumoral-control paired samples using the SureSelect Human Exome Kit 51Mb v4 (Agilent) and sequenced on an Illumina HiSeq2000. Targeted sequencing libraries were prepared for fresh-DNA and WGA-DNA following the manufacturer specifications for TruSight Myeloid Sequencing Panel protocol (Illumina), and then sequenced on one single run on an Illumina MiSeq. WES sequencing data was analyzed using an in-house pipeline, as previously reported. Targeted sequencing data analysis was performed with theMiSeq Reporter Software (Illumina). Filtering was performed in all cases by eliminating sequencing and mapping errors and by discarding intronic or synonym variants, variants located at highly variable regions or with low coverage, as well as know polymorphisms. Additional filtering was performed by visualization on Integrative Genome Viewer Software v.2.3.72. Results: Regarding targeted sequencing, fresh-DNA samples generated 6 million reads (SD = 1.9 million), with 98.5 % (SD = 0.8) of the mapped reads on-target and a mean target coverage of 12148.8 (SD = 3872.9). WGA-DNA samples yielded about 5.2 million reads (SD = 1.5 million), with 98.3 % (SD = 0.4) of the mapped reads on-target and a mean target coverage of 10447.5x (SD = 2946.3). A mean of 77% of total bases displayed a Q score ≥30, which did not differ between fresh and WGA-DNA. Comparison of all filtered variants within the four pairs revealed a high level of discordance between fresh/WGA samples (Figure 1A). A mean of 86% of the detected variants, considering both fresh and WGA-DNA, were detected at a low frequency (<10%). Therefore, a stricter variant filtering was performed, in which all variants detected at a frequency <10% were removed from further analyses. The pairwise comparison across the paired samples showed a total of 48.1% (SD = 49.3) of common variants, 23.2% (SD = 30.1) of variants exclusively detected in fresh-DNA, and 28.7% (SD = 38.4) of variants exclusively detected in WGA-DNA (Figure 1B). Overall, 100% (n=9) of the common variants were also detected by WES. Regarding fresh-DNA specific variants, 63% (5/8) were seen by WES and 37% (3/8) were not. However, these three variants were detected by targeted sequencing at frequencies between 10-12%. This suggests that even a stricter filtering may be necessary when working with WGA-DNA, or that they were not detected by WES because it was performed at a mean coverage of 60x making it difficult to detect low frequency variants. None of the WGA-DNA specific variants were seen by WES. Taking all these factors into account, we used the fresh-DNA specific variants as the gold standard to further calculate the Positive Predictive Value (PPV) and the sensitivity of the WGA-DNA samples, and thus validate the accuracy of WGA technique in the sample preparation. This revealed a sensitivity of 61.7% (SD = 43.3) and a PPV of 53.3% (SD = 54.2). Conclusions: These findings suggest that WGA methods may introduce errors, that can be detected at a low frequency, and that some bias can be expected, explaining why some variants present the gDNA may be lost during the amplification process. Therefore, we believe that applying WGA before library preparation should be restrained to cases with very limited material source and should be followed by a more in-depth and strict bioinformatics analysis and filtering process. Disclosures Sole: Celgene: Membership on an entity's Board of Directors or advisory committees.

Whole-Genome Sequencing of Primary Central Nervous System Lymphoma and Diffuse Large B-Cell Lymphoma

Blood ◽  
2016 ◽  
Vol 128 (22) ◽  
pp. 4112-4112
Author(s):  
Kenichi Yoshida ◽  
Yuichi Shiraishi ◽  
Kenichi Chiba ◽  
Yusuke Okuno ◽  
Rie Nakamoto-Matsubara ◽  
...  
Keyword(s):  
Central Nervous System ◽  
B Cell ◽  
Research Funding ◽  
Somatic Mutations ◽  
Central Nervous System Lymphoma ◽  
Whole Genome ◽  
Mutational Signatures ◽  
Driver Genes ◽  
Systemic Dlbcl ◽  
Large B Cell

Abstract Introduction Primary central nervous system lymphoma (PCNSL) is a rare subtype of non-Hodgkin's lymphoma. Although most cases (~95%) show histology of diffuse large B-cell lymphomas (DLBCLs), PCNSL shows very different biological and clinical characteristics from systemic DLBCL. Nevertheless, our knowledge about the molecular pathogenesis of PCNSL and genetic differences between both lymphomas are still incomplete. Method To obtain a comprehensive view of the genetic alterations, including mutations in non-coding regions as well as structural variants (SVs), we performed whole-genome sequencing (WGS) of 22 PCNSL cases. Subsequently, to unravel the genetic differences between PCNSL and systemic DLBCL, we re-analyzed WGS data from systemic DLBCL cases (N = 47) generated by the Cancer Genome Atlas Network (TCGA) and Cancer Genome Characterization Initiative (CGCI) using our in-house pipeline. The mean depth of WGS for tumor samples were 49X and 37X for PCNSL and DLBCL cases, respectively. Whole-exome sequencing (WES) was also performed for an additional 37 PCNSL cases to reliably capture driver alterations and also to analyze mutational signatures in PCNSL, which were compared to those obtained from the WES data for DLBCL from TCGA (N = 49). Results WGS identified 10.5 and 5.6 mutations per mega-base on average in PCNSL and DLBCL, respectively. We first explored the density of somatic mutations and identified 64 and 33 genomic loci showing significantly high mutation densities in PCNSL and DLBCL, respectively. In PCNSL, most of these loci corresponded to known targets of somatic hypermutations (SHMs) induced by activation-induced cytidine deaminase (AID), including those for IG genes (IGK, IGH and IGL), BCL6, and PIM1, as well as those for known driver genes, such as MYD88 and CD79B. Although most of the hypermutated regions were overlapped between PCNSL and DLBCL, some regions were differentially affected by hypermutations between both lymphoma types. For example, BCL2 and SGK1 loci were frequently affected by SHMs in germinal center B-cell (GCB) DLBCL, while not in PCNSL. In terms of non-coding driver mutations, we identified frequent mutations in a PAX5 enhancer region in 8/22 (36%) of PCNSL and 18/47 (38%) of DLBCL cases. SVs were common in both lymphoma types, where 104 (PCNSL) and 57 (DLBCL) SVs were detected per sample. SV clusters were identified in 34 (PCNSL) and 13 (DLBCL) regions, of which several clusters were commonly seen in both PCNSL and DLBCL, and included IG loci, BCL6, FHIT, TOX and CDKN2A. In PCNSL, SVs were clustered within the loci for known targets of SHMs, such as BCL6, BTG2 and PIM1. As was the case with somatic mutations, the SV cluster corresponding to BCL2 was only seen in DLBCL. We then analyzed these clustered breakpoints for their proximity to known sequence motifs targeted by AID (CpG and WGCW). Breakpoints of SVs found in the targets of SHMs, including PIM1, BCL6, BTG2 and BCL2, showed an enrichment at or near the CpG, supporting the involvement of AID in the generation of these SVs. By analyzing these SV clusters, we identified several novel driver genes in PCNSL. For example, WGS and WES identified an enrichment of breakpoints of deletions (7/22) and loss-of-function mutations (6/37) in GRB2, strongly indicating its tumor suppressor role in PCNSL. We also analyzed pentanucleotide signatures of mutations in coding sequences detected by WES of PCNSL and DLBCL, taking into consideration the two adjacent bases 3' and 5' of the substitutions as well as transcription strand biases. Two predominant mutational signatures were identified in PCNSL: the AID signature characterized by C>T mutations within the WRCY motif targeted by SHMs and the age-related signature involving C>T transition at CpG dinucleotides. For DLBCL, an additional signature (signature 17 according to Alexandrov et al.) was detected as well, which had been reported in DLBCL with an unknown mechanistic basis. Conclusions Comprehensive genomic analyses of a large cohort of PCNSL and DLBCL cases have revealed the major targets of somatic mutations and SVs, including novel driver genes. In both PCNSL and systemic DLBCL, an enhanced AID activity is thought to be associated with generation of both SHMs and SVs, although the activity and targets of AID seem to substantially differ between both lymphoma types, suggesting distinct pathogenesis therein. Disclosures Kataoka: Boehringer Ingelheim: Honoraria; Yakult: Honoraria; Kyowa Hakko Kirin: Honoraria. Ogawa:Takeda Pharmaceuticals: Consultancy, Research Funding; Kan research institute: Consultancy, Research Funding; Sumitomo Dainippon Pharma: Research Funding.

Landscape of Mutations in Relapsed Acute Myeloid Leukemia

Blood ◽  
2014 ◽  
Vol 124 (21) ◽  
pp. 2367-2367
Author(s):  
Samuli Eldfors ◽  
Mika Kontro ◽  
Kimmo Porkka ◽  
Olli Kallioniemi ◽  
Caroline Heckman
Keyword(s):  
Drug Resistance ◽  
Research Funding ◽  
Somatic Mutations ◽  
Sequence Data ◽  
Donor Cell ◽  
Driver Mutations ◽  
Cell Transplant ◽  
Cancer Genes ◽  
Hematopoietic Stem ◽  
Germline Variants

Abstract While the majority of acute myeloid leukemia (AML) patients respond to induction chemotherapy, disease recurrence and drug resistance is common. Recently, mutations underlying AML pathogenesis have been extensively characterized by sequencing large numbers of samples obtained at diagnosis. However, mutations driving disease progression and drug resistance in relapsed AML are not well characterized. In addition, understanding the clonal composition of relapsed AML is compounded by interference of donor cell variants present in those patients who have received an allogeneic hematopoietic stem cell transplant (alloHSCT). In this study we sought to identify mutations and copy number aberrations associated with development of drug resistant AML, and at the same time develop methods to identify and filter out donor variants. For the study we analyzed samples from patients who had relapsed after therapy (N=18) by exome sequencing. This included a set of patients where diagnosis and relapse samples were available (n=10), and one patient with diagnosis, remission and relapse samples. All patients had received prior chemotherapy and a subset had relapsed after receiving an allogeneic hematopoietic stem cell transplant (alloHSCT, n=6). Four patients had secondary AML that had developed after treatment for earlier hematologic malignancy. Tumor DNA was from bone marrow mononuclear cells and germline DNA from matched skin biopsies. Exome libraries were prepared then sequenced with the Illumina HiSeq instrument. Sequence data was processed and somatic variants identified as described previously (Koskela et al., NEJM, 2012). We identified relapse specific and relapse enriched somatic mutations by comparing mutation profiles of diagnosis and relapse samples. Donor derived germline variants in chimeric samples from patients relapsing after alloHSCT were identified with a bioinformatic methodology utilizing the dbSNP population variant database. Somatic mutations called from chimeric samples were filtered for common population variants present in the donor’s genome. Rare donor derived population variants that have not been previously described were identified as variants not present in the patient’s germline genome and which had similar tumor variant allele frequencies as the common donor derived variants. We estimated the level of chimerism based on the variant allele frequencies of all donor derived variants. In chimeric samples, the number of donor derived variants vastly exceeded the number of somatic mutations in AMLs (Fig 1). Donor cell content varied widely ranging from close to 100% in a post transplant remission sample to 10-40% in relapse samples. In post-transplant samples, we identified on average 6800 donor germline variants within the exome-capture regions, many of which occurred within cancer genes which could potentially be misinterpreted as driver mutations. Many recurrent driver mutations in cancer genes were identified in the relapse samples: FLT3 (n=6, 33%), DNMT3A (n=4, 22%), NPM1 (n=2, 11%), WT1 (n=2, 11%), TP53 (n=2, 11%), CBL (n=2, 11%), NRAS (n=1, 6%), KRAS (n=1, 6%), IDH1 (n=1, 6%), PHF6 (n=1, 6%) and PTPN11 (n=1, 6%). In several cases, we observed that relapse-specific driver mutations occurred in the same genes or pathways that already had initial mutations at diagnosis. For example, one patient’s AML had a FLT3-ITD at diagnosis; at relapse an activating mutation in CBL and a loss of function mutation in PTPN11 were acquired. Both CBL and PTPN11 act downstream of FLT3 (Fig 2). In two patients with a heterozygous WT1 mutation at diagnosis, we found additional WT1 mutations or deletion of the remaining wild type allele in the relapse sample, suggesting full loss of normal WT1 function contributes to disease progression. Our results suggest that AML progression and drug resistance may be caused by strengthening aberrant signaling through pathways already affected by a mutation present at diagnosis. Hence, the pattern of mutual exclusivity of mutations to genes affecting the same pathway, which has been observed in diagnostic samples, does not occur at relapse. On the contrary, in several cases the relapse specific mutations affected genes in pathways already affected at diagnosis. In addition, we show that donor derived germline variants can be identified and filtered from exome sequence data. Figure 1 Figure 1. Disclosures Porkka: BMS: Honoraria; BMS: Research Funding; Novartis: Honoraria; Novartis: Research Funding; Pfizer: Research Funding. Kallioniemi:Medisapiens: Consultancy, Membership on an entity's Board of Directors or advisory committees.

NGS-Based Copy Number Analysis in 1,185 Patients with Myeloid Neoplasms

Blood ◽  
2016 ◽  
Vol 128 (22) ◽  
pp. 955-955 ◽  
Author(s):  
Ryunosuke Saiki ◽  
Yusuke Shiozawa ◽  
Tetsuichi Yoshizato ◽  
Kenichi Yoshida ◽  
Yuichi Shiraishi ◽  
...  
Keyword(s):  
Board Of Directors ◽  
Deep Sequencing ◽  
Copy Number ◽  
Research Funding ◽  
De Novo ◽  
Driver Genes ◽  
Advisory Committees ◽  
Myeloid Neoplasms ◽  
Targeted Deep Sequencing ◽  
De Novo Aml

Abstract Background Copy number alteration (CNA) is a hallmark of cancer genomes and has been implicated in the development of human cancers, including myeloid neoplasms. We developed a novel, next-generation sequencing-based platform for highly sensitive detection of CNAs with a single exon resolution, which was applied to sequencing data from 1,185 patients to delineate a comprehensive landscape of CNAs in myeloid neoplasms. Materials and Methods We enrolled 1,185 patients with different myeloid neoplasms including myelodysplastic syndromes (n = 607), myelodysplastic/myeloproliferative neoplasms (n = 80), de novo acute myeloid leukemia (AML) (n = 136), secondary AML (sAML) (n = 226), and unknown myeloid malignancies (n = 136). Whole-exome sequencing (WES) was performed on samples from 260 patients, while samples from 925 patients including pre-transplantation peripheral blood samples provided by Japan Marrow Donor Program were subjected to targeted deep sequencing. Eight cases were serially evaluated before and after progression tosAML. RNA baits for targeted deep sequencing were designed to cover 69 driver genes in myeloid neoplasms and 1,158 single-nucleotide polymorphisms (SNPs)for assessment of allelic imbalance. In WES, allelic imbalance was examined using allele frequencies of SNPs within coding regions. Focal CNAs were defined as CNAs whose lengths relative to the chromosomal arms were below 10%. Results To obtain a landscape of CNAs in coding regions, a comprehensive copy number analysis was performed on 260 patients including 136 with de novo AML and 124 with myeloid neoplasms with myelodysplasia, all of whom were studied by WES. A total of 755 CNAs (502 deletions and 253 amplifications) were identified, where 52% of the patients harbored at least one alteration. Using GISTIC 2.0 algorism, we identified 21 significantly altered regions involving known or putative driver genes (Figure 1): losses of 7q22.1 (CUX1), 12p13.2 (ETV6), 13q14 (RB1),17p13.1(TP53), and 17q11.2 (NF1), and gains of 3q26-27 (EVI1), 8q24.21 (MYC), 11q13.5-14.1(PAK1), 11q23.3 (MLL),11q24-25 (ETS1), 13q12.2 (FLT3),21q22.2 (ETS2 and ERG). We next compared the frequencies of CNAs between de novo AML and myeloid neoplasms with myelodysplasia. While chromosomes 7, 12, and 17 were commonly affected, deletions of 13q14 were significantly enriched in myeloid neoplasms with myelodysplasia (Odds ratio [OR]: 5.07, P = 0.040), and amplifications of 11q24-25 (OR: 5.54, P = 0.028), and 21q22.2 (OR: 6.10, P = 0.020) in de novo AML, suggesting a specific role of these events in each disease entity. In addition, serial sampling revealed trisomy8, deletions of 7q and 12p were recurrently acquired during leukemic transformation in patients withmyelodysplasia. Taken together, many driver genes in myeloid neoplasms were frequently targeted by CNAs includingmicrodeletions. Based on these finding, we sought to obtain a more detailed landscape of CNAs in a larger cohort. We combined copy number profiles of patients studied by targeted deep sequencing and those by WES. Of total, 1,691 CNAs (1,096 deletions and 595 amplifications) were detected, where 39% of the cases harbored at least one alteration. Microdeletionsor focal amplifications were frequently found in the significantly altered regions revealed by WES: microdeletionsof ETV6 (n = 10), NF1 (n = 8), CUX1 (n = 5), TP53 (n = 5), and amplifications of FLT3 (n = 7), ETS1 (n = 3), ETS2 (n = 3), and ERG (n = 3), validating the result obtained from a cohort studied by WES. We also identified known driver genes in myeloid neoplasms were recurrently affected with focal CNAs: microdeletions of RUNX1, BCOR, ASXL2, DNMT3A, and ZRSR2, and amplifications of GNAS, RIT1, CSF3R, and BCL11A. Among them, DNMT3A and ASXL2, located within 500 kb in chromosome 2, tended to be co-deleted (3 out of 4 cases). Focal deletions of TP53 were often affected with homozygous deletions or were accompanied by gene mutations, implying bi-allelic inactivation. High amplifications were also observed in regions including ETS1, MLL, FLT3, MYC, and PAK1, which suggest a critical role in the pathogenesis of myeloid malignancy. Conclusion We obtained the landscape of CNAs in myeloid neoplasms based on the sequencing data of 1,185 patients. Collectively, our results indicated that CNAs targeted a specific set genes including well-known drivers of myeloid malignancies, indicating a critical role inleukemogenesis. Disclosures Kanda: Otsuka Pharmaceutical: Honoraria, Research Funding. Sekeres:Celgene: Membership on an entity's Board of Directors or advisory committees; Millenium/Takeda: Membership on an entity's Board of Directors or advisory committees. Makishima:The Yasuda Medical Foundation: Research Funding. Maciejewski:Celgene: Consultancy, Honoraria, Speakers Bureau; Alexion Pharmaceuticals Inc: Consultancy, Honoraria, Speakers Bureau; Apellis Pharmaceuticals Inc: Membership on an entity's Board of Directors or advisory committees. Ogawa:Takeda Pharmaceuticals: Consultancy, Research Funding; Kan research institute: Consultancy, Research Funding; Sumitomo Dainippon Pharma: Research Funding.

scholarly journals Mutational landscape of primary, metastatic, and recurrent ovarian cancer reveals c-MYC gains as potential target for BET inhibitors

2018 ◽  
Vol 116 (2) ◽  
pp. 619-624 ◽  
Author(s):  
Charles Li ◽  
Elena Bonazzoli ◽  
Stefania Bellone ◽  
Jungmin Choi ◽  
Weilai Dong ◽  
...  
Keyword(s):  
Ovarian Cancer ◽  
Somatic Mutations ◽  
Driver Mutations ◽  
Cancer Evolution ◽  
Metastatic Tumors ◽  
Driver Genes ◽  
Primary Tumors ◽  
Mutational Landscape ◽  
Recurrent Tumors ◽  
Bet Inhibitors

Ovarian cancer remains the most lethal gynecologic malignancy. We analyzed the mutational landscape of 64 primary, 41 metastatic, and 17 recurrent fresh-frozen tumors from 77 patients along with matched normal DNA, by whole-exome sequencing (WES). We also sequenced 13 pairs of synchronous bilateral ovarian cancer (SBOC) to evaluate the evolutionary history. Lastly, to search for therapeutic targets, we evaluated the activity of the Bromodomain and Extra-Terminal motif (BET) inhibitor GS-626510 on primary tumors and xenografts harboring c-MYC amplifications. In line with previous studies, the large majority of germline and somatic mutations were found in BRCA1/2 (21%) and TP53 (86%) genes, respectively. Among mutations in known cancer driver genes, 77% were transmitted from primary tumors to metastatic tumors, and 80% from primary to recurrent tumors, indicating that driver mutations are commonly retained during ovarian cancer evolution. Importantly, the number, mutation spectra, and signatures in matched primary–metastatic tumors were extremely similar, suggesting transcoelomic metastases as an early dissemination process using preexisting metastatic ability rather than an evolution model. Similarly, comparison of SBOC showed extensive sharing of somatic mutations, unequivocally indicating a common ancestry in all cases. Among the 17 patients with matched tumors, four patients gained PIK3CA amplifications and two patients gained c-MYC amplifications in the recurrent tumors, with no loss of amplification or gain of deletions. Primary cell lines and xenografts derived from chemotherapy-resistant tumors demonstrated sensitivity to JQ1 and GS-626510 (P = 0.01), suggesting that oral BET inhibitors represent a class of personalized therapeutics in patients harboring recurrent/chemotherapy-resistant disease.

scholarly journals Discovering the drivers of clonal hematopoiesis

2020 ◽  
Author(s):  
Oriol Pich ◽  
Iker Reyes-Salazar ◽  
Abel Gonzalez-Perez ◽  
Nuria Lopez-Bigas
Keyword(s):  
Positive Selection ◽  
Molecular Mechanisms ◽  
Somatic Mutations ◽  
Cancer Genomics ◽  
Variant Calling ◽  
Selective Advantage ◽  
Cancer Genes ◽  
Driver Genes ◽  
Hematopoietic Stem ◽  
Clonal Hematopoiesis

AbstractMutations in genes that confer a selective advantage to hematopoietic stem cells (HSCs) in certain conditions drive clonal hematopoiesis (CH). While some CH drivers have been identified experimentally or through epidemiological studies, the compendium of all genes able to drive CH upon mutations in HSCs is far from complete. We propose that identifying signals of positive selection in blood somatic mutations may be an effective way to identify CH driver genes, similarly as done to identify cancer genes. Using a reverse somatic variant calling approach, we repurposed whole-genome and whole-exome blood/tumor paired samples of more than 12,000 donors from two large cancer genomics cohorts to identify blood somatic mutations. The application of IntOGen, a robust driver discovery pipeline, to blood somatic mutations across both cohorts, and more than 24,000 targeted sequenced samples yielded a list of close to 70 genes with signals of positive selection in CH, available at http://www.intogen.org/ch. This approach recovers all known CH genes, and discovers novel candidates. Generating this compendium is an essential step to understand the molecular mechanisms of CH and to accurately detect individuals with CH to ascertain their risk to develop related diseases.

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