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  • 1
    In: Blood, American Society of Hematology, Vol. 122, No. 21 ( 2013-11-15), p. 2828-2828
    Abstract: Primary myelofibrosis (PMF) is a myeloproliferative neoplasm, characterized amongst others by stem-cell derived clonal myeloproliferation, bone marrow fibrosis, anemia, splenomegaly, constitutional symptoms and leukemic progression. Diagnosis is based in most cases on cytomorphology/histology demonstrating fibrosis as well as on mutations in JAK2 or MPL. The Dynamic Prognostic Scoring System (DIPSS)-plus is the current base for prognostication using different clinical parameters including karyotype. Furthermore, molecular genetic alterations are currently addressed to provide additional prognostic information. Recently, besides JAK2 and MPL further gene mutations have been described in a limited number of patients, including ASXL1 and SRSF2. Aim To analyze in a large cohort the frequency of SRSF2 and ASXL1 mutations in PMF patients, and to identify their prognostic impact in the context of other previously described gene mutations. Patients and Methods Diagnosis was done according to WHO classification. The cohort comprised 82 female and 131 male patients. In all cases a BCR-ABL rearrangement was excluded by RT-PCR or fluorescence in situ hybridization. JAK2V617F mutation was analyzed in all cases by melting curve analysis, MPLW515 mutation was subsequently analyzed in JAK2V617 wild type (wt) patients. In addition, we analyzed all patients for SRSF2 mutations by Sanger sequencing of the mutational hot spot region coding for amino acid Pro95. Cytogenetics was available in 139 patients. Patients were grouped in favorable (n=121) and unfavorable (n=18) karyotypes based on the DIPSS-plus-scoring system. Based on the previously described correlation of SRSF2mut with ASXL1mut and SETBP1mut in other myeloid entities, SRSF2 mutated cases were also analyzed for mutations in ASXL1 and SETBP1by Sanger sequencing. Follow-up data was available for 136 patients. Results 56% (120/213) of the patients showed JAK2V617F mutations and 18.0% (16/89) of JAK2wt patients carried a mutation in MPLW515 summing up to 65.1% of patients with an already established molecular marker. Of note, SRSF2 was mutated in 12.7% (27/213) of all PMF patients. Patients with SRSF2 mutation had higher white blood cell counts in comparison to SRSF2wt patients (20.00x109/L vs. 7.35x109/L; p=0.005), but there was no correlation to gender, age, hemoglobin level, platelet count or % of myeloblasts in the peripheral blood. In 17 SRSF2mut cases the karyotype was available, 12 were normal karyotype, while two cases showed an unfavorable karyotype according to DIPSS-plus with +8 and i(17)(q10), respectively. The remaining three aberrations belong to the favorable aberration group (del(20q), del(13q), and der(14)). There was no correlation of SRSF2 mutations to the cytogenetic subgroups normal karyotype (n=91) or DIPSS categories favorable and unfavorable aberrations. SRSF2 mutations were also equally distributed between both JAK2V617 or MPLW515 mutated and wild type cases. 18/27 SRSF2mut cases carried also either a JAK2 or MPL mutation, while 9 cases showed no additional JAK2 or MPL mutation. Therefore 30.6% patients remain that carry no mutation in at least one of the three genes investigated first. Interestingly, ASXL1 was frequently mutated in SRSF2 mutated patients (16/23 analyzed SRSF2mut patients) while none of the 24 analyzed SRSF2 mutated cases showed a mutation in SETBP1. To evaluate a potential influence of gene mutations on clinical outcome the overall survival (OS) was calculated. We could confirm that JAK2V617F had no prognostic impact. The same was true for MPLW515 mutations. In contrast to other studies we could not find any impact of SRSF2mutations on OS. Only cytogenetics, i.e. the normal karyotype showed a trend to a prognostic relevance: the median 3 year OS was 70.8% in patients with normal karyotype (n=56) but 58.8% in patients with cytogenetic aberrations (n=29; p=0.153). Conclusion 1) SRSF2 is mutated in 13% of PMF patients. 2) SRSF2 mutated patients show frequently an additional ASXL1 mutation but no coincidence with SETBP1. 3) The prognostic relevance of cytogenetic aberrations was confirmed, while the molecular marker SRSF2 shows no impact on prognosis. Disclosures: Meggendorfer: MLL Munich Leukemia Laboratory: Employment. Alpermann:MLL Munich Leukemia Laboratory: Employment. Eder:MLL Munich Leukemia Laboratory: Employment. Haferlach:MLL Munich Leukemia Laboratory: Employment, Equity Ownership. Kern:MLL Munich Leukemia Laboratory: Employment, Equity Ownership. Haferlach:MLL Munich Leukemia Laboratory: Employment, Equity Ownership. Schnittger:MLL Munich Leukemia Laboratory: Employment, Equity Ownership.
    Type of Medium: Online Resource
    ISSN: 0006-4971 , 1528-0020
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    Language: English
    Publisher: American Society of Hematology
    Publication Date: 2013
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  • 2
    In: Blood, American Society of Hematology, Vol. 120, No. 21 ( 2012-11-16), p. 2662-2662
    Abstract: Abstract 2662 Introduction: Diagnosis of mantle cell lymphoma (MCL) is based on cytomorphology/histology and/or immunophenotyping as well as demonstration of cyclin D1 (CCDN1) over-expression and/or presence of a t(11;14)(q13;q32)/IGH-CCND1 rearrangement. However, some cases that are considered to belong to the MCL entity lack the CCND1 over-expression and the t(11;14) translocation and thus are difficult to distinguish from other small B-cell lymphomas. This distinction is clinically very relevant, since true MCLs show an aggressive behavior while many other B-cell lymphomas do not. Recently, the over-expression of SOX11 has been demonstrated to be specific for MCLs independent of CCND1 positivity, suggesting a diagnostic role of SOX11 expression in t(11;14) negative MCLs. The prognostic role of SOX11 has been controversially discussed. Aim: To evaluate the applicability and usefulness of SOX11 expression as a diagnostic marker for differentiation of B-cell lymphomas and to determine its impact on outcome. Patients and Methods: In this study we analyzed 159 patients with B-cell lymphomas for SOX11 and CCND1 expression levels by quantitative real time PCR. Patients were diagnosed by cytomorphology, immunophenotyping, cytogenetics and FISH and based on these methods were categorized into t(11;14) positive MCL (n=55), t(11;14) negative mature B-cell neoplasms with an MCL-typical immunophenotype (n=37), CLL (n=29), and CLL/PL (n=38). The gene expression levels were quantified and are given relative to ABL1 gene expression. Based on a negative control cohort (n=40) comprising 20 peripheral blood and 20 bone marrow samples without evidence for malignancy the cut-off for rating the expression ratio positive was calculated by the mean value plus the threefold standard deviation and resulted in 0.29 for SOX11 and 2.9 for CCND1. Results: In the total cohort SOX11 expression was present in 53/159 cases (33.3%) and was strongly associated with a t(11;14) translocation (45/55, 81.8% in t(11;14) positive cases vs. 8/104, 7.7% in t(11;14) negative cases, p 〈 0.001). Correspondingly, SOX11 expression correlated with CCND1 expression regarding positivity (45/59 (76.3%) in CCND1 positive cases vs. 8/100 (8.0 %) in CCND1 negative cases, p 〈 0.001). Also the absolute expression levels of both genes showed a high correlation (Spearman, correlation coefficient: 0.631, p 〈 0.001). SOX11 positive patients were younger (63.8 vs. 68.8 years; p=0.011), showed a slightly lower hemoglobin level (12.13 vs. 12.96 g/dL; p=0.04) and a lower platelet count (145,024 vs. 202,914/μl; p 〈 0.001). A detailed analysis within the respective diagnostic subgroups revealed that SOX11 was expressed in 45/55 t(11;14) positive MCL cases (81.8%) with an overall high expression level (median: 58.9; range: 0.3–1363.8). As expected in this entity all cases were CCND1 positive. In the group of 37 t(11;14) negative B-cell neoplasms with an MCL-typical immunophenotype one case was rated positive for CCND1 expression while 6 other cases (16.2%) showed a SOX11 expression (median: 2.0; range: 0.5–322.7), suggesting that these 6 cases might be CCND1 negative MCLs. Two of the 38 CLL/PL cases were SOX11 positive but lacked CCND1 expression. In contrast, SOX11 was never rated positive in CLL cases, while 1 case showed high CCND1 expression. For a total of 107 patients the time to treatment (TTT) was available for correlation analysis. Cases with SOX11 expression had a shorter time to treatment as compared to those without (median TTT: 37 vs. 56 months, p=0.011), what was also true for CCDN1 positive (median TTT: 37 vs. 58 months, p=0.07) and t(11;14) positive cases (median TTT: 6 vs. 56 months, p=0.003). Conclusion: SOX11 expression may be used in addition to CCDN1 as a marker for identification of t(11;14) positive MCLs. However, some rare B-cell neoplasms are considered to belong to the MCL but lack the t(11;14) and CCND1 over-expression. The differential diagnosis of this entity from other small B-cell lymphomas is difficult. SOX11 expression may be considered as a useful marker in addition to CCND1 expression in identification of t(11;14) negative MCL. Patients with SOX11 expression showed a shorter time to treatment, but further analyses are warranted to proof the diagnostic role of SOX11 expression as well as its prognostic impact. Disclosures: Meggendorfer: MLL Munich Leukemia Laboratory: Employment. Kern:MLL Munich Leukemia Laboratory: Equity Ownership. Haferlach:MLL Munich Leukemia Laboratory: Equity Ownership. Haferlach:MLL Munich Leukemia Laboratory: Equity Ownership. Schnittger:MLL Munich Leukemia Laboratory: Equity Ownership.
    Type of Medium: Online Resource
    ISSN: 0006-4971 , 1528-0020
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    Language: English
    Publisher: American Society of Hematology
    Publication Date: 2012
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  • 3
    In: Blood, American Society of Hematology, Vol. 128, No. 22 ( 2016-12-02), p. 1710-1710
    Abstract: Introduction: Investigation of minimal residual disease (MRD) using NPM1 as a target has been proven to be of importance in AML. Guidelines for best schedules and implication on clinical use need to be defined. Aims: To better define the clinical impact and to suggest strategies for MRD monitoring in AML with NPM1 mutation. Patients and Methods: Between 2005 and 2015 we investigated 428 AML patients (pts) with NPM1 mutation at diagnosis and at a minimum of 2 follow-up time points. All pts had to achieve at least once a complete molecular remission (CMR) to be considered for this study. Sensitivity for MRD detection was at least 1:10,000. The median age of the cohort was 57 years (range: 18-85 yrs) and comprised of 198 males and 230 females. 3,039 samples (median number of samples per pts: 7, range: 2-35) were studied during course of disease. Molecular techniques applied included gene scan, sequencing and quantitative real-time PCR at diagnosis and quantitative real-time PCR during follow-up. Median time between 2 investigations was 2.8 months (mo; range: 0.3-71.0 mo). All pts were treated with standard protocols according to genotype and age. Allogeneic bone marrow or stem cell transplantation was performed in 136 pts (31.8%). Results: NPM1 type A mutation was the most frequent mutation type (317/428, 74.1%), followed by type B and D (36/428, 8.4% and 23/428, 5.4%), respectively. 25 other NPM1 types occurred at frequencies between 0.2 and 3.7%, in total demonstrating the expected distribution of NPM1 mutation types in an adult AML cohort. Subgroups of these pts were analyzed for FLT3-ITD (n=421) and mutations in DNMT3A (n=236). 122/421 (29%) pts showed a FLT3-ITD. In 96/236 (41%) DNMT3A was mutated. Further in 33/235 (14%) both genes were mutated. 103/235 (44%) screened for all three genes had a sole NPM1 mutation. All sole NPM1 mutated study pts achieved the CMR after a median of 4.1 mo (range: 1.0-8.6 mo). The presence of an additional DNMT3A mutation (CMR after a median of 4.4 mo, range 1.0-8.7) or a FLT3-ITD (CMR after a median of 2.7 mo, range 1.0-8.7) or both mutations (CMR after a median of 4.1 mo, range 1.1-7.9 mo) had no influence on time to achieve CMR. After achievement of CMR an increase of NPM1 ratio was detected in 185/428 (43%) pts. The median time to loss of CMR was 5.1 mo (range: 0.4-88 mo). In more detail, 42/185 of these patients also had FLT3-ITD, 53/109 had DNMT3A mutations and 13/109 had mutations in both genes. Patients with a DNMT3A mutation showed more often loss of CMR (40/60, 67%), while FLT3-ITD and FLT3-ITD/DNMT3A mutated patients showed no significant influence on loss of CMR ratio (46% and 48%, respectively) maybe due to number of cases. In 152/185 molecular relapses further follow up samples after loss of CMR were available. The median time between detected loss of CMR and the next follow-up sample was 2.0 mo. Due to treatment intervention 46/152 patients achieved a second CMR and 27/152 a decrease in NPM1 ratio. However, in 79/152 a further increase leading to clinical relapse was observed. The increase after loss of CMR was in median 13-fold between first and second sample after CMR was lost. Importantly, keeping periods between two MRD samplings at an interval of 3 mo allowed the detection of nearly all cases of first relapse at the molecular level. Addressing the sensitivity levels of the assays applied to bone marrow (BM) versus peripheral blood (pB) samples showed a 1.6 fold higher sensitivity for BM samples (median copies of reference gene, 14,628 vs 9,363). Due to the comparable sensitivities pB can be investigated until a first increase on the molecular level is detectable, followed by BM sampling for confirmation 4 weeks later. Conclusions: 1) NPM1 has proven to be a good marker for MRD monitoring in AML. 2) Time to CMR is short with a median of 4.1 mo. 3) An increase of NPM1 in all cases is followed by relapse after a median of 5.1 mo, if no treatment intervention has been initiated before. 4) Time intervals for MRD should be no longer than 3 mo, pB can be used. 5) Transplantation should already be planned after first molecular increase is detected. Disclosures Haferlach: MLL Munich Leukemia Laboratory: Employment, Equity Ownership. Haferlach:MLL Munich Leukemia Laboratory: Employment, Equity Ownership. Worseg:MLL Munich Leukemia Laboratory: Employment. Perglerová:MLL2 s.r.o: Employment. Kern:MLL Munich Leukemia Laboratory: Employment, Equity Ownership. Meggendorfer:MLL Munich Leukemia Laboratory: Employment.
    Type of Medium: Online Resource
    ISSN: 0006-4971 , 1528-0020
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    Language: English
    Publisher: American Society of Hematology
    Publication Date: 2016
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  • 4
    In: Blood, American Society of Hematology, Vol. 128, No. 22 ( 2016-12-02), p. 2857-2857
    Abstract: Background: The genomic landscape of hematological malignancies has been resolved mainly based on whole exome and whole genome sequencing, primarily targeting gene mutations. Beside mutations also gene fusions function as therapeutic targets, impressively shown for e.g. BCR-ABL1 and ETV6-PDGFRB. Hence, the need for a comprehensive genetic analysis is increasing, as it is the basis for precision medicine, selecting treatment based on genotype and providing markers for disease monitoring. Aim: To test the value of targeted RNA sequencing in a routine diagnostic work up. Patients and Methods: 38 cases were selected in which rearrangements involving KMT2A (n=8), RUNX1 (n=19), ETV6 (n=9), RARA (n=1) and JAK2 (n=1) had been identified by chromosome banding analysis (CBA) complemented by FISH analysis. In all cases the partner gene could not be identified using standard methods. Targeted RNA sequencing was performed using the TruSight RNA Fusion panel (Illumina, San Diego, CA) consisting of 7690 probes covering 507 genes known to be involved in gene fusions. Library was prepared according to manufacturer's protocol with ~50ng DNA extracted from fresh/frozen samples. This assay allows the capture of all targeted transcripts. Sequencing was performed on two NextSeq runs (Illumina, San Diego, CA) with 20 multiplexed samples including two samples with known fusions as positive control samples. Analysis was performed with the RNA-Seq Alignment App (BaseSpace Sequence Hub) using Star for Alignment and Manta for gene fusion calling with default parameters (Illumina, San Diego, CA). Results: In 22/38 cases with rearrangements involving KMT2A (n=8), RUNX1 (n=8), ETV6 (n=4), RARA (n=1) or JAK2 (n=1) this approach led to important new information: The following partner genes for KMT2A were identified: MLLT10 (n=2), MLLT1 (n=2), ITPR2, FLNC, ASXL2 and ARHGEF12. MLLT10 and MLLT1 are two of the most frequent partner genes of KMT2A, while KMT2A-ARHGEF12 fusions are rare. Fusion of KMT2A to ITPR2, FLNC, or ASXL2 have not been reported yet. Seven different partner genes were identified in RUNX1 translocated cases. These were PLAG1 (n=2), PRDM16, MECOM, ZFPM2, MAN1A2, N6AMT2, and KIAA1549L. PRDM1, MECOM and ZFPM2 have previously been described in the literature as RUNX1 partner genes but were not suspected in our cases as partner genes due to complex cytogenetic rearrangements in CBA. The other identified partner genes have not been described so far. Interestingly, PRDM1, MECOM, ZFPM2 and the newly identified PLAG1 are all members of the C2H2-type zinc finger gene family. Four different partner genes were identified in ETV6 rearranged cases: ABL1, CCDC126, CLPTM1L, and CFLAR-AS1. Most strikingly was the identification of the ETV6-ABL1 fusion, which could not be suspected by cytogenetics as the 5' ETV6 FISH signal was located on chromosome 7. This ETV6-ABL1 fusion was confirmed by conventional RT-PCR. In an ALL patient a JAK2-PPFIBP1 fusion was identified leading to classification as a BCR-ABL1-like ALL. In an APL patient showing an ins(17;11)(q12;q14q23) in chromosome banding analysis a ZBTB16-RARA fusion was identified and thus resistance to all-trans retinoic acid, arsenic trioxide, and anthracyclines can be predicted. All these fusions were not detectable by our routine RT-PCR analyses as these assays cover only the most frequently occurring breakpoints in fusions with known partner genes, but might miss very rare variants. For all yet undescribed fusion partners routine assays are not available. Based on the results of targeted RNA sequencing quantitative PCR assays for MRD monitoring can now be established. In 11 cases with a RUNX1 rearrangement and 5 cases with an ETV6 rearrangement no fusion transcript was identified. Further analyses will have to clarify whether in these cases no transcript was derived from the genomic rearrangement. Conclusions: 1) Targeted RNA sequencing was able to identify and characterize rare gene fusions and thus provided the basis for the design of RT-PCR based assays for monitoring MRD. 2) Targetable genetic aberrations were identified, which were not identifiable by chromosome banding analysis but would now lead to more individualized treatment. 3) Thus, targeted RNA sequencing may be a valuable tool in routine diagnostics for patients with rearrangements unresolved by standard techniques, also paving the way to precision medicine in a considerable number of patients. Disclosures Haferlach: MLL Munich Leukemia Laboratory: Employment, Equity Ownership. Nadarajah:MLL Munich Leukemia Laboratory: Employment. Meggendorfer:MLL Munich Leukemia Laboratory: Employment. Dicht:MLL Munich Leukemia Laboratory: Employment. Stengel:MLL Munich Leukemia Laboratory: Employment. Kern:MLL Munich Leukemia Laboratory: Employment, Equity Ownership. Haferlach:MLL Munich Leukemia Laboratory: Employment, Equity Ownership.
    Type of Medium: Online Resource
    ISSN: 0006-4971 , 1528-0020
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    Language: English
    Publisher: American Society of Hematology
    Publication Date: 2016
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  • 5
    In: Blood, American Society of Hematology, Vol. 124, No. 21 ( 2014-12-06), p. 700-700
    Abstract: Background: NPM1 mutations (mut) are considered the most frequent mutations in de novo acute myeloid leukemia (AML) and have been suggested as provisional entity in the WHO classification 2008. It has become clear that nearly all NPM1mut AML have additional mutations that may contribute to onset of AML by affecting different genetic pathways. However, it has not been evaluated yet whether the pattern of additional mutations varies between NPM1mut de novo AML and NPM1mut secondary AML (sAML) arising from a previous myelodysplastic syndrome (MDS). Aim: To evaluate the 1) genetic pattern associated with NPM1mut de novo AML and sAML, 2) chronologic sequence of mutations from MDS to sAML. Patients and Methods: 5,545 de novo AML and 504 sAML cases were analyzed during the last 9 years. The de novo cohort was comprised of 2,951 males and 2,594 females, median age was 65.7 years (y; range 17.5-93.1 y). The sAML cohort was comprised of 329 males and 175 females, median age was 71.7 y (range 29.3-91.8 y; p=0.004). All cases were analyzed for NPM1mut by a melting curve analysis. For more detailed analysis from these cohorts 359 NPM1mut de novo AML (162 male, 197 female; median age: 61.4 y, range: 17.8-88.0 y), and 21 sAML (12 male, 9 female; median age: 70.3 y, range: 44.2-87.4 y) were selected for mutation analysis in 13 different genes (ASXL1, CEBPA, DNMT3A, FLT3-ITD, FLT3-TKD, IDH1, IDH2, KRAS, MLL-PTD, NRAS, RUNX1, TET2, TP53, WT1). Paired samples from the diagnostic time points of both MDS and sAML, respectively, were available in all 21 sAML cases. For both time points an NPM1-specific quantitative real time PCR was performed in addition. Results: First the overall frequency of NPM1mut was calculated from the total cohort. NPM1mut was more frequent in de novo AML (1,737/5,545 cases; 31.2%) than in sAML (67/504; 13.3%) (p 〈 0.001). Frequencies for mutations in all other genes were calculated for the selected NPM1mut subcohorts only. In de novo AML DNMT3A was the most frequently mutated gene (204/359; 56.8%), followed by FLT3-ITD (n=157; 43.7%), TET2 (n=101; 28.1%), IDH2 (n=52; 14.5%), NRAS (n=50; 13.9%), FLT3-TKD (n=49; 13.6%), IDH1 (n=47; 13.1%), CEBPA (single mutated: n=30; 8.4%; no double mutated cases), WT1 (n=23; 6.4%), KRAS (n=16, 4.5%), ASXL1 (n=10; 2.8%) and RUNX1 (n=2; 0.6%). No mutations were detected in TP53 or MLL-PTD. In the sAML cohort of 21 NPM1mut cases the most frequent additional mutations were present in TET2 (n=12, 57.1%), followed by FLT3mut (7 ITD and 1TKD) (n=8, 38.1%), ASXL1 and DNMT3A (n=4, 19.0%, each) and each 2 (9.5%) in IDH1, IDH2, KRAS, NRAS, RUNX1 and WT1, respectively. Thus DNMT3Amut were significantly more frequent cooperating with NPM1mut in de novo AML (56.8% vs. 19.0%, p=0.001). In contrast, mutations in TET2 (57.1% vs 28.1%, p=0.005), ASXL1 (19% vs. 2.8%, p 〈 0.001) and RUNX1 (9.5% vs. 0.6%, p 〈 0.001) were more frequent in sAML. For none of the other mutations any significant difference between de novo and sAML was observed. Next, we evaluated the chronologic sequence of the emergence of the respective mutations by comparing the paired MDS and sAML samples. At MDS phase and at a sensitivity of 10-7 the NPM1 mutations were undetectable in 6 patients and detectable at a very low level (0.01-1%) in 8 pts. In contrast, in 7 cases the NPM1mut was already detectable at a level of 5-100% (median: 10%). At MDS phase the median number of additional mutations was 1 (range: 1-4), at sAML it increased to 3 (range: 1-5). All 12 TET2mut and all 4 DNMT3Amut cases carried this mutation already at MDS phase, thus these two genes can be regarded as early events. ASXL1 was present in 3 cases at MDS and was gained at AML in 1 case. IDH mutations (n=5) were stable in 3 and gained or lost in 1 patient each. RAS mutations were gained in 3 and lost in 1case. FLT3mut (n=8) were never detected at MDS but gained in all cases at sAML stage and thus can be regarded as late events. Median time from diagnosis of MDS to transformation to sAML was 9.2 months (range: 1.6 - 33.6 months). Median time to transformation was shorter in cases with TET2mut (8.2 vs.16.8 months, p=0.026) than in TET2 wildtype cases. No impact on time to transformation was seen for the other mutations. Conclusions: NPM1 mutations 1) occur less frequent in sAML than in de novo AML, 2) like FLT3mut are usually late events that drive transformation from MDS to sAML, 3) are frequently associated with TET2, ASXL1 and RUNX1 mutations in sAML whereas in de novo AML most frequently are accompanied by DNMT3A mutations. Disclosures Schnittger: MLL Munich Leukemia Laboratory: Employment, Equity Ownership. Haferlach:MLL Munich Leukemia Laboratory: Employment, Equity Ownership. Nadarajah:MLL Munich Leukemia Laboratory: Employment. Alpermann:MLL Munich Leukemia Laboratory: Employment. Meggendorfer:MLL Munich Leukemia Laboratory: Employment. Perglerová:MLL2 s.r.o.: Employment. Kern:MLL Munich Leukemia Laboratory: Employment, Equity Ownership. Haferlach:MLL Munich Leukemia Laboratory: Employment, Equity Ownership.
    Type of Medium: Online Resource
    ISSN: 0006-4971 , 1528-0020
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    Language: English
    Publisher: American Society of Hematology
    Publication Date: 2014
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  • 6
    In: Blood, American Society of Hematology, Vol. 122, No. 21 ( 2013-11-15), p. 1364-1364
    Abstract: The identification of mutations (mut) in SETBP1 recently shed light on a molecular marker in atypical chronic myeloid leukemia (aCML), a disease previously defined by exclusion criteria. SETBP1mut have been identified in different myeloid malignancies. We previously reported mutation frequencies in the range of 5-10% in MPN and MDS/MPN overlap, 32% in aCML, while we found SETBP1 less frequently mutated in AML (3%). SETBP1mut has been shown to associate with ASXL1, CBL and SRSF2 mutations, as well as the cytogenetic abnormalities -7 and i(17)(q10). Aim To investigate the mutation frequency of ASXL1, SETBP1, and SRSF2 in different myeloid entities in correlation to the cytogenetic abnormalities -7 and i(17)(q10). Patients and Methods A cohort of 451 patients (pts) with different myeloid entities was analyzed. Diagnoses according to cytomorphology followed the WHO classification from 2008 (n=439, for n=12 cases no cytomorphology was available): AML (n=29), aCML (n=62), MDS/MPN overlap (n=16), CMML (n=283), MDS (n=5), MPN (n=43), CML (n=1). The cohort consisted of 303 males and 148 females; cytogenetics was available in 445 cases. Patients were grouped by normal karyotype (n=291), i(17)(q10) (n=16), -7 (n=22), and other cytogenetic aberrations (n=117); one case carried both a i(17)(q10) and a -7. ASXL1 exon 13, the mutational hotspot regions of SETBP1 and SRSF2 were analyzed by Sanger sequencing in all cases. Results In the total cohort ASXL1 was mutated in 222/451 (49%), SETBP1 in 61/451 (14%), and SRSF2 in 209/451 (46%) cases. 137 pts showed no mutation in any of these three genes. 171 pts carried one mutation, thereof 84 a sole ASXL1mut, 82 a sole SRSF2mut and only 5 cases showed sole SETBP1mut. In 108 pts two, and in 35 pts all three analyzed genes were mutated. The most frequent combination within the group with two mutations was ASXL1 and SRSF2 (n=78), followed by ASXL1 and SETBP1 (n=16), only 5 cases were mutated in SRSF2 and SETBP1. Addressing the association with cytogenetics revealed that in cases with only one mutation SRSF2mut associated as sole mutation with a normal karyotype (68/124 (55%) SRSF2mut in the normal karyotype group vs. 12/42 (28%) SRSF2mut in all other karyotypes; p=0.003). In contrast, ASXL1mut and SETBP1mut as sole mutations showed no correlation to any addressed karyotype. However, addressing the cases with two mutations the combination of SRSF2mut and ASXL1mut correlated with a normal karyotype (67/291 (23%) SRSF2mut/ASXL1mut in the normal karyotype group vs. 19/154 (12%) SRSF2mut/ASXL1mut in all other karyotypes; p=0.008), while SRSF2mut and SETBP1mut occurred more frequently in i(17)(q10) pts (2/16 (13%) SRSF2mut/SETBP1mut in i(17)(q10) vs. 2/429 (1%) SRSF2mut/SETBP1mut in all other karyotypes; p=0.007). Remarkably, cases with mutations in all three analyzed genes (ASXL1mut, SETBP1mut, and SRSF2mut) highly associated with i(17)(q10) and -7. 11 of 16 cases with i(17)(q10) (69%) showed all three mutations (vs. 24/429 (6%) in all other karyotypes; p 〈 0.001). Furthermore, 6 of 22 cases with -7 (27%) showed mutations in all three genes (vs. 29/423 (7%); p=0.005). Therefore, 15 pts carried all three mutated genes as well as i(17)(q10) or -7. Interestingly, there was no case with only i(17)(q10) and no additional mutation, and only one case with i(17)(q10) and only one additional molecular mutation, 4 cases with two additional molecular mutations and 11 cases carrying all three mutations, possibly indicating that i(17)(q10) appear during clonal evolution. Therefore one might assume that this represents a specific genetic phenotype that is driven by the accumulation of molecular events, since addition of SETBP1mut shifts the association from a normal karyotype to i(17)(q10) or -7. Analyzing the distribution of these cases for mutations in all three analyzed genes +/- additional cytogenetic aberration i(17)(q10) or -7 in the different myeloid entities showed that AML, aCML, CMML, MDS as well as MPN showed this genetic phenotype (AML: n=7 (24%); atypical CML: n=12 (19%); CMML: n=8 (3%); MDS: n=1 (20%); MPN: n=6 (14%)). Conclusions Mutations in SETBP1 associate with ASXL1mut and SRSF2mut and are frequently found in patients with i(17)(q10) or -7. This combination of genetic lesions occurs in different myeloid entities and might therefore define a specific genetically defined subtype of myeloid malignancy. Disclosures: Meggendorfer: MLL Munich Leukemia Laboratory: Employment. Alpermann:MLL Munich Leukemia Laboratory: Employment. Haferlach:MLL Munich Leukemia Laboratory: Employment, Equity Ownership. Sirch:MLL Munich Leukemia Laboratory: Employment. Kern:MLL Munich Leukemia Laboratory: Employment, Equity Ownership. Haferlach:MLL Munich Leukemia Laboratory: Employment, Equity Ownership. Schnittger:MLL Munich Leukemia Laboratory: Employment, Equity Ownership.
    Type of Medium: Online Resource
    ISSN: 0006-4971 , 1528-0020
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    Language: English
    Publisher: American Society of Hematology
    Publication Date: 2013
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  • 7
    In: Blood, American Society of Hematology, Vol. 128, No. 10 ( 2016-09-08), p. 1408-1417
    Abstract: Risk assessment is crucial in patients with CMML because survival may range from a few months to several years. Integrating clinical features, morphology, and genetic lesions significantly improves risk stratification in CMML.
    Type of Medium: Online Resource
    ISSN: 0006-4971 , 1528-0020
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    Language: English
    Publisher: American Society of Hematology
    Publication Date: 2016
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  • 8
    In: Blood, American Society of Hematology, Vol. 124, No. 21 ( 2014-12-06), p. 4618-4618
    Abstract: Introduction: The World Health Organization (WHO) classification defines myelodysplastic/myeloproliferative neoplasms (MDS/MPN) based on clinical, morphologic, and laboratory findings that show features of MDS and characteristics more consistent with MPN. This category includes atypical chronic myeloid leukemia (aCML), chronic myelomonocytic leukemia (CMML), MDS/MPN, unclassifiable (MDS/MPN, U), and refractory anemia with ring sideroblasts associated with marked thrombocytosis (RARS-T). In recent years RARS-T, CMML, and also aCML were deciphered by several molecular studies, while MDS/MPN, U cases warrant closer investigations. Aim: To comprehensively investigate mutations in 17 genes known to be mutated in aCML, CMML, MDS/MPN, U, and RARS-T and to define entity specific mutation patterns in comparison to cytogenetic and clinical data. Patients and Methods: We investigated 179 patients diagnosed by cytomorphology, immunophenotyping and genetic studies following WHO criteria: 35 patients were diagnosed as aCML, 58 as CMML, 39 as MDS/MPN, U, and 47 as RARS-T. All patients underwent mutation analyses by a gene panel containing: ASXL1, TET2, DNMT3A, SRSF2, SF3B1, U2AF1, JAK2, CALR, MPL, NRAS, KRAS, CBL, BRAF, CSF3R, RUNX1, SETBP1, and NPM1. Gene mutations were analyzed by Sanger sequencing, next generation sequencing, melting curve analyses, or gene scan. Cytogenetics was available in 172/179 cases and was grouped as normal karyotype (n=128, 74%) or aberrant karyotype (n=44, 26%). Results: In the total cohort the most frequently mutated gene was ASXL1 (41%), followed by TET2 (40%), and the spliceosomal genes SF3B1 (31%) and SRSF2 (30%). Also frequently mutated were JAK2 (21%), NRAS (15%), RUNX1 (12%), and CBL (12%). All other investigated genes showed mutation frequencies below 10%. There were no significant differences between the 4 entities regarding frequencies of aberrant karyotypes (14-37%) and no correlation of the number of molecular mutations (0-6/patient) with any specific karyotype. Addressing the mutation patterns of these 4 entities showed that ASXL1 and TET2 are frequently mutated in all entities (19-60% and 26-53%, respectively), although significant differences between the entities exist (see figure): ASXL1 is less frequently mutated in RARS-T (19%) in comparison to aCML (60%; p 〈 0.001) and CMML (52%; p=0.001), TET2 is more often mutated in CMML (53%) in comparison to MDS/MPN, U (26%; p=0.007) and RARS-T (32%; p=0.031). SRSF2 is more frequently mutated in CMML (53%) than in RARS-T (9%; p 〈 0.001) and MDS/MPN, U (15%; p 〈 0.001), SF3B1 is more often mutated in RARS-T (92%) than in all other entities (aCML: 11%, CMML: 5%, MDS/MPN, U: 13%; for all p 〈 0.001). One important difference between aCML and CMML versus MDS/MPN, U and RARS-T was reflected by two different signaling pathways: i) JAK2/CALR/MPL (JAK/STAT pathway) were significantly more often affected in MDS/MPN, U (33%) and RARS-T (53%), (aCML: 9%, CMML: 7%; p 〈 0.001). ii) NRAS/KRAS/CBL (RAS pathway) were more often mutated in aCML (37%) and CMML (52%), (MDS/MPN, U: 5%, RARS-T: 9%; p 〈 0.001). The MDS/MPN, U cohort included most patients with no mutation in any analyzed gene (11/39, 28%) in contrast to aCML (2/23, 6%), CMML (5/58, 9%), and RARS-T (0/47, 0%). Furthermore all these MDS/MPN, U patients with no gene mutation had a normal karyotype. Looking at co-ocurrences of gene mutations in MDS/MPN, U revealed that SRSF2 and TET2 mutations occur together more frequently (4/10 vs. 2/29 in TET2wt; p=0.028). Of notice, in MDS/MPN, U U2AF1 (18%) was the most frequently mutated spliceosomal gene which was only rarely mutated in the other entities (5%, p=0.015). Conclusions: 1) ASXL1 and TET2 are the most frequently mutated genes found overall in MDS/MPN overlap. 2) SF3B1 mutations are specific for RARS-T. 3) SRSF2 is most frequently mutated in CMML, but also in aCML. 4) MDS/MPN, U is affected by mutations in all spliceosomal genes. 5) The JAK/STAT pathway is more often affected in MDS/MPN, U and RARS-T. 6) The RAS pathway is more often affected in aCML and CMML. 7) MDS/MPN, U shows a specific molecular pattern with characteristics reflecting a mixture of all other MDS/MPN entities. Red: gene mutation, orange: gene mutations combined, light grey: no mutation/normal karyotype, black: aberrant karyotype, white: not analyzed. Figure: Molecular abnormalities and cytogenetics in MDS/MPN entities. Figure:. Molecular abnormalities and cytogenetics in MDS/MPN entities. Disclosures Meggendorfer: MLL Munich Leukemia Laboratory: Employment. Haferlach:MLL Munich Leukemia Laboratory: Employment, Equity Ownership. Jeromin:MLL Munich Leukemia Laboratory: Employment. Haferlach:MLL Munich Leukemia Laboratory: Employment, Equity Ownership. Kern:MLL Munich Leukemia Laboratory: Employment, Equity Ownership. Schnittger:MLL Munich Leukemia Laboratory: Employment, Equity Ownership.
    Type of Medium: Online Resource
    ISSN: 0006-4971 , 1528-0020
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    Language: English
    Publisher: American Society of Hematology
    Publication Date: 2014
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  • 9
    Online Resource
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    American Society of Hematology ; 2015
    In:  Blood Vol. 126, No. 23 ( 2015-12-03), p. 3821-3821
    In: Blood, American Society of Hematology, Vol. 126, No. 23 ( 2015-12-03), p. 3821-3821
    Abstract: Introduction: Incidences of myeloid neoplasms, i.e. AML, MDS, MDS/MPN overlap, increase with age. Cytogenetic aberrations are still the hallmark for diagnosis and prognostication especially in AML and MDS. Different patterns of relations between chromosomal aberrations and age have been described. However, in recent years, gene mutations have been depicted to further discriminate patients with respect to their diagnosis and are increasingly used for prognostication. In parallel, recent studies (Jaiswal, NEJM 2014) have demonstrated that mutations in genes occurring in hematological neoplasms are also observed in healthy individuals and increase in frequency with age. Aim: To investigate if specific molecular markers, such as DNMT3A, ASXL1, and TET2, increase in frequency with age in myeloid neoplasms as recently shown for healthy individuals. Patients and methods: We investigated 1639 patients (pts) between 20 and 93 years (yrs), 578 with de novo AML (median age: 63 yrs), 846 with MDS (median age: 73 yrs), and 215 with CMML (median age: 75 yrs). In all cases, we followed the diagnostic criteria of the WHO classification based on morphology. All patients have also been investigated by cytogenetics and for disease-oriented molecular mutations (15-36 genes/pt: 15 in AML, 36 in MDS, and 21 in CMML). Analyses were performed by melting curve analysis, gene scan, Sanger sequencing, or next generation sequencing. Results: In total we detected 3089 mutations (range: 0-9/pt) spread over all except for seven analyzed genes. Grouping the entity-specific cohorts by age of the patients into decades revealed a steady increase of the prevalence of mutations with age in MDS (at least one mut/pt, 25% in 20-29 to 93% in 〉 80 yrs; p 〈 0.001), less prominent in AML (77% in 20-29 to 100% in 〉 80 yrs, p=0.007), but not in CMML (96%-100% in all decades). However, the number of mutations per patient increased according to age in all three entities, significantly in MDS (p 〈 0.001) and AML (p 〈 0.001). Considering AML patients separated into three cytogenetic classes (Grimwade, Blood 2010) resulted in the same findings for the intermediate risk (p=0.012) and adverse risk group (p 〈 0.001), while the good risk group showed no change in mutation numbers over decades (median: 1 mut/pt, range 0-3). This indicates that in good risk AML (PML-RARA, CBFB-MYH11, RUNX1 -RUNX1T1) only very few additional mutations are needed for AML initiation. In contrast, an age-dependent increasing incidence of gene mutations is specific in normal karyotype and in adverse cytogenetics. We next focused on specific gene mutations according to age 〈 60 vs ≥60 yrs within all three entities. In addition, AML patients where again subgrouped by cytogenetics. In AML good and adverse risk groups no age-dependent significant increase of specific gene mutations occurred, while in the intermediate risk group mutations in ASXL1 (3/160 vs 32/114, p 〈 0.001), MLL-PTD (3/160 vs 17/214, p=0.01), RUNX1 (32/160 vs 20/214, p=0.001), and TET2 (4/159 vs 26/214, p=0.001) were significantly more frequent at higher age. In contrast, NRAS mutations appeared more often in younger AML patients (32/160 vs 20/214, p=0.004). In MDS, mutations in SF3B1 (27/115 vs 253/731, p=0.019), SRSF2 (10/115 vs 133/730, p=0.011), TET2 (10/115 vs 250/731, p 〈 0.001), and TP53 (2/115 vs 50/731, p=0.035) were more frequently observed in older patients. In CMML only TET2 mutations occurred more often in older patients (5/12 vs 135/190, p=0.026). Focusing on the genes recently described to be mutated in healthy individuals showed that all of the above mentioned mutations found in myeloid neoplasms (except MLL-PTD and RUNX1) are comprised in the 10 most frequently mutated genes in the healthy aging population. However, the fact that the frequencies of these mutations are not age-dependent in some entities, e.g. ASXL1 only age-dependent in AML but not in CMML and MDS, might indicate different roles of these mutations in the pathogenesis, i.e. driver mutations independent of age, as well as their contribution to accumulation of mutations and onset of a myeloid neoplasm. Conclusions: 1) The number of mutations significantly increase with age in AML and MDS and non-significantly in CMML. 2) Several genes show age-dependent frequencies, which differ between AML, MDS, and CMML and are also related to the cytogenetic background. 3) Based on molecular mutations healthy aging and myeloid neoplasms are neighbouring scenarios. Disclosures Meggendorfer: MLL Munich Leukemia Laboratory: Employment. Kern:MLL Munich Leukemia Laboratory: Employment, Equity Ownership. Perglerová:MLL2 s.r.o.: Employment. Schnittger:MLL Munich Leukemia Laboratory: Employment, Equity Ownership. Haferlach:MLL Munich Leukemia Laboratory: Employment, Equity Ownership. Haferlach:MLL Munich Leukemia Laboratory: Employment, Equity Ownership.
    Type of Medium: Online Resource
    ISSN: 0006-4971 , 1528-0020
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    Language: English
    Publisher: American Society of Hematology
    Publication Date: 2015
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  • 10
    In: Blood, American Society of Hematology, Vol. 134, No. Supplement_1 ( 2019-11-13), p. 2735-2735
    Abstract: Background: AML with myelodysplasia related changes (AML-MRC) is as specific WHO category with poor prognosis. It requires ≥ 20% of blasts, and (1) the history of MDS or MDS/MPN, or (2) "MDS related cytogenetic abnormalities", or (3) multilineage dysplasia. Drugs such as Vyxeos® have been approved by FDA and EMA only for treatment of t-AML or AML-MRC. However, counting blasts or grading dysplasia in clinical routine is hampered by limited reproducibility due to different levels of expertise and small phenotypic alterations, challenging upfront treatment decisions. Cytogenetics is not available in all cases and has 5-10 days of turnaround time (TAT). In contrast, next-generation sequencing (NGS) panels for AML are now broadly available at faster TAT. Aim: (1) Use machine learning to define a molecular AML-MRC signature; (2) compare the impact of conventional WHO definitions and molecular factors on classification and outcome. Patients and Methods: Gold standard routine AML diagnosis was performed on 739 cases. Overall survival (OS) data was available for 619 patients. Amplification-free whole genome sequencing was performed on HiSeqX and NovaSeq with median coverage of 106x. Gender-matched reference DNA was used for unmatched normal variant calling with Strelka2. Pindel was used for FLT3-ITD. For variant classification, we applied a GnomAD cutoff of 0.0005 and filtered on protein-truncating and (likely) pathogenic variants from databases. Results: According to WHO standards 165/739 (22%) cases fulfilled MRC criteria (96 male; 69 female). The non-MRC cohort (n=574) represents a heterogeneous AML population incl. the WHO defined recurrent cytogenetic abnormalities or t-AML (301 male, 273 female). Median age was higher in the MRC cohort (73 [22-90] vs. 64 [18- 93] years, p 〈 .001) and OS was significantly shorter (median 6 vs. 23 months, p 〈 .001). Mutation analysis was limited to 73 frequently mutated genes, in order to allow application of our model on prospective diagnostic cases analyzed by common routine panels. In the MRC group, up to seven mutations were found per patient and an average of 2.7 genes per patient were mutated. The most frequently mutated gene in AML-MRC was TP53 (62/165, 38%) as expected by the inclusion of complex karyotypes. TP53 mutations were associated with shorter OS in the MRC cohort (median: 3 vs. 11 months, p =.001). We used machine learning (ML) approaches to identify with LASSO regression and 10-fold cross-validation the most informative features to distinguish between MRC and patients without MRC. The dataset was randomly divided into a training (90%) and test set (10%) and the procedure was repeated 500 times to cover all the variance in the dataset and to extract the most reliable factors. Factors with the highest weight on AML-MRC prediction were mutations in TP53, RUNX1, SETBP1, splicing factors and epigenetic regulators, and absence of mutations in NPM1, CEBPA and others (s. figure). In order to allow our model to be used in a routine diagnostic workflow, we also used the genes identified by ML but classified mutations by a simpler point system (≥2 points as cutoff for MRC, s. figure). This allowed us to identify 83% (137/165 by ML) and 70% (116/165 by points) of cases currently defined as MRC solely by molecular genetics. Including cytogenetic data and patient's history in an informed genetic model results in 99% (164/165 by ML) and 96% (159/165 by points) of true positive MRC definition. However, the molecular models classified 112 (ML) and 80 (points) of the 574 non-MRC cases, as being AML-MRC. Even after excluding AML with recurrent cytogenetic abnormalities and t-AML, 14% (82/574 DL) or 11% (63/574 points) show a MRC-like molecular profile. In both models MRC-like patients had dismal outcome analogous to AML-MRC (median OS: 6 months for both) and significantly inferior to remaining non-MRC patients (6 vs. 35 months, s. figure). Conclusions: (1) Using patients' history and genetic information instead of morphology allow to identify 96-99% of AML-MRC as defined in WHO today. In the future, extended NGS panels (e.g. incl. fusion gene detection) will allow fast and standardized AML-MRC classification even without chromosome banding analysis. (2) The molecular MRC-like pattern can be found in 〉 10% of patients currently not classified as AML-MRC but with comparably poor OS. This suggests considering MRC treatment strategies for patients with MRC-like molecular profile. Disclosures Baer: MLL Munich Leukemia Laboratory: Employment. Walter:MLL Munich Leukemia Laboratory: Employment. Stengel:MLL Munich Leukemia Laboratory: Employment. Hutter:MLL Munich Leukemia Laboratory: Employment. Meggendorfer:MLL Munich Leukemia Laboratory: Employment. Kern:MLL Munich Leukemia Laboratory: Employment, Equity Ownership. Haferlach:MLL Munich Leukemia Laboratory: Employment, Equity Ownership. Haferlach:MLL Munich Leukemia Laboratory: Employment, Equity Ownership.
    Type of Medium: Online Resource
    ISSN: 0006-4971 , 1528-0020
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    Language: English
    Publisher: American Society of Hematology
    Publication Date: 2019
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