Comparison Of Mutation Patterns Between Diagnosis and Relapse In 556 Adult Patients With AML Shows High Variability Of Stability

Abstract Background In acute myeloid leukemia (AML) molecular mutations are becoming increasingly important as markers for classification, risk stratification and disease monitoring. Frequencies and prognostic impact of most of the currently known mutations have been widely studied. In contrast, the stability during disease evolution and the role of single markers at relapse are less clear. Aim 1) To compare the patterns of molecular mutations between diagnosis and relapse. 2) To analyze the impact of single mutations on time to relapse (TTR). Patients and Methods We investigated paired diagnostic and relapse samples in a cohort of 556 adult AML cases that were selected based on confirmed relapse with available samples from both time points (483 de novo, 33 t-AML, 40 s-AML). The cohort comprized 255 females and 301 males; median age: 63.0 years (range: 18.6-85.2 years). In total, 5,726 paired analyses were performed (mean: 10.3/pt, range: 2-21). Besides analyses for fusion genes (n=114) the following genes were analyzed in paired samples for mutations in respective numbers: ASXL1: n=464, CBL: n=99, CEBPA: n=374, DNMT3A: n=244, FLT3-ITD: n=534, FLT3-TKD: n=461, IDH1: n=469, IDH2: n=418, KIT: n=34, KRAS: n=49, MLL-PTD: n=165, NPM1: n=343, NRAS: n=105, RUNX1: n=356, TET2: n=243, WT1: n=153, others: n=1,101. Mutations were analyzed by amplicon deep-sequencing, direct Sanger sequencing, gene scan, conventional PCR, quantitative real time PCR or melting curve analyses. In addition, chromosome banding analysis data was available in 552 cases. Results 629 relapses were detected in the 556 patients (pts). 67 pts had a second and 6 even a third relapse. At diagnosis the subtypes according to cytogenetics were as follows: PML-RARA (n=10), RUNX1-RUNX1T1 (n=24), CBFB-MYH11 (n=23), MLL-translocations (n=30), DEK-CAN (n=3), other recurrent translocations (n=14), complex karyotype (n=30), other aberrations (n=107), normal karyotype (NK, n=311). In 515/556 (92.6%) pts at least one mutation (mut) was detected at diagnosis (mean: 2.3; range:1-5). In detail, the most frequent markers were mut in: NPM1: n=233, FLT3-ITD: n=217, fusion genes: n=114, DNMT3A: n=101, RUNX1: n=98, TET2: n=81, FLT3-TKD: n=58, ASXL1: n=54, IDH2R140: n=46, MLL-PTD: n=44, WT1: n=42, TP53: n=26, biallelic CEBPA(bi): n=28, monoallelic CEBPA(mono): n=23. At relapse a similar incidence of 88.6% (558/630) mutated pts (mean: 2.0: range 1-6) was detected. However, the mutational pattern changed at relapse in 381/629 (60.6%) of the pts. On the marker level a change was seen for 309 (24.5%) of the mut, with gain of 142/1,263 new mut (11.3%) and a loss of 167 (13.2%) mut that were detectable at diagnosis. Different degrees of stability were observed. Compared to all other markers a stable pattern was found for CEBPAbi: p=0.025; NPM1: p<0.001; MLL-PTD: p=0.006; and fusion genes: p<0.001. This is supporting the respective definition of entity defining mut in the WHO classification. Instead, a low stability (for gain and/or loss) compared to all others was seen for CEBPAmono: p=0.002, FLT3-ITD: p<0.001, FLT3-TKD: <0.001, NRAS: p<0.001, TP53: p<0.001 (only for gain), WT1: p<0.001. This is in accordance with the concept of typical “secondary” mutations, leading to acceleration of the disease. An intermediate stability was detected for TET2, DNMT3A, RUNX1, ASXL1,IDH2R140 (see figure). Of note, of 200 FLT3-ITD positive pts that retained an FLT3-ITD at relapse, only 6 (3%) were stable with respect to mutational load whereas 134 (67%) showed an increase of the FLT3-ITD/wildtype load, and 60 (30%) a decrease showing a further quality of genetic instability. Between the various disease entity defining groups there were no relevant differences in TTR. In contrast, an impact on shorter TTR was seen for mutations in DNMT3A (median TTR: 8.7 vs 12.1 months (m), p=0.058), FLT3-ITD (7.6 vs 12.2 m, p<0.001), RUNX1mut (10.1 vs 12.8 m, p=0.038) and TET2mut (9.9 vs 10.9 m, p=0.049). In the normal karyotype group an effect was only seen for FLT3-ITD (7.3 vs 13.6, p<0.001) and TET2mut (9.9 vs 12.3 m, p=0.025). Conclusions 1) Genetic alterations in AML can be subdivided into stable, intermediate and unstable markers. Entity defining markers according to WHO (fusion genes, NPM1mut, CEBPAbi) are stable between diagnosis and relapse. 2) A significant negative impact on TTR was shown only for secondary mutations (FLT3-ITD, TET2mut, DNMT3Amut and RUNX1 mut). Disclosures: Schnittger: MLL Munich Leukemia Laboratory: Employment, Equity Ownership. Nadarajah:MLL Munich Leukemia Laboratory: Employment. Alpermann:MLL Munich Leukemia Laboratory: Employment. Eder:MLL Munich Leukemia Laboratory: Employment. Kohlmann:MLL Munich Leukemia Laboratory: Employment. Kuznia:MLL Munich Leukemia Laboratory: Employment. Weissmann:MLL Munich Leukemia Laboratory: Employment. Fasan:MLL Munich Leukemia Laboratory: Employment. Weber:MLL Munich Leukemia Laboratory: Employment. Albuquerque:MLL Munich Leukemia Laboratory: Employment. Jeromin:MLL Munich Leukemia Laboratory: Employment. Meggendorfer:MLL Munich Leukemia Laboratory: Employment. Dicker: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.

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In CLL with Normal Karyotype By Conventional and Genomic Array Karyotyping the Prognostic Impact of an Unmutated IGHV Status Is Stronger Than the Impact of Gene Mutations

Blood ◽

10.1182/blood.v128.22.4357.4357 ◽

2016 ◽

Vol 128 (22) ◽

pp. 4357-4357 ◽

Cited By ~ 1

Author(s):

Calogero Vetro ◽

Torsten Haferlach ◽

Manja Meggendorfer ◽

Sabine Jeromin ◽

Constance Regina Baer ◽

...

Keyword(s):

Gene Mutation ◽

Mutation Rate ◽

Gene Mutations ◽

Normal Karyotype ◽

Prognostic Impact ◽

Employment Equity ◽

Mutation Status ◽

Genomic Array ◽

Equity Ownership ◽

The Impact

Abstract Background: In 15-20% of CLL cases no aberrations are detected by chromosome banding analysis (CBA) and FISH due to limited resolution, lack of evaluable metaphases or presence of aberrations in loci not covered by standard-panel FISH probes. As reported in our previous study (Haferlach C. et al., ASH 2015, abs ID#79545), genomic arrays (GA) detected abnormalities in almost 20% of cases classified as normal by CBA and FISH and these showed an impact on time to first treatment (TTT) (Vetro C. et al., EHA 2016, abs ID# E1069). The CLL subgroup without abnormalities in CBA, FISH, and GA has not been characterised in detail, so far. Aims: 1) to describe CLL without abnormalities by CBA/FISH/GA by evaluating an extended gene panel, the IGHV mutation status and the B-cell receptor (BCR) stereotypy; 2) to determine prognostic impact of these factors. Patients and Methods: CLL diagnosis was based on cytomorphology and immunophenotyping according to standard guidelines. From a cohort of 1190 patients at diagnosis, 133 (11%) were selected based on normal karyotype by CBA, no abnormalities by interphase FISH with probes for 17p13 (TP53), 13q14 (D13S25, D13S319, DLEU), 11q22 (ATM), centromeric region of chromosome 12 and t(11;14)(q13;q32) (IGH-CCND1) and no abnormalities by GA (SurePrint G3 ISCA CGH+SNP Microarray, Agilent, Waldbronn, Germany). IGHV mutation status and BCR stereotypy were determined according to Agathangelidis et al., Blood 2012, and DNA sequencing was performed for the following genes: ATM; SF3B1; TP53; KLHL6; KRAS; MYD88; NOTCH1; NRAS; POT1; FBXW7; HIST1H1E; XPO1; ITPKB; MAPK1; BIRC3; BRAF; DDX3X; EGR2; RIPK1; RPS15; CND2. Results: Median age was 66 years (range: 33-83). Median follow-up was 5.6 years, 33 patients (25%) received treatment since genetic analyses. 10-year overall survival (OS) was 76% and median TTT was 9.2 years. Mutations were observed in 53 patients (40%): SF3B1 (n=17; 13%); NOTCH1 (n=10; 8%); KLHL6 (n=6; 5%); TP53 (n=6; 5%); ATM (n=5; 4%); XPO1 (n=4; 3%); FBXW7 (n=3; 2%); MYD88 (n=3; 2%); DDX3X (n=2; 2%); POT1 (n=2; 1.5%); ITPKB (n=1; 1%); KRAS (n=1; 1%); NRAS (n=1; 1%); and no mutation in RPS15, CCND2, MAPK1, EGR2, BRAF, HIST1H1E, RIPK1, BIRC3. 6 patients had 2 simultaneous gene mutations and 1 patient had 3 (i.e. NOTCH1, ATM and TP53). A mutated IGHV status (IGHV-M) was present in 100 patients (75%) and an unmutated IGHV status (IGHV-U) in 33 patients (25%). IGHV-U was related to both the occurrence of any gene mutation (p<0.001) and the number of gene mutations (p=0.001). NOTCH1 was mutated in 7 out of the 33 IGHV-U patients (21%), but only in 3 out of 99 IGHV-M patients (3%) (p=0.001). XPO1 mutation occurred in 4 IGHV-U patients (12%) and none out of IGHV-M (p<0.001). Two IGHV-U patients showed POT1 mutation (6%), but no IGHV-M case (p=0.014). 9 patients out of 133 (7%) showed BCR-stereotypy. 2 were in cluster CLL#1 (both showing NOTCH1 mutation), 2 in cluster CLL#2 (both of them with SF3B1 mutation), 2 in CLL#4, 1 in CLL#8 (showing NOTCH1 and XPO1 mutations), 1 in CLL#201 (with KLHL6 mutation) and 1 in CLL#202 (with mutations in ATM, TP53 and NOTCH1 genes). In Kaplan-Meier analysis, IGHV-M patients did not reach a median TTT, while IGHV-U had a median of 5.1 years (p<0.001). Stereotypy rate was too low for reliable statistics. At univariate analysis, TTT was only influenced by: IGHV-U (relative risk (RR): 3.9, p<0.001), TP53 mutation (RR: 3.7, p=0.03), % CLL cells (RR: 1.2 per 10% increase, p=0.013), and number of mutations (RR: 1.8 per each mutation, p=0.031). Multivariate Cox regression analysis showed an independent role for IGHV-U status (RR: 3.3, p=0.002) and % CLL cells (RR: 1.2 per 10% increase, p=0.038) Only age showed an impact on OS (RR: 1.2 per decade, p<0.001). Conclusions: 1. The CLL subset without any genomic event by CBA/FISH/genomic array is characterized by very low frequency of IGHV-U status; 2. IGHV-U subgroup showed higher gene mutation rate compared to IGHV-M subgroup, in particular higher NOTCH1, XPO1 and POT1 mutation rate; 3. BCR stereotypy is less frequent than in CLL in general. 4. IGHV-U, as well as the higher disease burden (i.e. % CLL cells), has an independent negative impact on TTT. 5. Requirement for treatment is low and prognosis very favorable in CLL without any genomic event by CBA/FISH/genomic array and a mutated IGHV status. Disclosures Vetro: MLL Munich Leukemia Laboratory: Employment. Haferlach:MLL Munich Leukemia Laboratory: Employment, Equity Ownership. Meggendorfer:MLL Munich Leukemia Laboratory: Employment. Jeromin:MLL Munich Leukemia Laboratory: Employment. Baer:MLL Munich Leukemia Laboratory: Employment. Nadarajah:MLL Munich Leukemia Laboratory: Employment. Kern:MLL Munich Leukemia Laboratory: Employment, Equity Ownership. Haferlach:MLL Munich Leukemia Laboratory: Employment, Equity Ownership.

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WT1 Mutations Are Secondary Events In AML and Show Varying Frequencies Within Genetic Subgroups and Different Impact On Prognosis

Blood ◽

10.1182/blood.v122.21.2542.2542 ◽

2013 ◽

Vol 122 (21) ◽

pp. 2542-2542

Author(s):

Susanne Schnittger ◽

Christiane Eder ◽

Tamara Alpermann ◽

Frank Dicker ◽

Madlen Ulke ◽

...

Keyword(s):

Multivariate Analysis ◽

Median Time ◽

Univariate Analysis ◽

Normal Karyotype ◽

Adverse Impact ◽

Prognostic Impact ◽

Employment Equity ◽

Genetic Aberrations ◽

Equity Ownership ◽

The Impact

Abstract Background Mutations (mut) in the WT1 gene belong to the first genetic aberrations described in AML. In contrast to recurrent fusion genes or NPM1mut WT1mut do not seem to be disease defining. Also in contrast to other mutations in AML, for most of which a certain prognostic value has been established, the impact of WT1mut still is discussed controversially. Aim Analyze the frequency and prognostic impact of WT1 mutations in comparison to other genetic aberrations. Patients and Methods 3,157 unselected AML patients (pts) were analyzed (de novo: n=2,699, s-AML: n=234, t-AML: n=224). 1,708 pts were male and 1,449 female. Median age was 67.1 years (y) (range: 17.8-100.4 y) with 1,108 pts <60 y and 2,049 ≥60 y. The mutational hot spot regions of WT1 (exons 7 and 9) were analyzed by direct Sanger sequencing with a sensitivity of ∼10%. Karyotype and WT1 mutation status was available in all cases. Other mutations were assessed in subsets: ASXL1 (n=1,951), CEBPA (n=2,670), DNMT3A (n=1,293), FLT3-ITD (n=3,149), FLT3-TKD (n=3,004), IDH1R132 (n=2,431), IDH2R140 (n=2,380), IDH2R172 (n=2,412), KRAS (n=1,409), NRAS (n=1,780), NPM1 (n=3,003), MLL-PTD (n=2,961), RUNX1 (n=2,390), TET2 (n=1,016) and TP53 (n=1,215). Results A total of 189 WT1 mutations were detected (exon 7: n=151, exon 9: n=38). The total frequency of WT1mut pts was 175/3,157 (5.5%). 11 pts were double to quadruple mutated. The frequency was heterogeneous with respect to AML subtypes. Compared to all others, significantly higher frequencies were detected in biallelic CEBPAmut (15/110; 13.6%; p=0.001), followed by t(15;17)/PML-RARA (18/164; 11.0%, p=0.004), and FLT3-ITD (58/682; 8.5%, p<0.001). Lower frequencies were observed in DNMT3Amut (18/412; 4.3%, p=0.014, ASXL1mut (6/355; 1.7%, p<0.001), IDH2R140 (5/286; 1.7%, p=0.001), and IDH1R132 (2/222; 0.9%, p<0.001). WT1mut were never detected in pts with complex karyotypes (0/175; p=0.047) or those with IDH2R172 (0/68; p=0.020). Further, WT1mut were more frequent in females (95/1,449, 6.6%) than in males (80/1,708, 4.7%) (p=0.014) and in younger pts (<60 y: 102/1,108, 9.2% vs ≥ 60 y: 73/2,049, 3.6%; p<0.001). Median age of pts with WT1mut was 55.5 y compared to 63.6 in WT1wt (p<0.001). Further, WT1mut were associated with lower platelet count (58.4 vs 84.7 x109/L; p<0.001) and lower hemoglobin level (8.8 vs 9.3 g/dL, p=0.001). There was no association to the history of the disease or white blood cell count. Stability of WT1mut was analyzed in 35 paired diagnostic and relapse samples (median time of relapse after diagnoses: 11.1 months (m); range: 2.6-60.6 m). In 23 cases (65.7%) the WT1mut was retained at relapse and in 12 cases (34.3%) it was lost. In 5 cases a sample at 2nd relapse was available (median time from 1st relapse: 8.5 m, range: 6.0-18.0 m). 3 of these cases retained and 2 lost the WT1mut. Analysis of prognostic impact was restricted to intensively treated pts (n=1,936, WT1mut: n=132, 6.8%). In the total cohort, there was no impact of WT1mut on prognosis. In pts ≥60 y there was a trend to shorter event free survival (EFS) for WT1mut (9.3 vs 12.3 m, p=0.052). In the two prognostically favorable groups with high WT1mut incidences (biallelic CEBPAmut and PML-RARA) no effect on outcome was seen. When restricting the analysis to normal karyotype AML (WT1mut: n=85, WT1wt: n=1,093) WT1mut pts had shorter EFS (10.8 vs 17.9 m, p=0.008). This was true for the younger (12.2 vs 29.0 m, p=0.007) as well as for the older pts (9.3 vs 13.9 m, p=0.016). In a multivariate analysis all parameters with significant impact on EFS in univariate analysis were included: age (p<0.001, HR: 1.24), ASXL1mut (p<0.001, HR: 1.36), FLT3-ITD (p<0.001, HR: 1.55), NPM1mut/FLT3-ITD wild-type (p<0.001, HR:1.55), RUNX1 (p=0.019, HR: 1.23, and WT1mut (p=0.009, HR: 1.64). In multivariate analysis WT1mut was found to have independent adverse impact on EFS (p=0.002, HR: 1.64) besides FLT3-ITD status (p<0.001, HR: 1.71) and age (p<0.001, HR: 1.28). Conclusions WT1 mutations are 1) more frequent in females and younger AML, 2) more frequent in t(15;17)/PML-RARA, biallelic CEBPAmut, FLT3-ITD mutated AML, and nearly mutually exclusive of ASXL1, IDH1, IDH2 and complex karyotype. 3) The distribution pattern in different genetic subtypes and the instability during follow-up as shown by paired sample analyses clearly emphasize a secondary character of this mutation. 4) For AML with normal karyotype an independent adverse impact of WT1mut on EFS was shown. Disclosures: Schnittger: MLL Munich Leukemia Laboratory: Employment, Equity Ownership. Eder:MLL Munich Leukemia Laboratory: Employment. Alpermann:MLL Munich Leukemia Laboratory: Employment. Dicker:MLL Munich Leukemia Laboratory: Employment. Ulke:MLL Munich Leukemia Laboratory: Employment. Kohlmann:MLL Munich Leukemia Laboratory: Employment. Kuznia: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.

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IDH Mutations Can Be Detected In 28.7% of All Normal Karyotype AML and Have Unfavourable Impact on the NPM1+/FLT3-ITD- Genotype

Blood ◽

10.1182/blood.v116.21.102.102 ◽

2010 ◽

Vol 116 (21) ◽

pp. 102-102

Author(s):

Susanne Schnittger ◽

Claudia Haferlach ◽

Tamara Alpermann ◽

Wolfgang Kern ◽

Torsten Haferlach

Keyword(s):

De Novo ◽

Hot Spot ◽

Normal Karyotype ◽

Prognostic Impact ◽

Employment Equity ◽

Therapeutic Decisions ◽

Idh Mutations ◽

Equity Ownership ◽

De Novo Aml ◽

The Impact

Abstract Abstract 102 Introduction: Mutations in IDH1 and IHD2 have recently been shown to play an important role in AML. As they code for enzymes from the citric acid cycle mutations within these genes from the mechanistical point of view are a totally new kind of mutation associated with AML. In IDH1 one mutational hot spot (amino acid R132) and in IDH2 two hotspots (R140 and R172) have been reported. We aimed at further delineating the impact of IDH1 and IDH2 mutations in AML and analyzed the interaction with other mutations in normal karyotype (NK) AML. Methods: 526 AML patients were selected according to normal karyotype and availability of mutational status for FLT3-ITD, NPM1 and MLL-PTD. Further mutation analyses were available in subgroups of the cohort (FLT3-TKD: n=318, CEBPA: n=369, RUNX1: n=174, NRAS: n=220). Female/male ratio was 283/243 and age ranged from 20.0–90.1 years (median, 66.9 years). 435 had de novo AML (82.6%), 71 AML following MDS (s-AML,13.5%) and 20 AML after previous treatment of other malignancies (t-AML, 3.8%). The respective base exchanges in R132, R140, and R172 were analysed by a melting curve assay with subsequent sequencing of the positive samples. Results: Overall, in 151 pts (28.7%) IDH mutations (IDHmut) were detected. In detail, 68 mutations (12.9% of all cases) were detected in IDH1 (R131C: n=35, R131L: n=17, R131H: n=7, R131G: n=6, R131S: n=3) and 83 mutations (15.8%) in IDH2 (R140Q: n=72, R140L: n=2, R140W: n=1, N141G: n=1, R174K: n=7). IDH1mut and IDH2mut were mutually exclusive in this cohort. IDH1mut were more frequent in females (18.2% vs 8.6 % in males, p=0.001), whereas there was no sex difference for IDH2. According to history IDH1 was equally distributed in de novo AML, s-AML and t-AML whereas IDH2 was more frequent in de novo compared to s- and t-AML (19.6% vs. 7.6 vs 11.8%, p=0.048). According to FAB the most prevalent subtype was FAB M1 with IDHmut in 23.2% compared to 9.8% in all other FAB (in detail: IDH1: 44.8% vs. 23.9%, IDH2: 27.0% vs. 15.1%; p<0.001, for both). IDH1 was underrepresented in M4 (4.9% vs. 15.0 % in all other subtypes, p=0.004), whereas the distribution of IHD2 was not different in M4 vs. all others. The immunophenotype (n= 297) of IDHmut cases tended to be more immature and featured a lower expression of monocytic markers. The analyzed 78 IDHmut cases, as compared to 219 IDHwt cases, showed a significantly higher expression of MPO and CD117 while CD116, CD11b, CD14, CD15, CD36. CD56, CD64, CD65 and CD7 were lower expressed. Age, WBC count, and platelet count were not different between IDH1, IDH2 and IDHwt cases. IDH mutations are not mutually exclusive of other mutations. However, the frequency of CEBPAmut in IDHmut compared to IDHwt was decreased (7.7% vs. 13.7, p=0.001) (IDH1: 0% vs 11.7%, p=0.022 and IDH2: 7.7% vs 13.4%, p=0.053). MLL-PTD was more frequent in IDHmut vs. IDHwt (44.7 vs. 5.8%, p=0.039), however, this is restricted to IDH1mut vs. IDH1wt (26.3 vs. 6.3%, p=0.018). RUNX1mut are distributed equally in IDH2mut and IDH2wt (20.0% vs 27.3%) but are underrepresented in IDH1mut compared to IDH1wt (2.2% vs. 28.7%, p=0.068). FLT3-ITDs are equally distributed between IDHmut and IDHwt, however, those IDH1mut with FLT3-ITD have lower FLT3-ITD/FLT3wt ratios compared to FLT3-ITD+ IDH1wt cases (mean: 0.16 vs. 0.72; p=0.005). All other mutations were distributed equally in IDHmut compared to IDHwt. For survival analysis only cases with de novo AML <65 years were included (n=164, IDHmut: n=37, n=, IDHwt: 127). In the total analysis there was no effect on overall survival or event free survival (EFS). However there was a trend for shorter EFS of the IDHmut vs. IDHwt (median: 439 days vs. not reached, p=0.080) in cases with NPM1+/FLT3-ITD- genotype. For IDH2 there was a significant adverse effect in the NPM1+/FLT3-ITD- group (median EFS: 397 vs. 679 days, p=0.045). Summary: IDH mutations belong to the most frequent mutations in NK AML and can occur together with all other known mutations. There is a high preponderance for the FAB M1 subtype and a more immature immunophenotype for both IDH mutations and a strong female preponderance for IDH1. In addition, an adverse prognostic impact of IDH mutations was shown for the NPM1+/FLT3-ITD- genotype. Further analyses should focus on the definition of the role and place of IDH mutations for therapeutic decisions in patients with AML. Disclosures: Schnittger: MLL Munich Leukemia Laboratory: Employment, Equity Ownership. Haferlach:MLL Munich Leukemia Laboratory: Employment, Equity Ownership. Alpermann:MLL Munich Leukemia Laboratory: Employment. Kern:MLL Munich Leukemia Laboratory: Employment, Equity Ownership. Haferlach:MLL Munich Leukemia Laboratory: Employment, Equity Ownership.

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The Prognostic Impact of High EVI1 expression In AML Is Due to Its Close Correlation to Rearrangements Involving EVI1 or MLL, which Are Cytogenetically Cryptic In a Subset of Patients: a Study on 332 Cases.

Blood ◽

10.1182/blood.v116.21.1676.1676 ◽

2010 ◽

Vol 116 (21) ◽

pp. 1676-1676

Author(s):

Claudia Haferlach ◽

Vera Grossmann ◽

Melanie Zenger ◽

Tamara Alpermann ◽

Alexander Kohlmann ◽

...

Keyword(s):

Chromosome Banding ◽

Normal Karyotype ◽

Fish Analysis ◽

Prognostic Impact ◽

Employment Equity ◽

Npm1 Mutation ◽

Banding Analysis ◽

Chromosome Banding Analysis ◽

Equity Ownership ◽

The Impact

Abstract Abstract 1676 Introduction: High EVI1 expression has been proposed as a negative prognostic factor in AML. An association between high EVI1 expression and distinct cytogenetic subgroups, such as 3q26-rearrangements, MLL-rearrangements and -7/7q- have been reported. Both 3q26- and MLL-rearrangements can be difficult to detect by chromosome banding analyses or may even be cytogenetically cryptic in a subset of patients due to limited resolution. Therefore, only studies using FISH for the detection of cryptic EVI1- or MLL-rearrangements can clarify their frequencies in AML with elevated EVI1 expression. Methods/Patients:: The study cohort was composed of 332 AML cases with a) normal karyotype (NK) (n=211), b) -7/7q- (n=77), and for comparison c) 3q26-rearrangements (n=38), and d) MLL-rearrangement (n=6). In all cases EVI1 expression was investigated using quantitative PCR calculating a % EVI1/ABL1 expression. In all cases FISH for EVI1 rearrangement was performed in addition to chromosome banding analysis. Cases with high EVI1 expression were also analyzed for MLL rearrangements by FISH. Results: In the total cohort, EVI1 expression varied between 0 and 1614 (median: 21.1). The highest EVI1 expression was measured in cases with cytogenetically identified 3q26-rearrangements (range: 6.1–566.4; median: 81.9) and in AML with MLL-rearrangements (range: 46.7–831; median: 239). The EVI1 expression was significantly lower in AML with NK (range: 0–1614; median: 0.5, p<0.001) and AML with -7/7q- (range: 0.03–199; mean: 34.5; median: 10.7, p<0.001). In the subgroup of cases with NK 4 MLL-rearrangements (1.9%) were detected by FISH and subsequently verified by fusion gene specific PCR. In addition, 4 cases with cryptic EVI1-rearrangements (1.9%) were identified by FISH analysis. Further genetic analysis revealed that these were due to t(3;8)(q26;q24) (n=2) and t(3;21)(q26;q11) (n=1). In one case, the EVI1-rearrangement could not be further analyzed due to lack of material. In the -7/7q- cohort 14/77 cases (18.2%) with cytogenetically cryptic EVI1 rearrangement including 3 novel recurrent abnormalities were detected: t(3;21)(q26;q11) (n=3), inv(3)(p24q26) (n=4) and t(3;8)(q26;q24) (n=2). In 5 cases FISH analysis revealed that the 7q- was not caused by an interstitial deletion but due to an unbalanced rearrangement between chromosomes 7 and 3: der(7)t(3;7)(q26;q21). In these 5 cases high-resolution SNP microarray were performed and revealed breakpoints in the CDK6 gene and centromeric of the EVI1 gene. Further mutation screening revealed that none of the cases with EVI1- or MLL-rearrangement harboured mutations in NPM1 or CEPBA. In 254 cases clinical follow-up data was available. Different cut-off levels of EVI1 expression were tested, and a cut-off at 30% EVI1/ABL1 expression was the lowest level that had a significant impact on outcome. Separating the cohort at this cut-off into high EVI1 (n=67) and low EVI1 expressors (n=187) showed a shorter EFS in patients with high EVI1-expression (p=0.001; relative risk (RR)=1.87, median EFS 6.2 vs 15.0 months (mo)), while no impact on OS was observed. When the same analyses were performed with respect to EVI1-rearrangements we observed both a significantly shorter EFS in cases with EVI1-rearrangement (n=39) vs all others (n=215) (p=0.001; RR=2.03, median EFS 4.6 vs 15.0 mo) and a significantly shorter OS (p=0.026; RR=1.73, median OS 10.1 vs 26.3 mo). Analyzing the impact of high EVI1 expression separately in the cohort without EVI1 rearrangement revealed no impact of EVI1 expression on EFS. Conclusions: The negative prognostic impact of high EVI1 expression is strongly associated with EVI1- or MLL-rearrangements and is absent in AML without EVI1- and MLL-rearrangement. Applying FISH in addition to chromosome banding analysis we identified cryptic rearrangements in 3.8% of AML with normal karyotype and in 18.2% of AML with -7/7q-, including 3 novel recurrent cytogenetically cryptic EVI1-rearrangements. This data supports the routine performance of FISH screening for EVI1- and MLL-rearrangements in patients with normal karyotype or 7q-/-7 and without NPM1 mutation and CEPBA mutation to assign patients to the correct biologic entity. The postulated independent prognostic impact of EVI1 expression should be tested further including this laboratory workflow as these parameters may have important impact on prognosis and future treatment strategies. Disclosures: Haferlach: MLL Munich Leukemia Laboratory: Employment, Equity Ownership. Grossmann:MLL Munich Leukemia Laboratory: Employment. Zenger:MLL Munich Leukemia Laboratory: Employment. Kohlmann: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.

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Specific Molecular Mutations with Prognostic Relevance in AML with Normal Karyotype Are Also Associated with Outcome in AML with Aberrant Karyotype: A Study on 1981 Cases,

Blood ◽

10.1182/blood.v118.21.3517.3517 ◽

2011 ◽

Vol 118 (21) ◽

pp. 3517-3517

Author(s):

Claudia Haferlach ◽

Torsten Haferlach ◽

Tamara Alpermann ◽

Wolfgang Kern ◽

Susanne Schnittger

Keyword(s):

Important Implication ◽

Mutation Screening ◽

Normal Karyotype ◽

Prognostic Impact ◽

Employment Equity ◽

Equity Ownership ◽

The Impact ◽

Length Mutations ◽

Tandem Duplications

Abstract Abstract 3517 Background and Aim: The karyotype and molecular mutations are well established prognostic parameters in AML. However, the impact on outcome of molecular mutations has been evaluated mainly in the subset of AML with normal karyotype (NK). The aim of this study was 1. to determine the frequency of NPM1 mutations (NPM1 mut), partial tandem duplications within the MLL gene (MLL -PTD), length mutations within the FLT3 gene (FLT3 -ITD) and CEPBA mutations (CEPBA mut) in distinct cytogenetic subgroups and 2. to evaluate the prognostic impact of these mutations in relation to chromosome abnormalities. Patients and Methods: 1981 patients with AML and evaluable cytogenetics were included. Mutation data was available in the majority of cases: NPM1: 1646, CEPBA: 1324, FLT3 -ITD: 1726 and MLL -PTD: 1656. Based on the karyotype the cohort was subdivided according to revised MRC criteria (Grimwade et al. Blood 2010) and in addition into distinct cytogenetic subgroups. Results: According to cytogenetics 170 cases were assigned to the favorable MRC class (MRCF), 1414 to the intermediate MRC (MRCI) and 397 to the unfavorable MRC subset (MRCU). The frequency of NPM1 mut, CEPBA mut, MLL -PTD and FLT3 -ITD differed significantly between MRC classes and distinct cytogenetic groups. In the MRCI subset we evaluated overall survival (OS) between patients with normal or aberrant karyotype (AK) within the respective mutation groups. Within NPM1 mut, CEPBA mut, MLL -PTD+ and FLT3 -ITD+ patients no significant differences in OS were observed between patients with NK or AK. When separating CEPBA mut into biallelic (n=52) and monoallelic cases (n=40) also no difference in OS was observed between pats with NK or AK. Next we tested the prognostic impact of the respective molecular mutations within MRCI including 966 cases with NK and 448 cases with AK. OS was significantly longer in patients with NPM1 mut or CEPBA mut (median OS (mOS) 49.6 months (mo) vs 18.6 mo, p=0.003; not reached (n.r.) vs 21.1 mo, p=0.016) and significantly worse for patients with MLL -PTD or FLT3 -ITD (mOS 10.8 vs 23.0 mo, p=0.039; 13.8 vs 24.9 mo, p=0.003). Analyzing biallelic and monoallelic CEPA mut separately revealed that only biallelic CEPBA mut was associated with a longer OS (p=0.006). Restricting the analysis to MRCI patients with aberrant karyotype revealed a longer OS for patients with NPM1 mut/FLT3 -ITD-, and a shorter OS for patients with FLT3 -ITD (mOS n.r. vs 18.0 mo, p=0.033; 5.7 vs 23.0 mo, p=0.015). A trend towards better OS was observed for biallelic CEBPA mut. Conclusions: 1. The frequency of molecular mutations varies significantly between distinct cytogenetic subsets. They are particularly common in AK within MRCI. NPM1 mut, CEBPA mut and MLL -PTD were not observed in MRCF, in AML with 11q23/MLL -rearrangements, or in 3q26/EVI1 -rearrangements. Their frequency was below 5% in AML with complex karyotype. 2. The outcome of NPM1 mut, CEPBA mut and MLL -PTD+ cases was not different in AML with normal or aberrant karyotype within MRCI. 3. This data suggest to extend mutation screening for NPM1 mut, CEPBA mut, MLL -PTD and FLT3 -ITD to all AML with intermediate risk cytogenetics, as they are significantly associated with outcome not only in AML with normal karyotype but also in AML with cytogenetic abnormalities assigned to MRCI. This consequently will lead to better characterization of a reasonable number of cases from MRCI with important implication on treatment. Disclosures: Haferlach: MLL Munich Leukemia Laboratory: Employment, Equity Ownership. Haferlach:MLL Munich Leukemia Laboratory: Employment, Equity Ownership. Alpermann:MLL Munich Leukemia Laboratory: Employment. Kern:MLL Munich Leukemia Laboratory: Employment, Equity Ownership. Schnittger:MLL Munich Leukemia Laboratory: Employment, Equity Ownership.

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Impact of Expression of BAALC, CDKN1B, ERG, EVI1, and MN1 on Prognosis and Their Association with Karyotype, FLT3-ITD, NPM1 and MLL-PTD Status In Adult AML: A Comprehensive Study on 286 Cases

Blood ◽

10.1182/blood.v116.21.953.953 ◽

2010 ◽

Vol 116 (21) ◽

pp. 953-953

Author(s):

Claudia Haferlach ◽

Alexander Kohlmann ◽

Sonja Schindela ◽

Tamara Alpermann ◽

Wolfgang Kern ◽

...

Keyword(s):

Molecular Genetic ◽

Normal Karyotype ◽

Genetic Alterations ◽

Complex Karyotype ◽

Employment Equity ◽

Aberrant Expression ◽

Cox Regression Analysis ◽

Total Cohort ◽

Equity Ownership ◽

Low Expression

Abstract Abstract 953 Introduction: The WHO classification in 2008 listed for the first time aberrant expression of genes as molecular genetic alterations affecting outcome in AML. High expression of BAALC, ERG and MN1 were shown thus far to be associated with unfavorable outcome in normal karyotype AML (AML-NK). In addition high EVI1 expression was suggested to predict poor outcome. Recently, our group identified low expression of CDKN1B as a favorable prognostic marker. The aim of this study was to evaluate the expression of BAALC, CDKN1B, ERG, EVI1 and MN1 in AML comprising all cytogenetic risk groups with respect to their association with distinct cytogenetic and known molecular genetic subgroups and their impact on prognosis. Patients/Methods:: Expression levels of BAALC, CDKN1B, ERG, EVI1 and MN1 were determined by oligonucleotide microarrays (HG-U133 Plus 2.0, Affymetrix) in 286 AML (t(15;17) n=15; t(8;21) n=16; inv(16) n=7; normal karyotype n=99; 11q23/MLL-rearrangements n=10; complex karyotype n=51; other abnormalities n=88). Patients were further analyzed for mutations in NPM1, FLT3-ITD, CEPBA and MLL-PTD. Results: Expression of BAALC, CDKN1B, ERG, EVI1 and MN1 varied significantly between genetic subgroups: While t(15;17), t(8;21) and 11q23/MLL-rearrangements were associated with low CDKN1B expression, AML-NK and NPM+ cases showed a higher CDKN1B expression. Lower BAALC expression was observed in AML with t(15;17), 11q23/MLL-rearrangement and AML-NK as well as in FLT3-ITD+ AML and in NPM1+ AML, while in AML with other abnormalities a higher BAALC expression was observed. ERG expression was lower in AML with 11q23/MLL-rearrangement and normal karyotype, while it was higher in AML with complex karyotype. Low EVI1 expression was observed in AML with t(15;17), t(8;21), inv(16) and AML-NK, while it was higher in AML with 11q23/MLL-rearrangements. Low MN1 expression was associated with t(15;17), t(8;21) and AML-NK, while it was increased in cases with inv(16) or other abnormalities. Next, Cox regression analysis was performed with respect to overall survival (OS) and event free survival (EFS). In the total cohort high BAALC and ERG expression as continuous variables were associated with shorter OS and EFS while CDKN1B, EVI1 and MN1 had no impact. Furthermore the cohort was subdivided into quartiles of expression for each gene. After inspection of the survival curves the cut-off for high vs low expression was set as follows: BAALC: 75th percentile, CDKN1B: 25th percentile, ERG and MN1: 50th percentile. For EVI1 expression pts were separated into expressers (n=44) and non-expressers (n=242). Low CDKN1B expression was associated with longer OS and EFS in the total cohort (p=0.005, not reached (n.r.) vs 14.9 months (mo); p=0.013, 31 vs 9.7 mo). High BAALC expression had no impact on OS, but was associated with shorter EFS in the total cohort as well as in AML with intermediate cytogenetics and AML with other abnormalities (p=0.032, 6.2 vs 13.0 mo; p=0.027, 5.1 vs 11.3 mo; p=0.006, 2.3 vs 14.8 mo). High ERG expression was significantly associated with shorter OS and EFS in the total cohort (p=0.002, 12.5 mo vs n.r.; p=0.001, 8.1 vs 15.7 mo) as well as in AML-NK (p=0.001, 11.3 mo vs n.r.; p=0.010, 7.2 vs 22.1 mo). OS was also shorter in AML with unfavorable karyotype (p=0.048, median OS 9.3 mo vs n. r.). With respect to MN1 high expressers had a significantly shorter OS and EFS in the total cohort (p=0.004, 12.3 mo vs. n.r.; p=0.001, 8.1 vs 16.7 mo) as well as in AML-NK (p=0.001, 9.7 mo vs n.r.; p=0.001, 5.1 vs 22.1 mo). In a multivariate analysis including CDKN1B, ERG and MN1 all parameters retained their impact on OS as well as on EFS, while BAALC lost its impact on EFS. Adding MLL-PTD, NPM1+/FLT3-ITD-, favorable and unfavorable karyotype into the model demonstrated an independent significant adverse impact on OS for MLL-PTD (p=0.027, relative risk (RR): 2.38) and ERG expression (p=0.044, RR: 1.59) only. In the respective analysis for EFS only favorable karyotype showed an independent association (p=0.002, RR: 0.261). Conclusion: 1) Expression of BAALC, CDKN1B, ERG, EVI1 and MN1 varies significantly between cytogenetic subgroups. 2) BAALC as a continuous variable and CDKN1B, ERG and MN1 as dichotomized variables are independently predictive for OS and EFS in AML. 3) ERG expression even retains its independent prediction of shorter OS if cytogenetic and other molecular genetic markers are taken into account. Disclosures: Haferlach: MLL Munich Leukemia Laboratory: Employment, Equity Ownership. Kohlmann:MLL Munich Leukemia Laboratory: Employment. Schindela:MLL Munich Leukemia Laboratory: Employment. Kern:MLL Munich Leukemia Laboratory: Employment, Equity Ownership. Schnittger:MLL Munich Leukemia laboratory: Employment, Equity Ownership. Haferlach:MLL Munich Leukemia Laboratory: Employment, Equity Ownership.

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Categorizing Molecular Mutations in MDS and AML

Blood ◽

10.1182/blood.v126.23.5222.5222 ◽

2015 ◽

Vol 126 (23) ◽

pp. 5222-5222 ◽

Cited By ~ 2

Author(s):

Dominic Rose ◽

Torsten Haferlach ◽

Wolfgang Kern ◽

Claudia Haferlach

Keyword(s):

Solid Tumors ◽

Copy Number ◽

Mutation Frequency ◽

Gene Mutations ◽

Hematologic Malignancies ◽

Genetic Alterations ◽

Fusion Genes ◽

Employment Equity ◽

Sequencing Studies ◽

Equity Ownership

Abstract Introduction: A huge amount of data on genetic alterations has been compiled by high throughput sequencing studies in several hematologic malignancies. A molecular based categorization of these abnormalities could be helpful for further diagnostic and therapeutic approaches. Based on the type of alterations we discriminate 3 major categories: 1. copy number gains or losses, 2. fusion genes, and 3. molecular mutations. Studies on copy number data revealed that distinct tumor entities show typical but rather unspecific genetic alterations. Some fusion genes, e.g. involving FGFR, occur in diverse cancers, but others can also be specific for distinct diseases, like PML-RARA which is only found in APL. In particular kinase fusions, like BCR -ABL1 in CML or ALL, have tremendous clinical impact as affected patients respond to specific kinase inhibitors. However, there is limited knowledge yet on the entity-specificity for many novel gene mutations found in hematologic malignancies and a comprehensive analysis of their specificity is missing. Aim: Categorize gene mutations most frequently occurring in MDS and AML into entity-specific mutations, i.e. to distinguish MDS/AML-specific mutations from "pan-hematologic" or "pan-cancer" mutations. Materials and Methods: We i) selected the 65 most frequently mutated genes according to 3 major sequencing studies investigating the molecular basis of MDS and AML (n=1882 patients; Papaemmanuil et al., Blood 2013; Haferlach et al., Leukemia 2014; TCGA, NEJM 2013), ii) evaluated their mutation frequencies in whole genome/exome studies of other hematologic malignancies (including CLL, DLBCL, MCL, Burkitt lymphoma and MM, see Fig.1 for references) and solid tumors (as accessible via http://www.cbioportal.org, including glioblastoma, breast, lung, thyroid, kidney, uterine, and bladder carcinoma). Characteristic for MDS as well as AML: Three genes were recurrently mutated in both entities but rarely in other hematologic malignancies and solid tumors: DNMT3A (MDS: 11-13%, AML: 25%, highest frequency (max) others: 5% in bladder), RUNX1 (MDS: 8-11%, AML: 14%, max others: 4% in bladder), TET2 (MDS: 26-33%, AML: 9%, max others: 8% in melanoma). Characteristic for MDS was SRSF2, the only gene with a mutation frequency ≥5% in MDS but ≤2% in other entities (15-18% in MDS vs. 2% in bladder). Further, SF3B1 mutations were frequent in MDS (25-33%), CLL (10-14%), and solid tumors (max: 8%). ASXL1 mutations (14-23% in MDS) were also found in colorectal adenocarcinoma (10%) and ZRSR2 mutations (5-8% in MDS) in uterine cancer (3%). Regarding AML, we identified 2 genes with a mutation frequency ≥5% in AML but ≤2% in any other entity: NPM1 (27%, max others: 2% in lung) and CEBPA (7%, max others: 2% in bladder). FLT3 mutations occurred significantly more often in AML (27%) than in other entities (max: 8% in melanoma; p<0.001). Other genes recurrently mutated in AML (≥5%) but rarely in other entities include IDH2 (10%, max others 8% in melanoma) and CBFB (6%, max others: 4% in breast). IDH1 mutations were more frequent in brain/glioma (76%) than in AML (10%). Analyzing the mutated genes grouped into different biologic processes revealed MDS, Burkitt lymphoma, uterine and bladder cancer sharing the majority of affected processes, i.e. regulation of transcription, gene expression, splicing, chromatin organization and cell cycle. In contrast, the pattern was completely different in AML and involved cell proliferation, differentiation and several signaling pathways. Conclusions: The majority of recurrently mutated genes in AML/MDS is rarely altered in other hematologic malignancies or solid tumors. While DNMT3A, RUNX1, and TET2 were linked to AML and MDS, we also found highly entity-specific genes either associated with AML or MDS. These can clearly be considered as driver genes and are of utmost diagnostic and/or therapeutic interest. Mutations of NPM1 and CEBPA turned out to be specific for AML supporting their currently discussed roles as distinct WHO entities. SRSF2 mutations were specifically associated with MDS making SRSF2 a prime candidate for further research on targeted therapies. Furthermore, the broad spectrum of mutated genes co-operatively impacting distinct biological processes in MDS, AML and the other analyzed malignancies supports its continued evaluation by comprehensive multi-gene screenings aiming at patient-specific and biology-based targeted therapies. Disclosures Rose: 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.

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The Number of RUNX1 Mutations and the Presence of One Intact RUNX1 Allele Influence Cytogenetic Abnormalities, Additional Molecular Mutations and Prognosis in RUNX1 Mutated AML

Blood ◽

10.1182/blood.v128.22.284.284 ◽

2016 ◽

Vol 128 (22) ◽

pp. 284-284 ◽

Cited By ~ 1

Author(s):

Anna Stengel ◽

Wolfgang Kern ◽

Manja Meggendorfer ◽

Karolina Perglerová ◽

Torsten Haferlach ◽

...

Keyword(s):

Genetic Alterations ◽

Adverse Impact ◽

Missense Mutations ◽

Employment Equity ◽

Frameshift Mutations ◽

Total Cohort ◽

Equity Ownership ◽

The Impact ◽

Runx1 Mutation ◽

Mutation Analyses

Abstract Background: According to the revised WHO classification of 2016, AML with mutated RUNX1 constitutes a new provisional entity. We previously reported that the subgroup of RUNX1-mutated AML with RUNX1 wild-type (WT) loss is associated with a distinct pattern of cytogenetic and molecular genetic abnormalities and with an adverse prognosis. However, the impact of multiple RUNX1 mutations is unclear yet. Aims: Evaluation of associated genetic alterations and prognosis in AML with >1 RUNX1 mutation as compared to those with (1) RUNX1 WT loss and (2) one RUNX1 mutation. Patient cohorts and methods: The total cohort comprised 467 AML cases with RUNX1 mutations (mut) (296 male, 171 female). Median age was 72 years (range: 18-91 years). All patients were investigated using chromosome banding analysis (CBA) and amplicon sequencing of RUNX1. The cohort was split into the subgroups with RUNX1 WT loss (UPD or RUNX1 deletion detected by genomic arrays) (n=50), cases with >1 RUNX1mut (n = 94) and cases with 1 RUNX1mut and conservation of the RUNX1 WT allele (n = 323). Of these, 50, 55 and 58 cases, respectively, were selected for further mutation analyses of ASXL1, BCOR, CBL, CEBPA, DNMT3A, ETV6, EZH2, FLT3-ITD, FLT3-TKD, GATA2, IDH1, IDH2, KIT, KRAS, MLL-PTD, NPM, NRAS, SETBP1, SF3B1, SRSF2, TET2, TP53, U2AF1 and WT1. Variants of unknown significance were excluded from statistical analysis. Results: In the total cohort of 467 cases, CBA revealed a normal karyotype (NK) in 53% of patients, 18% harbored trisomies, 3% showed a complex karyotype (>3 abnormalities), 26% other aberrations. The proportion of cases with trisomies was largest in cases with RUNX1 WT loss (26%), followed by >1 RUNX1mut (19%) and 1 RUNX1mut (16%). In more detail, in the total cohort, 56% of cases with trisomies harbored +8, in 30% +13 was found. A similar pattern was observed for 1 RUNX1mut, whereas in cases with WT loss +13 was the most abundant trisomy (+8: 66% in 1 RUNX1mut vs. 31% in WT loss, p=0.022; +13: 15% vs. 62%, p<0.001). Cases with >1 RUNX1mut showed an intermediate distribution (+8: 44%, +13: 50%). Missense mutations were the most abundant mutation type (53%) inWT loss cases, followed by frameshift mutations (28%). By contrast, in cases with 1 RUNX1mut, frameshift mutations were found more frequent (45%, p=0.016), whereas missense mutations were detected at a frequency of 31% (p=0.006). In cases with >1 RUNX1mut, both were observed at similar frequencies (missense: 36%, frameshift: 38%). Mutation analyses of 163 selected cases revealed SRSF2 (39%), ASXL1 (36%), DNMT3A (19%), BCOR (18%), IDH2 (17%), SF3B1 (17%) and TET2 (17%) mutations as most frequently mutated genes in the total cohort. Cases with RUNX1 WT loss showed a higher frequency of ASXL1mut compared to the other cases (50% vs. 29%, p=0.013), while U2AF1mut were absent from this group (0% vs. 15%, p=0.019). Differences between cases with and without RUNX1 WT loss were also detected for DNMT3A, TET2, SF3B1 (more abundant in WT loss) and IDH2, WT1 (less abundant in WT loss), although these were not statistically significant. For many genes, the group of cases with >1 RUNX1mut showed an intermediate abundance pattern, or mutation frequencies similar to cases with 1 RUNX1mut were observed. Mutations in spliceosome genes (SF3B1, SRSF2, U2AF1, ZRSR2) were very abundant in all subgroups but less frequent (although not statistically significant) in cases with 1 RUNX1mut. Median overall survival (OS) in the total cohort was 14 months. WT loss (OS: 5 months) and >1 RUNX1mut (14 months) showed an adverse impact on prognosis compared to 1 RUNX1mut (22 months; p=0.002 and p=0.048, respectively). Mutations in ASXL1 and KRAS showed a negative impact on OS in the total cohort (10 vs. 18 months, p=0.028; 1 vs. 15 months, p<0.001), whereas DNMT3A mutations negatively affected OS in WT loss only (in WT loss: 1 vs. 7 months, p=0.005). Conclusion: 1) RUNX1 mutated AML cases with WT loss show a high frequency of +13, RUNX1 missense mutations and accompanying ASXL1 mutations. 2) They clearly separate from cases with 1 RUNX1mut, which depict a predominance of +8, RUNX1 frameshift mutations and mutations in IDH2 and WT1. 3) Patients with >1 RUNX1mut show a pattern intermediate between the former two subgroups. 4) Loss of RUNX1 WT and > 1 RUNX1mut showed an adverse impact on OS. Thus, not only the presence and number of RUNX1mut but also the conservation of an intact RUNX1 allele is biologically and clinically relevant. Disclosures Stengel: MLL Munich Leukemia Laboratory: Employment. Kern:MLL Munich Leukemia Laboratory: Employment, Equity Ownership. Meggendorfer:MLL Munich Leukemia Laboratory: Employment. Perglerová:MLL2 s.r.o.: Employment. Haferlach:MLL Munich Leukemia Laboratory: Employment, Equity Ownership. Haferlach:MLL Munich Leukemia Laboratory: Employment, Equity Ownership.

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Characterization and Prognostic Impact of Multiple Productive IGHV Rearrangements in CLL

Blood ◽

10.1182/blood.v128.22.3207.3207 ◽

2016 ◽

Vol 128 (22) ◽

pp. 3207-3207

Author(s):

Sabine Jeromin ◽

Claudia Haferlach ◽

Frank Dicker ◽

Manja Meggendorfer ◽

Torsten Haferlach ◽

...

Keyword(s):

Prognostic Factors ◽

Lymphocytic Leukemia ◽

Prognostic Impact ◽

Employment Equity ◽

Mutational Status ◽

Treatment Naïve ◽

Trisomy 12 ◽

Equity Ownership ◽

The Impact

Abstract Background: In chronic lymphocytic leukemia (CLL) one of the strongest prognostic factors is IGHV mutational status. Infrequently, patients present not only with a single IGHV rearrangement but with multiple productive rearrangements. In about 2% of all CLL patients analyzed on cDNA level multiple rearrangements display the same mutational status and are categorized accordingly following ERIC recommendations. In another 1% rearrangements with discordant IGHV mutational status are detected and preclude a definite risk assignment. Only limited data exist on these rare subgroups. Aim: To characterize treatment-naive CLL patients with multiple productive IGHV rearrangements and determine the impact on prognosis. Patients and Methods: Out of 8,016 treatment-naive CLL patients between 2005 and 2015 and with data on IGHV mutational status we identified 204 (3%) with multiple productive rearrangements. IGHV mutational status was analyzed on cDNA and in all cases according to ERIC recommendations. IGHV mutated status (M) was defined by sequence identity <98% and unmutated status (U) by ≥98%. Chromosome banding analysis was available in 102 cases and interphase FISH with probes for 17p13, 13q14, 11q22 and centromeric region of chromosome 12 in 191. Male:female ratio was 3:1 and median age 68 years (range: 38-89). Additionally, data on SF3B1 and TP53 mutations was present in all cases. Follow-up data on time to first treatment (TTT) and overall survival (OS) was available in 105 cases with a median follow-up of 4 years. For statistical comparison we used a cohort of 1,262 untreated CLL patients with single IGHV rearrangement (median age: 67 years; range: 30-91, median follow-up: 6 years). Results: Out of 204 patients with multiple, productive rearrangements 199 (98%) presented with two and 5 patients (2%) with three IGHV rearrangements. Concordant IGHV mutated status (MM) was present in 120 cases (59%), whereas concordant unmutated status (UU) was seen in 34 patients (17%). In 50 cases (25%) a mixed IGHV status (UM) was detected. We analyzed frequencies of complex karyotype by CBA, biclonality according to immunophenotype (concurrent kappa restricted and lambda restricted subpopulations) and/or CBA, TP53 disruption (TP53mut and/or del(17p)), SF3B1mut, del(11q), trisomy 12, and del(13q). Overall, a higher frequency of biclonality was detected in patients with multiple vs. single IGHV rearrangements (16% vs. 1%, p<0.001). However, association to neither MM, UU nor UM existed. MM presented with molecular and cytogenetic characteristics similar to M. Correspondingly, UU showed similar frequencies of mutations and aberrations to U, except for higher frequency of trisomy 12 in UU vs. U (42% vs. 19%, p=0.003). Interestingly, UM presented with characteristics similar to U and UU. UM was associated with TP53 disruption vs. M (16% vs. 5%, p=0.003) and vs. MM (5%, p=0.035) as well as with SF3B1mut vs. M (16% vs. 5%, p=0.008). Furthermore, UM cases showed high frequency of del(11q) vs. M (29% vs. 3%, p<0.001) and vs. MM (1%, p<0.001) and less frequently del(13q) sole vs. M (41% vs. 60%, p=0.011) and MM (41% vs. 69%, p=0.001). No significantly differences in TTT were observed between MM and M (median: 13 vs. 14 years) and between UU and U (6 vs. 4 years), respectively. However, the difference between MM vs. UU (p=0.022) and M vs. U (p<0.001) was significant. The UM subgroup presented with a TTT (median: 4 years) similar to U and UU, whereas it was significantly shorter vs. M (p=0.003) and MM (p=0.006), respectively. A similar picture emerged for survival. 5-year OS of MM was not different vs. M (94% vs. 90%) but vs. U (78%, p=0.001). The statistical analysis of OS in UU was hampered by low case numbers. UM presented again with similar 5-year OS vs. U (81% vs. 78%, n.s.) and significantly worse OS vs. M (90%, p=0.049) and vs. MM (94%, p=0.014). Conclusions: (1) Patients with multiple productive IGHV rearrangements and concordant IGHV status show similar prognosis and characteristics to patients with single rearrangement with the respective IGHV status. (2) Cases with mixed IGHV status show similar prognosis to patients with IGHV unmutated status and accordingly are characterized by high frequencies of adverse prognostic factors like TP53 disruption, SF3B1mut, and del(11q), whereas del(13q) sole is less frequent. Disclosures Jeromin: MLL Munich Leukemia Laboratory: Employment. Haferlach:MLL Munich Leukemia Laboratory: Employment, Equity Ownership. Dicker:Munich Leukemia Laboratory: Employment. Meggendorfer:MLL Munich Leukemia Laboratory: Employment. Haferlach:MLL Munich Leukemia Laboratory: Employment, Equity Ownership. Kern:MLL Munich Leukemia Laboratory: Employment, Equity Ownership.

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Comprehensive Molecular Profiling of T-Cell Acute Lymphoblastic Leukemia Identifies Mutations in 76 (97.4%) of 78 Patients

Blood ◽

10.1182/blood.v118.21.2548.2548 ◽

2011 ◽

Vol 118 (21) ◽

pp. 2548-2548

Author(s):

Vera Grossmann ◽

Alexander Kohlmann ◽

Sandra Weissmann ◽

Susanne Schnittger ◽

Valentina Artusi ◽

...

Keyword(s):

Promoter Methylation ◽

Kinase Inhibitors ◽

Lymphoblastic Leukemia ◽

Methylation Status ◽

Normal Karyotype ◽

Genetic Alterations ◽

Cyclin Dependent Kinase ◽

Wild Type ◽

Employment Equity ◽

Equity Ownership

Abstract Abstract 2548 Introduction: At present, the diagnosis of T-ALL is based on immunophenotyping and specific chromosomal rearrangements. However, the knowledge about recurrent somatic mutations is limited. Patients and Methods: We studied a cohort of 78 adult T-ALL cases (n=33 early, n=33 cortical, n=2 mature T-ALL, n=10 subtype not available), including 57 males and 21 females. Age ranged from 18.8–87.7 yrs (median: 42 yrs). A deep-sequencing assay was used to investigate for specific molecular alterations in genes involved in transcriptional regulation: NOTCH1, FBXW7, CDKN2A, DNMT3A, FLT3-ITD, FLT3-TKD, NPM1, PTEN, and RUNX1. Further, chromosome banding analysis and FISH with probes for DNMT3A (2p23), SEC63 (6q21), MYB (6q23), CDKN2A (9p21), PTEN (10q23), CDKN1B (12p13) and TP53 (17p13), as well as CDKN2B promoter methylation analyses were performed. Results: Cytogenetic data was available in 68 patients: normal karyotype: n=22 (2 of these harbored a PICALM-MLLT10-rearrangement), SIL-TAL1-rearrangement: n=3, t(5;14)(q35;q32): n=2, t(10;14)(q24;q11)/t(7;10)(q34;q24): n=9, t(10;11)(p13;q21): n=3, other abnormalities n=29. Importantly, molecular mutations were detected in 67/78 patients (85.6%). In detail, NOTCH1 was the most frequently mutated gene (55/77 cases, 71.4%). Other alterations were detected in DNMT3A (16/78; 20.5%); RUNX1 (13/78; 16.6%); FBXW7 (11/75; 14.6%); PTEN (7/78; 10.0%); CDKN2A (3/58; 5.2%); FLT3-ITD (2/78; 2.5%); and FLT3-TKD (1/70; 1.4%). By FISH analyses, heterozygous deletions of the following loci were observed: DNMT3A (1/43; 2.3%), SEC63 (7/43; 16.3%), PTEN (1/32, 3.1%), CDKN1B (8/43; 18.6%) and TP53 (3/43; 7.0%). CDKN2A deletions were detected in 30/72 (41.6%) cases: n=14 heterozygous, n=15 homozygous, n=1 showed a clone with a heterozygous and a subclone with a homozygous deletion. Further, the CDKN2B promoter methylation status was analyzed. Here, 36/74 (48.6%) cases demonstrated hypermethylation. As such, when combining molecular mutations, CDKN2A deletions, and CDKN2B hypermethylation, in median 2 alterations per case were observed (range 1–5). Moreover, almost every patient (76/78) harbored at least one aberration resulting in a mutation rate of 97.4%. Interestingly, considering alterations in the group of cyclin-dependent kinase inhibitors (CDKN2A/1B deletions, CDKN2A mutations, and CDKN2B hypermethylation), 61/78 (78.2%) cases carried at least one such alteration. With respect to associations amongst molecular mutations, no specific pattern was observed except for a strong correlation between RUNX1 and DNMT3A mutations, i.e. 6/13 RUNX1 mutated cases concomitantly harbored DNMT3A mutations (p=0.021). Furthermore, we observed that DNMT3A and RUNX1 alterations were associated with higher age (DNMT3A: mean±SD 60.9±16 vs. 39.6±16 years; p<0.001; RUNX1: mean±SD 55.4±18 vs. 41.7±18 yrs; p=0.013) whereas PTENmut were associated with younger age (mean±SD 32.9±10 vs. 45.0±19 yrs; p=0.019). With regard to cytogenetics, DNMT3A was significantly correlated with normal karyotype (9/23, 39.1% vs. 6/45, 13.3%; p=0.028). Moreover, RUNX1mut were associated with lower WBC count (mean±SD 26.4±41 vs. 63.4±90 cell count G/L; p=0.025). With respect to immunophenotypes, cases with RUNX1mut showed a trend to be associated with early T-ALLs (9/23, 39.1% vs. 6/45, 13.3%; p=0.082). CDKN2B hypermethylation was significantly correlated with early T-ALLs (21/32, 65.6% vs. 10/31, 32.2%; p=0.012). In contrast, FBXW7mut were associated with the cortical subgroup (1/32, 3.1% vs. 9/32, 28.1%; p=0.013). With regard to clinical outcome, patients with RUNX1mut had a shorter overall survival (OS) compared to RUNX1wt patients (alive at 2 yrs: 44.4% mutated vs. 64.0% wild-type, p=0.011). Further, for NOTCH1mut cases (alive at 2 yrs: 67.4% mutated vs. 33.6% wild-type, p=0.060) a trend towards a better OS was detectable. Conclusions: 1. T-ALL is characterized by a high number of genetic alterations since 46/68 (67.6%) showed cytogenetic aberrations. In addition, at least one molecular alteration was observed in 76/78 (97.4%) patients. 2. The most frequent alterations observed were mutations in NOTCH1, DNMT3A, RUNX1 and FBXW7. 3. The cyclin-dependent kinase inhibitors were altered by deletion, mutation or hypermethylation in 78.2% of cases. 4. RUNX1 mutations are associated with shorter and NOTCH1 mutations with longer OS. Disclosures: Grossmann: MLL Munich Leukemia Laboratory: Employment. Kohlmann:MLL Munich Leukemia Laboratory: Employment. Weissmann:MLL Munich Leukemia Laboratory: Employment. Schnittger:MLL Munich Leukemia Laboratory: Employment, Equity Ownership. Artusi:MLL Munich Leukemia Laboratory: Employment. Schindela:MLL Munich Leukemia Laboratory: Employment. Stadler: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.

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