Therapeutic Outcomes and Prognostic Impact of Gene Mutations Including TP53 and SF3B1 in Patients with Del(5q) Myelodysplastic Syndromes (MDS)

2022 ◽  
Author(s):  
Onyee Chan ◽  
Najla Al Ali ◽  
David Sallman ◽  
Eric Padron ◽  
Jeffrey Lancet ◽  
...  
Keyword(s):  
Myelodysplastic Syndromes ◽  
Gene Mutations ◽  
Prognostic Impact ◽  
Therapeutic Outcomes

Personalized Prediction Model to Risk Stratify Patients With Myelodysplastic Syndromes

2021 ◽  
pp. JCO.20.02810
Author(s):  
Aziz Nazha ◽  
Rami Komrokji ◽  
Manja Meggendorfer ◽  
Xuefei Jia ◽  
Nathan Radakovich ◽  
...  
Keyword(s):  
Prediction Model ◽  
Myelodysplastic Syndromes ◽  
Gene Mutations ◽  
Molecular Data ◽  
Machine Learning Techniques ◽  
Prognostic Models ◽  
Prognostic Impact ◽  
Hematopoietic Stem ◽  
Training Cohort ◽  
Time Points

PURPOSE Patients with myelodysplastic syndromes (MDS) have a survival that can range from months to decades. Prognostic systems that incorporate advanced analytics of clinical, pathologic, and molecular data have the potential to more accurately and dynamically predict survival in patients receiving various therapies. METHODS A total of 1,471 MDS patients with comprehensively annotated clinical and molecular data were included in a training cohort and analyzed using machine learning techniques. A random survival algorithm was used to build a prognostic model, which was then validated in external cohorts. The accuracy of the proposed model, compared with other established models, was assessed using a concordance (c)index. RESULTS The median age for the training cohort was 71 years. Commonly mutated genes included SF3B1, TET2, and ASXL1. The algorithm identified chromosomal karyotype, platelet, hemoglobin levels, bone marrow blast percentage, age, other clinical variables, seven discrete gene mutations, and mutation number as having prognostic impact on overall and leukemia-free survivals. The model was validated in an independent external cohort of 465 patients, a cohort of patients with MDS treated in a prospective clinical trial, a cohort of patients with paired samples at different time points during the disease course, and a cohort of patients who underwent hematopoietic stem-cell transplantation. CONCLUSION A personalized prediction model on the basis of clinical and genomic data outperformed established prognostic models in MDS. The new model was dynamic, predicting survival and leukemia transformation probabilities at different time points that are unique for a given patient, and can upstage and downstage patients into more appropriate risk categories.

scholarly journals Prognostic impact of gene mutations in myelodysplastic syndromes with ring sideroblasts

2017 ◽  
Vol 7 (12) ◽  
Author(s):  
Iván Martín ◽  
Esperanza Such ◽  
Blanca Navarro ◽  
Eva Villamón ◽  
Ana Vicente ◽  
...  
Keyword(s):  
Myelodysplastic Syndromes ◽  
Gene Mutations ◽  
Prognostic Impact ◽  
Ring Sideroblasts

scholarly journals ETV6 and signaling gene mutations are associated with secondary transformation of myelodysplastic syndromes to chronic myelomonocytic leukemia

Blood ◽  
2014 ◽  
Vol 123 (23) ◽  
pp. 3675-3677 ◽  
Author(s):  
Eric Padron ◽  
Sean Yoder ◽  
Sateesh Kunigal ◽  
Tania Mesa ◽  
Jamie K. Teer ◽  
...  
Keyword(s):  
Myelodysplastic Syndromes ◽  
Gene Mutations ◽  
Chronic Myelomonocytic Leukemia ◽  
Myelomonocytic Leukemia

scholarly journals The Clinical Features and Prognostic Impact of PRDM16 gene Expression in Adult Acute Myeloid Leukemia

Blood ◽  
2016 ◽  
Vol 128 (22) ◽  
pp. 5228-5228
Author(s):  
Genki Yamato ◽  
Hiroki Yamaguchi ◽  
Hiroshi Handa ◽  
Norio Shiba ◽  
Satoshi Wakita ◽  
...  
Keyword(s):  
Gene Expression ◽  
Acute Myeloid Leukemia ◽  
Myeloid Leukemia ◽  
Risk Group ◽  
Gene Mutations ◽  
Genetic Alterations ◽  
Prognostic Impact ◽  
Pediatric Aml ◽  
Prdm16 Gene ◽  
Acute Myeloid

Abstract Background Acute myeloid leukemia (AML) is a complex disease caused by various genetic alterations. Some prognosis-associated cytogenetic aberrations or gene mutations such as FLT3-internal tandem duplication (ITD), t(8;21)(q22;q22)/RUNX1-RUNX1T1, and inv(16)(p13q22)/CBFB-MYH11 have been found and used to stratify the risk. Numerous gene mutations have been implicated in the pathogenesis of AML, including mutations of DNMT3A, IDH1/2, TET2 and EZH2 in addition to RAS, KIT, NPM1, CEBPA and FLT3in the recent development of massively parallel sequencing technologies. However, even after incorporating these molecular markers, the prognosis is unclear in a subset of AML patients. Recently, NUP98-NSD1 fusion gene was identified as a poor prognostic factor for AML. We have reported that all pediatric AML patients with NUP98-NSD1 fusion showed high expression of the PR domain containing 16 (PRDM16; also known as MEL1) gene, which is a zinc finger transcription factor located near the breakpoint at 1p36. PRDM16 is highly homologous to MDS1/EVI1, which is an alternatively spliced transcript of EVI1. Furthermore, PRDM16 is essential for hematopoietic stem cell maintenance and remarkable as a candidate gene to induce leukemogenesis. Recent reports revealed that high PRDM16 expression was a significant marker to predict poor prognosis in pediatric AML. However, the significance of PRDM16 expression is unclear in adult AML patients. Methods A total of 151 adult AML patients (136 patients with de novo AML and 15 patients with relapsed AML) were analyzed. They were referred to our institution between 2004 and 2015 and our collaborating center between 1996 and 2013. The median length of follow-up for censored patients was 30.6 months. Quantitative RT-PCR analysis was performed using the 7900HT Fast Real Time PCR System with TaqMan Gene Expression Master Mix and TaqMan Gene Expression Assay. In addition to PRDM16, ABL1 was also evaluated as a control gene. We investigated the correlations between PRDM16 gene expression and other genetic alterations, such as FLT3-ITD, NPM1, and DNMT3A, and clarified the prognostic impact of PRDM16 expression in adult AML patients. Mutation analyses were performed by direct sequence analysis, Mutation Biased PCR, and the next-generation sequencer Ion PGM. Results PRDM16 overexpression was identified in 29% (44/151) of adult AML patients. High PRDM16 expression correlated with higher white blood cell counts in peripheral blood and higher blast ratio in bone marrow at diagnosis; higher coincidence of mutation in NPM1 (P = 0.003) and DNMT3A (P = 0.009); and lower coincidence of t(8;21) (P = 0.010), low-risk group (P = 0.008), and mutation in BCOR (P = 0.049). Conversely, there were no significant differences in age at diagnosis and sex distribution. Patients with high PRDM16 expression tended to be low frequency in M2 (P = 0.081) subtype, and the remaining subtype had no significant differences between high and low PRDM16 expression. Remarkably, PRDM16 overexpression patients were frequently observed in non-complete remission (55.8% vs. 26.3%, P = 0.001). Patients with high PRDM16 expression tended to have a cumulative incidence of FLT3-ITD (37% vs. 21%, P = 0.089) and MLL-PTD (15% vs. 5%, P = 0.121). We analyzed the prognosis of 139 patients who were traceable. The overall survival (OS) and median survival time (MST) of patients with high PRDM16 expression were significantly worse than those of patients with low expression (5-year OS, 17% vs. 32%; MST, 287 days vs. 673 days; P = 0.004). This trend was also significant among patients aged <65 years (5-year OS, 25% vs. 48%; MST, 361 days vs. 1565 days, P = 0.013). Moreover, high PRDM16 expression was a significant prognostic factor for FLT3-ITD negative patients aged < 65 years in the intermediate cytogenetic risk group (5-year OS, 29% vs. 58%; MST, 215 days vs. undefined; P = 0.032). Conclusions We investigated the correlations among PRDM16 expression, clinical features, and other genetic alterations to reveal clinical and prognostic significance. High PRDM16 expression was independently associated with non-CR and adverse outcomes in adult AML patients, as well as pediatric AML patients. Our finding indicated that the same pathogenesis may exist in both adult and pediatric AML patients with respect to PRDM16 expression, and measuring PRDM16 expression was a powerful tool to predict the prognosis of adult AML patients. Disclosures Inokuchi: Bristol-Myers Squibb: Honoraria, Research Funding; Novartis: Honoraria; Celgene: Honoraria; Pfizer: Honoraria.

Prognostic impact of the number of methylated genes in myelodysplastic syndromes and acute myeloid leukemias treated with azacytidine

2013 ◽  
Vol 92 (11) ◽  
pp. 1543-1552 ◽  
Author(s):  
María Abáigar ◽  
Fernando Ramos ◽  
Rocío Benito ◽  
María Díez-Campelo ◽  
Javier Sánchez-del-Real ◽  
...  
Keyword(s):  
Myelodysplastic Syndromes ◽  
Prognostic Impact ◽  
Myeloid Leukemias ◽  
Acute Myeloid

Hemochromatois-Associated Gene Mutations in Patients with Myelodysplastic Syndromes with Refractory Anemia and Ringed Sideroblasts.

Blood ◽  
2006 ◽  
Vol 108 (11) ◽  
pp. 1541-1541
Author(s):  
Zachary P. Nearman ◽  
Bianca Serio ◽  
Hadrian Szpurka ◽  
Ilka Warshawsky ◽  
Alan Lichtin ◽  
...  
Keyword(s):  
Clinical Features ◽  
Myelodysplastic Syndromes ◽  
Phenotypic Variability ◽  
Gene Mutations ◽  
Differential Susceptibility ◽  
Control Population ◽  
Refractory Anemia ◽  
Hfe Gene ◽  
Jak2 Mutation ◽  
Ringed Sideroblasts

Abstract Complex interaction between a multitude of genetic variants may be responsible for differential susceptibility to specific diseases, and be responsible for phenotypic variability and heterogeneity of clinical presentations. Such a variability in clinical features confounded for many years investigations into the pathogenesis of myelodysplastic syndromes (MDS). We made a curious observation of increased ferritin levels in some newly diagnosed patients with MDS RARS (refractory anemia with ringed sideroblasts) in whom transfusional iron-overload was unlikely due to very low transfusion burden. Hence, we hypothesized that RARS patients may harbor hemochromatosis-related mutations, which could contribute to the pathophysiology of this particular subset of MDS. We studied a cohort of 109 MDS patients; 42 with RARS, and 67 with other forms of MDS (18 RA, 12 RAEB, 7 RAEB-T, 1 CMML, and 29 MDS/MPD overlap). All patients were genotyped using restriction fragment length polymorphism (RFLP) method, designed to detect presence of C282Y and H63D mutations of the HFE gene. We found significantly higher frequency of heterozygozity for the C282Y mutation in 21% of RARS patients (vs 9% in control population, n=2016, p= 0.017) while H63D genotype was not increased. The possible pathogenic role of this finding in RARS was supported by the normal distribution of mutant HFE alleles in patients with other forms of MDS (5% vs. 9%, p =0.35). Interestingly, 3/7 patients with RA not fulfilling the RARS criteria, but having increased numbers of ringed sideroblasts (<15%) also showed heterozygozity for either C282Y or H63D allele. To correlate the presence of C282Y allele with clinical features of RARS patients, we have performed a subset analysis. Within this group we have included patients with a rather nebulous and rare form of MDS, provisionally subclassified by WHO as RARS with thrombocytosis (RARSt); 7 of these patients (n=10) were found to have either C282Y or H63D allele resulting in a frequency of 30% and 40% of C282Y or H63D allele, respectively. The combined prevalence of either of these alleles in the control population is 33% (vs. 70% in RARSt, p=.01). Previously, we have demonstrated that RARSt patients are characterized by a high prevalence of the V617F JAK2 mutation (Szpurka et al, Blood 2006) suggestive of the pathophysiologic derivation of this syndrome from MPD rather than MDS. Consequently, we have tested the frequency of HFE gene variants associated with hemochromatosis in patients with MPD and Jak2 mutations. Of note is that patients with RARS harbored more C282Y alleles than those with other forms of MDS or MPD with Jak2 mutation (except for those with RARSt; (21% vs 5% and 3%, p =0.036 and .012, respectively). We conclude that hemochromatosis associated mutations may contribute to the pathogenesis of RARS. In patients with MPD and Jak2 mutation, concomitant presence of hemachromatosis-predisposing HFE variants may result in the unusual presentation associated with ringed sideroblasts.

Analysis of 12 Genes in 268 Cases with CMML Identifies ASXL1 Mutations As the Most Important Genetic Alteration Associated with Adverse Outcome

Blood ◽  
2012 ◽  
Vol 120 (21) ◽  
pp. 3491-3491
Author(s):  
Susanne Schnittger ◽  
Manja Meggendorfer ◽  
Vera Grossmann ◽  
Tamara Alpermann ◽  
Christiane Eder ◽  
...  
Keyword(s):  
Overall Survival ◽  
Adverse Outcome ◽  
Multivariable Analysis ◽  
Melting Curve ◽  
Gene Mutations ◽  
Prognostic Impact ◽  
Mutant Genotype ◽  
Cox Regression Analysis ◽  
Significant Difference ◽  
Equity Ownership

Abstract Abstract 3491 Introduction: Chronic myeloid monocytic leukemia (CMML) has been associated with a high number of somatic mutations in diverse genes and various mutant genotype combinations were observed. The patterns of marker combinations and prognostic impact of single markers are poorly understood. Aims: Comprehensive analysis of the genetic marker profile in a large CMML cohort and evaluation of potential prognostic implications. Patients and Methods: In total, 268 cases with CMML (CMML-1 n=191, CMML-2 n=77) were included. The cohort comprised 186 males and 82 females with a median age of 73.0 yrs (range: 21.9 – 93.3 yrs). In 262 cases cytogenetic data was available: 185 cases (70.6%) had a normal karyotype and 77 (29.4%) showed aberrant karyotypes. Data on mutations were available in all patients for SRSF2, U2AF1, JAK2 V617F, and in subcohorts for: ASXL1 (n=255), CBL (n=267), EZH2 (n=205), KIT D816 (n=263), KRAS (n=260), NRAS (n=266), RUNX1 (n=267), SF3B1 (n=240), and TET2 (n=157). Mutations were analyzed by a combination of amplicon deep-sequencing (Roche 454, Branford, CT), direct Sanger sequencing, real time PCR or melting curve analyses. Analysis for overall survival was restricted to 185 cases with evaluable clinical data (median follow-up: 427 days, median OS: 51%). Results: In total 633 mutations were detected in 268 patients (median: 2 per patient, range 0–7). In CMML-1 the mean number of mutations was equal to CMML-2 (2.38 vs. 2.55, p=n.s.). In detail, the most frequent mutations were detected in TET2 (61.1%; 96/157), followed by SRSF2 (47.8%; 128/268), ASXL1 (44.7%; 144/255), RUNX1 (22.8%; 61/267), CBL (19.1%; 51/267), NRAS (15.4%; 41/266), KRAS (10.8%; 28/260), EZH2 (9.3%; 19/205), JAK2 (6.7%; 18/268), U2AF1 (5.2%; 14/268), SF3B1 (5.0%; 12/240), and KIT (4.2%; 11/263). Impact on survival was tested for all 12 gene mutations. A significant difference in overall survival (OS) was observed only for ASXL1 mut vs ASXL1 wt patients (median OS: 19.4 months vs not reached; p=0.003). None of the other gene mutations showed a significant impact on OS. In a next step mutations from the RAS pathway (NRAS, KRAS, CBL) were combined into one group (n=85) and were analyzed in comparison to all others (n=90). However, no impact on OS was detected. Next, patients with at least one mutation in a gene from the splicing machinery (U2AF1, SRSF2, SF3B1) (n=109) were combined and tested vs all other patients (n=57), however, no prognostic relevance was found. In addition, no difference in outcome was observed between CMML-1 and CMML-2 patients. Of note, the adverse impact of ASXL1 mut was restricted to the CMML-2 subcohort (25 mut, 31 wt, median OS: 17.3 months vs n.r.; p=0.001), whereas there was no effect in CMML-1 pts (59 mut and 54 wt). We also evaluated the cytogenetic risk score introduced by Such et al. (Haematologica 2011) and were not able to find differences in survival (neither pairwise between the respective subgroups, nor overall). However, we were able to show prognostic impact of ASXL1 mut within the cytogenetic risk groups suggested by Such: within the favorable subgroup ASXL1 mut patients (n=56) had worse outcome than ASXL1 wt (n=65) (median 19.4 months vs n.r.; p=0.027). This was true also for the adverse subgroup showing a trend to worse outcome for ASXL1 mut vs ASXL1 wt (n=16 vs n=9; median 17.3 months vs n.r.; p=0.057). No difference was seen between the 9 ASXL1 mut and 8 ASXL1 wt patients within the intermediate risk group. In the univariable cox regression analysis taking age, gender, type dysplastic vs proliferative, CMML-1 vs CMML-2, WBC, hemoglobin (Hb), Such score and ASXL1 mut into account, the following parameters were found to be relevant for outcome: age (p=0.001, HR 1.74 per decade), WBC (p=0.044, HR 1.08 per 10×109/L), Hb (p<0.001, HR 0.70, ASXL1 mut (p=0.004, HR 2.38). These parameters entered the multivariable analysis and age (p=0.005, HR: 1.61 per 10 yrs of increase), Hb (p<0.001 HR 0.704) and mutated ASXL1 status (p=0.009, HR 2.30) were independent prognostic parameters for OS. Conclusion: 1) CMML-1 as well as CMML-2 are genetically complex diseases each showing a high number of mutations. 2) One of the most frequently mutated genes in both subgroups is ASXL1. 3) ASXL1 is the only one out of 12 genes which is independently associated with adverse outcome. Disclosures: Schnittger: MLL Munich Leukemia Laboratory: Equity Ownership. Meggendorfer:MLL Munich Leukemia Laboratory: Employment. Grossmann:MLL Munich Leukemia Laboratory: Employment. Alpermann:MLL Munich Leukemia Laboratory: Employment. Eder:MLL Munich Leukemia Laboratory: Employment. Kohlmann: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.

High Incidence of RAS Signalling Pathway Mutations in MLL–rearranged Acute Myeloid Leukemia

Blood ◽  
2012 ◽  
Vol 120 (21) ◽  
pp. 539-539
Author(s):  
Vera Grossmann ◽  
Susanne Schnittger ◽  
Alexander Kohlmann ◽  
Christiane Eder ◽  
Annette Fasan ◽  
...  
Keyword(s):  
Survival Data ◽  
De Novo ◽  
Gene Mutations ◽  
Signalling Pathway ◽  
Melting Curve Analysis ◽  
Prognostic Impact ◽  
Tp53 Mutations ◽  
Equity Ownership ◽  
Ras Signalling ◽  
Acute Myeloid

Abstract Abstract 539 Background: Chromosomal translocations of the MLL gene on chromosome 11q23 are associated with a unique subset of acute lymphoblastic or acute myeloid leukemias (AML). In adults, MLL rearrangements are detected in 3% of de novo AML and in 10% of therapy-related AML (t-AML) cases and are associated with poor prognosis. In addition to disease defining mutations recent high-throughput sequencing studies had shown that almost all myeloid malignancies accumulate a large number of cooperating gene mutations. Aim: Determination of somatic mutations occurring in cases harboring MLL rearrangements and investigation of the prognostic impact of molecular and additional chromosomal aberrations. Patients and Methods: We investigated a cohort of 110 adult AML (80 de novo, 30 t-AML) cases harboring an 11q23 translocation. The cohort was composed of 66 females and 44 males; median age: 55.8 years. MLL translocation partners were as follows: MLLT3 (n=46), MLLT4 (n=15), ELL (n=15); MLLT10 (n=8), others (n=26). Chromosome banding analysis data was available in all cases and survival data in 78 cases (median overall survival (OS) was 10.1 months). Patients were screened for mutations in ASXL1 (n=98), CBL (n=62), CEBPA (n=61), FLT3-ITD (n=103), FLT3-TKD (n=95), IDH1 (n=96), IDH2 (n=84), KRAS (n=107), NPM1 (n=101), NRAS (n=106), PTPN11 (n=99), RUNX1 (n=110), and TP53 (n=110) using amplicon deep-sequencing (454 Roche Life Sciences, Branford, CT), direct Sanger sequencing or melting curve analysis. Results: Overall, mutations were detected in 59/110 (53.6%) cases. We discovered that 42/110 (38.2%) MLL-translocated AML cases harbored mutations within the RAS signalling pathway (KRAS mut: 23/107; 21.5%; NRAS mut: 22/106; 20.8%; PTPN11 mut: 3/99, 3.0%) or alterations in the RAS regulating FLT3 gene (FLT3-ITD: 4/103, 3.9%, and FLT3-TKD: 10/95, 10.5%). Additional mutations were detected in the tumor suppressor gene TP53 (8/110; 7.3%), ASXL1 (6/98; 6.1%), RUNX1 (4/110; 3.6%), and IDH1 (1/96). No mutation was detected in IDH2, CBL, CEBPA, and NPM1. Most cases showed only one mutation (n=39, 66.1%), whereas 17 cases (28.8%) showed two and 3 cases (5.1%) three mutations in different genes. No difference of mutation distribution was seen between de novo and t-AML. In this cohort, no associations amongst gene mutations were observed, however, FLT3-ITD was associated with MLL-ELL (3/14 vs 1/89, P=0.008) and PTPN11 mutations with MLLT10-MLL (2/8 vs 1/91, P=0.017) alterations. In addition, KRAS mut and NRAS mut correlated with high WBC count (KRAS mut: 103.0±79 vs 59.2±67 x109/L, P=0.016; NRAS mut: 94.7±57 vs 60.4±72 x109/L, P=0.080). Further, we were interested in the prognostic impact of single gene mutations. NRAS mut and TP53 mut showed both a non-significant inferior impact on OS, i.e. OS after 2 years: 19.1% vs 46.4%, P=0.62; 0% vs 41.3%, P=0.114. Further, TP53 mutations were correlated with shorter event-free survival (EFS) (EFS after 2 years: 0% vs 20.0%, P=0.029). No associations with prognosis were observed for the remaining genes and translocation partners. In contrast, age was associated with OS and EFS (<60 years, n=59 vs ≥60 years, n=51: OS after 2 years: 51.4% vs 26.3%, P=0.003, EFS after 2 years: 28.0% vs 7.7%, P=0.004). Within the cohort of cases ≥60 years, TP53 mutations (n=5) were associated with worse EFS and OS in comparison to TP53 wild-type cases (n=45) (EFS after 2 years: 8.4% vs 0%, P= 0.006; OS after 2 years: 28.5% vs 0%, P=0.045). Of note, no correlations between mutation frequency and age were observed. We next focused on whether the number of mutations showed any impact on survival. This analysis revealed that cases with more than one mutation (n=20) showed shorter EFS (EFS after 2 years: 10.0% vs 27.3%, P=0.020). Finally, we concentrated on AML with t(9;11)(p22;q23)/MLLT3-MLL, recognized as a distinct WHO-entity. We neither detected an association of MLLT3-MLL (n=46) with OS (P=0.445) or EFS (P=0.644) in comparison to the remaining translocation partners nor a distinct gene mutation profile. However, NRAS mutations correlated with shorter OS and EFS in cases with MLLT3-MLL (after 2 years OS: 17.8% vs 48.3%, P=0.045; after 2 years EFS: 17.8% vs 35.2%, P=0.056). Conclusions: In patients with MLL-translocations a high number of secondary alterations (53.6%), predominantly in RAS pathway components (38.2%), were detected. This may have implication on novel therapeutic options in this unfavorable AML subset. Disclosures: Grossmann: MLL Munich Leukemia Laboratory: Employment. Schnittger:MLL Munich Leukemia Laboratory: Equity Ownership. Kohlmann:MLL Munich Leukemia Laboratory: Employment. Eder:MLL Munich Leukemia Laboratory: Employment. Fasan: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.

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