The challenge of risk stratification in acute myeloid leukemia with normal karyotype

Background BCOR gene is a transcription repressor that may influence normal hematopoiesis and is associated with poor prognosis in acute myeloid leukemia (AML) with normal karyotype. However, due to the rare mutation frequency in AML (3.8%-5%), clinical characteristics and prognosis of AML patients with BCOR mutation including abnormal karyotype are still unknown. In addition, the clonal evolution of AML patients with BCOR mutation has not been fully investigated. Methods By means of next generation of sequencing, we performed sequencing of 114 genes related to hematological diseases including BCOR on 509 newly diagnosed AML patients (except for acute promyelocytic leukemia) from March 2017 to April 2019. The 2017 European Leukemia Net (ELN) genetic risk stratification was used to evaluate prognosis. Overall survival (OS) was defined as the time from diagnosis to death or last follow-up. Relapse-free survival (RFS) was measured from remission to relapse or death. Clonal evolution was investigated through analyzing bone marrow samples at diagnosis, complete remission (CR) and relapse from the same patient. Result Among 509 AML patients, we found BCOR mutations in 23 patients (4.5%). BCOR mutations were enriched in patients with mutations of RUNX1 (p = 0.008) and BCORL1 (p = 0.0003). Patients with BCOR mutation were more at adverse ELN risk category compared to patients without BCOR mutation (p = 0.007). Besides, there was a larger proportion of patients with normal karyotype in BCOR mutation group but it had not reached statistical difference (62.5% vs 45.5%, p = 0.064). The abnormal karyotype in patients with BCOR mutations included trisomy 8, t(9;11), inv(3), -7 and complex karyotype.There were no significant differences in age, sex, white blood cell count, hemoglobin or platelet count between the two groups. More patients died during induction (13.0% vs 3.5%, p = 0.56) and fewer patients achieved CR after 2 cycles of chemotherapy when patients had BCOR mutations (69.6% vs 82.5%, p = 0.115) but the difference had not reached statistical difference . Patients with BCOR mutations had inferior 2-year OS (52.1% vs 70.7%, p = 0.0094) and 2-year RFS (29.8% vs 61.1%, p = 0.0090). After adjustment for ELN risk stratification, BCOR mutation was still remain a poor prognostic factor. However, the adverse prognostic impact of BCOR mutation is overcome by hematopoietic stem cell transplantation (HSCT), in which there was no difference between BCOR mutation group and wild type group (p = 0.474) (Figure 1). Through analysis of paired bone marrow sample at diagnosis, remission and relapse, we revealed the clonal evolution that BCOR mutation was only detected at diagnosis sample as a subclone and diminished at CR and relapse while TP53 mutation was only detected at relapse with a variant allele frequency (VAF) of 25.5%. We also found BCOR mutation at another patient's diagnosis and relapse sample while TP53 mutation was detected at relapse with VAF of 11.8%. Conclusion BCOR is associated with RUNX1 mutation and higher ELN risk. AML patients with BCOR mutation including normal and abnormal karyotype conferred a worse impact on OS that can be overcome by HSCT. BCOR mutation is a subclone at diagnosis or relapse in some patients, in which TP53 mutation clone occurred at relapse. Disclosures No relevant conflicts of interest to declare.

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Molecular Characterization of Acute Myeloid Leukemia Patients with Normal Karyotype

Blood ◽

10.1182/blood-2018-99-114782 ◽

2018 ◽

Vol 132 (Supplement 1) ◽

pp. 2809-2809

Author(s):

Aziz Nazha ◽

Manja Meggendorfer ◽

Sudipto Mukherjee ◽

Wencke Walter ◽

Stephan Hutter ◽

...

Keyword(s):

Machine Learning ◽

Acute Myeloid Leukemia ◽

Risk Stratification ◽

Board Of Directors ◽

Myeloid Leukemia ◽

Normal Karyotype ◽

Employment Equity ◽

Advisory Committees ◽

Equity Ownership ◽

Acute Myeloid

Abstract Background Conventional cytogenetic classification remains one of the most important prognostic factors in acute myeloid leukemia (AML). Approximately 50-60 % of patients (pts) with AML have normal karyotype (NK). NK status has traditionally been associated with intermediate risk AML, but actually represents a heterogeneous group with variable outcomes. Adding mutational data such as NPM1, FLT3-ITD, and CEBPa can improve risk stratification for a subset of pts but does not reflect the genomic complexity and mutation interactions that may impact the overall outcome. In this study, we evaluated the association among several mutations and overall survival (OS) in pts with NK AML using unbiased advanced analytics approaches. Method Genomic and clinical data of 2793 primary AML (pAML) pts were analyzed. A panel of 35 genes that are commonly mutated in AML and myeloid malignancies was included. OS was calculated from the time of diagnosis to time of death or last follow up. To study the association of mutations and OS using an unbiased approach, we applied several machine learning algorithms that included random survival forest and recommender system algorithms (machine learning algorithm analogues to Amazon or Netflix recommender systems, in which a customer who buys A and B is likely to buy C; mutations A and B are determined to be likely associated with mutation C). Results Of 2793 pts with pAML, 1352 (48%) had NK and included in the final analysis. The median age of NK pts was 55 years (range, 18-93). Median WBC, hemoglobin, and platelet count at diagnosis were; 21.3 X 109(range, .2-600), 9.1 g/L (range, 2.7-17.6), and 61 X 109 (range, 5-950), respectively. The median number of mutations/sample was 3 (range, 0-7). The most commonly mutated genes were: NPM1 (49%), DNMT3A (37%), FLT3-ITD (24%), CEBPa (19%), TET2 (17%), IDH2 (17%), and RUNX1 (15%). In univariate Cox regression analysis, mutations in NPM1 (HR .81, median OS 58.3 months[m], p= .008), and CEBPa (single mutant, HR, .8, median OS 91.4 m, and double mutant, HR .69, median OS not reached, p < .001, respectively) were all associated with longer OS, while mutations in DNMT3a (HR 1.26, median OS 24 m, p= .003), FLT3-ITD (HR 1.49, median OS 15.2 m, p< .001), TET2 (HR 1.26, median OS 22.3 m, p= .02), RUNX1 (HR 1.36, median OS 22.3 m, p= .003), SRSF2 (HR 1.58, median OS 20.5 m, p< .001), IDH1 (HR 1.29, median OS 20.5 m, p< .001), and ASXL1 (HR 1.89, median OS 15.6 m, p < .001) were associated with shorter OS. The median OS for pts with 0-2 mutations was 59.3 m (95%CI 38.2- 99.1) compared to 34.1m (95%CI 25.3-49.6) for pts with 3-4 mutations and 16.1m (95%CI 12.4- 24.1) for pts with ≥ 5 mutations, p < .001. Association rules identified several combinations of mutations that impacted OS and are summarized in Figure 1. Based on the median OS of each combination, we divided our pt cohort into favorable, intermediate-1, intermediate-2, and unfavorable categories with median OS of 174.9 m (95%CI 79.4-Not reached), 54.8 m (95%CI 28.7-Not reached), 29.2 m (95%CI 22.8-49.6), and 13.8 m (95%CI 12.2-16.1), respectively, p < .001), Figure 1. These findings suggest that the prognostic impact of molecular data on OS in AML pts with NK is limited when using only one or two mutations (in the exception of TP53 mutations which are present in ~ 1% of NK AML pts), Figure 1. For example, pts with NPM1 mutations can have variable OS depending on presence or absence of mutations in other genes. The median OS for pts with NMP1Mut/FLT3-ITDWt/DNMT3AWt(Mut = mutated, Wt = wild type) was 99.1 m compared to 13.4 m for pts with NPM1Mut/FLT3-ITDMut/DNMT3AMut (triple positive), p < .001, Figure 1. Conclusions We developed genomic combinations that can improve the risk stratification of AML pts with NK using unbiased advanced analytic approaches. These combinations can divide patients into 4 risk categories that may aid physicians in treatment decisions. Such approaches account for the impact of individual mutations and the complexity of genomic interactions on outcomes. Figure 1 Figure 1. Disclosures Nazha: MEI: Consultancy. Meggendorfer:MLL Munich Leukemia Laboratory: Employment. Walter:MLL Munich Leukemia Laboratory: Employment. Hutter:MLL Munich Leukemia Laboratory: Employment. Carraway:Balaxa: Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; Agios: Consultancy, Speakers Bureau; Amgen: Membership on an entity's Board of Directors or advisory committees; Celgene: Membership on an entity's Board of Directors or advisory committees, Research Funding, Speakers Bureau; FibroGen: Consultancy; Jazz: Speakers Bureau; Novartis: Speakers Bureau. Maciejewski:Ra Pharmaceuticals, Inc: Consultancy; Alexion Pharmaceuticals, Inc.: Consultancy, Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; Apellis Pharmaceuticals: Consultancy; Ra Pharmaceuticals, Inc: Consultancy; Apellis Pharmaceuticals: Consultancy; Alexion Pharmaceuticals, Inc.: Consultancy, Membership on an entity's Board of Directors or advisory committees, Speakers Bureau. Haferlach:MLL Munich Leukemia Laboratory: Employment, Equity Ownership. Sekeres:Opsona: Membership on an entity's Board of Directors or advisory committees; Celgene: Membership on an entity's Board of Directors or advisory committees; Celgene: Membership on an entity's Board of Directors or advisory committees; Opsona: Membership on an entity's Board of Directors or advisory committees. Haferlach:MLL Munich Leukemia Laboratory: Employment, Equity Ownership.

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Prognostic Gene-Expression Signatures in Adult Acute Myeloid Leukemia with Normal Karyotype.

Blood ◽

10.1182/blood.v106.11.756.756 ◽

2005 ◽

Vol 106 (11) ◽

pp. 756-756

Author(s):

Lars Bullinger ◽

Eric Bair ◽

Raphael Kranz ◽

Konstanze Dohner ◽

Stefan Frohling ◽

...

Keyword(s):

Gene Expression ◽

Overall Survival ◽

Acute Myeloid Leukemia ◽

Risk Stratification ◽

Myeloid Leukemia ◽

Learning Algorithm ◽

Principal Component ◽

Normal Karyotype ◽

Outcome Predictor ◽

Acute Myeloid

Abstract Acute myeloid leukemia (AML) encompasses a large number of morphologically similar but molecularly distinct variants. Recurrent cytogenetic aberrations have been shown to constitute markers of diagnostic and prognostic value. However, despite recent successes in detecting novel molecular markers like FLT3 (fms-related tyrosine kinase 3) mutation, treatment stratification is still difficult, especially for the 40–45% of patients with intermediate-risk, normal karyotype disease. To better characterize AML at the molecular level, and to address the need for improved risk stratification, we recently profiled gene expression in a large series of adult AML patients (Bullinger et al., N Engl J Med350:1605, 2004). By unsupervised analysis we identified new prognostically-relevant AML subgroups, and using a supervised learning algorithm we constructed a gene-expression based outcome predictor, which accurately predicted overall survival across all patients, including for the subset of AML cases normal karyotype. Having demonstrated the presence at diagnosis of normal karyotype signatures correlating with clinical outcome, we have now sought to refine a prognostic signature specific for normal karyotype disease. Towards this goal, we have now profiled 119 samples of adult AML patients with normal karyotype using 42k cDNA microarrays from the Stanford Functional Genomics Facility. By semi-supervised analysis using the supervised principal component method (Bair et al., PLoS Biology2:511, 2004), we built a cross-validated gene-expression based outcome predictor in a randomly partitioned training set (n=60 samples). This outcome signature, comprising only 16 genes, significantly predicted outcome class for normal karyotype samples in the independent test set (n=59 samples; P=0.001). In multivariate analysis, the 16-gene signature was a strong [odds ratio=0.35 (0.13 to 0.91); P=0.01] factor in predicting overall survival, independent of known prognostic factors including FLT3 mutations and preceeding malignancy. Our findings support the utility of expression profiling for improved risk stratification and clinical management of the clinically important subclass of AML patients with normal karyotype disease.

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Role of CD19 and specific KIT‐D816 on risk stratification refinement in t(8;21) acute myeloid leukemia induced with different cytarabine intensities

Cancer Medicine ◽

10.1002/cam4.3705 ◽

2020 ◽

Author(s):

Biao Wang ◽

Bin Yang ◽

Yun Ling ◽

Jihong Zhang ◽

Xiaoying Hua ◽

...

Keyword(s):

Acute Myeloid Leukemia ◽

Risk Stratification ◽

Myeloid Leukemia ◽

Acute Myeloid

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Genomics of Acute Myeloid Leukemia Diagnosis and Pathways

Journal of Clinical Oncology ◽

10.1200/jco.2016.71.2208 ◽

2017 ◽

Vol 35 (9) ◽

pp. 934-946 ◽

Cited By ~ 160

Author(s):

Lars Bullinger ◽

Konstanze Döhner ◽

Hartmut Döhner

Keyword(s):

Acute Myeloid Leukemia ◽

Risk Stratification ◽

Myeloid Leukemia ◽

Clinical Care ◽

Clonal Expansion ◽

Disease Classification ◽

Disease Evolution ◽

Myeloid Neoplasms ◽

Increased Risk ◽

Acute Myeloid

In recent years, our understanding of the molecular pathogenesis of myeloid neoplasms, including acute myeloid leukemia (AML), has been greatly advanced by genomics discovery studies that use novel high-throughput sequencing techniques. AML, similar to most other cancers, is characterized by multiple somatically acquired mutations that affect genes of different functional categories, a complex clonal architecture, and disease evolution over time. Patterns of mutations seem to follow specific and temporally ordered trajectories. Mutations in genes encoding epigenetic modifiers, such as DNMT3A, ASXL1, TET2, IDH1, and IDH2, are commonly acquired early and are present in the founding clone. The same genes are frequently found to be mutated in elderly individuals along with clonal expansion of hematopoiesis that confers an increased risk for the development of hematologic cancers. Furthermore, such mutations may persist after therapy, lead to clonal expansion during hematologic remission, and eventually lead to relapsed disease. In contrast, mutations involving NPM1 or signaling molecules (eg, FLT3, RAS) typically are secondary events that occur later during leukemogenesis. Genetic data are now being used to inform disease classification, risk stratification, and clinical care of patients. Two new provisional entities, AML with mutated RUNX1 and AML with BCR- ABL1, have been included in the current update of the WHO classification of myeloid neoplasms and AML, and mutations in three genes— RUNX1, ASXL1, and TP53—have been added in the risk stratification of the 2017 European LeukemiaNet recommendations for AML. Integrated evaluation of baseline genetics and assessment of minimal residual disease are expected to further improve risk stratification and selection of postremission therapy. Finally, the identification of disease alleles will guide the development and use of novel molecularly targeted therapies.

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Analysis of Efficacy and Prognostic Factors of CLAG Treatment in Chinese Patients with Refractory or Relapsed Acute Myeloid Leukemia

Acta Haematologica ◽

10.1159/000493250 ◽

2018 ◽

Vol 141 (1) ◽

pp. 43-53 ◽

Cited By ~ 4

Author(s):

Li Wang ◽

Jun Xu ◽

Xiaolong Tian ◽

Tingting Lv ◽

Guolin Yuan

Keyword(s):

Acute Myeloid Leukemia ◽

High Risk ◽

Risk Stratification ◽

Salvage Therapy ◽

Myeloid Leukemia ◽

Median Overall Survival ◽

Remission Rate ◽

Chinese Patients ◽

Acute Myeloid

Background/Aims: The aim of this work was to investigate the efficacy and predictive factors of CLAG treatment in refractory or relapsed (R/R) acute myeloid leukemia (AML) patients. Methods: Sixty-seven R/R AML patients were enrolled in this prospective cohort study and treated by a CLAG regimen: 5 mg/m2/day cladribine (days 1–5), 2 g/m2/day cytarabine (days 1–5), and 300 μg/day filgrastim (days 0–5). The median follow-up duration was 10 months. Results: A total of 57 out of 67 patients were evaluable for remission after CLAG therapy, of whom 57.9% achieved a complete remission (CR) and the overall remission rate was 77.2%. The median overall survival (OS) was 10.0 months, with a 1-year OS of 40.3 ± 6.0% and 3-year OS of 16.7 ± 5.7%. CR at first induction after the initial diagnosis was associated with a favorable CR. Age above 60 years, high risk stratification, second or higher salvage therapy, and bone marrow (BM) blasts ≥42.1% were correlated with an unfavorable CR. Secondary disease, age ≥60 years, high risk stratification, and second or higher salvage therapy were associated with worse OS. Patients developed thrombocytopenia (41, 61%), febrile neutropenia (37, 55%), leukopenia (33, 49%), neutropenia (18, 27%), and anemia (9, 13%). Conclusion: CLAG was effective and well tolerated for R/R AML. BM blasts ≥42.1%, age ≥60 years, high risk stratification, and second or higher salvage therapy were independent factors for a poor prognosis.

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