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

Blood ◽  
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.

scholarly journals Prospective Identification of Acute Myeloid Leukemia Patients Who Benefit from Gene-Expression Based Risk Stratification

Blood ◽  
2019 ◽  
Vol 134 (Supplement_1) ◽  
pp. 1397-1397
Author(s):  
Diego Chacon ◽  
Ali Braytee ◽  
Yizhou Huang ◽  
Julie Thoms ◽  
Shruthi Subramanian ◽  
...  
Keyword(s):  
Gene Expression ◽  
Acute Myeloid Leukemia ◽  
Risk Stratification ◽  
Genetic Risk ◽  
Myeloid Leukemia ◽  
Research Funding ◽  
Risk Groups ◽  
High Fidelity ◽  
Improve Outcome ◽  
Acute Myeloid

Background: Acute myeloid leukemia (AML) is a highly heterogeneous malignancy and risk stratification based on genetic and clinical variables is standard practice. However, current models incorporating these factors accurately predict clinical outcomes for only 64-80% of patients and fail to provide clear treatment guidelines for patients with intermediate genetic risk. A plethora of prognostic gene expression signatures (PGES) have been proposed to improve outcome predictions but none of these have entered routine clinical practice and their role remains uncertain. Methods: To clarify clinical utility, we performed a systematic evaluation of eight highly-cited PGES i.e. Marcucci-7, Ng-17, Li-24, Herold-29, Eppert-LSCR-48, Metzeler-86, Eppert-HSCR-105, and Bullinger-133. We investigated their constituent genes, methodological frameworks and prognostic performance in four cohorts of non-FAB M3 AML patients (n= 1175). All patients received intensive anthracycline and cytarabine based chemotherapy and were part of studies conducted in the United States of America (TCGA), the Netherlands (HOVON) and Germany (AMLCG). Results: There was a minimal overlap of individual genes and component pathways between different PGES and their performance was inconsistent when applied across different patient cohorts. Concerningly, different PGES often assigned the same patient into opposing adverse- or favorable- risk groups (Figure 1A: Rand index analysis; RI=1 if all patients were assigned to equal risk groups and RI =0 if all patients were assigned to different risk groups). Differences in the underlying methodological framework of different PGES and the molecular heterogeneity between AMLs contributed to these low-fidelity risk assignments. However, all PGES consistently assigned a significant subset of patients into the same adverse- or favorable-risk groups (40%-70%; Figure 1B: Principal component analysis of the gene components from the eight tested PGES). These patients shared intrinsic and measurable transcriptome characteristics (Figure 1C: Hierarchical cluster analysis of the differentially expressed genes) and could be prospectively identified using a high-fidelity prediction algorithm (FPA). In the training set (i.e. from the HOVON), the FPA achieved an accuracy of ~80% (10-fold cross-validation) and an AUC of 0.79 (receiver-operating characteristics). High-fidelity patients were dichotomized into adverse- or favorable- risk groups with significant differences in overall survival (OS) by all eight PGES (Figure 1D) and low-fidelity patients by two of the eight PGES (Figure 1E). In the three independent test sets (i.e. form the TCGA and AMLCG), patients with predicted high-fidelity were consistently dichotomized into the same adverse- or favorable- risk groups with significant differences in OS by all eight PGES. However, in-line with our previous analysis, patients with predicted low-fidelity were dichotomized into opposing adverse- or favorable- risk groups by the eight tested PGES. Conclusion: With appropriate patient selection, existing PGES improve outcome predictions and could guide treatment recommendations for patients without accurate genetic risk predictions (~18-25%) and for those with intermediate genetic risk (~32-35%). Figure 1 Disclosures Hiddemann: Celgene: Consultancy, Honoraria; Roche: Consultancy, Honoraria, Research Funding; Bayer: Research Funding; Vector Therapeutics: Consultancy, Honoraria; Gilead: Consultancy, Honoraria; Janssen: Consultancy, Honoraria, Research Funding. Metzeler:Celgene: Honoraria, Research Funding; Otsuka: Honoraria; Daiichi Sankyo: Honoraria. Pimanda:Celgene: Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding. Beck:Gilead: Research Funding.

scholarly journals BCOR Mutations in Acute Myeloid Leukemia: Clonal Evolution and Prognosis

Blood ◽  
2020 ◽  
Vol 136 (Supplement 1) ◽  
pp. 4-4
Author(s):  
Ashley Zhang ◽  
Yuntao Liu ◽  
Shuning Wei ◽  
Benfa Gong ◽  
Chunlin Zhou ◽  
...  
Keyword(s):  
Bone Marrow ◽  
Acute Myeloid Leukemia ◽  
Risk Stratification ◽  
Myeloid Leukemia ◽  
Statistical Difference ◽  
Tp53 Mutation ◽  
Clonal Evolution ◽  
Normal Karyotype ◽  
Abnormal Karyotype ◽  
Acute Myeloid

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.

The stem cell-associated gene expression signature allows risk stratification in pediatric acute myeloid leukemia

Leukemia ◽  
2018 ◽  
Vol 33 (2) ◽  
pp. 348-357 ◽  
Author(s):  
Nicolas Duployez ◽  
Alice Marceau-Renaut ◽  
Céline Villenet ◽  
Arnaud Petit ◽  
Alexandra Rousseau ◽  
...  
Keyword(s):  
Gene Expression ◽  
Acute Myeloid Leukemia ◽  
Stem Cell ◽  
Risk Stratification ◽  
Myeloid Leukemia ◽  
Gene Expression Signature ◽  
Pediatric Acute Myeloid Leukemia ◽  
Expression Signature ◽  
Acute Myeloid

Poor Prognosis of Adult Acute Myeloid Leukemia (AML) with High Level of Evi1 and BAALC Transcript.

Blood ◽  
2004 ◽  
Vol 104 (11) ◽  
pp. 2994-2994
Author(s):  
Valeria Biggio ◽  
Selim Corm ◽  
Hugues Leroy ◽  
Stephane De Botton ◽  
Christophe Roumier ◽  
...  
Keyword(s):  
Overall Survival ◽  
Acute Myeloid Leukemia ◽  
Molecular Markers ◽  
Myeloid Leukemia ◽  
Remission Rate ◽  
Prognostic Significance ◽  
Normal Karyotype ◽  
High Expression ◽  
Fab Classification ◽  
Acute Myeloid

Abstract Cytogenetics remain the most powerful prognostic factor in acute myeloid leukemia (AML). However, 50–60 % of those patients (pts) are included in intermediate or unknown karyotypic risk groups. Molecular markers might improve risk classification and recently, 2 groups have reported that the expression of BAALC and EVI1 might be associated with a poor outcome, especially in pts with normal karyotype (Blood.2003;102:1613; Blood2003;101:837). Thus, we retrospectively analyzed the prognostic significance of the expressions level of these genes, by real time quantitative PCR (RQ-PCR) in AML. Patients and methods: 189 adult pts were analyzed: median age was 49 years (range, 19-65), median WBC counts 19 Giga/L (range, 0-602). FAB classification was: M0=22, M1=41,M2=44,M4=37,M5=26,M6=7,M7=1 and unclassified =11. Karyotype was prognostically favorable (n=28), intermediate (n=115, including 80 normal), unfavorable (n=39) and unknown (n=7). All pts received anthracycline-AraC chemotherapy according to French ALFA group multicenter trials (Castaigne et al, Blood 2004; May 13, Epub ahead of print). Complete remission rate was 83 %, median overall survival: 22 months, range 0.1 to 123. RQ-PCR was performed according to the 2 previous paper recommendations. However the housekeeping gene used in this work was TBP (TF2D). Results were expressed using ΔCt method. High levels of EVI1 were defined by ΔCt lower than 11. BAALC (+) pts and (−) pts were defined by ΔCt value lower or higher than 2.45 (ie the median ΔCt for BAALC expression). Results: 24/189 (13%) pts had high expression of EVI1. By comparison to pts without high EVI1 expression, pretreatment variables other than karyotype (including age, WBC counts, FAB classification) were similar in pts with high EVI1 expression. Patients with high EVI1 expression had significantly worse karyotype: none had favorable karyotype, only 4 (17%) had 3q26 abnormalities ((associated with other adverse abnormalities in 3 cases (i.e. -7/7q-)), 3 had 11q23 abnormalities and 9/24 (37.5%) pts normal karyotype. No significant diferencies between pts with high and low EVI1 expression was found for CR rates and DFS, but high EVI1 expression was associated with poorer overall survival ( median:11.7 months versus 26.9 months; p=0.0372). No pretreatment parameters, including karyotype, differed between BAALC (+) (ie pts with BAALC expression lower than the ΔCt median value) and BAALC (−) pts (ie pts with expression greater than the ΔCt median value). Overall CR rate, DFS, OS were similar in BAALC (+) and BAALC (−) pts. However, in the intermediate cytogenetic subgroup (n=115 pts), BAALC (+) pts had lower median DFS (9.7 months versus 19.8 months; p=0.0316) and EFS (4.1 months versus 11.8 months; p=0.0027) than BAALC (−) pts and a trend for poorer OS:16 months versus 27 months (p=0.07). In conclusion: In adult AML patients, high expression of EVI and BAALC are associated with poorer outcome. Determination at diagnosis of the level of those two genes could be helpful for treatment adjustment, especially in the intermediate cytogenetic subgroup. Correlation between EVI1 and BAALC results and those of other molecular markers (CEBPA, RAS, FLT3) mutations will be presented.

Activating FLT3 Mutations Display a Wide Range Of Transforming Potential and a Characteristic Pathway Profile Associated With Prognosis In Acute Myeloid Leukemia

Blood ◽  
2013 ◽  
Vol 122 (21) ◽  
pp. 1312-1312
Author(s):  
Hanna Janke ◽  
Friederike Schneider ◽  
Daniela Schumacher ◽  
Tobias Herold ◽  
Hopfner Karl-Peter ◽  
...  
Keyword(s):  
Gene Expression ◽  
Acute Myeloid Leukemia ◽  
Tyrosine Kinase ◽  
Gene Expression Profile ◽  
Myeloid Leukemia ◽  
Normal Karyotype ◽  
Wide Range ◽  
Flt3 Mutations ◽  
Acute Myeloid

Abstract Background Internal tandem duplication (ITD) and pointmutations in the tyrosine kinase domain (TKD) of the receptor tyrosine kinase FLT3 occur in about 30% of patients with acute myeloid leukemia (AML). In contrast to the negative prognostic impact of FLT3-ITD in normal karyotype AML, FLT3 pointmutations occurring in the TKD and juxtamembrane (JM) region are less frequent and of unclear clinical impact. Although TKD mutations can induce resistance to tyrosine kinase inhibitors the individual transforming potential of FLT3 pointmutations has not been analysed in detail. In this study we have performed a comprehensive analysis of various FLT3 mutants in a comparative setting in vitro and analyzed gene expression profiles, and clinical outcome with respect to FLT3mutation status. Material and Methods We analyzed relapse and survival in 672 cytogenetically normal AML patients and the FLT3 status at diagnosis and relapse in 156 patients. In the murine Ba/F3 cell model we analyzed the transforming potential, subcellular localization, phosphorylation status and signaling properties of eight different FLT3 mutants. The investigated FLT3 mutations include three ITD of different length and insertion site, V592A in the JM region, common FLT3-TKD mutations D835V and D835Y as well as D839G and I867S in the second TKD. FLT3-D839G and -I867S were recently found in AML patients by our group during routine diagnostics but have not been functionally characterized before. The corresponding remission samples did not express these mutations. Further a gene expression profile analysis with respect to FLT3-ITD and -TKD mutation status and evaluation of differences in activation of predefined STAT5 target gene set was performed. Results In 672 normal karyotype AML patients FLT3-ITD, but not FLT3-TKD mutations were associated with an inferior relapse free and overall survival in multivariate analysis. In paired diagnosis-relapse samples FLT3-ITD showed higher stability (70%) compared to FLT3-TKD (30%). In vitro, FLT3-ITD induced a fully transformed phenotype in Ba/F3 cells, whereas FLT3 pointmutations showed a weaker but clearly transformed phenotype with gradual increase in proliferation and protection from apoptosis. The transforming capacity of the investigated mutants was associated with cell surface expression and tyrosine 591 phosphorylation of the FLT3 receptor. Western blot experiments revealed STAT5 activation only in FLT3-ITD transformed cells, further gene expression profile analyses displayed differences in predefined STAT5 target genes between FLT3-ITD and FLT3-TKD mutations. In contrast, FLT3-non-ITD mutants had an enhanced signal of AKT and MAPK activation. Further differences were found on mRNA level presenting deregulation of SOCS2, ENPP2, PRUNE2 and ART3 expression between FLT3-ITD, FLT3-TKD and FLT3-WT. Conclusion Although apparently divergent in response to treatment all functionally characterized mutants showed a clear gain-of-function phenotype with a wide range of transforming activity associated with clinical prognosis and signaling. Disclosures: No relevant conflicts of interest to declare.

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

2008 ◽  
Vol 1 (3) ◽  
pp. 141-158 ◽  
Author(s):  
Syed Z. Zaidi ◽  
Tarek Owaidah ◽  
Fahad Al Sharif ◽  
Said Y. Ahmed ◽  
Naeem Chaudhri ◽  
...  
Keyword(s):  
Acute Myeloid Leukemia ◽  
Risk Stratification ◽  
Myeloid Leukemia ◽  
Normal Karyotype ◽  
Acute Myeloid

Chromosome Aberrations, Gene Mutations and Expression Changes, and Prognosis in Adult Acute Myeloid Leukemia

Hematology ◽  
2006 ◽  
Vol 2006 (1) ◽  
pp. 169-177 ◽  
Author(s):  
Krzysztof Mrózek ◽  
Clara D. Bloomfield
Keyword(s):  
Gene Expression ◽  
Acute Myeloid Leukemia ◽  
Chromosome Aberrations ◽  
Myeloid Leukemia ◽  
Molecular Genetic ◽  
Prognostic Significance ◽  
Gene Mutations ◽  
Normal Karyotype ◽  
Genetic Alterations ◽  
Acute Myeloid

Abstract Pretreatment clinical features and prognosis of patients with acute myeloid leukemia (AML) are strongly influenced by acquired genetic alterations in leukemic cells, which include microscopically detectable chromosome aberrations and, increasingly, submicroscopic gene mutations and changes in gene expression. Cytogenetic findings separate AML patients into three broad prognostic categories: favorable, intermediate and adverse. The cytogenetic-risk classifications differ somewhat for younger adult patients and those aged 60 years or older. In many instances, patients with specific cytogenetic findings, e.g., those with a normal karyotype or those with either t(8;21)(q22;q22) or inv(16)(p13q22)/t(16;16)(p13;q22) [collectively referred to as core-binding factor (CBF) AML] can be further subdivided into prognostic categories based on the presence or absence of particular gene mutations or changes in gene expression. Importantly, many of these molecular genetic alterations constitute potential targets for risk-adapted therapies. In this article, we briefly review major cytogenetic prognostic categories and discuss molecular genetic findings of prognostic significance in two of the largest cytogenetic groups of patients with AML, namely AML with a normal karyotype and CBF AML.

scholarly journals Novel prognostic genes and subclasses of acute myeloid leukemia revealed by survival analysis of gene expression data

2021 ◽  
Vol 14 (1) ◽  
Author(s):  
Yanli Lai ◽  
Guifang OuYang ◽  
Lixia Sheng ◽  
Yanli Zhang ◽  
Binbin Lai ◽  
...  
Keyword(s):  
Gene Expression ◽  
Overall Survival ◽  
Acute Myeloid Leukemia ◽  
Network Analysis ◽  
Risk Score ◽  
Myeloid Leukemia ◽  
The Cancer Genome Atlas ◽  
Prognostic Biomarkers ◽  
High Expression ◽  
Acute Myeloid

Abstract Background Acute myeloid leukemia (AML) is biologically heterogeneous diseases with adverse prognosis. This study was conducted to find prognostic biomarkers that could effectively classify AML patients and provide guidance for treatment decision making. Methods Weighted gene co-expression network analysis was applied to detect co-expression modules and analyze their relationship with clinicopathologic characteristics using RNA sequencing data from The Cancer Genome Atlas database. The associations of gene expression with patients’ mortality were investigated by a variety of statistical methods and validated in an independent dataset of 405 AML patients. A risk score formula was created based on a linear combination of five gene expression levels. Results The weighted gene co-expression network analysis detected 63 co-expression modules. The pink and darkred modules were negatively significantly correlated with overall survival of AML patients. High expression of FNDC3B, VSTM1 and CALR was associated with favourable overall survival, while high expression of PLA2G4A was associated with adverse overall survival. Hierarchical clustering analysis of FNDC3B, VSTM1, PLA2G4A, GOLGA3 and CALR uncovered four subgroups of AML patients. The cluster1 AML patients showed younger age, lower cytogenetics risk, higher frequency of NPM1 mutations and more favourable overall survival than cluster3 patients. The risk score was demonstrated to be an indicator of adverse prognosis in AML patients Conclusions The FNDC3B, VSTM1, PLA2G4A, GOLGA3, CALR and risk score may serve as key prognostic biomarkers for the stratification and ultimately guide rational treatment of AML patients.

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