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.

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

A Precision Medicine Approach Incorporating Both Molecular and In Vitro Functional Data to Treat Patients with Relapsed/Refractory Acute Myeloid Leukemia

Blood ◽  
2016 ◽  
Vol 128 (22) ◽  
pp. 4043-4043
Author(s):  
Pamela S. Becker ◽  
Sylvia Chien ◽  
Timothy J Martins ◽  
Andrew Herstein ◽  
Cody Hammer ◽  
...  
Keyword(s):  
Gene Expression ◽  
Acute Myeloid Leukemia ◽  
Precision Medicine ◽  
Myeloid Leukemia ◽  
Research Funding ◽  
Expression Data ◽  
Allogeneic Transplant ◽  
Choice Of Treatment ◽  
Acute Myeloid

Abstract Introduction: Acute myeloid leukemia (AML) is a heterogeneous disorder such that each patient exhibits a unique pattern of mutations. Nevertheless, standard treatment approaches are largely used for all patients with the exception of those with the PML-RARA translocation or FLT3 mutations. We are conducting a feasibility study, "Individualized Treatment for Relapsed/Refractory Acute Leukemia Based on Chemosensitivity and Genomics/Gene Expression Data" (NCT02551718). This abstract summarizes the results in the AML patients. . Methods: The primary objective of this trial is to test the feasibility of rapidly assessing patient cells using a high throughput assay for in vitro drug sensitivity with individual drugs and drug combinations and mutation profiling by next generation sequencing (NGS) of 194 genes (MyAML) to enable prompt initiation of optimal therapy. The secondary objective is to evaluate the response to the chosen therapy. The eligibility criteria include diagnosis of acute leukemia, age ≥ 3, relapsed after or refractory to 2 prior lines of therapy, ECOG ≤ 3, and adequate organ function. The high throughput screen (HTS) is performed at a core facility under CLIA. The custom Oncopanel1 contains 160 drugs and drug combinations, including FDA approved and investigational agents, targeted agents including kinase, mTOR, proteasome, HDAC and other inhibitors, and chemotherapy drugs including alkylators, purine analogs, topoisomerase inhibitors and others. Patient blood or marrow samples enriched for leukemia cells are analyzed for survival after a 72-hour exposure to 8 customized drug concentrations spanning 4 logs in duplicate in 384 well plates adherent to matrix protein. DNA and RNA are isolated from the same enriched cell fractions for NGS (MyAML) and RNAseq. MyAML analyzes genes at high depth, including breakpoint hotspot loci with optimized detection of large insertion and deletions and other structural variants found in AML. Results: Fourteen patients signed consent, and 11 AML patients were enrolled in the study to date. Seven patients had unfavorable and 4 intermediate cytogenetic risk. Four were primary refractory, 5 had antecedent hematologic disorder. The average number of prior regimens was 4 (range 2 to 6). Six patients had relapsed within ≤3 months after allogeneic transplant, prior to enrollment on this study. HTS results were obtained within an average of 5.5 days; mutation testing was obtained within an average of 13 days (range 9-17), return time after receipt at MyAML was on average 8 (range 7-12) days. Drug regimens were chosen within 1-2 weeks from testing. For 2 patients, treatment start was delayed by about one month to allow recovery from toxicity from prior therapy. For the other patients, treatment was initiated on average 7.8, median 8 (range 4-11) days from start of testing. Of 7 patients treated so far, the median overall survival was 171 days, range 70 to >289 days. Regimens chosen based on HTS results, mutation analysis, and ability to obtain FDA approved drugs off label included: bortezomib (B)/daunorubicin/cytarabine, romidepsin, B/azacitidine (Aza), B/idarubicin (2 patients),cladribine, omacetaxine (HHT) then HHT/cytarabine, B/Aza/sorafenib, gemcitabine, bortezomib, sorafenib. Mutation analysis revealed previously unknown potential targets in those patients, including ABL kinase, FLT3 ITD in 2 patients, and FLT3 TKD mutations that led to choice of treatment with imatinib, sorafenib, and investigational Flt3 inhibitor for 4 patients, respectively. Other potentially targetable mutations identified included IDH1/2, NRAS, KRAS, KIT, TP53, WT1, and others (Table). None of these very heavily pre-treated patients obtained a complete remission, but 3 remain alive > 1 yr post early relapse after allogeneic transplant. One patient's marrow exhibited decline in blasts from 82% to 24%, and all patients exhibited a decline in circulating blasts with the chosen treatments. Conclusion: This trial has proven that application of rapid molecular and functional screening to choice of treatment for patients with advanced acute myeloid leukemia is feasible. Direct comparison of this precision medicine approach to results obtained with standard trials is planned. These data and the responses and correlation with gene expression data will contribute to a future algorithm to optimize precision medicine approaches to leukemia therapy. Table Table. Disclosures Becker: JW Pharmaceutical: Research Funding; Millennium: Research Funding; Glycomimetics: Research Funding; Pfizer: Other: Scientific Steering Committee for a post marketing study; Amgen: Research Funding; CVS Caremark: Other: Accordant Health Services Medical Advisory Board; Abbvie: Research Funding; Invivoscribe: Honoraria. Patay:Invivoscribe, Inc: Consultancy. Carson:Invivoscribe, Inc: Employment. Radich:Novartis: Consultancy, Other: laboratory contract; Bristol-MyersSquibb: Consultancy; TwinStrand: Consultancy; ARIAD: Consultancy; Pfizer: Consultancy.

scholarly journals Identification of Prognostic Signature Based on the Copy Number Variation (CNV) and Expression in Acute Myeloid Leukemia

2020 ◽  
Author(s):  
Changchun Niu ◽  
Di Wu ◽  
Alexander J. Li ◽  
Kevin H. Qin ◽  
Daniel A. Hu ◽  
...  
Keyword(s):  
Gene Expression ◽  
Acute Myeloid Leukemia ◽  
Survival Analysis ◽  
Copy Number Variation ◽  
Copy Number ◽  
Myeloid Leukemia ◽  
Risk Groups ◽  
Number Variation ◽  
Acute Myeloid ◽  
Cancer Panel

Abstract Purpose Acute myeloid leukemia (AML) is caused by multiple genetic alterations in the hematopoietic progenitors, and molecular genetic analysis has provided useful information for AML diagnosis and prognosis. However, an integrative understanding about the prognosis value of specific copy number variation (CNV) and CNV-modulated gene expression has been limited. Methods We conducted an integrative analysis of CNV profiling and gene expression using data from the TARGET and TCGA AML cohorts. The CNV data from TCGA were analyzed using the GISTIC. CNV survival analysis and mRNA survival analysis were conducted with the Multivariate Cox proportional hazards regression model using R software with “survminer” and “survival” packages. KEGG cancer panel genes were extracted from the cancer related pathways from Kyoto Encyclopedia of Genes and Genomes (KEGG). The R package “circlize” was used for mapping the CNV genes to chromosomes. Results From this investigation, we observed distinct CNV patterns in the AML risk groups as well as the expression of 251 genes significantly modulated by CNV in both cohorts. There were 102 CNV genes (located at 7q31-34, 16q24) associated with clinical outcomes in AML, which were identified in the TARGET cohort and validated in the TCGA cohort, three of which being miRNA genes (MIR29A, MIR183, MIR335) that overlapped with a KEGG cancer panel. Five genes were identified whose expressions were modulated by CNV and significantly associated with clinical outcomes, and among them, the deletion of SEMA4D and CBFB were found to potentially have protective effects against AML. Moreover, the distribution of CNV in these five CNV-modulated genes was independent of the risk groups, which suggests that they are independent prognosis factors. Conclusion Overall, this study identified 102 CNV genes and five CNV-modulated gene expressions that are crucial for developing new modes of prognosis evaluation and target therapy for AML.

scholarly journals DNA Methyltransferase Inhibitors Promote Homologous Recombination Deficiency through Induction of Immune Signaling, Sensitizing Acute Myeloid Leukemia Cells to PARP Inhibitors

Blood ◽  
2019 ◽  
Vol 134 (Supplement_1) ◽  
pp. 3763-3763
Author(s):  
Aksinija A Kogan ◽  
Lena J Mclaughlin ◽  
Maria R. Baer ◽  
Stephen Baylin ◽  
Michael Topper ◽  
...  
Keyword(s):  
Gene Expression ◽  
Acute Myeloid Leukemia ◽  
Homologous Recombination ◽  
Myeloid Leukemia ◽  
Research Funding ◽  
Dna Methyltransferase ◽  
Immune Signaling ◽  
Dna Methyltransferase Inhibitors ◽  
Acute Myeloid

Acute myeloid leukemia (AML) patients unfit for intensive chemotherapy are treated with DNA methyltransferase inhibitors (DNMTis). However, while many AML patients respond to DNMTis, responses are not durable. We previously reporteda novel treatment strategy for AML that combines DNMTis with poly (ADP-ribose) polymerase inhibitors (PARPis), drugs classically used to treat breast and ovarian cancer patients with BRCA mutations and homologous recombination defects (HRD) (Faraoni and Graziani, 2018). We found that combining low doses of the potent PARP-trapping PARPi talazoparib with DNMTis increases PARP trapping and cytotoxicityin vitroand increases therapeutic efficacy in vivo (Muvarak et al, 2016). We have nowidentified a novel mechanism through which DNMTis may sensitize BRCA-proficient AML cells to PARPis. This mechanism is tied to the capacity of these drugs to reprogram cancer signaling networks, including altering DNA repair pathways (Tsai et al, 2012). In studies in AML cell lines (N=6) and peripheral blood mononuclear cells (PBMCs) from AML patients (N=4), we now show that treatment with the DNMTi decitabine (DAC) at a low concentration (10nM) can directly induce HRD, by significantly (p<0.01) down-regulating key genes central to HR activity, including multiple genes in the Fanconi anemia (FA) pathway, as a mechanism for enhanced PARPi sensitivity. How do DNMTis downregulate HR gene expression? We show for the first time that immune signaling is linked to induction of HRD. We have previously shown that DNMTis activate innate immune pathways involving interferon (IFN) □ and tumor necrosis factor (TNF) □, a phenomenon known as viral mimicry (Chiappinelli et al, 2015).First, The Cancer Genome Atlas (TCGA) AML data sets show an inverse correlation between type 1 interferon (IFN)/pro-inflammatory response and HR-related genes. Second, we verified in BRCA-proficient AML cell lines (N=6) that immune signaling by exogenous TNF□□or IFN□□treatment decreases HR gene expression and activity by more than two-fold for the majority of genes tested (p<0.0001). Third, treatment of AML cells with IFN□and the signal transducer and activator of transcription (STAT) 1/3 inhibitor ruxolitinib can rescue DAC-induced HRD. Importantly, we identified a common immune signaling pathway induced by both DNMTis and PARPis. PARPis have also been shown to activate type 1 IFN pathways via induction of cytoplasmic double-stranded DNA sensing through signaling of the cyclic GMP-AMP Synthase - Stimulator of Interferon Genes(cGAS-STING) pathway. We now find that inhibition of STING with inhibitor H-151 (500nM) not only rescues immune signaling induced by PARPi, but also by DAC and PARPi combination treatment. Moreover, the STING inhibitor also rescues DAC- and/or PARPi-induced HRD. These data suggest that STING may be a central signaling hub linked to HRD and also suggest ways in which epigenetic therapy, inhibitors of DNA damage response proteins, and targeted immune therapy can synergize to treat AML. Disclosures Baer: Takeda: Research Funding; Incyte: Research Funding; Kite: Research Funding; Forma: Research Funding; AI Therapeutics: Research Funding; Abbvie: Research Funding; Astellas: Research Funding.

scholarly journals PTPN11 mutations and Outcomes in Adult Patients with Acute Myeloid Leukemia

Blood ◽  
2020 ◽  
Vol 136 (Supplement 1) ◽  
pp. 4-5
Author(s):  
Klaus H. Metzeler ◽  
Maja Rothenberg-Thurley ◽  
Dennis Görlich ◽  
Maria Cristina Sauerland ◽  
Annika Maria Dufour ◽  
...  
Keyword(s):  
Acute Myeloid Leukemia ◽  
Genetic Risk ◽  
Myeloid Leukemia ◽  
Research Funding ◽  
Risk Group ◽  
Newly Diagnosed ◽  
Wild Type ◽  
Prognostic Relevance ◽  
Multivariable Models ◽  
Acute Myeloid

Background: Mutations in the protein tyrosine phosphatase gene PTPN11 (also known as SHP2) are found in approximately 10% of adult patients with acute myeloid leukemia (AML). A recent study reported that mutated PTPN11 associates with inferior response rates and shorter survival among intensively treated AML patients, independently of the ELN prognostic groups (Alfayez et al., Leukemia 2020). Earlier analyses of the genomic landscape of AML did not uncover a similar prognostic relevance of PTPN11 mutations. Therefore, our aim was to clarify the prognostic relevance of mutated PTPN11 variants in AML patients receiving intensive front-line therapy. Patients and Methods: We studied 1116 AML patients enrolled on two subsequent multicenter phase III trials of the German AML Cooperative Group (AML-CG 1999, NCT00266136; and AML-CG 2008, NCT01382147) who were genetically characterized by amplicon-based targeted next-generation sequencing (Herold et al., Leukemia 2020). All patients had received induction chemotherapy containing cytarabine and daunorubicin or mitoxantrone. Results: We identified 146 PTPN11 mutations in 114 of 1116 patients (10%). Mutations clustered in two hotspot regions (5': codons 52-79; n=108 and 3': codons 491-512, n=38) as previously reported. Associations of PTPN11 mutations with baseline clinical and genetic patient characteristics are shown in Figure A. PTPN11 mutations were most frequent in the European LeukemiaNet (ELN) "favorable" genetic risk group, and associated with higher leukocyte counts. Patients with mutated PTPN11more commonly had mutated NPM1, IDH1 and DNMT3A, and less frequently had FLT3-ITD, IDH2 and TP53 mutations, compared to patients with wild-type PTPN11. With regard to treatment outcomes, the rate of complete remission was similar among patients with mutated and wild-type PTPN11 (65% vs. 59%, P=.25). In univariate analyses, PTPN11-mutated patients had significantly longer relapse-free survival (RFS; 5-year estimate, 55% vs 33% for PTPN11-wild type patients; P=.001; Figure B) and tended to have longer overall survival (OS; 5-year estimate, 43% vs 32%; P=.06; Figure C). However, in multivariable models adjusting for age, sex, leukocyte count, AML type (de novo/sAML/tAML) and ELN-2017 genetic risk group, mutated PTPN11 no longer associated with RFS (hazard ratio [HR], 0.89, 95% confidence interval [CI], 0.63 - 1.27; P=0.53) or OS (HR, 1.03; 95% CI, 0.80 - 1.33; P=.79). Moreover, PTPN11 mutations did not significantly associate with RFS or OS within any of the ELN genetic risk groups. Finally, we detected no significant differences in baseline characteristics or outcomes between patients with PTPN11 mutations affecting the 5' hotspot region (n=82), the 3' hotspot region (n=21), or mutations at both hotspots (n=11). Conclusion: In our cohort of newly diagnosed and intensively treated AML patients, mutations in PTPN11 occurred in 10% and associated with prognostically favorable genetic characteristics such as mutated NPM1 and absence of FLT3-ITD and TP53mutations. Consequently, PTPN11 mutations were most commonly found within the ELN-2017 favorable risk category. While patients with PTPN11 mutations had relatively favorable survival outcomes, multivariable models suggest this observation is confounded by the frequent co-occurrence of known favorable genetic markers. Our data are in disagreement with a recently published study on 880 newly diagnosed patients that found an unfavourable prognostic impact of mutated PTPN11, particularly among the 410 patients who received intensive treatment. Possible explanations for these discrepant results include differences in treatment regimens between the two cohorts, as well as the play of chance when studying a relatively rare gene mutation in medium-sized cohorts. In summary, our data do not support a role of PTPN11 mutations as an adverse prognostic biomarker in newly diagnosed, intensively treated adult AML patients. Figure Disclosures Metzeler: Daiichi Sankyo: Honoraria; Otsuka Pharma: Consultancy; Pfizer: Consultancy; Celgene: Consultancy, Honoraria, Research Funding; Novartis: Consultancy; Jazz Pharmaceuticals: Consultancy; Astellas: Honoraria. Subklewe:AMGEN: Consultancy, Honoraria, Research Funding; Celgene: Consultancy, Honoraria; Pfizer: Consultancy, Honoraria; Novartis: Consultancy, Research Funding; Janssen: Consultancy; Morphosys: Research Funding; Seattle Genetics: Research Funding; Roche AG: Consultancy, Research Funding; Gilead Sciences: Consultancy, Honoraria, Research Funding.

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.

The Prognostic Impact of the Revised IPSS Cytogenetic Scoring System for Patients with MDS Allows a Risk-Stratification for Patients with MDS-Derived Acute Myeloid Leukemia

Blood ◽  
2012 ◽  
Vol 120 (21) ◽  
pp. 1715-1715
Author(s):  
Friedrich Stölzel ◽  
Michael Kramer ◽  
Brigitte Mohr ◽  
Martin Wermke ◽  
Martin Bornhäuser ◽  
...  
Keyword(s):  
Acute Myeloid Leukemia ◽  
Risk Stratification ◽  
Scoring System ◽  
Myeloid Leukemia ◽  
De Novo ◽  
Risk Groups ◽  
Prognostic Impact ◽  
Poor Risk ◽  
The Impact ◽  
Acute Myeloid

Abstract Abstract 1715 Besides cytopenias and the medullary blast count, cytogenetic risk groups (good vs. intermediate vs. poor) according to IPSS are of main prognostic relevance for overall survival (OS) in patients with myelodysplastic syndrome (MDS). Recently, the revised IPSS (rIPSS) was introduced involving 5 (very good vs. good vs. intermediate vs. poor vs. very poor) instead of 3 cytogenetic risk groups, which better predict disease progression to MDS-derived acute myeloid leukemia (mdsAML) and OS of MDS patients receiving supportive care only. We analyzed the impact of the rIPSS-based cytogenetic scoring systems on the outcome of patients with AML undergoing intensive chemotherapy within the AML96, AML2003, and AML60+ trials of the Study Alliance Leukemia (SAL). This was done in an intention to compare its general prognostic influence as well as between patients with mdsAML and those with a de novo disease (dnAML). A total of 258 patients (median age 63 years, range 24 – 82) with mdsAML were identified and 258 patients with dnAML were matched with regards to age, gender, clinical trial, induction and consolidation therapy, respectively. Distributions of the cytogenetics in both groups according to MRC, IPSS and rIPSS score are shown in Table 1. Expectedly, the MRC cytogenetic scoring system revealed a stratification into two risk groups for patients with mdsAML with intermediate (3-year OS 27%) and adverse (3-year OS 10%), p=.004, and stratification into three groups for dnAML with favorable (3-year OS 50%), intermediate (3-year OS 32%) and adverse (3-year OS 10%), p=.001. When using the new rIPSS, this allowed a stratification of mdsAML patients with a 3-year OS of 28% for good+intermediate, 12% for poor, and 2% for very poor, p<.001, compared to 28% for good, 22% for intermediate, and 7% for poor risk cytogenetics according to the IPSS, p=.002. Importantly, the rIPSS allowed for a refined subdivision of patients within the poor and very poor group. By applying the rIPSS in dnAML patients we observed a 3-year OS of 34% for good+intermediate, 22% for poor, and 11% for very poor, p<.001, compared to 37% for good, 23% for intermediate, and 19% for poor risk cytogenetics according to the IPSS, p=.028. In conclusion, the rIPSS and IPSS-based classifications are feasible for prognostic risk stratification of patients with both dnAML and mdsAML. Interestingly, the rIPSS-based good and intermediate risk groups do not separate patients in both groups sufficiently. Furthermore, the rIPSS as compared to the current MRC-based cytogenetic scoring system allowed for a more concise distribution of mdsAML patients with the detection of a very poor (rIPSS) risk group with a dismal outcome. Table 1. dnAML, n=258 (%) mdsAML, n=258 (%) Cytogenetics MRC AML Good 16 (7) 0 Intermediate 210 (81) 179 (69) Poor 32 (12) 79 (31) Cytogenetics IPSS Good 158 (61) 121 (47) Intermediate 59 (23) 79 (31) Poor 41 (16) 58 (22) Cytogenetics rIPSS Very good 0 0 Good 167 (65) 131 (51) Intermediate 47 (18) 53 (20) Poor 18 (7) 34 (13) Very poor 26 (10) 40 (15) Disclosures: Platzbecker: Novartis: Consultancy; Celgene: Consultancy; GlaxoSmithKline: Consultancy; Amgen: Consultancy.

The Actin Binding Protein Plastin-3 Is Involved in the Pathogenesis of Acute Myeloid Leukemia

Blood ◽  
2016 ◽  
Vol 128 (22) ◽  
pp. 1662-1662
Author(s):  
Arne Velthaus ◽  
Kerstin Cornils ◽  
Saskia Grüb ◽  
Hauke Stamm ◽  
Daniel Wicklein ◽  
...  
Keyword(s):  
Gene Expression ◽  
Acute Myeloid Leukemia ◽  
Stromal Cells ◽  
Myeloid Leukemia ◽  
Research Funding ◽  
Binding Protein ◽  
Actin Binding ◽  
Actin Binding Protein ◽  
Mutational Status ◽  
Acute Myeloid

Abstract Leukemia-initiating cells reside within the bone marrow (BM) in specialized niches where they undergo complex interactions with their surrounding stromal cells. In order to identify genes being implicated in the interaction of acute myeloid leukemia (AML) cells and stromal cells, we performed co-cultures of primary AML cells with primary endothelial cells and osteoblasts. The gene expression of co-cultured AML blasts was compared to AML cells grown without adherent cells using microarray analysis. Amongst those genes being dysregulated upon co-culture was the actin binding protein plastin-3 (PLS3). Further RT-qPCR analysis revealed an endogenous PLS3 expression in about 50% of BM samples from AML patients (n=25). In contrast, expression of PLS3 was only detected in 2 of 12 analyzed AML cell lines with Kasumi-1 showing strong and THP-1 showing only weak expression. Therefore, functional analysis of PLS3 in AML was studied using shRNA knockdown and overexpression of PLS3 in Kasumi-1 cells. We could show that PLS3 has an impact on the colony formation capacity of AML cells in vitro as the knockdown resulted in significantly reduced colony numbers while increased colony growth was observed in the Kasumi-1 cells overexpressing PLS3 (p<0.001 and p<0.001, respectively). To investigate the role of PLS3 in vivo, NSG mice were transplanted with the PLS3 knockdown Kasumi-1 cells. Compared to mice transplanted with Kasumi-1 cells transduced with a vector carrying a scrambled shRNA, the PLS3 knockdown mice survived significantly longer (median survival time 64 vs. 110 days, respectively; p<0.001; n=9 mice per group). Finally, we investigated whether the expression of PLS3 was associated with AML patients' outcome using published microarray-based gene expression data (Verhaak et al, Haematologica 2009;94). Clinical data of 290 AML patients were available. Based on the mean gene expression value, the patient cohort was divided into high vs low PLS3 expressors. The overall survival was analyzed in a multivariate Cox proportional hazards model including PLS3 gene expression and the baseline parameters age, karyotype and FLT3 mutational status. After a stepwise removal of insignificant terms, the patient's age and a high PLS3 expression remained as independent prognostic survival markers (for PLS3: HR 1.58 (CI 1.05 - 2.37) and for age: HR 1.01 (CI 1.00 - 1.03)). In conclusion, our results identify the actin binding protein PLS3 as potential novel therapeutic target in AML. Disclosures Stamm: Astellas: Other: Travel, Accommodation, Expenses. Heuser:BerGenBio: Research Funding; Tetralogic: Research Funding; Novartis: Consultancy, Research Funding; Celgene: Honoraria; Bayer Pharma AG: Research Funding; Pfizer: Research Funding; Karyopharm Therapeutics Inc: Research Funding. Fiedler:Kolltan: Research Funding; Ariad/Incyte: Consultancy; Novartis: Consultancy; Gilead: Other: Travel; Teva: Other: Travel; GSO: Other: Travel; Pfizer: Research Funding; Amgen: Consultancy, Other: Travel, Patents & Royalties, Research Funding. Wellbrock:Astellas: Other: Travel, Accommodation, Expenses.

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