Decitabine Response Associated Gene Expression Patterns In Acute Myeloid Leukemia (AML)

Blood ◽  
2013 ◽  
Vol 122 (21) ◽  
pp. 3756-3756 ◽  
Author(s):  
Stephan R Bohl ◽  
Rainer Claus ◽  
Anna Dolnik ◽  
Richard F. Schlenk ◽  
Konstanze Döhner ◽  
...  
Keyword(s):  
Gene Expression ◽  
Immune Response ◽  
Acute Myeloid Leukemia ◽  
Immune System ◽  
Cell Surface ◽  
Myeloid Leukemia ◽  
Research Funding ◽  
Expression Patterns ◽  
Gene Expression Patterns ◽  
Acute Myeloid

Abstract The hypomethylating agent decitabine (DAC) represents a therapeutic option for acute myeloid leukemia (AML) patients who are not eligible for an intensive treatment regime. However, there are no biomarkers available yet that can predict patients who will likely benefit from this epigenetic therapy. Therefore, we executed a gene expression analysis prior to the treatment of patients with DAC in order to evaluate gene expression patterns associated with response to DAC that ultimately might be used to predict DAC outcome. Patients had been entered in a multicenter phase II trial of DAC as first-line treatment of older AML patients judged unfit for induction chemotherapy (Lübbert et al. Haematologica 2011; NCT00866073). Gene expression was profiled in selected DAC responders (n=17) and non-responders (n=19; non-response was defined as stable disease or progressive disease). These groups did not show significant differences regarding age, gender, performance status, blast counts and cytogenetics. Supervised data analysis strategies were applied to identify genes and gene patterns associated with DAC response. While the study cohort comprised a heterogeneous group of AML patients, a class comparison analysis nevertheless could reveal a DAC response associated gene pattern comprising 301 genes at a significance level of p<0.05. This signature was enriched for genes belonging to pathways that are essential in immune response and tumor suppressor function. Among these genes that were significantly associated with no DAC response included IFI44L, IFI27, PDK4, MX1, FAS, and ITGB2; in contrast to SLC24A3, MUM1, TNFSF9, DBN1, ABAT, and DDX52, which were significantly higher expressed in patients that showed response to DAC treatment. Significantly over-expressed in the DAC non-responder group, the immune and inflammation-related genes IFI44L and IFI27 might reflect a hyperstimulated, but insufficient immune system as has been recently shown in myelofibrosis. As DAC was shown to have the capability to induce cancer testis antigens, thereby generating an efficient immune response with tumor cell lysis by CD8+ T-lymphocytes, an impaired immune system may prevent response to DAC. Furthermore, the non-response signature contained known poor prognostic markers such as PDK4, which has been associated with EVI1 and FLT3-ITD mediated signaling. In addition, we observed high expression of MX1 and FAS in the non-response group. Notably, both genes have been shown to be repressed by promoter hypermethylation in distinct AML subtypes and DAC treatment was able to upregulate their expression levels. In contrast, high pre-treatment expression levels might indicate that in the respective AML cases deregulated promotor methylation might not be the prominent pathomechanism, and thus these cases might less likely benefit from DAC treatment. Finally, we found ITGB2, encoding for an integral cell-surface protein participating in cell-surface mediated signaling, associated with DAC resistance. As recently ITGB3, another member of this integrin protein family, was shown mandatory for leukemogenesis, but not relevant for normal hematopoiesis, high expression of ITGB2 might also play a role in AML and point to leukemias where epigenetic deregulation at the DNA level seems to be a less prone pathomechanism. Among the group of genes linked with response to DAC treatment TNFSF9 can act as cytotoxic leukemic specific T-cell inducer, which has previously been correlated with unfavorable AML subtypes and poor outcome. However, due to the immunomodulation of DAC it seems that the poor prognostic impact of TNFSF9 might be overcome by DAC, thereby rendering TNFSF9 a positive marker for DAC response. In accordance, we found that several genes of the 4-1BB-dependent immune response pathway, including TNFSF9, were more highly expressed in DAC responding patients. Finally, MUM1 encodes also a gene important for interferon dependent immune response, thereby further underscoring a potential immunomodulation effect of DAC. In summary, we were able to elucidate a gene signature which could be used to predict response to DAC treatment in AML. While this gene expression pattern included many genes involved in the immune response, thereby suggesting that the DAC treatment effect is at least in part depending on immunomodulatory effects, further studies are warranted to evaluate the respective markers in larger AML cohorts. Disclosures: Schlenk: Amgen: Research Funding; Pfizer: Research Funding; Novartis: Research Funding; Chugai: Research Funding; Ambit: Honoraria.

Distinct Expression Patterns in Cytogenetically Normal Acute Myeloid Leukemia (CN-AML) Characterized by Uniparental Disomy.

Blood ◽  
2008 ◽  
Vol 112 (11) ◽  
pp. 1193-1193
Author(s):  
Lars Bullinger ◽  
Jan Kronke ◽  
Ursula Botzenhardt ◽  
Sabrina Heinrich ◽  
Katja Urlbauer ◽  
...  
Keyword(s):  
Gene Expression ◽  
Acute Myeloid Leukemia ◽  
Myeloid Leukemia ◽  
Gene Dosage ◽  
Expression Patterns ◽  
Uniparental Disomy ◽  
T Test ◽  
Gene Expression Patterns ◽  
Gene Dosage Effect ◽  
Acute Myeloid

Abstract Genome-wide single nucleotide polymorphism (SNP) analyses have revealed uniparental disomy (UPD) to be a common event in cytogenetically normal acute myeloid leukemia (CN-AML) occurring in approximately 20% of cases. Acquired UPD results in copy number neutral loss of heterozygosity (LOH). Comparing matched tumor and germline DNA samples recurrent acquired UPDs affecting chromosomes 11p and 13q were identified. As DNA microarray-based gene expression profiling (GEP) has recently been shown to powerfully capture the molecular heterogeneity of leukemia, we sought to identify gene expression patterns associated with recurrent UPD in CN-AML. We profiled a set of clinically annotated CN-AML specimens (n=66) entered on a multicenter trial for patients &lt;60 years (AMLSG 07-04) which had been characterized by either 50k or 500k Affymetrix SNP microarrays. All cases were analyzed using Affymetrix microarrays (Human Genome U133 Plus 2.0 Arrays). In this data set we investigated 12 UPDs (affecting chromosomes 1p, 2p, 6p, 11p, 13q and 19q) and applied supervised analyses to define gene-expression patterns associated with UPDs on chromosome 11p and 13q. For the case with an acquired UPD on 19q a gene dosage effect could be demonstrated. Genes located in the 36 Mb large UPD region showed a significantly lower average expression (p&lt;0.001; t-test). Similarly, we observed a gene dosage effect in one of the UPDs observed on chromosome 1 (p=0.0097; t-test), whereas for the other UPDs no significant association between LOH and gene expression levels could be identified. Despite small sample numbers supervised analyses revealed a biologically meaningful gene expression signatures associated with acquired UPD 11p and 13q. In accordance with the association of UPD 13q with FLT3-ITD, the UPD13q gene expression signature was enriched for genes associated with FLT3-ITD. The UPD11p expression pattern was characterized by genes found to be down-regulated in CEBPAmut CN-AML cases, such as down-regulation of homeobox genes HOXA9, HOXA10, HOXB2, and MEIS1. Notably, the UPD11p signature was also characterized by the expression of e.g. UGT2B28, P2RX5, PGDS, CAPN1, NDFIP1, and TRIB2, an expression profile that has been shown to be associated with CEBPAmut CN-AML as well as AML cases with epigenetic CEBPA silencing. Thus, our findings represent a starting point to further dissect CN-AML characterized by recurrent UPD, and ongoing analyses will provide additional insights into leukemia biology.

scholarly journals Distinct gene expression patterns associated with FLT3- and NRAS-activating mutations in acute myeloid leukemia with normal karyotype

Oncogene ◽  
2005 ◽  
Vol 24 (9) ◽  
pp. 1580-1588 ◽  
Author(s):  
Kai Neben ◽  
Susanne Schnittger ◽  
Benedikt Brors ◽  
Björn Tews ◽  
Felix Kokocinski ◽  
...  
Keyword(s):  
Gene Expression ◽  
Acute Myeloid Leukemia ◽  
Myeloid Leukemia ◽  
Expression Patterns ◽  
Normal Karyotype ◽  
Gene Expression Patterns ◽  
Activating Mutations ◽  
Distinct Gene ◽  
Acute Myeloid

scholarly journals Gene expression patterns in acute myeloid leukemia correlate with centrosome aberrations and numerical chromosome changes

Oncogene ◽  
2004 ◽  
Vol 23 (13) ◽  
pp. 2379-2384 ◽  
Author(s):  
Kai Neben ◽  
Björn Tews ◽  
Gunnar Wrobel ◽  
Meinhard Hahn ◽  
Felix Kokocinski ◽  
...  
Keyword(s):  
Gene Expression ◽  
Acute Myeloid Leukemia ◽  
Myeloid Leukemia ◽  
Expression Patterns ◽  
Gene Expression Patterns ◽  
Numerical Chromosome ◽  
Acute Myeloid

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 Predicting Complete Remission of Acute Myeloid Leukemia: Machine Learning Applied to Gene Expression

2019 ◽  
Vol 18 ◽  
pp. 117693511983554 ◽  
Author(s):  
Ophir Gal ◽  
Noam Auslander ◽  
Yu Fan ◽  
Daoud Meerzaman
Keyword(s):  
Gene Expression ◽  
Machine Learning ◽  
Acute Myeloid Leukemia ◽  
Complete Remission ◽  
Myeloid Leukemia ◽  
Statistical Significance ◽  
Expression Patterns ◽  
Pathway Enrichment Analysis ◽  
Data Set ◽  
Acute Myeloid

Machine learning (ML) is a useful tool for advancing our understanding of the patterns and significance of biomedical data. Given the growing trend on the application of ML techniques in precision medicine, here we present an ML technique which predicts the likelihood of complete remission (CR) in patients diagnosed with acute myeloid leukemia (AML). In this study, we explored the question of whether ML algorithms designed to analyze gene-expression patterns obtained through RNA sequencing (RNA-seq) can be used to accurately predict the likelihood of CR in pediatric AML patients who have received induction therapy. We employed tests of statistical significance to determine which genes were differentially expressed in the samples derived from patients who achieved CR after 2 courses of treatment and the samples taken from patients who did not benefit. We tuned classifier hyperparameters to optimize performance and used multiple methods to guide our feature selection as well as our assessment of algorithm performance. To identify the model which performed best within the context of this study, we plotted receiver operating characteristic (ROC) curves. Using the top 75 genes from the k-nearest neighbors algorithm (K-NN) model ( K = 27) yielded the best area-under-the-curve (AUC) score that we obtained: 0.84. When we finally tested the previously unseen test data set, the top 50 genes yielded the best AUC = 0.81. Pathway enrichment analysis for these 50 genes showed that the guanosine diphosphate fucose (GDP-fucose) biosynthesis pathway is the most significant with an adjusted P value = .0092, which may suggest the vital role of N-glycosylation in AML.

Identification of Distinct inv(16) Subclasses in Adult Acute Myeloid Leukemia Based on Gene Expression Profiling.

Blood ◽  
2004 ◽  
Vol 104 (11) ◽  
pp. 2037-2037
Author(s):  
Lars Bullinger ◽  
Claudia Scholl ◽  
Eric Bair ◽  
Konstanze Dohner ◽  
Stefan Frohling ◽  
...  
Keyword(s):  
Gene Expression ◽  
Acute Myeloid Leukemia ◽  
Myeloid Leukemia ◽  
Target Genes ◽  
Expression Patterns ◽  
Rank Test ◽  
Survival Times ◽  
Strong Trend ◽  
Candidate Target ◽  
Acute Myeloid

Abstract Recurrent cytogenetic aberrations have been shown to constitute markers of diagnostic and prognostic value in acute myeloid leukemia (AML). However, even within the well-defined cytogenetic AML subgroup with an inv(16) we see substantial biological and clinical heterogeneity which is not fully reflected by the current classification system. To better characterize this cytogenetic group on the molecular level we profiled gene expression in a series of adult AML patients (n=26) with inv(16) using 42k cDNA microarrays. By unsupervised hierarchical clustering we observed that samples with inv(16) separated primarily into two different subgroups. These showed no significant differences regarding known risk factors like age, WBC, LDH, etc. However, these newly defined inv(16)-subgroups were characterized by distinct clinical behavior. There was a strong trend towards unfavorable outcome with shorter overall survival times in one group (P=0.09, log rank test). Since the primary translocation/inversion events themselves are not sufficient for leukemogenesis, distinct patterns of gene expression found within each of these cytogenetic groups may suggest alternative cooperating mutations and deregulated pathways leading to transformation. Therefore, we performed a supervised analysis to determine the characteristic gene expression patterns underlying the cluster-defined subgroups. This Significance Analysis of Microarrays (SAM) method identified 260 genes significantly differentially expressed between the two newly defined inv(16)-subgroups (false discovery rate = 0.002). High expression levels of JUN, JUNB, JUND, FOS and FOSB characterized the first inv(16) subgroup (having less favorable prognosis). FOS gene family members can dimerize with proteins of the JUN family, forming the transcription factor complex AP-1 which has been implicated in the regulation of cell proliferation, differentiation, and transformation. Among the second subgroup, the proto-oncogene ETS1,displayed elevated expression, possibly resulting from aberrant MEK/ERK pathway activation as these cases also showed an over-expression of MAP3K1 and MAP3K2. In conclusion, both supervised and unsupervised methods provide numerous insights into the pathogenesis of AML with inv(16), identifying clinically significant patterns of gene expression, as well as candidate target genes involved in leukemogenesis.

Gene Expression Profiling Identifies Distinct Subclasses in Core Binding Factor Acute Myeloid Leukemia.

Blood ◽  
2005 ◽  
Vol 106 (11) ◽  
pp. 673-673
Author(s):  
Lars Bullinger ◽  
Stephan Kurz ◽  
Konstanze Dohner ◽  
Claudia Scholl ◽  
Stefan Frohling ◽  
...  
Keyword(s):  
Gene Expression ◽  
Acute Myeloid Leukemia ◽  
Myeloid Leukemia ◽  
Expression Patterns ◽  
The Other ◽  
Rank Test ◽  
Core Binding Factor ◽  
Log Rank Test ◽  
Binding Factor ◽  
Acute Myeloid

Abstract Recurrent cytogenetic aberrations have been shown to constitute markers of diagnostic and prognostic value in acute myeloid leukemia (AML). However, even within well-defined cytogenetic AML subgroups with an inv(16) or a t(8;21) we see substantial biological and clinical heterogeneity which is not fully reflected by the current classification system. Therefore, we profiled gene expression in a large series of adult AML patients with core binding factor (CBF) leukemia [inv(16) n=55, t(8;21) n=38] using a whole genome DNA microarray platform in order to better characterize this disease on the molecular level. By unsupervised hierarchical clustering based on 8556 filtered genes we observed that our CBF leukemia samples separated primarily into three different subgroups. While two of the subgroups were characterized by inv(16) and t(8;21) cases, respectively, the third subgroup contained a mixture of both cytogenetic groups. There was no obvious correlation with known secondary aberrations or molecular marker like FLT3-ITD, NRAS and KIT mutations between the cases in the mixed subgroup and the others. However, the newly defined inv(16)/t(8;21)-subgroup (n=35) was characterized by distinct clinical behavior with shorter overall survival times (P=0.029; log rank test) compared to the other two groups. Unsupervised analyses within the inv(16) and t(8;21) cases also revealed corresponding inv(16) and t(8;21) subgroups with a strong trend towards inferior outcome (P=0.11 and P=0.09, respectively; log rank test). Since the primary translocation/inversion events themselves are not sufficient for leukemogenesis, distinct patterns of gene expression found within each of these cytogenetic groups may suggest alternative cooperating mutations and deregulated pathways leading to transformation. Therefore, we performed a supervised analysis to determine the characteristic gene expression patterns underlying the cluster-defined subgroups. We identified 528 genes significantly differentially expressed between the newly defined inv(16)/t(8;21)-subgroup and the other CBF cases (significance analysis of microarrays, false discovery rate &lt; 0.001). Potential candidates for cooperating pathways characterizing the mixed inv(16)/t(8;21)-subgroup included e.g. AVO3, a member of the mTOR pathway, oncogene homologs like LYN and BRAF, as well as FOXO1A and IL6ST which have been previously identified to correlate with outcome in AML (Bullinger et al., N Engl J Med350:1605, 2004). In conclusion, while the observed signatures remain to be validated for their functional relevance, both supervised and unsupervised methods provide numerous insights into the pathogenesis of CBF AML, identifying clinically significant patterns of gene expression, as well as candidate target genes involved in leukemogenesis.

Inhibition Of LSD1 As a Therapeutic Strategy For The Treatment Of Acute Myeloid Leukemia

Blood ◽  
2013 ◽  
Vol 122 (21) ◽  
pp. 3964-3964 ◽  
Author(s):  
Ryan G. Kruger ◽  
Helai Mohammad ◽  
Kimberly Smitheman ◽  
Monica Cusan ◽  
Yan Liu ◽  
...  
Keyword(s):  
Gene Expression ◽  
Bone Marrow ◽  
Acute Myeloid Leukemia ◽  
Cell Surface ◽  
Growth Inhibition ◽  
Cell Lines ◽  
Myeloid Leukemia ◽  
Stem Cell Differentiation ◽  
Ethical Review Process ◽  
Acute Myeloid

Abstract Lysine specific demethylase 1 (LSD1) is a histone H3K4me1/2 demethylase found in various transcriptional co-repressor complexes. These complexes include Histone Deacetylases (HDAC1/2) and Co-Repressor for Element-1-Silencing Transcription factor (CoREST). LSD1 mediated H3K4 demethylation can result in a repressive chromatin environment that silences gene expression. LSD1 has been shown to play a role in development in various contexts. LSD1 can interact with pluripotency factors in human embryonic stem cells and is important for decommissioning enhancers in stem cell differentiation. Beyond embryonic settings, LSD1 is also critical for hematopoietic differentiation. LSD1 is overexpressed in multiple cancer types and recent studies suggest inhibition of LSD1 reactivates the all-trans retinoic acid receptor pathway in acute myeloid leukemia (AML). These studies implicate LSD1 as a key regulator of the epigenome that modulates gene expression through post-translational modification of histones and through its presence in transcriptional complexes. The current study describes the anti-tumor effects of a novel LSD1 inhibitor (GSK2879552) in AML. GSK2879552 is a potent, selective, mechanism-based, irreversible inhibitor of LSD1. Screening of over 150 cancer cell lines revealed that AML cells have a unique requirement for LSD1. While LSD1 inhibition did not affect the global levels of H3K4me1 or H3K4me2, local changes in these histone marks were observed near transcriptional start sites of putative LSD1 target genes. This increase in the transcriptionally activating histone modification correlated with a dose dependent increase in gene expression. Treatment with GSK2879552 promoted the expression of cell surface markers, including CD11b and CD86, associated with a differentiated immunophenotype in 12 of 13 AML cell lines. For example, in SKM-1 cells, increases in cell surface expression of CD86 and CD11b occurred after as early as one day of treatment with EC50 values of 13 and 7 nM respectively. In a separate study using an MV-4-11 engraftment model, increases in CD86 and CD11b were observed as early as 8 hours post dosing. GSK2879552 treatment resulted in a potent anti-proliferative growth effect in 19 of 25 AML cell lines (average EC50 = 38 nM), representing a range of AML subtypes. Potent growth inhibition was also observed on AML blast colony forming ability in 4 out of 5 bone marrow samples derived from primary AML patient samples (average EC50 = 205 nM). The effects of LSD1 inhibition were further characterized in an in vivo mouse model of AML induced by transduction of mouse hematopoietic progenitor cells with a retrovirus encoding MLL-AF9 and GFP. Primary AML cells were transplanted into a cohort of secondary recipient mice and upon engraftment, the mice were treated for 17 days. After 17 days of treatment, control treated mice had 80% GFP+ cells in the bone marrow whereas treated mice possessed 2.8% GFP positive cells (p<0.012). The percentage of GFP+ cells continued to decrease to 1.8% by 1-week post therapy. Remarkably, in a preliminary assessment for survival, control-treated mice succumbed to AML by 28 days post transplant, while treated mice showed prolonged survival. Together, these data demonstrate that pharmacological inhibition of LSD1 may provide a promising treatment for AML by promoting differentiation and subsequent growth inhibition of AML blasts. GSK2879552 is currently in late preclinical development and clinical trials are anticipated to start in 2014. All studies were conducted in accordance with the GSK Policy on the Care, Welfare and Treatment of Laboratory Animals and were reviewed the Institutional Animal Care and Use Committee either at GSK or by the ethical review process at the institution where the work was performed. Disclosures: Kruger: GlaxoSmithKline Pharmaceuticals: Employment. Mohammad:GlaxoSmithKline Pharmaceuticals: Employment. Smitheman:GlaxoSmithKline Pharmaceuticals: Employment. Liu:GlaxoSmithKline Pharmaceuticals: Employment. Pappalardi:GlaxoSmithKline Pharmaceuticals: Employment. Federowicz:GlaxoSmithKline Pharmaceuticals: Employment. Van Aller:GlaxoSmithKline Pharmaceuticals: Employment. Kasparec:GlaxoSmithKline Pharmaceuticals: Employment. Tian:GlaxoSmithKline Pharmaceuticals: Employment. Suarez:GlaxoSmithKline Pharmaceuticals: Employment. Rouse:GlaxoSmithKline Pharmaceuticals: Employment. Schneck:GlaxoSmithKline Pharmaceuticals: Employment. Carson:GlaxoSmithKline Pharmaceuticals: Employment. McDevitt:GlaxoSmithKline Pharmaceuticals: Employment. Ho:GlaxoSmithKline Pharmaceuticals: Employment. McHugh:GlaxoSmithKline Pharmaceuticals: Employment. Miller:GlaxoSmithKline Pharmaceuticals: Employment. Johnson:GlaxoSmithKline Pharmaceuticals: Employment. Armstrong:Epizyme Inc.: Has consulted for Epizyme Inc. Other. Tummino:GlaxoSmithKline Pharmaceuticals: Employment.

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 Peripheral blood T cells in acute myeloid leukemia (AML) patients at diagnosis have abnormal phenotype and genotype and form defective immune synapses with AML blasts

Blood ◽  
2009 ◽  
Vol 114 (18) ◽  
pp. 3909-3916 ◽  
Author(s):  
Rifca Le Dieu ◽  
David C. Taussig ◽  
Alan G. Ramsay ◽  
Richard Mitter ◽  
Faridah Miraki-Moud ◽  
...  
Keyword(s):  
Gene Expression ◽  
Immune Response ◽  
T Cells ◽  
Acute Myeloid Leukemia ◽  
T Cell ◽  
Peripheral Blood ◽  
Myeloid Leukemia ◽  
Absolute Number ◽  
Immune Synapses ◽  
Acute Myeloid

Abstract Understanding how the immune system in patients with cancer interacts with malignant cells is critical for the development of successful immunotherapeutic strategies. We studied peripheral blood from newly diagnosed patients with acute myeloid leukemia (AML) to assess the impact of this disease on the patients' T cells. The absolute number of peripheral blood T cells is increased in AML compared with healthy controls. An increase in the absolute number of CD3+56+ cells was also noted. Gene expression profiling on T cells from AML patients compared with healthy donors demonstrated global differences in transcription suggesting aberrant T-cell activation patterns. These gene expression changes differ from those observed in chronic lymphocytic leukemia (CLL), indicating the heterogeneous means by which different tumors evade the host immune response. However, in common with CLL, differentially regulated genes involved in actin cytoskeletal formation were identified, and therefore the ability of T cells from AML patients to form immunologic synapses was assessed. Although AML T cells could form conjugates with autologous blasts, their ability to form immune synapses and recruit phosphotyrosine signaling molecules to the synapse was significantly impaired. These findings identify T-cell dysfunction in AML that may contribute to the failure of a host immune response against leukemic blasts.

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