Inhibition of the Epigenetic Modifier EZH2 Upregulates Cell Cycle Control Genes to Inhibit Myeloma Cell Growth and Overcome High-Risk Disease Features

Blood ◽  
2016 ◽  
Vol 128 (22) ◽  
pp. 3289-3289 ◽  
Author(s):  
Charlotte Pawlyn ◽  
Michael Bright ◽  
Amy Buros ◽  
Caleb K. Stein ◽  
Zoe Walters ◽  
...  
Keyword(s):  
Gene Expression ◽  
Cell Cycle ◽  
High Risk ◽  
Cell Lines ◽  
Research Funding ◽  
Cell Cycle Control ◽  
Myeloma Cell ◽  
Expression Arrays ◽  
Molecular Features ◽  
High Risk Disease

Abstract Introduction High expression of the H3K27 histone methyltransferase EZH2 mRNA in myeloma (MM) patient samples is associated with molecular features of high risk disease, including increased proliferation, and adverse outcomes (1). Mutations or deletions in the H3K27 demethylase KDM6A are associated with similar findings (2) and would be expected to have the same epigenetic effect, increasing H3K27me3 levels, a mark associated with repression of gene expression. We, therefore, sought to identify the role EZH2 plays in controlling myeloma cell proliferation. Methods A panel of MM cell lines and primary patient samples (CD138 selected from bone marrow with consent) representing a variety of different MM molecular subgroups were used. Cell viability (WST-1), cell cycle (PI) and apoptosis (AnnexinV/PI, Caspase-Glo 3/7) assays were performed. Affymetrix gene expression arrays followed by validation with RT-PCR were used to identify patterns of gene expression change with EZH2i. Western blotting confirmed changes at the protein level and Chip-PCR was performed using a validated antibody and isotype control to identify H3K27me3 changes at the relevant gene promotors. Affymetrix gene expression data for 1213 patients enrolled in the Total Therapy studies were used to investigate the relevance of our findings in myeloma patient samples. Results We confirmed a reduction in viability following EZH2i using two chemically distinct, specific small molecule inhibitors (EPZ005687 and UNC1999) and the negative control compound UNC2400. There was a reduction in viability in 6/8 cell lines and 5/6 patient samples. Response to inhibition was not related to molecular subgroup or the presence of high-risk molecular features including del17p. Global levels of H3K27me3 measured by Western blot were reduced in all cell lines regardless of response to EZH2i. In responding cell lines EZH2i induced cell cycle arrest at G1/S followed by induction of apoptosis. Gene expression arrays performed using mRNA from KMS11 and KMM1 cell lines highlighted a change in expression of cell cycle control genes associated with EZH2i. This finding was validated using qRT-PCR, which demonstrated upregulation of the cyclin dependent kinase inhibitors CDKN2B, CDKN1A or both. These findings were confirmed at the protein level by Western blotting. Chip-PCR experiment using cell lysates from KMS11 cells following incubation with EZH2i over 6 days identified changes in H3K27me3 at the promoter and transcriptional start site (PROM/TSS) regions of the CDKN2B and CDKN1A genes. The most specific changes occurred at the CDKN1A PROM/TSS, which were more heavily marked with H3K27me3 at baseline compared to a region approx. 5KB upstream. Given these results, which suggest that CDKN1A expression may be controlled by changes in H3K27me3, we explored the effect of CDKN1A mRNA expression in our patient datasets. We found the expression of EZH2 and CDKN1A to be inversely correlated (R=-0.170, p<0.0001) and that low expression of CDKN1A was associated with a significantly shorter progression free and overall survival (p<0.001). In order to confirm whether these gene expression changes could be used as a potential biomarker of response we looked at our panel of cell lines with variable responses to EZH2i. We identified a consistent increase in expression of CDKN1A only in responding cell lines suggesting it could be used as a biomarker of efficacy in the clinic. Conclusions These data support the hypothesis that CDKN1A expression is suppressed by increased H3K27me3, due to high expression of EZH2 and that this can be reversed with pharmacological EZH2 inhibition leading to a reduction in proliferation of myeloma cells. We provide data which supports the investigation of EZH2i in clinical trials of myeloma patients, which has the potential to be an effective therapeutic strategy even for those with high-risk disease, for whom current treatment approaches are ineffective.Pawlyn et al, EZH2 Overexpression in Myeloma Patients Shortens Survival and in-vitro Data Supports a Potential New Targeted Treatment Strategy. AACR and IMW abstracts, 2015Pawlyn et al, The Spectrum and Clinical Impact of Epigenetic Modifier Mutations in Myeloma. Clinical Cancer Research, 2016 Disclosures Pawlyn: Celgene: Consultancy, Honoraria, Other: Travel Support; Takeda Oncology: Consultancy. Kaiser:Celgene: Consultancy, Honoraria, Research Funding; Janssen: Consultancy, Honoraria; Amgen: Consultancy, Honoraria; BMS: Consultancy, Other: Travel Support; Takeda: Consultancy, Other: Travel Support; Chugai: Consultancy. Jones:Celgene: Honoraria, Research Funding. Jackson:Amgen: Consultancy, Honoraria, Speakers Bureau; Roche: Consultancy, Honoraria, Speakers Bureau; MSD: Consultancy, Honoraria, Speakers Bureau; Janssen: Consultancy, Honoraria, Speakers Bureau; Celgene: Consultancy, Honoraria, Other: Travel support, Research Funding, Speakers Bureau; Takeda: Consultancy, Honoraria, Other: Travel support, Research Funding, Speakers Bureau. Bergsagel:Novartis: Research Funding; Amgen, BMS, Novartis, Incyte: Consultancy. Morgan:Univ of AR for Medical Sciences: Employment; Janssen: Research Funding; Bristol Meyers: Consultancy, Honoraria; Takeda: Consultancy, Honoraria; Celgene: Consultancy, Honoraria, Research Funding. Davies:Celgene: Consultancy, Honoraria; Takeda: Consultancy, Honoraria; Janssen: Consultancy, Honoraria.

The Combination of Romidepsin and Bortezomib Results in Synergistic Induction of Apoptosis in Human B-Lymphoma Cell Lines.

Blood ◽  
2009 ◽  
Vol 114 (22) ◽  
pp. 1689-1689 ◽  
Author(s):  
Deshpande S. Deshpande ◽  
Mary Jo Lechowicz ◽  
Rajni Sinha ◽  
Jonathan L. Kaufman ◽  
Lawrence H. Boise ◽  
...  
Keyword(s):  
Cell Cycle ◽  
B Cell ◽  
Cell Lines ◽  
Mtt Assay ◽  
Research Funding ◽  
Annexin V ◽  
Myeloma Cell ◽  
Parp Cleavage ◽  
Sequence Specificity ◽  
B Cell Malignancies

Abstract Abstract 1689 Poster Board I-715 Introduction The use of the proteasome inhibitor bortezomib has demonstrated activity in multiple myeloma and lymphomas. The HDAC inhibitor romidepsin is being evaluated in CTCL and PTCL, though its activity in B-cell lymphomas is less clear. We hypothesized that the combination of bortezomib and romidepsin would result in synergistic apoptosis in different B-cell NHL cell lines based upon the observed activity of this combination in more mature B-cell malignancies such as myeloma. Experimental Design Daudi, HT, Ramos and SUDHL-4 cell lines were exposed to different concentrations of bortezomib and romidepsin, separately, concurrently, and sequentially. Cell viability was assessed using MTT-assay, induced apoptosis was evaluated using Annexin V and PI staining from 24-48 hours. Apoptosis was also evaluated using western blot analysis of caspases and PARP cleavage. LC3 and HDAC6 level expressions were performed to determine if the effect of the combination was a result of the aggresome or autophagy pathway. Cell cycle studies were also performed to study if there were any changes after treating cells with the combination. Results The combination of bortezomib and romidepsin resulted in synergistic B-cell apoptosis as measured by MTT-assay with combination indices of < 0.5. This was associated with increased caspases and PARP cleavage as early as 24 hours after exposure. Order of addition experiments demonstrated definite sequence specificity. When romidepsin was added first, and 6 hours later followed by bortezomib, apoptosis was enhanced, compared to both agents being given concurrently or when bortezomib was administered first. Cell cycle analysis studies demonstrated that pretreatment of cells with romidepsin for 6 hours followed by the addition of bortezomib arrested the cells in G2M phase. HDAC6 expression was significantly reduced following combination therapy, and LC3-I was cleaved to LC3-II in treated cells suggesting that the combination affected aggresome formation and autophagy. Conclusion The combination of romidepsin and bortezomib at low nanomolar concentrations suggests that this may be an important clinical combination to test in patients with relapsed or refractory B-cell malignancies. Sequence of administration data is currently being tested to determine if the effect is a result of autophagy inhibition as is seen in myeloma cell lines. Additional mechanistic studies will be presented with the goals of identifying predictors of response that can then be validated in prospective clinical trials. Disclosures Lechowicz: Gloucester: Consultancy. Kaufman:Millennium: Consultancy; Genzyme: Consultancy; Celgene: Consultancy; Merck: Research Funding; Celgene: Research Funding. Lonial:Gloucester: Research Funding; Novartis: Consultancy; BMS: Consultancy; Millennium: Consultancy, Research Funding; Celgene: Consultancy. Flowers:Millennium: Research Funding.

Reduced TET2 expression in Patients with Myelodysplastic Syndromes and Acute Myeloid Leukemia.

Blood ◽  
2012 ◽  
Vol 120 (21) ◽  
pp. 2822-2822
Author(s):  
Renata Scopim-Ribeiro ◽  
Joao Machado-Neto ◽  
Paula de Melo Campos ◽  
Patricia Favaro ◽  
Adriana S. S. Duarte ◽  
...  
Keyword(s):  
Gene Expression ◽  
Overall Survival ◽  
High Risk ◽  
Myeloid Leukemia ◽  
Research Funding ◽  
Erythroid Differentiation ◽  
Low Risk ◽  
High Risk Disease ◽  
Cd34 Cells ◽  
Acute Myeloid

Abstract Abstract 2822 Introduction: Acquired mutations in TET2 and DNMT3A have been found in myelodysplastic syndromes (MDS) and acute myeloid leukemia (AML), and may predict a worse survival in these diseases. TET2 mutations are considered to be a loss-of-function mutation and results in decreased 5-hydroxymethylcitosine (5-hmc) levels. In normal CD34+ cells, TET2 silencing skews progenitor differentiation towards the granulomonocytic lineage at the expense of lymphoid and erythroid lineages. Dnmt3a participates in the epigenetic silencing of hematopoietic stem cell regulatory genes, enabling efficient differentiation. Here, we attempted to evaluate the expression of TET2 and DNMT3A in total bone marrow cells from normal donors, patients with MDS and AML, and in CD34+ cells from MDS and normal controls during erythroid differentiation. Materials and Methods: The study included normal donors (n = 21), patients with MDS (n = 43) and AML (n = 42) at diagnosis. All normal donors and patients provided informed written consent and the study was approved by the ethics committee of the Institution. MDS patients were stratified into low and high-risk according to WHO classification (RCUD/RCMD/RARS=31 and RAEB1/RAEB2=12). TET2 and DNMT3A mRNA expression was assessed by quantitative PCR. CD34+ cells from normal donors (n = 9) and low-risk MDS patients (n = 7) were submitted to erythroid differentiation. Cells were collected and submitted to immunophenotyping for GPA and CD71 (days 6 and 12) and q-PCR for TET2 and DNMT3A expression (days 6, 8 and 12). Results of gene expression in normal donors and patients are presented as median, minimum-maximum, and were compared using Mann-Whitney test. Student t test was used for comparison of gene expression during CD34+ erythroid diferentiation. Overall survival was defined from the time of sampling to the date of death or last seen. Univariate analysis for overall survival was conducted with the Cox proportional hazards model. Results: TET2 expression was significantly reduced in both AML (0.62; 0.01–32.69) and MDS (1.46; 0.17–21.30) compared to normal donors (2.72; 0.43–31.49); P<0.0001 and P=0.01, respectively. TET2 expression was also significantly reduced in AML compared to MDS (P=0.0007). MDS patients were stratified into low and high-risk disease, and we still observed a significant reduction in TET2 expression in high-risk (0.73, 0.17–7.25) when compared to low-risk (1.58; 0.48–21.30; P=0.02) patients, but no difference was noted between normal donors vs. low-risk MDS, and high-risk MDS vs. AML. In MDS cohort, the median overall survival was 14 months (range 1–83), increased TET2 expression was associated with a longer survival (HR, 0.44; 95% CI, 0.21–0.91, P=0.03), and, as expected, WHO high-risk disease was associated with a shorter survival (HR, 10.16; 95% CI, 3.06–33.72, P<0.001), even though the confidence interval (CI) was large. TET2 expression did not impact survival in our cohort of AML patients. The erythroid differentiation was effective in cells from normal donors and MDS patients, as demonstrated by the flow cytometry analyses of GPA and CD71. TET2 expression was significantly increased on day 12 of erythroid differentiation, P<0.05. On the other hand, DNMT3A expression was similar between normal donors (0.74; 0.22–1.53), MDS (0.78; 0.26–3.46) and AML (0.95, 0.15–6.46), and during erythroid differentiation, with no impact on survival. Conclusion: These data suggest that decreased TET2 expression may participate in leukemogenesis, and supports the participation of TET2 in the erythroid differentiation of MDS. DNMT3A was not differentially expressed in AML and MDS, indicating that the presence of mutations in this gene may be the predominant mechanism of changes in protein function. We thus suggest that decreased TET2 expression may explain the reduced levels of 5-hmc found in TET2 wild type patients, and may become a predictive marker for outcomes in MDS and other myeloid diseases. Further studies would be necessary to better elucidate the clinical relevance and biologic significance of our findings, and whether the decreased TET2 expression results in hypermethylation in these diseases. Disclosures: Maciejewski: NIH: Research Funding; Aplastic Anemia&MDS International Foundation: Research Funding.

Drug Design for Overcoming High-Risk Myeloma and Identification of Novel Binding Proteins to Immune-Modulatory Drugs

Blood ◽  
2015 ◽  
Vol 126 (23) ◽  
pp. 1800-1800
Author(s):  
Masashi Hozumi ◽  
Daiju Ichikawa ◽  
Maiko Matsushita ◽  
Eriko Kamiyama ◽  
Hiroshi Yanagawa ◽  
...  
Keyword(s):  
High Risk ◽  
Tumor Cell ◽  
Pharmaceutical Company ◽  
Cell Lines ◽  
Research Funding ◽  
Chemical Structure ◽  
Myeloma Cell ◽  
Tumor Cell Growth ◽  
Myeloma Cells

Abstract PURPOSE: Recent progress of the treatment of multiple myeloma (MM) has significantly improved prognosis. However, the MM patients with high-risk cytogenetic abnormalities still showed significantly shorter survival. The purpose of this study is to find compounds effective for high-risk myeloma with lower toxicity by developing chemical structure of the phthalimide. We also tried to isolate their binding molecules to understand molecular pharmacology of the compounds. RESULTS: (1) Screening and optimization of phthalimide derivatives: We screened library of synthetic phthalimide derivatives by their ability to induce apoptosis of MM cell line, KMS34, which has high-risk cytogenetic abnormalities such as t(4;14) and TP53 gene deletion. We finally found TC11, 2-(2,6-diisopropylphenyl)-5-amino-1H-isoindole-1,3-dione, which showed the most potent tumor growth inhibition. Based on the results of screening of phthalimide library, we found the two important points of chemical structure: (i) A 4-amino group lacked growth inhibitory effect, and thus, 5-amino branch is necessary for strong anti-tumor activity. (ii) Modification of 2,6-diisopropylphenyl in phenyl ring of TC11 significantly decreased inhibitory effects of tumor cell growth. (2) Anti-myeloma effects of phthalimide derivatives: TC11 showed significant growth inhibition of all myeloma cell lines (IC50=3-8μM) including those with high-risk cytogenetic changes. Lenalidomide also significantly inhibited growth of myeloma cell lines. However, 30μM of lenalidomide failed to inhibit growth of KMS34 and KMS28 cell lines that have high-risk cytogenetic alterations. TC11 also inhibited growth of bone marrow myeloma cells obtained from the MM patients. (3) Anti-myeloma effects of TC11 in vivo: Intraperitoneal injections of TC11 significantly delayed the growth of subcutaneous plasmacytoma in human myeloma cell (KMS34 and KMS11)-bearing SCID xenografts. In the pharmacokinetic analyses, the Cmax was 2.1μM at 1 h after the injection of TC11, with 1.2 h as the half-life. Cmax was 18.1μM at 1.5hr (Tmax), and T1/2 was 4.5hr, when 100mg/kg of TC11 was injected. Cmax was 2.1μM at 1.0hr (Tmax), and T1/2 was 1.2hr, if 20mg/kg was injected. In oral administration of 200mg/kg of TC11 in lcr mice, Cmax was 3.81μM at 8.0hr (Tmax), and T1/2 was 2.77hr. (4) Toxicity of TC11 and lenalidomide: When 20mg/kg of TC11 was injected to SCID-mice for two weeks, weight loss compared with control mice was not observed. Clonological assay using mice bone marrow cells showed that 10μM TC11 did not suppress the colony formation while 5μM lenalidomide significantly decreased the colony out put. Therefore, TC11 in the concentrations that induced apoptosis of myeloma cells unlikely caused systemic and hematological toxicity. (5) Binding molecules: To understand the molecular mechanism, we employed our unique in vitro screening system using mRNA display, in vitro virus (IVV) method. It was found that TC11 directly bound to nucleophosmin 1 (NPM1) and α-tubulin. Knock-down of NPM1 gene in myeloma cells significantly delayed tumor cell growth. However, cereblon (CRBN), which was considered to be associated with teratogenicity of thalidomide, was not included in TC11-binding molecules in IVV assay. TC11 lacked glutarimide moiety to which CRBN was reported to bind. Thus, TC11 revealed anti-myeloma activity in a CRBN-independent pathway and is conceptionally expected as a non-teratogenic thalidomide-related compound. Interestingly, lenalidomide also directly bound to NPM1. Further analyses were needed to elucidate biological significance of interaction of IMiDs with NPM1 and α-tubulin. CONCLUSION: Our results suggested the possibility that phthalimide derivatives induce tumor cell death independent of CRBN pathway. It was also suggested that drug design and modification of chemical structure of phthalimide enable us to develop further new thalidomide derivatives which have more potent antitumor activity and less toxicity. Disclosures Ichikawa: Takeda Pharmaceutical Company: Research Funding. Matsushita:Takeda Pharmaceutical Company: Research Funding. Hattori:MSD company: Research Funding; Ono Pharmaceutical company: Research Funding; Takeda Pharmaceutical Company: Consultancy; Novo Nordisk company: Research Funding; Mitsubisi Tanabe Pharm: Research Funding; Cosmic Corporation: Research Funding.

MicroRNA 15a and 16-1 Target Identification in Deletion 13 Multiple Myeloma

Blood ◽  
2008 ◽  
Vol 112 (11) ◽  
pp. 631-631
Author(s):  
Travis J. Henry ◽  
Rafael Fonseca
Keyword(s):  
Gene Expression ◽  
Multiple Myeloma ◽  
Cell Lines ◽  
Target Identification ◽  
Myeloma Cell ◽  
Rt Pcr ◽  
Total Rna ◽  
Expression Arrays ◽  
Gene Expression Arrays ◽  
Functional Investigation

Abstract Deletion 13 multiple myeloma (MM) is detected in nearly 50 % of patients diagnosed with MM and confers a shorter survival. A region of minimal deletion was identified for chromosome 13 using Agilent 500K aCGH arrays that included microRNAs 15a and 16- 1. MicroRNAs (miRs) are small RNAs that negatively regulate gene expression through degradation of mRNA transcripts or translational inhibition. In order to determine the contribution of deletion of miRs 15a and 16-1 to MM progression, miR precursors were transfected into KMS-11 and JJN3 adherent myeloma cell lines and total RNA hybridized to Affymetrix U133 Plus 2.0 gene expression arrays for the purpose of identification of mRNA target transcripts. Thirty nanomolar miR 15a and 16-1 precursors and a nonsilencing siRNA control were transfected into adherent KMS-11 and JJN3 myeloma cell lines. Cultures were harvested 16 hours after transfection to minimize the downregulation of transcripts that are not direct targets of miRs 15a and 16-1. Total RNA was extracted using the miRNeasy kit to allow retention of the miR fraction for RT-PCR confirmation of miR over-expression following transfection. Following transfection of miR precursors, expression of miRs 15a and 16-1 were increased 64 and 128-fold, respectively, compared to non-silencing control. Total RNA was hybridized to Affymetrix gene expression arrays using protocols supplied by the manufacturer. Transcripts down-regulated following miR transfection were compared to mathematical models for prediction of miR targets. Additionally, the 3′ UTRs of down-regulated transcripts were inspected for complementarity to miR 15a and 16-1 seed sequences. RT-PCR validation of identified targets was performed. Cross reference of down-regulated transcripts with the TargetSCAN and PictarVERT miR prediction algorithms resulted in a list of 9 genes that represented potential miR-15a/16-1 targets in MM. This list included: FGF2, BCL2, CCNE1, V-MYB, WEE1, E2F7, CDK6, CDC25A and CDC27. Following target identification, reporter constructs were used to confirm direct regulation of transcripts by miRs 15a and 16-1. Functional investigation of miR targets was performed using siRNA reduction of identified targets followed by MTT assay and cell cycle analysis.

scholarly journals Activity of the Phosphatidylinositol 3-Kinase (PI3K) Inhibitor, Copanlisib, As a Single Agent and in Combination with Carfilzomib in Multiple Myeloma

Blood ◽  
2016 ◽  
Vol 128 (22) ◽  
pp. 5665-5665
Author(s):  
Sarah M Larson ◽  
Mao Yu Peng ◽  
Andrae Vandross ◽  
Monica Mead ◽  
Zoe Fuchs ◽  
...  
Keyword(s):  
Cell Cycle ◽  
Multiple Myeloma ◽  
Cell Lines ◽  
Research Funding ◽  
Single Agent ◽  
Myeloma Cell ◽  
Resistant Cell ◽  
Cell Senescence ◽  
Sensitive Cell ◽  
Multiple Myeloma Cell

Abstract Background: The PI3K pathway signals for cell proliferation and survival in many malignancies including multiple myeloma. Copanlisib (BAY 80-6946) is a pan-class I PI3K inhibitor with preferential activity of the alpha and delta isoforms, of which the alpha isoform has particular importance in multiple myeloma. Here we demonstrate the pharmacological activity of copanlisib in multiple myeloma as a single agent and in combination with carfilzomib biomarker exploratory evaluation using phosphorylation of the S6 ribosomal protein (p-S6). Methods: 21 multiple myeloma cell lines were initially screened. Using an IC50 cut off of 100nM, 3 sensitive: NCI-H929, MM.1S, L-363 and 3 resistant: AMO-1, JJN3, COLO-677 were selected for further analysis. Apoptosis and cell senescence assays were done with each agent (copanlisib at 50nM and 100nM at 72 hours; carfilzomib at 2 nM and 20nM at 96 hours). Cell cycle analysis and induction of apoptosis were performed by FACS after propidium iodide or Annexin V FITC staining, respectively. Cellular senescencewas determined by measurement of β-galactosidase activity in cells treated for 96 hours. Combination studies utilized excess over highest single agent statistics (EOHSA) to evaluate potentiation. Reverse phase protein array (RPPA) was performed at baseline and post treatment for proteomics analysis with confirmatory western blot at 4 and 24 hours post treatment. Results: Copanlisib induced apoptosis and cell cycle arrest in the sensitive cell lines, but not the resistant cell lines. The cell senescence assays confirmed apoptosis rather than cell senescence as the mechanism of inhibition of proliferation. Pretreatment RPPA analysis demonstrated lower p-S6 levels in the sensitive cells lines compared to the resistant cell lines. Further, treatment with copanlisib resulted in a greater decrease in p-S6 in the sensitive cell lines than in the resistant cell lines, which was validated by western blot. Downstream pathway effects were confirmed by an increase in PDCD4 in the sensitive cell lines. Treatment with copanlisib and carfilzomib showed potentiation by EOHSA statistics and further decrease in p-S6 expression in the sensitive rather than resistant cell lines. Discussion: Copanlisib demonstrated single agent activity in human multiple myeloma cell lines, which is enhanced by the addition of carfilzomib. p-S6 levels may serve to select the most appropriate patient population to study combination of carfilzomib and copanlisib in relapsed/refractory multiple myeloma. With the choices of therapy available to patients with multiple myeloma there is a need for predictive biomarkers in order to better sequence therapies. Disclosures Larson: BMS: Consultancy. Slamon:Novartis: Consultancy, Honoraria, Research Funding; Biomarin: Consultancy, Honoraria; Pfizer: Honoraria, Research Funding; Eli Lilly: Consultancy; Syndax: Research Funding; Bayer: Consultancy.

scholarly journals PBX1 Co-Operates with FOXM1 to Regulate Myeloma Cell Proliferation and to Define an Ultra High-Risk chr1q Gain Myeloma Patient Subgroup

Blood ◽  
2019 ◽  
Vol 134 (Supplement_1) ◽  
pp. 3760-3760
Author(s):  
Nikolaos Trasanidis ◽  
Alexia Katsarou ◽  
Bien Bergonia ◽  
Keren Keren ◽  
Ioannis V. Kostopoulos ◽  
...  
Keyword(s):  
Cell Cycle ◽  
High Risk ◽  
Research Funding ◽  
Poor Prognosis ◽  
Enrichment Analysis ◽  
Myeloma Cell ◽  
Pathway Enrichment Analysis ◽  
Myeloma Cells ◽  
Pathway Enrichment ◽  
Ultra High Risk

BACKGROUND: The biological basis for the adverse prognosis of chr1q gain/amplification (1q+) present in ~30% of patients with multiple myeloma (MM) remains ill-defined. The transcription factor (TF) Pre-B-cell leukaemia homeobox 1 (PBX1), encoded on chr1q, acts as master regulator of early hematopoiesis and as an oncogene in leukemia and other malignancies. Herein, we hypothesized that PBX1 orchestrates proliferative regulatory networks that underpin the poor prognosis associated with 1q+ in MM. METHODS: We employed qPCR for mRNA quantification, western blotting and immunohistochemistry for protein analysis, lentiviral shRNA-mediated knock-down, Hoechst/Annexin V staining and flow-cytometry for apoptosis and cell cycle analysis, ChIPseq for cistrome and RNAseq after knock-down for transcriptome analysis. Additional data were obtained from MMRF/CoMMpass, Blueprint Consortium and Arkansas datasets. Computational analysis of clinical and "-omics" data was performed using standard bioinformatic work-flows; pathway enrichment analysis using EnrichR and GSEA. RESULTS: Combined genomic (WGS/WES) and transcriptomic (RNAseq) analysis of the CoMMpass dataset identified a subgroup of 1q+ MM patients (60%) characterized by aberrant PBX1 overexpression and amplification (PBX1amp); survival analysis revealed significantly worse outcome of this subgroup compared to 1q+ non-PBX1amp (p<0.05) and 1q-negative (p<0.001) patients. Analysis of the Arkansas dataset validated these findings while immunohistochemistry confirmed PBX1 protein expression in 8/11 1q+ MM patient bone marrow biopsies. Depletion of PBX1 using 2 validated shRNAs was toxic to the 1q+ MM1.S t(14;16) and U266 t(11;14) myeloma cell lines (MMCL) in vitro, revealing a novel myeloma cell addiction to PBX1. Transcriptome analysis of PBX1-depleted cells showed significant de-regulation of genes (MM1.S: 753down/320up; U266: 598 down/288up) highly enriched in cell cycle and proteasome/ER stress response pathways. Flow-cytometric analysis confirmed that PBX1-depleted myeloma cells undergo cell cycle arrest (G0/1 phase) and apoptosis (n=3; p<0.001). Genome-wide binding profiling of PBX1 identified 7,354 significantly enriched peaks shared between MM1.S and U266 MMCL. These peaks were distributed at active promoters (~50%) and active enhancers (~30%), as defined by ChromHMM maps; the PBX1 consensus binding motif was identified as top hit upon motif enrichment analysis. Transcriptome-cistrome integration identified 728 and 282 genes directly activated or repressed, respectively, by PBX1 in MM1.S cells. Again, pathway enrichment analysis of PBX1 direct targets demonstrated significant over-representation of cell cycle and proliferation pathways, as well as positive regulation of various metabolic processes (oxidative phosphorylation, glycolysis, unfolded protein response). Strikingly, enrichment analysis against public ChIPseq datasets revealed significant overlap with gene targets of FOXM1 (200) and E2F (150) TF, suggesting the presence of a united PBX1-FOXM1-E2F regulatory circuitry. In fact, PBX1 binding was detected at an active FOXM1 enhancer and at the E2F1/2 promoters, while FOXM1 and E2F1/2 mRNA levels decreased significantly upon PBX1 depletion in two MMCL. To further explore the PBX1-FOXM1 interaction, we overlaid the FOXM1-depleted transcriptome with the PBX1 network in MM.1S cells. This identified 160 genes to be co-regulated by PBX1 and FOXM1, including genes previously linked to myeloma cell drug resistance (NEK2, TOP2A, AURKA); however, PBX1 expression was not altered in FOXM1-depleted cells, suggesting that PBX1 is functionally upstream of FOXM1. Additional analysis across 814 primary MM patient CoMMpass transcriptomes confirmed significant co-expression of PBX1 with FOXM1, E2F1/2 and another 67 PBX1-FOXM1 highly expressed, co-regulated gene targets, conferring poor OS (p<0.0001). CONCLUSIONS: We found that genetic amplification and overexpression of PBX1 defines an ultra high-risk subgroup of 1q+ MM with proliferative features. Myeloma cells are addicted to aberrant PBX1 expression. As well as essential metabolic pathways, PBX1 regulates cell cycle progression by direct transcriptional regulation of FOXM1 and of its target genes. These data reveal PBX1 as a critical biological link between chr1q gain/amplification and poor prognosis in a subset of MM patients. Disclosures Auner: Karyopharm: Consultancy; Amgen: Other: Consultancy and Research Funding; Takeda: Consultancy. Caputo:GSK: Research Funding. Karadimitris:GSK: Research Funding.

Identifying Ultra-High Risk Myeloma By Integrated Molecular Genetic and Gene Expression Profiling

Blood ◽  
2016 ◽  
Vol 128 (22) ◽  
pp. 4407-4407 ◽  
Author(s):  
Amy L Sherborne ◽  
Dil B Begum ◽  
Amy Price ◽  
David C Johnson ◽  
Sidra Ellis ◽  
...  
Keyword(s):  
Gene Expression ◽  
High Risk ◽  
Research Funding ◽  
Molecular Genetic ◽  
High Risk Group ◽  
Risk Status ◽  
Risk Profiling ◽  
High Risk Disease ◽  
Ultra High Risk ◽  
Support Research

Abstract Introduction A significant proportion of myeloma patients relapse early and show short survival with current therapies. Molecular diagnostic tools are needed to identify these high risk patients at diagnosis to stratify treatment and offer the prospect of improving outcomes. Two validated molecular approaches for risk prediction are widely used: 1) molecular genetic risk profiling [e.g. del(17p), t(4;14)] 2) gene expression (GEP) risk profiling, [e.g. EMC92 (Kuiper et al., Leukemia 2012)]. We profiled patients from a large multicentric UK National trial using both approaches for integrated risk stratification. Methods A representative group of 221 newly diagnosed, transplant eligible patients (median age 64 years) treated on the UK NCRI Myeloma XI trial were molecularly profiled. DNA and RNA were extracted from immunomagnetically CD138-sorted bone marrow plasma cells. Molecular genetic profiles, including t(4;14), t(14;16), Del(17p), Gain(1q) were generated using MLPA (MRC Holland) and a TC-classification based qRT-PCR assay (Boyle EM, et al., Gen Chrom Canc 2015, Kaiser MF, et al., Leukemia 2013). GEP risk status as per EMC92 was profiled on a diagnostic Affymetrix platform using the U133plus2.0-based, CE-marked MMprofiler (SkylineDx) which generates a standardised EMC92 risk score, called 'SKY92'. Progression-free (PFS) and overall survival (OS) were measured from initial randomization and median follow-up for the analysed group was 36 months. Statistical analyses were performed using R 3.3.0 and the 'survival' package. Results were confirmed in an independent dataset, MRC Myeloma IX, for which median follow-up was 82.7 months. Results Of the 221 analysed patients, 116 were found to carry an established genetic high risk lesion [t(4;14), t(14;16), del(17p) or gain(1q)]. We and others have recently demonstrated that adverse lesions have an additive effect and that co-occurrence of ≥2 high risk lesions is specifically associated with adverse outcome (Boyd KD et al, Leukemia 2011). 39/221 patients (17.6%) were identified as genetic high risk with ≥2 risk lesions (termed HR2). By GEP, 53/221 patients (24.0%) were identified as SKY92 high risk. Genetic and GEP high risk co-occurred in 22 patients (10.0%), 31 patients (14.0%) were high risk only by GEP and 17 patients (7.7%) by genetics only. SKY92 high risk status was associated with significantly shorter PFS (median 17.1 vs. 34.3 months; P<0.0001; Hazard ratio [HR] 3.2 [95%CI: 2.2-4.7]) and OS (median 36.0 vs. not reached; P<0.0001; HR 3.9 [2.3-6.9]). Genetic risk by HR2 was similarly associated with adverse outcome: median PFS 17.0 vs. 33.6 months; P<0.0001; HR 2.9 [1.9-4.4]), median OS 33.5 vs. not reached; P<0.0001; HR 4.1 [2.3-7.2]). Importantly, by multivariate analysis GEP and genetic high risk status were independently associated with shorter PFS (P<0.001) and OS (P<0.005). We next investigated interactions between genetic and gene expression high risk status. Three groups were defined: 1) Patients with both SKY92 and genetic (HR2) high risk status (n=22), 2) either GEP or genetic high risk (n=48) or 3) absence of GEP or genetic (HR2) high risk status (n=151). Co-occurring GEP and genetic high risk status was associated with very short PFS (median 12.5 vs. 20.0 vs. 38.3 months; P<0.0001) and OS (median 25.6 vs. 47.3 vs. not reached; P<0.0001) [Figure]. When comparing this ultra-high risk group against the remainder of cases (n=199), their risk of progressing and dying early was significantly elevated (PFS HR 4.4 [2.5-6.7]; OS HR 5.9 [3.1-11.0]). We confirmed this finding in 116 transplant-eligible patients from the MRC Myeloma IX trial. Patients carrying both EMC92 and genetic high risk status had a median PFS of 7.8 vs. 25.5 months and median OS of 9.5 vs. 62.1 months (both P<0.0001). Moreover, all patients in this ultra-high risk group progressed within 24 months and died within 48 months. Conclusion We demonstrate, for the first time, that combined genetic and gene expression risk profiling identifies a group of patients with ultra-high risk disease behaviour with high fidelity, using molecular features of the disease. Our results indicate that GEP and genetic high risk profiling identify independently relevant, but inter-related features of high risk disease biology. Integrated genetic and gene expression risk profiling could serve as a valuable tool for risk stratified, innovative treatment approaches in myeloma. Figure Figure. Disclosures Jones: Celgene: Honoraria, Research Funding. Pawlyn:Takeda Oncology: Consultancy; Celgene: Consultancy, Honoraria, Other: Travel Support. Jenner:Amgen: Consultancy, Honoraria, Other: Travel support; Janssen: Consultancy, Honoraria, Other: Travel support, Research Funding; Novartis: Consultancy, Honoraria; Takeda: Consultancy, Honoraria, Other: Travel support; Celgene: Consultancy, Honoraria, Research Funding. Cook:Glycomimetics: Consultancy, Honoraria; Takeda: Consultancy, Honoraria, Research Funding, Speakers Bureau; Amgen: Consultancy, Honoraria, Research Funding, Speakers Bureau; Bristol-Myers Squibb: Consultancy, Honoraria; Sanofi: Consultancy, Honoraria, Speakers Bureau; Celgene: Consultancy, Honoraria, Research Funding, Speakers Bureau; Janssen: Consultancy, Honoraria, Research Funding, Speakers Bureau. Drayson:Abingdon Health: Equity Ownership, Membership on an entity's Board of Directors or advisory committees. Davies:Takeda: Consultancy, Honoraria; Janssen: Consultancy, Honoraria; Celgene: Consultancy, Honoraria. Morgan:Janssen: Research Funding; Celgene: Consultancy, Honoraria, Research Funding; Univ of AR for Medical Sciences: Employment; Bristol Meyers: Consultancy, Honoraria; Takeda: Consultancy, Honoraria. Jackson:Celgene: Consultancy, Honoraria, Other: Travel support, Research Funding, Speakers Bureau; Takeda: Consultancy, Honoraria, Other: Travel support, Research Funding, Speakers Bureau; MSD: Consultancy, Honoraria, Speakers Bureau; Janssen: Consultancy, Honoraria, Speakers Bureau; Amgen: Consultancy, Honoraria, Speakers Bureau; Roche: Consultancy, Honoraria, Speakers Bureau. Kaiser:Takeda: Consultancy, Other: Travel Support; Amgen: Consultancy, Honoraria; BMS: Consultancy, Other: Travel Support; Janssen: Consultancy, Honoraria; Celgene: Consultancy, Honoraria, Research Funding; Chugai: Consultancy.

scholarly journals Preclinical Validation Studies Support Causal Machine Learning Based Identification of Novel Drug Targets for High-Risk Multiple Myeloma

Blood ◽  
2018 ◽  
Vol 132 (Supplement 1) ◽  
pp. 3210-3210
Author(s):  
Arnold Bolomsky ◽  
Fred Gruber ◽  
Kathrin Stangelberger ◽  
Leon Furchtgott ◽  
Dominik Arnold ◽  
...  
Keyword(s):  
Cell Cycle ◽  
High Risk ◽  
Cell Growth ◽  
Cell Lines ◽  
Drug Targets ◽  
Post Treatment ◽  
High Risk Disease ◽  
Induction Of Apoptosis ◽  
Novel Drug ◽  
Novel Drug Targets

Abstract Introduction Regardless of significant advances in the therapy of multiple myeloma (MM) there is still a lack of effective treatment options for patients with high-risk disease. In this context, we recently developed a network of high-risk disease based on more than 30 000 genomic and clinical variables from 645 patients of the CoMMpass dataset (Gruber et al., ASH 2016). Validation of these findings has been performed in the IFM/DFCI 2009 trial dataset (Furchtgott et al., ASH 2017). This comprehensive computational approach revealed a network of 17 genes driving high-risk (defined as progression or myeloma-related death within 18 months). Here, we performed preclinical validation of potential novel drug targets to confirm the utility of in silico guided target discovery in high-risk MM. Methods TTK (CFI402257, BAY-1217389), PLK4 (CFI400945, Centrinone), MELK (OTSSP167) and CDK1 (CPG71514) inhibitors were studied in a panel of human MM cell lines (n=11) for their activity in cell viability, cell growth, cell cycle, apoptosis, colony formation, drug combination and co-culture experiments. PKMYT1, TTK and PLK4 were targeted with doxycycline-inducible shRNAs. Analysis of gene expression (GEP) data (GSE24080) was used to link candidate genes to certain MM subgroups. Results The network of 17 genes driving high-risk disease contained eight kinases that serve as attractive drug targets (AURKA, NEK2, CDK1, BUB1B, MELK, TTK, PKMYT1, and PLK4), all of them involved in cell cycle regulation. Accordingly, expression levels of all kinases (except PKMYT1) were enriched in the GEP-defined proliferation associated subgroup of MM and thus linked to poor outcome. To study the interconnectedness of the individual network genes we first investigated the impact of previously reported CDK1 and MELK inhibitors on other network members. This demonstrated rapid loss of CDK1, NEK2, MELK, PKMYT1 and FOXM1 protein levels. We then selected TTK and PLK4 as putative novel MM targets with available inhibitors undergoing clinical testing in solid tumors. Protein and mRNA expression of both genes was confirmed in all MM cell lines. Two selective compounds per gene were used for preclinical studies. All four inhibitors significantly reduced MM cell viability and single dose IC70 treatment impaired cell growth up to 10 days (60-98% reduction, P<0.01). This growth inhibitory effect was confirmed with inducible shRNAs. Mechanistically, growth impairment was linked to G2M cell cycle arrest followed by the accumulation of polyploid cells (15-90% of cells 72h post treatment) which is in line with the role of both genes in chromosome segregation. The formation of aberrant mitoses led to the induction of apoptosis 3-5 days post treatment (≤20% viable cells at day 5 post treatment with 3/4 inhibitors) and was accompanied by the presence of active caspase 3 and cleaved PARP. Importantly, the activity of these drugs persisted in the presence of BMSCs and showed potent activity in colony formation assays (DMSO: 168±15 and 131±57, BAY-1217389: 39±29 and 41±3, CFI-400945: 19±26 and 30±6 colonies in KMS12BM and OPM2 cells at day 14, P<0.05). Drug combination studies pointed to favorable activity in combination with dexamethasone and lenalidomide. Furthermore, confirmatory TTK knockdown with two independent shRNAs sensitized MM cells to dexamethasone. Finally, PKMYT1 was chosen as putative target based on its role as major driver of high-risk in our model. We transduced MM cells with three doxycycline-inducible PKMYT1-targeting shRNAs and observed an impressive impact on myeloma cell growth upon doxycycline induction compared to non-targeting control shRNA (up to 85% reduction at day 10, P<0.01). Furthermore, PKMYT1 knockdown led to the induction of apoptosis in all MM cell lines tested. Based on these encouraging results we currently perform in-depth in silico and in vitro analyses of the underlying PKMYT1 signaling network. Detailed results of these sub-studies will be presented at the meeting. Conclusions Our results confirm the utility of computational based modelling of high-risk disease. This strategy not only revealed a genetic network closely associated to adverse prognosis, but also enabled the identification of so far unnoticed drug targets. Importantly, inhibitors of TTK and PLK4 are already in clinical testing and thus enable rapid clinical translation of our findings to MM patients in need of alternative therapeutic options. Disclosures Gruber: GNS Healthcare: Employment. Furchtgott:GNS Healthcare: Employment. Raut:GNS Healthcare: Employment. Wuest:GNS Healthcare: Employment. Runge:GNS Healthcare: Employment. Khalil:GNS Healthcare: Employment. Munshi:OncoPep: Other: Board of director. Hayete:GNS Healthcare: Employment. Ludwig:Amgen: Research Funding, Speakers Bureau; BMS: Speakers Bureau; Takeda: Research Funding, Speakers Bureau; Cilag-Janssen: Speakers Bureau; Celgene: Speakers Bureau.

ANKHD1 Silencing Induces S-Phase Arrest and Modulates Cell Cycle Gene Expression in Human Myeloma Cells

Blood ◽  
2011 ◽  
Vol 118 (21) ◽  
pp. 1828-1828
Author(s):  
Anamika Dhyani ◽  
Adriana S S Duarte ◽  
Patricia Favaro ◽  
Sara T Olalla Saad
Keyword(s):  
Gene Expression ◽  
Cell Cycle ◽  
Multiple Myeloma ◽  
Cell Lines ◽  
Lentiviral Vector ◽  
Myeloma Cell ◽  
S Phase ◽  
Cell Cycle Gene ◽  
Myeloma Cells ◽  
Protein Levels

Abstract Abstract 1828 ANKHD1 is a multiple ankyrin repeats containing protein with a single KH domain. It is a large protein (∼ 280 kDa) derived from an 8 kb transcript. The ANKHD1 gene, present in human chromosome 5q31.3 as a single copy is ubiquitously expressed in normal human tissues and reported to be highly expressed in cancers, such as acute leukemia. Previous study showed higher expression of ANKHD1 in bone marrow plasma cells (CD138+) from Multiple Myeloma patients as compared to control (1) and it is also over expressed in multiple myeloma cell lines such as MM1S, MM1R, U266 and RPMI 8266 at both mRNA and protein level (2). However, the functional role of ANKHD1 in myeloma cells is unknown. In the present study, by silencing ANKHD1 gene expression in glucocorticoid resistant (U266) and sensitive (MM1S) myeloma cell lines, we studied its effect on cell cycle, proliferation and apoptosis. For gene silencing, specific shRNA-expressing lentiviral vector targeting the ANKHD1 gene and as negative control, sequence specific to Lac z gene were used. Cell growth was measured using the MTT colorimetric assay, whereas for apoptosis and cell cycle analysis Flow cytometry was used. Western blot and RTPCR were used for studying gene expression and protein levels, respectively. The results showed that lentiviral vector containing coding sequences for shRNA significantly downregulated ANKHD1 gene expression in Multiple Myeloma cells at the mRNA and the protein levels (p<0.05). Furthermore, we found that the cell cycle was arrested at S phase and the cell proliferation was significantly inhibited in both cell lines studied (p<0.05). However, ANKHD1 suppression did not induce apoptosis in myeloma cells, as evidenced by annexin V binding assay and flow cytometric detection of sub-G1 DNA content. To address the mechanism of the antiproliferative effect of ANKHD1 silencing, we examined the effect of ANKHD1 inhibition on cell cycle-related gene expression and proteins. ANKHD1 suppression caused downregulation of CDKN1B (p27), CCNB1 (cyclin B1), CDC25, CCNE1 (cyclin E1) and WEE 1 gene expression. There was no significant change in CCNA2 (Cyclin A2), CDC20 expression at mRNA levels. On the other hand, expression of CDKN1A (p21),which inhibits cyclin dependent kinases (CDKs) and plays role in preventing proliferation, was highly upregulated in both the cell lines. At protein levels, expression of Cdk2,Cdk4, p27 (CDKN1B) and E2F1 was decreased in both the cell lines with almost complete inhibition of expression in U266 cells. Taken together, the above results suggest that accumulation of cells in S phase (S phase arrest) can be due to inhibition of CDKs which binds with cyclins and are responsible for progression of cell cycle. Further, this inhibition of CDKs could be associated to increased induction of (CDKN1A) p21 in both cell lines. In conclusion, the present study demonstrates that the suppression of ANKHD1 potently inhibits proliferation and promotes cell cycle arrest without affecting rate of apoptosis in both glucocorticoid resistant as well as sensitive multiple myeloma cells. Also, as ANKHD1 suppression prevents S to G2/M progression, ANKHD1 protein might have role in cell cycle control by modulating cell cycle gene expression in intra S phase check point. The mechanisms modulating expression of these genes are under investigation. Further studies with combination of drugs that induce apoptosis and suppression of ANKHD1 may be an effective strategy for treatment of cancers, and therefore needed to be explored. Disclosures: No relevant conflicts of interest to declare.

scholarly journals DYRK1A Is Required to Alleviate Replication Stress in KMT2A-Rearranged Acute Lymphoblastic Leukemia

Blood ◽  
2020 ◽  
Vol 136 (Supplement 1) ◽  
pp. 39-40
Author(s):  
Christian Hurtz ◽  
Martin P. Carroll ◽  
Sarah K Tasian ◽  
Gerald Wertheim ◽  
Rahul S. Bhansali ◽  
...  
Keyword(s):  
Cell Cycle ◽  
Cell Proliferation ◽  
B Cells ◽  
High Risk ◽  
Fusion Protein ◽  
Cell Lines ◽  
Research Funding ◽  
Meta Analysis ◽  
Replication Stress ◽  
Pharmacologic Inhibition

Background: KMT2A-rearranged (R) ALL is associated with chemoresistance, relapse, and poor survival with a frequency of 75% in infants and 10% in children and adults with ALL. Current intensive multiagent chemotherapy regimens induce significant side effects, yet fail to cure many patients, demonstrating continued need for novel therapeutic approaches. We performed a kinome-wide CRISPR screen and identified DYRK1A as required for KMT2A-R ALL cell survival, but not in other high risk ALL genetic subtypes. DYRK1A is a member of the dual-specificity tyrosine phosphorylation-regulated kinase family and has been reported as a critical oncoprotein in a murine Down syndrome model of megakaryoblastic leukemia. DYRK1A negatively regulates cell proliferation and induces quiescence. Paradoxically, genetic deletion or pharmacological inhibition of DYRK1A upregulates the cell cycle regulator CCND3 and increased numbers of B cells in S-phase, yet also significantly reduces cell proliferation. The specific role of DYRK1A in ALL has not been reported. Results: We assessed the importance of DYRK1A deletion in a focused screen of 14 previously identified kinases. Meta-analysis of ChIP-Seq data from two KMT2A-AFF1 cell lines and a human KMT2A-Aff1-FLAG transduced ALL model demonstrated direct binding of both N-terminal (KMT2AN) and C-terminal (AFF1C) and the FLAG-tagged KMT2A-fusion to the DYRK1A promoter. To assess if KMT2A fusion directly regulates DYRK1A expression, we treated SEM cells with the menin-KMT2A disrupter MI-503 and identified that the KMT2A fusion protein is a positive regulator of DYRK1A. Pharmacologic inhibition of DYRK1A with EHT1610 demonstrated potent leukemic cell growth inhibition, demonstrating that DYRK1 could be a new therapeutic target in KMT2A-R ALL. To further elucidate the mechanism of DYRK1A function, we treated several KMT2A-R ALL cell lines in vitro with EHT1610, which resulted in accumulation of CCND3 as expected. In addition, we detected upregulation of the positive cell cycle regulator MYC and the replication stress response molecule CHK1. In a second experiment, we validated the upregulation of MYC and identified significant upregulation of the proapoptotic protein BIM. Strikingly, meta-analysis of gene expression data from Dyrk1a-deleted murine pre-B cells isolated from a conditional Dyrk1a knockout mouse model also demonstrated increased levels of MYC and CHK1, validating that the EHT1610 mediated upregulation of MYC or CHK1 is a specific effect induced by DYRK1A inhibition. Western blot analysis demonstrated that KMT2A-R ALL cell lines have constitutive activation of pH2AX. Based on these data, we hypothesize that DYRK1A-mediated upregulation of CCND3 and MYC forces the cells to proliferate, which significantly increases replication stress and causes apoptosis, as evident by upregulation of CHK1 and BIM. To test if targeting the interaction of BIM with BCL2 will have an increased apoptotic effect when combined with EHT1610, we treated two KMT2A-R ALL cell lines with increasing concentrations of EHT1610 and the BCL2 inhibitor venetoclax. Strikingly, we observed a synergistic effect with both drugs, suggesting that combining these inhibitors has superior anti-leukemic activity. Conclusions: DYRK1A and MYC are positively regulated by the KMT2A fusion protein in KMT2A-R ALL and negatively regulate each other. Pharmacologic inhibition of DYRK1A resulted in significant growth disadvantage of KMT2A-R ALL cells due to increased MYC and CHK1 proteins that induce replication stress. While further in vivo studies are needed, we predict that combining DYRK1A inhibition with venetoclax may be a novel precision medicine strategy for KMT2A-R ALL that is translatable to the clinic for patients with these high-risk leukemias. Disclosures Tasian: Gilead Sciences: Research Funding; Aleta Biotherapeutics: Membership on an entity's Board of Directors or advisory committees; Incyte Corporation: Research Funding.

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