Introduction: Low-grade and secondary high-grade gliomas frequently contain a mutation in the IDH1 metabolic enzyme that is hypothesized to drive tumorigenesis by inhibiting many of the chromatin-regulating enzymes that regulate DNA structure. Much of the previous research has focused on DNA methylation leaving histone modifications relatively under-studied. Histone deacetylase inhibitors are promising anti-cancer agents and have already been used in clinical trials, however a clear understanding of their mechanism or gene targets is lacking. In this study, the authors genetically dissect patient-derived IDH1 mutant cultures to determine which HDAC enzymes drive growth in IDH1 mutant gliomas and what are the down-stream gene targets. This information will allow clinicians to design more specific HDAC inhibitors as well as monitor for treatment response. Methods: A panel of patient-derived gliomasphere cell lines (2 IDH1 mutant lines, 3 IDH1 wildtype lines) were subjected to a drug-screen of 110 epigenetic modifying drugs from 34 different epigenetic classes. The effect of LBH (Panobinostat) on gene expression and chromatin structure was tested on patient-derived IDH1 mutant lines. The role of each of the highly expressed HDAC enzymes was molecularly dissected using lentiviral RNA interference knock-down vectors and a patient-derived IDH1 mutant in vitro model of glioblastoma (HK252). These results were then confirmed in an in vivo xenotransplant model (BT-142). Results: The IDH1 mutation leads to gene down-regulation, DNA hypermethylation, increased DNA accessibility and H3K27 hypo-acetylation in two distinct IDH1 mutant over-expression models. The drug screen identified histone deacetylase inhibitors (HDACi) and Panobinostat (LBH) more specifically as the most selective compounds to inhibit growth in IDH1 mutant glioma lines. Of the eleven annotated HDAC enzymes (HDAC1-11) only six are expressed in IDH1 mutant glioma tissue samples and patient-derived gliomasphere lines (HDAC1, HDAC2, HDAC3, HDAC4, HDAC6, HDAC9). Lentiviral knock-down experiments revealed that HDAC1 and HDAC6 are the most consistently essential for growth both in vitro and in vivo and target very different gene modules. Knock-down of HDAC1 or HDAC6 in vivo led to a more circumscribed less invasive tumor. Conclusions: The gene dysregulation induced by the IDH1 mutation is wide-spread and only partially reversible by direct IDH1 inhibition. This study reports a previously under-described phenomenon of histone deacetylation induced by the IDH1 mutant enzyme and identifies HDAC1 and HDAC6 as important and drug-targetable enzymes that are necessary for growth and invasiveness in IDH1 mutant gliomas.

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Background: Resistance to chemotherapy-induced apoptotic death is a major mechanism responsible for the failure of AML therapies. Levels of anti-apoptotic proteins BCL2 and MCL1 are increased in relapsed AML samples. Venetoclax, a BH3 mimetic that binds to BCL-2, was recently granted accelerated approval for use in AML in combination with cytotoxic chemotherapy. However, MCL-1 and BCL-XL are known pathways of resistance to BCL-2 directed therapy. AMG-176 is a first-in-class MCL-1 specific inhibitor that induces specific and significant apoptosis-mediated toxicity against leukemia cell lines, tumor xenograft models, and primary patient samples. We compared anti-leukemic synergy of Venetoclax and AMG-176 together and individually with cytotoxic chemotherapy used in AML. We sought to identify optimal combinations for efficacy against varying molecular signatures of AML. Methods: To examine the potential of pairing Venetoclax with AMG-176 we performed a series of in vitro 8x8 dose response matrices on a panel of 11 leukemias spanning AML and Acute Lymphocytic Leukemia (ALL) (Table). This included 3 relapsed pediatric Patient Derived Xenograft (PDX) AML lines propagated in the presence of cytokines to better model inflammation, stem cell function, and niche derived support of leukemic blasts. An additional 8 established cell lines representing key AML & ALL molecular classes were employed. We used the Delta Bliss (DB) method for scoring matrices and report the DBsum, the summation of all of the synergistic(-) and antagonistic(+) well scores in an 8x8 matrix. Drugs tested in combinations with Venetoclax and/or AMG-176 included cytarabine and daunorubicin. Results: The Figure shows average DBSum for the Venetoclax+AMG-176 combination was -3.41 in the 8 commercial lines, whereas combining the anthracycline Daunorubicin+AMG-176 combination yielded a DBsum score of -0.34, with the score being skewed by a marked antagonism observed with the t(8;21) AML line Kasumi-1 with a DBSum score of 2.13. The 3 relapsed pediatric PDX derived AML lines continued the trend of strong synergy with the Venetoclax+AMG-176 combination with an average score of -3.68 with no observed antagonistic interactions. For context, a synergistic DBSum score of -2.33 would be considered noteworthy from a combination dataset of over >4000 discreet combinations. The Venetoclax+AMG-176 combination exhibited the highest degree of synergy broadly across AML and ALL molecular subgroups. Different patterns of cytotoxicity of combination of chemotherapy with BCL2 or MCL1 inhibition were observed in leukemias with varying molecular backgrounds and histology, including patterns of strong synergy, additivity or antagonism. However, leukemias carrying KMT2A rearrangements exhibited strong synergy or additivity of BCL2 or MCL1 combinations with either daunorubicin or cytarabine, regardless of histology. Conclusions: We identified broad synergy in high risk genetic subtypes of AML and ALL with the combination of BCL-2 and MCL-1 inhibition, and the effect was superior to either agent combined with chemotherapy individually. We identified potential genetic signatures associated with response to chemotherapy cytotoxicity with either Venetoclax or AMG-176. In vivo experiments are in progress to evaluate the efficacy of this combination and better determine genetic subtypes who would most benefit from this treatment approach. Figure Disclosures Perentesis: Kurome Therapeutics: Consultancy.

Each case of Acute Myeloid Leukemia (AML) represents a unique ecosystem. Despite recent advances in our understanding of the genetic landscape of AML, this information remains insufficient to accurately match patients with targeted therapies. While pediatric and adult AML share phenotypic similarities, pediatric AML represents a genetically distinct disease from adult AML, and will benefit from independent genomic studies and novel therapeutic strategies. Real-time ex-vivo functional screening can identify mechanisms underpinning drug response and diversity between tumors, aiding in patient stratification. We established an in vitro drug screening system that incorporates cytokine signaling to better model inflammation, stem cell function, and niche derived support of leukemic blasts. This approach provided insight into variability between patients who currently would be placed on the same therapeutic regimen. Samples were acquired from 12 pediatric AML patients, after informed consent was obtained. Samples were enriched for blasts, and cultured in the presence of SCF, TPO, FLT3-L, IL-3, and IL-6 (KTF36). A panel of 38 drugs was selected from a larger screen of 1839 compounds done on commercially available hematological malignancy cell lines. Drugs included standard chemotherapy agents used in AML and drugs currently under clinical development. Cells were exposed to drugs for 72hrs. An MTS assay was performed and results reported as % of viable cells remaining, after normalization to vehicle control wells. Targeted DNA NGS sequencing of 406 genes, 31 introns, and RNA sequencing of 265 genes was performed for genetic characterization. In vitro drug screening revealed variations in drug sensitivity between samples and revealed time ex-vivo and cytokine milieu to be important factors affecting response of the same cells to the same drugs. Engraftment of long term cultures into immunodeficient mice produced aggressive disease in all cases, indicating robust support of stem cell function via addition of KTF36 cytokines. When possible, clinical response to therapy was compared with in vitro response to the same drugs. This screening approach highlighted well established agents that showed significant activity in highly refractory disease providing rationale for further clinical trial development. An unsupervised clustering showed drug sensitivity primarily correlated with the presence of MLL-X fusion, NRAS/KRAS and PTPN11 alterations. Linear Regression with interaction effects showed drug sensitivity/resistance to be highly selective for single/signature of specific molecular alterations. Figure. Figure. Disclosures No relevant conflicts of interest to declare.

Background: Hematologic malignancies present a varied genetic landscape that plays an important role in prognosis and therapeutic outcome of patients. However, our understanding of the impact of a patient's molecular alterations on therapy is limited. Cell Line-Based High Throughput Screening (CBHTS) can allow novel drug discovery and systematic evaluation of drug response in cell lines or patient samples to large panels of drugs. Here, we present a comprehensive profiling of molecular alterations in hematologic malignancies and their impact on drug response, which we believe provides novel insight into drug sensitivity and resistance correlated with unique molecular alteration signatures as well as clinical trial development. Methods: Cell lines were acquired from ATCC, suspended in growth media, plated in 384 well plates, and allowed to proliferate for 24 hours before addition of drugs. Compounds were obtained from Selleck Chemicals and were added to cells at concentrations of 100nM and 1nM in quadruplicate, with a 0.1% concentration of DMSO. Cell viability was measured after 72 hours with drugs. DMSO was used as the vehicle control, and all drug effects are normalized to the DMSO control and reported as percent viable. Drug activity was studied across a panel of 1,828 drugs and 30 cell-lines. Drug activity clusters were defined using unsupervised learning (Distance metric: Euclidean and Ward linkage; tree height: 1.2). Cell lines were annotated using Broad CCLE and Gnomad database, and mutations were ranked into four groups based on predicted variant effect - high, medium, low, and modifier. Drugs were annotated using Anatomical Therapeutic Classification (ATC), while pathways and targets were annotated using ToppGene Suite. T-statistic was used to estimate significance of differential drug activity between sensitive (cell-lines with viability <20% considered highly sensitive) versus resistant cell-line groups (cell-lines with viability >85% considered highly resistant). Results: We identified 25 clusters with significant differential drug activity across the 30 cell lines. Corticosteroids (n=19), for example, clustered together by activity profile, and showed most differential response across five cell lines: NB4 (Acute Myeloid Leukemia, AML), Kasumi-1 (AML), HL-60 (Acute Lymphoblastic Leukemia, ALL), RS4-11 (ALL) and MV4-11 (Biphenotypic Acute Leukemia, BAL), p = 6.10-27. Steroid activity was minimal in NB4, MV4-11 and HL-60; however, highest in RS4-11 (<11% cell viability) and Kasumi-1. Interestingly, loxapine, an antipsychotic, which acts as a dopamine and serotonin 5-HT2 antagonist, clustered with the main corticosteroid group, and shared similar activity profile (p = 5.5 10-3). A unique gene signature common to RS4-11 and Kasumi-1 included mutations in LOXHD1, FBN3, TRIB3, TDRD6, ALX4, ALDH3B2, NT5DC3, TTC3, ZFAT and GLI2 with moderate variant effects impacting key hematologic processes. Conclusions: This high-dimensional screening against a backdrop of molecular alterations highlighted a potential for correlating differential drug activity with a patient's genetic landscape, with potential for experimental validation and clinical trial development. This pilot study further demonstrates that drug response in hematologic malignancy cell lines may be uniquely driven by a signature of molecular alterations sensitive to single or multiple therapeutic classes and provides rationale for novel drug discovery and drug repositioning in precision medicine. Disclosures No relevant conflicts of interest to declare.