Ex Vivo Drug Sensitivity Assay Correlates with Clinical Response and Identifies Panobinostat and Bortezomib As a Potential Novel Drug Combination for Pediatric AML

Background Pediatric acute myeloid leukemia (AML) is a rare disease with roughly 600 cases diagnosed in the United States each year with minimal improvement in clinical outcomes over the last few decades. We previously demonstrated that an ex vivo drug sensitivity assay (DSA) can predict clinical response in myelodysplastic syndrome (Spinner et al. Blood Adv 2020). Here we investigated whether the DSA performed on pre-induction pediatric AML samples correlates with clinical response and can identify potent novel drug combinations. Methods Pre-induction blood or bone marrow samples were assayed from 20 de novo pediatric AML patients diagnosed at Texas Children's between 5/2015 and 10/2020. All patients consented to research (82% enrolled in clinical trial identifier NCT03568994) and received ADE (Cytarabine, Daunorubicin, and Etoposide), and next-generation sequencing was done as part of clinical care. Risk stratification was per AAML1831 guidelines. Drug sensitivity data was analyzed from 13/20 samples that passed quality control with matched treatment conditions: 9/13 (69%) patients had M1/M2 histology, 3/13 (23%) were M4/M5 and 1/13 (8%) was M7 with a median age of 12.3 years. For the ex vivo DSA, samples were incubated in conditioned media and treated with a single dose of up to 25 unique compounds and up to 149 drug combinations. After 72 hours, changes in tumor blast populations were assessed by flow cytometry using an 11-marker panel to identify blasts. For each treatment condition, drug sensitivity was calculated based on the number of blasts remaining after treatment compared to DMSO control. Clinical response data, including minimal residual disease (MRD) percentage by flow cytometry, and 1-year relapse-free survival (RFS), were correlated with drug sensitivity results. Log odds ratios (OR) were calculated with the Haldane-Anscombe correction. ORs were used to quantitatively measure the association between clinical attributes and the DSA to the clinical response data. For evaluation of ORs, a normalized blast score of 70% viability was used to maximize the separation between high and low drug sensitivity. Results Ex vivo drug sensitivity correlated with both MRD (r=0.63) and 1-year RFS (r=0.59) in the de novo patient subset (Fig A). Three patients with an MRD >1% exhibited low ex vivo sensitivity to ADE, and among these 3 patients, 2 did not achieve 1-year RFS. Results from the DSA predicted increased odds of having an MRD >1% compared to demographic and mutational clinical attributes that showed weaker associations with MRD (Fig B). Of the 77 treatment conditions that were tested in 13 patient samples, Bortezomib in combination with Panobinostat (B/P) was the most efficacious treatment in the DSA, where drug sensitivity ranged from low (>100% blast viability) to high (0% blast viability). Separation of patient samples into two distinct low and high DSA response groups was observed with B/P, whereas ADE and single agents showed a graded distribution (Fig C). Within these response groups, pAML3 showed low sensitivity to ADE in the ex vivo DSA and the patient did not respond to ADE. In contrast, pAML8 showed high sensitivity to ADE ex vivo and the patient responded to ADE treatment. While pAML3 and pAML8 showed similar ex vivo sensitivity to B/P as for ADE (Fig D), pAML4 showed preferential sensitivity to ADE and not B/P, and conversely pAML6 showed sensitivity to B/P and not ADE. Conclusion Ex vivo drug sensitivity to ADE correlates with both MRD and 1-year RFS in a cohort of 13 de novo pediatric AML patients. These results suggest that clinical response in pediatric AML may be assessed prior to treatment using an ex vivo drug sensitivity assay. Compared to demographic and mutational clinical characteristics queried, ex vivo drug sensitivity to ADE has the potential to be a more predictive measure compared to clinical attributes alone. Combining genomics with functional ex vivo drug sensitivity data could further enhance precision medicine and biomarker discovery in pediatric AML. The DSA also highlights Bortezomib/Panobinostat as a potential novel drug combination for pediatric AML, and the ability to identify a patient sample that is insensitive to ADE and sensitive to Bortezomib/Panobinostat ex vivo supports the use of the DSA to not only predict clinical response but also to possibly inform treatment decisions for pediatric AML patients. Figure 1 Figure 1. Disclosures Strachan: Notable Labs: Current Employment, Current holder of stock options in a privately-held company. Gu: Notable Labs: Current Employment, Current holder of stock options in a privately-held company. Kita: Notable Labs: Current Employment, Current holder of stock options in a privately-held company. Richardson: Notable Labs: Current holder of stock options in a privately-held company, Ended employment in the past 24 months. Anderson: Notable Labs: Current holder of individual stocks in a privately-held company, Ended employment in the past 24 months. Santaguida: Notable Labs: Consultancy, Current holder of individual stocks in a privately-held company, Ended employment in the past 24 months, Patents & Royalties.

Custom High Throughput Drug Sensitivity Assay Reveals Therapeutic Options for Chronic Myeloid Leukemia Patients Resistant to or Intolerant of Tyrosine Kinase Inhibitors

Introduction. Tyrosine kinase inhibitors (TKIs) have revolutionized chronic phase (CP) chronic myeloid leukemia (CML) care with many patients achieving major and deeper molecular responses. However, for those who are resistant to or do not tolerate the approved TKIs, there are few alternatives. We therefore developed a custom high throughput drug screen comprised of both FDA approved and investigational agents. Methods. Fifty-six samples (50 individual patients) have undergone testing in the drug sensitivity assay, for which a large fraction exhibited resistance to approved agents. The Quellos High Throughput Core Laboratory's Cancer Drug Sensitivity has been CLIA approved for leukemia since 2015. Blood and bone marrow samples were obtained from CML patients with written informed consent. Mononuclear cells were isolated by density depletion. The myeloid population was obtained by lineage depletion of non-myeloid cells using magnetic beads and antibodies to erythroid lineage (CD235a), T (CD3) and B (CD19) lymphocytes, and NK (CD56) cells. Flow cytometry confirmed successful enrichment of the myeloid cell population. Cells were plated on extracellular matrix coated 384 well plates to test under conditions of adhesion mediated chemotherapy resistance. Initially, the assay was comprised of 32 drugs (11 patients) selected based on published activity in CML and resistant CML. The assay was then expanded to 64 drugs. Compounds are added (ranging from 5 pM to 100 μM) to patient samples using the CyBio CyBi-Well Vario and incubated at 37°C, 5% CO2 for 72 hours, then viability is assessed by CellTiterGlo. IC50s and AUCs are calculated for each drug using XLFit (IDBS) and a standard 4 parameter logistical model. Transcriptome analysis is planned for these samples. Results. Clinical characteristics are shown in Table 1. Mean and median BCR-ABL1 transcripts were 69% and 70% in diagnosis samples and 63% and 55% in resistant samples, respectively (P=0.607). ABL mutations were present in 5 patients (M244V, T315I, F359I). Additional myeloid mutations were present in 5 of 6 evaluable advanced phase samples, 4 of 17 evaluable diagnostic samples, and 3 of 10 evaluable resistant samples and included ASXL1, DNMT3A, IDH1, JAK2V617F, NRAS, RUNX1, and TET2. Figure 1 illustrates the breadth of sensitivity to agents in the assay. Figure 2 is a heat map of area under the curve (AUCs) illustrating the unique drug sensitivity patterns for all patients, with unsupervised clustering. For new diagnosis patients, the TKIs imatinib, dasatinib, nilotinib, bosutinib, and ponatinib ranked in the top 8 drugs. For primary resistant patients, the IC50 values for imatinib, nilotinib, bosutinib, and ponatinib were higher than the new diagnosis patients. For example, for ponatinib, the mean IC50 was 402.6 ± 354.7 X 10 E-9 M for primary resistant samples vs. 1.65 ± 0.45 X 10 E-9 M for diagnosis group, p=0.015 (Welch t test), or about 250-fold higher (less sensitive). In accelerated and blast phase samples drugs with IC50 values lower than 0.1 µM, a range that could correlate with in vivo drug response, were identified for all patients (range, 3-20 drugs per patient). Top candidates included proteasome and kinase inhibitors. In 2 patients harboring NRAS mutations, IC50 for trametinib was less than 0.1 µM as compared to patients without NRAS mutations, where the IC50s were higher. Clinical outcomes are available for nearly all patients. Although the study was not designed to select next-line TKI therapy in resistant patients, drug profiling was informative in many cases. Data for 7 resistant patients are shown in Table 2. For example, CML-012 had the lowest IC50 value (indicating most sensitive) for dasatinib, 4.1 X 10E-8 M and responded to dasatinib after failing imatinib (IC50 8.4 X 10E-7M). CML-003 did not respond to bosutinib (IC50 1.2 X 10E-6M) and did respond to dasatinib (IC50 1.2 X 10E-7M). CML-056 did not respond to nilotinib (IC50 1.4 X 10E-6M), dasatinib (IC50 6.9 X 10E-4M), or ponatinib (IC50 1.0 X 10E-6M). Notably, in all resistant patient samples we identified drugs with IC50 values lower than 0.1 µM. These therapeutics can be prioritized for further evaluation, either alone or in combination with TKIs, in resistant CML patients. Conclusion. In vitro drug sensitivity testing provides data for potential agents for patients with resistance or intolerance to FDA approved TKIs, or those that have entered accelerated phase or blast phase. Figure 1 Figure 1. Disclosures Oehler: Blueprint Medicines: Consultancy; Takeda: Consultancy; Pfizer: Research Funding; OncLive: Honoraria; BMS: Consultancy. Becker: Abbie: Research Funding; SecuraBio: Research Funding; Cardiff Oncology: Research Funding; Pfizer: Research Funding; BMS: Research Funding; CVS Caremark: Consultancy; Glycomimetics: Research Funding. OffLabel Disclosure: We developed a custom high throughput drug screen comprised of both FDA approved and investigational agents

Development of a multiomics and functional drug sensitivity platform to investigate cell type specific drug effects in AML.

e19013 Background: Understanding the heterogeneity of AML is necessary for developing targeted drugs and diagnostics. A key measure of heterogeneity is the variance in response to treatments. Previously, we developed an ex vivo flow cytometry drug sensitivity assay (DSA) that predicted response to treatments in myelodysplastic syndrome. Unlike bulk cell viability measures of other drug sensitivity assays, our flow cytometry assay provides single cell resolution. The assay measures a drug’s effect on the viability or functional state of specific cell types. Here we present the development of this technology for AML, with additional measurements of DNA-Seq and RNA-Seq. Using the data from this assay, we aim to characterize the heterogeneity in AML drug sensitivity and the molecular mechanisms that drive it. Methods: As an initial feasibility analysis, we assayed 1 bone marrow and 3 peripheral blood AML patient samples. For the DSA, the samples were cultured with six AML standard of care (SOC) compounds across seven doses, in addition to two combinations. The cells were stained to detect multiple cell types including tumor blasts, and drug response was measured by flow cytometry. For the multi-omics, the cells were magnetically sorted to enrich for blasts and then assayed using a targeted 400 gene DNA-Seq panel and whole bulk transcriptome RNA-Seq. For comparison with BeatAML, Pearson correlations between gene expression and venetoclax sensitivity were investigated. Results: In our drug sensitivity assay, we measured dose response curves for the six SOC compounds, for each different cell type across each sample. The dose responses had cell type specific effects, including differences in drug response between CD11b+ blasts, CD11b- blasts, and other non-blast populations. Integrating with the DNA-Seq and RNA-Seq data, known associations between ex vivo drug response and gene expression were identified with additional cell type specificity. For example, BCL2A1 expression was negatively correlated with venetoclax sensitivity in CD11b- blasts but not in CD11b+ blasts. To further corroborate, among the top 1000 genes associated with venetoclax sensitivity in BeatAML, 93.7% had concordant directionality in effect. Conclusions: Here we describe the development of an integrated ex vivo drug sensitivity assay and multi-omics dataset. The data demonstrated that ex vivo responses to compounds differ between cell types, highlighting the importance of measuring drug response in specific cell types. In addition, we demonstrated that integrating these data will provide unique insights on molecular mechanisms that affect cell type specific drug response. As we continue to expand the number of patient samples evaluated with our multi-dimensional platform, this dataset will provide insights for novel drug target discovery, biomarker development, and, in the future, informing treatment decisions.

Genetic profiling of the Plasmodium falciparum parasite population in uncomplicated malaria from India

Background The genetic complexity and the existence of several polymorphisms in parasites are the major hindrances for the malaria control programmes of the country. The genetic profiling in the parasite populations in India will provide useful baseline data for future studies elucidating the parasite structure and distribution of drug resistance genotypes in different regions. Methods The blood samples of symptomatic patients were collected and analysed for drug resistance genes (Pfcrt, Pfmdr-1, dhfr, dhps and k13) and gametocyte genes (Pfs25, Pfg377); in vitro drug sensitivity assay by schizont maturation inhibition (SMI) was also performed in adapted field isolates. Results Of the 122 field isolates analysed; 65.5% showed Pfcrt K76T mutant alleles, 61.4% Pfmdr-1 N86Y mutants, 59.5% dhfr mutants, 59.8% dhps mutants was observed, but no polymorphism was seen for k13. The sequence analysis of Pfg377 gene revealed five types of populations in the field isolates. The inhibitory concentrations (IC50) for anti-malarial drugs viz chloroquine (CQ), artesunate (AS), were in the range of 10.11–113.2 nM and 2.26–4.08 nM, respectively, in the field isolates evaluate by in vitro assay. The IC50 values for CQ have shown a remarkable reduction on comparison with the previous available data, whereas a slight increase in the IC50 values for AS was observed in the study. Conclusions The increase in mutation rate in drug resistance allelic loci with inhibitory concentration of CQ and AS drugs was observed in the field isolates and high diversity in Pfg377 gametocyte gene indicate towards parasite multifactorial behaviour. The knowledge of the prevalent drug resistance genes is important for intervention measures to be successful and efforts should also be made to prevent transmission of P. falciparum.

High Throughput Drug Synergy Testing in a Clinical Trial of Panobinostat, Carfilzomib, Dexamethasone to Define Response Biomarkers for Relapsed/Refractory Multiple Myeloma

Background: The treatment of multiple myeloma (MM) is optimized by use of combination regimens consisting of agents with different mechanisms of action. Panobinostat is a pan-inhibitor of histone deacetylases types I,II, and IV. Panobinostat, bortezomib, dexamethasone was shown to be an effective regimen (San Miguel et al Lancet Hematol 2016; Richardson et al Blood 2016), leading to the FDA approval of panobinostat for patients with relapsed/refractory MM. Carfilzomib is a proteasome inhibitor that was FDA approved in relapsed/refractory MM with the advantage of minimal neuropathy. Panobinostat and carfilzomib has also been shown to be a highly active regimen in relapsed/refractory MM with an overall response rate of up to 75% (Berdeja et al, Haematologica, 2015). With the heterogeneity of MM, individual patients exhibit wide variability in responses to drug combinations. A test that could predict patient responses to specific agents might enable clinicians to optimize therapy for patients, improving outcomes. We developed an in vitro high throughput drug sensitivity assay with formal synergy testing to predict response. In this ongoing trial, Panobinostat with Carfilzomib and Dexamethasone for Relapsed/Refractory Multiple Myeloma: Correlation with In Vitro Chemosensitivity Testing (NCT03256045), we will correlate individual patient in vitro sensitivity assay results with individual clinical response to the same triple drug regimen. Study Design and Methods: This study's objective is to directly demonstrate the utility of a high throughput drug sensitivity assay in determining biomarkers (e.g. individual IC50s, AUCs and/or synergy scores) to accurately predict response to combination therapy that was given prospectively to all enrolled patients. We are enrolling patients with relapsed/refractory MM by IMWG criteria with measurable disease defined by the detection of a quantifiable monoclonal protein in the urine or serum or an abnormal serum free light chain ratio. Additionally, patients must have adequate blood counts and organ function. Patients who have had prior autologous or allogeneic transplants or CAR-T cell therapy are eligible. The regimen consists of panobinostat 20 mg orally on days 1,3,5,15,17,19; carfilzomib 20 mg/m2/dose IV on days 1,2 of cycle 1, then dose escalation up to 45 mg/m2/dose days 8,9,15,16 and all days for subsequent cycles; and dexamethasone 20 mg orally on days of carfilzomib. Dose reductions of all three drugs are permitted per patient tolerance to allow continuation on study treatment. Up to 12 cycles of treatment are permitted. Patients are monitored by serial electrocardiograms and assessments of cardiac function. Safety parameters including adverse events are recorded. CD138+ plasma cells are procured from the patient bone marrow (aspiration and biopsy) and blood (when present) by magnetic bead separation. Cells are then added to 384-well plates and incubated overnight before the drugs are added. Cells are exposed to 8 concentrations (spanning 4 logs) of panobinostat, carfilzomib, or dexamethasone as singlet, doublet and triplet combinations for 72 hours. Cell viability is determined using CellTiter-Glo and IC50 and AUC values are are calculated by fitting data using least squares method to the standard four-parameter logistic model. Curve fitting is performed using IDBS XLFit software. The combination index is calculated by the method described by Chou and Talalay, Trends Pharmacol Sci 1983;4:450-4. Concentrations of Drug1 and Drug2 (that is, panobinostat and dexamethasone or panobinostat and carfilzomib) alone or in combinations are determined that give rise to 90% growth inhibition. At 90% Growth Inhibition, the Combination Index or CI = ([D1] in the combination / [D1] alone) + ([D2] in the combination / [D2] alone). All patients are treated with panobinostat, carfilzomib, and dexamethasone and evaluated for response using the IMWG response criteria. At the completion of enrollment at 35 patients, we plan to correlate the in vitro testing data with in vivo clinical response to determine appropriate biomarkers. This will be done by correlating the IC50s and AUCs for the individual drugs for responders vs. non-responders (including degree of response VGPR vs PR vs SD), as well as correlations of the synergy scores for each of the pairs of drugs in the responders vs. non-responders. Enrollment was initiated in April 2018. Disclosures Becker: Accordant Health Services/Caremark: Consultancy; AbbVie, Amgen, Bristol-Myers Squibb, Glycomimetics, Invivoscribe, JW Pharmaceuticals, Novartis, Trovagene: Research Funding; The France Foundation: Honoraria. Libby:Abbvie: Consultancy; Pharmacyclics and Janssen: Consultancy; Akcea: Consultancy; Alnylam: Consultancy. Cowan:Juno: Research Funding; Abbvie: Research Funding; Sanofi: Consultancy; Janssen: Consultancy, Research Funding; Cellectar: Consultancy; Celgene: Consultancy, Research Funding. Hammer:Glycomimetics: Consultancy.

Extracellular Vesicle-derived circular RNAs confers chemoresistance in Colorectal cancer

Chemo-resistance is associated with poor prognosis in colorectal cancer (CRC), with the absence of early biomarker. Exosomes are microvesicles released by body cells for intercellular communication. Circular RNAs (circRNAs) are non-coding RNAs with covalently closed loops and enriched in exosomes. Crosstalk between circRNAs in exosomes and chemo-resistance in CRC remains unknown. This research aims to identify exosomal circRNAs associated with FOLFOX-resistance in CRC. FOLFOX-resistant HCT116 CRC cells (HCT116-R) were generated from parental HCT116 cells (HCT116-P) using periodic drug induction. Exosomes were characterized using transmission electron microscopy (TEM), Zetasizer and Western blot. Our exosomes were translucent cup-shaped structures under TEM with differential expression of TSG101, CD9, and CD63. We performed circRNAs microarray using exosomal RNAs from HCT116-R and HCT116-P cells. We validated our microarray data using serum samples. We performed drug sensitivity assay and cell cycle analysis to characterize selected circRNA after siRNA-knockdown. Using fold change >2 and p < 0.05, we identified 105 significantly upregulated and 34 downregulated circRNAs in HCT116-R exosomes. Knockdown of circ_0000338 improved the chemo-resistance of CRC cells. We have proposed that circ_0000338 may have dual regulatory roles in chemo-resistant CRC. Exosomal circ_0000338 could be a potential biomarker for further validation in CRC.