Ex vivo drug screening defines novel drug sensitivity patterns for informing personalized therapy in myeloid neoplasms

Integrated drug profiling and CRISPR screening identify BCR::ABL1-independent vulnerabilities in chronic myeloid leukemia

BCR::ABL1-independent pathways contribute to primary resistance to tyrosine kinase inhibitor (TKI) treatment in chronic myeloid leukemia (CML) and play a role in leukemic stem cell persistence. Here, we perform ex vivo drug screening of CML CD34+ leukemic stem/progenitor cells using 100 single drugs and TKI-drug combinations and identify sensitivities to Wee1, MDM2, and BCL2 inhibitors. These agents effectively inhibit primitive CD34+CD38- CML cells and demonstrate potent synergies when combined with TKIs. Flow-cytometry-based drug screening identifies mepacrine to induce differentiation of CD34+CD38- cells. We employ genome-wide CRISPR-Cas9 screening for six drugs, and mediator complex, apoptosis, and erythroid-lineage-related genes are identified as key resistance hits for TKIs, whereas the Wee1 inhibitor AZD1775 and mepacrine exhibit distinct resistance profiles. KCTD5, a consistent TKI-resistance-conferring gene, is found to mediate TKI-induced BCR::ABL1 ubiquitination. In summary, we delineate potential mechanisms for primary TKI resistance and non-BCR::ABL1-targeting drugs, offering insights for optimizing CML treatment.

Ex vivo discovery of synergistic drug combinations for hematologic malignancies

Combination therapies have improved outcomes for patients with acute myeloid leukemia (AML). However, these patients still have poor overall survival. Although many combination therapies are identified with high-throughput screening (HTS), these approaches are constrained to disease models that can be grown in large volumes (e.g., immortalized cell lines), which have limited translational utility. To identify more effective and personalized treatments, we need better strategies for screening and exploring potential combination therapies. Our objective was to develop an HTS platform for identifying effective combination therapies with highly translatable ex vivo disease models that use size-limited, primary samples from patients with leukemia (AML and myelodysplastic syndrome). We developed a system, ComboFlow, that comprises three main components: MiniFlow, ComboPooler, and AutoGater. MiniFlow conducts ex vivo drug screening with a miniaturized flow-cytometry assay that uses minimal amounts of patient sample to maximize throughput. ComboPooler incorporates computational methods to design efficient screens of pooled drug combinations. AutoGater is an automated gating classifier for flow cytometry that uses machine learning to rapidly analyze the large datasets generated by the assay. We used ComboFlow to efficiently screen more than 3000 drug combinations across 20 patient samples using only 6 million cells per patient sample. In this screen, ComboFlow identified the known synergistic combination of bortezomib and panobinostat. ComboFlow also identified a novel drug combination, dactinomycin and fludarabine, that synergistically killed leukemic cells in 35 % of AML samples. This combination also had limited effects in normal, hematopoietic progenitors. In conclusion, ComboFlow enables exploration of massive landscapes of drug combinations that were previously inaccessible in ex vivo models. We envision that ComboFlow can be used to discover more effective and personalized combination therapies for cancers amenable to ex vivo models.

Clinical forecasting of acute myeloid leukemia using ex vivo drug-sensitivity profiling

Current treatment selection for acute myeloid leukemia (AML) patients depends on risk stratification based on cytogenetic and genomic markers. However, the forecasting accuracy of treatment response remains modest, with most patients receiving intensive chemotherapy. Recently, ex vivo drug screening has gained traction in personalized treatment selection and as a tool for mapping patient groups based on relevant cancer dependencies. Here, we systematically evaluated the use of drug sensitivity profiling for predicting patient survival and clinical response to chemotherapy in a cohort of AML patients. We compared computational methodologies for scoring drug efficacy and characterized tools to counter noise and batch-related confounders pervasive in high-throughput drug testing. We show that ex vivo drug sensitivity profiling is a robust and versatile approach to patient prognostics that comprehensively maps functional signatures of treatment response and disease progression. In conclusion, ex vivo drug profiling can assess risk for individual AML patients and may guide clinical decision-making.

Tretinoin Enhances the Effects of Chemotherapy in Juvenile Myelomonocytic Leukemia Using an Ex Vivo Drug Sensitivity Assay

PURPOSE

Juvenile myelomonocytic leukemia (JMML) is an aggressive pediatric malignancy with myelodysplastic and myeloproliferative features. Curative treatment is restricted to hematopoietic stem-cell transplantation. Fludarabine combined with cytarabine (FLA) and 5-azacitidine (AZA) monotherapy are commonly used pre-transplant therapies. Here, we present a drug screening strategy using a flow cytometry-based precision medicine platform to identify potential additional therapeutic vulnerabilities.

METHODS

We screened 120 dual- and 10 triple-drug combinations (DCs) on peripheral blood (n = 21) or bone marrow (n = 6) samples from 27 children with JMML to identify DCs more effectively reducing leukemic cells than the DCs' components on their own. If fewer leukemic cells survived a DC ex vivo treatment compared with that DC's most effective component alone, the drug effect was referred to as cooperative. The difference between the two resistant fractions is the effect size.

RESULTS

We identified 26 dual- and one triple-DC more effective than their components. The differentiation agent tretinoin (TRET; all-trans retinoic acid) reduced the resistant fraction of FLA in 19/21 (90%) samples (decrease from 15% [2%-61%] to 11% [2%-50%] with a mean effect size of 3.8% [0.5%-11%]), and of AZA in 19/25 (76%) samples (decrease from 69% [34%-100+%] to 47% [17%-83%] with a mean effect size of 16% [0.3%-40%]). Among the resistant fractions, the mean proportion of CD38+ cells increased from 7% (0.03%-25%; FLA) to 17% (0.3%-38%; FLA + TRET) or from 10% (0.2%-31%; AZA) to 51% (0.8%-88%; AZA + TRET).

CONCLUSION

TRET enhanced the effects of FLA and AZA in ex vivo assays with primary JMML samples.

Resistance to vincristine in DLBCL by disruption of p53-induced cell cycle arrest and apoptosis mediated by KIF18B and USP28

The frontline therapy R-CHOP for patients with diffuse large B-cell lymphoma (DLBCL) has remained unchanged for two decades despite numerous Phase III clinical trials investigating new alternatives. Multiple large studies have uncovered genetic subtypes of DLBCL enabling a targeted approach. To further pave the way for precision oncology, we perform genome-wide CRISPR screening to uncover the cellular response to one of the components of R-CHOP, vincristine, in the DLBCL cell line SU-DHL-5. We discover important pathways and subnetworks using gene-set enrichment analysis and protein-protein interaction networks and identify genes related to mitotic spindle organization that are essential during vincristine treatment. The inhibition of KIF18A, a mediator of chromosome alignment, using the small molecule inhibitor BTB-1 causes complete cell death in a synergistic manner when administered together with vincristine. We also identify the genes KIF18B and USP28 of which CRISPR/Cas9-directed knockout induces vincristine resistance across two DLBCL cell lines. Mechanistic studies show that lack of KIF18B or USP28 counteracts a vincristine-induced p53 response suggesting that resistance to vincristine has origin in the mitotic surveillance pathway (USP28-53BP1-p53). Collectively, our CRISPR screening data uncover potential drug targets and mechanisms behind vincristine resistance, which may support the development of future drug regimens.

Ex vivo venetoclax sensitivity testing predicts treatment response in acute myeloid leukemia

The BCL-2 inhibitor venetoclax has revolutionized the treatment of acute myeloid leukemia (AML) in patients not benefiting from intensive chemotherapy. Nevertheless, treatment failure remains a challenge, and predictive markers are needed, particularly for relapsed or refractory AML. Ex vivo drug sensitivity testing may correlate with outcomes, but its prospective predictive value remains unexplored. Here we report the results of the first stage of the prospective phase II VenEx trial evaluating the utility and predictiveness of venetoclax sensitivity testing using different cell culture conditions and cell viability assays in patients receiving venetoclax-azacitidine. Participants with de novo AML ineligible for intensive chemotherapy, relapsed or refractory AML, or secondary AML were included. The primary endpoint was the treatment response in participants showing ex vivo sensitivity and the key secondary endpoints were the correlation of sensitivity with responses and survival. Venetoclax sensitivity testing was successful in 38/39 participants. Experimental conditions significantly influenced the predictive accuracy. Blast-specific venetoclax sensitivity measured in conditioned medium most accurately correlated with treatment outcomes; 88% of sensitive participants achieved a treatment response. The median survival was significantly longer for participants who were ex vivo-sensitive to venetoclax (14.6 months for venetoclax-sensitive patients vs. 3.5 for venetoclax-insensitive patients, P<0.001). This analysis illustrates the feasibility of integrating drug-response profiling into clinical practice and demonstrates excellent predictivity. This trial is registered with ClinicalTrials.gov identifier: NCT04267081.

Early response evaluation by single cell signaling profiling in acute myeloid leukemia

Aberrant pro-survival signaling is a hallmark of cancer cells, but the response to chemotherapy is poorly understood. In this study, we investigate the initial signaling response to standard induction chemotherapy in a cohort of 32 acute myeloid leukemia (AML) patients, using 36-dimensional mass cytometry. Through supervised and unsupervised machine learning approaches, we find that reduction of extracellular-signal-regulated kinase (ERK) 1/2 and p38 mitogen-activated protein kinase (MAPK) phosphorylation in the myeloid cell compartment 24 h post-chemotherapy is a significant predictor of patient 5-year overall survival in this cohort. Validation by RNA sequencing shows induction of MAPK target gene expression in patients with high phospho-ERK1/2 24 h post-chemotherapy, while proteomics confirm an increase of the p38 prime target MAPK activated protein kinase 2 (MAPKAPK2). In this study, we demonstrate that mass cytometry can be a valuable tool for early response evaluation in AML and elucidate the potential of functional signaling analyses in precision oncology diagnostics.

Cancer: slaying the nine-headed Hydra

Modern medicine continues to evolve, and the treatment armamentarium for various diseases grows more individualized across a breadth of medical disciplines. Cure rates for infectious diseases that were previously pan-fatal approach 100% because of the identification of the specific pathogen(s) involved and the use of appropriate combinations of drugs, where needed, to completely extinguish infection and hence prevent emergence of resistant strains. Similarly, with the assistance of technologies such as next-generation sequencing and immunomic analysis as part of the contemporary oncology armory, therapies can be tailored to each tumor. Importantly, molecular interrogation has revealed that metastatic cancers are distinct from each other and complex. Therefore, it is conceivable that rational personalized drug combinations will be needed to eradicate cancers, and eradication will be necessary to mitigate clonal evolution and resistance.

Ex Vivo Drug Sensitivity Correlates with Clinical Response and Supports Personalized Therapy in Pediatric AML

Acute myeloid leukemia (AML) is a heterogeneous disease that accounts for ~20% of all childhood leukemias, and more than 40% of children with AML relapse within three years of diagnosis. Although recent efforts have focused on developing a precise medicine-based approach towards treating AML in adults, there remains a critical gap in therapies designed specifically for children. Here, we present ex vivo drug sensitivity profiles for children with de novo AML using an automated flow cytometry platform. Fresh diagnostic blood or bone marrow aspirate samples were screened for sensitivity in response to 78 dose conditions by measuring the reduction in leukemic blasts relative to the control. In pediatric patients treated with conventional chemotherapy, comprising cytarabine, daunorubicin and etoposide (ADE), ex vivo drug sensitivity results correlated with minimal residual disease (r = 0.63) and one year relapse-free survival (r = 0.70; AUROC = 0.94). In the de novo ADE analysis cohort of 13 patients, AML cells showed greater sensitivity to bortezomib/panobinostat compared with ADE, and comparable sensitivity between venetoclax/azacitidine and ADE ex vivo. Two patients showed a differential response between ADE and bortezomib/panobinostat, thus supporting the incorporation of ex vivo drug sensitivity testing in clinical trials to further evaluate the predictive utility of this platform in children with AML.

A pipeline for malignancy and therapy agnostic assessment of cancer drug response using cell mass measurements

Functional precision medicine offers a promising complement to genomics-based cancer therapy guidance by testing drug efficacy directly on a patient's tumor cells. Here, we describe a workflow that utilizes single-cell mass measurements with inline brightfield imaging and machine-learning based image classification to broaden the clinical utility of such functional testing for cancer. Using these image-curated mass measurements, we characterize mass response signals for 60 different drugs with various mechanisms of action across twelve different cell types, demonstrating an improved ability to detect response for several slow acting drugs as compared with standard cell viability assays. Furthermore, we use this workflow to assess drug responses for various primary tumor specimen formats including blood, bone marrow, fine needle aspirates (FNA), and malignant fluids, all with reports generated within two days and with results consistent with patient clinical responses. The combination of high-resolution measurement, broad drug and malignancy applicability, and rapid return of results offered by this workflow suggests that it is well-suited to performing clinically relevant functional assessment of cancer drug response.

Sensitivity of canine hematological cancers to BH3 mimetics

BACKGROUND

Inhibition of antiapoptotic B-cell lymphoma 2 (BCL2) proteins by small molecule Bcl-2 homology 3 (BH3) mimetics causes rapid induction of apoptosis of human hematological cancers in vitro and in vivo.

OBJECTIVES

Assess in vitro sensitivity of non-neoplastic lymphocytes and primary hematological cancer cells from dogs to venetoclax (VEN) or the dual BCL2/ B-cell lymphoma-extra-large (BCLxL) inhibitor, navitoclax (NAV), and evaluate the association between BCL2 protein expression and VEN sensitivity.

ANIMALS

Nine client-owned dogs without cancer and 18 client-owned dogs with hematological cancer.

METHODS

Prospective, nonrandomized noncontrolled study. Lymphocytes isolated from peripheral blood, lymph node, or bone marrow from dogs were incubated with BH3 mimetics for 24 hours. Viable cells were counted using flow cytometry and half maximal effective concentration (EC₅₀ ) was calculated. BCL2 protein from whole cell lysates was assessed via immunoblots.

RESULTS

Nodal B and T lymphocytes were more sensitive to VEN than circulating lymphocytes (P = .02). Neoplastic T lymphocytes were sensitive to VEN (mean EC₅₀  ± SD = 0.023 ± 0.018 μM), whereas most non-indolent B cell cancers were resistant to killing by VEN (mean EC₅₀  ± SD = 288 ± 700 μM). Unclassified leukemias showed variable sensitivity to VEN (mean EC₅₀  ± SD = 0.49 ± 0.66 μM). Detection of BCL2 protein was not associated with VEN sensitivity.

CONCLUSION AND CLINICAL IMPORTANCE

Neoplastic canine T lymphocytes are sensitive to VEN in vitro. Quantification of BCL2 protein alone is insufficient to predict sensitivity to VEN.

An ex vivo platform to guide drug combination treatment in relapsed/refractory lymphoma

Although combination therapy is the standard of care for relapsed/refractory non-Hodgkin's lymphoma (RR-NHL), combination treatment chosen for an individual patient is empirical, and response rates remain poor in individuals with chemotherapy-resistant disease. Here, we evaluate an experimental-analytic method, quadratic phenotypic optimization platform (QPOP), for prediction of patient-specific drug combination efficacy from a limited quantity of biopsied tumor samples. In this prospective study, we enrolled 71 patients with RR-NHL (39 B cell NHL and 32 NK/T cell NHL) with a median of two prior lines of treatment, at two academic hospitals in Singapore from November 2017 to August 2021. Fresh biopsies underwent ex vivo testing using a panel of 12 drugs with known efficacy against NHL to identify effective single and combination treatments. Individualized QPOP reports were generated for 67 of 75 patient samples, with a median turnaround time of 6 days from sample collection to report generation. Doublet drug combinations containing copanlisib or romidepsin were most effective against B cell NHL and NK/T cell NHL samples, respectively. Off-label QPOP-guided therapy offered at physician discretion in the absence of standard options (n = 17) resulted in five complete responses. Among patients with more than two prior lines of therapy, the rates of progressive disease were lower with QPOP-guided treatments than with conventional chemotherapy. Overall, this study shows that the identification of patient-specific drug combinations through ex vivo analysis was achievable for RR-NHL in a clinically applicable time frame. These data provide the basis for a prospective clinical trial evaluating ex vivo-guided combination therapy in RR-NHL.

Functional precision cancer medicine: drug sensitivity screening enabled by cell culture models

Functional precision medicine is a new, emerging area that can guide cancer treatment by capturing information from direct perturbations of tumor-derived, living cells, such as by drug sensitivity screening. Precision cancer medicine as currently implemented in clinical practice has been driven by genomics, and current molecular tumor boards rely extensively on genomic characterization to advise on therapeutic interventions. However, genomic biomarkers can only guide treatment decisions for a fraction of the patients. In this review we provide an overview of the current state of functional precision medicine, highlight advances for drug-sensitivity screening enabled by cell culture models, and discuss how artificial intelligence (AI) can be coupled to functional precision medicine to guide patient stratification.

Application of High Throughput Technologies in the Development of Acute Myeloid Leukemia Therapy: Challenges and Progress

Acute myeloid leukemia (AML) is a complex hematological malignancy characterized by extensive heterogeneity in genetics, response to therapy and long-term outcomes, making it a prototype example of development for personalized medicine. Given the accessibility to hematologic malignancy patient samples and recent advances in high-throughput technologies, large amounts of biological data that are clinically relevant for diagnosis, risk stratification and targeted drug development have been generated. Recent studies highlight the potential of implementing genomic-based and phenotypic-based screens in clinics to improve survival in patients with refractory AML. In this review, we will discuss successful applications as well as challenges of most up-to-date high-throughput technologies, including artificial intelligence (AI) approaches, in the development of personalized medicine for AML, and recent clinical studies for evaluating the utility of integrating genomics-guided and drug sensitivity testing-guided treatment approaches for AML patients.

Emvododstat, a Potent Dihydroorotate Dehydrogenase Inhibitor, Is Effective in Preclinical Models of Acute Myeloid Leukemia

Blocking the pyrimidine nucleotide de novo synthesis pathway by inhibiting dihydroorotate dehydrogenase (DHODH) results in the cell cycle arrest and/or differentiation of rapidly proliferating cells including activated lymphocytes, cancer cells, or virally infected cells. Emvododstat (PTC299) is an orally bioavailable small molecule that inhibits DHODH. We evaluated the potential for emvododstat to inhibit the progression of acute myeloid leukemia (AML) using several in vitro and in vivo models of the disease. Broad potent activity was demonstrated against multiple AML cell lines, AML blasts cultured ex vivo from patient blood samples, and AML tumor models including patient-derived xenograft models. Emvododstat induced differentiation, cytotoxicity, or both in primary AML patient blasts cultured ex vivo with 8 of 10 samples showing sensitivity. AML cells with diverse driver mutations were sensitive, suggesting the potential of emvododstat for broad therapeutic application. AML cell lines that are not sensitive to emvododstat are likely to be more reliant on the salvage pathway than on de novo synthesis of pyrimidine nucleotides. Pharmacokinetic experiments in rhesus monkeys demonstrated that emvododstat levels rose rapidly after oral administration, peaking about 2 hours post-dosing. This was associated with an increase in the levels of dihydroorotate (DHO), the substrate for DHODH, within 2 hours of dosing indicating that DHODH inhibition is rapid. DHO levels declined as drug levels declined, consistent with the reversibility of DHODH inhibition by emvododstat. These preclinical findings provide a rationale for clinical evaluation of emvododstat in an ongoing Phase 1 study of patients with relapsed/refractory acute leukemias.

Tumor Genomic Profiling and Ex Vivo Drug Sensitivity Testing for Pediatric Leukemia and Lymphoma Patients

OBJECTIVE

To describe the frequency of use of tumor genomic profiling and functional ex vivo drug sensitivity testing in pediatric patients with hematologic malignancies at our institution, and to determine how the results affected treatment selection.

METHODS

A retrospective chart review was conducted to analyze the frequency of tumor genomic profiling and functional drug sensitivity screening in our institution in pediatric patients with hematologic malignancies and to ask if the results were used to direct treatment. A case series of patients for whom these testing recommendations resulted in therapeutic interventions is reported.

RESULTS

Thirty-three patients underwent tumor genomic profiling assays, functional ex vivo testing, or both. Nineteen patients (58%) had genomic profiling assays performed alone, 3 (9%) had functional ex vivo testing performed alone, and 11 (33%) had both tests performed. Twenty-one (64%) patients had potentially actionable mutations detected by the genomic profiling assay. Seven (21%) patients received at least 1 chemotherapeutic agent in accordance with the tumor genomic profiling or functional ex vivo drug sensitivity testing results. Three (43%) of the 7 patients who were treated with testing directed therapy had a favorable treatment response (PR or CR) to treatments selected based upon results of genomic or functional ex vivo testing.

CONCLUSIONS

This retrospective case series demonstrates that precision medicine techniques such as genomic profiling and drug sensitivity testing can positively inform treatment selection in pediatric patients with relapsed or refractory leukemia and lymphoma.

Implementing a Functional Precision Medicine Tumor Board for Acute Myeloid Leukemia

We generated ex vivo drug-response and multiomics profiling data for a prospective series of 252 samples from 186 patients with acute myeloid leukemia (AML). A functional precision medicine tumor board (FPMTB) integrated clinical, molecular, and functional data for application in clinical treatment decisions. Actionable drugs were found for 97% of patients with AML, and the recommendations were clinically implemented in 37 relapsed or refractory patients. We report a 59% objective response rate for the individually tailored therapies, including 13 complete responses, as well as bridging five patients with AML to allogeneic hematopoietic stem cell transplantation. Data integration across all cases enabled the identification of drug response biomarkers, such as the association of IL15 overexpression with resistance to FLT3 inhibitors. Integration of molecular profiling and large-scale drug response data across many patients will enable continuous improvement of the FPMTB recommendations, providing a paradigm for individualized implementation of functional precision cancer medicine. SIGNIFICANCE: Oncogenomics data can guide clinical treatment decisions, but often such data are neither actionable nor predictive. Functional ex vivo drug testing contributes significant additional, clinically actionable therapeutic insights for individual patients with AML. Such data can be generated in four days, enabling rapid translation through FPMTB.See related commentary by Letai, p. 290.This article is highlighted in the In This Issue feature, p. 275.

Patient-tailored design for selective co-inhibition of leukemic cell subpopulations

The extensive drug resistance requires rational approaches to design personalized combinatorial treatments that exploit patient-specific therapeutic vulnerabilities to selectively target disease-driving cell subpopulations. To solve the combinatorial explosion challenge, we implemented an effective machine learning approach that prioritizes patient-customized drug combinations with a desired synergy-efficacy-toxicity balance by combining single-cell RNA sequencing with ex vivo single-agent testing in scarce patient-derived primary cells. When applied to two diagnostic and two refractory acute myeloid leukemia (AML) patient cases, each with a different genetic background, we accurately predicted patient-specific combinations that not only resulted in synergistic cancer cell co-inhibition but also were capable of targeting specific AML cell subpopulations that emerge in differing stages of disease pathogenesis or treatment regimens. Our functional precision oncology approach provides an unbiased means for systematic identification of personalized combinatorial regimens that selectively co-inhibit leukemic cells while avoiding inhibition of nonmalignant cells, thereby increasing their likelihood for clinical translation.