Molecularly targeted drug combinations demonstrate selective effectiveness for myeloid- and lymphoid-derived hematologic malignancies

Ubiquitin-specific protease 7 inhibitors reveal a differentiated mechanism of p53-driven anti-cancer activity

The USP7 deubiquitinase regulates proteins involved in the cell cycle, DNA repair, and epigenetics and has been implicated in cancer progression. USP7 inhibition has been pursued for the development of anti-cancer therapies. Here, we describe the discovery of potent and specific USP7 inhibitors exemplified by FX1-5303. FX1-5303 was used as a chemical probe to study the USP7-mediated regulation of p53 signaling in cells. It demonstrates mechanistic differences compared to MDM2 antagonists, a related class of anti-tumor agents that act along the same pathway. FX1-5303 synergizes with the clinically approved BCL2 inhibitor venetoclax in acute myeloid leukemia (AML) cell lines and ex vivo patient samples and leads to strong tumor growth inhibition in in vivo mouse xenograft models of multiple myeloma and AML. This work introduces new USP7 inhibitors, differentiates their mechanism of action from MDM2 inhibition, and identifies specific opportunities for their use in the treatment of AML.

High throughput screening aids clinical decision-making in refractory acute myeloid leukaemia

BACKGROUND

Despite advances in therapeutics for adverse-risk acute myeloid leukaemia (AML), overall survival remains poor, especially in refractory disease. Comprehensive tumour profiling and pre-clinical drug testing can identify effective personalised therapies.

CASE

We describe a case of ETV6-MECOM fusion-positive refractory AML, where molecular analysis and in vitro high throughput drug screening identified a tolerable, novel targeted therapy and provided rationale for avoiding what could have been a toxic treatment regimen. Ruxolitinib combined with hydroxyurea led to disease control and enhanced quality-of-life in a patient unsuitable for intensified chemotherapy or allogeneic stem cell transplantation.

CONCLUSION

This case report demonstrates the feasibility and role of combination pre-clinical high throughput screening to aid decision making in high-risk leukaemia. It also demonstrates the role a JAK1/2 inhibitor can have in the palliative setting in select patients with AML.

Designing patient-oriented combination therapies for acute myeloid leukemia based on efficacy/toxicity integration and bipartite network modeling

Acute myeloid leukemia (AML), a heterogeneous and aggressive blood cancer, does not respond well to single-drug therapy. A combination of drugs is required to effectively treat this disease. Computational models are critical for combination therapy discovery due to the tens of thousands of two-drug combinations, even with approved drugs. While predicting synergistic drugs is the focus of current methods, few consider drug efficacy and potential toxicity, which are crucial for treatment success. To find effective new drug candidates, we constructed a bipartite network using patient-derived tumor samples and drugs. The network is based on drug-response screening and summarizes all treatment response heterogeneity as drug response weights. This bipartite network is then projected onto the drug part, resulting in the drug similarity network. Distinct drug clusters were identified using community detection methods, each targeting different biological processes and pathways as revealed by enrichment and pathway analysis of the drugs' protein targets. Four drugs with the highest efficacy and lowest toxicity from each cluster were selected and tested for drug sensitivity using cell viability assays on various samples. Results show that ruxolitinib-ulixertinib and sapanisertib-LY3009120 are the most effective combinations with the least toxicity and the best synergistic effect on blast cells. These findings lay the foundation for personalized and successful AML therapies, ultimately leading to the development of drug combinations that can be used alongside standard first-line AML 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.

Sorafenib plus triplet therapy with venetoclax, azacitidine and homoharringtonine for refractory/relapsed acute myeloid leukemia with FLT3-ITD: A multicenter phase 2 study

BACKGROUND

Patients with relapsed or refractory acute myeloid leukemia (R/R AML) and FLT3-internal tandem duplication (FLT3-ITD) respond infrequently to salvage chemotherapy.

OBJECTIVE

To investigate the efficacy of sorafenib plus triplet therapy with venetoclax, azacitidine, and homoharringtonine (VAH) as a salvage therapy in this population.

METHODS

This multicenter, single-arm, phase 2 study was conducted at 12 hospitals across China. Eligible patients had R/R AML with FLT3-ITD (aged 18-65 years) who were treated with VAH. The primary endpoint was composite complete remission (CRc) after two cycles. Secondary outcomes included the overall response rate (ORR), safety, and survival.

RESULTS

Between July 9, 2020, and March 19, 2022, 58 patients were assessed for eligibility, 51 of whom were enrolled. The median patient age was 47 years (interquartile range [IQR] 31-57). CRc was 76.5% with ORR of 82.4%. At a median follow-up of 17.7 months (IQR, 8.7-24.7), the median duration of CRc was not reached (NR), overall survival was 18.1 months (95% confidence interval [CI], 11.8-NR) and event-free survival was 11.4 months (95% CI, 5.6-NR). Grade 3 or 4 adverse events occurring in ≥10% of patients included neutropenia in 47 (92.2%), thrombocytopenia in 41 (80.4%), anemia in 35 (68.6%), febrile neutropenia in 29 (56.9%), pneumonia in 13 (25.5%), and sepsis in 6 (11.8%) patients. Treatment-related death occurred in two (3.9%) patients.

CONCLUSIONS

The sorafenib plus VAH regimen was well tolerated and highly active against R/R AML with FLT3-ITD. This regimen may be a suitable therapeutic option for this population, but larger population trials are needed to be explored.

TRIAL REGISTRATION

Clinical Trials Registry: NCT04424147.

Transcriptional and phenotypic heterogeneity underpinning venetoclax resistance in AML

The venetoclax BCL2 inhibitor in combination with hypomethylating agents represents a cornerstone of induction therapy for older AML patients, unfit for intensive chemotherapy. Like other targeted therapies, venetoclax-based therapies suffer from innate and acquired resistance. While several mechanisms of resistance have been identified, the heterogeneity of resistance mechanism across patient populations is poorly understood. Here we utilized integrative analysis of transcriptomic and ex-vivo drug response data in AML patients to identify four transcriptionally distinct VEN resistant clusters (VR_C1-4), with distinct phenotypic, genetic and drug response patterns. VR_C1 was characterized by enrichment for differentiated monocytic- and cDC-like blasts, transcriptional activation of PI3K-AKT-mTOR signaling axis, and energy metabolism pathways. They showed sensitivity to mTOR and CDK inhibition. VR_C2 was enriched for NRAS mutations and associated with distinctive transcriptional suppression of HOX expression. VR_C3 was characterized by enrichment for TP53 mutations and higher infiltration by cytotoxic T cells. This cluster showed transcriptional expression of erythroid markers, suggesting tumor cells mimicking erythroid differentiation, activation of JAK-STAT signaling, and sensitivity to JAK inhibition, which in a subset of cases synergized with venetoclax. VR_C4 shared transcriptional similarities with venetoclax-sensitive patients, with modest over-expression of interferon signaling. They were also characterized by high rates of DNMT3A mutations. Finally, we projected venetoclax-resistance states onto single cells profiled from a patient who relapsed under venetoclax therapy capturing multiple resistance states in the tumor and shifts in their abundance under venetoclax selection, suggesting that single tumors may consist of cells mimicking multiple VR_Cs contributing to intra-tumor heterogeneity. Taken together, our results provide a strategy to evaluate inter- and intra-tumor heterogeneity of venetoclax resistance mechanisms and provide insights into approaches to navigate further management of patients who failed therapy with BCL2 inhibitors.

Mapping the proteogenomic landscape enables prediction of drug response in acute myeloid leukemia

Acute myeloid leukemia is a poor-prognosis cancer commonly stratified by genetic aberrations, but these mutations are often heterogeneous and fail to consistently predict therapeutic response. Here, we combine transcriptomic, proteomic, and phosphoproteomic datasets with ex vivo drug sensitivity data to help understand the underlying pathophysiology of AML beyond mutations. We measure the proteome and phosphoproteome of 210 patients and combine them with genomic and transcriptomic measurements to identify four proteogenomic subtypes that complement existing genetic subtypes. We build a predictor to classify samples into subtypes and map them to a "landscape" that identifies specific drug response patterns. We then build a drug response prediction model to identify drugs that target distinct subtypes and validate our findings on cell lines representing various stages of quizartinib resistance. Our results show how multiomics data together with drug sensitivity data can inform therapy stratification and drug combinations in AML.

Non-genetic mechanisms of drug resistance in acute leukemias

Acute leukemia is characterized by clonal heterogeneity that contributes to poor drug responses in patients. Despite treatment advances, the occurrence of relapse remains a major barrier to achieving cures as current therapeutic approaches are inadequate to effectively prevent or overcome resistance. Given that only a few genetic mutations are associated with relapse in acute leukemia patients, there is a growing focus on 'non-genetic' mechanisms that affect the hallmarks of cancer to allow leukemic cells to survive post therapy. In this review, we provide an overview of the therapeutic landscape in acute leukemias. Importantly, we discuss non-genetic mechanisms exploited by leukemic cells to promote their survival after treatment. Last, we present current strategies to prevent or overcome drug resistance in this disease.

Standardized assays to monitor drug sensitivity in hematologic cancers

The principle of drug sensitivity testing is to expose cancer cells to a library of different drugs and measure its effects on cell viability. Recent technological advances, continuous approval of targeted therapies, and improved cell culture protocols have enhanced the precision and clinical relevance of such screens. Indeed, drug sensitivity testing has proven diagnostically valuable for patients with advanced hematologic cancers. However, different cell types behave differently in culture and therefore require optimized drug screening protocols to ensure that their ex vivo drug sensitivity accurately reflects in vivo drug responses. For example, primary chronic lymphocytic leukemia (CLL) and multiple myeloma (MM) cells require unique microenvironmental stimuli to survive in culture, while this is less the case for acute myeloid leukemia (AML) cells. Here, we present our optimized and validated protocols for culturing and drug screening of primary cells from AML, CLL, and MM patients, and a generic protocol for cell line models. We also discuss drug library designs, reproducibility, and quality controls. We envision that these protocols may serve as community guidelines for the use and interpretation of assays to monitor drug sensitivity in hematologic cancers and thus contribute to standardization. The read-outs may provide insight into tumor biology, identify or confirm treatment resistance and sensitivity in real time, and ultimately guide clinical decision-making.

Pan-Cancer Pharmacogenomic Analysis of Patient-Derived Tumor Cells Using Clinically Relevant Drug Exposures

As a result of tumor heterogeneity and solid cancers harboring multiple molecular defects, precision medicine platforms in oncology are most effective when both genetic and pharmacologic determinants of a tumor are evaluated. Expandable patient-derived xenograft (PDX) mouse tumor and corresponding PDX culture (PDXC) models recapitulate many of the biological and genetic characteristics of the original patient tumor, allowing for a comprehensive pharmacogenomic analysis. Here, the somatic mutations of 23 matched patient tumor and PDX samples encompassing four cancers were first evaluated using next-generation sequencing (NGS). 19 antitumor agents were evaluated across 78 patient-derived tumor cultures using clinically relevant drug exposures. A binarization threshold sensitivity classification determined in culture (PDXC) was used to identify tumors that best respond to drug in vivo (PDX). Using this sensitivity classification, logic models of DNA mutations were developed for 19 antitumor agents to predict drug response. We determined that the concordance of somatic mutations across patient and corresponding PDX samples increased as variant allele frequency increased. Notable individual PDXC responses to specific drugs, as well as lineage-specific drug responses were identified. Robust responses identified in PDXC were recapitulated in vivo in PDX-bearing mice and logic modeling determined somatic gene mutation(s) defining response to specific antitumor agents. In conclusion, combining NGS of primary patient tumors, high-throughput drug screen using clinically relevant doses, and logic modeling, can provide a platform for understanding response to therapeutic drugs targeting cancer.

Uncovering expression signatures of synergistic drug responses via ensembles of explainable machine-learning models

Machine learning may aid the choice of optimal combinations of anticancer drugs by explaining the molecular basis of their synergy. By combining accurate models with interpretable insights, explainable machine learning promises to accelerate data-driven cancer pharmacology. However, owing to the highly correlated and high-dimensional nature of transcriptomic data, naively applying current explainable machine-learning strategies to large transcriptomic datasets leads to suboptimal outcomes. Here by using feature attribution methods, we show that the quality of the explanations can be increased by leveraging ensembles of explainable machine-learning models. We applied the approach to a dataset of 133 combinations of 46 anticancer drugs tested in ex vivo tumour samples from 285 patients with acute myeloid leukaemia and uncovered a haematopoietic-differentiation signature underlying drug combinations with therapeutic synergy. Ensembles of machine-learning models trained to predict drug combination synergies on the basis of gene-expression data may improve the feature attribution quality of complex machine-learning models.

A tumor microenvironment model of chronic lymphocytic leukemia enables drug sensitivity testing to guide precision medicine

The microenvironment of chronic lymphocytic leukemia (CLL) cells in lymph nodes, spleen, and bone marrow provides survival, proliferation, and drug resistance signals. Therapies need to be effective in these compartments, and pre-clinical models of CLL that are used to test drug sensitivity must mimic the tumor microenvironment to reflect clinical responses. Ex vivo models have been developed that capture individual or multiple aspects of the CLL microenvironment, but they are not necessarily compatible with high-throughput drug screens. Here, we report on a model that has reasonable associated costs, can be handled in a regularly equipped cell lab, and is compatible with ex vivo functional assays including drug sensitivity screens. The CLL cells are cultured with fibroblasts that express the ligands APRIL, BAFF and CD40L for 24 h. The transient co-culture was shown to support survival of primary CLL cells for at least 13 days, and mimic in vivo drug resistance signals. Ex vivo sensitivity and resistance to the Bcl-2 antagonist venetoclax correlated with in vivo responses. The assay was used to identify treatment vulnerabilities and guide precision medicine for a patient with relapsed CLL. Taken together, the presented CLL microenvironment model enables clinical implementation of functional precision medicine in CLL.

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.

Pharmacogenomic Profiling of Pediatric Acute Myeloid Leukemia to Identify Therapeutic Vulnerabilities and Inform Functional Precision Medicine

Despite the expanding portfolio of targeted therapies for adults with acute myeloid leukemia (AML), direct implementation in children is challenging due to inherent differences in underlying genetics. Here we established the pharmacologic profile of pediatric AML by screening myeloblast sensitivity to approved and investigational agents, revealing candidates of immediate clinical relevance. Drug responses ex vivo correlated with patient characteristics, exhibited age-specific alterations, and concorded with activities in xenograft models. Integration with genomic data uncovered new gene-drug associations, suggesting actionable therapeutic vulnerabilities. Transcriptome profiling further identified gene-expression signatures associated with on- and off-target drug responses. We also demonstrated the feasibility of drug screening-guided treatment for children with high-risk AML, with two evaluable cases achieving remission. Collectively, this study offers a high-dimensional gene-drug clinical data set that could be leveraged to research the unique biology of pediatric AML and sets the stage for realizing functional precision medicine for the clinical management of the disease.

SIGNIFICANCE

We conducted integrated drug and genomic profiling of patient biopsies to build the functional genomic landscape of pediatric AML. Age-specific differences in drug response and new gene-drug interactions were identified. The feasibility of functional precision medicine-guided management of children with high-risk AML was successfully demonstrated in two evaluable clinical cases. This article is highlighted in the In This Issue feature, p. 476.

Retinoblastoma protein as an intrinsic BRD4 inhibitor modulates small molecule BET inhibitor sensitivity in cancer

Bromodomain and extraterminal (BET) proteins including BRD4 play important roles in oncogenesis and immune inflammation. Here we demonstrate that cancer cells with loss of the retinoblastoma (RB) tumor suppressor became resistant to small molecule bromodomain inhibitors of BET proteins. We find that RB binds to bromodomain-1 (BD1) of BRD4, but binding is impeded by CDK4/6-mediated RB phosphorylation at serine-249/threonine-252 (S249/T252). ChIP-seq analysis shows RB knockdown increases BRD4 occupancy at genomic loci of genes enriched in cancer-related pathways including the GPCR-GNBIL-CREB axis. S249/T252-phosphorylated RB positively correlates with GNBIL protein level in prostate cancer patient samples. BET inhibitor resistance in RB-deficient cells is abolished by co-administration of CREB inhibitor. Our study identifies RB protein as a bona fide intrinsic inhibitor of BRD4 and demonstrates that RB inactivation confers resistance to small molecule BET inhibitors, thereby revealing a regulatory hub that converges RB upstream signaling onto BRD4 functions in diseases such as cancer.

Integrative analysis of drug response and clinical outcome in acute myeloid leukemia

Acute myeloid leukemia (AML) is a cancer of myeloid-lineage cells with limited therapeutic options. We previously combined ex vivo drug sensitivity with genomic, transcriptomic, and clinical annotations for a large cohort of AML patients, which facilitated discovery of functional genomic correlates. Here, we present a dataset that has been harmonized with our initial report to yield a cumulative cohort of 805 patients (942 specimens). We show strong cross-cohort concordance and identify features of drug response. Further, deconvoluting transcriptomic data shows that drug sensitivity is governed broadly by AML cell differentiation state, sometimes conditionally affecting other correlates of response. Finally, modeling of clinical outcome reveals a single gene, PEAR1, to be among the strongest predictors of patient survival, especially for young patients. Collectively, this report expands a large functional genomic resource, offers avenues for mechanistic exploration and drug development, and reveals tools for predicting outcome in AML.

Proteomic and phosphoproteomic measurements enhance ability to predict ex vivo drug response in AML

Acute Myeloid Leukemia (AML) affects 20,000 patients in the US annually with a five-year survival rate of approximately 25%. One reason for the low survival rate is the high prevalence of clonal evolution that gives rise to heterogeneous sub-populations of leukemic cells with diverse mutation spectra, which eventually leads to disease relapse. This genetic heterogeneity drives the activation of complex signaling pathways that is reflected at the protein level. This diversity makes it difficult to treat AML with targeted therapy, requiring custom patient treatment protocols tailored to each individual's leukemia. Toward this end, the Beat AML research program prospectively collected genomic and transcriptomic data from over 1000 AML patients and carried out ex vivo drug sensitivity assays to identify genomic signatures that could predict patient-specific drug responses. However, there are inherent weaknesses in using only genetic and transcriptomic measurements as surrogates of drug response, particularly the absence of direct information about phosphorylation-mediated signal transduction. As a member of the Clinical Proteomic Tumor Analysis Consortium, we have extended the molecular characterization of this cohort by collecting proteomic and phosphoproteomic measurements from a subset of these patient samples (38 in total) to evaluate the hypothesis that proteomic signatures can improve the ability to predict response to 26 drugs in AML ex vivo samples. In this work we describe our systematic, multi-omic approach to evaluate proteomic signatures of drug response and compare protein levels to other markers of drug response such as mutational patterns. We explore the nuances of this approach using two drugs that target key pathways activated in AML: quizartinib (FLT3) and trametinib (Ras/MEK), and show how patient-derived signatures can be interpreted biologically and validated in cell lines. In conclusion, this pilot study demonstrates strong promise for proteomics-based patient stratification to assess drug sensitivity in AML.

Luxeptinib (CG-806) Targets FLT3 and Clusters of Kinases Operative in Acute Myeloid Leukemia

Luxeptinib (CG-806) simultaneously targets FLT3 and select other kinase pathways operative in myeloid malignancies. We investigated the range of kinases it inhibits, its cytotoxicity landscape ex vivo with acute myeloid leukemia (AML) patient samples, and its efficacy in xenograft models. Luxeptinib inhibits wild-type (WT) and many of the clinically relevant mutant forms of FLT3 at low nanomolar concentrations. It is a more potent inhibitor of the activity of FLT3-internal tandem duplication, FLT3 kinase domain and gatekeeper mutants than against WT FLT3. Broad kinase screens disclosed that it also inhibits other kinases that can drive oncogenic signaling and rescue pathways, but spares kinases known to be associated with clinical toxicity. In vitro profiling of luxeptinib against 186 AML fresh patient samples demonstrated greater potency relative to other FLT3 inhibitors, including cases with mutations in FLT3, isocitrate dehydrogenase-1/2, ASXL1, NPM1, SRSF2, TP53, or RAS, and activity was documented in a xenograft AML model. Luxeptinib administered continuously orally every 12 hours at a dose that yielded a mean Cmin plasma concentration of 1.0 ± 0.3 μmol/L (SEM) demonstrated strong antitumor activity but no myelosuppression or evidence of tissue damage in mice or dogs in acute toxicology studies. On the basis of these studies, luxeptinib was advanced into a phase I trial for patients with AML and myelodysplastic/myeloproliferative neoplasms.

Inhibition of mitochondrial complex I reverses NOTCH1-driven metabolic reprogramming in T-cell acute lymphoblastic leukemia

T-cell acute lymphoblastic leukemia (T-ALL) is commonly driven by activating mutations in NOTCH1 that facilitate glutamine oxidation. Here we identify oxidative phosphorylation (OxPhos) as a critical pathway for leukemia cell survival and demonstrate a direct relationship between NOTCH1, elevated OxPhos gene expression, and acquired chemoresistance in pre-leukemic and leukemic models. Disrupting OxPhos with IACS-010759, an inhibitor of mitochondrial complex I, causes potent growth inhibition through induction of metabolic shut-down and redox imbalance in NOTCH1-mutated and less so in NOTCH1-wt T-ALL cells. Mechanistically, inhibition of OxPhos induces a metabolic reprogramming into glutaminolysis. We show that pharmacological blockade of OxPhos combined with inducible knock-down of glutaminase, the key glutamine enzyme, confers synthetic lethality in mice harboring NOTCH1-mutated T-ALL. We leverage on this synthetic lethal interaction to demonstrate that IACS-010759 in combination with chemotherapy containing L-asparaginase, an enzyme that uncovers the glutamine dependency of leukemic cells, causes reduced glutaminolysis and profound tumor reduction in pre-clinical models of human T-ALL. In summary, this metabolic dependency of T-ALL on OxPhos provides a rational therapeutic target.

SynergyFinder 3.0: an interactive analysis and consensus interpretation of multi-drug synergies across multiple samples

SynergyFinder (https://synergyfinder.fimm.fi) is a free web-application for interactive analysis and visualization of multi-drug combination response data. Since its first release in 2017, SynergyFinder has become a popular tool for multi-dose combination data analytics, partly because the development of its functionality and graphical interface has been driven by a diverse user community, including both chemical biologists and computational scientists. Here, we describe the latest upgrade of this community-effort, SynergyFinder release 3.0, introducing a number of novel features that support interactive multi-sample analysis of combination synergy, a novel consensus synergy score that combines multiple synergy scoring models, and an improved outlier detection functionality that eliminates false positive results, along with many other post-analysis options such as weighting of synergy by drug concentrations and distinguishing between different modes of synergy (potency and efficacy). Based on user requests, several additional improvements were also implemented, including new data visualizations and export options for multi-drug combinations. With these improvements, SynergyFinder 3.0 supports robust identification of consistent combinatorial synergies for multi-drug combinatorial discovery and clinical translation.

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.

Functional Precision Medicine: Putting Drugs on Patient Cancer Cells and Seeing What Happens

For too long, assays exposing patient tumor cells to drugs to identify active therapies have been dismissed as ineffective. In this issue of Cancer Discovery, two groups independently demonstrate clinical utility of such functional precision medicine assays in hematologic malignancies.See related article by Kornauth et al., p. 372.See related article by Malani et al., p. 388.

Associating Drug Sensitivity with Differentiation Status Identifies Effective Combinations for Acute Myeloid Leukemia

Combined targeting of AML patient cells with p38 MAPK and BCL2 inhibitors overcomes monocytic-associated resistance to VEN.

Exploiting complementary drug sensitivity profiles with respect to leukemic differentiation state affords enhanced efficacy in AML.

Using ex vivo drug screening of primary patient specimens, we identified the combination of the p38 MAPK inhibitor doramapimod (DORA) with the BCL2 inhibitor venetoclax (VEN) as demonstrating broad, enhanced efficacy compared with each single agent across 335 acute myeloid leukemia (AML) patient samples while sparing primary stromal cells. Single-agent DORA and VEN sensitivity was associated with distinct, nonoverlapping tumor cell differentiation states. In particular, increased monocytes, M4/M5 French-American-British classification, and CD14⁺ immunophenotype tracked with sensitivity to DORA and resistance to VEN but were mitigated with the combination. Increased expression of MAPK14 and BCL2, the respective primary targets of DORA and VEN, were observed in monocytic and undifferentiated leukemias, respectively. Enrichment for DORA and VEN sensitivities was observed in AML with monocyte-like and progenitor-like transcriptomic signatures, respectively, and these associations diminished with the combination. The mechanism underlying the combination’s enhanced efficacy may result from inhibition of p38 MAPK-mediated phosphorylation of BCL2, which in turn enhances sensitivity to VEN. These findings suggest exploiting complementary drug sensitivity profiles with respect to leukemic differentiation state, such as dual targeting of p38 MAPK and BCL2, offers opportunity for broad, enhanced efficacy across the clinically challenging heterogeneous landscape of AML.

Novel Treatments for Pediatric Relapsed or Refractory Acute B-Cell Lineage Lymphoblastic Leukemia: Precision Medicine Era

With the markedly increased cure rate for children with newly diagnosed pediatric B-cell acute lymphoblastic leukemia (B-ALL), relapse and refractory B-ALL (R/R B-ALL) remain the primary cause of death worldwide due to the limitations of multidrug chemotherapy. As we now have a more profound understanding of R/R ALL, including the mechanism of recurrence and drug resistance, prognostic indicators, genotypic changes and so on, we can use newly emerging technologies to identify operational molecular targets and find sensitive drugs for individualized treatment. In addition, more promising and innovative immunotherapies and molecular targeted drugs that are expected to kill leukemic cells more effectively while maintaining low toxicity to achieve minimal residual disease (MRD) negativity and better bridge hematopoietic stem cell transplantation (HSCT) have also been widely developed. To date, the prognosis of pediatric patients with R/R B-ALL has been enhanced markedly thanks to the development of novel drugs. This article reviews the new advancements of several promising strategies for pediatric R/R B-ALL.

Ex Vivo Drug Screening Informed Targeted Therapy for Metastatic Parotid Squamous Cell Carcinoma

The purpose of ex vivo drug screening in the context of precision oncology is to serve as a functional diagnostic method for therapy efficacy modeling directly on patient-derived tumor cells. Here, we report a case study using integrated multiomics ex vivo drug screening approach to assess therapy efficacy in a rare metastatic squamous cell carcinoma of the parotid gland. Tumor cells isolated from lymph node metastasis and distal subcutaneous metastasis were used for imaging-based single-cell resolution drug screening and reverse-phase protein array-based drug screening assays to inform the treatment strategy after standard therapeutic options had been exhausted. The drug targets discovered on the basis of the ex vivo measured drug efficacy were validated with histopathology, genomic profiling, and in vitro cell biology methods, and targeted treatments with durable clinical responses were achieved. These results demonstrate the use of serial ex vivo drug screening to inform adjuvant therapy options prior to and during treatment and highlight HER2 as a potential therapy target also in metastatic squamous cell carcinoma of the salivary glands.

Monocytic differentiation and AHR signaling as Primary Nodes of BET Inhibitor Response in Acute Myeloid Leukemia

To understand mechanisms of response to BET inhibitors (BETi), we mined the Beat AML functional genomic dataset and performed genome-wide CRISPR screens on BETi- sensitive and BETi- resistant AML cells. Both strategies revealed regulators of monocytic differentiation, SPI1, JUNB, FOS, and aryl-hydrocarbon receptor signaling (AHR/ARNT), as determinants of BETi response. AHR activation synergized with BETi while inhibition antagonized BETi-mediated cytotoxicity. Consistent with BETi sensitivity dependence on monocytic differentiation, ex vivo sensitivity to BETi in primary AML patient samples correlated with higher expression of monocytic markers CSF1R, LILRs, and VCAN. In addition, HL-60 cell line differentiation enhanced its sensitivity to BETi. Further, screens to rescue BETi sensitivity identified BCL2 and CDK6 as druggable vulnerabilities. Finally, monocytic AML patient samples refractory to venetoclax ex vivo were significantly more sensitive to combined BETi + venetoclax. Together, our work highlights mechanisms that could predict BETi response and identifies combination strategies to overcome resistance.

Pharmacologic Targeting of Mcl-1 Induces Mitochondrial Dysfunction and Apoptosis in B-Cell Lymphoma Cells in a TP53- and BAX-Dependent Manner

PURPOSE

Bcl-2 has been effectively targeted in lymphoid malignancies. However, resistance is inevitable, and novel approaches to target mitochondrial apoptosis are necessary. AZD5991, a selective BH3-mimetic in clinical trials, inhibits Mcl-1 with high potency.

EXPERIMENTAL DESIGN

We explored the preclinical activity of AZD5991 in diffuse large B-cell lymphoma (DLBCL) and ibrutinib-resistant mantle cell lymphoma (MCL) cell lines, MCL patient samples, and mice bearing DLBCL and MCL xenografts using flow cytometry, immunoblotting, and Seahorse respirometry assay. Cas9 gene editing and ex vivo functional drug screen assays helped identify mechanisms of resistance to Mcl-1 inhibition.

RESULTS

Mcl-1 was expressed in DLBCL and MCL cell lines and primary tumors. Treatment with AZD5991 restricted growth of DLBCL cells independent of cell of origin and overcame ibrutinib resistance in MCL cells. Mcl-1 inhibition led to mitochondrial dysfunction as manifested by mitochondrial membrane depolarization, decreased mitochondrial mass, and induction of mitophagy. This was accompanied by impairment of oxidative phosphorylation. TP53 and BAX were essential for sensitivity to Mcl-1, and oxidative phosphorylation was implicated in resistance to Mcl-1 inhibition. Induction of prosurvival proteins (e.g., Bcl-xL) in stromal conditions that mimic the tumor microenvironment rendered protection of primary MCL cells from Mcl-1 inhibition, while BH3-mimetics targeting Bcl-2/xL sensitized lymphoid cells to AZD5991. Treatment with AZD5991 reduced tumor growth in murine lymphoma models and prolonged survival of MCL PDX mice.

CONCLUSIONS

Selective targeting Mcl-1 is a promising therapeutic approach in lymphoid malignancies. TP53 apoptotic network and metabolic reprogramming underlie susceptibility to Mcl-1 inhibition.

Antileukemic efficacy of a potent artemisinin combined with sorafenib and venetoclax

Artemisinins are active against human leukemia cell lines and have low clinical toxicity in worldwide use as antimalarials. Because multiagent combination regimens are necessary to cure fully evolved leukemias, we sought to leverage our previous finding that artemisinin analogs synergize with kinase inhibitors, including sorafenib (SOR), by identifying additional synergistic antileukemic drugs with low toxicity. Screening of a targeted antineoplastic drug library revealed that B-cell lymphoma 2 (BCL2) inhibitors synergize with artemisinins, and validation assays confirmed that the selective BCL2 inhibitor, venetoclax (VEN), synergized with artemisinin analogs to inhibit growth and induce apoptotic cell death of multiple acute leukemia cell lines in vitro. An oral 3-drug "SAV" regimen (SOR plus the potent artemisinin-derived trioxane diphenylphosphate 838 dimeric analog [ART838] plus VEN) killed leukemia cell lines and primary cells in vitro. Leukemia cells cultured in ART838 had decreased induced myeloid leukemia cell differentiation protein (MCL1) levels and increased levels of DNA damage-inducible transcript 3 (DDIT3; GADD153) messenger RNA and its encoded CCATT/enhancer-binding protein homologous protein (CHOP), a key component of the integrated stress response. Thus, synergy of the SAV combination may involve combined targeting of MCL1 and BCL2 via discrete, tolerable mechanisms, and cellular levels of MCL1 and DDIT3/CHOP may serve as biomarkers for action of artemisinins and SAV. Finally, SAV treatment was tolerable and resulted in deep responses with extended survival in 2 acute myeloid leukemia (AML) cell line xenograft models, both harboring a mixed lineage leukemia gene rearrangement and an FMS-like receptor tyrosine kinase-3 internal tandem duplication, and inhibited growth in 2 AML primagraft models.

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

Precision medicine approaches such as ex vivo drug sensitivity screening (DSS) are appealing to inform rational drug selection in myelodysplastic syndromes (MDSs) and acute myeloid leukemia, given their marked biologic heterogeneity. We evaluated a novel, fully automated ex vivo DSS platform that uses high-throughput flow cytometry in 54 patients with newly diagnosed or treatment-refractory myeloid neoplasms to evaluate sensitivity (blast cytotoxicity and differentiation) to 74 US Food and Drug Administration-approved or investigational drugs and 36 drug combinations. After piloting the platform in 33 patients, we conducted a prospective feasibility study enrolling 21 patients refractory to hypomethylating agents (HMAs) to determine whether this assay could be performed within a clinically actionable time frame and could accurately predict clinical responses in vivo. When assayed for cytotoxicity, ex vivo drug sensitivity patterns were heterogeneous, but they defined distinct patient clusters with differential sensitivity to HMAs, anthracyclines, histone deacetylase inhibitors, and kinase inhibitors (P < .001 among clusters) and demonstrated synergy between HMAs and venetoclax (P < .01 for combinations vs single agents). In our feasibility study, ex vivo DSS results were available at a median of 15 days after bone marrow biopsy, and they informed personalized therapy, which frequently included venetoclax combinations, kinase inhibitors, differentiative agents, and androgens. In 21 patients with available ex vivo and in vivo clinical response data, the DSS platform had a positive predictive value of 0.92, negative predictive value of 0.82, and overall accuracy of 0.85. These data demonstrate the utility of this approach for identifying potentially useful and often novel therapeutic drugs for patients with myeloid neoplasms refractory to standard therapies.

Mitochondrial metabolism as a target for acute myeloid leukemia treatment

Acute myeloid leukemias (AML) are a group of aggressive hematologic malignancies resulting from acquired genetic mutations in hematopoietic stem cells that affect patients of all ages. Despite decades of research, standard chemotherapy still remains ineffective for some AML subtypes and is often inappropriate for older patients or those with comorbidities. Recently, a number of studies have identified unique mitochondrial alterations that lead to metabolic vulnerabilities in AML cells that may present viable treatment targets. These include mtDNA, dependency on oxidative phosphorylation, mitochondrial metabolism, and pro-survival signaling, as well as reactive oxygen species generation and mitochondrial dynamics. Moreover, some mitochondria-targeting chemotherapeutics and their combinations with other compounds have been FDA-approved for AML treatment. Here, we review recent studies that illuminate the effects of drugs and synergistic drug combinations that target diverse biomolecules and metabolic pathways related to mitochondria and their promise in experimental studies, clinical trials, and existing chemotherapeutic regimens.

The Intriguing Clinical Success of BCL-2 Inhibition in Acute Myeloid Leukemia

Over the past several decades numerous preclinical and clinical studies have pursued new approaches for the treatment of acute myeloid leukemia (AML). While some degree of clinical response has been demonstrated for many therapies, for the most part, fundamental changes in the treatment landscape have been lacking. Recently, the use of the BCL-2 inhibitor venetoclax has emerged as a potent therapy for a majority of newly diagnosed AML patients. Venetoclax regimens have shown broad response rates with deep and durable remissions, with a superior toxicity profile compared with traditional intensive chemotherapy agents. Numerous ongoing studies are now using venetoclax in combination with a wide range of other agents as investigators seek even more effective and well-tolerated regimens. Notably, however, while the empirical results of BCL-2 inhibition are encouraging, the mechanisms that have led to these successful clinical outcomes remain unclear. Intriguingly, the activity of venetoclax in AML patients appears to go beyond simply modulating canonical antiapoptosis mechanisms; in addition, the efficacy of venetoclax is linked to its combined use with conventional low-intensity backbone therapies. This article will evaluate the state of the field, provide a summary of key considerations, and propose directions for future studies.

Precision Medicine in Hematology 2021: Definitions, Tools, Perspectives, and Open Questions

During the past few years, our understanding of molecular mechanisms and cellular interactions relevant to malignant blood cell disorders has improved substantially. New insights include a detailed knowledge about disease-initiating exogenous factors, endogenous (genetic, somatic, epigenetic) elicitors or facilitators of disease evolution, and drug actions and interactions that underlie efficacy and adverse event profiles in defined cohorts of patients. As a result, precision medicine and personalized medicine are rapidly growing new disciplines that support the clinician in making the correct diagnosis, in predicting outcomes, and in optimally selecting patients for interventional therapies. In addition, precision medicine tools are greatly facilitating the development of new drugs, therapeutic approaches, and new multiparametric prognostic scoring models. However, although the emerging roles of precision medicine and personalized medicine in hematology and oncology are clearly visible, several questions remain. For example, it remains unknown how precision medicine tools can be implemented in healthcare systems and whether all possible approaches are also affordable. In addition, there is a need to define terminologies and to relate these to specific and context-related tools and strategies in basic and applied science. To discuss these issues, a working conference was organized in September 2019. The outcomes of this conference are summarized herein and include a proposal for definitions, terminologies, and applications of precision and personalized medicine concepts and tools in hematologic neoplasms. We also provide proposals aimed at reducing costs, thereby making these applications affordable in daily practice.

Re-defining synthetic lethality by phenotypic profiling for precision oncology

High-throughput functional and genomic screening techniques provide systematic means for phenotypic discovery. Using synthetic lethality (SL) as a paradigm for anticancer drug and target discovery, we describe how these screening technologies may offer new possibilities to identify therapeutically relevant and selective SL interactions by addressing some of the challenges that have made robust discovery of SL candidates difficult. We further introduce an extended concept of SL interaction, in which a simultaneous perturbation of two or more cellular components reduces cell viability more than expected by their individual effects, which we feel is highly befitting for anticancer applications. We also highlight the potential benefits and challenges related to computational quantification of synergistic interactions and cancer selectivity. Finally, we explore how tumoral heterogeneity can be exploited to find phenotype-specific SL interactions for precision oncology using high-throughput functional screening and the exciting opportunities these methods provide for the identification of subclonal SL interactions.

The delta isoform of phosphatidylinositol-3-kinase predominates in chronic myelomonocytic leukemia and can be targeted effectively with umbralisib and ruxolitinib

Chronic myelomonocytic leukemia (CMML) is a myelodysplastic syndrome/myeloproliferative neoplasm overlap syndrome characterized by monocytic proliferation in the presence of dysplastic bone marrow changes, inflammatory symptoms, and propensity for transformation to acute myeloid leukemia (AML), with a poor prognosis and limited treatment options. Unlike the α and β isoforms, the phosphatidylinositol-3-kinase (PI3K)-δ signaling protein is predominantly expressed by hematopoietic cells and therefore has garnered interest as a potential target for the treatment of lymphomas and leukemias. We revealed a pattern of increased PIK3CD:PIK3CA ratio in monocytic M5 AML patients and cell lines, and this ratio correlated with responsiveness to pharmacological PI3K-δ inhibition in vitro. Because CMML is a disease defined by monocytic clonal proliferation, we tested the PI3K-δ inhibitor umbralisib as a single agent and in combination with the JAK1/2 inhibitor ruxolitinib, in CMML. Our ex vivo experiments with primary CMML patient samples revealed synergistic inhibition of viability and clonogenicity with this combination. Phospho-specific flow cytometry revealed that dual inhibition had the unique ability to decrease STAT5, ERK, AKT, and S6 phosphorylation simultaneously, which offers a mechanistic hypothesis for the enhanced efficacy of the combination treatment. These preclinical data indicate promising activity by co-inhibition of PI3K-δ and JAK1/2 and support the use of ruxolitinib + umbralisib combination therapy in CMML under active clinical investigation.

Matched Targeted Therapy for Pediatric Patients with Relapsed, Refractory, or High-Risk Leukemias: A Report from the LEAP Consortium

Despite a remarkable increase in the genomic profiling of cancer, integration of genomic discoveries into clinical care has lagged behind. We report the feasibility of rapid identification of targetable mutations in 153 pediatric patients with relapsed/refractory or high-risk leukemias enrolled on a prospective clinical trial conducted by the LEAP Consortium. Eighteen percent of patients had a high confidence Tier 1 or 2 recommendation. We describe clinical responses in the 14% of patients with relapsed/refractory leukemia who received the matched targeted therapy. Further, in order to inform future targeted therapy for patients, we validated variants of uncertain significance, performed ex vivo drug-sensitivity testing in patient leukemia samples, and identified new combinations of targeted therapies in cell lines and patient-derived xenograft models. These data and our collaborative approach should inform the design of future precision medicine trials. SIGNIFICANCE: Patients with relapsed/refractory leukemias face limited treatment options. Systematic integration of precision medicine efforts can inform therapy. We report the feasibility of identifying targetable mutations in children with leukemia and describe correlative biology studies validating therapeutic hypotheses and novel mutations.See related commentary by Bornhauser and Bourquin, p. 1322.This article is highlighted in the In This Issue feature, p. 1307.

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.

Predicting likelihood of in vivo chemotherapy response in canine lymphoma using ex vivo drug sensitivity and immunophenotyping data in a machine learning model

We report a precision medicine platform that evaluates the probability of chemotherapy drug efficacy for canine lymphoma by combining ex vivo chemosensitivity and immunophenotyping assays with computational modelling. We isolated live cancer cells from fresh fine needle aspirates of affected lymph nodes and collected post‐treatment clinical responses in 261 canine lymphoma patients scheduled to receive at least 1 of 5 common chemotherapy agents (doxorubicin, vincristine, cyclophosphamide, lomustine and rabacfosadine). We used flow cytometry analysis for immunophenotyping and ex vivo chemosensitivity testing. For each drug, 70% of treated patients were randomly selected to train a random forest model to predict the probability of positive Veterinary Cooperative Oncology Group (VCOG) clinical response based on input variables including antigen expression profiles and treatment sensitivity readouts for each patient's cancer cells. The remaining 30% of patients were used to test model performance. Most models showed a test set ROC‐AUC > 0.65, and all models had overall ROC‐AUC > 0.95. Predicted response scores significantly distinguished (P < .001) positive responses from negative responses in B‐cell and T‐cell disease and newly diagnosed and relapsed patients. Patient groups with predicted response scores >50% showed a statistically significant reduction (log‐rank P < .05) in time to complete response when compared to the groups with scores <50%. The computational models developed in this study enabled the conversion of ex vivo cell‐based chemosensitivity assay results into a predicted probability of in vivo therapeutic efficacy, which may help improve treatment outcomes of individual canine lymphoma patients by providing predictive estimates of positive treatment response.

Identification of genetic targets in acute myeloid leukaemia for designing targeted therapy

Few effective therapies exist for acute myeloid leukaemia (AML), in part due to the molecular heterogeneity of this disease. We sought to identify genes crucial to deregulated AML signal transduction pathways which, if inhibited, could effectively eradicate leukaemia stem cells. Due to difficulties in screening primary cells, most previous studies have performed next-generation sequencing (NGS) library knockdown screens in cell lines. Using carefully considered methods including evaluation at multiple timepoints to ensure equitable gene knockdown, we employed a large NGS short hairpin RNA (shRNA) knockdown screen of nearly 5 000 genes in primary AML cells from six patients to identify genes that are crucial for leukaemic survival. Across various levels of stringency, genome-wide bioinformatic analysis identified a gene in the NOX family, NOX1, to have the most consistent knockdown effectiveness in primary cells (P = 5∙39 × 10^-5 , Bonferroni-adjusted), impacting leukaemia cell survival as the top-ranked gene for two of the six AML patients and also showing high effectiveness in three of the other four patients. Further investigation of this pathway highlighted NOX2 as the member of the NOX family with clear knockdown efficacy. We conclude that genes in the NOX family are enticing candidates for therapeutic development in AML.

BH3 Mimetics in AML Therapy: Death and Beyond?

B cell lymphoma 2 (BCL2) homology domain 3 (BH3) mimetics are targeted therapeutic agents that allow response prediction and patient stratification. BH3 mimetics are prototypical activators of the mitochondrial death program in cancer. They emerged as important modulators of cellular mechanisms contributing to poor therapeutic responses, including cancer cell stemness, cancer-specific metabolic routes, paracrine signaling to the tumor microenvironment, and immune modulation. We present an overview of the antagonism between BH3 mimetics and antiapoptotic BCL2 proteins. We focus on acute myeloid leukemia (AML), a cancer with reduced therapeutic options that have recently been improved by BH3 mimetics.

Precision medicine in acute myeloid leukemia: where are we now and what does the future hold?

INTRODUCTION

Precision medicine has revolutionized the diagnostic and therapeutic management of acute myeloid leukemia (AML), from standardized schemes based on chemotherapy to tailored approaches according to molecular and genetic profile and targeted therapy.

AREAS COVERED

The main topics of precision medicine in AML were reviewed in MEDLINE, EMBASE, and Cochrane Central Register databases, and future directions in this therapeutic area were addressed. This review included targeted therapies, drug-sensitivity tests and predictive biomarkers, and genetic studies employing pharmacogenetic and deep sequencing strategies.

EXPERT OPINION

Precision medicine has opened the door to personalized therapy for specific AML patient populations with promising results. Several targeted therapies have been approved or are being tested for specific mutations (i.e. FLT3, IDH, BCL-2, TP53), obtaining improvements in clinical outcomes and less toxicity as compared with intensive treatment, allowing potential combination therapy. Ongoing trials and real data will establish the role of these molecules in monotherapy or combined in different AML settings (front-line, relapsed/refractory, or post-transplant). Experience in drug-sensitivity predictors and pharmacogenetic biomarkers is encouraging and could be useful tools in the next years, but we need a better understanding of AML biology and pathogenesis as well as confirmatory studies to demonstrate the utility in clinical practice.

Myelodysplastic syndromes: moving towards personalized management

The myelodysplastic syndromes (MDS) share their origin in the hematopoietic stem cell but have otherwise very heterogeneous biological and genetic characteristics. Clinical features are dominated by cytopenia and a substantial risk for progression to acute myeloid leukemia. According to the World Health Organization, MDS is defined by cytopenia, bone marrow dysplasia and certain karyotypic abnormalities. The understanding of disease pathogenesis has undergone major development with the implementation of next-generation sequencing and a closer integration of morphology, cytogenetics and molecular genetics is currently paving the way for improved classification and prognostication. True precision medicine is still in the future for MDS and the development of novel therapeutic compounds with a propensity to markedly change patients' outcome lags behind that for many other blood cancers. Treatment of higher-risk MDS is dominated by monotherapy with hypomethylating agents but novel combinations are currently being evaluated in clinical trials. Agents that stimulate erythropoiesis continue to be first-line treatment for the anemia of lower-risk MDS but luspatercept has shown promise as second-line therapy for sideroblastic MDS and lenalidomide is an established second-line treatment for del(5q) lower-risk MDS. The only potentially curative option for MDS is hematopoietic stem cell transplantation, until recently associated with a relatively high risk of transplant-related mortality and relapse. However, recent studies show increased cure rates due to better tools to target the malignant clone with less toxicity. This review provides a comprehensive overview of the current status of the clinical evaluation, biology and therapeutic interventions for this spectrum of disorders.

Heme Oxygenase 1-Targeted Hybrid Nanoparticle for Chemo- and Immuno-Combination Therapy in Acute Myelogenous Leukemia

Acute myelogenous leukemia (AML) is a fatal blood cancer with high patient mortality. Daunorubicin and cytarabine are first-line chemotherapy for AML, with bone marrow transplantation in most cases. Recently, cancer immunotherapy has been challenged in AML and leukemia-niche myeloid cells are promising targets for the AML immunotherapy. Heme oxygenase 1 (HO1) is an antioxidative and cytoprotective enzyme inducing chemo-resistant AML and has been focused as an immune checkpoint molecule in tumor microenvironments. Herein, lipid-polymer hybrid nanoparticle (hNP) is loaded with tin mesoporphyrin (SnMP), a HO1-inhibitor, and non-covalently modified with an engineered antibody for leukemic cell-targeted delivery. HO1-inhibiting T-hNP (T-hNP/SnMP) enhances chemo-sensitivity in human leukemia cells. In a human AML-bearing orthotopic mouse model, intravenously injected T-hNP not only actively targets to human leukemia cells but passively targets to CD11b+ myeloid cells in a bone marrow niche. The T-hNP/SnMP enhances the chemo-therapeutic effect of daunorubicin and boosts immune response by reprogramming bone marrow myeloid cells resulting from the recruitment of the monocyte-lineage and induction of inflammatory genes. The ex vivo study demonstrates an enhanced immune response of HO1-inhibited bone marrow CD11b+ myeloid cells against apoptotic leukemia cells. Collectively, HO1-inhibiting dual cell-targeted T-hNP/SnMP has a strong potential as a novel therapeutic in AML.

A chemogenomic approach to identify personalized therapy for patients with relapse or refractory acute myeloid leukemia: results of a prospective feasibility study

Targeted next-generation sequencing (tNGS) and ex vivo drug sensitivity/resistance profiling (DSRP) have laid foundations defining the functional genomic landscape of acute myeloid leukemia (AML) and premises of personalized medicine to guide treatment options for patients with aggressive and/or chemorefractory hematological malignancies. Here, we have assessed the feasibility of a tailored treatment strategy (TTS) guided by systematic parallel ex vivo DSRP and tNGS for patients with relapsed/refractory AML (number NCT02619071). A TTS issued by an institutional personalized committee could be achieved for 47/55 included patients (85%), 5 based on tNGS only, 6 on DSRP only, while 36 could be proposed on the basis of both, yielding more options and a better rationale. The TSS was available in <21 days for 28 patients (58.3%). On average, 3 to 4 potentially active drugs were selected per patient with only five patient samples being resistant to the entire drug panel. Seventeen patients received a TTS-guided treatment, resulting in four complete remissions, one partial remission, and five decreased peripheral blast counts. Our results show that chemogenomic combining tNGS with DSRP to determine a TTS is a promising approach to propose patient-specific treatment options within 21 days.

Epigenomics-Guided Drug Development: Recent Advances in Solving the Cancer Treatment "jigsaw puzzle"

The human epigenome plays a key role in determining cellular identity and eventually function. Drug discovery undertakings have focused mainly on the role of genomics in carcinogenesis, with the focus turning to the epigenome recently. Drugs targeting DNA and histone modifications are under development with some such as 5-azacytidine, decitabine, vorinostat, and panobinostat already approved by the Food and Drug Administration (FDA) and the European Medicines Agency (EMA). This expert review offers a critical analysis of the epigenomics-guided drug discovery and development and the opportunities and challenges for the next decade. Importantly, the coupling of epigenetic editing techniques, such as clustered regularly interspersed short palindromic repeat (CRISPR)-CRISPR-associated protein-9 (Cas9) and APOBEC-coupled epigenetic sequencing (ACE-seq) with epigenetic drug screens, will allow the identification of small-molecule inhibitors or drugs able to reverse epigenetic changes responsible for many diseases. In addition, concrete and sustainable innovation in cancer treatment ought to integrate epigenome targeting drugs with classic therapies such as chemotherapy and immunotherapy.

Utilizing Synergistic Potential of Mitochondria-Targeting Drugs for Leukemia Therapy

Acute myeloid leukemia (AML) is an aggressive group of cancers with high mortality rates and significant relapse risks. Current treatments are insufficient, and new therapies are needed. Recent discoveries suggest that AML may be particularly sensitive to chemotherapeutics that target mitochondria. To further investigate this sensitivity, six compounds that target mitochondria [IACS-010759, rotenone, cytarabine, etoposide, ABT-199 (venetoclax), and carbonyl cyanide m-chlorophenylhydrazone] were each paired with six compounds with other activities, including tyrosine kinase inhibitors (midostaurin and dasatinib), glycolytic inhibitors (2-deoxy-D-glucose, 3-bromopyruvate, and lonidamine), and the microtubule destabilizer vinorelbine. The 36 resulting drug combinations were tested for synergistic cytotoxicity against MOLM-13 and OCI-AML2 AML cell lines. Four combinations (IACS-010759 with vinorelbine, rotenone with 2-deoxy-D-glucose, carbonyl cyanide m-chlorophenylhydrazone with dasatinib, and venetoclax with lonidamine) showed synergistic cytotoxicity in both AML cell lines and were selective for tumor cells, as survival of healthy PBMCs was dramatically higher. Among these drug pairs, IACS-010759/vinorelbine decreased ATP level and impaired mitochondrial respiration and coupling efficiency most profoundly. Some of these four treatments were also effective in K-562, KU812 (chronic myelogenous leukemia) and CCRF-CEM, MOLT-4 (acute lymphoblastic leukemia) cells, suggesting that these treatments may have value in treating other forms of leukemia. Finally, two of the four combinations retained high synergy and strong selectivity in primary AML cells from patient samples, supporting the potential of these treatments for patients.

Drug responses are conserved across patient-derived xenograft models of melanoma leading to identification of novel drug combination therapies

BACKGROUND

Patient-derived xenograft (PDX) mouse tumour models can predict response to therapy in patients. Predictions made from PDX cultures (PDXC) would allow for more rapid and comprehensive evaluation of potential treatment options for patients, including drug combinations.

METHODS

We developed a PDX library of BRAF-mutant metastatic melanoma, and a high-throughput drug-screening (HTDS) platform utilising clinically relevant drug exposures. We then evaluated 34 antitumor agents across eight melanoma PDXCs, compared drug response to BRAF and MEK inhibitors alone or in combination with PDXC and the corresponding PDX, and investigated novel drug combinations targeting BRAF inhibitor-resistant melanoma.

RESULTS

The concordance of cancer-driving mutations across patient, matched PDX and subsequent PDX generations increases as variant allele frequency (VAF) increases. There was a high correlation in the magnitude of response to BRAF and MEK inhibitors between PDXCs and corresponding PDXs. PDXCs and corresponding PDXs from metastatic melanoma patients that progressed on standard-of-care therapy demonstrated similar resistance patterns to BRAF and MEK inhibitor therapy. Importantly, HTDS identified novel drug combinations to target BRAF-resistant melanoma.

CONCLUSIONS

The biological consistency observed between PDXCs and PDXs suggests that PDXCs may allow for a rapid and comprehensive identification of treatments for aggressive cancers, including combination therapies.

Prediction of drug combination effects with a minimal set of experiments

High-throughput drug combination screening provides a systematic strategy to discover unexpected combinatorial synergies in pre-clinical cell models. However, phenotypic combinatorial screening with multi-dose matrix assays is experimentally expensive, especially when the aim is to identify selective combination synergies across a large panel of cell lines or patient samples. Here we implemented DECREASE, an efficient machine learning model that requires only a limited set of pairwise dose-response measurements for accurate prediction of drug combination synergy and antagonism. Using a compendium of 23,595 drug combination matrices tested in various cancer cell lines, and malaria and Ebola infection models, we demonstrate how cost-effective experimental designs with DECREASE capture almost the same degree of information for synergy and antagonism detection as the fully-measured dose-response matrices. Measuring only the diagonal of the matrix provides an accurate and practical option for combinatorial screening. The open-source web-implementation enables applications of DECREASE to both pre-clinical and translational studies.

The impact of At1r inhibition via losartan on the anti-leukaemic effects of doxorubicin in acute myeloid leukaemia

Introduction:

Bone marrow renin–angiotensin system(RAS) modulates acute myeloid leukaemia(AML).The aim of this study is to clarify the relationships between RAS and AML, and to show the effect of losartan and doxorubicin treatment in AML cell lines.

Methods:

AML cell lines including CESS, HL-60, MO-1, P31/FUJ, GDM-1 and KASUMI-3 were used as models in this study.

Results:

After treating the six AML cell lines with a combination of losartan and doxorubicin, they were divided into two groups based on their behaviour: one became more sensitive to drug treatment (Group A) and the other had no change observed in behaviour after drug treatment (Group B). In silico analyses showed that Group A is involved in cellular apoptosis, while Group B is involved in tumour angiogenesis further supporting the in vitro results.

Conclusion:

The combined treatment of the AML cell lines with losartan and doxorubicin resulted in an increase in sensitivity of some of the cell lines. Those leukaemic cells are modulated via the induction of apoptosis, whereas the other cells resistant to the drug treatment are closely related to tumour angiogenesis indicating that RAS-AT1R seems to be differently expressed in different leukaemic blast cells and tumour microenvironments. Pharmaco-biological actions of RAS inhibitors may be different in distinct leukaemic cells based on the pathological behaviour of AML genomic subtypes.

Illuminating biological pathways for drug targeting in head and neck squamous cell carcinoma

Head and neck squamous cell carcinoma (HNSCC) remains a morbid disease with poor prognosis and treatment that typically leaves patients with permanent damage to critical functions such as eating and talking. Currently only three targeted therapies are FDA approved for use in HNSCC, two of which are recently approved immunotherapies. In this work, we identify biological pathways involved with this disease that could potentially be targeted by current FDA approved cancer drugs and thereby expand the pool of potential therapies for use in HNSCC treatment. We analyzed 508 HNSCC patients with sequencing information from the Genomic Data Commons (GDC) database and assessed which biological pathways were significantly enriched for somatic mutations or copy number alterations. We then further classified pathways as either “light” or “dark” to the current reach of FDA-approved cancer drugs using the Cancer Targetome, a compendium of drug-target information. Light pathways are statistically enriched with somatic mutations (or copy number alterations) and contain one or more targets of current FDA-approved cancer drugs, while dark pathways are enriched with somatic mutations (or copy number alterations) but not currently targeted by FDA-approved cancer drugs. Our analyses indicated that approximately 35–38% of disease-specific pathways are in scope for repurposing of current cancer drugs. We further assess light and dark pathways for subgroups of patient tumor samples according to HPV status. The framework of light and dark pathways for HNSCC-enriched biological pathways allows us to better prioritize targeted therapies for further research in HNSCC based on the HNSCC genetic landscape and FDA-approved cancer drug information. We also highlight the importance in the identification of sub-pathways where targeting and cross targeting of other pathways may be most beneficial to predict positive or negative synergy with potential clinical significance. This framework is ideal for precision drug panel development, as well as identification of highly aberrant, untargeted candidates for future drug development.