Predicting cancer-specific vulnerability via data-driven detection of synthetic lethality.

Synthetic lethality occurs when the inhibition of two genes is lethal while the inhibition of each single gene is not. It can be harnessed to selectively treat cancer by identifying inactive genes in a given cancer and targeting their synthetic lethal (SL) partners. We present a data-driven computational pipeline for the genome-wide identification of SL interactions in cancer by analyzing large volumes of cancer genomic data. First, we show that the approach successfully captures known SL partners of tumor suppressors and oncogenes. We then validate SL predictions obtained for the tumor suppressor VHL. Next, we construct a genome-wide network of SL interactions in cancer and demonstrate its value in predicting gene essentiality and clinical prognosis. Finally, we identify synthetic lethality arising from gene overactivation and use it to predict drug efficacy. These results form a computational basis for exploiting synthetic lethality to uncover cancer-specific susceptibilities.

Breeze 2.0: an interactive web-tool for visual analysis and comparison of drug response data.

Functional precision medicine (fPM) offers an exciting, simplified approach to finding the right applications for existing molecules and enhancing therapeutic potential. Integrative and robust tools ensuring high accuracy and reliability of the results are critical. In response to this need, we previously developed Breeze, a drug screening data analysis pipeline, designed to facilitate quality control, dose-response curve fitting, and data visualization in a user-friendly manner. Here, we describe the latest version of Breeze (release 2.0), which implements an array of advanced data exploration capabilities, providing users with comprehensive post-analysis and interactive visualization options that are essential for minimizing false positive/negative outcomes and ensuring accurate interpretation of drug sensitivity and resistance data. The Breeze 2.0 web-tool also enables integrative analysis and cross-comparison of user-uploaded data with publicly available drug response datasets. The updated version incorporates new drug quantification metrics, supports analysis of both multi-dose and single-dose drug screening data and introduces a redesigned, intuitive user interface. With these enhancements, Breeze 2.0 is anticipated to substantially broaden its potential applications in diverse domains of fPM.

Dependency of a therapy-resistant state of cancer cells on a lipid peroxidase pathway.

Plasticity of the cell state has been proposed to drive resistance to multiple classes of cancer therapies, thereby limiting their effectiveness. A high-mesenchymal cell state observed in human tumours and cancer cell lines has been associated with resistance to multiple treatment modalities across diverse cancer lineages, but the mechanistic underpinning for this state has remained incompletely understood. Here we molecularly characterize this therapy-resistant high-mesenchymal cell state in human cancer cell lines and organoids and show that it depends on a druggable lipid-peroxidase pathway that protects against ferroptosis, a non-apoptotic form of cell death induced by the build-up of toxic lipid peroxides. We show that this cell state is characterized by activity of enzymes that promote the synthesis of polyunsaturated lipids. These lipids are the substrates for lipid peroxidation by lipoxygenase enzymes. This lipid metabolism creates a dependency on pathways converging on the phospholipid glutathione peroxidase (GPX4), a selenocysteine-containing enzyme that dissipates lipid peroxides and thereby prevents the iron-mediated reactions of peroxides that induce ferroptotic cell death. Dependency on GPX4 was found to exist across diverse therapy-resistant states characterized by high expression of ZEB1, including epithelial-mesenchymal transition in epithelial-derived carcinomas, TGFß-mediated therapy-resistance in melanoma, treatment-induced neuroendocrine transdifferentiation in prostate cancer, and sarcomas, which are fixed in a mesenchymal state owing to their cells of origin. We identify vulnerability to ferroptic cell death induced by inhibition of a lipid peroxidase pathway as a feature of therapy-resistant cancer cells across diverse mesenchymal cell-state contexts.

Targeting SAMHD1 with hydroxyurea in first-line cytarabine-based therapy of newly diagnosed acute myeloid leukaemia: Results from the HEAT-AML trial.

BACKGROUND: Treatment of newly diagnosed acute myeloid leukaemia (AML) is based on combination chemotherapy with cytarabine (ara-C) and anthracyclines. Five-year overall survival is below 30%, which has partly been attributed to cytarabine resistance. Preclinical data suggest that the addition of hydroxyurea potentiates cytarabine efficacy by increasing ara-C triphosphate (ara-CTP) levels through targeted inhibition of SAMHD1. OBJECTIVES: In this phase 1 trial, we evaluated the feasibility, safety and efficacy of the addition of hydroxyurea to standard chemotherapy with cytarabine/daunorubicin in newly diagnosed AML patients. METHODS: Nine patients were enrolled and received at least two courses of ara-C (1 g/m2 /2 h b.i.d. d1-5, i.e., a total of 10 g/m2 per course), hydroxyurea (1-2 g d1-5) and daunorubicin (60 mg/m2 d1-3). The primary endpoint was safety; secondary endpoints were complete remission rate and measurable residual disease (MRD). Additionally, pharmacokinetic studies of ara-CTP and ex vivo drug sensitivity assays were performed. RESULTS: The most common grade 3-4 toxicity was febrile neutropenia (100%). No unexpected toxicities were observed. Pharmacokinetic analyses showed a significant increase in median ara-CTP levels (1.5-fold; p = 0.04) in patients receiving doses of 1 g hydroxyurea. Ex vivo, diagnostic leukaemic bone marrow blasts from study patients were significantly sensitised to ara-C by a median factor of 2.1 (p = 0.0047). All nine patients (100%) achieved complete remission, and all eight (100%) with validated MRD measurements (flow cytometry or real-time quantitative polymerase chain reaction [RT-qPCR]) had an MRD level <0.1% after two cycles of chemotherapy. Treatment was well-tolerated, and median time to neutrophil recovery >1.0 × 109 /L and to platelet recovery >50 × 109 /L after the start of cycle 1 was 19 days and 22 days, respectively. Six of nine patients underwent allogeneic haematopoietic stem-cell transplantation (allo-HSCT). With a median follow-up of 18.0 (range 14.9-20.5) months, one patient with adverse risk not fit for HSCT experienced a relapse after 11.9 months but is now in second complete remission. CONCLUSION: Targeted inhibition of SAMHD1 by the addition of hydroxyurea to conventional AML therapy is safe and appears efficacious within the limitations of the small phase 1 patient cohort. These results need to be corroborated in a larger study.

Immediate Adaptation Analysis Implicates BCL6 as an EGFR-TKI Combination Therapy Target in NSCLC.

Drug resistance is a major obstacle to curative cancer therapies, and increased understanding of the molecular events contributing to resistance would enable better prediction of therapy response, as well as contribute to new targets for combination therapy. Here we have analyzed the early molecular response to epidermal growth factor receptor (EGFR) inhibition using RNA sequencing data covering 13,486 genes and mass spectrometry data covering 10,138 proteins. This analysis revealed a massive response to EGFR inhibition already within the first 24 h, including significant regulation of hundreds of genes known to control downstream signaling, such as transcription factors, kinases, phosphatases and ubiquitin E3-ligases. Importantly, this response included upregulation of key genes in multiple oncogenic signaling pathways that promote proliferation and survival, such as ERBB3, FGFR2, JAK3, and BCL6, indicating an early adaptive response to EGFR inhibition. Using a library of more than 500 approved and experimental compounds in a combination therapy screen, we could show that several kinase inhibitors with targets including JAK3 and FGFR2 increased the response to EGFR inhibitors. Further, we investigated the functional impact of BCL6 upregulation in response to EGFR inhibition using siRNA-based silencing of BCL6. Proteomics profiling revealed that BCL6 inhibited transcription of multiple target genes including p53, resulting in reduced apoptosis which implicates BCL6 upregulation as a new EGFR inhibitor treatment escape mechanism. Finally, we demonstrate that combined treatment targeting both EGFR and BCL6 act synergistically in killing lung cancer cells. In conclusion, or data indicates that multiple different adaptive mechanisms may act in concert to blunt the cellular impact of EGFR inhibition, and we suggest BCL6 as a potential target for EGFR inhibitor-based combination therapy.

The transcriptome-wide landscape of molecular subtype-specific mRNA expression profiles in acute myeloid leukemia.

Molecular classification of acute myeloid leukemia (AML) aids prognostic stratification and clinical management. Our aim in this study is to identify transcriptome-wide mRNAs that are specific to each of the molecular subtypes of AML. We analyzed RNA-sequencing data of 955 AML samples from three cohorts, including the BeatAML project, the Cancer Genome Atlas, and a cohort of Swedish patients to provide a comprehensive transcriptome-wide view of subtype-specific mRNA expression. We identified 729 subtype-specific mRNAs, discovered in the BeatAML project and validated in the other two cohorts. Using unique proteomics data, we also validated the presence of subtype-specific mRNAs at the protein level, yielding a rich collection of potential protein-based biomarkers for the AML community. To enable the exploration of subtype-specific mRNA expression by the broader scientific community, we provide an interactive resource to the public.

Prediction of intracellular exposure bridges the gap between target- and cell-based drug discovery.

Inadequate target exposure is a major cause of high attrition in drug discovery. Here, we show that a label-free method for quantifying the intracellular bioavailability (Fic) of drug molecules predicts drug access to intracellular targets and hence, pharmacological effect. We determined Fic in multiple cellular assays and cell types representing different targets from a number of therapeutic areas, including cancer, inflammation, and dementia. Both cytosolic targets and targets localized in subcellular compartments were investigated. Fic gives insights on membrane-permeable compounds in terms of cellular potency and intracellular target engagement, compared with biochemical potency measurements alone. Knowledge of the amount of drug that is locally available to bind intracellular targets provides a powerful tool for compound selection in early drug discovery.

Targeting CDK2 overcomes melanoma resistance against BRAF and Hsp90 inhibitors.

Novel therapies are undergoing clinical trials, for example, the Hsp90 inhibitor, XL888, in combination with BRAF inhibitors for the treatment of therapy-resistant melanomas. Unfortunately, our data show that this combination elicits a heterogeneous response in a panel of melanoma cell lines including PDX-derived models. We sought to understand the mechanisms underlying the differential responses and suggest a patient stratification strategy. Thermal proteome profiling (TPP) identified the protein targets of XL888 in a pair of sensitive and unresponsive cell lines. Unbiased proteomics and phosphoproteomics analyses identified CDK2 as a driver of resistance to both BRAF and Hsp90 inhibitors and its expression is regulated by the transcription factor MITF upon XL888 treatment. The CDK2 inhibitor, dinaciclib, attenuated resistance to both classes of inhibitors and combinations thereof. Notably, we found that MITF expression correlates with CDK2 upregulation in patients; thus, dinaciclib would warrant consideration for treatment of patients unresponsive to BRAF-MEK and/or Hsp90 inhibitors and/or harboring MITF amplification/overexpression.

Small-molecule studies identify CDK8 as a regulator of IL-10 in myeloid cells.

Enhancing production of the anti-inflammatory cytokine interleukin-10 (IL-10) is a promising strategy to suppress pathogenic inflammation. To identify new mechanisms regulating IL-10 production, we conducted a phenotypic screen for small molecules that enhance IL-10 secretion from activated dendritic cells. Mechanism-of-action studies using a prioritized hit from the screen, BRD6989, identified the Mediator-associated kinase CDK8, and its paralog CDK19, as negative regulators of IL-10 production during innate immune activation. The ability of BRD6989 to upregulate IL-10 is recapitulated by multiple, structurally differentiated CDK8 and CDK19 inhibitors and requires an intact cyclin C-CDK8 complex. Using a highly parallel pathway reporter assay, we identified a role for enhanced AP-1 activity in IL-10 potentiation following CDK8 and CDK19 inhibition, an effect associated with reduced phosphorylation of a negative regulatory site on c-Jun. These findings identify a function for CDK8 and CDK19 in regulating innate immune activation and suggest that these kinases may warrant consideration as therapeutic targets for inflammatory disorders.

Quantitative Interpretation of Intracellular Drug Binding and Kinetics Using the Cellular Thermal Shift Assay.

Evidence of physical interaction with the target protein is essential in the development of chemical probes and drugs. The cellular thermal shift assay (CETSA) allows evaluation of drug binding in live cells but lacks a framework to support quantitative interpretations and comparisons with functional data. We outline an experimental platform for such analysis using human kinase p38α. Systematic variations to the assay's characteristic heat challenge demonstrate an apparent loss of compound potency with an increase in duration or temperature, in line with expectations from the literature for thermal shift assays. Importantly, data for five structurally diverse inhibitors can be quantitatively explained using a simple model of linked equilibria and published binding parameters. The platform further distinguishes between ligand mechanisms and allows for quantitative comparisons of drug binding affinities and kinetics in live cells and lysates. We believe this work has broad implications in the appropriate use of the CETSA for target and compound validation.

Reprint of: A chemical screen identifies trifluoperazine as an inhibitor of glioblastoma growth.

Glioblastoma (GBM) is regarded as the most common malignant brain tumor but treatment options are limited. Thus, there is an unmet clinical need for compounds and corresponding targets that could inhibit GBM growth. We screened a library of 80 dopaminergic ligands with the aim of identifying compounds capable of inhibiting GBM cell line proliferation and survival. Out of 45 active compounds, 8 were further validated. We found that the dopamine receptor D2 antagonist trifluoperazine 2HCl inhibits growth and proliferation of GBM cells in a dose dependent manner. Trifluoperazine's inhibition of GBM cells is cell line dependent and correlates with variations in dopamine receptor expression profile. We conclude that components of the dopamine receptor signaling pathways are potential targets for pharmacological interventions of GBM growth.

Correlating chemical sensitivity and basal gene expression reveals mechanism of action.

Changes in cellular gene expression in response to small-molecule or genetic perturbations have yielded signatures that can connect unknown mechanisms of action (MoA) to ones previously established. We hypothesized that differential basal gene expression could be correlated with patterns of small-molecule sensitivity across many cell lines to illuminate the actions of compounds whose MoA are unknown. To test this idea, we correlated the sensitivity patterns of 481 compounds with ∼19,000 basal transcript levels across 823 different human cancer cell lines and identified selective outlier transcripts. This process yielded many novel mechanistic insights, including the identification of activation mechanisms, cellular transporters and direct protein targets. We found that ML239, originally identified in a phenotypic screen for selective cytotoxicity in breast cancer stem-like cells, most likely acts through activation of fatty acid desaturase 2 (FADS2). These data and analytical tools are available to the research community through the Cancer Therapeutics Response Portal.

A chemical screen identifies trifluoperazine as an inhibitor of glioblastoma growth.

Glioblastoma (GBM) is regarded as the most common malignant brain tumor but treatment options are limited. Thus, there is an unmet clinical need for compounds and corresponding targets that could inhibit GBM growth. We screened a library of 80 dopaminergic ligands with the aim of identifying compounds capable of inhibiting GBM cell line proliferation and survival. Out of 45 active compounds, 8 were further validated. We found that the dopamine receptor D2 antagonist trifluoperazine 2HCl inhibits growth and proliferation of GBM cells in a dose dependent manner. Trifluoperazine's inhibition of GBM cells is cell line dependent and correlates with variations in dopamine receptor expression profile. We conclude that components of the dopamine receptor signaling pathways are potential targets for pharmacological interventions of GBM growth.

Discovery of a Small-Molecule Probe for V-ATPase Function.

Lysosomes perform a critical cellular function as a site of degradation for diverse cargoes including proteins, organelles, and pathogens delivered through distinct pathways, and defects in lysosomal function have been implicated in a number of diseases. Recent studies have elucidated roles for the lysosome in the regulation of protein synthesis, metabolism, membrane integrity, and other processes involved in homeostasis. Complex small-molecule natural products have greatly contributed to the investigation of lysosomal function in cellular physiology. Here we report the discovery of a novel, small-molecule modulator of lysosomal acidification derived from diversity-oriented synthesis through high-content screening.

Cancer-associated fibroblasts rewire the estrogen receptor response in luminal breast cancer, enabling estrogen independence.

Advanced breast cancers represent a major therapeutic challenge due to their refractoriness to treatment. Cancer-associated fibroblasts (CAFs) are the most abundant constituents of the tumor microenvironment and have been linked to most hallmarks of cancer. However, the influence of CAFs on therapeutic outcome remains largely unchartered. Here, we reveal that spatial coincidence of abundant CAF infiltration with malignant cells was associated with reduced estrogen receptor (ER)-α expression and activity in luminal breast tumors. Notably, CAFs mediated estrogen-independent tumor growth by selectively regulating ER-α signaling. Whereas most prototypical estrogen-responsive genes were suppressed, CAFs maintained gene expression related to therapeutic resistance, basal-like differentiation, and invasion. A functional drug screen in co-cultures identified effector pathways involved in the CAF-induced regulation of ER-α signaling. Among these, the Transforming Growth Factor-ß and the Janus kinase signaling cascades were validated as actionable targets to counteract the CAF-induced modulation of ER-α activity. Finally, genes that were downregulated in cancer cells by CAFs were predictive of poor response to endocrine treatment. In conclusion, our work reveals that CAFs directly control the luminal breast cancer phenotype by selectively modulating ER-α expression and transcriptional function, and further proposes novel targets to disrupt the crosstalk between CAFs and tumor cells to reinstate treatment response to endocrine therapy in patients.

High-content screening of drug combinations of an mPGES-1 inhibitor in multicellular tumor spheroids leads to mechanistic insights into neuroblastoma chemoresistance.

High-throughput drug screening enables the discovery of new anticancer drugs. Although monolayer cell cultures are commonly used for screening, their limited complexity and translational efficiency require alternative models. Three-dimensional cell cultures, such as multicellular tumor spheroids (MCTS), mimic tumor architecture and offer promising opportunities for drug discovery. In this study, we developed a neuroblastoma MCTS model for high-content drug screening. We also aimed to decipher the mechanisms underlying synergistic drug combinations in this disease model. Several agents from different therapeutic categories and with different mechanisms of action were tested alone or in combination with selective inhibition of prostaglandin E2 by pharmacological inhibition of microsomal prostaglandin E synthase-1 (mPGES-1). After a systematic investigation of the sensitivity of individual agents and the effects of pairwise combinations, GFP-transfected MCTS were used in a confirmatory screen to validate the hits. Finally, inhibitory effects on multidrug resistance proteins were examined. In summary, we demonstrate how MCTS-based high-throughput drug screening has the potential to uncover effective drug combinations and provide insights into the mechanism of synergy between an mPGES-1 inhibitor and chemotherapeutic agents.

Delineating functional and molecular impact of ex vivo sample handling in precision medicine.

Consistent handling of samples is crucial for achieving reproducible molecular and functional testing results in translational research. Here, we used 229 acute myeloid leukemia (AML) patient samples to assess the impact of sample handling on high-throughput functional drug testing, mass spectrometry-based proteomics, and flow cytometry. Our data revealed novel and previously described changes in cell phenotype and drug response dependent on sample biobanking. Specifically, myeloid cells with a CD117 (c-KIT) positive phenotype decreased after biobanking, potentially distorting cell population representations and affecting drugs targeting these cells. Additionally, highly granular AML cell numbers decreased after freezing. Secondly, protein expression levels, as well as sensitivity to drugs targeting cell proliferation, metabolism, tyrosine kinases (e.g., JAK, KIT, FLT3), and BH3 mimetics were notably affected by biobanking. Moreover, drug response profiles of paired fresh and frozen samples showed that freezing samples can lead to systematic errors in drug sensitivity scores. While a high correlation between fresh and frozen for the entire drug library was observed, freezing cells had a considerable impact at an individual level, which could influence outcomes in translational studies. Our study highlights conditions where standardization is needed to improve reproducibility, and where validation of data generated from biobanked cohorts may be particularly important.

A phenotypic screening approach to target p60AmotL2-expressing invasive cancer cells.

BACKGROUND: Tumor cells have the ability to invade and form small clusters that protrude into adjacent tissues, a phenomenon that is frequently observed at the periphery of a tumor as it expands into healthy tissues. The presence of these clusters is linked to poor prognosis and has proven challenging to treat using conventional therapies. We previously reported that p60AmotL2 expression is localized to invasive colon and breast cancer cells. In vitro, p60AmotL2 promotes epithelial cell invasion by negatively impacting E-cadherin/AmotL2-related mechanotransduction. METHODS: Using epithelial cells transfected with inducible p60AmotL2, we employed a phenotypic drug screening approach to find compounds that specifically target invasive cells. The phenotypic screen was performed by treating cells for 72 h with a library of compounds with known antitumor activities in a dose-dependent manner. After assessing cell viability using CellTiter-Glo, drug sensitivity scores for each compound were calculated. Candidate hit compounds with a higher drug sensitivity score for p60AmotL2-expressing cells were then validated on lung and colon cell models, both in 2D and in 3D, and on colon cancer patient-derived organoids. Nascent RNA sequencing was performed after BET inhibition to analyse BET-dependent pathways in p60AmotL2-expressing cells. RESULTS: We identified 60 compounds that selectively targeted p60AmotL2-expressing cells. Intriguingly, these compounds were classified into two major categories: Epidermal Growth Factor Receptor (EGFR) inhibitors and Bromodomain and Extra-Terminal motif (BET) inhibitors. The latter consistently demonstrated antitumor activity in human cancer cell models, as well as in organoids derived from colon cancer patients. BET inhibition led to a shift towards the upregulation of pro-apoptotic pathways specifically in p60AmotL2-expressing cells. CONCLUSIONS: BET inhibitors specifically target p60AmotL2-expressing invasive cancer cells, likely by exploiting differences in chromatin accessibility, leading to cell death. Additionally, our findings support the use of this phenotypic strategy to discover novel compounds that can exploit vulnerabilities and specifically target invasive cancer cells.

Targeting autophagy as a therapeutic strategy in pediatric acute lymphoblastic leukemia.

Autophagy is activated in response to a variety of stress conditions including anti-cancer therapies, and tumors cells often depend on autophagy for survival. In this study, we have evaluated inhibition of autophagy as therapeutic strategy in acute lymphoblastic leukemia (ALL) in children, both as a single treatment and in combination with glucocorticoid (GC) Dexamethasone (Dexa). Analysis of proteomics and RNA-seq of ALL cell lines and primary samples identified an upregulation of Vps34 and ATG14 proteins and autophagy and lysosomal pathway enrichment in a genetic subgroup with a recurrent t(12;21) translocation. Cells from this sugbroup were also significantly more sensitive to the selective autophagy or lysosomal inhibitors than cells with other genetic rearrangements. Further, combination of Dexa with either lysosomal or autophagy inhibitors was either synergistic or additive in killing leukemic cells across various genetic and lineage backgrounds, for both cell lines and primary samples, as assessed using viability assays and SynergyFinder as well as apoptotic caspase 3/7-based live-cell assays. Our data demonstrate that targeting autophagy represents a promising strategy for the treatment of pediatric ALL, both as a selective modality for the t(12;21) pre-B-ALL subgroup, and in combination treatments to sensitize to GC-induced cytotoxicity.

High-throughput cell spheroid production and assembly analysis by microfluidics and deep learning.

3D cell culture models are important tools in translational research but have been out of reach for high-throughput screening due to complexity, requirement of large cell numbers and inadequate standardization. Microfluidics and culture model miniaturization technologies could overcome these challenges. Here, we present a high-throughput workflow to produce and characterize the formation of miniaturized spheroids using deep learning. We train a convolutional neural network (CNN) for cell ensemble morphology classification for droplet microfluidic minispheroid production, benchmark it against more conventional image analysis, and characterize minispheroid assembly determining optimal surfactant concentrations and incubation times for minispheroid production for three cell lines with different spheroid formation properties. Notably, this format is compatible with large-scale spheroid production and screening. The presented workflow and CNN offer a template for large scale minispheroid production and analysis and can be extended and re-trained to characterize morphological responses in spheroids to additives, culture conditions and large drug libraries.