Elucidating Compound Mechanism of Action by Network Perturbation Analysis.

Genome-wide identification of the mechanism of action (MoA) of small-molecule compounds characterizing their targets, effectors, and activity modulators represents a highly relevant yet elusive goal, with critical implications for assessment of compound efficacy and toxicity. Current approaches are labor intensive and mostly limited to elucidating high-affinity binding target proteins. We introduce a regulatory network-based approach that elucidates genome-wide MoA proteins based on the assessment of the global dysregulation of their molecular interactions following compound perturbation. Analysis of cellular perturbation profiles identified established MoA proteins for 70% of the tested compounds and elucidated novel proteins that were experimentally validated. Finally, unknown-MoA compound analysis revealed altretamine, an anticancer drug, as an inhibitor of glutathione peroxidase 4 lipid repair activity, which was experimentally confirmed, thus revealing unexpected similarity to the activity of sulfasalazine. This suggests that regulatory network analysis can provide valuable mechanistic insight into the elucidation of small-molecule MoA and compound similarity.

Silencing c-Myc translation as a therapeutic strategy through targeting PI3Kδ and CK1ε in hematological malignancies.

Phosphoinositide 3-kinase (PI3K) and the proteasome pathway are both involved in activating the mechanistic target of rapamycin (mTOR). Because mTOR signaling is required for initiation of messenger RNA translation, we hypothesized that cotargeting the PI3K and proteasome pathways might synergistically inhibit translation of c-Myc. We found that a novel PI3K δ isoform inhibitor TGR-1202, but not the approved PI3Kδ inhibitor idelalisib, was highly synergistic with the proteasome inhibitor carfilzomib in lymphoma, leukemia, and myeloma cell lines and primary lymphoma and leukemia cells. TGR-1202 and carfilzomib (TC) synergistically inhibited phosphorylation of the eukaryotic translation initiation factor 4E (eIF4E)-binding protein 1 (4E-BP1), leading to suppression of c-Myc translation and silencing of c-Myc-dependent transcription. The synergistic cytotoxicity of TC was rescued by overexpression of eIF4E or c-Myc. TGR-1202, but not other PI3Kδ inhibitors, inhibited casein kinase-1 ε (CK1ε). Targeting CK1ε using a selective chemical inhibitor or short hairpin RNA complements the effects of idelalisib, as a single agent or in combination with carfilzomib, in repressing phosphorylation of 4E-BP1 and the protein level of c-Myc. These results suggest that TGR-1202 is a dual PI3Kδ/CK1ε inhibitor, which may in part explain the clinical activity of TGR-1202 in aggressive lymphoma not found with idelalisib. Targeting CK1ε should become an integral part of therapeutic strategies targeting translation of oncogenes such as c-Myc.

Systematic, network-based characterization of therapeutic target inhibitors.

A large fraction of the proteins that are being identified as key tumor dependencies represent poor pharmacological targets or lack clinically-relevant small-molecule inhibitors. Availability of fully generalizable approaches for the systematic and efficient prioritization of tumor-context specific protein activity inhibitors would thus have significant translational value. Unfortunately, inhibitor effects on protein activity cannot be directly measured in systematic and proteome-wide fashion by conventional biochemical assays. We introduce OncoLead, a novel network based approach for the systematic prioritization of candidate inhibitors for arbitrary targets of therapeutic interest. In vitro and in vivo validation confirmed that OncoLead analysis can recapitulate known inhibitors as well as prioritize novel, context-specific inhibitors of difficult targets, such as MYC and STAT3. We used OncoLead to generate the first unbiased drug/regulator interaction map, representing compounds modulating the activity of cancer-relevant transcription factors, with potential in precision medicine.

Nonsteroidal anti-inflammatory drug sensitizes Mycobacterium tuberculosis to endogenous and exogenous antimicrobials.

Existing drugs are slow to eradicate Mycobacterium tuberculosis (Mtb) in patients and have failed to control tuberculosis globally. One reason may be that host conditions impair Mtb's replication, reducing its sensitivity to most antiinfectives. We devised a high-throughput screen for compounds that kill Mtb when its replication has been halted by reactive nitrogen intermediates (RNIs), acid, hypoxia, and a fatty acid carbon source. At concentrations routinely achieved in human blood, oxyphenbutazone (OPB), an inexpensive anti-inflammatory drug, was selectively mycobactericidal to nonreplicating (NR) Mtb. Its cidal activity depended on mild acid and was augmented by RNIs and fatty acid. Acid and RNIs fostered OPB's 4-hydroxylation. The resultant 4-butyl-4-hydroxy-1-(4-hydroxyphenyl)-2-phenylpyrazolidine-3,5-dione (4-OH-OPB) killed both replicating and NR Mtb, including Mtb resistant to standard drugs. 4-OH-OPB depleted flavins and formed covalent adducts with N-acetyl-cysteine and mycothiol. 4-OH-OPB killed Mtb synergistically with oxidants and several antituberculosis drugs. Thus, conditions that block Mtb's replication modify OPB and enhance its cidal action. Modified OPB kills both replicating and NR Mtb and sensitizes both to host-derived and medicinal antimycobacterial agents.

Discovering Venom-Derived Drug Candidates Using Differential Gene Expression.

Venoms are a diverse and complex group of natural toxins that have been adapted to treat many types of human disease, but rigorous computational approaches for discovering new therapeutic activities are scarce. We have designed and validated a new platform-named VenomSeq-to systematically identify putative associations between venoms and drugs/diseases via high-throughput transcriptomics and perturbational differential gene expression analysis. In this study, we describe the architecture of VenomSeq and its evaluation using the crude venoms from 25 diverse animal species and 9 purified teretoxin peptides. By integrating comparisons to public repositories of differential expression, associations between regulatory networks and disease, and existing knowledge of venom activity, we provide a number of new therapeutic hypotheses linking venoms to human diseases supported by multiple layers of preliminary evidence.

Systematic elucidation and pharmacological targeting of tumor-infiltrating regulatory T cell master regulators.

Due to their immunosuppressive role, tumor-infiltrating regulatory T cells (TI-Tregs) represent attractive immuno-oncology targets. Analysis of TI vs. peripheral Tregs (P-Tregs) from 36 patients, across four malignancies, identified 17 candidate master regulators (MRs) as mechanistic determinants of TI-Treg transcriptional state. Pooled CRISPR-Cas9 screening in vivo, using a chimeric hematopoietic stem cell transplant model, confirmed the essentiality of eight MRs in TI-Treg recruitment and/or retention without affecting other T cell subtypes, and targeting one of the most significant MRs (Trps1) by CRISPR KO significantly reduced ectopic tumor growth. Analysis of drugs capable of inverting TI-Treg MR activity identified low-dose gemcitabine as the top prediction. Indeed, gemcitabine treatment inhibited tumor growth in immunocompetent but not immunocompromised allografts, increased anti-PD-1 efficacy, and depleted MR-expressing TI-Tregs in vivo. This study provides key insight into Treg signaling, specifically in the context of cancer, and a generalizable strategy to systematically elucidate and target MR proteins in immunosuppressive subpopulations.

OncoLoop: A Network-Based Precision Cancer Medicine Framework.

Prioritizing treatments for individual patients with cancer remains challenging, and performing coclinical studies using patient-derived models in real time is often unfeasible. To circumvent these challenges, we introduce OncoLoop, a precision medicine framework that predicts drug sensitivity in human tumors and their preexisting high-fidelity (cognate) model(s) by leveraging drug perturbation profiles. As a proof of concept, we applied OncoLoop to prostate cancer using genetically engineered mouse models (GEMM) that recapitulate a broad spectrum of disease states, including castration-resistant, metastatic, and neuroendocrine prostate cancer. Interrogation of human prostate cancer cohorts by Master Regulator (MR) conservation analysis revealed that most patients with advanced prostate cancer were represented by at least one cognate GEMM-derived tumor (GEMM-DT). Drugs predicted to invert MR activity in patients and their cognate GEMM-DTs were successfully validated in allograft, syngeneic, and patient-derived xenograft (PDX) models of tumors and metastasis. Furthermore, OncoLoop-predicted drugs enhanced the efficacy of clinically relevant drugs, namely, the PD-1 inhibitor nivolumab and the AR inhibitor enzalutamide. SIGNIFICANCE: OncoLoop is a transcriptomic-based experimental and computational framework that can support rapid-turnaround coclinical studies to identify and validate drugs for individual patients, which can then be readily adapted to clinical practice. This framework should be applicable in many cancer contexts for which appropriate models and drug perturbation data are available. This article is highlighted in the In This Issue feature, p. 247.

A Transcriptome-Based Precision Oncology Platform for Patient-Therapy Alignment in a Diverse Set of Treatment-Resistant Malignancies.

Predicting in vivo response to antineoplastics remains an elusive challenge. We performed a first-of-kind evaluation of two transcriptome-based precision cancer medicine methodologies to predict tumor sensitivity to a comprehensive repertoire of clinically relevant oncology drugs, whose mechanism of action we experimentally assessed in cognate cell lines. We enrolled patients with histologically distinct, poor-prognosis malignancies who had progressed on multiple therapies, and developed low-passage, patient-derived xenograft models that were used to validate 35 patient-specific drug predictions. Both OncoTarget, which identifies high-affinity inhibitors of individual master regulator (MR) proteins, and OncoTreat, which identifies drugs that invert the transcriptional activity of hyperconnected MR modules, produced highly significant 30-day disease control rates (68% and 91%, respectively). Moreover, of 18 OncoTreat-predicted drugs, 15 induced the predicted MR-module activity inversion in vivo. Predicted drugs significantly outperformed antineoplastic drugs selected as unpredicted controls, suggesting these methods may substantively complement existing precision cancer medicine approaches, as also illustrated by a case study. SIGNIFICANCE: Complementary precision cancer medicine paradigms are needed to broaden the clinical benefit realized through genetic profiling and immunotherapy. In this first-in-class application, we introduce two transcriptome-based tumor-agnostic systems biology tools to predict drug response in vivo. OncoTarget and OncoTreat are scalable for the design of basket and umbrella clinical trials. This article is highlighted in the In This Issue feature, p. 1275.

A Model for Network-Based Identification and Pharmacological Targeting of Aberrant, Replication-Permissive Transcriptional Programs Induced by Viral Infection.

Precise characterization and targeting of host cell transcriptional machinery hijacked by viral infection remains challenging. Here, we show that SARS-CoV-2 hijacks the host cell transcriptional machinery to induce a phenotypic state amenable to its replication. Specifically, analysis of Master Regulator (MR) proteins representing mechanistic determinants of the gene expression signature induced by SARS-CoV-2 in infected cells revealed coordinated inactivation of MRs enriched in physical interactions with SARS-CoV-2 proteins, suggesting their mechanistic role in maintaining a host cell state refractory to virus replication. To test their functional relevance, we measured SARS-CoV-2 replication in epithelial cells treated with drugs predicted to activate the entire repertoire of repressed MRs, based on their experimentally elucidated, context-specific mechanism of action. Overall, >80% of drugs predicted to be effective by this methodology induced significant reduction of SARS-CoV-2 replication, without affecting cell viability. This model for host-directed pharmacological therapy is fully generalizable and can be deployed to identify drugs targeting host cell-based MR signatures induced by virtually any pathogen.

A model for network-based identification and pharmacological targeting of aberrant, replication-permissive transcriptional programs induced by viral infection.

SARS-CoV-2 hijacks the host cell transcriptional machinery to induce a phenotypic state amenable to its replication. Here we show that analysis of Master Regulator proteins representing mechanistic determinants of the gene expression signature induced by SARS-CoV-2 in infected cells revealed coordinated inactivation of Master Regulators enriched in physical interactions with SARS-CoV-2 proteins, suggesting their mechanistic role in maintaining a host cell state refractory to virus replication. To test their functional relevance, we measured SARS-CoV-2 replication in epithelial cells treated with drugs predicted to activate the entire repertoire of repressed Master Regulators, based on their experimentally elucidated, context-specific mechanism of action. Overall, 15 of the 18 drugs predicted to be effective by this methodology induced significant reduction of SARS-CoV-2 replication, without affecting cell viability. This model for host-directed pharmacological therapy is fully generalizable and can be deployed to identify drugs targeting host cell-based Master Regulator signatures induced by virtually any pathogen.

TOP2B Enzymatic Activity on Promoters and Introns Modulates Multiple Oncogenes in Human Gliomas.

PURPOSE: The epigenetic mechanisms involved in transcriptional regulation leading to malignant phenotype in gliomas remains poorly understood. Topoisomerase IIB (TOP2B), an enzyme that decoils and releases torsional forces in DNA, is overexpressed in a subset of gliomas. Therefore, we investigated its role in epigenetic regulation in these tumors. EXPERIMENTAL DESIGN: To investigate the role of TOP2B in epigenetic regulation in gliomas, we performed paired chromatin immunoprecipitation sequencing for TOP2B and RNA-sequencing analysis of glioma cell lines with and without TOP2B inhibition and in human glioma specimens. These experiments were complemented with assay for transposase-accessible chromatin using sequencing, gene silencing, and mouse xenograft experiments to investigate the function of TOP2B and its role in glioma phenotypes. RESULTS: We discovered that TOP2B modulates transcription of multiple oncogenes in human gliomas. TOP2B regulated transcription only at sites where it was enzymatically active, but not at all native binding sites. In particular, TOP2B activity localized in enhancers, promoters, and introns of PDGFRA and MYC, facilitating their expression. TOP2B levels and genomic localization was associated with PDGFRA and MYC expression across glioma specimens, which was not seen in nontumoral human brain tissue. In vivo, TOP2B knockdown of human glioma intracranial implants prolonged survival and downregulated PDGFRA. CONCLUSIONS: Our results indicate that TOP2B activity exerts a pleiotropic role in transcriptional regulation of oncogenes in a subset of gliomas promoting a proliferative phenotype.

Simulating henipavirus multicycle replication in a screening assay leads to identification of a promising candidate for therapy.

Nipah (NiV) and Hendra (HeV) viruses are emerging zoonotic paramyxoviruses that cause encephalitis in humans, with fatality rates of up to 75%. We designed a new high-throughput screening (HTS) assay for inhibitors of infection based on envelope glycoprotein pseudotypes. The assay simulates multicycle replication and thus identifies inhibitors that target several stages of the viral life cycle, but it still can be carried out under biosafety level 2 (BSL-2) conditions. These features permit a screen for antivirals for emerging viruses and select agents that otherwise would require BSL-4 HTS facilities. The screening of a small compound library identified several effective molecules, including the well-known compound chloroquine, as highly active inhibitors of pseudotyped virus infection. Chloroquine inhibited infection with live HeV and NiV at a concentration of 1 microM in vitro (50% inhibitory concentration, 2 microM), which is less than the plasma concentrations present in humans receiving chloroquine treatment for malaria. The mechanism for chloroquine's antiviral action likely is the inhibition of cathepsin L, a cellular enzyme that is essential for the processing of the viral fusion glycoprotein and the maturation of newly budding virions. Without this processing step, virions are not infectious. The identification of a compound that inhibits a known cellular target that is important for viral maturation but that had not previously been shown to have antiviral activity for henipaviruses highlights the validity of this new screening assay. Given the established safety profile and broad experience with chloroquine in humans, the results described here provide an option for treating individuals infected by these deadly viruses.

The transcriptomic response of cells to a drug combination is more than the sum of the responses to the monotherapies.

Our ability to discover effective drug combinations is limited, in part by insufficient understanding of how the transcriptional response of two monotherapies results in that of their combination. We analyzed matched time course RNAseq profiling of cells treated with single drugs and their combinations and found that the transcriptional signature of the synergistic combination was unique relative to that of either constituent monotherapy. The sequential activation of transcription factors in time in the gene regulatory network was implicated. The nature of this transcriptional cascade suggests that drug synergy may ensue when the transcriptional responses elicited by two unrelated individual drugs are correlated. We used these results as the basis of a simple prediction algorithm attaining an AUROC of 0.77 in the prediction of synergistic drug combinations in an independent dataset.

The Host Cell ViroCheckpoint: Identification and Pharmacologic Targeting of Novel Mechanistic Determinants of Coronavirus-Mediated Hijacked Cell States.

Most antiviral agents are designed to target virus-specific proteins and mechanisms rather than the host cell proteins that are critically dysregulated following virus-mediated reprogramming of the host cell transcriptional state. To overcome these limitations, we propose that elucidation and pharmacologic targeting of host cell Master Regulator proteins-whose aberrant activities govern the reprogramed state of coronavirus-infected cells-presents unique opportunities to develop novel mechanism-based therapeutic approaches to antiviral therapy, either as monotherapy or as a complement to established treatments. Specifically, we propose that a small module of host cell Master Regulator proteins (ViroCheckpoint) is hijacked by the virus to support its efficient replication and release. Conventional methodologies are not well suited to elucidate these potentially targetable proteins. By using the VIPER network-based algorithm, we successfully interrogated 12h, 24h, and 48h signatures from Calu-3 lung adenocarcinoma cells infected with SARS-CoV, to elucidate the time-dependent reprogramming of host cells and associated Master Regulator proteins. We used the NYS CLIA-certified Darwin OncoTreat algorithm, with an existing database of RNASeq profiles following cell perturbation with 133 FDA-approved and 195 late-stage experimental compounds, to identify drugs capable of virtually abrogating the virus-induced Master Regulator signature. This approach to drug prioritization and repurposing can be trivially extended to other viral pathogens, including SARS-CoV-2, as soon as the relevant infection signature becomes available.

Inhibition of NF-κB-Dependent Signaling Enhances Sensitivity and Overcomes Resistance to BET Inhibition in Uveal Melanoma.

Bromodomain and extraterminal protein inhibitors (BETi) are epigenetic therapies aimed to target dysregulated gene expression in cancer cells. Despite early successes of BETi in a range of malignancies, the development of drug resistance may limit their clinical application. Here, we evaluated the mechanisms of BETi resistance in uveal melanoma, a disease with little treatment options, using two approaches: a high-throughput combinatorial drug screen with the clinical BET inhibitor PLX51107 and RNA sequencing of BETi-resistant cells. NF-κB inhibitors synergistically sensitized uveal melanoma cells to PLX51107 treatment. Furthermore, genes involved in NF-κB signaling were upregulated in BETi-resistant cells, and the transcription factor CEBPD contributed to the mechanism of resistance. These findings suggest that inhibitors of NF-κB signaling may improve the efficacy of BET inhibition in patients with advanced uveal melanoma. SIGNIFICANCE: These findings provide evidence that inhibitors of NF-κB signaling synergize with BET inhibition in in vitro and in vivo models, suggesting a clinical utility of these targeted therapies in patients with uveal melanoma.

Tissue-Specific Analysis of Pharmacological Pathways.

Understanding the downstream consequences of pharmacologically targeted proteins is essential to drug design. Current approaches investigate molecular effects under tissue-naïve assumptions. Many target proteins, however, have tissue-specific expression. A systematic study connecting drugs to target pathways in in vivo human tissues is needed. We introduced a data-driven method that integrates drug-target relationships with gene expression, protein-protein interaction, and pathway annotation data. We applied our method to four independent genomewide expression datasets and built 467,396 connections between 1,034 drugs and 954 pathways in 259 human tissues or cell lines. We validated our results using data from L1000 and Pharmacogenomics Knowledgebase (PharmGKB), and observed high precision and recall. We predicted and tested anticoagulant effects of 22 compounds experimentally that were previously unknown, and used clinical data to validate these effects retrospectively. Our systematic study provides a better understanding of the cellular response to drugs and can be applied to many research topics in systems pharmacology.

Identification of Fluorescent Small Molecule Compounds for Synaptic Labeling by Image-Based, High-Content Screening.

Few tools are available for noninvasive imaging of synapses in the living mammalian brain. Current paradigms require the use of genetically modified mice or viral delivery of genetic material to the brain. To develop an alternative chemical approach, utilizing the recognition of synaptic components by organic small molecules, we designed an imaging-based, high-content screen in cultured cortical neurons to identify molecules based on their colocalization with fluorescently tagged synaptic proteins. We used this approach to screen a library of ∼7000 novel fluorescent dyes, and identified a series of compounds in the xanthone family that exhibited consistent synaptic labeling. Follow-up studies with one of these compounds, CX-G3, demonstrated its ability to label acidic organelles and in particular synaptic vesicles at glutamatergic synapses in cultured neurons and murine brain tissue, indicating the potential of this screening approach to identify promising lead compounds for use as synaptic markers, sensors, and targeting devices.

A precision oncology approach to the pharmacological targeting of mechanistic dependencies in neuroendocrine tumors.

We introduce and validate a new precision oncology framework for the systematic prioritization of drugs targeting mechanistic tumor dependencies in individual patients. Compounds are prioritized on the basis of their ability to invert the concerted activity of master regulator proteins that mechanistically regulate tumor cell state, as assessed from systematic drug perturbation assays. We validated the approach on a cohort of 212 gastroenteropancreatic neuroendocrine tumors (GEP-NETs), a rare malignancy originating in the pancreas and gastrointestinal tract. The analysis identified several master regulator proteins, including key regulators of neuroendocrine lineage progenitor state and immunoevasion, whose role as critical tumor dependencies was experimentally confirmed. Transcriptome analysis of GEP-NET-derived cells, perturbed with a library of 107 compounds, identified the HDAC class I inhibitor entinostat as a potent inhibitor of master regulator activity for 42% of metastatic GEP-NET patients, abrogating tumor growth in vivo. This approach may thus complement current efforts in precision oncology.

PLATE-Seq for genome-wide regulatory network analysis of high-throughput screens.

Pharmacological and functional genomic screens play an essential role in the discovery and characterization of therapeutic targets and associated pharmacological inhibitors. Although these screens affect thousands of gene products, the typical readout is based on low complexity rather than genome-wide assays. To address this limitation, we introduce pooled library amplification for transcriptome expression (PLATE-Seq), a low-cost, genome-wide mRNA profiling methodology specifically designed to complement high-throughput screening assays. Introduction of sample-specific barcodes during reverse transcription supports pooled library construction and low-depth sequencing that is 10- to 20-fold less expensive than conventional RNA-Seq. The use of network-based algorithms to infer protein activity from PLATE-Seq data results in comparable reproducibility to 30 M read sequencing. Indeed, PLATE-Seq reproducibility compares favorably to other large-scale perturbational profiling studies such as the connectivity map and library of integrated network-based cellular signatures.Despite the importance of pharmacological and functional genomic screens the readouts are of low complexity. Here the authors introduce PLATE-Seq, a low-cost genome-wide mRNA profiling method to complement high-throughput screening.

PI3Kγ/δ and NOTCH1 Cross-Regulate Pathways That Define the T-cell Acute Lymphoblastic Leukemia Disease Signature.

PI3K/AKT and NOTCH1 signaling pathways are frequently dysregulated in T-cell acute lymphoblastic leukemias (T-ALL). Although we have shown that the combined activities of the class I PI3K isoforms p110γ and p110δ play a major role in the development and progression of PTEN-null T-ALL, it has yet to be determined whether their contribution to leukemogenic programing is unique from that associated with NOTCH1 activation. Using an Lmo2-driven mouse model of T-ALL in which both the PI3K/AKT and NOTCH1 pathways are aberrantly upregulated, we now demonstrate that the combined activities of PI3Kγ/δ have both overlapping and distinct roles from NOTCH1 in generating T-ALL disease signature and in promoting tumor cell growth. Treatment of diseased animals with either a dual PI3Kγ/δ or a γ-secretase inhibitor reduced tumor burden, prolonged survival, and induced proapoptotic pathways. Consistent with their similar biological effects, both inhibitors downregulated genes involved in cMYC-dependent metabolism in gene set enrichment analyses. Furthermore, overexpression of cMYC in mice or T-ALL cell lines conferred resistance to both inhibitors, suggesting a point of pathway convergence. Of note, interrogation of transcriptional regulators and analysis of mitochondrial function showed that PI3Kγ/δ activity played a greater role in supporting the disease signature and critical bioenergetic pathways. Results provide insight into the interrelationship between T-ALL oncogenic networks and the therapeutic efficacy of dual PI3Kγ/δ inhibition in the context of NOTCH1 and cMYC signaling. Mol Cancer Ther; 16(10); 2069-82. ©2017 AACR.