Charles Karan

A community computational challenge to predict the activity of pairs of compounds

Recent therapeutic successes have renewed interest in drug combinations, but experimental screening approaches are costly and often identify only small numbers of synergistic combinations. The DREAM consortium launched an open challenge to foster the development of in silico methods to computationally rank 91 compound pairs, from the most synergistic to the most antagonistic, based on gene-expression profiles of human B cells treated with individual compounds at multiple time points and concentrations. Using scoring metrics based on experimental dose-response curves, we assessed 32 methods (31 community-generated approaches and SynGen), four of which performed significantly better than random guessing. We highlight similarities between the methods. Although the accuracy of predictions was not optimal, we find that computational prediction of compound-pair activity is possible, and that community challenges can be useful to advance the field of in silico compound-synergy prediction.

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.

Preclinical Pharmacologic Evaluation of Pralatrexate and Romidepsin Confirms Potent Synergy of the Combination in a Murine Model of Human T-cell Lymphoma

Purpose: T-cell lymphomas (TCL) are aggressive diseases, which carry a poor prognosis. The emergence of new drugs for TCL has created a need to survey these agents in a rapid and reproducible fashion, to prioritize combinations which should be prioritized for clinical study. Mouse models of TCL that can be used for screening novel agents and their combinations are lacking. Developments in noninvasive imaging modalities, such as surface bioluminescence (SBL) and three-dimensional ultrasound (3D-US), are challenging conventional approaches in xenograft modeling relying on caliper measurements. The recent approval of pralatrexate and romidepsin creates an obvious combination that could produce meaningful activity in TCL, which is yet to be studied in combination. Experimental Design: High-throughput screening and multimodality imaging approach of SBL and 3D-US in a xenograft NOG mouse model of TCL were used to explore the in vitro and in vivo activity of pralatrexate and romidepsin in combination. Corresponding mass spectrometry–based pharmacokinetic and immunohistochemistry-based pharmacodynamic analyses of xenograft tumors were performed to better understand a mechanistic basis for the drug:drug interaction. Results: In vitro, pralatrexate and romidepsin exhibited concentration-dependent synergism in combination against a panel of TCL cell lines. In a NOG murine model of TCL, the combination of pralatrexate and romidepsin exhibited enhanced efficacy compared with either drug alone across a spectrum of tumors using complementary imaging modalities, such as SBL and 3D-US. Conclusions: Collectively, these data strongly suggest that the combination of pralatrexate and romidepsin merits clinical study in patients with TCLs. Clin Cancer Res; 21(9); 2096–106. ©2015 AACR.

Convection-enhanced delivery of etoposide is effective against murine proneural glioblastoma

BACKGROUND Glioblastoma subtypes have been defined based on transcriptional profiling, yet personalized care based on molecular classification remains unexploited. Topoisomerase II (TOP2) contributes to the transcriptional signature of the proneural glioma subtype. Thus, we targeted TOP2 pharmacologically with etoposide in proneural glioma models. METHODS TOP2 gene expression was evaluated in mouse platelet derived growth factor (PDGF)(+)phosphatase and tensin homolog (PTEN)(-/-)p53(-/-) and PDGF(+)PTEN(-/-) proneural gliomas and cell lines, as well as human glioblastoma from The Cancer Genome Atlas. Correlation between TOP2 transcript levels and etoposide susceptibility was investigated in 139 human cancer cell lines from the Cancer Cell Line Encyclopedia public dataset and in mouse proneural glioma cell lines. Convection-enhanced delivery (CED) of etoposide was tested on cell-based PDGF(+)PTEN(-/-)p53(-/-) and retroviral-based PDGF(+)PTEN(-/-) mouse proneural glioma models. RESULTS TOP2 expression was significantly higher in human proneural glioblastoma and in mouse proneural tumors at early as well as late stages of development compared with normal brain. TOP2B transcript correlated with susceptibility to etoposide in mouse proneural cell lines and in 139 human cancer cell lines from the Cancer Cell Line Encyclopedia. Intracranial etoposide CED treatment (680 μM) was well tolerated by mice and led to a significant survival benefit in the PDGF(+)PTEN(-/-)p53(-/-) glioma model. Moreover, etoposide CED treatment at 80 μM but not 4 μM led to a significant survival advantage in the PDGF(+)PTEN(-/-) glioma model. CONCLUSIONS TOP2 is highly expressed in proneural gliomas, rendering its pharmacological targeting by intratumoral administration of etoposide by CED effective on murine proneural gliomas. We provide evidence supporting clinical testing of CED of etoposide with a molecular-based patient selection approach.

RABiT-II: Implementation of a High-Throughput Micronucleus Biodosimetry Assay on Commercial Biotech Robotic Systems

We demonstrate the use of high-throughput biodosimetry platforms based on commercial high-throughput/high-content screening robotic systems. The cytokinesis-block micronucleus (CBMN) assay, using only 20 μl whole blood from a fingerstick, was implemented on a PerkinElmer cell::explorer and General Electric IN Cell Analyzer 2000. On average 500 binucleated cells per sample were detected by our FluorQuantMN software. A calibration curve was generated in the radiation dose range up to 5.0 Gy using the data from 8 donors and 48,083 binucleated cells in total. The study described here demonstrates that high-throughput radiation biodosimetry is practical using current commercial high-throughput/high-content screening robotic systems, which can be readily programmed to perform and analyze robotics-optimized cytogenetic assays. Application to other commercial high-throughput/high-content screening systems beyond the ones used in this study is clearly practical. This approach will allow much wider access to high-throughput biodosimetric screening for large-scale radiological incidents than is currently available.

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.

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.

A novel, rapid method to compare the therapeutic windows of oral anticoagulants using the Hill coefficient.

A central challenge in designing and administering effective anticoagulants is achieving the proper therapeutic window and dosage for each patient. The Hill coefficient, nH, which measures the steepness of a dose-response relationship, may be a useful gauge of this therapeutic window. We sought to measure the Hill coefficient of available anticoagulants to gain insight into their therapeutic windows. We used a simple fluorometric in vitro assay to determine clotting activity in platelet poor plasma after exposure to various concentrations of anticoagulants. The Hill coefficient for argatroban was the lowest, at 1.7 ± 0.2 (95% confidence interval, CI), and the Hill coefficient for fondaparinux was the highest, at 4.5 ± 1.3 (95% CI). Thus, doubling the dose of fondaparinux from its IC50 would decrease coagulation activity by nearly a half, whereas doubling the dose of argatroban from its IC50 would decrease coagulation activity by merely one quarter. These results show a significant variation among the Hill coefficients, suggesting a similar variation in therapeutic windows among anticoagulants in our assay.