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

TSH RECEPTOR SIGNALING ABROGATION BY A NOVEL SMALL MOLECULE

Pathological activation of the thyroid stimulating hormone receptor (TSHR) is caused by thyroid stimulating antibodies in patients with Graves’ disease or by somatic and rare genomic mutations that enhance constitutive activation of the receptor influencing both G protein and non-G protein signaling. Potential selective small molecule antagonists represent novel therapeutic compounds for abrogation of such abnormal TSHR signaling. In this study we describe the identification and in-vitro characterization of a novel small molecule antagonist by high-throughput screening (HTS). The identification of the TSHR antagonist was performed using a transcription-based TSH inhibition bioassay. TSHR expressing CHO cells which also expressed a luciferase tagged CRE response element were optimized using bovine TSH as the activator in a 384 well plate format which had a Z score of 0.3-0.6. Using this HTS assay we screened a diverse library of ~80,000 compounds at a final concentration of 16.7μM. The selection criteria for a positive hit were based on a mean signal threshold of 50% inhibition of control TSH stimulation. The screening resulted in 450 positive hits giving a hit ratio of 0.56%. A secondary confirmation screen against TSH and forskolin - a post receptor activator of adenylyl cyclase – confirmed one TSHR-specific candidate antagonist molecule (named VA-K-14). This lead molecule had an IC50 of 12.3µM and a unique chemical structure. A parallel analysis for cell viability indicated that the lead inhibitor was non-cytotoxic at its effective concentrations. In-silico docking studies performed using a TSHR transmembrane model showed the hydrophobic contact locations and the possible mode of inhibition of TSHR signaling. Furthermore, this molecule was capable of inhibiting TSHR stimulation by Graves’ disease patient sera and monoclonal stimulating TSHR antibodies.In conclusion, we report the identification of a novel small molecule TSHR inhibitor which has the potential to be developed as a therapeutic antagonist for abrogation of TSHR signaling by TSHR autoantibodies in Graves’ disease

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

Targeted Knockdown of GDCH in Rice Leads to a Photorespiratory-Deficient Phenotype Useful as a Building Block for C4 Rice

The glycine decarboxylase complex (GDC) plays a critical role in the photorespiratory C2 cycle of C3 species by recovering carbon following the oxygenation reaction of ribulose-1,5-bisphosphate carboxylase/oxygenase. Loss of GDC from mesophyll cells (MCs) is considered a key early step in the evolution of C4 photosynthesis. To assess the impact of preferentially reducing GDC in rice MCs, we decreased the abundance of OsGDCH (Os10g37180) using an artificial microRNA (amiRNA) driven by a promoter that preferentially drives expression in MCs. GDC H- and P-proteins were undetectable in leaves of gdch lines. Plants exhibited a photorespiratory-deficient phenotype with stunted growth, accelerated leaf senescence, reduced chlorophyll, soluble protein and sugars, and increased glycine accumulation in leaves. Gas exchange measurements indicated an impaired ability to regenerate ribulose 1,5-bisphosphate in photorespiratory conditions. In addition, MCs of gdch lines exhibited a significant reduction in chloroplast area and coverage of the cell wall when grown in air, traits that occur during the later stages of C4 evolution. The presence of these two traits important for C4 photosynthesis and the non-lethal, down-regulation of the photorespiratory C2 cycle positively contribute to efforts to produce a C4 rice prototype

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

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

© 2018 The Author(s). 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

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