A molecular cascade modulates MAP1B and confers resistance to mTOR inhibition in human glioblastoma.

Background: Clinical trials of therapies directed against nodes of the signaling axis of phosphatidylinositol-3 kinase/Akt/mammalian target of rapamycin (mTOR) in glioblastoma (GBM) have had disappointing results. Resistance to mTOR inhibitors limits their efficacy. Methods: To determine mechanisms of resistance to chronic mTOR inhibition, we performed tandem screens on patient-derived GBM cultures. Results: An unbiased phosphoproteomic screen quantified phosphorylation changes associated with chronic exposure to the mTOR inhibitor rapamycin, and our analysis implicated a role for glycogen synthase kinase (GSK)3B attenuation in mediating resistance that was confirmed by functional studies. A targeted short hairpin RNA screen and further functional studies both in vitro and in vivo demonstrated that microtubule-associated protein (MAP)1B, previously associated predominantly with neurons, is a downstream effector of GSK3B-mediated resistance. Furthermore, we provide evidence that chronic rapamycin induces microtubule stability in a MAP1B-dependent manner in GBM cells. Additional experiments explicate a signaling pathway wherein combinatorial extracellular signal-regulated kinase (ERK)/mTOR targeting abrogates inhibitory phosphorylation of GSK3B, leads to phosphorylation of MAP1B, and confers sensitization. Conclusions: These data portray a compensatory molecular signaling network that imparts resistance to chronic mTOR inhibition in primary, human GBM cell cultures and points toward new therapeutic strategies.

Identification of an Efficient Gene Expression Panel for Glioblastoma Classification.

We present here a novel genetic algorithm-based random forest (GARF) modeling technique that enables a reduction in the complexity of large gene disease signatures to highly accurate, greatly simplified gene panels. When applied to 803 glioblastoma multiforme samples, this method allowed the 840-gene Verhaak et al. gene panel (the standard in the field) to be reduced to a 48-gene classifier, while retaining 90.91% classification accuracy, and outperforming the best available alternative methods. Additionally, using this approach we produced a 32-gene panel which allows for better consistency between RNA-seq and microarray-based classifications, improving cross-platform classification retention from 69.67% to 86.07%. A webpage producing these classifications is available at http://simplegbm.semel.ucla.edu.

Inhibition of Nucleotide Synthesis Targets Brain Tumor Stem Cells in a Subset of Glioblastoma.

Inhibition of both the de novo (DNP) and salvage (NSP) pathways of nucleoside synthesis has been demonstrated to impair leukemia cells. We endeavored to determine whether this approach would be efficacious in glioblastoma. To diminish nucleoside biosynthesis, we utilized compound DI-39, which selectively targets NSP, in combination with thymidine (dT), which selectively targets DNP. We employed in vitro and ex vivo models to determine the effects of pretreatment with dT + DI-39 on brain tumor stem cells (BTSC). Here, we demonstrate that this combinatorial therapy elicits a differential response across a spectrum of human patient-derived glioblastoma cultures. As determined by apoptotic markers, most cultures were relatively resistant to treatment, although a subset was highly sensitive. Sensitivity was unrelated to S-phase delay and to DNA damage induced by treatment. Bioinformatics analysis indicated that response across cultures was associated with the transcription factor PAX3 (associated with resistance) and with canonical pathways, including the nucleotide excision repair pathway, PTEN (associated with resistance), PI3K/AKT (associated with sensitivity), and ErbB2-ErbB3. Our in vitro assays demonstrated that, in sensitive cultures, clonal sphere formation was reduced upon removal from pretreatment. In contrast, in a resistant culture, clonal sphere formation was slightly increased upon removal from pretreatment. Moreover, in an intracranial xenograft model, pretreatment of a sensitive culture caused significantly smaller and fewer tumors. In a resistant culture, tumors were equivalent irrespective of pretreatment. These results indicate that, in the subset of sensitive glioblastoma, BTSCs are targeted by inhibition of pyrimidine synthesis. Mol Cancer Ther; 15(6); 1271-8. ©2016 AACR.

Large-scale assessment of the gliomasphere model system.

BACKGROUND: Gliomasphere cultures are widely utilized for the study of glioblastoma (GBM). However, this model system is not well characterized, and the utility of current classification methods is not clear. METHODS: We used 71 gliomasphere cultures from 68 individuals. Using gene expression-based classification, we performed unsupervised clustering and associated gene expression with gliomasphere phenotypes and patient survival. RESULTS: Some aspects of the gene expression-based classification method were robust because the gliomasphere cultures retained their classification over many passages, and IDH1 mutant gliomaspheres were all proneural. While gene expression of a subset of gliomasphere cultures was more like the parent tumor than any other tumor, gliomaspheres did not always harbor the same classification as their parent tumor. Classification was not associated with whether a sphere culture was derived from primary or recurrent GBM or associated with the presence of EGFR amplification or rearrangement. Unsupervised clustering of gliomasphere gene expression distinguished 2 general categories (mesenchymal and nonmesenchymal), while multidimensional scaling distinguished 3 main groups and a fourth minor group. Unbiased approaches revealed that PI3Kinase, protein kinase A, mTOR, ERK, Integrin, and beta-catenin pathways were associated with in vitro measures of proliferation and sphere formation. Associating gene expression with gliomasphere phenotypes and patient outcome, we identified genes not previously associated with GBM: PTGR1, which suppresses proliferation, and EFEMP2 and LGALS8, which promote cell proliferation. CONCLUSIONS: This comprehensive assessment reveals advantages and limitations of using gliomaspheres to model GBM biology, and provides a novel strategy for selecting genes for future study.

Cysteine scanning mutagenesis of transmembrane helix 3 of a brain glutamate transporter reveals two conformationally sensitive positions.

Glutamate transporters in the brain remove the neurotransmitter from the synapse by cotransport with three sodium ions into the surrounding cells. Recent structural work on an archaeal homolog suggests that, during substrate translocation, the transport domain, including the peripheral transmembrane helix 3 (TM3), moves relative to the trimerization domain in an elevator-like process. Moreover, two TM3 residues have been proposed to form part of a transient Na3' site, and another, Tyr-124, appears close to both Na3' and Na1. To obtain independent evidence for the role of TM3 in glutamate transport, each of its 31 amino acid residues from the glial GLT-1 transporter was individually mutated to cysteine. Except for six mutants, substantial transport activity was detected. Aqueous accessibility of the introduced cysteines was probed with membrane-permeant and membrane-impermeant sulfhydryl reagents under a variety of conditions. Transport of six single cysteine mutants, all located on the intracellular side of TM3, was affected by membrane-permeant sulfhydryl reagents. However, only at two positions could ligands modulate the reactivity. A120C reactivity was diminished under conditions expected to favor the outward-facing conformation of the transporter. Sulfhydryl modification of Y124C by 2-aminoethyl methanethiosulfonate, but not by N-ethylmaleimide, was fully protected in the presence of sodium. Our data are consistent with the idea that TM3 moves during transport. Moreover, computational modeling indicated that electrostatic repulsion between the positive charge introduced at position 124 and the sodium ions bound at Na3' and Na1 underlies the protection by sodium.

Inward-facing conformation of glutamate transporters as revealed by their inverted-topology structural repeats.

Glutamate transporters regulate synaptic concentrations of this neurotransmitter by coupling its flux to that of sodium and other cations. Available crystal structures of an archeal homologue of these transporters, GltPh, resemble an extracellular-facing state, in which the bound substrate is occluded only by a small helical hairpin segment called HP2. However, a pathway to the cytoplasmic side of the membrane is not clearly apparent. We previously modeled an alternate state of a transporter from the neurotransmitter:sodium symporter family, which has an entirely different fold, solely on the presence of inverted-topology structural repeats. In GltPh, we identified two distinct sets of inverted-topology repeats and used these repeats to model an inward-facing conformation of the protein. To test this model, we introduced pairs of cysteines into the neuronal glutamate transporter EAAC1, at positions that are >27 A apart in the crystal structures of GltPh, but approximately = 10 A apart in the inward-facing model. Transport by these mutants was activated by pretreatment with the reducing agent dithithreitol. Subsequent treatment with the oxidizing agent copper(II)(1,10-phenantroline)(3) abolished this activation. The inhibition of transport was potentiated under conditions thought to promote the inward-facing conformation of the transporter. By contrast, the inhibition was reduced in the presence of the nontransportable substrate analogue D,L-threo-beta-benzyloxyaspartate, which favors the outward-facing conformation. Other conformation-sensitive accessibility measurements are also accommodated by our inward-facing model. These results suggest that the inclusion of inverted-topology repeats in transporters may provide a general solution to the requirement for two symmetry-related states in a single protein.

Ligand-target interaction-based weighting of substructures for virtual screening.

A methodology is introduced to assign energy-based scores to two-dimensional (2D) structural features based on three-dimensional (3D) ligand-target interaction information and utilize interaction-annotated features in virtual screening. Database molecules containing such fragments are assigned cumulative scores that serve as a measure of similarity to active reference compounds. The Interaction Annotated Structural Features (IASF) method is applied to mine five high-throughput screening (HTS) data sets and often identifies more hits than conventional fragment-based similarity searching or ligand-protein docking.

Which aspects of HTS are empirically correlated with downstream success?

High-throughput screening (HTS) is a well-established hit-finding approach used in the pharmaceutical industry. In this article, recent experience at Novartis with respect to factors influencing the success of HTS campaigns is discussed. An inherent measure of HTS quality could be defined by the assay Z and Z' factors, the number of hits and their biological potencies; however, such measures of quality do not always correlate with the advancement of hits to the later stages of drug discovery. Also, for many target classes, such as kinases, it is easy to identify hits, but, as a result of selectivity, intellectual property and other issues, the projects do not result in lead declarations. In this article, HTS success is defined as the fraction of HTS campaigns that advance into the later stages of drug discovery, and the major influencing factors are examined. Interestingly, screening compounds in individual wells or in mixtures did not have a major impact on the HTS success and, equally interesting, there was no difference in the progression rates of biochemical and cell-based assays. Particular target types, assay technologies, structure-activity relationships and powder availability had a much greater impact on success as defined above. In addition, significant mutual dependencies can be observed - while one assay format works well with one target type, this situation might be completely reversed for a combination of the same readout technology with a different target type. The results and opinions presented here should be regarded as groundwork, and a plethora of factors that influence the fate of a project, such as biophysical measurements, chemical attractiveness of the hits, strategic reasons and safety pharmacology, are not covered here. Nonetheless, it is hoped that this information will be used industry-wide to improve success rates in terms of hits progressing into exploratory chemistry and beyond. The support that can be obtained from new in silico approaches to phase transitions are also described, along with the gaps they are designed to fill.

"Virtual fragment linking": an approach to identify potent binders from low affinity fragment hits.

In this work we explore the possibilities of using fragment-based screening data to prioritize compounds from a full HTS library, a method we call virtual fragment linking (VFL). The ability of VFL to identify compounds of nanomolar potency based on micromolar fragment binding data was tested on 75 target classes from the WOMBAT database and succeeded in 57 cases. Further, the method was demonstrated for seven drug targets from in-house screening programs that performed both FBS of 8800 fragments and screens of the full library. VFL captured between 28% and 67% of the hits (IC 50 < 10microM) in the top 5% of the ranked library for four of the targets (enrichment between 5-fold and 13-fold). Our findings lead us to conclude that proper coverage of chemical space by the fragment library is crucial for the VFL methodology to be successful in prioritizing HTS libraries from fragment-based screening data.

Understanding false positives in reporter gene assays: in silico chemogenomics approaches to prioritize cell-based HTS data.

High throughput screening (HTS) data is often noisy, containing both false positives and negatives. Thus, careful triaging and prioritization of the primary hit list can save time and money by identifying potential false positives before incurring the expense of followup. Of particular concern are cell-based reporter gene assays (RGAs) where the number of hits may be prohibitively high to be scrutinized manually for weeding out erroneous data. Based on statistical models built from chemical structures of 650 000 compounds tested in RGAs, we created "frequent hitter" models that make it possible to prioritize potential false positives. Furthermore, we followed up the frequent hitter evaluation with chemical structure based in silico target predictions to hypothesize a mechanism for the observed "off target" response. It was observed that the predicted cellular targets for the frequent hitters were known to be associated with undesirable effects such as cytotoxicity. More specifically, the most frequently predicted targets relate to apoptosis and cell differentiation, including kinases, topoisomerases, and protein phosphatases. The mechanism-based frequent hitter hypothesis was tested using 160 additional druglike compounds predicted by the model to be nonspecific actives in RGAs. This validation was successful (showing a 50% hit rate compared to a normal hit rate as low as 2%), and it demonstrates the power of computational models toward understanding complex relations between chemical structure and biological function.

"Plate cherry picking": a novel semi-sequential screening paradigm for cheaper, faster, information-rich compound selection.

This work describes a novel semi-sequential technique for in silico enhancement of high-throughput screening (HTS) experiments now employed at Novartis. It is used in situations in which the size of the screen is limited by the readout (e.g., high-content screens) or the amount of reagents or tools (proteins or cells) available. By performing computational chemical diversity selection on a per plate basis (instead of a per compound basis), 25% of the 1,000,000-compound screening was optimized for general initial HTS. Statistical models are then generated from target-specific primary results (percentage inhibition data) to drive the cherry picking and testing from the entire collection. Using retrospective analysis of 11 HTS campaigns, the authors show that this method would have captured on average two thirds of the active compounds (IC(50) < 10 microM) and three fourths of the active Murcko scaffolds while decreasing screening expenditure by nearly 75%. This result is true for a wide variety of targets, including G-protein-coupled receptors, chemokine receptors, kinases, metalloproteinases, pathway screens, and protein-protein interactions. Unlike time-consuming "classic" sequential approaches that require multiple iterations of cherry picking, testing, and building statistical models, here individual compounds are cherry picked just once, based directly on primary screening data. Strikingly, the authors demonstrate that models built from primary data are as robust as models built from IC(50) data. This is true for all HTS campaigns analyzed, which represent a wide variety of target classes and assay types.