Glioblastoma and the search for non-hypothesis driven combination therapeutics in academia

Glioblastoma (GBM) remains a cancer of high unmet clinical need. Current standard of care for GBM, consisting of maximal surgical resection, followed by ionisation radiation (IR) plus concomitant and adjuvant temozolomide (TMZ), provides less than 15-month survival benefit. Efforts by conventional drug discovery to improve overall survival have failed to overcome challenges presented by inherent tumor heterogeneity, therapeutic resistance attributed to GBM stem cells, and tumor niches supporting self-renewal. In this review we describe the steps academic researchers are taking to address these limitations in high throughput screening programs to identify novel GBM combinatorial targets. We detail how they are implementing more physiologically relevant phenotypic assays which better recapitulate key areas of disease biology coupled with more focussed libraries of small compounds, such as drug repurposing, target discovery, pharmacologically active and novel, more comprehensive anti-cancer target-annotated compound libraries. Herein, we discuss the rationale for current GBM combination trials and the need for more systematic and transparent strategies for identification, validation and prioritisation of combinations that lead to clinical trials. Finally, we make specific recommendations to the preclinical, small compound screening paradigm that could increase the likelihood of identifying tractable, combinatorial, small molecule inhibitors and better drug targets specific to GBM.Peer reviewe

Chemogenomic library design strategies for precision oncology, applied to phenotypic profiling of glioblastoma patient cells

Summary: Designing a targeted screening library of bioactive small molecules is a challenging task since most compounds modulate their effects through multiple protein targets with varying degrees of potency and selectivity. We implemented analytic procedures for designing anticancer compound libraries adjusted for library size, cellular activity, chemical diversity and availability, and target selectivity. The resulting compound collections cover a wide range of protein targets and biological pathways implicated in various cancers, making them widely applicable to precision oncology. We characterized the compound and target spaces of the virtual libraries, in comparison with a minimal screening library of 1,211 compounds for targeting 1,386 anticancer proteins. In a pilot screening study, we identified patient-specific vulnerabilities by imaging glioma stem cells from patients with glioblastoma (GBM), using a physical library of 789 compounds that cover 1,320 of the anticancer targets. The cell survival profiling revealed highly heterogeneous phenotypic responses across the patients and GBM subtypes

Glioblastoma and the search for non-hypothesis driven combination therapeutics in academia

Glioblastoma (GBM) remains a cancer of high unmet clinical need. Current standard of care for GBM, consisting of maximal surgical resection, followed by ionisation radiation (IR) plus concomitant and adjuvant temozolomide (TMZ), provides less than 15-month survival benefit. Efforts by conventional drug discovery to improve overall survival have failed to overcome challenges presented by inherent tumor heterogeneity, therapeutic resistance attributed to GBM stem cells, and tumor niches supporting self-renewal. In this review we describe the steps academic researchers are taking to address these limitations in high throughput screening programs to identify novel GBM combinatorial targets. We detail how they are implementing more physiologically relevant phenotypic assays which better recapitulate key areas of disease biology coupled with more focussed libraries of small compounds, such as drug repurposing, target discovery, pharmacologically active and novel, more comprehensive anti-cancer target-annotated compound libraries. Herein, we discuss the rationale for current GBM combination trials and the need for more systematic and transparent strategies for identification, validation and prioritisation of combinations that lead to clinical trials. Finally, we make specific recommendations to the preclinical, small compound screening paradigm that could increase the likelihood of identifying tractable, combinatorial, small molecule inhibitors and better drug targets specific to GBM

Evenness mediates the global relationship between forest productivity and richness

1. Biodiversity is an important component of natural ecosystems, with higher species richness often correlating with an increase in ecosystem productivity. Yet, this relationship varies substantially across environments, typically becoming less pronounced at high levels of species richness. However, species richness alone cannot reflect all important properties of a community, including community evenness, which may mediate the relationship between biodiversity and productivity. If the evenness of a community correlates negatively with richness across forests globally, then a greater number of species may not always increase overall diversity and productivity of the system. Theoretical work and local empirical studies have shown that the effect of evenness on ecosystem functioning may be especially strong at high richness levels, yet the consistency of this remains untested at a global scale. 2. Here, we used a dataset of forests from across the globe, which includes composition, biomass accumulation and net primary productivity, to explore whether productivity correlates with community evenness and richness in a way that evenness appears to buffer the effect of richness. Specifically, we evaluated whether low levels of evenness in speciose communities correlate with the attenuation of the richness–productivity relationship. 3. We found that tree species richness and evenness are negatively correlated across forests globally, with highly speciose forests typically comprising a few dominant and many rare species. Furthermore, we found that the correlation between diversity and productivity changes with evenness: at low richness, uneven communities are more productive, while at high richness, even communities are more productive. 4. Synthesis. Collectively, these results demonstrate that evenness is an integral component of the relationship between biodiversity and productivity, and that the attenuating effect of richness on forest productivity might be partly explained by low evenness in speciose communities. Productivity generally increases with species richness, until reduced evenness limits the overall increases in community diversity. Our research suggests that evenness is a fundamental component of biodiversity–ecosystem function relationships, and is of critical importance for guiding conservation and sustainable ecosystem management decisions

Evenness mediates the global relationship between forest productivity and richness

1. Biodiversity is an important component of natural ecosystems, with higher species richness often correlating with an increase in ecosystem productivity. Yet, this relationship varies substantially across environments, typically becoming less pronounced at high levels of species richness. However, species richness alone cannot reflect all important properties of a community, including community evenness, which may mediate the relationship between biodiversity and productivity. If the evenness of a community correlates negatively with richness across forests globally, then a greater number of species may not always increase overall diversity and productivity of the system. Theoretical work and local empirical studies have shown that the effect of evenness on ecosystem functioning may be especially strong at high richness levels, yet the consistency of this remains untested at a global scale. 2. Here, we used a dataset of forests from across the globe, which includes composition, biomass accumulation and net primary productivity, to explore whether productivity correlates with community evenness and richness in a way that evenness appears to buffer the effect of richness. Specifically, we evaluated whether low levels of evenness in speciose communities correlate with the attenuation of the richness–productivity relationship. 3. We found that tree species richness and evenness are negatively correlated across forests globally, with highly speciose forests typically comprising a few dominant and many rare species. Furthermore, we found that the correlation between diversity and productivity changes with evenness: at low richness, uneven communities are more productive, while at high richness, even communities are more productive. 4. Synthesis. Collectively, these results demonstrate that evenness is an integral component of the relationship between biodiversity and productivity, and that the attenuating effect of richness on forest productivity might be partly explained by low evenness in speciose communities. Productivity generally increases with species richness, until reduced evenness limits the overall increases in community diversity. Our research suggests that evenness is a fundamental component of biodiversity–ecosystem function relationships, and is of critical importance for guiding conservation and sustainable ecosystem management decisions

Evenness mediates the global relationship between forest productivity and richness

Biodiversity is an important component of natural ecosystems, with higher species richness often correlating with an increase in ecosystem productivity. Yet, this relationship varies substantially across environments, typically becoming less pronounced at high levels of species richness. However, species richness alone cannot reflect all important properties of a community, including community evenness, which may mediate the relationship between biodiversity and productivity. If the evenness of a community correlates negatively with richness across forests globally, then a greater number of species may not always increase overall diversity and productivity of the system. Theoretical work and local empirical studies have shown that the effect of evenness on ecosystem functioning may be especially strong at high richness levels, yet the consistency of this remains untested at a global scale. 2. Here, we used a dataset of forests from across the globe, which includes composition, biomass accumulation and net primary productivity, to explore whether productivity correlates with community evenness and richness in a way that evenness appears to buffer the effect of richness. Specifically, we evaluated whether low levels of evenness in speciose communities correlate with the attenuation of the richness–productivity relationship. 3. We found that tree species richness and evenness are negatively correlated across forests globally, with highly speciose forests typically comprising a few dominant and many rare species. Furthermore, we found that the correlation between diversity and productivity changes with evenness: at low richness, uneven communities are more productive, while at high richness, even communities are more productive. 4. Synthesis. Collectively, these results demonstrate that evenness is an integral component of the relationship between biodiversity and productivity, and that the attenuating effect of richness on forest productivity might be partly explained by low evenness in speciose communities. Productivity generally increases with species richness, until reduced evenness limits the overall increases in community diversity. Our research suggests that evenness is a fundamental component of biodiversity–ecosystem function relationships, and is of critical importance for guiding conservation and sustainable ecosystem management decisions. © 2023 The Authors. Journal of Ecology published by John Wiley & Sons Ltd on behalf of British Ecological Society

The Role of metals and Aβ in excitotoxicity and Alzheimer’s disease

© 2015 Dr. Timothy JohanssenBackground: N-methyl-d-aspartate receptors (NMDARs) are ionotropic channels gated by the excitatory amino acid, glutamate. They play an essential role in synaptic plasticity, enhancing synaptic signal strength through long-term potentiation (LTP), a process thought to underlie learning and memory. At the synapse, NMDARs mediate neuroprotective signaling pathways including the regulation of calcineurin activity and inhibition of glycogen synthase kinase (GSK3). Under pathological conditions the prolonged and enhanced exposure of NMDARs to glutamate results in an excessive flux of calcium (Ca2+) into the cell. This triggers a range of responses resulting in cell death, including increased oxidative stress, inappropriate activation of proteases such as calpain, dysregulation of Ca2+- related pathways, mitochondrial damage and an apoptotic cascade. This process, termed excitotoxicity, contributes significantly to the acute neurodegeneration in ischemia and traumatic brain injury (TBI) and is believed to underlie the chronic neurodegeneration in Huntington’s disease (HD) and more recently, Alzheimer’s disease (AD). Alzheimer’s disease (AD) is characterised by progressive cognitive impairment resulting from synaptic degeneration and neuronal loss. A proposed key event in its aetiology is the formation of oligomeric species of the beta amyloid (Aβ) peptide. Recent work has demonstrated that the soluble Aβ oligomers induce excessive calcium influx across the cell membrane resulting in neuronal death by excitotoxicity. It is believed these toxic species of Aβ oligmomerise in the synaptic cleft between neurons in the hippocampus due to high levels of zinc and copper. These metals are released upon NMDAR activity from the pre- and post-synapse, respectively and can bind Aβ, increasing its rate of oligomerisation. Subsequent excitotoxic interactions between Aβ and NMDARs are copper (Cu2+)-dependent. In contrast, Cu2+ is also neuroprotective against excitotoxicity demonstrating the crucial role of metal homeostasis in specific regions of the brain affected by neurodegenerative diseases. Objectives: This PhD project has sought to determine the contribution of metals in excitotoxicity and whether modulating their levels could provide a mechanism to protect against this form of cell death. As excitotoxicity is strongly implicated in the aetiology of Alzheimer’s disease subsequent research aimed to describe the involvement of excitotoxicity in Aβ-mediated cell death in cortical neural model and to establish whether metals played a necessary role in this process. The final goal of the research presented here was the development of a neural-based assay, which could be employed to screen various forms of Aβ to detect more toxic forms of the peptide. Results: In experiments with the metal chaperone PBT2, a therapeutic in clinical trials for chronic neurodegenerative diseases, neurons were protected against excitotoxic cell death by pretreatment with the drug. Subsequent experiments demonstrated that this was a metal-mediated effect that required zinc. Pretreatment with this drug induced preconditioning in neurons by moderate increases in intracellular levels of calcium that activated survival pathways and inhibited activation of calcineurin and GSK3 preventing cell death. In further investigations the parameters for Aβ-induced excitotoxicity in cortical neurons were determined. In the presence of non-toxic levels of glutamate, Aβ induced significant toxicity that was dependent on the presence of metals, as demonstrated by metal chelation. These findings translated to the development of a calcium flux assay, which provided a functional readout of Aβ toxicity. Finally, this assay was validated by screening species of Aβ with varied degrees of toxicity to neurons. Conclusions: This work highlights the importance of metals in neurodegenerative disease and demonstrates modulation of both Cu2+ and Zn2+ levels in hippocampal synapses provide valid targets for future therapeutic approaches by preventing the formation of toxic oligomeric species. A concurrent finding has iii been the identification of the parameters required for Aβ-induced excitotoxicity, which provides the tools to screen an array of both in vivo and in vitro Aβ species to determine their toxicity. This knowledge will enable targeted clearance of these forms of the Aβ peptide, which, along with therapies preventing oligomer formation, will show significant therapeutic affects in the treatment of Alzheimer’s Disease

Glioblastoma and the search for non-hypothesis driven combination therapeutics in academia

Glioblastoma (GBM) remains a cancer of high unmet clinical need. Current standard of care for GBM, consisting of maximal surgical resection, followed by ionisation radiation (IR) plus concomitant and adjuvant temozolomide (TMZ), provides less than 15-month survival benefit. Efforts by conventional drug discovery to improve overall survival have failed to overcome challenges presented by inherent tumor heterogeneity, therapeutic resistance attributed to GBM stem cells, and tumor niches supporting self-renewal. In this review we describe the steps academic researchers are taking to address these limitations in high throughput screening programs to identify novel GBM combinatorial targets. We detail how they are implementing more physiologically relevant phenotypic assays which better recapitulate key areas of disease biology coupled with more focussed libraries of small compounds, such as drug repurposing, target discovery, pharmacologically active and novel, more comprehensive anti-cancer target-annotated compound libraries. Herein, we discuss the rationale for current GBM combination trials and the need for more systematic and transparent strategies for identification, validation and prioritisation of combinations that lead to clinical trials. Finally, we make specific recommendations to the preclinical, small compound screening paradigm that could increase the likelihood of identifying tractable, combinatorial, small molecule inhibitors and better drug targets specific to GBM.Peer reviewe

Concentration dependent Cu2+ induced aggregation and dityrosine formation of the Alzheimer's disease amyloid-beta peptide.

The Amyloid beta peptide (Abeta) of Alzheimer's diseases (AD) is closely linked to the progressive cognitive decline associated with the disease. Cu2+ ions can induce the de novo aggregation of the Abeta peptide into non-amyloidogenic aggregates and the production of a toxic species. The mechanism by which Cu2+ mediates the change from amyloid material toward Cu2+ induced aggregates is poorly defined. Here we demonstrate that the aggregation state of Abeta1-42 at neutral pH is governed by the Cu2+:peptide molar ratio. By probing amyloid content and total aggregation, we observed a distinct Cu2+ switching effect centered at equimolar Cu2+:peptide ratios. At sub-equimolar Cu2+:peptide molar ratios, Abeta1-42 forms thioflavin-T reactive amyloid; conversely, at supra-equimolar Cu2+:peptide molar ratios, Abeta1-42 forms both small spherical oligomers approximately 10-20 nm in size and large amorphous aggregates. We demonstrate that these insoluble aggregates form spontaneously via a soluble species without the presence of an observable lag phase. In seeding experiments, the Cu2+ induced aggregates were unable to influence fibril formation or convert into fibrillar material. Aged Cu2+ induced aggregates are toxic when compared to Abeta1-42 aged in the absence of Cu2+. Importantly, the formation of dityrosine crosslinked Abeta, by the oxidative modification of the peptide, only occurs at equimolar molar ratios and above. The formation of dityrosine adducts occurs following the initiation of aggregation and hence does not drive the formation of the Cu2+ induced aggregates. These results define the role Cu2+ plays in modulating the aggregation state and toxicity of Abeta1-42

Amyloid- Peptide A-3pE-42 Induces Lipid Peroxidation, Membrane Permeabilization, and Calcium Influx in Neurons

Pyroglutamate-modified amyloid-β (pE-Aβ) is a highly neurotoxic amyloid-β (Aβ) isoform and is enriched in the brains of individuals with Alzheimer disease compared with healthy aged controls. Pyroglutamate formation increases the rate of Aβ oligomerization and alters the interactions of Aβ with Cu(2+) and lipids; however, a link between these properties and the toxicity of pE-Aβ peptides has not been established. We report here that Aβ3pE-42 has an enhanced capacity to cause lipid peroxidation in primary cortical mouse neurons compared with the full-length isoform (Aβ(1–42)). In contrast, Aβ(1–42) caused a significant elevation in cytosolic reactive oxygen species, whereas Aβ3pE-42 did not. We also report that Aβ3pE-42 preferentially associates with neuronal membranes and triggers Ca(2+) influx that can be partially blocked by the N-methyl-d-aspartate receptor antagonist MK-801. Aβ3pE-42 further caused a loss of plasma membrane integrity and remained bound to neurons at significantly higher levels than Aβ(1–42) over extended incubations. Pyroglutamate formation was additionally found to increase the relative efficiency of Aβ-dityrosine oligomer formation mediated by copper-redox cycling