Biology subjects

Fisher, J. L.

Publications and source records attributed to Fisher, J. L..

10 recordsLinked to original sources

bioRxiv2025

Molecular mechanisms regulating PDE11A4 age-related liquid-liquid phase separation (LLPS) and its reversal by selective, potent and orally-available PDE11A4 small molecule inhibitors both in vitro and in vivo

PDE11A is a little-studied phosphodiesterase family that breaks down cAMP and cGMP, with the PDE11A4 isoform enriched in the memory-related hippocampus. Age-related increases in hippocampal PDE11A expression occur in human and rodents, causing age-related cognitive decline of social memories. Interestingly, this age-related increase triggers PDE11A4 liquid-liquid phase separation (LLPS), causing the enzyme to accumulate in the brain in filamentous structures termed "ghost axons". Here we sought to identify molecular mechanisms regulating PDE11A4 LLPS and therapeutic approaches capable of reversing it. PDE11A4 LLPS was reduced by phosphorylation of PDE11A4-S163 or-S239 and the D355A mutation that blocks the effect of cGMP binding the PDE11A4 GAF-A domain. PDE11A4 LLPS was increased by inhibiting kinases with staurosporine or stimulating packaging/repacking via the trans-Golgi network by overexpressing TGN38 or RhoB. 8 PDE11 inhibitors (MLG-122, MLG-185, MLG-199, SMQ-02-57, SMQ-03-30, SMQ-03-20, tadalafil, and BC11-38) across 3 scaffolds reverse overexpression-related PDE11A4 LLPS in HT22 mouse hippocampal neuronal cells. This effect of PDE11A4 inhibitors occurs within minutes, is reversed upon washout of lower but not higher concentrations, and occurs in part by reducing PDE11A4 homodimerization. PDE11A4 inhibitors also rescued exacerbated PDE11A4 LLPS triggered by aging-like S117D/S124D phosphomimic mutations, staurosporine, or TGN38/RhoB overexpression. In vivo, orally-administered 30mg/kg SMQ-03-20 reversed age-related increases in PDE11A4 ghost axons and neuroinflammation in old mice. Thus, PDE11A inhibitors that reverse age-related PDE11A4 LLPS in HT22 hippocampal cells also reduce PDE11A4 ghost axons and neuroinflammation in the aged mouse brain, indicating therapeutical potential.

neuroscience↗

bioRxiv2023

The sleep quality- and myopia-linked PDE11A-Y727C variant impacts neural physiology by reducing catalytic activity and altering subcellular compartmentalization of the enzyme

Recently, a Y727C variant in the dual-specific 3,5-cyclic nucleotide phosphodiesterase 11A (PDE11A-Y727C) was linked to increased sleep quality and reduced myopia risk in humans. Given the well-established role that the PDE11 substrates cAMP and cGMP play in eye physiology and sleep, we determined if 1) PDE11A protein is expressed in the retina or other eye segments in mouse, 2) PDE11A-Y7272C affects catalytic activity and/or subcellular compartmentalization more so than the nearby suicide-associated PDE11A-M878V variant, and 3) Pde11a deletion alters eye growth or sleep quality in male and female mice. Western blots show distinct protein expression of PDE11A4, but not PDE11A1-3, in eyes of Pde11a WT--but not KO mice--that vary by eye segment and age. In HT22 and COS-1 cells, PDE11A4-Y727C reduces PDE11A4 catalytic activity far more than PDE11A4-M878V, with both variants reducing PDE11A4-cAMP more so than PDE11A4-cGMP activity. Despite this, Pde11a deletion does not alter age-related changes in retinal or lens thickness, axial length, nor vitreous or anterior chamber depth. Further, Pde11a deletion only minimally changes refractive error and sleep quality. That said, both variants also dramatically alter the subcellular compartmentalization of human and mouse PDE11A4, an effect occurring independently of dephosphorylating PDE11A4-S117/S124 or phosphorylating PDE11A4-S162. Rather, re-compartmentalization of PDE11A4-Y727C is due to the loss of the tyrosine changing how PDE11A4 is packaged/repackaged via the trans-Golgi network. Therefore, the protective impact of the Y727C variant may reflect a gain-of-function (e.g., PDE11A4 displacing another PDE) that warrants further investigation in the context of reversing/preventing sleep disturbances or myopia.

neuroscience↗

bioRxiv2023

Sex-biased gene expression and gene-regulatory networks of sex-biased adverse event drug targets and drug metabolism genes

BackgroundPrevious pharmacovigilance studies and a retroactive review of cancer clinical trial studies identified that women were more likely to experience drug adverse events (i.e., any unintended effects of medication), and men were more likely to experience adverse events that resulted in hospitalization or death. These sex-biased adverse events (SBAEs) are due to many factors not entirely understood, including differences in body mass, hormones, pharmacokinetics, and liver drug metabolism enzymes and transporters. MethodsWe first identified drugs associated with SBAEs from the FDA Adverse Event Reporting System (FAERS) database. Next, we evaluated sex-specific gene expression of the known drug targets and metabolism enzymes for those SBAE-associated drugs. We also constructed sex-specific tissue gene-regulatory networks to determine if these known drug targets and metabolism enzymes from the SBAE-associated drugs had sex-specific gene-regulatory network properties and predicted regulatory relationships. ResultsWe identified liver-specific gene-regulatory differences for drug metabolism genes between males and females, which could explain observed sex differences in pharmacokinetics and pharmacodynamics. In addition, we found that [~]85% of SBAE-associated drug targets had sex-biased gene expression or were core genes of sex- and tissue-specific network communities, significantly higher than randomly selected drug targets. Lastly, we provide the sex-biased drug-adverse event pairs, drug targets, and drug metabolism enzymes as a resource for the research community. ConclusionsOverall, we provide evidence that many SBAEs are associated with drug targets and drug metabolism genes that are differentially expressed and regulated between males and females. These SBAE-associated drug metabolism enzymes and drug targets may be useful for future studies seeking to explain or predict SBAEs.

genomics↗

bioRxiv2023

Inferring chromosomal instability from copy number aberrations as a measure of chromosomal instability across human cancers

BackgroundCancer is a complex disease that is the second leading cause of death in the United States. Despite research efforts, the ability to manage cancer and select optimal therapeutic responses for each patient remains elusive. Chromosomal instability (CIN) is primarily a product of segregation errors wherein one or many chromosomes, in part or whole, vary in number. CIN is an enabling characteristic of cancer, contributes to tumor-cell heterogeneity, and plays a crucial role in the multistep tumorigenesis process, especially in tumor growth and initiation and in response to treatment. AimsMultiple studies have reported different metrics for analyzing copy number aberrations as surrogates of CIN from DNA copy number variation data. However, these metrics differ in how they are calculated with respect to the type of variation, the magnitude of change, and the inclusion of breakpoints. Here we compared metrics capturing CIN as either numerical aberrations, structural aberrations, or a combination of the two across 33 cancer data sets from The Cancer Genome Atlas (TCGA). Methods and resultsUsing CIN inferred by methods in the CINmetrics R package, we evaluated how six copy number CIN surrogates compared across TCGA cohorts by assessing each across tumor types, as well as how they associate with tumor stage, metastasis, and nodal involvement, and with respect to patient sex. ConclusionsWe found that the tumor type impacts how well any two given CIN metrics correlate. While we also identified overlap between metrics regarding their association with clinical characteristics and patient sex, there was not complete agreement between metrics. We identified several cases where only one CIN metric was significantly associated with a clinical characteristic or patient sex for a given tumor type. Therefore, caution should be used when describing CIN based on a given metric or comparing it to other studies.

genomics↗

bioRxiv2023

Evaluating cancer cell line and patient-derived xenograft recapitulation of tumor and non-diseased tissue gene expression profiles

Preclinical models like cancer cell lines and patient-derived xenografts (PDXs) are vital for studying disease mechanisms and evaluating treatment options. It is essential that they accurately recapitulate the disease state of interest to generate results that will translate in the clinic. Prior studies have demonstrated that preclinical models do not recapitulate all biological aspects of human tissues, particularly with respect to the tissue of origin gene expression signatures. Therefore, it is critical to assess how well preclinical model gene expression profiles correlate with human cancer tissues to inform preclinical model selection and data analysis decisions. Here we evaluated how well preclinical models recapitulate human cancer and non-diseased tissue gene expression patterns in silico with respect to the full gene expression profile as well as subsetting by the most variable genes, genes significantly correlated with tumor purity, and tissue-specific genes by using publicly available gene expression profiles across multiple sources. We found that using the full gene set improves correlations between preclinical model and tissue global gene expression profiles, confirmed that GBM PDX global gene expression correlation to GBM tumor global gene expression outperforms GBM cell line to GBM tumor global gene expression correlations, and demonstrated that preclinical models in our study often failed to reproduce tissue-specific expression. While including additional genes for global gene expression comparison between cell lines and tissues decreases the overall correlation, it improves the relative rank between a cell line and its tissue of origin compared to other tissues. Our findings underscore the importance of using the full gene expression set measured when comparing preclinical models and tissues and confirm that tissue-specific patterns are better preserved in GBM PDX models than in GBM cell lines. Future studies can build on these findings to determine the specific pathways and gene sets recapitulated by particular preclinical models to facilitate model selection for a given study design or goal.

genomics↗

bioRxiv2023

Signature reversion of three disease-associated gene signatures prioritizes cancer drug repurposing candidates

Drug repurposing is promising because approving a drug for a new indication requires fewer resources than approving a new drug. Signature reversion detects drug perturbations most inversely related to the disease-associated gene signature to identify drugs that may reverse that signature. We assessed the performance and biological relevance of three approaches for constructing disease-associated gene signatures (i.e, limma, DESeq2, and MultiPLIER) and prioritized the resulting drug repurposing candidates for four low-survival human cancers. Our results were enriched for candidates that had been used in clinical trials or performed well in the PRISM drug screen. Additionally, we found that pamidronate and nimodipine, drugs predicted to be efficacious against the brain tumor glioblastoma (GBM), inhibited the growth of a GBM cell line and cells isolated from a patient derived xenograft (PDX). Our results demonstrate that by applying multiple disease-associated gene signature methods, we prioritized several drug repurposing candidates for low-survival cancers. Graphical Abstract O_FIG O_LINKSMALLFIG WIDTH=155 HEIGHT=200 SRC="FIGDIR/small/532074v1_ufig1.gif" ALT="Figure 1"> View larger version (45K): org.highwire.dtl.DTLVardef@1c5d402org.highwire.dtl.DTLVardef@e1dc86org.highwire.dtl.DTLVardef@54e6feorg.highwire.dtl.DTLVardef@96856_HPS_FORMAT_FIGEXP M_FIG C_FIG

genomics↗

bioRxiv2022

An updated end-to-end ecosystem model of the Northern California Current reflecting ecosystem changes due to recent marine heat waves

The Northern California Current is a highly productive marine upwelling ecosystem that is economically and ecologically important. It is home to both commercially harvested species and those that are federally listed under the U.S. Endangered Species Act. Recently, there has been a global shift from single-species fisheries management to ecosystem-based fisheries management, which acknowledges that more complex dynamics can reverberate through a food web. Here, we have integrated new research into an end-to-end ecosystem model (i.e., physics to fisheries) using data from long-term ocean surveys, phytoplankton satellite imagery paired with a vertically generalized production model, a recently assembled diet database, fishery catch information, species distribution models, and existing literature. This spatially-explicit model includes 90 living and detrital functional groups ranging from phytoplankton, krill, and forage fish to salmon, seabirds, and marine mammals, and nine fisheries that occur off the coast of Washington, Oregon, and Northern California. This model was updated from previous regional models to account for more recent changes in the Northern California Current (e.g., increases in market squid and some gelatinous zooplankton such as pyrosomes and salps), to expand the previous domain to increase the spatial resolution, to include data from previously unincorporated surveys, and to add improved characterization of endangered species, such as Chinook salmon (Oncorhynchus tshawytscha) and southern resident killer whales (Orcinus orca). Our model is mass-balanced, ecologically plausible, without extinctions, and stable over 150-year simulations. Ammonium and nitrate availability, total primary production rates, and model-derived phytoplankton time series are within realistic ranges. As we move towards holistic ecosystem-based fisheries management, we must continue to openly and collaboratively integrate our disparate datasets and collective knowledge to solve the intricate problems we face. As a tool for future research, we provide the data and code to use our ecosystem model.

systems biology↗

bioRxiv2022

Prioritized polycystic kidney disease drug targets and repurposing candidates from pre-cystic and cystic mouse model gene expression reversion

Autosomal dominant polycystic kidney disease (ADPKD) is one of the most prevalent monogenic human diseases. It is mostly caused by pathogenic variants in PKD1 or PKD2 genes that encode interacting transmembrane proteins polycystin-1 (PC1) and polycystin-2 (PC2). Among many pathogenic processes described in ADPKD, those associated with cAMP signaling, inflammation, and metabolic reprogramming appear to regulate the disease manifestations. Tolvaptan, a vasopressin receptor-2 antagonist that regulates cAMP pathway, is the only FDA-approved ADPKD therapeutic. Tolvaptan reduces renal cyst growth and kidney function loss, but it is not tolerated by many patients and is associated with idiosyncratic liver toxicity. Therefore, additional therapeutic options for ADPKD treatment are needed. As drug repurposing of FDA-approved drug candidates can significantly decrease the time and cost associated with traditional drug discovery, we used the computational approach signature reversion to detect inversely related drug response gene expression signatures from the Library of Integrated Network-Based Cellular Signatures (LINCS) database and identified compounds predicted to reverse disease-associated transcriptomic signatures in three publicly available Pkd2 kidney transcriptomic data sets of mouse ADPKD models. We focused on a pre-cystic model for signature reversion, as it was less impacted by confounding secondary disease mechanisms in ADPKD, and then compared the resulting candidates target differential expression in the two cystic mouse models. We further prioritized these drug candidates based on their known mechanism of action, FDA status, targets, and by functional enrichment analysis. With this in-silico approach, we prioritized 29 unique drug targets differentially expressed in Pkd2 ADPKD cystic models and 16 prioritized drug repurposing candidates that target them, including bromocriptine and mirtazapine, which can be further tested in-vitro and in-vivo. Collectively, these indicate drug targets and repurposing candidates that may effectively treat pre-cystic as well as cystic ADPKD. O_FIG O_LINKSMALLFIG WIDTH=110 HEIGHT=200 SRC="FIGDIR/small/518863v2_ufig1.gif" ALT="Figure 1"> View larger version (33K): org.highwire.dtl.DTLVardef@18af02org.highwire.dtl.DTLVardef@89d45corg.highwire.dtl.DTLVardef@d4fffdorg.highwire.dtl.DTLVardef@1f244b3_HPS_FORMAT_FIGEXP M_FIG Graphical abstract of the study created with Biorender.com. C_FIG

genomics↗

bioRxiv2021

CINmetrics: An R package for chromosomal instability analysis

Genomic instability is an important hallmark of cancer and more recently has been identified in others like neurodegenrative diseases. Chromosomal instability, as a measure of genomic instability, has been used to characterize clinical and biological phenotypes associated with these diseases by measuring structural and numerical chromosomal alterations. There have been multiple chromosomal instability scores developed across many studies in the literature; however, these scores have not been compared because of the lack of a single tool available to calculate and facilitate these various metrics. Here, we provide an R package CINmetrics, that calculates six different chromosomal instability scores and allows direct comparison between them. We also demonstrate how these scores differ by applying CINmetrics to breast cancer data from The Cancer Genome Atlas (TCGA). The package is available on CRAN at https://cran.r-project.org/package=CINmetrics and on github at https://github.com/lasseignelab/CINmetrics.

cancer biology↗

bioRxiv2018

Potential combined pro-cognitive, anxiolytic and antidepressant properties of novel GABAA receptor positive modulators with preferential efficacy at the α5-subunit

Altered {gamma}-aminobutyric acid (GABA) function is consistently reported in psychiatric disorders, normal aging and neurodegenerative disorders, and reduced function of somatostatin - expressing GABA interneurons is associated with both mood and cognitive symptoms. Somatostatin-neurons signal in part through 5-subunit containing GABAA receptors (5-GABAA-Rs) which are localized in brain regions implicated in emotion and cognition. We hypothesize that enhancing 5-GABAA-R activity has therapeutic potential for both mood and cognitive symptoms in stress-based and aging rodent models.\n\nWe synthesized four novel imidazobenzodiazepine (IBZD) amide ligands, tested them for positive allosteric modulation at 5-GABAA-R (5-PAM), pharmacokinetic properties, and for anxiolytic and antidepressant activities in adult mice. Pro-cognitive activity was tested in adult mice submitted to chronic stress and in old mice. Diazepam (DZP), with broad PAM activity at GABAA-Rs, was used as a control.\n\nThree novel IBZD amide ligands (GL-II-73, GL-II-74 and GL-II-75) demonstrated adequate brain penetration, affinity and 5-PAM activity, and metabolic stability for in vivo studies. GL-II-73/74/75 showed significant anxiolytic and antidepressant efficacies in adult mice. GL-II-73 and GL-II-75 significantly reversed cognitive deficits induced by stress or occurring throughout normal aging. This activity was maintained after sub-chronic administration for GL-II-73. In contrast DZP displayed anxiolytic but no antidepressant or pro-cognitive activities.\n\nWe demonstrate for the first time the potential for combined anxiolytic, antidepressant and pro-cognitive therapeutic, mediated by newly designed IBDZ amide ligands with efficacy at 5-GABAA-Rs. These results suggest a novel therapeutic approach targeting both mood and cognitive symptoms in depression and/or aging.

pharmacology and toxicology↗