Biology subjects

Steinberg, J.

Publications and source records attributed to Steinberg, J..

13 recordsLinked to original sources

bioRxiv2026

The metastasis susceptibility gene RRP1B is a stress-responsive regulator of nuclear RNA processing and splicing in breast cancer

The tumor microenvironment exposes cancer cells to mechanical, thermal, hypoxic, and acidic stresses, yet how cells integrate these signals to remodel RNA processing remains poorly understood. Here, we show that ribosomal RNA Processing 1B (RRP1B), previously characterized as a nucleolar ribosome biogenesis factor and metastasis modifier, functions as a broad-spectrum stress sensor that dynamically repositions among the nuclear envelope, nucleolus, and nuclear speckles (NS). Relocalization is governed by multi-site phosphorylation within intrinsically disordered regions (IDRs): phosphomimetic substitutions promote NS-proximal condensate formation in an RNA-dependent manner, while unphosphorylatable substitutions confine RRP1B to the nucleolus. Under stress, the RRP1B interactome shifts globally, with ribosomal processing partners replaced by pre-mRNA splicing components enriched for NS-resident proteins. RNA immunoprecipitation sequencing (RIP-seq) demonstrates that under basal conditions RRP1B associates with long, intron-rich, nuclear periphery-proximal transcripts, whereas heat shock redirects binding toward shorter, exon-dense transcripts enriched for motifs of serine/arginine-rich (SR) proteins near the NS. RRP1B overexpression nearly abolishes cytoplasmic retained intron accumulation and drives preferential export of specific transcript isoforms in a compartment- and temperature-dependent manner, establishing RRP1B as a regulator of RNA localization fidelity rather than transcriptional output. An RRP1B overexpression signature is most highly activated in basal-like and claudin-low breast tumors, and the RRP1B-associated retained intron splicing program correlates with reduced survival in a tumor-grade-dependent manner. These findings reframe RRP1B as a microenvironmentally sensitive regulator of nuclear RNA processing with direct implications for aggressive breast cancer biology.

Cancer Biology↗

bioRxiv2025

Integration of artificial intelligence and high-content screening enabled identification of drugs for long-term treatment of cerebral cavernous malformation disease

BackgroundAdults and children with cerebral cavernous malformations (CCMs) are at risk of experiencing lifelong complications such as hemorrhagic strokes, neurological deficits, and epileptic seizures. These complications can severely reduce quality of life. At present, there is no safe or effective therapeutic option for the long-term treatment of CCMs. MethodsUsing advanced artificial intelligence (AI) and machine learning models, powered by the Benevolent Platform, we aimed to identify therapeutic drug targets for CCM pathology (e.g., CCM1, CCM2, CCM3). An AI integrative approach utilized various data types from biomedical entities, including diseases, genes, tissues, and biological mechanisms, together with CCM transcriptomic experimental data. High-throughput drug screening of AI-selected FDA-approved medications, analyses of mitochondrial morphology, and studies on pharmacokinetics, pharmacodynamics, and toxicology were conducted in CCM animal models to identify drugs that could potentially be repurposed for the long-term treatment of CCM disease. ResultsAI predicted the AMPK (AMP-activated protein kinase) and mTOR (mammalian target of rapamycin) pathways as potential therapeutic targets that contribute to CCM pathology. High-content screening validation revealed that the FDA-approved drug metformin, which acts as an AMPK agonist and mTOR inhibitor, can reverse changes in cell-cell junction organization and increase KLF4 expression, a marker for CCM, in human CCM endothelial cells in cultured assays. In addition, pharmacodynamic markers of metformin were observed in CCM mouse models (Slco1c1-iCreERT2;Krit1fl/fl;Ptenfl/wt and Slco1c1-iCreERT2;Pdcd10fl/fl) including reduced S6 kinase or ribosomal protein phosphorylation, a marker of decrease mTOR signaling, and increased AMPK phosphorylation, a marker of AMPK activation, that corresponded to reduced lesion burden. Pharmacokinetic and toxicological studies in CCM animal models showed that that metformin penetrates the brain and long-term administration has a favorable safety profile. We also demonstrated that brain endothelial cells in chronic CCM mouse models exhibit increased levels of the inflammatory marker VCAM-1, which is associated with altered mitochondrial phenotypes, as observed by immunofluorescence, MITO-tagging, and electron microscopy analysis. Additionally, we discovered that metformin and a potent AMPK activator, PF-06409577, can reverse mitochondrial phenotypic changes in brain endothelial cells and reduce the elevation of VCAM-1 expression associated with chronic CCM disease. Therefore, metformin can provide cytoprotection and may reverse the CCM endothelial phenotype by activating AMPK. ConclusionsPredictions using AI technology and high-throughput drug screening, combined with pharmacokinetic, pharmacodynamic, and toxicological studies in CCM animal models, identified metformin as a promising drug candidate for repurposing for the long-term treatment of CCM disease. We propose that metformin enhances metabolic adaptation to brain vascular malformations by activating AMPK, which helps reverse mitochondrial fragmentation in brain endothelial cells. Graphical abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=140 SRC="FIGDIR/small/693036v1_ufig1.gif" ALT="Figure 1"> View larger version (37K): org.highwire.dtl.DTLVardef@17bfadforg.highwire.dtl.DTLVardef@936708org.highwire.dtl.DTLVardef@15171ceorg.highwire.dtl.DTLVardef@69029_HPS_FORMAT_FIGEXP M_FIG C_FIG

pathology↗

bioRxiv2025

Persistent Activation of Endothelial Cells is Linked to Thrombosis and Inflammation in Cerebral Cavernous Malformation Disease

AbstractO_ST_ABSBACKGROUNDC_ST_ABSCerebral cavernous malformations (CCM) are neurovascular lesions that affect both children and adults, and morbidity often results from thrombosis, bleeding, and neurological dysfunction. Studies indicate that inflammation-related activation of endothelial cells contributes significantly to the worsening of CCM disease. This suggests that ongoing vascular inflammation and endothelial dysfunction are key factors associated with thrombosis and bleeding in CCM disease. However, the inflammatory mechanisms leading to altered brain endothelial cell function with a high propensity for thrombosis, inflammation, and dysfunction are not fully understood. METHODSMulti-omic analyses was conducted by performing simultaneous high-throughput single-nucleus RNA sequencing (snRNA-seq) and single-nucleus transposase-accessible chromatin sequencing (snATAC-seq) with the 10x Genomics multiome platform in combination with immunofluorescence to study CCM pathogenesis in both female and male mice with CCM (Slco1c1-CreERT2; Pdcd10fl/fl) disease. The analysis was complemented with bulk RNA-seq, bulk ATAC-seq, and ChIP-seq (Chromatin immunoprecipitation sequencing) using an in vitro human CCM model. An AAV-BR1 viral system selectively upregulates the activator protein-1 (AP-1) transcription factor JUNB in brain endothelial cells was used to evaluate its effectiveness in maintaining a persistent activated cell state during the pathogenesis of CCM. RESULTSWe found that epigenetics significantly influences the subtype identity and function of brain endothelial cells within the arteriovenous axis. Through multi-omic analyses, specific regulatory elements and enhancers (cis-Regulatory Elements, cCREs) in mouse brain endothelial cells were identified that influence subtype-specific transcriptional programs and the transcription factors responsible for establishing the various subtypes of brain endothelial cells. Additionally, large-scale epigenomic reprogramming of brain endothelial cell subtypes was observed during the pathogenesis of CCM disease. Among the most significant changes were alterations in the chromatin state of endothelial cells, along with transcriptional processes associated with a persistently activated endothelial cell state, which renders them susceptible to inflammation and thrombosis. The activator AP-1 transcription factor JUNB was identified as a key regulator of the persistently activated endothelial state during chronic neuroinflammation. Moreover, both trans- and cis-regulatory factors conserved between mice and humans were discovered and contribute to the progression of chronic CCM disease. CONCLUSIONSEpigenetics plays a crucial role in determining the transcription patterns and functions of brain arteriovenous endothelial cells. The activator JUNB is identified as a driver of chronic brain vascular inflammation by inducing a persistent activated endothelial cell state from epigenome reprogramming. Graphical Abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=111 SRC="FIGDIR/small/662238v1_ufig1.gif" ALT="Figure 1"> View larger version (30K): org.highwire.dtl.DTLVardef@1297edforg.highwire.dtl.DTLVardef@1488e27org.highwire.dtl.DTLVardef@6cae62org.highwire.dtl.DTLVardef@12cb282_HPS_FORMAT_FIGEXP M_FIG C_FIG

genomics↗

bioRxiv2025

Receptor Allostery Promotes Context-Specific Sonic Hedgehog Signaling During Embryonic Development

Sonic Hedgehog (SHH) signaling functions in temporal- and context-dependent manners to pattern diverse tissues during embryogenesis. The signal transducer Smoothened (SMO) is activated by sterols, oxysterols, and arachidonic acid (AA) through binding pockets in its extracellular cysteine-rich domain (CRD) and 7-transmembrane (7TM) bundle. In vitro analyses suggest SMO signaling is allosterically enhanced by combinatorial ligand binding to these pockets but in vivo evidence of SMO allostery is lacking. Herein, we map an AA binding pocket at the top of the 7TM bundle and show that its disruption attenuates SHH and sterol-stimulated SMO induction. A knockin mouse model of compromised AA binding reveals that homozygous mutant mice are cyanotic, exhibit high perinatal lethality, and show congenital heart disease. Surviving mutants demonstrate pulmonary maldevelopment and fail to thrive. Neurodevelopment is unaltered in these mice, suggesting that context-dependent allosteric regulation of SMO signaling allows for precise tuning of pathway activity during cardiopulmonary development.

developmental biology↗

bioRxiv2024

Conditional c-MYC activation in catecholaminergic cells drives distinct neuroendocrine tumors: neuroblastoma vs somatostatinoma

The MYC proto-oncogenes (c-MYC, MYCN, MYCL) are among the most deregulated oncogenic drivers in human malignancies including high-risk neuroblastoma, 50% of which are MYCN-amplified. Genetically engineered mouse models (GEMMs) based on the MYCN transgene have greatly expanded the understanding of neuroblastoma biology and are powerful tools for testing new therapies. However, a lack of c-MYC-driven GEMMs has hampered the ability to better understand mechanisms of neuroblastoma oncogenesis and therapy development given that c-MYC is also an important driver of many high-risk neuroblastomas. In this study, we report two transgenic murine neuroendocrine models driven by conditional c-MYC induction in tyrosine hydroxylase (Th) and dopamine {beta}-hydroxylase (Dbh)-expressing cells. c-MYC induction in Th-expressing cells leads to a preponderance of Pdx1+ somatostatinomas, a type of pancreatic neuroendocrine tumor (PNET), resembling human somatostatinoma with highly expressed gene signatures of {delta} cells and potassium channels. In contrast, c-MYC induction in Dbh-expressing cells leads to onset of neuroblastomas, showing a better transforming capacity than MYCN in a comparable C57BL/6 genetic background. The c-MYC murine neuroblastoma tumors recapitulate the pathologic and genetic features of human neuroblastoma, express GD2, and respond to anti-GD2 immunotherapy. This model also responds to DFMO, an FDA-approved inhibitor targeting ODC1, which is a known MYC transcriptional target. Thus, establishing c-MYC-overexpressing GEMMs resulted in different but related tumor types depending on the targeted cell and provide useful tools for testing immunotherapies and targeted therapies for these diseases.

cancer biology↗

bioRxiv2022

Associative memory of structured knowledge

A long standing challenge in biological and artificial intelligence is to understand how new knowledge can be constructed from known building blocks in a way that is amenable for computation by neuronal circuits. Here we focus on the task of storage and recall of structured knowledge in long-term memory. Specifically, we ask how recurrent neuronal networks can store and retrieve multiple knowledge structures. We model each structure as a set of binary relations between events and attributes (attributes may represent e.g., temporal order, spatial location, role in semantic structure), and map each structure to a distributed neuronal activity pattern using a vector symbolic architecture (VSA) scheme. We then use associative memory plasticity rules to store the binarized patterns as fixed points in a recurrent network. By a combination of signal-to-noise analysis and numerical simulations, we demonstrate that our model allows for efficient storage of these knowledge structures, such that the memorized structures as well as their individual building blocks (e.g., events and attributes) can be subsequently retrieved from partial retrieving cues. We show that long-term memory of structured knowledge relies on a new principle of computation beyond the memory basins. Finally, we show that our model can be extended to store sequences of memories as single attractors.

neuroscience↗

bioRxiv2021

Dicer promotes genome stability via the bromodomain transcriptional co-activator Brd4.

RNA interference is essential for transcriptional silencing and genome stability, but conservation of this role in mammals has been difficult to demonstrate. Dicer1-/- mouse embryonic stem cells have microRNA-independent proliferation defects, and we conducted a CRISPR-Cas9 screen to restore viability. We identified suppressor mutations in transcriptional activators, H3K9 methyltransferases, and chromosome segregation factors, strongly resembling Dicer suppressors in fission yeast. Suppressors rescued chromosomal defects, and reversed strand-specific transcription of major satellite repeats in Dicer1-/-. The strongest suppressors were in Brd4, and in the transcriptional elongator/histone acetyltransferase Elp3. Using viable mutants and pharmaceutical inhibitors, we demonstrate that deletion of specific residues in Brd4 rescue genome instability defects of Dicer1-/- in both mammalian cells and fission yeast, implicating Dicer in coordinating transcription and replication of satellite repeats. SummaryReplication and segregation defects in Dicer1-/- stem cells depend on centromeric transcription by Brd4, and are deeply conserved in fission yeast.

genetics↗

bioRxiv2019

Decoding the genomic basis of osteoarthritis

Osteoarthritis causes pain and functional disability for a quarter of a billion people worldwide, with no disease-stratifying tools nor modifying therapy. Here, we use primary cartilage and synovium from osteoarthritis patients to construct a molecular quantitative trait locus map of gene expression and protein abundance. By integrating data across omics levels, we identify likely effector genes for osteoarthritis-associated genetic signals. We detect pronounced molecular differences between macroscopically intact and highly degenerated cartilage. We identify molecularly-defined patient subgroups that correlate with clinical characteristics, stratifying patients on the basis of their molecular profile. We construct and validate a 7-gene classifier that reproducibly distinguishes between these disease subtypes, and identify potentially actionable compounds for disease modification and drug repurposing.

genomics↗

bioRxiv2019

Accelerating functional gene discovery in osteoarthritis

Osteoarthritis causes debilitating pain and disability, resulting in a huge socioeconomic burden, yet no drugs are available that prevent disease onset or progression. Here, we develop, validate and use rapid-throughput imaging techniques to identify abnormal joint phenotypes in unselected mutant mice generated by the International Knockout Mouse Consortium. We identify 14 genes with functional involvement in osteoarthritis pathogenesis, including the homeobox gene Pitx1, and functionally characterize 6 candidate human osteoarthritis genes in mouse models. We demonstrate sensitivity of the methods by identifying age-related degenerative joint damage in wild-type mice. Finally, we generate mutant mice with an osteoarthritis-associated polymorphism in the Dio2 gene by Crispr/Cas9 genome editing and demonstrate a protective role in disease onset with public health implications. This expanding resource of unselected mutant mice will transform the field by accelerating functional gene discovery in osteoarthritis and offering unanticipated drug discovery opportunities for this common and incapacitating chronic disease.

genetics↗

bioRxiv2018

Identification of new therapeutic targets for osteoarthritis through genome-wide analyses of UK Biobank

Osteoarthritis is the most common musculoskeletal disease and the leading cause of disability globally. Here, we perform the largest genome-wide association study for osteoarthritis to date (77,052 cases and 378,169 controls), analysing 4 phenotypes: knee osteoarthritis, hip osteoarthritis, knee and/or hip osteoarthritis, and any osteoarthritis. We discover 64 signals, 52 of them novel, more than doubling the number of established disease loci. Six signals fine map to a single variant. We identify putative effector genes by integrating eQTL colocalization, fine-mapping, human rare disease, animal model, and osteoarthritis tissue expression data. We find enrichment for genes underlying monogenic forms of bone development diseases, and for the collagen formation and extracellular matrix organisation biological pathways. Ten of the likely effector genes, including TGFB1, FGF18, CTSK and IL11 have therapeutics approved or in clinical trials, with mechanisms of action supportive of evaluation for efficacy in osteoarthritis.

genetics↗

bioRxiv2018

Measures of Possible Allostatic Load in Comorbid Cocaine and Alcohol use Disorder: Brain White Matter Integrity, Telomere Length, and Anti-Saccade Performance

Chronic cocaine and alcohol use impart significant stress on biological and cognitive systems, resulting in changes consistent with an allostatic load model of neurocognitive impairment. The present study measured potential markers of allostatic load in individuals with comorbid cocaine/alcohol use disorders (CUD/AUD) and control subjects. Measures of brain white matter (WM) integrity, telomere length, and impulsivity/attentional bias were obtained. WM integrity (CUD/AUD only) was indexed by diffusion tensor imaging metrics, including radial diffusivity (RD) and fractional anisotropy (FA). Telomere length was indexed by T/S ratio. Impulsivity and attentional bias to drug cues were measured via eye-tracking, and were also modeled using the Hierarchical Diffusion Drift Model (HDDM). Average whole-brain RD and FA were associated with years of cocaine use (R2 = 0.56 and 0.51, both p < .005) but not years of alcohol use. CUD/AUD subjects showed more anti-saccade errors (p < .01), greater attentional bias scores (p < .001), and higher HDDM drift rates on cocaine-cue trials (Bayesian probability CUD/AUD > control = p > 0.99). Telomere length was shorter in CUD/AUD, but the difference was not statistically significant. Within the CUD/AUD group, exploratory regression using an elastic-net model determined that more years of cocaine use, older age, larger HDDM drift rate differences and shorter telomere length were all predictive of white matter integrity as measured by RD (model R2 = 0.79). Collectively, the results provide modest support linking CUD/AUD to putative markers of allostatic load.

neuroscience↗

bioRxiv2017

The genetic architecture of osteoarthritis: insights from UK Biobank

Osteoarthritis is a common complex disease with huge public health burden. Here we perform a genome-wide association study for osteoarthritis using data across 16.5 million variants from the UK Biobank resource. Following replication and meta-analysis in up to 30,727 cases and 297,191 controls, we report 9 new osteoarthritis loci, in all of which the most likely causal variant is non-coding. For three loci, we detect association with biologically-relevant radiographic endophenotypes, and in five signals we identify genes that are differentially expressed in degraded compared to intact articular cartilage from osteoarthritis patients. We establish causal effects for higher body mass index, but not for triglyceride levels or type 2 diabetes liability, on osteoarthritis.

genetics↗

bioRxiv2017

The Genetic Epidemiology of Developmental Dysplasia of the Hip: A Genome-Wide Association Study Harnessing National Clinical Audit Data

BackgroundDevelopmental dysplasia of the hip (DDH) is a common, heritable condition characterised by abnormal formation of the hip joint, but has a poorly understood genetic architecture due to small sample sizes. We apply a novel case-ascertainment approach using national clinical audit (NCA) data to conduct the largest DDH genome-wide association study (GWAS) to date, and replicate our findings in independent cohorts.\n\nMethodsWe used the English National Joint Registry (NJR) dataset to collect DNA and conducted a GWAS in 770 DDH cases and 3364 controls. We tested the variant most strongly associated with DDH in independent replication cohorts comprising 1129 patients and 4652 controls.\n\nResultsThe heritable component of DDH attributable to common variants was 55% and distributed similarly across autosomal and the X-chromosomes. Variation within the GDF5 gene promoter was strongly and reproducibly associated with DDH (rs143384, OR 1.44 [95% CI 1.34-1.56], p=3.55x10-22). Two further replicating loci showed suggestive association with DDH near NFIB (rs4740554, OR 1.30 [95% CI 1.16-1.45], p=4.44x10-6) and LOXL4 (rs4919218, 1.19 [1.10-1.28] p=4.38x10-6). Through gene-based enrichment we identify GDF5, UQCC1, MMP24, RETSAT and PDRG1 association with DDH (p<1.2x10-7). Using the UK Biobank and arcOGEN cohorts to generate polygenic risk scores we find that risk alleles for hip osteoarthritis explain <0.5% of the variance in DDH susceptibility.\n\nConclusionUsing the NJR as a proof-of-principle, we describe the genetic architecture of DDH and identify several candidate intervention loci and demonstrate a scalable recruitment strategy for genetic studies that is transferrable to other complex diseases.\n\nKey MessagesO_LIWe report the first genome-wide scan for DDH in a European population, and the first to use national clinical audit data for case-ascertainment in complex disease.\nC_LIO_LIThe heritable component of DDH attributable to common variants is 55% and is distributed similarly across autosomal and the X-chromosomes.\nC_LIO_LIVariation within the GDF5 gene promoter is strongly and reproducibly associated with DDH, with fine-mapping indicating rs143384 as the likely casual variant.\nC_LIO_LIEnrichment analyses implicate GDF5, UQCC1, MMP24, RETSAT and PDRG1 as candidate targets for intervention in DDH.\nC_LIO_LIDDH shares little common genetic aetiology with idiopathic osteoarthritis of the hip, despite sharing variation within the GDF5 promoter as a common risk factor.\nC_LI

genetics↗