Biology subjects

Brown, J.

Publications and source records attributed to Brown, J..

At least 37 records · Page 2Linked to original sources

bioRxiv2025

Which evolutionary game-theoretic model best captures non-small cell lung cancer dynamics?

Understanding and predicting the eco-evolutionary dynamics of cancer requires identifying mathematical models that best capture tumor growth and treatment response. In this study, we fit a family of two-population models to in-vitro data from non-small cell lung cancer (NSCLC), tracking drug-sensitive and drug-resistant cells under varying environmental conditions. The dataset, originally presented by Kaznatcheev et al., includes conditions with and without the drug Alectinib and cancer-associated fibroblasts (CAFs). We compare combinations of growth models (logistic, Gompertz, von Bertalanffy) and drug efficacy terms (Norton-Simon, linear, ratio-dependent) to identify which best explains the observed dynamics. Our models incorporate density dependence, frequency-dependent competition, and drug response, enabling mechanistic interpretation of tumor cell interactions. The logistic model with ratio-dependent drug efficacy best fits monoculture data. Using growth parameters from monocultures, we infer inter-type competition coefficients in co-cultures. We find that growth rate and carrying capacity are stable across CAF conditions, while competition and drug efficacy parameters shift, altering interaction dynamics. Notably, CAFs promote coexistence between resistant and sensitive cells, whereas Alectinib induces competitive exclusion. Our results underscore the need to evaluate both model fit and biological plausibility to guide therapeutic modeling of cancer. Author summaryHow cancer cells grow, compete, and respond to treatment depends not only on the drug, but also on their ecological context, including interactions with other cells and components of the tumor microenvironment. In this study, we explore how different mathematical models capture the behavior of non-small cell lung cancer (NSCLC) cells under various conditions. We focus on two cell populations: one sensitive to treatment, and one resistant. Using in-vitro data, we compare growth models and drug response types to identify which model best explains the observed population dynamics. We also investigate how different factors, such as the drug Alectinib and cancer-associated fibroblasts (CAFs), change the way cancer cells interact. Our game-theoretic approach allows us to quantify how these external conditions affect competition between cell types, revealing when resistant and sensitive cells can coexist. These findings contribute to a deeper understanding of tumor ecology and may support the development of adaptive cancer therapies that anticipate evolutionary responses to treatment.

systems biology↗

bioRxiv2025

Viral adsorption to Moore swabs in passive wastewater sampling

Moore swabs have been used extensively for passive sampling in wastewater surveillance, typically yielding presence/absence information for targets of interest. Quantitative analysis of Moore swab data is only possible if target uptake is well characterized, specifically the relationship between quantity of the target in the liquid sample matrix and the quantity of target sorbing to the Moore swab as a function of time. The mechanism of Moore swab absorption remains unclear and is important to understand toward using them more quantitatively. We conducted viral adsorption and desorption experiments using nonpathogenic SARS-CoV-2 surrogates: {Phi}6, MHV, and BCoV as well as heat-inactivated Zika virus (ZIKV). We fit empirical adsorption data from batch experiments to Langmuir, Freundlich and Redlich-Peterson isotherm models. We observed the adsorption behavior of viral targets onto Moore swabs is best characterized by the Redlich-Peterson isotherm model. Moore swabs retained the highest viral RNA concentrations after exposure durations between 9-12 hours in the presence of target microbes during kinetic viral adsorption experiments. The results inform current and future use of Moore swabs to produce quantitative data during wastewater surveillance, especially in settings where composite sampling remains infeasible. ImportanceThis paper describes the adsorption behavior of viruses and bacteriophages to Moore swabs. Passive sampling via Moore swabs is among the most scalable form of passive wastewater sampling, considered critical to advance wastewater surveillance globally. But key unknowns constrain the utility of Moore swabs and all passive sampling approaches, including the quantitative relationship between targets in wastewater and recovery via Moore swabs. Practical questions such as how long they should be deployed and whether they can be interpreted quantitatively really depend on a characterization of viral target loading behaviors on Moore swab material as a function of time and concentration in the wastewater. Here, we use an approach that is seldom applied to microbial targets to examine adsorption behavior of viruses to Moore swabs, deriving isotherms that describe the relationships between concentration of the viral targets in wastewater and time on attachment to swab material. This is a critical step in advancing the application of Moore swab passive sampling for wastewater surveillance, with potential relevance to other microbial targets of interest.

microbiology↗

bioRxiv2025

Delaying Cancer Progression by Integrating Toxicity Constraints in a Model of Adaptive Therapy

Cancer therapies often fail when intolerable toxicity or drug-resistant cancer cells undermine otherwise effective treatment strategies. Over the past decade, adaptive therapy has emerged as a promising approach to postpone emergence of resistance by altering dose timing based on tumor burden thresholds. Despite encouraging results, these protocols often overlook the crucial role of toxicity-induced treatment breaks, which may permit tumor regrowth. Herein, we explore the following question: would incorporating toxicity feedback improve or hinder the efficacy of adaptive therapy? To address this question, we propose a mathematical framework for incorporating toxic feedback into treatment design. We find that the degree of competition between sensitive and resistant populations, along with the growth rate of resistant cells, critically modulates the impact of toxicity feedback on time to progression. Further, our model identifies circumstances where strategic treatment breaks, which may be based on either tumor size or toxicity, can mitigate overtreatment and extend time to progression, both at the baseline parameterization and across a heterogeneous virtual population. Taken together, these findings highlight the importance of integrating toxicity considerations into the design of adaptive therapy.

systems biology↗

bioRxiv2025

Exploring the Pathogen Profiles of Ancient Feces

Analysis of ancient desiccated feces - termed paleofeces or coprolites - can unlock insights into the lives of ancient people. We collected desiccated feces from caves in the Rio Zape Valley in Mexico (725-920 CE). First, we extracted DNA with methods previously optimized for paleofeces. Then, we applied highly sensitive modern molecular tools (i.e., PCR pre-amplification followed by multi-parallel qPCR) to assess the presence of 30 enteric pathogens. We detected [≥]1 pathogen associated gene in each of the ten samples and a mean of 3.9 pathogens per sample. The targets detected included Blastocystis spp. (n=7), atypical enteropathogenic E. coli (n=7), Enterobius vermicularis (n=6), Entamoeba spp. (n=5), enterotoxigenic E. coli (n=5), Shigella spp./enteroinvasive E. coli (n=3), Giardia spp. (n=2), and E. coli O157:H7 (n=1). The protozoan pathogens we detected (i.e., Giardia spp. and Entamoeba spp.) have been previously detected in paleofeces via enzyme-linked immunoassay (ELISA), but have not via PCR. This work represents the first detection of Blastocystis spp. atypical enteropathogenic E. coli, enterotoxigenic E. coli, Shigella spp./enteroinvasive E. coli, and E. coli O157:H7 in paleofeces. These results suggest that sensitive modern molecular tools, such as PCR, can be used to evaluate ancient materials for genes of interest.

microbiology↗

bioRxiv2025

Recurrent oncogenic ZC3H18 mutations stabilize endogenous retroviral RNA

Endogenous retroviral (ERV) RNA is highly expressed in cancer, although the molecular causes and consequences remain unknown. We found that ZC3H18 (Z18), a component of multiple nuclear RNA surveillance complexes, has recurrent truncating mutations in cancer. We show that Z18trunc mutations are oncogenic and that Z18 plays an evolutionarily conserved role in nuclear RNA surveillance of ERV RNA. In zebrafish, Z18trunc expedited melanoma onset and promoted a specific accumulation of ERV RNA. Z18 mutant human cell lines from the Cancer Cell Line Encyclopedia also expressed higher levels of ERV RNA. In engineered human melanoma cells, Z18trunc enhanced ERV RNA accumulation more than loss of one Z18 copy, indicating dominant negative activity. Z18trunc directly bound and stabilized ERV RNA. Notably, expression of ERV RNA was sufficient to expedite oncogenesis in a zebrafish model, which is the first evidence of which we are aware that ERV transcripts can play a functional role in cancer. Our work illuminates a mechanism for elevated ERV transcripts in cancer and supports that aberrant RNA accumulation is broadly oncogenic.

cancer biology↗

bioRxiv2024

ProCyon: A multimodal foundation model for protein phenotypes

Characterizing human proteins remains a major challenge: approximately 29% of human proteins lack experimentally validated functions and even well-annotated proteins often lack context-specific phenotypic insights. To enable universal modeling of protein phenotypes, we present PO_SCPLOWROC_SCPLOWCO_SCPLOWYONC_SCPLOW, a multimodal foundation model that utilizes protein sequence, structure, and natural language for generating and predicting protein phenotypes across diverse knowledge domains. PO_SCPLOWROC_SCPLOWCO_SCPLOWYONC_SCPLOW is trained on our novel dataset, PO_SCPLOWROC_SCPLOWCO_SCPLOWYONC_SCPLOW-IO_SCPLOWNSTRUCTC_SCPLOW, with 33 million protein phenotype instructions. On dozens of benchmarking tasks, PO_SCPLOWROC_SCPLOWCO_SCPLOWYONC_SCPLOW performs competitively against single-modal and multimodal models. Further, PO_SCPLOWROC_SCPLOWCO_SCPLOWYONC_SCPLOW conditionally retrieves proteins via mechanisms of action of small molecule drugs and disease contexts, and it generates candidate phenotypic descriptions for poorly characterized proteins, including those implicated in Parkinsons disease that were identified after PO_SCPLOWROC_SCPLOWCO_SCPLOWYONC_SCPLOWs knowledge cutoff date. We experimentally confirm PO_SCPLOWROC_SCPLOWCO_SCPLOWYONC_SCPLOWs predictions in multiple sclerosis using post-mortem brain RNA-seq, identifying novel MS genes and elucidating associated pathway mechanisms consistent with cortical pathology. PO_SCPLOWROC_SCPLOWCO_SCPLOWYONC_SCPLOW paves the way toward a general approach to generate functional insights into the human proteome.

bioinformatics↗

bioRxiv2024

Mitochondrial and Microtubule Defects in Exfoliation Glaucoma

Exfoliation Syndrome (XFS) is an age-related systemic condition characterized by large aggregated fibrillar material deposition in the anterior eye tissues. This aggregate formation and deposition on the aqueous humor outflow pathway are significant risk factors for developing Exfoliation Glaucoma (XFG), a secondary open-angle glaucoma. XFG is a complex, multifactorial late-onset disease that shares common features of neurodegenerative diseases, such as altered cellular processes with increased protein aggregation, impaired protein degradation, and oxidative and cellular stress. XFG patients display decreased mitochondrial membrane potential and mitochondrial DNA deletions. Here, using Tenon Capsule Fibroblasts (TFs) from Normal (No Glaucoma) and XFG patients, we found that XFG TFs have impaired mitochondrial bioenergetics and increased reactive oxygen species (ROS) accumulation. These defects are associated with mitochondrial abnormalities as XFG TFs exhibit smaller mitochondria that contain dysmorphic cristae, with an increase in mitochondrial localization to lysosomes and slowed mitophagy flux. Mitochondrial dysfunction in the XFG TFs was associated with an increase in the dynamics of the microtubule cytoskeleton, decreased acetylated tubulin, and increased HDAC6 activity. Treatment of XFG TFs with a mitophagy inducer, Urolithin A, and a mitochondrial biogenesis inducer, NAD+ precursor, Nicotinamide Ribose, improved mitochondrial bioenergetics and reduced ROS accumulation. Our results demonstrate abnormal mitochondria in XFG TFs and suggest that mitophagy inducers may represent a potential class of therapeutics for reversing mitochondrial dysfunction in XFG patients.

cell biology↗

bioRxiv2024

Optogenetic stimulation of a cortical biohybrid implant guides goal directed behavior

Brain-computer interfaces (BCIs) hold exciting therapeutic potential, but tissue damage caused by probe insertion limits channel count. Biohybrid devices, in which the cell-device interface is crafted in the laboratory, hold promise to address this limitation, but these devices have lacked a demonstration of their applicability for BCI. We developed a biohybrid approach to engraft optogenetically-enabled neurons on the cortical surface housed in a 2D-scaffold of circular microwells. The engrafted neurons survived, exhibited spontaneous activity, and integrated with the host brain several weeks after implantation. We then trained mice with biohybrid implants to perform an optical stimulation task and showed that they could effectively report optogenetic stimulation of their neural graft. This demonstration shows that a cortical biohybrid implant can be used to transmit information to the brain of an implanted animal.

neuroscience↗

bioRxiv2024

Tet2 loss suppress α-synuclein pathology by stimulating ciliogenesis

There are no approved treatments that slow Parkinsons disease (PD) progression and therefore it is important to identify novel pathogenic mechanisms that can be targeted. Loss of the epigenetic marker, Tet2 appears to have some beneficial effects in PD models, but the underlying mechanism of action is not well understood. We performed an unbiased transcriptomic analysis of cortical neurons isolated from patients with PD to identify dysregulated pathways and determine their potential contributions to the disease process. We discovered that genes associated with primary cilia, non-synaptic sensory and signaling organelles, are upregulated in both early and late PD patients. Enhancing ciliogenesis in primary cortical neurons via sonic hedgehog signaling suppressed the accumulation of -synuclein pathology in vitro. Interestingly, deletion of Tet2 in mice also enhanced the expression of primary cilia and sonic hedgehog signaling genes and rescued the accumulation of -synuclein pathology and dopamine neuron degeneration in vivo. Our findings demonstrate the crucial role of Tet2 loss in regulating ciliogenesis and potentially affecting the progression of PD pathology.

neuroscience↗

bioRxiv2024

Scorpio : Enhancing Embeddings to Improve Downstream Analysis of DNA sequences

Analysis of genomic and metagenomic sequences is inherently more challenging than that of amino acid sequences due to the higher divergence among evolutionarily related nucleotide sequences, variable k-mer and codon usage within and among genomes of diverse species, and poorly understood selective constraints. We introduce Scorpio, a versatile framework designed for nucleotide sequences that employs contrastive learning to improve embeddings. By leveraging pre-trained genomic language models and k-mer frequency embeddings, Scorpio demonstrates competitive performance in diverse applications, including taxonomic and gene classification, antimicrobial resistance (AMR) gene identification, and promoter detection. A key strength of Scorpio is its ability to generalize to novel DNA sequences and taxa, addressing a significant limitation of alignment-based methods. Scorpio has been tested on multiple datasets with DNA sequences of varying lengths (long and short) and shows robust inference capabilities. Additionally, we provide an analysis of the biological information underlying this representation, including correlations between codon adaptation index as a gene expression factor, sequence similarity, and taxonomy, as well as the functional and structural information of genes.

genomics↗

bioRxiv2024

Murine Progeria Model Exhibits Delayed Fracture Healing with Dysregulated Local Immune Response

ABSTRACTO_ST_ABSBackgroundC_ST_ABSBone fracture is one of the most globally prevalent injuries, with an estimated 189 million bone fractures occurring annually. Delayed union or nonunion occurs in up to 15% of fractures and involves the interruption or complete failure of bone continuity following fracture. Preclinical testing is essential to support the translation of novel strategies to promote improved fracture repair treatment, but there is a paucity of small animal models that recapitulate clinical attributes associated with delayed fracture healing. This study explores whether the Zmpste24-/- (Z24-/-) knockout mouse model of Hutchinson-Gilford progeria syndrome presents with delayed fracture healing. Leveraging the previously characterized Z24-/- phenotype of genomic instability, epigenetic changes, and fragility, we hypothesize that these underlying alterations will lead to significantly delayed fracture healing relative to age-matched wild type (WT) controls. MethodsWT and Z24-/- mice received intramedullary fixed tibia fractures at [~]12 weeks of age. Mice were sacrificed throughout the time course of repair for the collection of organs that would provide information regarding the local (fracture callus, bone marrow, inguinal lymph nodes) versus peripheral (peripheral blood, contralateral tibia, abdominal organs) tissue microenvironments. Analyses of these specimens include histomorphometry, CT, mechanical strength testing, protein quantification, gene expression analysis, flow cytometry for cellular senescence, and immunophenotyping. ResultsZ24-/- mice demonstrated a significantly delayed rate of healing compared to WT mice with consistently smaller fracture calli containing higher proportion of cartilage and less bone after injury. Cellular senescence and pro-inflammatory cytokines were elevated in the Z24-/- mice before and after fracture. These mice further presented with a dysregulated immune system, exhibiting generally decreased lymphopoiesis and increased myelopoiesis locally in the bone marrow, with more naive and less memory T cell but greater myeloid activation systemically in the peripheral blood. Surprisingly, the ipsilateral lymph nodes had increased T cell activation and other pro-inflammatory NK and myeloid cells, suggesting that elevated myeloid abundance and activation contributes to an injury-specific hyperactivation of T cells. ConclusionTaken together, these data establish the Z24-/- progeria mouse as a model of delayed fracture healing that exhibits decreased bone in the fracture callus, with weaker overall bone quality, immune dysregulation, and increased cellular senescence. Based on this mechanism for delayed healing, we propose this Z24-/- progeria mouse model could be useful in testing novel therapeutics that could address delayed healing. The Translational Potential of this ArticleThis study employs a novel animal model for delayed fracture healing that researchers can use to screen fracture healing therapeutics to address the globally prevalent issue of aberrant fracture healing.

molecular biology↗

bioRxiv2024

deepGOLSA: Goal-directed planning with subgoal reduction models human brain activity

Goal-directed planning presents a challenge for classical RL algorithms due to the vastness of the combinatorial state and goal spaces, while humans and animals adapt to complex environments, especially with diverse, non-stationary objectives, often employing intermediate goals for long-horizon tasks. Here, we propose a goal reduction mechanism for effectively deriving subgoals from arbitrary and distant original goals, using a novel loop-removal technique.1 The product of the method, called goal-reducer, distills high-quality subgoals from a replay buffer, all without the need for prior global environmental knowledge. Simulations show that the goal-reducer can be integrated into RL frameworks like Deep Q-learning and Soft Actor-Critic. It accelerates performance in both discrete and continuous action space tasks, such as grid world navigation and robotic arm manipulation, relative to the corresponding standard RL models. Moreover, the goal-reducer, when combined with a local policy, without iterative training, outperforms its integrated deep RL counterparts in solving a navigation task. This goal reduction mechanism also models human problem-solving. Comparing the models performance and activation with human behavior and fMRI data in a treasure hunting task, we found matching representational patterns between a goal-reducer agents components and corresponding human brain areas, particularly the vmPFC and basal ganglia. The results suggest that humans may use a similar computational framework for goal-directed behaviors.

neuroscience↗

bioRxiv2024

Temporal interference electrical neurostimulation yields fMRI BOLD activation in humans

Temporal interference electrical neurostimulation (TI) is a relatively new method of non-invasive neurostimulation that may be able to stimulate deep brain regions without stimulating the overlying superficial regions. Despite studies in rodents, almost no studies have investigated its effects on human brain activity along with safety and tolerability profiles. We performed simultaneous TI stimulation and fMRI to investigate the effects of TI on human BOLD signals. Here we show that TI can induce increased BOLD activation in humans, with good safety and tolerability profiles. We also show the limits of spatial precision and explore the nature and causes of additional off target effects. TI may be a promising approach for addressing questions about the causal role of deep brain structures in human cognition and may also afford new clinical treatments.

neuroscience↗

bioRxiv2024

Monkey Prefrontal Cortex Learns to Minimize Sequence Prediction Error

In this study, we develop a novel recurrent neural network (RNN) model of pre-frontal cortex that predicts sensory inputs, actions, and outcomes at the next time step. Synaptic weights in the model are adjusted to minimize sequence prediction error, adapting a deep learning rule similar to those of large language models. The model, called Sequence Prediction Error Learning (SPEL), is a simple RNN that predicts world state at the next time step, but that differs from standard RNNs by using its own prediction errors from the previous state predictions as inputs to the hidden units of the network. We show that the time course of sequence prediction errors generated by the model closely matched the activity time courses of populations of neurons in macaque prefrontal cortex. Hidden units in the model responded to combinations of task variables and exhibited sensitivity to changing stimulus probability in ways that closely resembled monkey prefrontal neurons. Moreover, the model generated prolonged response times to infrequent, unexpected events as did monkeys. The results suggest that prefrontal cortex may generate internal models of the temporal structure of the world even during tasks that do not explicitly depend on temporal expectation, using a sequence prediction error minimization learning rule to do so. As such, the SPEL model provides a unified, general-purpose theoretical framework for modeling the lateral prefrontal cortex.

neuroscience↗

bioRxiv2024

Large- and Small-Animal Studies of Safety, Pharmacokinetics (PK), and Biodistribution of Inflammasome-Targeting Nanoligomer in the Brain and Other Target Organs

Immune malfunction or misrecognition of healthy cells and tissue, termed autoimmune disease, is implicated in more than 80 disease conditions and multiple other secondary pathologies. While pan-immunosuppressive therapies like steroids offer some relief for systemic inflammation for some organs, many patients never achieve remission and such drugs do not cross the blood-brain barrier making them ineffective for tackling neuroinflammation. Especially in the brain, unintended activation of microglia and astrocytes is hypothesized to be directly or indirectly responsible for Multiple Sclerosis (MS), Amyotrophic Lateral Sclerosis (ALS), Parkinsons Disease (PD), and Alzheimers Disease (AD). Recent studies have also shown that targeting inflammasome and specific immune targets can be beneficial for these diseases. Further, our previous studies have shown targeting NF-{kappa}B and NLRP3 through brain penetrant Nanoligomer cocktail SB_NI_112 (abbreviated to NI112) can be therapeutic for several neurodegenerative diseases. Here we show safety-toxicity studies, followed by pharmacokinetics (PK) and biodistribution in small- (mice) and large-animal (dog) studies of this inflammasome-targeting Nanoligomer cocktail NI 112. We conducted studies using four different routes of administration: intravenous (IV), subcutaneous (SQ), intraperitoneal (IP), and intranasal (IN), and identified the drug concentration over time using inductively coupled plasma mass spectrometry (ICP-MS) in the blood serum, the brain (including different brain regions), and other target organs like liver, kidney, and colon. Our results indicate the Nanoligomer cocktail has a strong safety profile, and shows high biodistribution (F [~]0.98) and delivery across multiple routes of administration. Further analysis showed high brain bioavailability with a ratio of NI112 in brain tissue to blood serum [~]30%. Our model accurately shows dose scaling, translation between different routes of administration, and interspecies scaling. These results provide an excellent platform for human clinical translation and predicting therapeutic dosage between different routes of administration.

pharmacology and toxicology↗

bioRxiv2024

Dietary tryptophan and genetic susceptibility expand gut microbiota that promote systemic autoimmune activation

Tryptophan modulates disease activity and the composition of microbiota in the B6.Sle1.Sle2.Sle3 (TC) mouse model of lupus. To directly test the effect of tryptophan on the gut microbiome, we transplanted fecal samples from TC and B6 control mice into germ-free or antibiotic-treated non-autoimmune B6 mice that were fed with a high or low tryptophan diet. The recipient mice with TC microbiota and high tryptophan diet had higher levels of immune activation, autoantibody production and intestinal inflammation. A bloom of Ruminococcus gnavus (Rg), a bacterium associated with disease flares in lupus patients, only emerged in the recipients of TC microbiota fed with high tryptophan. Rg depletion in TC mice decreased autoantibody production and increased the frequency of regulatory T cells. Conversely, TC mice colonized with Rg showed higher autoimmune activation. Overall, these results suggest that the interplay of genetic and tryptophan can influence the pathogenesis of lupus through the gut microbiota.

immunology↗

bioRxiv2024

Human coronavirus HKU1 recognition of the TMPRSS2 host receptor

The human coronavirus HKU1 spike (S) glycoprotein engages host cell surface sialoglycans and transmembrane protease serine 2 (TMPRSS2) to initiate infection. The molecular basis of HKU1 binding to TMPRSS2 and determinants of host receptor tropism remain elusive. Here, we designed an active human TMPRSS2 construct enabling high-yield recombinant production in human cells of this key therapeutic target. We determined a cryo-electron microscopy structure of the HKU1 RBD bound to human TMPRSS2 providing a blueprint of the interactions supporting viral entry and explaining the specificity for TMPRSS2 among human type 2 transmembrane serine proteases. We found that human, rat, hamster and camel TMPRSS2 promote HKU1 S-mediated entry into cells and identified key residues governing host receptor usage. Our data show that serum antibodies targeting the HKU1 RBD TMPRSS2 binding-site are key for neutralization and that HKU1 uses conformational masking and glycan shielding to balance immune evasion and receptor engagement.

biochemistry↗

bioRxiv2023

Atypical Cell Cycle Regulation over Neural Stem Cell Expansion

Populations of adult neural stem cells (NSCs) that reside in the mammalian brain aid in neurogenesis throughout life and can be identified by a type VI intermediate filament protein, Nestin. Cell cycle regulation plays an important role in maintaining a balance between self-renewal and differentiation and determining the fate of NSCs. Data from our group and others support that the atypical cyclin-like protein Spy1 (also called RingoA; gene SPDYA) plays a critical role in activating NSCs from a quiescent state. Elevated levels of Spy1 are found in aggressive human brain cancers, including glioblastoma. Using a conditional mouse model, we demonstrate that driving the expression of Spy1, in the Nestin-enriched NSC population of the brain, increases stemness characteristics, decreases differentiation, and increases susceptibility to oncogenic transformation. This study contributes to better understanding of intricate cell cycle mechanisms which lead to deviation from the homeostatic state, promoting aberrant changes in adult NSCs.

molecular biology↗