Biology subjects

Arora, S.

Publications and source records attributed to Arora, S..

At least 19 recordsLinked to original sources

bioRxiv2026

Transcriptomic analysis reveals differential regulation of synaptic components in pediatric and adult brain tumors

Neuronal-cancer cell interactions are a key component of brain tumor pathophysiology, yet many fundamental questions remain unanswered, with even more remaining unasked. Here, we present a comprehensive brain tumor reference map generated from bulk RNA-seq data of ~4,300 adult and pediatric brain tumors, including various glioma subtypes, medulloblastomas, ependymomas, and meningiomas, alongside ~1,400 healthy brain samples. By analyzing synaptic processes and synaptic gene expression across tumor types, we reveal the complexity of neuron-tumor crosstalk and its potential impact on patient survival. Our findings identify key synaptic signaling pathways and dysregulated patterns in brain tumors, including HNRNPH2 upregulation, a key factor in RNA processing and metabolism, in gliomas and medulloblastomas. Additionally, we highlight the role of cholinergic signaling, particularly CHRNA9, as a driver of glioma progression, which is also upregulated in WNT and Group 4 medulloblastomas, ependymomas, and meningiomas. Furthermore, P2 purinergic signaling emerges as a key player in glioma progression. These insights lay the groundwork for future studies exploring whether targeting these pathways could reprogram the tumor microenvironment toward an anti-tumor state, ultimately leading to novel therapeutic strategies and improved patient outcomes.

cancer biology↗

bioRxiv2026

Embeddings from standardized sorghum leaf images capture variation in disease response that human scoring misses

Ordinal scoring of plant disease severity by human raters compresses variation in lesion color, size, and number. Inter-rater variability further complicates comparisons and integrated analyses across environments. We developed a low-cost portable imaging chamber to rapidly image large numbers of leaves under standardized lighting, orientation, and backdrops in the field and employed this system to image more than 11,000 leaves across three states. Embeddings from vision encoders predicted human-assigned disease severity scores. No significant GWAS hits were identified using human-assigned or vegetation-index-based disease severity scores, but GWAS using embeddings identified twelve genomic hotspots controlling leaf appearance. Nine were linked to variation in disease symptom severity. Five hotspots corresponded to previously characterized sorghum genes: all three hotspots not linked to disease and two of the nine that were. Roughly one-third of tested embedding--hotspot associations replicated across at least two states, and twenty replicated across all three. eQTL, PheWAS, and large-effect variant analyses identified single candidate genes with plausible mechanistic links to disease symptom severity for six of the seven hotspots not mapping to characterized genes. These results demonstrate the power of combining scalable, standardized leaf imaging with pretrained image encoders to capture genetically controlled variation in diverse disease symptoms that human ordinal scoring misses.

plant biology↗

bioRxiv2026

A pan-cohort transcriptional landscape of breast cancer maps subtype and microenvironmental programs

Breast cancer comprises heterogeneous transcriptional states that are incompletely captured by discrete clinical or molecular subtype labels. To visualize this heterogeneity in a unified framework, we integrated bulk RNA-seq data from 2,284 patient samples across 13 studies using 18,089 protein coding genes, a harmonized processing pipeline, batch correction, consensus clustering and PaCMAP dimensionality reduction to construct an interactive breast cancer transcriptional landscape. Consensus clustering identified five major regions, which were annotated using PAM50 scores calculated for each sample: Luminal A, Luminal B, HER2 enriched, and two basal associated clusters. The basal clusters separated into an immune rich region marked by T cell-inflamed, tumor-associated macrophages (TAM), and low-purity signatures, and a cell-cycle driven region enriched for proliferation and DNA replication programs. Overlay of marker genes, pathways, kinases, neuronal like signaling programs, cancer associated fibroblasts (CAF) states, and TAM programs revealed spatially organized subtype biology and microenvironmental heterogeneity. Finally, projection of therapy associated resistance signatures identified landscape regions linked to predicted resistance to HER2-targeted therapy and hormone receptor directed endocrine therapies. By enabling interactive exploration of transcriptional states, marker genes, pathways, and therapeutic response programs, this resource provides a community framework for biomarker discovery in breast cancer.

bioinformatics↗

bioRxiv2026

Tirzepatide preserves hematopoietic stem and progenitor cycling while remodeling inflammatory monocytes in obese mice

Obesity expands myeloid progenitors, myelopoiesis and increases the production of monocytes. While weight loss (WL) alleviates aspects of this inflammatory dysregulation, it is not known whether GLP-1 receptor agonists or other traditional modalities of WL differentially modify hematopoietic stem/progenitor cells (HSPCs), hematopoiesis, or inflammatory cell production. To test this, we compared the hematopoietic compartment in lean, obese and weight-reduced mice from tirzepatide treatment and caloric restriction (CR) implemented to match the body weight in both groups. At equal WL, we found CR induced multilineage cytopenias, whereas tirzepatide preserved blood lineages while specifically reducing classical Ly6Chi CCR2+ monocytes. To define the mechanisms underlying these changes we performed single-cell mRNA sequencing of bone marrow HSPCs and mature mononuclear blood cells. CR-HSPCs suppressed gene sets associated with nutrient sensing, proliferation and oxidative phosphorylation (OXPHOS) and exhibited lower inferred cell cycle activity, whereas tirzepatide-HSPCs attenuated these changes. Unlike CR, we found that across progressively differentiated cells from HSPCs to mature blood monocytes, tirzepatide increasingly suppressed OXPHOS and simultaneously shifted the maturation spectrum away from classical monocytes. Following six weeks of tirzepatide withdrawal and weight regain, Ly6Chi CCR2+ monocytes rebounded to levels seen in obese mice. These findings suggest that tirzepatide uncouples WL from the broad hematopoietic suppression seen in CR by preserving progenitor activity but selectively remodeling inflammatory/classical monocytes. We demonstrate that WL modality differentially impacts hematopoietic adaptation and provide evidence that classical monocytes are an effector cell through which tirzepatide may dampen obesity-associated inflammation.

immunology↗

bioRxiv2026

Incomplete Reverse Remodeling of the Tricuspid Valve Leaflets Following Relief of Pressure Overload

Objective(s)Tricuspid valve (TV) remodeling and functional tricuspid regurgitation (FTR) progression during right ventricular (RV) pressure overload and reverse remodeling after resolution of RV afterload is poorly understood. We set out to investigate tricuspid leaflet tissue response to induction and subsequent alleviation of pressure overload in a large animal model of RV failure with FTR. MethodsFifteen healthy adult male Dorset sheep (72{+/-}4 kg) underwent pulmonary artery banding (PAB) to induce RV failure and FTR. After 8 weeks, 7 sheep (PAB, n=7) were terminated, and remaining 8 had the PAB removed (rPAB, n=8) and were followed for another 8 weeks before termination. Both groups underwent epicardial echocardiography and hemodynamic assessment during banding surgery and at terminal operation. Ten healthy sheep served as a control group (CTL, n=10) and underwent terminal procedure only. In all animals, TV leaflets and right ventricular (RV) tissue were harvested at terminal procedure and analyzed histologically and transcriptionally. ResultsTV leaflets in PAB animals showed increased cross-sectional area and ECM alterations, some of which persisted after resolution of RV pressure overload. rPAB valves exhibited distinct ECM composition, with notably altered mucin and fibrin content, suggesting a shift toward matrix stabilization, dissimilar to control and PAB. RNA sequencing uncovered a unique molecular state in rPAB valves, with persistent changes in PRG4, PDE3A, CXCL8, and HLA transcripts. RV tissue also demonstrated a separate remodeling trajectory, with sustained expression of stress-related genes including PDE3A, NAV2, ANFB, and ACTS. These findings indicate that both valve and ventricular tissues retain a persistent remodeled phenotype post-unloading. ConclusionsTV leaflets actively remodel in response to hemodynamic stress and do not fully revert to a normal state after relief of pressure overload. This persistent altered phenotype may represent a biological contribution of the TV leaflets to recurrent TR with implications for long-term outcomes following treatment of FTR. Clinical Perspective What is new?O_LIRelief of right ventricular pressure overload, in a large animal model, resulted in substantial reverse remodeling of the right heart and reduction of tricuspid regurgitation severity, but tricuspid valve leaflets did not return to a normal state. C_LIO_LIReverse remodeled leaflets remained enlarged despite normalization of hemodynamics with an altered extracellular matrix. C_LIO_LICellular proliferation and immune cell infiltration observed during pressure overload resolved after unloading, yet transcriptomic analysis identified a distinct molecular phenotype that differed from both healthy and diseased valves. C_LIO_LITricuspid valve leaflets are active biological participants in the remodeling process and exhibit persistent adaptation or maladaptation after resolution of the initiating hemodynamic stress. C_LI What Are the Clinical Implications?O_LISecondary tricuspid regurgitation should be considered a disease involving both right heart geometry and leaflet biology. C_LIO_LIResolution of the underlying cause of tricuspid regurgitation may not restore leaflet structure and molecular homeostasis. C_LIO_LIPersistent leaflet remodeling may contribute to residual or recurrent tricuspid regurgitation despite successful treatment of pulmonary hypertension or other inciting conditions. C_LIO_LITherapies directed at leaflet remodeling may ultimately complement surgical and transcatheter strategies currently focused on annular and ventricular geometry. C_LI

physiology↗

bioRxiv2026

FABP8/PMP2 is a positive regulator of PNS myelination

Myelin formation in peripheral nerves is orchestrated by axon-derived signals and the ability of Schwann cells to expand lipid-rich membrane. Axonal Neuregulin-1 type III (NRG1t3) is known to promote thicker myelin and is associated with increased lipid abundance in peripheral nerves. NRG1t3 also strongly upregulates peripheral myelin protein 2 (FABP8/PMP2), a fatty acid binding protein in myelinating Schwann cells. Here, we directly tested whether elevating PMP2 in Schwann cells is sufficient to enhance myelin growth in nerves. We generated transgenic mice with Schwann cell-specific PMP2 overexpression and showed that PMP2 overexpression drove significant myelin thickening in peripheral nerves, without altering myelin ultrastructure, impairing nerve conduction, or causing detectable adverse effects despite sustained expression. Strikingly, this hypermyelination occurred without activating canonical promyelinating signaling pathways. Instead, elevated PMP2 selectively enhanced fatty acid uptake in Schwann cells, identifying PMP2 as a dosage sensitive enhancer of myelin growth. These findings suggest that in the absence of axonal signaling-driven upregulation, enhanced PMP2 expression itself promotes myelin membrane expansion and enhanced fatty acid availability that could favor complex lipid synthesis. These findings reveal new role for PMP2 as a regulator for myelin expansion in vivo, highlighting a key link between lipid trafficking and myelin growth.

neuroscience↗

bioRxiv2026

ADMETron: An AI-driven SaaS platform for comprehensive ADMET prediction and compound prioritisation

ONTOSIGHT(R) ADMETron is a high-performance SaaS based AI platform designed for the rapid profiling and visualization of ADMET (Absorption, Distribution, Metabolism, Excretion, and Toxicity) properties. The platform integrates a highly interactive web interface with a robust predictive engine, enabling the batch processing of compounds for high-throughput virtual screening. The core engine employs an ensemble model that combines recurrent neural network (RNN)-derived embeddings from SMILES strings with physicochemical descriptors, which are fed into gradient boosting machines (GBMs). This architecture provides accurate predictions across 34 distinct ADMET endpoints, encompassing critical categories such as physicochemical properties, absorption, CYP450 inhibition, hERG toxicity, and mutagenicity. The platforms superior performance is quantitatively validated by its top-tier ranking on the Therapeutics Data Commons (TDC) ADMET Benchmark Group, demonstrating robustness and generalizability with notable results including 2nd place for Ames mutagenicity (AUROC 0.870) and 2nd place for LD50 (MAE 0.573). In addition to its predictive capabilities, ADMETron introduces a novel SAR analysis framework that enables real-time comparison of multiple compounds and approved drugs through an interactive radar graph visualization. Comparative evaluation against widely used online ADMET platforms demonstrated broader endpoint coverage, including pharmacokinetic, physicochemical, and medicinal chemistry assessments within a unified environment. The combination of benchmark-validated predictive performance, comprehensive ADMET profiling, and advanced visualization tools positions ADMETron as a next-generation platform for virtual screening, lead optimization, and data-driven decision-making in modern drug discovery (https://admetron.partex.ai/).

bioinformatics↗

bioRxiv2026

Beyond Histology: A Unified Transcriptomic Atlas Defines Lung Cancer Biologic States and Subtypes

Lung cancer encompasses multiple histological entities with substantial molecular heterogeneity that remain incompletely resolved at population scale. Here, we constructed a unified reference landscape of lung cancer by analyzing raw RNA sequencing data from 1,824 tumors spanning adenocarcinoma (n=966), squamous cell carcinoma (n=628), small cell lung cancer (n=150), and unclassified non small cell lung cancer (n=80). Following batch correction, samples were analyzed using consensus clustering and visualized with PaCMAP to generate a molecular atlas annotated with clinical and biological metadata. Rather than segregating by pathological diagnosis, tumors organized along conserved transcriptional axes defined by tumor-intrinsic biology including proliferative or metabolic programs and immune-infiltrated states. Consensus clustering resolved nine robust molecular clusters, including an adenocarcinoma-associated subgroup, a neuroendocrine-like adenocarcinoma marked by ASCL1 activation, immune-associated regions, and bifurcation of both small cell and squamous carcinomas into biologically distinct states. Spatially restricted expression of selected clinically relevant transcripts nominated state-specific therapeutic hypotheses requiring future functional and clinical validation. Projection of patient tumors and patient-derived xenografts onto the atlas demonstrated preservation of transcriptional identity and enabled quantitative assessment of model fidelity. This integrated framework organizes lung cancer as a structured continuum of transcriptional states and provides a reference resource for biological interpretation and future translational studies.

bioinformatics↗

bioRxiv2026

Multi-Objective Bayesian Optimization for Data-Efficient Bioprocess Development

Process optimization for Chinese hamster ovary (CHO) cell culture remains a challenge in biopharmaceutical development because multiple interacting parameters jointly influence productivity and product quality attributes. Traditional design-of-experiments (DoE) methods, while systematic, become impractically expensive when extended across multiple parameters and clones. To address this challenge, we developed a multi-objective Bayesian Optimization (BO) framework that identifies optimal process conditions efficiently in grouped recommendations, which is well suited for experimental workflows in bioprocess development. The model integrates continuous variables such as pH, DO, temperature, and feed rate with categorical identifiers to enable knowledge transfer across clones and scales, optimizing titer, glycan profile, and charge variants. We validated the framework through in-silico benchmarks on analytic functions, retrospective cross-validation on historical CHO datasets, and forward experimental validation in small-scale bioreactors. Across these tests, our algorithm consistently outperformed Latin Hypercube Sampling (LHS) and Random Search baselines, achieving superior performance under a limited experimental budget. The framework improved titer by up to 37% under single-objective optimization. In the multi-objective setting, it increased titer by 25% while simultaneously reducing overall glycan-profile error by a factor of seven, demonstrating the ability to optimize multiple biologically coupled objectives simultaneously. Through comprehensive in-silico and experimental validation, this study establishes a framework that enables adaptive, AI-guided process development and improves decision-making across multiple objectives, clones, and scales while minimizing experimental runs in process development and optimization workflows.

bioengineering↗

bioRxiv2025

PTEN deficiency linked to chromosome 10q loss leads to aggressive NF2mutant meningioma biology

While most meningiomas are benign and can be surgically removed, a subset behaves aggressively, recurs quickly, and can ultimately be fatal. Recent work has focused on defining this aggressive group. To better characterize this clinically distinct, high-risk group, we analyzed bulk RNA sequencing (RNA-seq) from human meningiomas using a dimension-reduced reference landscape. We identified an NF2 mutant subtype enriched for chromosome 10q loss and low PTEN expression, both of which were strongly associated with shorter time to recurrence. To directly test causality, we engineered several genetically accurate, immunocompetent in vitro and in vivo mouse models with Pten knockdown or knockout. Across models, Pten loss markedly accelerated YAP1-driven tumorigenesis. Projection of Pten-deficient mouse tumors onto bulk and single-cell RNA-seq datasets from human meningiomas revealed that mouse tumors faithfully recapitulate the transcriptional programs of aggressive NF2 mutant meningiomas and robustly predicted clinical outcomes. Collectively, these findings demonstrate that PTEN loss cooperates with YAP1 activation to drive aggressive NF2 mutant meningioma biology, and that the high fidelity of this model to human disease establishes it as a robust platform for mechanistic investigation and therapeutic testing. More broadly, this work highlights the power of cross-species integration in both validating preclinical models and enhancing the translational relevance and utility of dimension-reduced reference landscapes across diverse disease types. One Sentence SummaryPTEN loss causally drives aggressive NF2 mutant meningiomas, and cross-species integration provides a novel, high-fidelity system to validate preclinical models to human disease.

cancer biology↗

bioRxiv2025

Chemical Dice Integrator (CDI): A Scalable Framework for Multimodal Molecular Representation Learning

The machine learning landscape for molecular property prediction is fragmented, with numerous Featurizers each capturing a narrow, specialized view of chemical structure. This heterogeneity forces a suboptimal choice of representation a priori, limiting model generalizability. We introduce the Chemical Dice Integrator (CDI), a hierarchical framework that unifies six orthogonal molecular representations, physicochemical (Mordred), topological (GROVER), visual (ImageMol), biological (Signaturizer), quantum-mechanical (MOPAC), and linguistic (ChemBERTa), into a single, coherent embedding. The framework consists of CDI-Basic, a two-tiered autoencoder that fuses these modalities, and CDI-Generalised, a Mamba State-Space Model (SSM) that learns a direct, efficient map from SMILES strings to the unified embedding space. Extensive benchmarking across 23 classification (171 tasks) and 10 regression datasets demonstrates that CDI embeddings consistently achieve superior predictive performance compared to individual Featurizers and standard feature aggregation methods. The CDI-Generalised model achieves this performance with exceptional computational efficiency, outperforming deep learning Featurizers in terms of speed and resource overhead. Furthermore, we demonstrate that the CDI embedding is chemically intuitive, allowing for the sensitive distinction of nuanced structural variants, such as chiral enantiomers and kekulized SMILES forms. By bridging multimodal chemical intelligence with scalable, sequence-based inference, CDI offers a strong foundation for molecular machine learning.

bioinformatics↗

bioRxiv2025

Elucidating Neurodevelopmental Trajectories in Cancer with Topic Modeling: Revealing Persistent External Granule Layer Lineages in Medulloblastoma

Single-cell transcriptomics transformed our understanding of cellular heterogeneity, yet cross-dataset comparison remains fundamentally limited by batch effects, technology differences, and inconsistent annotation frameworks. These challenges have impeded efforts to connect developmental programs with disease states which creates a critical gap for understanding pediatric cancers with suspected developmental origins. Here, we demonstrate that topic modeling, an unsupervised natural language processing technique, overcomes these barriers by learning transferable transcriptional genetic signatures that generalize across datasets, technologies, and biological contexts without requiring data integration. Applying this framework to over one million fetal cerebellar nuclei, we identify seven distinct topics that capture the developmental spectrum of rhombic lip progenitors through external granule layer (EGL) differentiation, including transitional states missed by conventional clustering. These topics transfer successfully across sequencing technologies (SPLiT-seq to sci-RNA-seq3), developmental timepoints, species (human to mouse), and from single-cell to bulk RNA sequencing of 876 medulloblastoma tumors. We reveal that Sonic hedgehog (SHH) medulloblastoma subtypes retain these topics, corresponding to distinct stages of EGL development. Our findings highlight that developmental timing at tumor initiation fundamentally shapes tumor biology, with immediate implications for subtype-specific therapeutic strategies in pediatric brain cancer. Our workflow establishes topic modeling as a scalable solution for mining expanding genomic atlases with broad applications across different datasets, technologies, and biological contexts.

bioinformatics↗

bioRxiv2025

N6-methyladenosine regulation of mRNA translation is essential for early human erythropoiesis

N6-methyladenosine (m6A) is an abundant modification of mRNA with important regulatory roles in normal and malignant hematopoiesis. We previously reported that in human erythroid leukemia (HEL) cells, m6A mRNA marking selectively regulates translation of essential erythropoiesis genes required for in vitro differentiation and human erythroid colony formation. Here, we further investigated the timing and nature of requirement for m6A-methyltransferase (MTase) activity during human erythropoiesis, using a standardized in vitro erythroid differentiation assay for hHSPCs. We identified two critical m6A regulated developmental windows in BFU-E and during the transition from CFU-E to proerythroblasts. These windows of m6A-MTase requirement coincide with rising global m6A levels, which peak in proerythroblasts. After proerythroblast formation, however, m6A -MTase activity is dispensable for differentiation, proliferation, and survival. In BFU-E, m6A-MTase promotes proliferation but is dispensable for differentiation, while, in CFU-E, both m6A -MTase and the YTHDF family of m6A readers are essential for differentiation to proerythroblasts. Mechanistically, in CFU-E, m6A MTase activity enhances translation of ribosomal and oxidative phosphorylation (OXPHOS) genes, thereby elevating global protein synthesis rates and enabling efficient erythroblast formation. We propose that this form of translational regulation by m6A emerged as an evolutionary adaptation to meet the high translational demands of human erythropoiesis.

developmental biology↗

bioRxiv2025

A Triple-Hit Alcoholic Liver Disease Model Linking High-Fat Diet, Endotoxins, and Neo-Antigen Formation

BACKGROUNDExisting rodent models of alcoholic liver disease (ALD) often fail to replicate its full clinical progression--from steatosis to alcoholic hepatitis and ultimately cirrhosis--and overlook key metabolic contributors. Clinically, high-fat diets and gut-derived endotoxins (from enteric dysbiosis) act as additional "hits" that exacerbate alcohol-induced liver injury. Moreover, alcohol metabolism generates oxidative stress and modifies self-proteins into neo-antigens, potentially triggering immune responses. A model that incorporates these elements is critical for studying ALD pathogenesis and its immunological aspects. METHODSMale Wistar rats were randomized into four groups. The AL group received alcohol (36% caloric equivalent) and a single LPS dose (1 {micro}g/kg) 24 hours before sacrifice. The AF group was fed a high-fat diet (35% caloric equivalent) for 15 days, then maintained on alcohol and fat. The ALF group was similarly primed with fat, maintained on alcohol and fat, and given LPS prior to sacrifice. The ICC group served as isocaloric controls. Liver injury was assessed via histology, biochemical markers (AST, ALT, MDA), and serum endotoxin levels. Antibody titers against liver proteins were analyzed by ELISA; neo-antigens were identified using proteomics. RESULTSAll treated groups showed elevated liver enzymes, MDA, and endotoxin levels, indicating progressive liver damage. The ALF group exhibited the most severe pathology within six weeks, progressing from steatosis to steatohepatitis and fibrosis. In contrast, the AF group showed steatosis alone, and the AL group displayed moderate inflammation. Neo-antigens were most abundant in the ALF group. CONCLUSIONWe present a novel, rapid-onset triple-hit model of ALD that mimics the diseases full spectrum. This model enables mechanistic studies on how diet and gut-derived endotoxins contribute to ALD and highlights the immunogenic potential of alcohol-induced neo-antigens.

immunology↗

bioRxiv2025

CRISPR-mediated transcriptional activation as a mutation-independent therapeutic strategy for SYNGAP1-related intellectual disability

Synaptic Ras GTPase-activating protein (SynGAP) regulates synaptic strength and neuronal signaling, with essential roles in cortical development and synaptic plasticity. Heterozygous loss-of-function variants in SYNGAP1 cause SYNGAP1-related intellectual disability (SRID), a severe neurodevelopmental disorder characterized by epilepsy, developmental delay, and autism. SYNGAP1 mutations often result in haploinsufficiency, providing a strong rationale for gene-targeted therapies. However, no treatment currently addresses the underlying genetic cause of SRID. Here, we developed a CRISPR-mediated transcriptional activation (CRISPRa) approach to upregulate the functional Syngap1 allele in a SRID mouse model. CRISPRa activated Syngap1, normalized SynGAP protein expression and downstream signaling, and rescued working memory deficits. We validated the translational potential of this strategy in human induced pluripotent stem cell (hiPSC)-derived excitatory cortical neurons. CRISPRa rescued SYNGAP1 in two distinct loss-of-function variant lines. Together, these findings demonstrate the feasibility of mutation-independent transcriptional activation as a therapeutic approach for SRID and its broader applicability to haploinsufficiency disorders.

neuroscience↗

bioRxiv2025

Characterization of quiescent subpopulations and proliferative compartments in glioblastoma

Glioblastoma (GBM) quiescent (Q) cell populations are hypothesized to contain cancer stem-like cells (CSC) that drive tumor growth, cellular heterogeneity, and recurrence. However, GBM tumors do not neatly resolve into developmental hierarchies and Q stem-like activities are difficult to assess. Here, we evaluated tumor Q subpopulations in patient-derived GBM xenograft tumors using live cell reporters, DNA label retention assays, and single cell genomics. Compared to adult neural stems cells (NSCs), GBM Q populations contain hybrid transcriptional states composed of networks found in both dormant and activated adult NSCs, resulting in constitutive expression of key Q egress transcription factors and their targets (e.g., AP-1 and CCND1/2). As a result, even the longest Q-residing cells ([~]12 days) in xenograft tumors continuously cycle and fail to enter dormant Q states. We provide evidence and hypothesize that transient Q states in primary tumors arise as part of distinct proliferative compartments rather than deterministic developmental hierarchies driven by CSC activity. We further speculate that increases in basal translation rates drive Q instability in GBM tumors.

cancer biology↗

bioRxiv2025

Intracellular Delivery of Full Length Antibodies via Poly-L-lysine-Coated PEG b PLGA Polymersomes Enables Non-invasive Pulmonary Immunotherapy

The intracellular delivery of full-length antibodies holds transformative potential for treating a range of diseases but is hindered by poor cellular uptake, extracellular degradation, and limited encapsulation strategies. Here, we report a non-invasive, scalable, and biocompatible nanocarrier system using poly-L-lysine (PLL)-coated PEG-PLGA polymersomes to encapsulate and deliver full-length antibodies intracellularly via passive diffusion. Coating with 30 kDa {varepsilon}-poly-L-lysine enhanced antibody loading efficiency by modulating membrane permeability and reduced vesicle surface charge, facilitating endocytic uptake while preserving antibody activity. The resulting polymersomes exhibited no detectable cytotoxicity and enabled efficient aerosol-based pulmonary delivery to lung epithelial cells in vitro. To our knowledge, this is the first demonstration of using PLL-coated PEG-PLGA polymersomes for passive intracellular delivery of full-length antibodies. This platform opens new avenues for lung-targeted immunotherapy and broadens the translational potential of intracellular antibody therapeutics. Graphical Abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=84 SRC="FIGDIR/small/676558v1_ufig1.gif" ALT="Figure 1"> View larger version (21K): org.highwire.dtl.DTLVardef@e4e1cdorg.highwire.dtl.DTLVardef@a46058org.highwire.dtl.DTLVardef@1b134d0org.highwire.dtl.DTLVardef@1024cc3_HPS_FORMAT_FIGEXP M_FIG C_FIG HighlightsO_LIPLL coating enhances passive antibody encapsulation efficiency C_LIO_LIPLL-coated polymersomes exhibit tunable, biocompatible surface charge profiles C_LIO_LIEfficient intracellular delivery of full-length antibodies via aerosol-mediated uptake in pulmonary epithelial cells C_LIO_LIFunctional preservation of antibodies post-delivery validates PLL-PEG-PLGA as a protective nanocarrier C_LI

bioengineering↗

bioRxiv2025

A dominant role of cell death in limiting Chandipura virus propagation at cell-saturating high multiplicity of infection

Viruses transit from a low to high multiplicity of infection (MOI) regime in infected tissues. Type-1 interferons (IFNs) enforce a cellular state refractory to virus multiplication, while the death of infected cells eliminates viral replicative niche. Here, we investigated how these two innate antiviral mechanisms cooperate at various MOIs upon cell infection by Chandipura virus (CHPV), a cytopathic RNA virus implicated in several outbreaks of acute encephalitis in India. We found that as expected, a gradual increase in the input MOI from 0.02 to 2 led to a proportionate surge in the viral yield. Surprisingly, a further rise to MOI 20 caused a reduction in the progeny titer. Our mathematical modeling together with ex vivo infection studies involving mutant cells suggested that cell death - more so than virus-induced type-1 IFNs - restricted CHPV propagation at cell-saturating high MOIs, leading to a net fall in the yield at MOI 20. We argue that the distinct involvement of innate immune pathways at varied MOIs imparts robust cellular defense against cytopathic viruses. Significance sentenceCell death - more so than type-1 interferons - limits Chandipura virus propagation at cell-saturating high multiplicity of infection. Highlights# Type-1 IFNs and cell death cooperate at varied MOI in limiting CHPV multiplication. # At sub-saturating low MOI, type-1 IFNs play a dominant role in controlling CHPV propagation. # At cell-saturating high MOI, cell death determines the progeny yield.

systems biology↗