Biology subjects

Sen, S.

Publications and source records attributed to Sen, S..

At least 37 records · Page 2Linked to original sources

bioRxiv2025

A Quantitative Design Guideline for Biomolecular Positive Feedback Systems

Feedback is at the core of biological systems found in medicine and in biotechnology. While design metaphors from control engineering are widely used to understand negative feedback in such systems, they are relatively uncommon for positive feedback, especially for biomolecular circuits. Here, we extended a block diagram modelling framework for the design of positive feedback. We found a quantitative design guideline for the strength of the positive feedback, which when wrapped around a saturation function can give a threshold and a hysteretic response. The critical feedback strength was inversely proportional to the saturation value and directly proportional to the input scale where saturation starts. We found that this saturation-threshold-hysteresis hierarchy persisted in a realistic model of a positively autoregulated gene. We showed how this classical model fitted well in a block diagram framework with multiplicative feedback and derived expressions for the critical feedback strength in terms of the saturation parameters. The dependence of the critical feedback on the parameters matched with the obtained design guideline. To complete a rigorous workflow, we discussed how Groebner Bases computations and an Interval Newton algorithm can be used to provide validated numerical solutions in biological positive feedback systems. These results should be helpful in the analysis and design of biomolecular systems with applications to the control of biomedical systems and in biotechnology.

systems biology↗

bioRxiv2025

NPM1 mislocalization mediated by RNA Pol I inhibition alters chromatin landscape

RNA polymerase I inhibition affects rRNA synthesis from rDNA clusters residing in nucleolar organizer regions (NORs). Here we have demonstrated RNA Pol I inhibition disrupts nucleolar architecture, NPM1 localization, and alters the chromatin landscape using coordinated eraser and writer enzymes. siRNA mediated depletion or dissociation of NPM1 allows HDAC1 loading on the chromatin. HDAC1 mediated deacetylation of H3K9ac creates H3K9 that undegoes SUV39H1-mediated methylation. The stripping of active histone marks leads to enrichment of repressive H3K9me3 in the genome. These altered chromatin landscape corroborates with loss of genome-wide chromatin accessibility and DNA hypermethylation mediated by DNMT1. Chromatin architectural analysis revealed disrupted nucleolar associated domains (NADs) transforming to lamin associated domains (LADs) with specific histone signatures and repressive states. The 3D nuclear architecture was remodeled by A/B compartments reorganization and loss of Hi-C loops at the H3K9ac depleted sites.

molecular biology↗

bioRxiv2025

XIST Self-regulates its Association with THOC2 and the Nuclear Epigenetic Machinery via miR-186 in Alzheimer's disease

Alzheimers disease (AD) exhibits a strong female bias, yet the underlying molecular basis remains poorly understood. This study identifies the long non-coding RNA (lncRNA) XIST, a master regulator of X-chromosome inactivation (XCI), as a driver of female-specific AD pathology. Single-nucleus RNA-seq (snRNA-seq) analyses from human AD cortex and in vitro AD models reveal elevated and abnormally cytoplasmic XIST, a feature not previously reported in neurodegeneration. Reduced EZH2 levels in AD impair histone H3 lysine-27 trimethylation (H3K27me3) on the inactive X chromosome, disturbing epigenetic silencing. The epigenetic dysregulation elevates the X-linked RNA export factor THOC2, which participates in a feedback loop with XIST. Cytoplasmic XIST functions as a competing endogenous RNA (ceRNA) by sequestering miR-186-5p, thereby rescuing EZH2 and THOC2 transcripts. The resulting XIST/miR-186/EZH2/THOC2 axis couples XIST-driven epigenetic changes with nuclear RNA export pathways via cytoplasmic XIST. Disrupted EZH2-XIST interaction reduces H3K27me3 marks on the inactive X, while increased THOC2 promotes THOC2(TREX)-XIST interaction, maintaining the harmful feedback. Our findings reveal a novel mechanism through which XIST gets recruited to the nuclear RNA export pathways in AD. XIST thus emerges as a critical node in sex-specific AD pathophysiology and a promising target for therapeutic intervention. Graphical Abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=140 SRC="FIGDIR/small/680468v3_ufig1.gif" ALT="Figure 1"> View larger version (41K): org.highwire.dtl.DTLVardef@1d640d9org.highwire.dtl.DTLVardef@13b8c6eorg.highwire.dtl.DTLVardef@809298org.highwire.dtl.DTLVardef@1186899_HPS_FORMAT_FIGEXP M_FIG C_FIG

neuroscience↗

bioRxiv2025

Development of a Serum-Free Producer Cell Line Generation Process for Scalable and Efficient rAAV Production for gene therapy applications

1.The growing field of recombinant Adeno-Associated Virus (rAAV) gene therapy demands scalable and efficient production platforms. Manufacturing platforms based on producer cell lines (PCL) hold substantial promise due to their capacity for high productivity and scalability. However, the generation of stable cell lines for rAAV production is typically performed using serum-containing processes, which pose a risk due to safety and regulatory concerns related to animal-derived components. In this study, we established a fully serum-free process for PCL generation for rAAV production, optimizing critical stages of this process, including transfection methodologies for stable plasmid integration, isolation of highly productive cell pools, and media supplementation to support single-cell cloning. The developed serum-free process generated clonally derived PCLs with productivity and product quality on par with traditional serum-based methods. This approach significantly reduced the cell line generation timeline and eliminated the challenge related to serum supplementation, adapting it to industry requirements. The reported advances overcome a critical step in cell line development for rAAV production, facilitating the implementation of scalable and efficient production platforms to support the development of rAAV-based gene therapies.

bioengineering↗

bioRxiv2025

Design and Characterisation of a Sensor Integrating Chemical and Temperature Inputs for Gene Expression

The modularity of transcription factors has facilitated the development of combinatorial promoters that regulate gene expression in response to chemical inducers. Nevertheless, controlling gene expression by the joint influence of a chemical inducer and an environmental variable, such as temperature, has not been as extensively studied or analyzed. We designed a two-input combinatorial sensor combining the action of a chemical inducer (Anhydrotetracycline, aTc) and temperature. The design was based on transcriptional regulation by the Ptet promoter and translational regulation by an RNA thermometer. The design functioned as an AND Gate, exhibiting a four-fold change between a completely ON state, with aTc at 37 {degrees}C, and a completely OFF state, without aTc at 29 {degrees}C. We mapped the design into a Logic-Symmetry space and found that the design functioned like an AND Gate with an asymmetry of 0.266. This work should contribute to developing a temperature-based combinatorial regulation system.

synthetic biology↗

bioRxiv2025

Cannabinoid Receptor 2 Activating Antibodies: A Promising Therapeutic Strategy for Macrophage-Driven Fibro-Inflammatory Diseases

Fibrotic diseases, often fueled by chronic inflammation, represent a major unmet medical need. A critical driver of this process is the activation of macrophages, which secrete pro-inflammatory cytokines and chemokines, leading to immune cell recruitment and collagen deposition by myofibroblasts. Agonizing the cannabinoid receptor 2 (CB2), expressed on macrophages, offers a potential therapeutic avenue to suppress this activation. Despite widespread interest in CB2 modulation, challenges remain in the development of small molecule agonists, including insufficient specificity and poor drug-like properties. Antibodies are highly specific with favorable pharmacokinetics and bioavailability, but GPCR agonist antibodies have been difficult to discover. Here we present first-in-class CB2 agonist antibodies, AB120 and AB150. These antibodies are CB2 specific, G-alpha biased, and effectively decrease the expression of macrophage activation markers and key pro-inflammatory cytokines, including IL-6, IL-1{beta} and TNF-. Furthermore, using an ex vivo human precision-cut liver slice (hPCLS) model of liver fibrosis, we observe that treatment with these CB2 agonist antibodies not only reduces inflammatory markers but also decreases collagen expression, indicating a potential to halt or reverse fibrosis. These novel CB2-specific agonist antibodies hold promise as therapeutics for a range of fibrotic and inflammatory conditions driven by chronic macrophage activation and demonstrate the potential of GPCR antibody agonists to drug this challenging class of targets. Significance StatementFibrotic diseases driven by chronic inflammation lack effective treatments. CB2 agonism modulates macrophage activation to reduce pro-inflammatory cytokines suggesting a novel avenue of treatment, but small molecule CB2 agonists have faced substantial limitations due to off-target effects. We introduce two novel CB2-specific agonist antibodies with potent anti-inflammatory and anti-fibrotic effects in vitro and in a human ex vivo liver fibrosis model. These antibodies provide a promising new therapeutic strategy and highlight the advantages of antibodies as GPCR agonist drugs.

pharmacology and toxicology↗

bioRxiv2025

Long-acting hydrogel-based depot formulations of tirzepatide and semaglutide for the management of type 2 diabetes and weight

Several incretin hormone therapies have been clinically approved and have revolutionized the treatment of diabetes and obesity. Promising therapeutics include semaglutide (Ozempic(R) and Wegovy(R)), an agonist for glucagon-like peptide-1 (GLP-1) receptor, and tirzepatide (Mounjaro(R)), a dual agonist for GLP-1 and glucose-dependent insulinotropic polypeptide (GIP) receptors. These molecules help to regulate blood glucose levels, enhance insulin secretion and sensitivity, and reduce appetite. Currently, these treatments require weekly injections, which can be challenging for patients to adhere to. We recently reported the development of an injectable hydrogel depot technology enabling months-long release of semaglutide (Sema). Here, we further develop this technology for improved prolonged release of both Sema and tirzepatide (TZP). In a rat model of diabetes, we show a single administration of hydrogel-based formulations of either Sema or TZP maintained relevant drug levels for over 6 weeks. In these studies, single administrations of long-acting hydrogel-based therapies of Sema or TZP were similarly effective at regulating blood glucose and weight compared to daily injections of either Sema or TZP in standard aqueous vehicles. This hydrogel depot technology is easy to manufacture, injectable, and exhibits excellent biocompatibility, enabling months-long-acting treatments with the potential to improve management of diabetes and weight.

bioengineering↗

bioRxiv2025

Phosphoglycerate Kinase Can Adopt a Topologically Misfolded Form that is More Stable than its Native State

The native states of globular proteins are typically viewed as being the most stable conformations on their respective proteins soluble free energy landscapes. This view, known as the Thermodynamic Hypothesis, explains why many proteins can reversibly refold after being denatured. Here we report an intriguing counterexample to this paradigm. When E. coli phosphoglycerate kinase (PGK) is stimulated to refold upon dilution from denaturant, instead of returning to its native state, it populates an unusual misfolded form that is monomeric and native-like, but which is even more kinetically stable than its native form, as based on its resistance to thermal and detergent-induced denaturation. Moreover, this misfolded form cannot self-correct, even for days. We show that the key structural feature of this misfolded form of PGK is topological in nature by demonstrating that kinetically stable misfolded forms do not form any longer if PGK is circularized, which prevents its termini from threading through other portions of the protein. Our findings demonstrate that a misfolded protein need not aggregate or form an amyloid to become stabilized with respect to the native state, and call attention to topologically-misfolded proteins as a potential Achilles heel to the cellular proteostasis network.

biophysics↗

bioRxiv2025

Advancing in silico drug design with Bayesian refinement of AlphaFold models

Virtual screening has become an indispensable tool in modern structure-based drug discovery, enabling the identification of candidate molecules by computationally evaluating their potential to bind target proteins. The accuracy of such screenings critically depends on the quality of the target structures employed. Recent advances in protein structure prediction, particularly AlphaFold2, have revolutionized this field with unprecedented accuracy. However, AlphaFold2 models often exhibit limitations in local structural details, especially within binding pockets, which limit their utility for small molecule docking. In contrast, molecular dynamics simulations with accurate atomistic force fields can refine protein structures, but lack the ability to leverage the structural information provided by deep learning approaches. Here, we introduce bAIes, an integrative method that bridges this gap by combining physics-based force fields with data-driven predictions through Bayesian inference. Crucially, bAIes demonstrates a superior ability to discriminate between binders and non-binders in virtual screening campaigns, outperforming both AlphaFold2 and molecular dynamics-refined models. By enhancing the usability of AlphaFold2 models without requiring extensive experimental or computational resources, bAIes offers a convenient solution to a longstanding challenge in structure-based drug design, potentially accelerating the early phases of drug discovery.

bioinformatics↗

bioRxiv2025

Atomic resolution ensembles of intrinsically disordered and multi-domain proteins with Alphafold

Intrinsically disordered proteins are ubiquitous in biological systems and play essential roles in a wide range of biological processes and diseases. Despite recent advances in high-resolution structural biology techniques and breakthroughs in deep learning-based protein structure prediction, accurately determining structural ensembles of IDPs at atomic resolution remains a major challenge. Here we introduce bAIes, a Bayesian framework that integrates AlphaFold2 predictions with physico-chemical molecular mechanics force fields to generate accurate atomic-resolution ensembles of IDPs. We show that bAIes produces structural ensembles that match a wide range of high- and low-resolution experimental data across diverse systems, achieving accuracy comparable to atomistic molecular dynamics simulations but at a fraction of their computational cost. Furthermore, bAIes outperforms state-of-the-art IDP models based on coarse-grained potentials as well as deep-learning approaches. Our findings pave the way for integrating structural information from modern deep-learning approaches with molecular simulations, advancing ensemble-based understanding of disordered proteins.

bioinformatics↗

bioRxiv2025

Engineering Sustained-Release Broadly Neutralizing Antibody Formulations

Sustained serum levels of broadly neutralizing antibodies (bnAbs) are crucial for effective passive immunization against infectious diseases as protection persists only while these bnAbs remain at adequate concentrations within the body. Current obstacles, such as poor pharmacokinetics (PK) and burdensome administration, must be overcome to make bnAbs a viable option for pre- and post-exposure prophylaxis. In this work, we explore how a polymer-nanoparticle (PNP) hydrogel depot technology can be engineered to prolong protein delivery. In-vivo studies in mice and rats demonstrate prolonged protein release, and modeling efforts predict the impact of both the elimination half-life of the active pharmaceutical ingredient and hydrogel depot volume on overall pharmacokinetics. Moreover, flow cytometry characterization reveals that immune cell infiltration into the hydrogel depot can result in faster-than-expected release of antibody cargo on account of active transport via cellular uptake. We then demonstrate that co-formulation of antibodies with an anti-inflammatory agent reduces cellular infiltration and resulting active transport, further extending delivery and pharmacokinetics. Finally, multicompartmental modeling predicts the human PK profiles of clinically relevant HIV bnAbs delivered via subcutaneous hydrogel injection. These findings aid in the development of next generation hydrogel materials that stabilize and slowly release bnAbs for long-term pre-exposure immunoprophylaxis.

bioengineering↗

bioRxiv2025

Combinatorial mutagenesis of N-terminal sequences reveals unexpected and expanded stability determinants of the Escherichia coli N-degron pathway

Although it is known that residues near the N-terminus can influence protein stability, there has not been a comprehensive effort to document how these penultimate residues impact protein stability in prokaryotes. Here, we utilize combinatorial mutagenesis, cell sorting, and next generation sequencing to perform the deepest sequence coverage screen of the bacterial N-degron pathway of proteolysis. We present nuance and exceptions to the N-terminus (P1) functioning as a primary stability determinant. We reveal stability contributions for P2-P5 motifs, including lowered stability for clustered bulky residues and Gln, and heightened stability for negatively charged residues, Pro, and Gly. We find that P1 Cys can be an N-degron component in a sequence-specific manner. Furthermore, we employ stability-predictive machine learning to identify motifs with unexpected fates. Our work expands the stability determinants of the N-degron pathway with unprecedented granularity, serving as a resource for N-degron identification, N-degron design, and future molecular basis elucidation.

synthetic biology↗

bioRxiv2025

Insights into gallbladder cancer pathogenesis from a living organoid gallbladder cholangiocyte biorepository

Gallbladder cancer (GBC) while rare worldwide has a high prevalence in India. Pathogenesis is unclear and outcomes poor. Gallbladder cholangiocyte organoids (GCOs) or gallbladder carcinoma organoids (GBCOs) were developed and serially propagated from surgically resected gallbladder tissues with benign or malignant diseases, respectively. Patient derived organoids (PDOs) were derived from 15 normal; 58 inflamed; 12 xanthogranulomatous cholecystitis (XGC); 5 pre-invasive neoplasm and 13 invasive malignant gallbladder pathologies. Protocol optimisation achieved 58% (69/119) success in organoid generation and expansion. Organoids maintained tight junction integrity; P-gp pump and enzymatic activity; preserved tissue-specific gene and protein marker expression; histological features and genetic variations. Cryopreserved organoids from 62 patients with primary tissue and high-quality DNA, RNA and protein derivatives have been banked. In gene expression analyses of tissue, XGC samples clustered with malignant subtypes, separate from benign pathologies. Derived XGC organoids showed a similar clustering. Enriched hallmark pathways in XGC support neoplastic change through chronic inflammation. PDOs generated from different gallbladder pathologies are a promising model to investigate the pathogenesis of GBC. Graphical Abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=199 SRC="FIGDIR/small/651639v1_ufig1.gif" ALT="Figure 1"> View larger version (69K): org.highwire.dtl.DTLVardef@465f3dorg.highwire.dtl.DTLVardef@16c5f0org.highwire.dtl.DTLVardef@11d4807org.highwire.dtl.DTLVardef@163d072_HPS_FORMAT_FIGEXP M_FIG C_FIG

cancer biology↗

bioRxiv2025

Genetic Modulation of Lifespan: Dynamic Effects, Sex Differences, and Body Weight Trade-offs

The dynamics of lifespan are shaped by DNA variants that exert effects at different ages. We have mapped genetic loci that modulate age-specific mortality using an actuarial approach. We started with an initial population of 6,438 pubescent siblings and ended with a survivorship of 559 mice that lived to at least 1100 days. Twenty-nine Vita loci dynamically modulate the mean lifespan of survivorships with strong age- and sex-specific effects. Fourteen have relatively steady effects on mortality while other loci act forcefully only early or late in life and with polarities of effects that invert. A distinct set of 19 Soma loci shape the negative correlation between weights of young adults with their life expectancies--much more strongly so in males than females. Another set of 11 Soma loci shape the positive correlation between weights at older ages with life expectancies. The Vita and Soma loci share 289 age-dependent epistatic interactions (LODs [≥]3.8) but fewer than 4% are common to both sexes. We provide two examples of how to move from maps toward potential mechanisms. Our findings provide an empirical bridge between evolutionary theories on aging and genetic and molecular causes. These loci and their interactions are key to begin to understand the impact of interventions that may extend healthy lifespan in mice and even in humans.

genetics↗

bioRxiv2025

PLGA Soya Lecithin Based Hybrid Nanocomposite for Targeted Topical Delivery of Resveratrol in Psoriasis Management

Psoriasis is a recurring autoimmune-driven inflammatory skin disorder characterised by red, scaly, dry skin patches, keratinocyte hyperproliferation and infiltration of inflammatory cells, impacting millions globally. Patients with psoriasis often require repeated treatments with corticosteroids, which are often associated with significant side effects and comorbidities. Therefore, there is a growing need for advanced nanomedicine-based therapeutic approaches. Resveratrol (RSV), a plant-derived polyphenol, has shown promising anti-inflammatory and antioxidant properties for the treatment and management of psoriasis. However, its therapeutic potential is limited due to its poor solubility, low stability, and reduced skin penetration. To overcome these challenges, we have developed dual-carrier conjugated nanoparticles (RSVNPL) composed of soya lecithin and poly(lactic-co-glycolic acid) (PLGA). To further enhance its ease of application and prolong skin residence time, RSVNPL was incorporated into a carbomer 974P-based hydrogel system, forming RSVNPGel. Our formulation demonstrated improved physicochemical properties, including enhanced spreadability, superior skin adhesiveness and stability. Ex vivo skin permeation studies confirmed a significantly higher accumulation of RSV in the epidermis and dermis compared to free drugs. In vivo, efficacy was investigated using imiquimod (IMQ)-induced psoriatic mouse model, where RSVNPGel treatment led to a notable reduction in epidermal thickness, inflammatory cell infiltration, and key histopathological features associated with psoriasis. Additionally, serum biochemical analysis and organ histology established the biocompatibility and safety of the formulation. Overall, RSVNPGel presents a promising nanocarrier-based strategy for the effective topical management of psoriasis, enhancing RSV delivery and therapeutic efficacy while minimizing systemic exposure. Research HighlightsO_LIHybrid nanoparticles composite of soya lecithin and PLGA were developed for RSV delivery. C_LIO_LIThe formulation enhanced skin penetration, retention and created a better skin adhesive profile in psoriatic lesions. C_LIO_LISignificant anti-psoriatic effects were achieved in a preclinical model. C_LIO_LIThe system showed excellent safety and biocompatibility. C_LI Graphical Abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=101 SRC="FIGDIR/small/648585v1_ufig1.gif" ALT="Figure 1"> View larger version (33K): org.highwire.dtl.DTLVardef@e28c4corg.highwire.dtl.DTLVardef@1690c80org.highwire.dtl.DTLVardef@1b3e4bforg.highwire.dtl.DTLVardef@16ec0ad_HPS_FORMAT_FIGEXP M_FIG C_FIG

bioengineering↗

bioRxiv2025

Macrophages maintain signaling fidelity in response to ligand mixtures

As immune sentinel cells, macrophages are required to respond specifically to diverse immune threats and initiate appropriate immune responses. This stimulus-response specificity (SRS) is in part encoded in the signaling dynamics of the NF{kappa}B transcription factor. While experimental stimulus-response studies have typically focused on single defined ligands, in physiological contexts cells are exposed to multi-ligand mixtures. It remains unclear how macrophages combine multi-ligand information and whether they are able to maintain SRS in such complex exposure conditions. Here, we leveraged an established mathematical model that captures the heterogeneous single-cell NF{kappa}B responses of macrophage populations to extend experimental studies with systematic simulations of complex mixtures containing up to five ligands. Live-cell microscopy experiments for some conditions validated model predictions but revealed a discrepancy when TLR3 and TLR9 are stimulated. Refining the model suggested that the observed but unexpected ligand antagonism arises from a limited capacity for endosomal transport which is required for responses to CpG and pIC. With the updated model, we systematically analyzed SRS across all combinatorial-ligand conditions and employed three ways of quantifying SRS involving trajectory decomposition into informative trajectory features or machine learning. Our findings show that macrophages most effectively distinguish single-ligand stimuli, and distinguishability declines as more ligands are combined. However, even in complex combinatorial conditions, macrophages still maintain statistically significant distinguishability. These results indicate a robustness of innate immune response specificity: even in the context of complex exposure conditions, the NF{kappa}B temporal signaling code of macrophages can still classify immune threats to direct an appropriate response. Significance ([≤]120)Macrophages sense diverse pathogens within complex environments and respond appropriately. Experimental studies have found that the NF{kappa}B pathway responds with stimulus-specific dynamics when macrophages are exposed to single ligand stimuli. However, it remains unclear complex contexts might erode this stimulus-specificity. Here we systematically studies NF{kappa}B responses using a mathematical model that provides simulations of the heterogeneous population of single cell responses. We show that although the model is parameterized to single ligand data it can predict the responses to multi-ligand mixtures. Indeed, model validation uncovered signaling antagonism between two ligands and the underlying mechanism. Importantly, we found that NF{kappa}B signaling dynamics distinguish ligands within multi-ligand mixtures indicating a robustness of the NF{kappa}B temporal code that was not previously appreciated.

systems biology↗

bioRxiv2025

Loss of plasma membrane conductance in outside-xylem zone explains non-stomatal control of transpiration

The conventional assumption is that stomatal conductance (gs) dominates the regulation of water and carbon dioxide fluxes between leaves and the atmosphere. Here, a nanoreporter of water status at the mesophyll cell surface and local xylem within intact maize leaves documents significant undersaturation of water vapor in the outside-xylem zone (OXZ) and a large loss of conductance of this zone (goxz) at moderate xylem water stress (no turgor loss). The ratio of the resistances (1/goxz)/(1/gs) serves as a predictive phenotype of undersaturation, non-stomatal regulation of transpiration, errors in standard gas exchange analysis, and an increase of intrinsic water use efficiency (iWUE). Cell-scale access to water status reveals symplasmic-apoplasmic disequilibrium and informs a biophysical model that can explain experimental observations quantitatively based on localization of variable conductance to the plasma membrane. This work opens new paths of inquiry into the molecular basis and functional consequences of non-stomatal regulation of transpiration.

plant biology↗

bioRxiv2025

siRNA-based Therapeutic Candidate Targeting PRDM2 for Inhibition of Lung Cancer Progression

Lung cancer is the leading cause of tumor-related fatalities worldwide. The current precision therapies are effective but target only those molecules that are impacted in a minority of lung cancer patients. Positive Regulatory Domain 2 (PRDM2), a member of the PRDM gene family, also known as Retinoblastoma Interacting Zinc finger (RIZ) protein. RIZ is found to be misregulated in more than 60% of lung cancer patients, representing a significantly affected population when compared to other mutation-prone oncogenic factors. RIZ expresses two contrasting variants, a tumor suppressor RIZ1, and an oncogenic RIZ2 protein. In lung cancer, the RIZ1/RIZ2 ratio alters, and the epigenetic silencing of RIZ1 promotes RIZ2 overexpression. In this study, we used siRNA (ARIZ-047) to knockdown and inhibit the effect of the oncogenic protein RIZ2. Inhibiting RIZ2 with ARIZ-047 treatment increased RIZ1 expression and decreased the viability of a lung cancer cell line (A549). The ARIZ-047 treatment also upregulated the negative regulators of the Wnt signaling pathway and restrained the tumor progression in the xenograft mice model. In conclusion, this study identifies ARIZ-047 as a targeted therapy in lung cancer, which specifically inhibits RIZ2 and suggests the role of the Wnt signaling pathway in RIZ2 overexpression. Graphical Abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=127 SRC="FIGDIR/small/636957v1_ufig1.gif" ALT="Figure 1"> View larger version (30K): org.highwire.dtl.DTLVardef@1a5eb34org.highwire.dtl.DTLVardef@1f4dc2forg.highwire.dtl.DTLVardef@a3ce29org.highwire.dtl.DTLVardef@33f576_HPS_FORMAT_FIGEXP M_FIG C_FIG

cancer biology↗