Biology subjects

Xia, S.

Publications and source records attributed to Xia, S..

At least 19 recordsLinked to original sources

bioRxiv2026

The human-specific lncRNA HD-LINC drives lipid droplet-associated neurodegeneration in Huntington's disease

Huntington's disease (HD) is characterized by degeneration of striatal medium spiny neurons (MSNs), yet the human-specific regulatory mechanisms that contribute to neuronal vulnerability remain poorly understood. Here, we identify HD-LINC (LINC01139), a human-specific long intergenic noncoding RNA selectively induced in symptomatic HD patient-derived MSNs (HD-MSNs) and human HD caudate. Single-cell transcriptomic analysis in HD-MSNs revealed that HD-LINC was enriched in a symptomatic HD neuronal state associated with lipid metabolic and protein clearance regulation, while not observed in non-degenerative reprogrammed MSNs derived from pre-manifest HD individuals. Reducing HD-LINC attenuated mutant HTT aggregation, dystrophic neurites, DNA damage, and neuronal death, whereas HD-LINC overexpression exacerbated these phenotypes. Transcriptomic and lipidomic analyses further implicated HD-LINC in neuronal lipid regulation. We found that HD-MSNs exhibited aberrant accumulation of enlarged, low-mobility lipid droplets (LDs) within neurites, a previously unrecognized phenotype in patient-derived neurons. Critically, increased lipid peroxidation was observed within LD-enriched dystrophic neurites in HD-MSNs. HD-LINC knockdown cleared neuritic LD accumulation, restored soma-enriched LD distribution, and reduced lipid peroxidation. Finally, we developed antisense oligonucleotides that effectively reduced HD-LINC and reversed HD-LINC-associated phenotypes, nominating HD-LINC lowering as a potential therapeutic strategy in HD. These results identify HD-LINC as a human-specific regulator of neuronal LD spatial organization, lipid peroxidation, and neuronal degeneration in HD. They further reveal dysregulated neuritic LD accumulation driven by HD-LINC, and highlight lincRNA-mediated lipid dysregulation as a significant contributor to neuronal vulnerability to degeneration.

neuroscience↗

bioRxiv2026

PlantRegMoD: An integrative and AI-driven multi-omics database for plant regeneration research

Plant regeneration underpins plant developmental plasticity, tissue culture, genetic transformation and crop improvement. Although numerous related omics datasets have been generated, specialized multi-omics databases for this field are still scarce. Here, we constructed PlantRegMoD, an AI-powered integrated database dedicated to plant regeneration. This platform hosts 20.54 TB standardized multi-omics data from 147 projects across 32 plant species and 2,593 samples. We established a unified hierarchical classification system covering five major categories and nine regeneration models, and curated 236 regeneration genes as well as their 28,190 homologs across 58 representative plant species. It contains extensive transcriptomic resources across all regeneration models, together with 196,423 single cells and over 8.81 million epigenetic peaks to dissect cellular heterogeneity and multi-layered epigenetic regulation. Equipped with nine online omics-related tools and a RAG-based intelligent Q&A system, PlantRegMoD greatly reduces bioinformatic barriers and serves as a robust resource for mechanistic, functional and evolutionary studies of plant regeneration.

plant biology↗

bioRxiv2026

Capsid-specialized protein language models reveal higher-order viral architecture from sequence

Viral capsid proteins preserve information on higher-order shell architecture and deep evolutionary history, yet current capsid annotation relies predominantly on homology-based methods that have reduced sensitivity across highly divergent environmental sequences. Here we develop ESMCapsid, a capsid-specialized protein language model for remote capsid detection and architecture-aware representation learning. Screening 343 million representative metagenomic protein clusters revealed a large homology-dark capsid repertoire, with approximately 62% of candidates lacking matches to existing reference databases. Sparse autoencoder decomposition identified recurrent semantic motifs linking homology-dark proteins to known structural lineages, suggesting that interpretable higher-order architectural information can be recovered directly from capsid sequences at metagenomic scale. Mapping conserved motif cores onto resolved viral shells showed spatial clustering and restricted radial positions, indicating that ESMCapsid captures geometric constraints beyond sequence similarity alone. Together, our findings establish a sequence-based route to organize homology-dark viral diversity through conserved architectural principles, extending viral discovery beyond sequence homology.

microbiology↗

bioRxiv2026

The HES1-SOD1 Antagonism Shapes Senescence Heterogeneity and Impacts Metastatic Relapse of Circulating Tumor Cells

Circulating tumor cells (CTCs) encounter multiple challenges within the blood microenvironment, including oxidative stress, flow shear forces, and immune surveillance, often leading to anoikis. Recently, a transitional state of CTC senescence has been identified, contributing to metastatic inefficiency. However, the molecular mechanisms linking senescent CTCs to disease relapse remain to be defined. By integrating a genetic model of cortactin knockdown-induced CTC senescence with single-cell multi-omic analyses, we revealed two distinct senescent CTC subpopulations marked by HES1 expression levels. These HES1low and HES1high subpopulations exhibited differential evolutionary trajectory dynamics and unique molecular and metabolic signatures, which were significantly correlated with adverse clinical outcome across several patient cohorts. HES1low senescent CTCs displayed enhanced mitochondrial fitness, oxidative phosphorylation, and ROS-detoxifying capabilities, resulting in more efficient tumor regrowth with a pro-inflammatory and thrombotic phenotype when compared to the HES1high group. Mechanistically, HES1 directly bound to the Sod1 promoter and repressed its expression, leading to redox imbalance and mitochondrial dysfunction that were linked to weakened tumor regrowth capacity. Both senescent CTC subpopulations were broadly resistant to cytotoxic and targeted therapies, yet they showed elevated dependency on anti-apoptosis programs that make them susceptible to dual blockade by SOD1 inhibitor and the anti-senolytic drug ABT737 in vivo. Finally, in a prospective cohort of on-treatment melanoma patients, HES1 senescent CTCs were highly enriched in patients with progressive disease. Thus, the HES1-SOD1 antagonism shapes CTC senescence heterogeneity and contributes to differential tumor relapse, which can be therapeutically explored for eliminating residual metastatic disease.

cancer biology↗

bioRxiv2026

BTK promotes neuroinflammation by interacting with hub genes and modulating microglia following intracerebral hemorrhage

Brutons tyrosine kinase (BTK) has been reported to be important in the inflammatory response in many diseases. However, its role and explicit mechanisms in intracerebral hemorrhage (ICH) remain unclear. Here, we used a mouse ICH model and transcriptomic datasets to explore the effect of BTK on neuroinflammation after ICH. Inhibiting BTK with ibrutinib alleviated ICH-induced neurological deficits and neuroinflammation in mice. After analyzing RNA-sequencing data of ICH and control mice by weighted gene co-expression network analysis (WGCNA) and protein-protein interaction (PPI) analysis, we found that Btk was a hub gene in the green dynamic module. Also, 12 hub genes that closely interacted with BTK were identified in the key gene module, all having a critical role in the inflammatory process. Then, single cell RNA-sequencing data analysis showed that microglia were the immune cells that expressed the most BTK in the mouse brain. After dividing microglia in ICH mice into BTK_high and BTK_low groups, GO/KEGG enrichment analyses of differentially expressed genes (DEGs) between these two microglia groups revealed that most of the top 30 enriched pathways were immune-related. Then, gene set enrichment analysis (GSEA) of the BTK_high and BTK_low microglia showed that the expression levels of four anti-inflammatory and phagocytosis-related pathways were significantly lower in the BTK_high microglia than in the BTK_low microglia. Furthermore, gene set variation analysis (GSVA) demonstrated that multiple immune pathways were expressed differentially between the two microglia groups. Also, six microglia polarization scores were calculated, and the results showed that the BTK_high microglia tend to polarize towards M1 and M2b states, while the BTK_high microglia towards M2 (M2a, M2c) states. Finally, intercellular communication analysis was conducted, and BTK was revealed to promote communication between microglia and other immune cells both at the general level and in specific inflammatory pathways. In conclusion, our study showed that BTK is critical in promoting post-ICH neuroinflammation, at least partly by interacting with Btk-related hub genes and modulating microglias immune pathways, polarization, and intercellular communication.

neuroscience↗

bioRxiv2026

Healthcare Infrastructure Shapes Evolutionary Trade-offs and Geographic Dissemination of Multidrug-Resistant Acinetobacter baumannii

Antimicrobial-resistant pathogens pose an existential threat to modern medicine, yet the evolutionary forces driving their adaptation in healthcare systems remain largely unexplored. We revealed that hospital network architecture functions as a primary selective pressure, driving pathogen evolution through infrastructure-dependent virulence-transmission trade-offs. Phylogenomic analysis of 5,023 Acinetobacter baumannii isolates across Chinas centralized healthcare system identifies two co-existing evolutionary strategies: a virulence-optimized clade (ESL2.4) that spread slowly (20.4 km per year) in low-connectivity hospitals, and a transmission-optimized clade (ESL2.5) that disseminate rapidly (65.2 km per year) through mega-city healthcare hubs, likely attributed to its capsule conversion and increased upper respiratory colonization. Comparative analysis with European A. baumannii populations demonstrates that healthcare connectivity, not geography, governs pathogen distribution through convergent genomic adaptations. Our simulation suggests competitive asymmetries of the two clades, following the ecotype principle and enabling stable coexistence. The COVID-19 pandemic provided a natural experiment validating these mechanisms: outpatient restrictions reduced transmission-optimized lineage spread by 89%, while virulence-optimized lineage persisted through inpatient networks. These findings establish healthcare infrastructure as a critical evolutionary driver with immediate implications for predicting and controlling antimicrobial resistance emergence across diverse healthcare systems.

microbiology↗

bioRxiv2025

Sex-biased duplicates are rapidly generated during Drosophila tRNA repertoire evolution

Eukaryotic genomes encode hundreds of transfer RNA genes ostensibly to ensure efficient translation. How these seemingly redundant tRNA copies arise and are naturally selected in metazoan genomes and populations remains largely unexplored, owing to challenges in accurate sequencing of tRNA loci and their transcripts. We leveraged long-read genome assemblies of 24 Drosophilid species to infer the origination times of the entire Drosophila melanogaster tRNA gene repertoire and found that continuous gain and loss of tRNA duplicates throughout 60 million years of divergence has resulted in rapid taxonomic restriction of isodecoding and isoaccepting copies--even producing one isodecoder specific to D. melanogaster. Moreover, we identified patterns of global codon usage, especially in lineage-specific genes, incongruous with translational efficiency hypotheses. Through generation of tRNA sequencing in D. melanogaster we observed that recently duplicated, taxonomically restricted tRNA copies had sexually dimorphic patterns of expression, fragmentation, and nucleoside modification. Our work implicates the emergence of taxonomically restricted tRNA genes as sources of regulatory diversity and reveals that sexual and natural selection affect the evolutionary dynamics of the tRNA gene family in metazoan species.

evolutionary biology↗

bioRxiv2025

Captamer: A Novel Quantitative Protein Detecting Method Depending on Aptamer-activated Molecular Switches and RPA Signal Amplification

There are various protein assays for specific and quantitative detection and widely used for laboratory and clinic purposes, but current methods still have limitations. Immunoassays based on antibodies, like ELISA, suffer from slow response and a long antibody-screening period, while physical or electrochemical methods are generally restricted by high cost or the stringent requirement of equipment or operating skills. In this study, we developed an in vitro sensitive protein quantification method: Captamer. The Captamer system comprises a molecular switch derived from aptamer sequence and an exponential fluorescence signal amplification pathway based on recombinase polymerase amplification (RPA). We demonstrated the Captamer for SARS-CoV-2 nucleocapsid protein detection and obtained results from samples within 30 min, displaying a wide detection window from 0.2 pg/mL to 200 pg/mL with high specificity. Furthermore, we tested the Captamer for Tau441 protein (a potential Alzheimers disease biomarker) and thrombin (a classic aptamer-protein interaction model), showing the limit of detection as low as 1 ng/mL and 0.02pg/mL respectively, which suggested the capacity of Captamer to be applied to various aptamer-protein pairs. Compared with the most commonly used and recently reported protein quantification methods, Captamer stands out for its high sensitivity, short response time, low cost, and simplicity, indicating its great potential to be widely used in protein quantification. O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=131 SRC="FIGDIR/small/686180v1_ufig1.gif" ALT="Figure 1"> View larger version (32K): org.highwire.dtl.DTLVardef@1e38ffaorg.highwire.dtl.DTLVardef@1019e72org.highwire.dtl.DTLVardef@1498b68org.highwire.dtl.DTLVardef@15f5ea2_HPS_FORMAT_FIGEXP M_FIG C_FIG

biochemistry↗

bioRxiv2025

Evolutionary landscape of oral microbiome over 100,000 years

The human oral microbiome represents an intimate and enduring partnership between host and microbial communities, yet its evolutionary trajectory across deep time remains largely uncovered. Here we reconstruct the global history of the oral microbiome over 102,400 years using a global collection of 1854 oral samples spanning 61 countries. We reveal that major cultural transitions of the Neolithic Revolution, industrialization, and recent medical advances have driven a directional, globally coordinated co-evolution of oral microbial ecology, function, and population structure. Network analysis identifies two universal microbial modules of dental calculus modules: the commensal-enriched DCM1 module and the pathogen-enriched DCM2, both exhibiting progressive ecological polarization. DCM2 surged around 4,000 years ago with agricultural intensification but subsequently declined in modern European populations while persisting at high levels in African and some American groups, a geographic divide mirroring socioeconomic inequities. Species-level analyses demonstrate widespread directional changes, with obligate anaerobes declining as aerotolerant taxa expand, reflecting a carbohydrate-associated functional remodeling toward starch metabolism. Phylogenomic reconstruction reveals contrasting evolutionary trajectories. Pauljensenia mediterranea experienced near-extinction following a severe bottleneck, while Actinomyces israelii underwent a selective sweep with rapid population expansion 1,000 years ago. Critically, the oral resistome has accelerated in the antibiotic era, resulting in [~]33-50-fold surge of highly mobile, clinically relevant antimicrobial resistance genes in the last century, with Streptococcus acting as a central hub of dissemination. Collectively, these results position the oral microbiome as an active participant that has co-evolved with human subsistence, urbanization and medical practice, with direct implications for global oral health, antimicrobial resistance and interventions aimed at restoring resilient microbial states.

microbiology↗

bioRxiv2025

Distinct and compensatory roles of Stag1 and Stag2 in post-mitotic genome refolding

The three-dimensional architecture of the eukaryotic genome is largely shaped by the cohesin complex, which contains either Stag1 or Stag2 subunits. Although both subunits contribute to chromatin organization, their specific functions in de novo loop formation during post-mitotic genome refolding remain elusive. Here, we leverage the mitosis-to-G1 transition to dissect their individual roles. We found that Stag1 depletion has a negligible impact on post-mitotic genome restructuring or transcription reactivation. In contrast, Stag2 orchestrates chromatin remodeling in a manner that is both cell cycle stage-specific and chromatin context-dependent. During early-G1, Stag2 preferentially associates with euchromatin, where it drives the rapid formation of small chromatin loops. This facilitates prompt promoter-enhancer (P-E) contact formation and enables efficient transcription activation. As the nuclear concentration of Stag2 increases by late-G1, it progressively suppresses large loops, likely due to its shorter chromatin residence time and its potential to competitively displace the more extrusion-capable Stag1-associated cohesin. Mechanistically, Stag2-mediated loop extrusion is constrained by CTCF-bound barriers, rather than by genomic travel distance. Although Stag2 associates rapidly with euchromatin in early-G1, its recruitment to heterochromatin is delayed until late-G1. Simultaneous depletion of both Stag proteins results in a synergistic loss of virtually all structural loops and a more severe disruption of transcription than that caused by individual deletions. Together, these results establish Stag2 as the principal regulator of post-mitotic genome reorganization among Stag paralogs, mediating spatiotemporal control of chromatin architecture, while Stag1 provides compensatory support to ensure functional robustness.

molecular biology↗

bioRxiv2025

Cinematic Simulation of Substrate-to-Product Chemical Reactions with Chemical Accuracy Using QuantaMind MD

Polyethylene terephthalate hydrolases (PETases) are enzymes that catalyze the breakdown of PET plastic. Previous studies have employed classical molecular dynamics (MD) and quantum mechanical/molecular mechanical (QM/MM) simulations to probe the catalytic mechanisms of the PETase-catalyzed reaction. In this work, we apply QuantaMind, a deep learning-based machine learning force field (MLFF) trained on diverse chemical systems and transition-state energies at density functional theory (DFT)-level, to simulate the complete catalytic cycle of the PETase reaction. Our simulations capture key proton transfer events and the stabilization role of the oxyanion hole in PETase, in agreement with previous computational studies, without introducing artificial biases to the interactions. The simulations also provide estimates of free energy barriers for each reaction step with uncertainty estimation, consistent with experimental values and previous QM/MM studies. To our knowledge, this work represents the first complete DFT-level MD simulation of a biomolecular enzymatic reaction using DL-based MLFFs.

biochemistry↗

bioRxiv2025

QuantaMind MD enables protein modeling with ab initio accuracy

Accurate biomolecular simulations are essential for understanding chemical processes and advancing applications such as protein engineering and drug design. While quantum mechanical (QM) methods can provide chemical accuracy, their computational cost limits their scalability. Machine learning force fields (MLFFs) offer a promising alternative by achieving similar accuracy with vastly improved efficiency, but their effectiveness is often constrained by limited conformational and chemical diversity in training. We introduce QuantaMind, a robust MLFF workflow designed to extend chemical and conformational coverage, particularly in transition-state regions. QuantaMind enables quantum-accurate molecular dynamics simulations, successfully capturing complex phenomena such as proton diffusion, water dissociation, and acid-base neutralization. We show that QuantaMind can be applied to large biomolecular systems, enabling accurate protein structure optimization and improving the prediction of residue contacts and hydrogen bonds. A pocket-centric simulation strategy further allows QuantaMind to efficiently model protein-ligand interactions with high structural accuracy. These results establish QuantaMind as a versatile and scalable tool for atomistic simulations at ab initio accuracy.

biochemistry↗

bioRxiv2025

SpaFoundation: a visual foundation model for spatial transcriptomics

Spatial transcriptomics (ST) has revolutionized biological research by enabling the joint profiling of gene expression and spatial context, along with histological images. However, current existing ST technologies remain high-cost and time-consuming, hindering their broader clinical applications. Although computational methods have been developed to infer gene expression directly from histology images, these methods still suffer from limited accuracy and spatial resolution due to insufficient training data and model capacity. Here, we introduce SpaFoundation, a large-scale histology foundation model designed to accurately predict spatial gene expression from tissue images. SpaFoundation employs a teacher-student Vision Transformer (ViT) architecture to learn generalizable histological representations by modeling potential dependencies among image patches. Notably, we incorporated self-distillation and masked image modeling (MIM) jointly to capture high-level semantic representations and fine-grained structural features, enriching spots representations. The model is pretrained on 1.79 million patches spanning 26 tissue types, with 80 million parameters. We validated SpaFoundation using 117 samples, demonstrating its flexibility across different spatial resolutions and superior performance in spatial gene expression prediction, as well as strong transferability to downstream tasks such as tumor detection and spatial domain clustering. Our results highlight the potential of large-scale foundation model to learn informative histological representations and underscore the benefits of domain-specific pretraining in extracting task-relevant representations, paving the way for foundation model-driven spatial gene expression inference. The implementation and pre-trained weights of SpaFoundation are publicly available at https://github.com/NingZhangCSUBio/SpaFoundation.

bioinformatics↗

bioRxiv2025

The Role of Primate-Specific Genes and Network Dynamics in Cancer Evolution

The atavistic evolutionary theory of cancer evolution highlights the role of ancient and unicell-originated genes, and comprehensive research demonstrated the evolutionary inference. Comparably, very few reports linked young genes with cancer development and maintenance. Here, we found that in cancer cell lines a higher proportion of core essential genes was present among primate-specific genes (PSG) than early metazoan-originated genes (Wilcoxon rank-sum test, p-value = 4.67e-12) and mammal-originated genes (Wilcoxon rank-sum test, p-value = 1.22e-16). Additionally, we found that the loss of many co-expression gene pairs in pan-cancer leads to their network becoming looser compared with normal tissue. However, PSGs particularly those being essential, exhibit a dynamic increase in co-expression, explaining their enhanced role in maintaining cancers. Furthermore, clustering of the gene co-expressions brings a cancer-exclusive module, which contains a large number of PSG connections. We also demonstrate the divergence between essential genes in healthy individuals and those in cancer cells. Our findings complement the atavistic theory in elucidating the evolutionary process of cancer.

evolutionary biology↗

bioRxiv2025

Senescent mast cells contribute to the progression of benign prostatic hyperplasia via SCF/c-KIT mediated endothelial-mesenchymal transition

Benign prostatic hyperplasia (BPH) is a common age-associated urological condition characterized by stromal expansion, but its cellular origins and regulatory mechanisms remain unclear. In this study, we identified endothelial-to-mesenchymal transition (EndMT) as a contributor to stromal cell accumulation in BPH. Using single-cell transcriptomic analysis, endothelial lineage tracing in mice, and validation in human samples, we showed that senescence-associated mast cells increased the expression of vascular endothelial growth factor A (VEGFA) and transforming growth factor-beta 1 (TGF-{beta}1) through the stem cell factor (SCF)/c-KIT-MAPK-JUND signaling pathway, thereby inducing EndMT in endothelial progenitor cells. Stromal fibroblasts express SCF, promoting mast cell activation and establishing a feedback loop that supports continued stromal proliferation. Intriguingly, inhibition of mast cell activation reduces EndMT and attenuates prostate enlargement in vivo. Thus, these findings revealed a senescence-linked immune-stromal interaction in the aging prostate and identify potential targets for therapeutic intervention in BPH.

cell biology↗

bioRxiv2025

Engineered protein circuits for cancer therapy

A central challenge in cancer therapy is selectively killing cancer cells while minimizing resistance. Here, we engineer modular protease-based protein circuits that sense mutant RAS, the most frequently mutated oncogene in cancer, and conditionally activate cell death. Delivered transiently as mRNA in lipid nanoparticles (LNPs), circuits selectively eliminated RAS-mutant cancer cells in culture and suppressed aggressive, multifocal RAS-driven liver tumors. Compared to RAS inhibitors, circuits killed cancer cells independently of oncogene addiction, achieved potent cytotoxicity rather than cytostasis, and functioned at low RAS occupancy through catalysis rather than stoichiometric inhibition. Critically, circuits acquired minimal to no resistance under prolonged selection, while remaining potent against prevalent drug-resistance mechanisms including RAS amplification and bypass signaling. Together, these results establish design principles for engineering therapeutic protein circuits and highlight their potential to overcome longstanding limitations of existing therapeutic modalities.

synthetic biology↗

bioRxiv2025

HPV integration in head and neck cancer: downstream splicing events and expression ratios linked with poor outcomes

HPV integration (HPVint) is associated with carcinogenesis and tumor progression in HPV-associated cancers, including head and neck squamous cell carcinomas (HNSCC). While its impact on human DNA has been well characterized, its relationship with clinical outcomes remains unconfirmed. Here we investigate the consequences of HPVint both with respect to human and HPV characteristics by analyzing 261 HPV-associated HNSCC bulk and single-cell RNA-seq samples from five cohorts, and DNA HPVint events from 102 HPV+ participants in two of the cohorts. By leveraging this large meta-cohort, we first reveal an oncogenic network based on the recurrent HPV integration locations in HNSCC. We then classify HPVint-positive (HPVint(+)) participants by HPV RNA features, specifically based on spliced HPV-human fusion transcripts and ratios of HPV gene transcripts, showing that subsets of participants have worse clinical outcomes. Our analyses, focused mainly on RNA instead of DNA, expand our understanding of the carcinogenic mechanisms of HPVint, partially addressing the conflicting findings of whether HPVint is associated with aggressive phenotypes and worse clinical consequences, and provide potential biomarkers to advance precision oncology in HPV-associated HNSCC.

cancer biology↗

bioRxiv2024

Degradation of intrinsically disordered proteins using proteolysis targeting nanobody conjugate

Intrinsically disordered proteins (IDPs) play crucial roles in diverse cellular processes and are implicated in numerous diseases. However, due to the inherently unstructured nature, it is challenging to modulate their function using small molecule degraders or inhibitors. To address this, we introduced proteolysis targeting nanobody conjugate (PROTNC) composed of a nanobody that binds to an IDP, an E3 ligase ligand, and a cyclic cell-penetrating peptide for efficient intracellular delivery. We first showed a general-purpose PROTNC system capable to degrade different endogenous IDPs based on a co-condensate formation mechanism. We also introduced a straightforward strategy to degrade individual IDPs using specific PROTNCs equipped with a nanobody recognizing that particular IDP. Notably, we demonstrated the degradation of TPX2 which is an undruggable oncogenic IDP responsible for microtubule nucleation. This targeted degradation effectively inhibited cancer cell proliferation by disrupting bipolar mitotic spindle assembly in metaphase and directed cells to apoptotic pathway.

cell biology↗