Biology subjects

Zhang, B.

Publications and source records attributed to Zhang, B..

At least 163 records · Page 9Linked to original sources

bioRxiv2025

A Universal 6iL/E4 Culture System for Deriving and Maintaining Embryonic Stem Cells Across Mammalian Species

The derivation of authentic embryonic stem cells (ESCs) from diverse mammalian species offers valuable opportunities for advancing regenerative medicine, studying developmental biology, and enabling species conservation. Here, we report the development of a robust, serum-free culture system, termed 6iL/E4 that enables the derivation and long-term self-renewal of ESCs from multiple mammalian species, including mouse, rat, bovine, rabbit, and human. Using systematic signaling pathway analysis, we identified key regulators--including GSK3, STAT3, PDGFR, BRAF, and LATS--critical for ESC maintenance across species. Additionally, inducible expression of KLF2 and NANOG enhances the naive pluripotency and chimeric potential of bovine ESCs. The E4 medium also supports stable ESC growth while minimizing lineage bias. These findings reveal conserved principles underlying ESC self-renewal across divergent mammalian species and provide a universal platform for cross-species stem cell research, disease modeling, and biotechnology applications. In BriefWang et al. developed 6iL/E4, a serum-free system sustaining ESCs from mouse, rat, bovine, rabbit, and human. These findings reveal conserved fundamental mechanisms governing ESC self-renewal across diverse mammalian species. HighlightsO_LIDeveloped 6iL/E4 system for ESC derivation across five mammalian species. C_LIO_LIPDGFR signaling inhibition as critical for ESC derivation across species. C_LIO_LIE4 medium improves ESC maintenance and avoids neural bias of traditional N2B27. C_LIO_LIInducible KLF2/NANOG enhances naive pluripotency and chimera formation in bovine. C_LI

cell biology↗

bioRxiv2025

Longitudinal single cell RNA-sequencing reveals evolution of micro- and macro-states in chronic myeloid leukemia

Single cell RNA sequencing (scRNA-seq) has revolutionized our understanding of cancer, yet identifying meaningful disease states from single cell data remains challenging. Here, we systematically explore the chronic myeloid leukemia (CML) specific information content encoded in single cell versus bulk transcriptomics to resolve this paradox and clarify how discrete disease-defining states emerge from inherently noisy single cell data. We demonstrate that, while CML single cell transcriptomes exist along continuous transcriptional microstates, clinically relevant leukemia phenotypes clearly manifest only at the pseudobulk (macrostate) level. By leveraging state-transition theory, we reveal how robust disease phenotype state-transitions are governed by cell type specific contributions. Our results establish a theoretical framework explaining why discrete disease phenotypes remain hidden at the single cell scale but emerge clearly at the aggregated macrostate level, enabling previously inaccessible biological insights into leukemia evolution. By resolving how single-cell variation aggregates into macroscopic disease states, our framework provides new insight into CML progression and offers a broadly applicable strategy for exploring disease dynamics across cancers and other complex conditions.

systems biology↗

bioRxiv2025

Regulation of the Yolk Microtubule and Actin Cytoskeleton by Dachsous Cadherins during Zebrafish Epiboly

Epiboly is a crucial morphogenetic process during early animal embryogenesis that expands surface area of embryonic tissues while thinning them. During zebrafish development, epiboly spreads the superficial enveloping layer (EVL), germ layers, and yolk syncytial layer to cover the yolk cell. Here we investigated functions of the three zebrafish dchs genes, dchs1a, dchs1b and dchs2 that encode large atypical cadherins and report that they have partially overlapping functions in epiboly progression. We have inserted GFP at the C-terminal Dchs1b intracellular domain of the endogenous dchs1b locus using homologous recombination. We observed the resulting Dchs1b-GFP fusion protein localized in both the cell membrane and the cytoplasm of EVL and embryonic cells during gastrulation. The dynamic microtubule and actin cytoskeleton of the yolk cell are essential for epiboly. Our studies of the yolk microtubule network demonstrate that these microtubules are more bundled and show faster polymerization during epiboly in dchs triple loss-of-function mutant embryos than in wild-type embryos, indicating that dchs genes are required for limiting microtubule polymerization and promoting dynamics during epiboly. The epiboly progression defects of dchs1b deficient mutants were suppressed by mutations in the tetratricopeptide repeat protein 28 (ttc28) gene encoding a cytoplasmic protein previously shown to bind to Dchs1b intracellular domain and alter microtubule dynamics during early cleavages. We further demonstrate that MZdchs1b mutants exhibit abnormal organization and dynamics of yolk cell actin cytoskeleton during epiboly. Together, these lines of evidence as well as our transcriptomic analyses support the notion that like during early embryonic cleavages, Dchs1b plays a major role, while Dchs1a and Dchs2 proteins have supporting roles in regulating microtubule dynamics and organization of both microtubule and actin cytoskeleton to ensure normal epiboly.

developmental biology↗

bioRxiv2025

Repositioning of polyubiquitin alters the pathologic tau filament structure

Structurally diverse tau filaments form proteinaceous aggregates in a heterogeneous group of neurodegenerative diseases called tauopathies1. The factors extrinsic to the highly ordered core structure that influence tau filament stability are not well understood. Here, we found that polyubiquitinated tau filaments from Alzheimers disease and vacuolar tauopathy human brain tissue exhibit distinct seeding patterns in mice, in association with differences in tau filament ultrastructure determined by cryo-electron microscopy. Interestingly, chemical modulation of the polarity of polyubiquitin adjacent to the tau core with the small molecule ubistatin B resulted in the repositioning of poorly structured densities towards positively charged residues on the highly structured core filament, leading to shifting of the protofilament-protofilament interface of certain vacuolar tauopathy tau filaments. These results suggest that the structure of tau filaments that are associated with different seeding activities in vivo can be influenced by post-translational modifications.

neuroscience↗

bioRxiv2025

No Evidence of Direct Activation of Human Neutrophil Responses by Multivalent Prefusion Trimeric SARS-CoV-2 Spike Protein ex vivo

The SARS-CoV-2 Spike (S) protein is essential for viral entry and serves as the primary immunogen in most COVID-19 vaccines. While its role in adaptive immunity is well defined, its potential to contribute directly to innate immune activation and remains incompletely understood. Neutrophils, in particular, are prominent effectors in COVID-19 severity, yet how they respond directly to the S protein presented in a multivalent format is unclear. Here, we investigated whether the S protein can directly activate human neutrophils ex vivo using two biologically relevant models: nanoparticles displaying multivalent stabilized prefusion trimeric S glycoprotein, and purified {beta}-propiolactone-inactivated SARS-CoV-2 virions. Neutrophils were exposed to nanoparticles or inactivated virus, either alone or pre-coated with monoclonal or polyclonal anti-S antibodies. Nanoparticles displaying Respiratory Syncytial Virus (RSV) Fusion (F) protein and purified {beta}-propiolactone-inactivated RSV served as comparators. Across all models and conditions tested, the S protein did not induce significant neutrophil responses. No consistent effects were observed on cell viability, surface marker expression, reactive oxygen species production, neutrophil extracellular trap formation, cytokine release, or inflammatory gene expression--even in the presence of anti-S antibodies mimicking immune complexes. Results with F-nanoparticles and inactivated RSV were similarly modest. These findings indicate that the trimeric prefusion S protein, whether displayed multivalently on nanoparticles or in the context of inactivated viral particles, is insufficient to trigger robust neutrophil activation. This work provides insight into the innate immune profile of the S protein and suggests that its use in vaccine platforms is unlikely to directly provoke neutrophil-mediated inflammatory responses.

immunology↗

bioRxiv2025

Quantification of single cell-type-specific alternative transcript initiation

Cells can transcribe different isoforms of a gene by using distinct Transcriptional Start Regions (TSRs), which are recognized by RNA-Polymerase II and regulated by cell-type-specific expressed transcription factors, eventually forming tissue and cell-type-specific expression during development. However, how the distinct TSRs are selectively activated in different tissues and cell types remains largely uncharacterized. To better explore the alternative usage of gene TSRs, we developed TSRdetector, a novel bioinformatic method specifically designed to detect the significant usage alteration of gene TSRs in different tissues, cell types, or diseases. TSRdetector can process either scRNA-seq or bulk-RNA-seq transcriptome data, define dominant TSRs, and compute the differential usage of gene TSRs between given conditions. To demonstrate the capacity of TSRdetector, we applied TSRdetector to analyze a 10X snRNA-seq dataset of healthy and diabetic human kidneys, a Smart-seq2 dataset of mouse B-cell differentiation, and bulk-RNA-seq data of pluripotency transition in human ESCs. In all three analyses, TSRdetectors discovered significant alterations in TSR usage, accompanied by the significant remodeling of the epigenetic landscape. Alteration of TSR usage can change the dominant transcript isoform and further affect the major protein products. Interestingly, a large proportion of these alterations of TSR usage in different cell types did not change the overall gene expression, revealing unique transcription regulations that are independent of expression level. In summary, TSRdetector is a user-friendly package to analyze the differential usage of gene TSRs by using both scRNA-seq and bulk-RNA-seq data, and can be used to explore the alternative transcription initiations of genes at the single cell-type level.

bioinformatics↗

bioRxiv2025

Fucoidans are senotherapeutics that enhance SIRT6-dependent DNA repair

Aging is marked by the accumulation of senescent cells (SnCs), which contribute to tissue dysfunction and age-related diseases. Senotherapeutics, including senolytics which specifically induce lysis of SnCs and senomorphics, which suppress the senescence phenotype, represent promising therapeutic interventions for mitigating age-related pathologies and extending healthspan. Using a phenotypic-based senescent cell screening assay, we identified fucoidans, a class of sulfated polysaccharides derived from brown algae and seaweed, as novel senotherapeutics. In particular, fucoidan from Fucus vesiculosus (Fucoidan-FV) displayed potent senomorphic activity in different types of SnCs, reduced senescence in multiple tissues in aged mice, and extended healthspan in a mouse model of accelerated aging. Fucoidan-FV also enhanced the deacetylation and mono-ADP-ribosylation (mADPr) activity of SIRT6 and improved DNA repair and reduced senescence, in part, through SIRT6-dependent pathways. In addition, Fucoidan-FV downregulated genes associated with inflammation, Wnt signaling, and ECM remodeling pathways in SnCs and increased expression of genes involved with DNA repair. These findings support the translational potential of fucoidans as novel senotherapeutics that also are able to improve SIRT6-mediated DNA repair.

cell biology↗

bioRxiv2025

BioMiner: A Multi-modal System for Automated Mining of Protein-Ligand Bioactivity Data from Literature

Protein-ligand bioactivity data published in the literature are essential for drug discovery, yet manual curation struggles to keep pace with rapidly growing literature. Automated bioactivity extraction remains challenging because it requires not only interpreting biochemical semantics distributed across text, tables, and figures, but also reconstructing chemically exact ligand structures (e.g., Markush structures). To address this bottleneck, we introduce BO_SCPLOWIOC_SCPLOWMO_SCPLOWINERC_SCPLOW, a multi-modal extraction framework that explicitly separates bioactivity semantic interpretation from ligand structure construction. Within BO_SCPLOWIOC_SCPLOWMO_SCPLOWINERC_SCPLOW, bioactivity semantics are inferred through direct reasoning, while chemical structures are resolved via a chemical-structure-grounded visual semantic reasoning paradigm, in which multi-modal large language models operate on chemically grounded visual representations to infer inter-structure relationships, and exact molecular construction is delegated to domain chemistry tools. For rigorous evaluation and method development, we further establish BO_SCPLOWIOC_SCPLOWVO_SCPLOWISTAC_SCPLOW, a comprehensive benchmark comprising 16,457 bioactivity entries curated from 500 publications. BO_SCPLOWIOC_SCPLOWMO_SCPLOWINERC_SCPLOW validates its extraction ability and provides a quantitative baseline, achieving an F1 score of 0.32 for bioactivity triplets. BO_SCPLOWIOC_SCPLOWMO_SCPLOWINERC_SCPLOWs practical utility is demonstrated via three applications: (1) extracting 82,262 data from 11,683 papers to build a pre-training database that improves downstream models performance by 3.9%; (2) enabling a human-in-the-loop workflow that doubles the number of high-quality NLRP3 bioactivity data, helping 38.6% improvement over 28 QSAR models and identification of 16 hit candidates with novel scaffolds; and (3) accelerating protein-ligand complex bioactivity annotation, achieving a 5.59-fold speed increase and 5.75% accuracy improvement over manual workflows in PoseBusters dataset. BO_SCPLOWIOC_SCPLOWMO_SCPLOWINERC_SCPLOW and BO_SCPLOWIOC_SCPLOWVO_SCPLOWISTAC_SCPLOW provide a scalable extraction methodology and a rigorous benchmark, paving the way to unlock bioactivity data that previously required extensive human effort. All data and code are available at GitHub.

bioinformatics↗

bioRxiv2025

Early-Life Environmental Exposures Reprogram Epigenomic Aging to Alter Gene Expression Trajectories

To understand how early-life environmental exposures shape health and disease risk across the lifecourse, the TaRGET II Consortium exposed mice to diverse toxicants from pre-conception through weaning, and followed individual animals into adulthood, generating over 800 epigenomic and transcriptomic profiles. These profiles revealed that early-life exposures induced persistent epigenomic reprogramming and significantly disrupted the adult transcriptome. Notably, despite their diverse mechanisms of action, the exposure signatures of the xenoestrogen BPA, obesogen TBT, dioxin TCDD, and air pollutant PM2.5, were all largely comprised of genes normally differentially expressed during liver aging. Epigenetic histone modifications at enhancers--and, to a lesser extent, promoters--emerged as key targets for this reprogramming. Despite differing mechanisms of action, these four toxicants imparted similar "fingerprints" on the adult liver, characterized by direction-and cell type-specific polarization of the transcriptome. Hepatocyte genes that typically increase with age, particularly those in metabolic pathways, were downregulated, while conversely, non-parenchymal cell genes that typically decrease with age, such as those involved in extracellular matrix production, were upregulated. A similar signature of anti-correlation with programmed aging aging was also found in the transcriptome of patients with liver disease and hepatocellular carcinoma (HCC), and was effective at distinguishing healthy from diseased human livers. These findings demonstrate that the plasticity of epigenomic aging is vulnerable to early-life environmental exposures, which can reprogram the epigenome with lasting impacts on the transcriptome, and disease risk, later in life.

genomics↗

bioRxiv2025

Distinct Bomanins at the Drosophila 55C locus function in resistance and resilience to infections

Host defense against many Gram-positive bacteria and fungal pathogens is mainly provided by the Toll-dependent systemic immune response in Drosophila. While antimicrobial peptides active against these categories of pathogens contribute only modestly to protection, Bomanin peptides are major effectors of the Toll pathway. Remarkably, flies deleted for the 55C locus that contains 10 Bomanin genes are as sensitive as Toll pathway mutant flies to these infections. Yet, the exact functions of single Bomanins in resistance or resilience to infections remain poorly characterized. Here, we have extensively studied the role of these Bomanin genes. BomT1 functions in resistance to Enterococcus faecalis while playing a role in resilience against Metarhizium robertsii infection, like BomS2. BomT1 and BomT2 prevent the dissemination of Candida albicans throughout the host, even though they are not sufficient to confer protection to immunodeficient flies against this pathogen in survival experiments. Furthermore, BomT1 and BomBc1 mutants are sensitive to an Aspergillus fumigatus ribotoxin. We conclude that 55C Bomanins have defined albeit sometimes overlapping roles in the different facets of host defense against infections.

immunology↗

bioRxiv2025

Allosteric modulation of dimeric GPR3 by ligands in the dimerization interface

Class C G-protein coupled receptors (GPCRs) are widely recognized to function as a dimer, whereas the existence, molecular mechanisms and functional importance of dimerization in class A GPCRs remain poorly explored. GPR3, GPR6 and GPR12 are closely related to cannabinoid receptors, and are associated with neurogenerative diseases such as Parkinsons and Alzheimers diseases. Here, we determined cryo-EM structures of GPR3-Gs complex in the active state and GPR3 alone in the inactive state. We observe that GPR3 forms symmetric dimers in both states, with the dimerization interface primarily involving TM5 and TM6. Upon activation, GPR3 undergoes an outward movement of TM6 and an inward movement of TM7, alongside stabilization of helix 8, which is disordered in the inactive state. Functionally, GPR3 dimerization attenuates Gs signaling. Furthermore, we identify AF64394 as a negative allosteric modulator that targets the GPR3 dimerization interface and allosterically shifts the -helical structure of ICL2 into a random coil structure, thereby impairing Gs coupling. Our findings provide structural and mechanistic insights into class A GPCR dimerization, offering potential therapeutic strategies targeting the dimerization interface of these receptors.

biochemistry↗

bioRxiv2025

Slow Gompertzian aging in long-lived C. elegans results from expansion of decrepitude, not decelerated aging

The Gompertz equation describes exponential age-increases in animal mortality rate arising from biological aging. Its parameters, and {beta}, are widely used to evaluate lifespan-extending interventions and human mortality patterns: it is assumed that reduction in {beta} corresponds to deceleration of aging rate, and reduction in to reduced aging-independent mortality. However, this view has never been empirically validated. We therefore investigated the biological basis of and {beta}, by simultaneous quantification of mortality and age-related health in long-lived populations of the nematode Caenorhabditis elegans. We show that reduction in {beta} arises not from decelerated aging but expansion of decrepitude in longer-lived individuals, whereas reduction in arises from decelerated aging. This empirical re-evaluation of Gompertzian aging inverts and challenges long-standing ideas in the biodemography of aging.

physiology↗

bioRxiv2025

Multiple evolutionary events in host plant adaptation in Lepidoptera

The evolution of insect host adaptation is a key component of insect-plant coevolution, a complex process often shaped by multiple evolutionary events. In this study, we identified two UDP-glycosyltransferase (UGT) genes, SfruUGT33T10 and SfruUGT33F32, in the fall armyworm Spodoptera frugiperda, which play critical roles in the tolerance of benzoxazinoids (BXs), secondary metabolites in maize. These two detoxification enzymes exhibited distinct glycosylation patterns for BXs and varying detoxification efficiencies, reflecting independent evolutionary trajectories. Phylogenetic analyses revealed that SfruUGT33T10 originated independently within Noctuidae, while SfruUGT33F32 resulted from tandem duplication within the UGT33F gene family and may have undergone neofunctionalization within the Spodoptera genus. Our findings provide evidence that the evolution of these two UGT paralogs contributed to the variation in the tolerance to maize BXs among different Lepidopteran species. This research underscores the significance of multiple independent evolutionary routes in host plant adaptation and offer new insights into the complex evolutionary processes underlying insect-plant interactions.

evolutionary biology↗

bioRxiv2025

Capturing Natural Evolution in Function-guided RNA Design via Genomic Foundation Models

RNAs play critical roles in gene expression regulation, catalysis, genetic information transmission, and immune response. However, current RNA engineering approaches face limitations in designing RNA for efficient in vivo folding and functional execution. Here, we present a novel, zero-shot strategy that integrates genomic large language models (LLMs) with inverse folding models (IFMs) to generate RNA sequences that mirror natural evolutionary patterns while preserving the structural integrity of critical functional regions. Benchmarking 9 state-of-the-art genomic foundation models, we show that their unsupervised log-likelihood scores correlate strongly with RNA fitness, enabling zero-shot sequence design. Applied to fluorescent RNA aptamers, our approach yielded 20 Broccoli variants, over half of which achieved up to 155% in fluorescence and a twofold increase in binding affinity, with robust performance both in vitro and in vivo. For Pepper, two rounds of optimization produced 40 variants, 16 of which demonstrated up to 2.6 fold in fluorescence and a threefold boost in binding affinity, including five with superior in vivo brightness.This approach offers a scalable, efficient, and resource-light method for RNA design, with significant implications for RNA-based therapeutics and diagnostics. By leveraging general foundation models to facilitate RNA evolution in a zero-shot fashion, we believe our work represents a major advancement in the field of RNA engineering.

evolutionary biology↗

bioRxiv2025

Expression spectrum of TE-derived transcripts in human adult tissues

Transposable elements (TEs) are vital components of eukaryotic genomes and have played a critical role in genome evolution. Although most TEs are silenced in the mammalian genome, increasing evidence suggests that certain TEs are actively involved in gene regulation during early developmental stages. However, the extent to which human TEs drive gene transcription in adult tissues remains largely unexplored. In this study, we systematically analyzed 17,329 human transcriptomes to investigate how TEs influence gene transcription across 47 adult tissues. Our findings reveal that TE-derived transcripts are broadly expressed in human tissues, contributing to both housekeeping functions and tissue-specific gene regulation. We identified sex-specific expression of TE-derived transcripts regulated by sex hormones in breast tissue between females and males. Our results demonstrated that TE-derived alternative transcription initiation significantly enhances the variety of translated protein products, e.g., changes in the N-terminal peptide length of WNT2B caused by TE-derived transcription result in isoform-specific subcellular localization. Additionally, we identified 68 human-specific TE-derived transcripts associated with metabolic processes and environmental adaptation. Together, these findings highlight the pivotal evolutionary role of TEs in shaping the human transcriptome, demonstrating how conserved and human-specific TEs contribute to transcriptional and translational innovation in human genome evolution.

genomics↗

bioRxiv2025

Machine learning-predicted chromatin organization landscape across pediatric tumors

Structural variants (SVs) are increasingly recognized as important contributors to oncogenesis through their effects on 3D genome folding. Recent advances in whole-genome sequencing have enabled large-scale profiling of SVs across diverse tumors, yet experimental characterization of their individual impact on genome folding remains infeasible. Here, we leveraged a convolutional neural network, Akita, to predict disruptions in genome folding caused by somatic SVs identified in 61 tumor types from the Childrens Brain Tumor Network dataset. Our analysis reveals significant variability in SV-induced disruptions across tumor types, with the most disruptive SVs coming from lymphomas and sarcomas, metastatic tumors, and germline cell tumors. Dimensionality reduction of disruption scores identified five recurrently disrupted regions enriched for high-impact SVs across multiple tumors. Some of these regions are highly disrupted despite not being highly mutated, and harbor tumor-associated genes and transcriptional regulators. To further interpret the functional relevance of high-scoring SVs, we integrated epigenetic data and developed a modified Activity-by-Contact scoring approach to prioritize SVs with disrupted genome contacts at active enhancers. This method highlighted highly disruptive SVs near key oncogenes, as well as novel candidate loci potentially implicated in tumorigenesis. These findings highlight the utility of machine learning for identifying novel SVs, loci, and genetic mechanisms contributing to pediatric cancers. This framework provides a foundation for future studies linking SV-driven regulatory changes to cancer pathogenesis.

genomics↗

bioRxiv2025

A differentiated and durable allogeneic strategy applicable to cell therapies

Autologous T cell therapies have shown profound clinical responses; however, their widespread use has been limited primarily due to their individualized manufacturing requirements. To develop a persistent "off-the-shelf" allogeneic (Allo) approach, a multiplex Nme2Cas9-based cytosine base editor was deployed to knockout select HLA Class I and II alleles (HLA-A, HLA-B, and the class II transactivator (CIITA)), while retaining HLA-C to protect from NK cell rejection. Matching the residual HLA-C allele from homozygous donors to the host prevented rejection of the donor T cells by allogeneic host T and NK cells. Site-specific integration of a tumor-specific CAR or TCR into the TRAC locus using SpyCas9 nuclease and an adeno-associated virus (AAV) template allowed for high localized insertion rate while simultaneously removing the endogenous TCR and preventing GvHD. Using a lipid nanoparticle (LNP)-based delivery system of the editing components enabled a robust cell engineering process, achieving high editing rates and cell expansion. These allogeneic T cells demonstrated comparable functional activity to their autologous counterparts in preclinical assays. Moreover, this gene editing approach generated cells with minimal chromosomal aberrations. The Allo strategy has also been applied to induced pluripotent stem cells (iPSCs), suggesting potential applications in regenerative medicine applications.

bioengineering↗

bioRxiv2025

Machine Learning-Based Identification of Survival-Associated CpG Biomarkers in Pancreatic Ductal Adenocarcinoma

Pancreatic ductal adenocarcinoma (PDAC) is an exceptionally aggressive cancer with a 5-year survival rate of less than 10%, driven by late-stage diagnosis, limited treatment options, and a lack of reliable biomarkers for early detection and prognosis. In this study, we integrated DNA methylation data from TCGA and ICGC cohorts, categorizing samples based on survival time, and identified 684 differentially methylated CpG sites, along with 224 CpG biomarkers significantly associated with patient survival through statistical and machine learning-based analyses. We developed a random forest model to predict patient survival, achieving 85.2% accuracy for short-survival patients and 70.0% for long-survival patients in the validation set. External dataset validation further confirmed the models robustness and accuracy. De novo motif analysis of genomic regions surrounding the 224 CpG biomarkers identified TWIST1 and FOXA2 as key transcriptional regulators enriched in survival-associated CpG sites, linking their activity to patient survival outcomes. Collectively, our findings highlight valuable epigenetic biomarkers and provide a predictive model to assess PDAC risk levels post-surgery, offering the potential for improved patient stratification and personalized therapeutic strategies.

bioinformatics↗