Biology subjects

Wang, J.

Publications and source records attributed to Wang, J..

At least 595 records · Page 33Linked to original sources

bioRxiv2025

Integrative Multi-omics Deciphers the Assembly Rules of the Human Skin Microbiome and Highlights Lipid-Mediated Niche Partitioning

Understanding the ecological assembly mechanisms of microbial communities is critical for deciphering host-microbiota interactions, however, such processes remain poorly characterized in cutaneous ecosystems. By profiling a non-industrialized rural cohort, this study deciphers the assembly rules governing the human skin microbiome and reveals an evolutionarily conserved core microbiota structured by niche selection. Microbial -diversity peaks when C. acnes and M. osloensis reach equilibrium, supporting the Intermediate Disturbance Hypothesis. Host lipids, rather than aqueous compounds, emerged as the primary drivers of microbial niche partitioning. We further demonstrate that C. acnes and Malassezia restricta function as core metabolic engineers, expressing diverse lipases that hydrolyze triglycerides (TGs) into free fatty acids (FFAs), thereby maintaining skin surface lipid homeostasis ([~]85% TG + FFA). Notably, virtually all skin surface FFAs are microbially derived and function as "public goods", enabling cross-feeding that supports auxotrophic members and fosters mutualistic interactions. Importantly, in vitro coculture experiments confirm that C. acnes establish a survival niche for M. restricta. Our findings support a paradigm shift from a taxonomic to a functional understanding of the skin ecosystem, underscoring microbial lipid metabolism as a central orchestrator of ecological stability and a promising target for therapeutic intervention. O_FIG O_LINKSMALLFIG WIDTH=182 HEIGHT=200 SRC="FIGDIR/small/674196v1_ufig1.gif" ALT="Figure 1"> View larger version (62K): org.highwire.dtl.DTLVardef@1274fa5org.highwire.dtl.DTLVardef@1ddfa07org.highwire.dtl.DTLVardef@49f917org.highwire.dtl.DTLVardef@807a14_HPS_FORMAT_FIGEXP M_FIG O_FLOATNOGRAPHIC ABSTRACTC_FLOATNO C_FIG

microbiology↗

bioRxiv2025

Poly(ADP-ribose) Polymerase 1 Deficiency Attenuates Amyloid Pathology, Neurodegeneration, and Cognitive Decline in a Familial Alzheimer Disease Model

Poly(ADP-ribose) (PAR) polymerase-1 (PARP1) has been implicated in DNA damage responses and neuroinflammation in Alzheimers disease (AD), yet its role in amyloid-{beta} (A{beta}) pathology remains unclear. Here, we show that PARP1 activation drives A{beta} pathology and neurodegeneration. Using a sensitive ELISA, we observed significantly elevated PAR levels in the cerebrospinal fluid (CSF) of patients with mild cognitive impairment (MCI) and AD compared to controls. In vitro, oligomeric A{beta}1-42 activated PARP1 and induced DNA damage, while genetic or pharmacological inhibition of PARP1 conferred neuroprotection. In vivo, PARP1 knockout in the 5XFAD mouse model of amyloidosis led to reduced amyloid plaque burden, preserved synaptic and neuronal integrity, attenuated glial activation and neuroinflammation, and rescued cognitive deficits. Mechanistically, PARP1 deficiency decreased amyloid precursor protein (APP) and BACE1 levels, altered {gamma}-secretase complex composition, and enhanced A{beta} degradation via neprilysin. These findings position PARP1 as a critical mediator of A{beta} toxicity and neurodegeneration, suggesting its inhibition as a promising therapeutic strategy for AD. Significance StatementOur study identifies poly(ADP-ribose) (PAR) as an elevated biomarker in the cerebrospinal fluid of patients with mild cognitive impairment and Alzheimers disease, correlating with established markers of amyloid pathology. We demonstrate that PARP1, the enzyme responsible for PAR synthesis, is activated by neurotoxic A{beta}1-42 and mediates neuronal death, amyloid plaque formation, neuroinflammation, and cognitive deficits in a mouse model of AD. Importantly, genetic ablation of PARP1 not only protects neurons from A{beta} toxicity but also reduces amyloid burden by suppressing A{beta} production and enhancing its degradation. These findings highlight PARP1 as a critical regulator of amyloid pathology and neurodegeneration, and suggest that PARP1 inhibition may offer a promising therapeutic avenue for Alzheimers disease by simultaneously targeting multiple pathogenic mechanisms.

neuroscience↗

bioRxiv2025

Integrative reverse vaccinology approach for identification of a vaccine antigen candidate with immunoprotective and anti-fibrotic potential against Schistosoma japonicum-associated liver fibrosis

Schistosoma japonicum-associated liver fibrosis (SSLF) is a major cause of morbidity in Schistosomiasis, yet no licensed vaccines or specific therapies exist to prevent or treat this complication. Current vaccine development has focused mainly on infection prevention, with limited attention to pathology-driven outcomes such as fibrosis. To address this gap, we developed an in-silico pipeline integrating host single-cell transcriptomic analysis, parasite antigen screening, and structure-based modeling. Single-cell RNA-seq of liver tissues from SSLF and controls identified three fibrosis-related hub proteins: FYN, BCL2, and AKT3. In parallel, parasite antigens curated from public databases were evaluated for immunogenicity and safety using reverse vaccinology principles. Among these, DRE2_SCHJA, an Anamorsin homolog involved in Fe-S cluster assembly, was prioritized as the top candidate. Docking analysis predicted the strongest interaction between DRE2_SCHJA and FYN ({Delta}G = -14.9 kcal/mol), linking the antigen to a central regulator of fibrosis. Unlike Saracatinib, which inhibits FYN at the ATP-binding pocket, DRE2_SCHJA bound to the SH2 domain through both canonical and non-canonical contacts, indicating a different regulatory mechanism. Taken together, these findings suggest DRE2_SCHJA as a potential vaccine candidate with both protective and anti-fibrotic potential against SSLF. While experimental validation is required, this study supports the early identification of SSLF vaccine candidates in a rapid and cost-effective manner and provides a framework applicable to other neglected tropical diseases. Athor summarySchistosoma japonicum (S. japonicum) is a parasitic disease that remains a major health problem in parts of Asia, especially in China. One of its most harmful consequences is liver fibrosis, which causes long-term illness and reduces quality of life. Currently, there are no drugs or vaccines that specifically prevent or treat this condition. In this study, we used a fast and low-cost computer-based method to search for vaccine targets against liver fibrosis caused by S. japonicum. We identified a parasite protein that could serve as a vaccine target, with the potential to prevent fibrosis from developing and to slow its progression. If future studies confirm its role, such a vaccine could greatly improve the long-term health of people living with schistosomiasis and inspire new strategies for vaccine development in other neglected tropical diseases.

bioinformatics↗

bioRxiv2025

Chemo-mechanotherapy of fibrosis: dynamic control of biological materials through tissue-architecture-dependent crosslink disruption

Extracellular matrix (ECM) stiffness drives cell fate, but tissues are nonlinear and difficult to modify chemically without harming patients. Here, we show that nonlinear mechanical responses of fibrous and porous tissues can be controlled by mechanically modulating crosslinks. Through integrated in vivo, in vitro, and computational approaches, we found that physiological dynamic stretching disrupts pathological advanced glycation end-product (AGE) crosslink-induced fibrogenesis in an architecture-dependent manner. This was effective in lung-like porous scaffolds but not in liver-like fibrous matrices, revealing a critical structure-property relationship. Computational and in vitro models established that this modulates cell-ECM feedback, and that controlling mechanical crosslinking modulates key nonlinearity of networked solids. This discovery inspired a non-invasive, "mechanotherapuetic" ventilation protocol, which reversed pulmonary fibrosis in mice by physically disrupting ECM pathological crosslinks. The therapeutic efficacy was further amplified when combined with pharmacological AGE inhibition. These findings establish design principles for dynamically reprogrammable biological materials and mechano-targeted therapies.

bioengineering↗

bioRxiv2025

Tech Note: Simplified protocol for SMARTer Pico kit

The SMARTer(R) Stranded Total RNA-Seq Kit v2 - Pico Input Mammalian kit from Takara(R) (SMARTer Pico) has proved successful and reliable in generating stranded RNA Illumina libraries from degraded total RNA and ultra-low input amounts of total RNA below detection level. Here we attempted to streamline and simplify the library prep protocol at the key fragmentation step bottleneck. Our key findings were that reduced fragmentation times neither affect the depletion efficiency, nor the library complexity. Skipping the fragmentation resulted in longer libraries when examined in the capillary electrophoresis but this was compensated for during sequencing, as long fragments are less likely to form clusters during sequencing. Skipping the fragmentation also affected the gene body coverage, where a bias to the 5 end was observed though this compromised neither the data quality, complexity nor reproducibility. Additionally, using 16 PCR cycles seems to have little effect on the library complexity. Overall, we can see that sample input is the key to library complexity and reproducibility, while fragmentation time has less impact on data. Is total RNA fragmentation needed? Is rRNA depletion affected by fragmentation time? Or affected by input? Can we get reliable data when starting with low input?

genomics↗

bioRxiv2025

CMDdemux: an efficient single cell demultiplexing method

Multiplexing technologies label cells with molecular tags, allowing cells from different donors to be pooled together for sequencing. Although this approach enhances cell throughput, eliminates batch effects, and enables doublet detection, limitations of hashtag-based labelling can still lead to low-quality data. Existing demultiplexing methods can accurately assign donor identities in high-quality datasets, but they often fail on low-quality data. To address this, we developed CMDdemux, a method comprising three key steps: within-cell centered log-ratio (CLR) normalization of hashtag count data, K-medoids clustering, and classification of cells based on Mahalanobis distance. By integrating both hashing and mRNA data, CMDdemux achieves high accuracy in distinguishing singlets, doublets, and negatives. It also provides visualization tools to help users inspect potentially misclassified droplets. We benchmarked CMDdemux against existing methods using a range of high- and low-quality datasets. Results show that CMDdemux consistently outperforms other approaches, demonstrating robust performance on both high- and low-quality data where other methods fail. CMDdemux is particularly effective in handling diverse types of low-quality multiplexing data across different multiplexing technologies.

bioinformatics↗

bioRxiv2025

The Brain/MINDS 3D Digital Marmoset Brain Atlas Version 2.0: Population-based Cortical Region Parcellations with Multi-Modal Standard Templates

We present our new Brain/MINDS 3D digital marmoset brain atlas version 2.0 (BMA2.0), a population-based 3D digital brain atlas of the common marmoset (Callithrix jacchus), designed to overcome the limitations of previous single subject atlases that are prone to structural biases arising from individual variation. Here, manually delineated cortical regions from 10 myelin-stained brains were used to create a generalized cortical parcellation. Newly refined subcortical regions from a previous atlas and a completely new cerebellum parcellation were also incorporated, resulting in a comprehensive whole brain parcellation for both hemispheres. To facilitate multimodal data analysis, the atlas package includes co-registered average templates for myelin and Nissl staining from the same individuals, ex vivo MRI T2 (91 individuals), and in vivo MRI T2 (446 individuals). Cortical flat maps and pial, cortical mid-thickness, and white matter surfaces are also provided. BMA2.0 provides a central brain space for multimodal data integration, spatial analysis, and comparative neuroscience. Standard formats and transformations are provided for easy integration into existing workflows and interoperability with existing atlases.

neuroscience↗

bioRxiv2025

GSDME unlocks astrocyte-driven neurotoxicity in Alzheimer's Disease

Astrocytic calcium dysregulation and reactivity precede A{beta} deposition in amyloid-{beta} deposition in Alzheimers disease (AD) but the neurotoxic mechanisms remain unclear. We show that GSDME acts as a switch, linking MAM-mediated calcium release to astrocyte-driven neurotoxicity. Specifically, A{beta}-activated microglial signals activate astrocytic GSDME, releasing its N-terminal fragment, which targets MAMs and triggers ER calcium efflux. This induces biphasic CaMKII phosphorylation, initially boosting NRF2 defenses, then activating NF-{kappa}B-driven inflammation, shifting astrocytes from protective to toxic states. GSDME activation also drives astrocyte-derived exosomes (ADEs) to carry neurotoxic tau, proinflammatory miRNAs, and toxic lipids, propagating toxicity. GSDME deletion in AD mice reduces A{beta} burden, restores NF-{kappa}B/NRF2 balance, reprograms astrocytes and ADEs to protective states, and rescues cognition. Multi-omics profiling of serum ADEs from AD patients reveals a disease-specific signature with central neurotoxicity and peripheral immune regulation. These findings position GSDME as a promising dual diagnostic and therapeutic target for early AD invention.

neuroscience↗

bioRxiv2025

Differential effects of sodium on agonist-induced conformational transitions and signaling at μ and κ opioid receptors

Sodium ions are classically conceptualized as negative allosteric modulators for G protein coupled receptors (GPCRs), although there have been reports of either positive allosteric modulation or no effect of sodium on GPCR function. Here we identified opposing actions of sodium on the and {kappa} opioid receptors. We utilized a variety of methods including radioligand binding, real-time conformational monitoring of transitions using bioluminescence resonance energy transfer and signaling assays using the TRUPATH resource. At the receptors, sodium behaved as a negative allosteric modulator of binding, conformational transitions and signaling. Intriguingly, bitopic agonists were unaffected by sodium concentrations. By contrast, at the {kappa} opioid receptor sodium negatively modulated agonist binding and positively modulated conformational transitions and signaling. Taken together, these findings support the notion that the differential sensitivities to sodium concentrations will result in opposing effects on cell surface and intracellular signaling.

neuroscience↗

bioRxiv2025

Mapping early PRC2 nucleation sites upon Suz12 reintroduction reveals features of de novo Polycomb recruitment

Polycomb domains safeguard cell identity by maintaining lineage-specific chromatin states enriched in repressive histone modifications, preserving the epigenetic memory of cell lineages. While Polycomb Repressive Complex 2 (PRC2) can re-establish its occupancy after perturbation, the mechanisms that guide de novo Polycomb recruitment remain unclear. To address this, we engineered an auxin-inducible degradation system to reversibly deplete and reintroduce the endogenous PRC2 core subunit Suz12 in mouse embryonic stem cells (mESCs). Genome-wide profiling at an early recovery time point revealed [~]1,100 PRC2 nucleation sites, characterized by rapid Suz12 and histone H3K27me3 re-accumulation with strong signal, with minimal impact on gene expression. These sites were significantly enriched at bivalent promoters, coinciding with unmethylated CpG islands and chromatin states associated with developmental regulation, and were largely conserved in differentiated cells. Motif analysis identified G/C-rich DNA sequences associated with E2F and zinc-finger proteins, alongside strong co-occupancy with MTF2 and JARID2, two PRC2 cofactors previously implicated in Polycomb targeting. Notably, a subset of nucleation sites overlapped with long-range chromatin interaction anchors in histone H3K27me3 HiChIP datasets. These findings reveal that PRC2 de novo nucleation sites are associated with a combination of chromatin states, DNA sequence features, cofactor co-occupancy and spatial genome organization, suggesting that epigenetic memory can be re-established through defined genomic and chromatin features. Author summaryPolycomb group proteins are key epigenetic regulators that silence gene expression by establishing and dispersing repressive chromatin domains marked by histone modifications such as histone H3K27me3 and H2AK119ub1 and are critical for defining cell identity. During differentiation, Polycomb domains are dynamically redistributed, implying a mechanism for de novo targeting to specific loci. How the Polycomb Repressive Complex 2 (PRC2) is initially recruited to these nucleation sites and which features stabilize its binding remain poorly understood. To explore this, we studied the characteristics of the de novo recruitment sites of PRC2 in mouse embryonic stem cells (mESCs) using an auxin-inducible degradation (AID) system targeting PRC2 to deplete and reintroduce the core subunit Suz12. We identified recruitment sites after complete clearance of the histone H3K27me3 through ChIP-seq at a very early time point after Suz12 reintroduction. Most nucleation sites were located at bivalent promoters of developmental genes and correlated with unmethylated CpG islands. Motif analysis revealed over-represented sequences and accessory partners such as MTF2 and JARID2, along with long-range chromatin interactions. These nucleation sites were also conserved in differentiated cells, highlighting their potential role in developmental regulation. Our study provides insight into how Polycomb domains are established and how epigenetic memory is maintained in stem cells.

molecular biology↗

bioRxiv2025

Disgust propensity, not disgust sensitivity, shapes the reactivity of a subjective disgust circuit in humans

Disgust constitutes an evolutionary adaptive defensive-avoidance response, yet humans vary markedly in their dispositional tendency to experience disgust (disgust propensity) and in their negative appraisal of such experience (disgust sensitivity). Conceptual frameworks and neuroimaging studies suggest that these traits may differentially modulate neural responses to disgust-eliciting stimuli; however, methodological constraints have left their precise roles unresolved. Our comparably large fMRI study (n = 142) therefore aimed to systematically determine how trait disgust modulates neural responses to carefully selected and validated disgust-specific visual stimuli across varying levels of subjective disgust experience. The whole-brain voxel-wise regression analyses revealed a neural dissociation between the two disgust traits, with disgust propensity, but not disgust sensitivity, modulating disgust-related neural activity in the anterior, middle, and posterior insula, as well as the caudate, putamen, thalamus, hippocampus, and parahippocampal gyrus. Mediation and network-level analyses further supported this dissociation by showing that disgust propensity shapes disgust experience via insula - striatal - hippocampal pathways. Together, these findings provide evidence for a neurofunctional dissociation of disgust propensity and sensitivity and elucidate how trait disgust shapes subjective experiences. They further suggest that disgust propensity and the identified systems may represent promising targets for the regulation of disgust-related pathology.

neuroscience↗

bioRxiv2025

Fusion-driven oncogenic programs shape the immune landscape in translocation renal cell carcinoma

Renal cell carcinomas comprise multiple molecularly distinct cancers but most are treated empirically with therapies designed for clear cell RCC (ccRCC), the most common subtype, due to incomplete understanding of subtype-specific biology. We analyzed single-cell transcriptomes and chromatin accessibility profiles from translocation renal cell carcinoma (tRCC), an aggressive RCC defined by oncogenic TFE3 gene fusions. Unexpectedly, despite arising from a proximal tubule cell of origin similar to ccRCC, tRCCs display markedly distinct oncogenic programs and an immunosuppressive tumor microenvironment. tRCCs exhibit six conserved tumor meta-programs, including epithelial-mesenchymal transition and proximal tubule identity programs whose balance is regulated by TFE3 fusion activity. The fusion-driven EMT program drives a suppressive TME marked by progenitor-exhausted CD8+ T cells, anti-inflammatory SPP1+ macrophages, and matrix-associated fibroblasts (mCAFs). Our findings highlight unique TFE3 fusion-driven biology in tRCC, explaining its reduced immunotherapy responsiveness relative to ccRCC, and suggesting strategies for targeting fusion-driven oncogenic programs and TME reprogramming.

genomics↗

bioRxiv2025

A Multi-Disciplinary Framework for Decoding S1PR1-Selective Agonism

Sphingosine-1-phosphate (S1P), a key metabolite of sphingolipids, plays crucial roles in a wide range of physiological and pathological processes. S1P primarily exerts its functions by binding to G protein-coupled sphingosine-1-phosphate receptors (S1PRs), which include five subtypes (S1PR1-5), thereby activating these receptors and their downstream signaling pathways. Understanding the molecular determinants that govern agonist selectivity among different S1PR subtypes is vital for the rational and precise development of targeted therapeutic agents. Here, four cryo-electron microscopy structures of agonist-bound S1PR1-Gi complexes are reported. Through an integrated approach combining structural analysis, molecular dynamics simulations, and pharmacological assays, the molecular basis for the selectivity of CYM5442, HY-X-1011, Ponesimod, and SAR247799 toward S1PR1 over S1PR3 and S1PR5 is uncovered. Specifically, the selectivity arises from a combination of non-conserved residues within the ligand-binding pocket and at the Gi-protein interface, distinct curved agonist-binding modes oriented toward transmembrane helices 5-7 that cause steric clashes with S1PR3, and the presence of branched moieties at the lower part of three agonists. These features collectively enhance agonist potency and efficacy for S1PR1 while reducing activity at S1PR3 and S1PR5. These findings establish a structural framework for the rational design of next-generation S1PR1 highly selective agonists with improved therapeutic potential.

biochemistry↗

bioRxiv2025

Seq2Karyotype (S2K): A Method for in-silico Karyotyping Using Single-Sample Whole-Genome Sequencing Data

DNA abnormalities characterized by cytogenetic imaging at the single cell resolution, i.e. karyotyping, have long served as cancer diagnostic and prognostic biomarkers. To enable in-silico karyotyping using unpaired whole-genome sequencing data, we developed Seq2Karyotype (S2K), a tool that fits karyotype models with clonality estimation based on read-depth and allelic imbalance in a bulk sample and supports visualization-guided refinement. Analysis on 19 adult and pediatric cancer cell lines revealed unexpected intratumoral heterogeneity involving multiple copy number variation (CNV) states including whole-genome duplication, which were validated by imaging and single-cell omics profiling. Analyses on patient samples showed high concordance with clinical cytogenetic reports for acute myeloid leukemia, and revealed evolutionary trajectories from multi-region metastatic neuroblastomas implicating reversion. These findings highlight extensive and dynamic intratumoral heterogeneity contributed by CNV in both cell line models and patient samples, which may inform future research on tumor evolution under selective pressure such as drug exposure.

bioinformatics↗

bioRxiv2025

Identification and quantification of alternative polyadenylation sites in single cell RNA-seq data using scPAISO

AbstractsAlternative polyadenylation (APA) is a critical posttranscriptional mechanism that generates transcriptomic diversity through the production of mRNA isoforms with distinct 3 UTRs or coding sequences. Current APA analysis based on single-cell RNA sequencing (scRNA-seq) for establishing cell type-specific APA landscapes primarily rely on Read2 data, which lacks precise cleavage site (CS) information. This limitation restricts their ability to achieve precise de novo mapping of polyadenylation sites (PASs). Here, we present single-cell PolyAdenylation ISOform quantification (scPAISO), a computational pipeline designed for de novo identification of PAS and quantification of PAS isoforms in scRNA-seq data, by leveraging the often-discarded Read1 from 3 tag-based scRNA-seq protocols. Unlike existing tools, scPAISO directly captures mRNA 3 end cleavage sites, enabling superior performance in motif enrichment (stronger AAUAAA signal) and peak precision (sharper PAS peaks). Moreover, the smaller peak widths enhance the spatial resolution, enabling more accurate detection of closely spaced PASs in the genome. By integrating Read1 and Read2 data, scPAISO achieves isoform-level quantification with an assignment accuracy exceeding 95%. We demonstrate the robustness of scPAISO in identifying PASs and quantifying APA events across diverse biological contexts, including hematopoiesis, systemic sclerosis (SSc), and mouse tissues. We identified stage-specific 3 UTR lengthening in hematopoietic progenitors, global 3 UTR remodeling in SSc and tissue-specific polyadenylation (PA) preference along with RNA-binding proteins in mice. Overall, scPAISO represents a significant advancement in the analysis of APA at single-cell resolution and provides a powerful tool for exploring the regulatory landscape of APA, offering new insights into transcriptome complexity and gene regulation in both health and disease.

bioinformatics↗

bioRxiv2025

An integrated multi-tissue atlas of epigenomic landscapes and regulatory elements in the bovine genome

Deciphering the regulatory syntax of the genome is essential to understand the genetic and molecular architecture of complex traits, as most trait-associated variants lie in non-coding regions. Yet, functional annotation of the bovine genome remains limited, hindering our ability to unravel the mechanisms underpinning complex traits of economic and ecological importance in cattle. Here, we present a comprehensive epigenetic atlas comprising 1,138 genome-wide epigenetic profiles, including chromatin accessibility, six histone modifications, CCCTC-binding factor (CTCF) transcription factor binding, DNA methylation, chromatin conformation, and transcriptomes across 53 adult tissues, five fetal tissues, and seven primary cell types. This atlas-level data enables us to annotate around 45% of the genome as putative regulatory elements exhibiting tissue- or cell-specific regulatory activity. Leveraging sequence-to-function deep learning models, we discovered 301 sequence motifs and predicted the functional impact of genetic variants through in silico mutagenesis, thereby facilitating the decoding of the regulatory syntax of the cattle genome and fine-mapping of GWAS loci for 22 complex traits. Cross-species analysis further revealed evolutionarily conserved features of regulatory architecture and provided evolutionary insights into complex traits and diseases in humans. Together, this atlas offers a foundational resource for advancing cattle functional genomics, sustainable breeding, and studies of regulatory evolution.

genomics↗

bioRxiv2025

TRIM24 Degradation Counteracts Adaptation to Androgen Receptor Inhibition in Prostate Cancer

The androgen receptor (AR) is the primary therapeutic target in prostate cancer. While androgen deprivation therapy (ADT) and androgen receptor signaling inhibitors (ARSi) are effective, the disease eventually progresses to fatal castration-resistant prostate cancer (CRPC). That said, little is known about the mechanisms in residual disease that initiates tumor relapse upon ADT/ARSi. Here, we discover a crucial role for TRIM24 in supporting the survival of residual cell clusters primed for tumor relapse in vivo. Consequently, reducing TRIM24 with bifunctional degraders (dTRIM24) significantly delays or even prevents the emergence of CRPC in the context of AR reactivation and lineage plasticity. dTRIM24 not only inhibits AR signaling but also counteracts adaptive pathways engaged by AR inhibition itself, such as STAT3 activation and EMT. Our findings underscore the potential of TRIM24 as an effective and druggable target for preventing prostate cancer progression under AR inhibition. SignificanceDespite advances in targeting AR signaling in prostate cancer, tumor relapse remains a major concern. Here, we provide evidence that more durable responses can be achieved by pharmacologically degrading TRIM24. At the molecular level, TRIM24 degradation inhibits both AR signaling and adaptive pathways that enable tumor relapse.

cancer biology↗

bioRxiv2025

MRDadaptis: Self-Adaptive Parameter Configuration Enhances Minimal Residual Disease Detection in Heterogeneous ctDNA Samples

Detection of structural variations (SV) through circulating tumor DNA (ctDNA) has become a key method for detecting minimal residual disease (MRD). However, the heterogeneity of ctDNA samples, characterized by variable limits of detection (LOD) and diverse structural variant types, significantly impacts detection stability and consistency, posing persistent challenges for conventional SV detection tools such as Delly and Manta. These widely-used methods require extensive manual parameter tuning, hindered by the combinatorial complexity of multiple parameters and heterogeneous sequencing data. To address this, we propose MRDadaptis, a novel SV detection tool that uniquely incorporates a self-adaptive parameter optimization mechanism. MRDadaptis distinguishes itself by integrating Bayesian optimization with meta-learning techniques to dynamically adjust detection parameters automatically, based on intrinsic features derived from the ctDNA sequencing data itself. This innovative approach not only reduces manual intervention but also effectively captures sample-specific characteristics, significantly improving detection stability and detection performance. Extensive validation experiments using both simulated and real-world ctDNA datasets demonstrates MRDadaptiss distinct advantages, including markedly improved average F1-scores and superior stability (reduced variance, lower RMSE, increased kurtosis) These results highlight the significant advantages of MRDadaptis in addressing sample heterogeneity, underscoring its potential to improve the accuracy and reliability of MRD detecting through ctDNA analysis. https://github.com/aAT0047/MRDadaptis.git

bioinformatics↗