Biology subjects

Qiao, Y.

Publications and source records attributed to Qiao, Y..

At least 19 recordsLinked to original sources

bioRxiv2026

Response to SMAC mimetics in patient-derived models of triple-negative breast cancer relies on RIPK1 activation

Triple-negative breast cancer (TNBC) is a highly metastatic and aggressive breast cancer subtype with limited targeted treatment options. Second mitochondrial activator of caspases (SMAC) mimetics represent a promising therapeutic class for TNBC patients, although they have yet to be approved clinically. Screening a repository of 69 breast cancer patient-derived xenograft organoid (PDxO) lines revealed that approximately 39% were sensitive to the SMAC mimetic birinapant. To define the basis of resistance in lines that did not respond, we compared birinapant-sensitive (S-) and de novo resistant (R-) TNBC PDxOs. Birinapant caused degradation of inhibitor of apoptosis proteins (IAPs) in both groups but failed to induce cell death in R-PDxOs. We determined that R-PDxOs were susceptible to certain types of apoptosis but were specifically resistant to TNFR-mediated cell death, an integral pathway involved in SMAC mimetic response. Moreover, RIPK1 activation via autophosphorylation, a critical event in TNFR-mediated apoptosis, was absent in both R-PDxOs and PDxOs selected for acquired birinapant resistance. Pharmacologic inhibition or degradation of RIPK1 protected S-PDxOs from birinapant-induced cell death, demonstrating that RIPK1 activation is required for response in TNBC. To investigate how to restore RIPK1 activation in R-PDxOs, we discovered that HOIP, an E3 ubiquitin ligase that inhibits RIPK1 autophosphorylation, was more abundant in R-PDxOs compared to S-PDxOs. Inhibiting HOIP activity restored RIPK1 autophosphorylation and sensitized a subset of R-PDxOs to birinapant. Together, these findings identify impaired RIPK1 autophosphorylation as a mechanism of birinapant resistance in TNBC and suggest that RIPK1 activation state may distinguish SMAC mimetic-sensitive and -resistant tumors. Targeting HOIP may provide a strategy to overcome resistance in selected tumors.

cancer biology↗

bioRxiv2026

Bayesian in situ point spread function modeling enables high-fidelity three-dimensional nanoscopy in deep tissue

Three-dimensional single-molecule localization microscopy enables nanometer-resolution mapping of biomolecular organization in native cellular environments, but extending this capability to deep tissue requires in situ point spread function (PSF) modeling to account for specimen-induced optical distortions. Existing in situ approaches rely on a deterministic mapping between each single-molecule detection and the underlying PSF model. In deep tissue, however, specimen-induced aberrations, optical scattering and elevated background degrade the information content of single-molecule observations, posing a fundamental barrier to reliable PSF estimation. Here we introduce Bayesian in situ PSF modeling (BIM), a computational framework that explicitly models uncertainty in emitter axial position and propagates it through PSF reconstruction. By using an uncertainty-aware posterior fusion strategy, BIM retrieves accurate specimen-matched PSF models directly from raw blinking data under native imaging conditions. We demonstrate BIM by resolving hollow mitochondrial membranes, amyloid-{beta} fibrils, dendrites and spines with high fidelity. When combined with adaptive optics, BIM improves high-fidelity 3D reconstruction in deep tissue at depths exceeding one hundred micrometers.

biophysics↗

bioRxiv2026

Coordinated GlcNAc transport couples nutrient acquisition to invasive growth and virulence in Candida albicans

Candida albicans is a prevalent gut commensal and opportunistic fungal pathogen whose transition from intestinal colonization to invasive infection is influenced by environmental cues. N-acetylglucosamine (GlcNAc), abundant in the gut from host and microbial sources, serves not only as a carbon source but also as a potent signal that promotes hyphal morphogenesis and virulence. However, how C. albicans coordinates GlcNAc uptake to regulate these pathogenic responses remains incompletely understood. Here, we identify Hgt1, a canonical glucose transporter, as an alternative GlcNAc transporter that cooperates with the GlcNAc-specific transporter Ngt1 to promote fungal morphogenesis and virulence. Simultaneous deletion of HGT1 and NGT1 markedly impairs GlcNAc-induced hyphal morphogenesis and virulence-associated gene expression. Mechanistically, Hgt1 facilitates the initial uptake of GlcNAc, promoting Ngt1 induction and subsequent robust hyphal growth, as evidenced by delayed Ngt1 expression and hyphal formation in cells lacking HGT1. These findings reveal a coordinated uptake mechanism involving two differentially regulated sugar transporters that enables C. albicans to respond efficiently to GlcNAc availability. Importantly, disruption of GlcNAc uptake reduces fungal dissemination to distal organs and associated host inflammatory responses in a mouse intestinal colonization model under GlcNAc-supplemented conditions. Together, our findings uncover a previously unrecognized mechanism by which C. albicans coordinates sugar transport to drive nutrient-induced pathogenicity, highlighting GlcNAc uptake as a potential target for limiting fungal virulence and systemic dissemination.

microbiology↗

bioRxiv2026

A multimodal precision oncology platform integrating genomics,single-cell transcriptomics, and functional drug screening expandstherapeutic options in pediatric brain tumors

Precision oncology for pediatric brain tumors mainly relies on clinically validated, targetable genomic alterations, which are often sparse, yield few matched therapies, and do not guide chemotherapy selection. We developed a tiered framework in which deep whole-genome sequencing and single-cell RNA sequencing extend targeted-therapy selection, with ex vivo functional drug screening supporting selection of both targeted therapies and chemotherapies. We applied it to 17 children with malignant CNS tumors. The approach expanded recommendations beyond genomics: functional screening provided every patient with at least one high-confidence targeted-therapy or chemotherapy nomination, while single-cell RNA sequencing identified an average of 37 druggable gene targets per patient, producing a fourfold increase in high-confidence targeted-therapy recommendations. In an exploratory analysis, functional classifications were directionally consistent with outcomes in 8 of 10 evaluable cases, although combination treatments and radiation precluded causal attribution. Single-cell profiling also identified subclone-specific vulnerabilities, supporting prospective evaluation of the platform's feasibility and predictive utility.

cancer biology↗

bioRxiv2026

DS5: An Open-Source Framework for Standardized High-Throughput Drug Screening Data Storage, Analysis, and Drug Prioritization

Background. High-throughput drug screening (HTS) is increasingly used in precision oncology across cell lines, patient-derived models such as organoids (PDO) and xenograft organoids (PDxO), and ex vivo patient samples, with multiple active clinical trials incorporating HTS for individualizing treatment. Yet HTS efforts predominantly rely on ad hoc, spreadsheet-based workflows, with no standardized infrastructure for storing, analyzing, and comparing screens across patients, cohorts, or institutions, limiting reproducibility and slowing clinical data exchange. Existing tools address isolated pieces of the workflow, handling either data management or analysis and visualization, but none integrate standardized storage, reproducible dose-response analysis, individualized drug prioritization, and clinician and molecular tumor board friendly reporting in a single open-source framework. Results. We present DS5, an open-source Python framework that operates on an HDF5-based DS5 file format that unifies standardized storage, quality control, dose-response analysis, cohort-level drug prioritization, and automated reporting in a single lightweight package. DS5 enforces raw-data immutability, integrates RxNorm-based drug name standardization, and scales from small clinical cohorts to large pharmacogenomics datasets on a standard laptop. We validated DS5 against two public benchmarks spanning over 428,000 drug, cell line pairs, recovering published LN IC50 values from GDSC2 (Pearson r = 0.973) and Emax values from CTRP (r = 0.961). Using a published breast cancer PDxO dataset (45 compounds by 16 models), we reproduced GR-based profiles via a custom-metric extension and used DS5's cohort-level prioritization to predict in vivo tumor response with ROC AUC = 0.907 across 30 drug PDX pairs. Finally, we demonstrate the utilities of DS5 in an ongoing pediatric brain tumor precision oncology initiative, where its cohort-normalized drug rankings and automated reports directly support molecular tumor board discussions. Conclusion. DS5 provides the cancer basic and translational research community with a standardized file format and reproducible computational analysis methods to support functional drug screening experiments; and its reporting features facilitate bridging raw drug screening measurements to translational decisions. DS5 is released open-source under the permissible MIT license.

bioinformatics↗

bioRxiv2026

A druggable chromatin vulnerability in suppressive neutrophils restores antitumor immunity

Many cancers evade immunity by converting neutrophils into polymorphonuclear myeloid-derived suppressor cells (PMN-MDSCs), but the chromatin mechanisms that maintain this pathological state remain unclear. Here we show that tumor-induced suppressive neutrophils depend on mSWI/SNF chromatin remodeling. Two orally bioavailable mSWI/SNF ATPase antagonists, a degrader and a catalytic inhibitor, produced immune-dependent tumor control across syngeneic models, including tumors resistant to PD-1 blockade, and enhanced checkpoint therapy without overt toxicity. Treatment rapidly depleted intratumoral PMN-MDSCs, restored functional CD8+ T cells, and blocked tumor explant-induced expansion and suppressive activity of mouse and human PMN-MDSCs. mSWI/SNF antagonism collapsed chromatin accessibility and PU.1/C/EBP{beta} occupancy at regulatory elements that sustain PMN-MDSC identity. Thus, suppressive neutrophils harbor a druggable chromatin vulnerability that can be exploited to restore cancer immunity.

cancer biology↗

bioRxiv2026

Multiomics Characterization Identifies S1P-secreting USSHigh Skeletal Muscle Stem Cells as Essential Drivers of Niche Remodeling and Muscle Regeneration

Acutely induced cellular senescence is increasingly recognized as vital for tissue repair but the precise roles of senescent cells in skeletal muscle regeneration remain paradoxical. Here, using single-cell RNA sequencing and a Unified Senescence Score (USS) methodology, we identify a distinct USSHigh (USSHi) muscle stem cell (MuSC) subpopulation emerging in early phase of acute injury induced muscle regeneration. Isolation via the surface marker MHCII enables characterization of these cells as exhibiting canonical senescent-like features. Further characterization through integrated transcriptomics, proteomics, and secretomics reveals their highly pro-inflammatory secretory capacity. Moreover, lipidomic profiling uncovers that the USSHi MuSCs undergo profound sphingolipid metabolic remodeling to generate upregulated bioactive lipid Sphingosine-1-phosphate (S1P). In vivo specific ablation of this subpopulation using a Pax7-CreERT; Ccl2-LSL-DTA genetic strategy significantly impaired muscle regeneration. Furthermore, spatial transcriptomics and cell-cell communication analyses revealed that USSHi MuSCs act as critical niche modulators, directing crosstalk with multiple cell types. Specifically, S1P is essential for mediating direct USSHi interaction with endothelial cells and USSLo cells to promote endothelial angiogenesis and MuSC expansion in the regenerating muscle. Crucially, exogenous S1P rescues the regenerative deficits caused by USSHi MuSC ablation. Altogether our findings define a senescent-like MuSC population emerging in acute injury induced muscle regeneration and provide definitive evidence to demonstrate the positive role of these cells in enhancing muscle repair via their robust secretory phenotypes and inter-cellular communicative capacity.

cell biology↗

bioRxiv2026

A pretrained unified model enables cellular functional profile prediction and multi-objective virtual drug screening

Cells are characterized by molecular states, coordinated molecular interactions, regulatory programs, and responses to perturbations. Systematic mapping of these cellular functional profiles across biological contexts remains experimentally costly and fragmented. Here we present InsilicoCell, a pretrained multi-modal, multi-task model that unifies prediction of cellular functional profiles spanning molecular states, molecular interactions, and perturbation-induced responses. Built on a supervised transformer architecture and pretrained on more than 88 million measurements across seven tasks, including drug sensitivity, drug-induced gene expression, and drug-protein binding, InsilicoCell learns a shared representation that links molecular profiles to cellular phenotypes, improves performance over task-specific models, and generalizes to unseen entities, contexts, and conditions. InsilicoCell extends beyond cell line systems to patient, spatial and single-cell settings, and enables multi-objective virtual drug screening. It identifies novel candidate compounds with experimental validation, including c-Myc activity inhibitors, antifibrotic agents and stemness-inducing compounds. Together, InsilicoCell provides a scalable framework for predictive cellular biology and therapeutic discovery.

bioinformatics↗

bioRxiv2026

Selective GRAB sensors reveal distinct endocannabinoid dynamics in vivo

The endocannabinoid system modulates diverse physiological processes via two endogenous lipid ligands, 2-arachidonoylglycerol (2-AG) and anandamide (AEA); however, their specific spatiotemporal dynamics remain poorly understood owing to the lack of selective probes. Here, we developed GRAB2-AG2.0 and GRABAEA2.0, two genetically encoded fluorescent sensors that selectively detect 2-AG and AEA, respectively. Both sensors exhibited high apparent affinity and molecular specificity for their respective ligands, enabling the real-time detection of 2-AG and AEA release evoked by electrical stimulation in cultured neurons and acute brain slices. In freely behaving mice, these sensors revealed ligand- and context-specific eCB dynamics: aversive stimulation preferentially evoked 2-AG, whereas psychoactive drugs produced distinct 2-AG and AEA responses. Notably, {Delta}9-THC elicited a sustained 2-AG signal in the nucleus accumbens shell, and local deletion of Dagla markedly attenuated both this signal and {Delta}9-THC-induced hypolocomotion. These sensors therefore enable detecting 2-AG and AEA signaling seperately and reveal an endogenous 2-AG component of the behavioral response to {Delta}9-THC.

neuroscience↗

bioRxiv2026

Coevolution-driven reconstruction of multi-taxa siderophore interaction networks reveals topological diversity of microbial exploitation

Microbial communities are shaped by secreted metabolites that mediate ecological interactions, yet predicting these interactions from genomic sequences remains difficult, because the specific recognition between co-functional metabolites (CFMs), such as siderophores, and their receptor proteins (Rec) cannot be inferred from gene annotation alone. This difficulty arises from three factors: the prevalence of Rec-mediated exploitation, the lack of high-accuracy functional annotations, and the absence of genomic co-localization between functionally paired CFM-Rec in Gram-positive bacteria. Here we present the Coevolution-based Interaction Model (CIM), an automated framework that maps specific CFM-Rec pairings directly from uncurated genomic datasets. Using a dynamic joint optimization strategy that accounts for exploitation asymmetry and avoids combinatorial explosion, CIM identifies functional pairings solely through evolutionary covariation. We validated this approach by reconstructing macroscale iron scavenging networks across nine bacterial taxa. Experiments confirmed that CIM can bridge genomic distances exceeding 3 Mb in the Gram-positive genus Rhodococcus to identify unlinked cognate receptors, and can accurately predict cross-utilization by exploiter strains despite substantial receptor sequence heterogeneity in Burkholderiaceae and Rhizobiaceae. Finally, topological analysis of the reconstructed networks shows that siderophore exploitation acts as a universal topological glue, fusing fragmented microbial populations into highly connected communities, and that the exploitability of siderophore production reverses depending on network modularity. CIM thus offers a scalable, sequence-to-ecology approach for predicting interactions mediated by secondary metabolites in microbial communities.

systems biology↗

bioRxiv2026

A Promoter Competition Hub Orchestrates Runx1 Alternative Promoter Usage during Skeletal Muscle Stem Cell Activation

Alternative promoter (AP) usage profoundly expands transcriptomic and proteomic diversity, yet the regulatory principles governing promoter choice remain poorly understood. Here, using the dual-promoter Runx1 locus as a paradigm in skeletal muscle stem cells (MuSCs), we uncover a promoter competition hub that orchestrates AP selection during MuSC fate transition from activation to proliferation. We find antagonistic expression dynamics between the two Runx1 promoters, with the primary promoter (PP) active in the early activating stage and the secondary promoter (SP) induced later in proliferation. Combinatorial genetic perturbations in vitro and in vivo establish the non-redundant roles of PP- and SP-derived isoforms in MuSC lineage progression. Mechanistically, we find that PP and SP engage in reciprocal competition in a multi-connected enhancer-promoter (E-P) loop hub. Further dissection identifies a cohort of key enhancers that dynamically interact with PP/SP to orchestrate the competition. Moreover, we establish the transcription factor USF1 as a key factor driving the dynamic E-P interactions and PP/SP competition. Beyond Runx1, high-resolution Micro-C reveals promoter competition as a general mechanism regulating a subset of AP choices in MuSC activation/proliferation. Collectively, our study uncovers a dynamic promoter competition hub that governs AP selection in MuSC lineage progression, offering fundamental insights into how 3D genome architecture coordinates precise, stage-specific gene expression programs during cell fate transitions.

genetics↗

bioRxiv2026

SALL2 constrains TEAD4 by maintaining repressive chromatin to restrict trophectoderm identity

Embryonic development is marked by the successive restriction of developmental potential and the specification of embryonic and extraembryonic lineages. Yet, how these lineage decisions are established, and how the epigenome is remodelled to promote and restrict cell fate transitions, remains poorly understood. Here, we demonstrate that SALL2 knockdown in primed human pluripotent stem cells (hPSCs) triggers a trophectoderm (TE)-like phenotype, characterized by palisade-like morphology and the up-regulation of TE-associated genes. Mechanistically, SALL2 physically interacts with the key TE driver TEAD4 and maintains bivalent, repressive chromatin (H3K4me3/H3K27me3) at TE-specific loci. Reduced SALL2 led to enhanced TEAD4 occupancy and disrupted H3K27me3 and increased active chromatin marks at TE genes. Importantly, depletion of TEAD4 abolished the TE-like phenotype induced by SALL2 knockdown, demonstrating that TEAD4 is required for the downstream effects of SALL2 loss. In support of this, blastoid-like aggregates can be generated from primed hPSCs with SALL2 knocked down. Together, our findings identify SALL2 as a key epigenetic barrier that restrains TE lineage commitment by limiting TEAD4-dependent activation of the trophoblast transcriptional program. Key findingsO_LISALL2 acts as a molecular barrier to trophectoderm differentiation. C_LIO_LISALL2 suppresses the trophectoderm by maintaining bivalent repressive chromatin at TEAD4-bound loci. C_LIO_LIBlastoid-like structures can be generated from primed-state media when SALL2 was knocked down. C_LI O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=91 SRC="FIGDIR/small/737659v1_ufig1.gif" ALT="Figure 1"> View larger version (20K): org.highwire.dtl.DTLVardef@42cafaorg.highwire.dtl.DTLVardef@11c040borg.highwire.dtl.DTLVardef@4d9ffborg.highwire.dtl.DTLVardef@42546a_HPS_FORMAT_FIGEXP M_FIG C_FIG

cell biology↗

bioRxiv2026

Extracellular injection system combined with peptides for intracellular Staphylococcus aureus treatment

The inaccessibility of intracellular bacteria has long rendered the treatment of Staphylococcus aureus infections an challenge. Studies have demonstrated that the extracellular injection system PVC can accurately deliver proteins into cells, which would not need small molecules, and enables effective intracellular delivery of antimicrobial peptides for treatment. Accordingly, we selected antimicrobial peptides including Cecropin, LL37 and Indolicidin that possess potent bactericidal activity, and established the Directed Antimicrobial Assault platform (DAAT) by leveraging the intracellular delivery capacity of PVC. DAAT Cecropin, DAAT LL37 and DAAT Indolicidin inhibited intracellular bacteria in a dose-dependent manner, with DAAT LL37 reaching 86.76% inhibition; after 72 h of treatment, viable-cell numbers reduse to 66--82-fold those of the control. Tail-fibre retargeting enabled direct extracellular S. aureus killing, while combined DAAT therapy promoted wound healing in mice. These findings expand the utility of PVC-derived nanosyringes and establish DAAT as a modular platform for intracellular antimicrobial peptide therapy.

synthetic biology↗

bioRxiv2026

A Stress-Adaptive Lipid Kinase Axis Defines Metabolic Vulnerabilities in Neuroendocrine Prostate Cancer

Neuroendocrine prostate cancer (NEPC) persists in a profoundly hypoxic microenvironment, yet the mechanisms enabling tumor adaptation to this metabolically challenging niche remain undefined. Here, we identify the lipid kinase PIKfyve as overexpressed in NEPC, functioning as a central node in a stress-lipid kinase axis that drives adaptation to persistent endoplasmic reticulum (ER) stress. Mechanistically, NEPC requires PIKfyve-mediated lysosomal degradation and lipid recycling to maintain metabolic homeostasis under hypoxia. PIKfyve inhibition disrupts lysosomal function, leading to ER stress accumulation and activation of a compensatory, sterol regulatory element-binding protein (SREBP)-dependent de novo lipogenesis program essential for NEPC survival. This stress-lipid axis creates a synthetic vulnerability between PIKfyve and fatty acid synthase (FASN), where dual inhibition synergistically amplifies ER stress, triggers the terminal unfolded protein response, and induces tumor cell death. These findings reveal a metabolic adaptation in NEPC and provide preclinical evidence that co-targeting PIKfyve and FASN can overcome hypoxia-associated stress adaptation.

cancer biology↗

bioRxiv2026

cuBayes: GPU accelerated FreeBayes that achieves 1-minute whole-genome SNV calling while maintaining algorithmic semantics

Next-generation sequencing now produces whole-genome data in hours, but downstream variant calling remains a multi-hour to multi-day bottleneck that excludes genomic analysis from time-critical clinical settings. GPU acceleration offers a natural path forward -- variant calling is inherently parallelizable across genomic positions -- yet open-source infrastructure for porting existing algorithms to GPU hardware remains limited, leaving many widely-used tools without accelerated implementations. FreeBayes, a haplotype-based variant caller central to the 1000 Genomes Project and to multi-sample tumor evolution analyses, exemplifies this gap: it is natively single-threaded despite its algorithmic suitability for parallelization. We present cuBayes, a CUDA implementation of FreeBayes germline SNV calling that completes HG002 and HG004 2x250bp Illumina 60x whole-genome analysis in one minute (as opposed to hours if not days with manual region-based CPU parallelization) on a single NVIDIA RTX 6000 Ada GPU, while producing variant calls with 99.97% concordance to the CPU reference. cuBayes is structured around an atom/molecule architecture in which reusable functional units (BAM decompression, position-wise pileup, batch coordination) are cleanly separated from algorithm-specific logic, providing a foundation intended to support acceleration of additional sequence analysis algorithms without redundant low-level engineering.

bioinformatics↗

bioRxiv2026

TDP-43 regulates chromatin looping and gene transcription through binding and stabilizing DNA G-quadruplex structures

TAR DNA-binding protein 43 (TDP-43) is a multifunctional DNA/RNA-binding protein implicated in transcriptional and post-transcriptional regulation. Dysregulation of TDP-43 is closely correlated with human diseases such as cancer and neurodegenerative diseases. Although its roles in RNA metabolism are well characterized, its function in transcriptional regulation remains largely underexplored. DNA G-quadruplexes (dG4s) are non-canonical nucleic acid structures enriched at gene promoters and regulatory elements, where they facilitate chromatin looping and gene transcription. Here, we investigated the transcriptional regulatory role of TDP-43 by integrating multi-omics datasets, including Hi-C, dG4 ChIP-seq, TDP-43 ChIP-seq, RNA-seq and ATAC-seq from K562 and HepG2 cells. Our analyses demonstrate TDP-43 binding and dG4s formation are highly colocalized at chromatin loop anchors, particularly at promoter and enhancer regions. TDP-43 occupancy at these anchors correlates with increased dG4 stability, chromatin loop interaction frequency, elevated chromatin accessibility, and upregulated gene expression. Morover, TDP-43 knockdown in HepG2 cells revealed a significant reduction in dG4 formation and loop interaction strength, accompanied by widespread transcriptional dysregulation. Collectively, our findings highlight a novel regulatory role of TDP-43 in facilitating long-range chromatin interactions and transcriptional activation through binding to and stabilizing dG4 structures, providing a mechanistic basis for gene dysregulation driven by TDP-43 dysfunction in diseases.

bioinformatics↗

bioRxiv2026

Rewiring Oncogenic Transcriptional Complexes with Domain-ALTeration Chimeras (DALTACs) in Prostate Cancer

Transcriptional addiction to the androgen receptor (AR) underlies metastatic castration-resistant prostate cancer (mCRPC), where AR maintains oncogenic programs through domain-specific interactions with the acetyltransferases p300/CBP. Here, we describe a distinct therapeutic modality, Domain-ALTerAtion Chimeras (DALTACs), that rewire endogenous protein complexes by enforcing non-native domain-domain interactions. Our first-in-class AR-p300/CBP DALTAC-1 induces synthetic proximity between the AR ligand-binding domain and p300/CBP-bromodomain, misconfiguring their native interface and locking the complex in a non-productive state. DALTAC-1 triggers a super-inhibitory effect, suppressing AR-driven transcription and proliferation more potently than combined AR and p300/CBP inhibition. Mechanistically, DALTAC-1 reprograms p300/CBP substrate engagement, abolishing the histone mark H2B N-terminal acetylation (H2BNTac) while inducing neomorphic acetylation of AR and coactivators, ultimately collapsing the AR neo-enhanceosome. Chromatin profiling revealed redistribution of AR and p300/CBP toward palindromic AREs, accompanied by disruption of cofactor and transcriptional machinery recruitment at oncogenic AR/ERG neo-enhancers. DALTAC-1 exhibits exquisite lineage selectivity, displaying potent activity in AR-p300/CBP dual-dependent cells while sparing AR-negative cells. In multiple in vivo models, DALTAC-1 induces deep and durable tumor regressions. Together, these findings establish DALTACs as a broadly applicable strategy to rewire disease-defining complexes through domain-topology alteration, expanding induced-proximity therapeutics, while DALTAC-1's precise lineage-selectivity supports its translational potential in AR-driven prostate cancer.

cancer biology↗

bioRxiv2026

VeloTrace Reconciles Divergent Velocity and Trajectory in Single-cell Transcriptomics with Deep Neural ODE

Cellular identity and fate transitions are governed by continuous molecular processes that form dynamic trajectories within a high-dimensional transcriptomic landscape. Existing methods attempt to model these dynamics from two complementary perspectives: trajectory inference and velocity modeling. Ideally, velocity and trajectory are dual aspects of transcriptomic dynamics where velocity is tangent to trajectory everywhere. This inherent connection between velocity and trajectory is currently absent in transcriptomic analysis. Splicing velocity are precision-limited to inadequately-sequenced genes, while trajectory inference prioritizes the modeling of global trends while omitting local dynamics. This divergence breaks the geometric continuity between local velocities and global trajectories, hindering the reliable interpretation of developmental dynamics. To reconcile trajectory inference and RNA velocity, we introduce VeloTrace, a framework that unifies them through Neural Ordinary Differential Equations (NeuralODEs). VeloTrace learns a continuous-time velocity field whose integral curves constitute the trajectory itself, while ensuring that velocities are tangent to integral paths everywhere. Leveraging a splicing quality score, VeloTrace incorporates high-quality splicing velocity as partial supervision for velocity orientation and grounding. During optimization, VeloTrace incorporates a Monte Carlo multi-time-frame supervision strategy to ensure coherence between local and global trajectorys and suppress sequencing-induced stochastic diffusion. Through refining the velocity field and cell-specific parameters for pseudo-time, expression, and velocity, VeloTrace reconstructs a smooth, local-and-global-coherent velocity-vector-guided flow in the transcriptomic latent space. This strategy ensures a complementary integration of velocity and trajectory, imputing the transcriptional kinetics for genes of insufficient strength, whose kinetics cannot be accurately portrayed by splicing velocity. In simulation benchmarks, VeloTrace captured the transcriptional dynamics of all expressed genes, even those with inadequate sequencing coverage, producing velocity directions that were most consistent with the true direction and every-where tangential across the entire process, outperforming state-of-the-art methods, including scVelo, UniTVelo, VeloVI and scTour. VeloTrace uniquely reconciles RNA velocity and trajectory inference, creating a velocity field where each cell can infer past and future transitions from its current state. Moreover, VeloTrace extends reliable velocity estimation to a broader set of genes. When applied to mouse neural stem cell differentiation data, it successfully recovers dynamics of driver genes for two developmental lineages, including those with low expression, shedding light on their regulatory roles during differentiation. This unified framework lays the foundation for more accurate modeling of gene regulation and cell fate decisions in complex biological systems.

bioinformatics↗