Biology subjects

Huang, Y.

Publications and source records attributed to Huang, Y..

At least 91 records · Page 5Linked to original sources

bioRxiv2026

Proteomic Profiling Identifies CLDN3 as a Tumor-Selective Therapeutic Target in Small Cell Lung Cancer

Small cell lung cancer (SCLC) remains a highly lethal disease with limited targetable surface antigens beyond delta-like ligand 3 (DLL3). We sought to systematically identify and validate tumor-selective cell-surface targets in relapsed SCLC. To this end, we developed an integrated proteogenomic pipeline combining single-cell RNA sequencing, combinatorial optimization, mass spectrometry-based proteomics, and immunohistochemistry to systematically map the SCLC surfaceome of 49 tumors across 25 patients with relapsed SCLC. Using this approach we found claudin-3 (CLDN3) to be a consistently expressed and tumor-selective antigen, with broader coverage than DLL3, which is the current clinical benchmark. CLDN3 was highly expressed across various treatment states, while maintaining low expression in most nonmalignant tissues. Functional validation using a novel CLDN3-specific monoclonal antibody (ABN501) demonstrated NK cell-mediated cytotoxicity in vitro and tumor regression in vivo, as well as a favorable safety profile. These findings support clinical development of CLDN3-directed therapies and demonstrate the utility of integrated proteogenomic approaches for antigen discovery in solid tumors.

cancer biology↗

bioRxiv2026

Tree diversity and mycorrhizal associations jointly regulate seasonal canopy cooling in forests

The increasing frequency and intensity of heatwaves under climate change highlight the need to understand how biodiversity regulates forest canopy thermal dynamics. Although tree diversity can buffer the microclimate, its effects on canopy temperature and the role of mycorrhizal symbioses remain unclear. We addressed this question in the MyDiv tree diversity experiment in Germany, where tree species richness (1-, 2-, and 4-species mixtures) and mycorrhizal types (arbuscular, ectomycorrhizal, and mixed) are factorially manipulated. During the 2024 growing season, we conducted nine uncrewed aerial vehicle (UAV) surveys using integrated thermal and LiDAR sensors to quantify canopy temperature and structural complexity, together with measurements of leaf water content, specific leaf area, soil moisture, and vapour pressure deficit (VPD). Increasing tree diversity generally reduced canopy temperature, although the strength of this relationship varied seasonally and among mycorrhizal types. Cooling effects were strongest during peak summer heat and were more pronounced in arbuscular mycorrhizal (AM) communities than in ectomycorrhizal (EM) and mixed (AM+EM) communities. In contrast, EM communities exhibited greater canopy structural complexity, whereas AM communities maintained higher soil and leaf water content. Structural complexity increased with tree diversity but did not necessarily result in greater canopy cooling. Structural equation modelling revealed that forest thermal buffering emerged through complementary structural and hydraulic pathways, whose relative importance shifted seasonally, with hydraulic regulation becoming increasingly important under hotter and drier conditions. By linking canopy temperature, canopy structure, and plant water relations, our study provides mechanistic insights for understanding how multiple facets of biodiversity regulate forest thermal buffering under climate warming.

ecology↗

bioRxiv2026

The endosomal trafficking protein Myopic differentially regulates Drosophila C virus infection in cultured cells and adult flies

Positive-sense RNA viruses extensively exploit host membrane trafficking pathways to establish intracellular replication organelles required for efficient viral replication. However, the contribution of endosomal trafficking proteins to infection by Drosophila C virus (DCV), a natural dicistrovirus of Drosophila melanogaster, remains poorly understood. Here, we investigated the role of Myopic (Mop), a conserved ESCRT-associated endosomal trafficking protein, during DCV infection. Knockdown of mop in cultured S2 cells significantly increased DCV RNA and viral protein accumulation without affecting viral binding or entry, indicating that Mop restricts DCV replication at a post-entry stage. In addition, depletion of mop altered the intracellular distribution of viral proteins, suggesting that Mop may influence the organization of DCV-associated intracellular membrane compartments. Unexpectedly, fat body-specific knockdown of mop in adult flies produced the opposite phenotype, resulting in reduced viral accumulation and prolonged survival following systemic DCV infection. This antiviral phenotype was not associated with enhanced activation of the STING or JAK-STAT pathways. Instead, transcriptomic and proteomic analyses revealed extensive remodeling of gene and protein expression, including altered abundance of proteins associated with autophagy and RNA interference. Together, our findings identify Mop as a previously unrecognized regulator of DCV infection and reveal distinct cell-autonomous and systemic functions of this conserved trafficking protein. These results highlight the importance of endosomal trafficking in antiviral defense and demonstrate that host membrane trafficking factors can exert fundamentally different effects on virus infection at the cellular and organismal levels.

microbiology↗

bioRxiv2026

Patterns and correlates of invasive alien plant richness in China's abandoned croplands

Cropland abandonment is a widespread socio-ecological transition that can generate heterogeneous ecological outcomes, including opportunities for vegetation recovery as well as the accumulation of invasive alien plants (IAPs). Understanding broad-scale correlates of IAP richness in abandoned croplands is challenging because published studies differ in sampling design, spatial extent, and reporting detail. To provide an exploratory national-scale synthesis, we compiled literature-derived occurrence records of 57 IAP species reported from abandoned croplands across China and examined study-level recorded richness using generalized linear mixed models (GLMMs) with province as a random effect. Fourteen socio-economic and environmental predictors were screened for multicollinearity and standardized, and the number of Higher Education Institutions (HEIs) was included as a proxy for potential sampling-effort variation. Asteraceae accounted for 43.9% of recorded species, and more than 70% of taxa were classified as high-risk invaders (Levels 1-2). Recorded richness exhibited a pronounced southeast-northwest gradient, with higher values in economically developed coastal provinces. In the exploratory GLMM, regional GDP (IRR = 1.67, p < 0.05) and mean annual temperature (IRR = 1.49, p < 0.05) were positively associated with recorded richness, whereas other environmental, accessibility, soil, and sampling-effort variables showed no detectable associations. Model diagnostics indicated no evidence of overdispersion, zero inflation, or residual spatial autocorrelation. Given the heterogeneous nature of literature-derived data and the small number of study units, these results should be interpreted as broad-scale correlational patterns rather than causal drivers. The findings highlight regional socio-economic context and climatic conditions as key correlates of recorded IAP richness in abandoned croplands and provide an initial baseline for understanding invasion patterns in post-agricultural landscapes undergoing rapid land-use transitions..

ecology↗

bioRxiv2026

scSAID: A Comprehensive Cross-Species Single-Cell Skin Atlas Reveals Species-Specific Responses to Psoriasis

Single-cell RNA sequencing has rapidly expanded the scale of skin transcriptomic data, yet these datasets remain fragmented across studies spanning different species, diseases and experimental manipulations. An up-to-date, comprehensive, and queryable single-cell cross-species repository for skin is still lacking. Here, we present scSAID (skin-scsaid.com), a single-cell database with an interactive web portal offering a broad suite of in-depth analyses for human and mouse skin. It integrates more than 1.2 million high-quality cells collected from 252 samples, establishing a unified reference for cell-type annotation, cross-species comparison and pathological studies. Using psoriasis as a case study, we demonstrate how scSAID can be used to evaluate how faithfully mouse models reproduce human pathology. Systematic comparison with the imiquimod-induced mouse model revealed numerous species-specific molecular signatures of psoriasis, including human-specific NFKB1 activation and STAT1 involvement, indicating that the current mouse model captures only limited aspects of the disease. We further introduce psoSpotter, a disease-biomarker-selection algorithm that, coupled with in silico perturbation using scSAID data, uncovers PPIA as a novel psoriasis drug target, illustrating the potential of scSAID for identifying therapeutic approaches. Overall, scSAID delivers a large-scale, cross-species skin single-cell resource and analysis platform, opening new opportunities for the discovery of disease-relevant targets in skin diseases.

bioinformatics↗

bioRxiv2026

pHaseMD4AI: Phase-Space Dynamics Dataset with Chemical and pH Perturbations for Physically and Kinetically Consistent Biomolecular AI

Protein function emerges from dynamic conformational ensembles and transitions that are challenging to characterize experimentally and computationally. Recent advances in generative AI have created new opportunities for learning molecular thermodynamics, kinetics, and conformational evolution directly from simulation data, but progress is limited by the availability of large-scale datasets that combine rigorous sampling, complete phase-space information, and diverse physicochemical perturbations. Here, we present pHaseMD4AI, a molecular dynamics dataset that combines a globally equilibrated peptide branch with a protein-scale constant-pH molecular dynamics (CpHMD) branch spanning hundreds of soluble proteins. The peptide branch includes a complete set of canonical tripeptide and tetrapeptide systems together with post-translationally modified (PTM) and protonation-state datasets, providing synchronized atomic coordinates (R), velocities (V), forces (F), and Markov state model-based kinetic annotations. An accompanying web portal (https://isb.zju.edu.cn/md4ai/) enables users to browse, visualize, and download trajectories, annotations, and metadata. As an example application, we demonstrate a sequence-based model that can predict residue-level equilibrium dihedral distributions from sequence. pHaseMD4AI provides a resource for developing and benchmarking molecular machine learning methods while supporting broader studies of biomolecular dynamics under sequence, post-translational modification, and protonation-state perturbations.

bioinformatics↗

bioRxiv2026

Widely used GWAS methods can be poorly suited to SNP-level localization under diffuse polygenic architecture in livestock

In livestock populations, genome-wide association studies (GWAS) can produce strong, apparently localized associations even when no truly discrete nearby causal effect exists. This occurs because small effective population sizes, strong family structure, long-range linkage disequilibrium (LD), and diffuse polygenic architecture can cause the effects of many variants to accumulate and be captured jointly across broad genomic intervals, making variant-level associations difficult to interpret biologically. Using real pig genotypes, we constructed a benchmark in which phenotypes were simulated under diffuse polygenic architecture across a genome partitioned into alternating effect and null windows, with central-null regions (at least 1 Mb away from effect-containing regions) positioned to detect long-range LD-driven signal propagation. We evaluated nine configurations of six GWAS methods (BOLT-LMM, REGENIE, fastGWA, FarmCPU, BLINK, and SLEMM) under this architecture. The central finding is that strong associations, of the kind normally read as evidence of nearby moderate- or large-effect variants, are produced by many of these methods even though the simulated signal is distributed across many tiny effects and cannot be localized to any single variant. The methods differed sharply in the extent of locus-level spillover: several produced large numbers of genome-wide significant loci within central-null regions, whereas the full-GRM mixed-model benchmark (SLEMM) produced no genome-wide significant loci in central-null regions. These results show that, under a highly polygenic architecture with livestock-like LD, GWAS tool choice has major consequences for biological interpretation. When the goal is to localize biologically meaningful signals rather than to flag association peaks that may merely reflect tiny effects accumulated through LD across a broad block, methods that control long-range LD spillover should be prioritized.

genetics↗

bioRxiv2026

APOE4 disrupts the central dogma by arresting neuronal proteome dynamics

Apolipoprotein E4 (APOE4) is the strongest genetic risk factor for late-onset Alzheimers disease and promotes neuronal dysfunction through incompletely understood mechanisms. Here, we integrated transcriptomic, translatomic, and proteomic profiling of isogenic APOE3 and APOE4 human iPSC-derived neurons and found that APOE4 fundamentally impairs neuronal proteome renewal. Although transcriptional changes were modest, APOE4 disrupted ribosome occupancy, altered translational dynamics, and uncoupled protein abundance from transcript levels. Proteome-wide turnover measurements revealed a global extension of protein half-lives and widespread accumulation of long-lived proteins. Functional proteomic analyses demonstrated concurrent lysosomal and proteasomal impairments associated with reduced proteasome activity and increased association of APOE with neuronal proteasomes. Longitudinal proteomics further showed that protein accumulation emerges during neuronal maturation and precedes a senescence-like cellular stress state. Together, these findings identify impaired proteome renewal as a central mechanism underlying neuronal vulnerability to APOE4 and establish defective proteostasis as an early pathogenic event in Alzheimers disease.

neuroscience↗

bioRxiv2026

Combination siRNA delivery as a therapeutic strategy for ADPKD

Autosomal dominant polycystic kidney disease (ADPKD) is the most common genetic kidney disease worldwide, characterized by progressive cyst growth and inflammation, yet effective targeted therapies remain limited. Here we show that TMEM16A and MCP-1, key mediators of cyst-lining epithelial expansion and inflammatory macrophage recruitment respectively, are consistently upregulated in cyst-lining collecting duct (CD) epithelia across murine, porcine, and human ADPKD models. In human ADPKD patient cells, although individual silencing of TMEM16A or MCP-1 transcripts reduced cyst growth, combined silencing produced superior therapeutic efficacy, establishing the rationale for evaluating dual-target delivery. To achieve dual gene silencing in the kidneys, we delivered Tmem16a and Mcp-1 siRNA using peptide amphiphile micelles (PAMs), an ultrasmall nanoparticle platform that enables efficient renal targeting. To redirect siRNA-loaded PAMs to CD epithelia, we functionalized their surface with a CD-targeting peptide (CDM), which enabled preferential accumulation in cyst-lining CD epithelia. In an inducible Pkd1-deficient mouse model, co-delivery of CDMs loaded with Tmem16a and Mcp-1 siRNA reduced kidney enlargement, cystic burden, tubular injury, and macrophage infiltration, with efficacy exceeding non-targeted siRNA delivery at equivalent doses. CDM demonstrated enhanced uptake in primary human ADPKD patient-derived CD cells and dual gene silencing reduced target gene expression and cyst expansion, establishing translational relevance. These findings establish CD peptide-functionalized micelles as a route to cell-type-selective RNAi in the kidney, delivering siRNA to cyst-lining CD cells. Furthermore, because both targets, TMEM16A and MCP-1, are transcribed within CD cells, our siRNA-loaded CD-targeting micelles silence two drivers of cyst expansion, and their simultaneous suppression represents an effective therapeutic strategy for ADPKD.

bioengineering↗

bioRxiv2026

Damaging RBM20 E-rich domain variants are not rescued by gene replacement

The promise of precision therapeutics in genetic cardiomyopathies relies on linking specific therapies to variant mechanisms. Missense variants in the cardiac splice regulator RBM20 cause a highly penetrant and arrhythmogenic dilated cardiomyopathy. Disease-causing variants in RBM20s arginine-serine rich (RS) domain act via formation of toxic gain of function cytoplasmic granules, but this is not true for a small number of clinically adjudicated pathogenic variants in its glutamate(E)-rich domain. To better define the effects of E-rich domain variants, we developed a scalable screen based on induced pluripotent stem cell (iPSC) cardiomyocyte differentiation that identified several additional damaging variants. Several of these reduced RBM20 protein abundance and stability. We therefore hypothesized that, unlike RS domain variants, these E-rich variants might be rescued by RBM20 overexpression. To test this hypothesis, we generated induced pluripotent stem cells (iPSCs) from a patient with a pathogenic E-rich domain variant (p.E913K), and confirmed reduced RBM20 protein expression in these RBM20+/p.E913K cells after differentiation to iPSC-derived cardiomyocytes (iPSC-CM, vs. engineered isogenic RBM20+/+). These iPSC-CMs also displayed aberrant transcriptional splicing, reduced contractility, increased calcium-induced calcium release, and nuclear localization of RBM20 protein, often with more than the two expected RBM20-centric splice factories. AAV-based overexpression of RBM20 reversed some, but not all of the mis-splicing events identified in RBM20+/p.E913K iPSC-CMs, and did not improve their abnormal contractility, calcium handling or supernumerary RBM20 nuclear granules. In summary, our data indicate that pathogenic E-rich domain variants reduce RBM20 protein abundance, but that their mechanism is unlikely to be explained by haploinsufficiency alone.

genetics↗

bioRxiv2026

High-resolution transcriptomic profiling of Arabidopsis thaliana across a 37°C-40°C thermal gradient

Thermal adaptation is critical for organismal viability, with acquired thermotolerance (AT) in Arabidopsis thaliana typically conferred by acclimation temperatures between 34{degrees}C and 37{degrees}C, while acclimation at 40{degrees}C fails to protect against lethal heat stress. To elucidate the transcriptional mechanisms underlying the loss of AT at higher temperatures we performed RNA-seq profiling of Arabidopsis seedlings across a single-degree thermal gradient from 37{degrees}C to 40{degrees}C. Our analysis reveals that all of these temperatures result in a robust heat shock response, characterized by the upregulation of genes involved in protein folding and stress responses. However, each temperature elicits a distinct transcriptional signature. These findings demonstrate that temperature-specific fine-tuning of the heat shock response occurs within this narrow range and that these differences may dictate the successful acquisition of thermotolerance. This dataset provides a valuable resource for understanding the molecular architecture of heat-stress adaptation and the distinct transcriptional states associated with different thermal regimes.

plant biology↗

bioRxiv2026

A shear lag model of the podocyte foot process network predicts a mechanical feedback loop driving progressive effacement

The podocyte foot process network forms the final barrier of the kidneys glomerular filtration system. Under mechanical stress this network is prone to injury in which podocytes lose connectivity to their neighbors and begin the progression toward effacement, but what governs its mechanical resilience is unknown. We show that the network is built like a lap joint: two major processes coupled through interdigitating foot processes, a configuration that behaves as a classical shear lag system, with force concentrating at the joint ends and decaying over a characteristic transfer length set by geometry and stiffness. A discrete network model reproduces the continuum shear lag solution and identifies a hierarchy among governing parameters, with cytoskeletal stiffening of the major process amplifying foot process force more potently than basement membrane stiffness. Applying the model to morphometric data from puromycin aminonucleoside nephrosis, a model of human minimal change disease and early focal segmental glomerulosclerosis, reveals a mechanical positive feedback loop: force concentration drives foot process loss, which raises force on surviving segments and accelerates further loss. This nonlinear amplification implies a threshold beyond which failure becomes self-sustaining, analogous to the critical crack length in fracture mechanics.

biophysics↗

bioRxiv2026

SHINE: Decoding transcriptional-metabolic microenvironments through higher-order spatial integration

Spatial omics technologies are expanding to co-profile transcriptomics and metabolomics on the same tissue slide, providing complementary views of gene expression and biochemical activity to reveal molecular programs within native tissue microenvironments. However, integrating the transcriptome and metabolome remains technically challenging due to spatial misalignment, resolution disparity, and higher-order cross-modality interactions. Here, we present SHINE, a hypergraph-based computational framework for the joint analysis of spatial gene expression and metabolic networks derived from the co-profiling slide, focusing on representation learning and cross-modality interaction. Across multiple datasets, SHINE consistently outperformed existing methods for domain segmentation and biomarker co-localization, and provided interpretable insights into metabolic-transcriptional microenvironments. Specifically, on Parkinsons disease mouse models, SHINE accurately delineates dopaminergic neuron-depleted regions and reconstructs coherent dopamine-associated axes. In human lung and breast cancers, SHINE resolves tumor-associated spatial regions and identifies spatially organized gene-metabolite programs associated with the tumor microenvironment. SHINE enables scalable spatial multi-omics integration across diverse biological systems.

bioinformatics↗

bioRxiv2026

High-throughput stomatal phenotyping provides selection targets for stress-resilient wheat

Phenotyping stomatal traits and their developmental plasticity is time-consuming but holds potential to improve water use efficiency and photosynthesis for designing stress-tolerant crops under climate change. Here, we develop a robust, high-throughput pipeline for phenotyping 14 stomatal traits in winter wheat related to size, variation, maximum conductance, and spatial patterning. We (1) analyze over 25,000 images from 60 wheat cultivars grown in growth chamber, greenhouse, and field conditions; (2) investigate the impact of light, temperature, and reduced water and nitrogen supply on stomatal traits and their developmental plasticity across adaxial and abaxial surfaces; and (3) evaluate genetic diversity and breeding progress of stomatal traits. Stomatal traits were highly broad-sense heritable, were largely plastic in response to environmental conditions, and showed genotype-specific responses. Stomatal traits of third leaves under controlled environments with stable light and temperature conditions reliably captured the genetic variance of flag leaves under field conditions. Our data suggests that the upper leaf surface contributed more to transpiration and cooling through consistently higher stomatal density, area, and maximum conductance, while the lower surface facilitated CO2 diffusion via systematic proper patterning and spacing. Breeding maintains the genetic diversity of stomatal traits, and our pipeline facilitates breeders to target them to enhance water use efficiency in high-yielding modern cultivars.

plant biology↗

bioRxiv2026

TEscape: Defining the human transposable element transcriptome using multiplatform long-read sequencing

Transposable elements (TEs) not only account for half of the human genome sequence but also generate transcripts that contribute to transcriptomic diversity. Yet, their repetitive nature has hindered accurate quantification of the full TE-derived transcriptome, a challenge that long-read sequencing can overcome. Here, we combined multiplexed arrays isoform sequencing (MAS-ISO-seq) with a dedicated computational framework (TEscape) to perform an in-depth annotation of the human TE transcriptome. To capture the breadth of human transcriptome diversity, we profiled six representative cell types spanning three distinct biological contexts, including metabolism with, primary patient-derived adipogenic cells at two differentiation stages, and iPSC derived hepatic progenitor cells; the nervous system with iPSC-derived neurons, neural progenitor cells (NPCs), and pluripotency using induced pluripotent stem cells (iPSCs). Together, these datasets yielded over 235 million full-length long reads. First, to assess data coverage and transcriptome depth, we quantified protein-coding gene expression, detecting 14,312 genes (73.6% of all annotated protein-coding genes), which is a level consistent with deep and comprehensive transcriptome representation. Second, focusing on TE-derived transcripts, we identified >83,000 previously unannotated isoforms, the vast majority (84%) originating from a complex combination of multi-TEs. We also identified solo TEs, which are predominantly from LINE1 (14%). We confirmed that TE-transcripts are able to be exemplified by signatures detected in Liver Hepatocellular Carcinoma (LICH). Together, MAS-ISO-seq and TEscape establish the first long-read-based, high-resolution atlas of transcribed human TEs, providing a foundational resource for integrative transcriptome analyses and for investigating TE expression and regulation in health and disease. O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=112 SRC="FIGDIR/small/737305v1_ufig1.gif" ALT="Figure 1"> View larger version (35K): org.highwire.dtl.DTLVardef@18158aeorg.highwire.dtl.DTLVardef@e51fdforg.highwire.dtl.DTLVardef@8f9504org.highwire.dtl.DTLVardef@804113_HPS_FORMAT_FIGEXP M_FIG Graphical Abstract C_FIG

bioinformatics↗

bioRxiv2026

Mechanism of fatty acid uptake and inhibition in human FATP2

Fatty Acid Transport Protein 2 (FATP2) couples fatty acid uptake to intracellular activation and is associated with pathological lipid accumulation in cancer and nonalcoholic fatty liver disease. Here, we present cryo-electron microscopy structures of human FATP2 across its reaction cycle. Our structures suggest that FATP2 recruits fatty acids directly from the membrane interface through a hydrophobic tunnel. Catalysis involves a [~]130{degrees} rotation of the C-terminal domain, a transition trapped by the antihypertensive drugs isradipine and benidipine. Both drugs lock the enzyme in a thioester-forming state, but benidipine exhibits superior efficacy by extending a bulky moiety into the primary catalytic tunnel to sterically block substrate entry. Furthermore, we identify a product inhibition mechanism where excess acyl-CoA traps the enzyme, potentially limiting metabolic overload. These findings provide a structural framework for understanding vectorial fatty acid channeling and a scaffold for developing modulators of metabolic flux. HighlightsO_LICryo-EM structures of human FATP2 reveal a membrane-anchored lollipop topology C_LIO_LIEndogenous fatty acids within a hydrophobic tunnel delineate the fatty acid uptake pathway C_LIO_LIIsradipine and benidipine displace fatty acids to trap a non-productive conformation C_LIO_LIAcyl-CoA product inhibition may provide negative feedback via steric occlusion C_LI

biophysics↗

bioRxiv2026

Lab on a Capillary: Instrument-Free Compartmentalization Using Photopatterned Hydrogel Rings Embedded inside a Glass Capillary for Amplified Bioassays

Sensitive and low-cost protein biomarker detection is critical for disease diagnosis. Advanced microfluidic systems can generate miniature reaction compartments for a high-sensitivity assay. However, these platforms often require external instruments, skilled operators, and complex setups. Here, we develop a Lab on a Capillary (LabCap) platform that integrates photopatterned hydrogel rings within a glass capillary using a reconfigurable stop-flow lithography system. During sample loading and unloading steps, nanoliter-scale aqueous droplets (torodrops) are spontaneously formed around the hydrogel rings, creating isolated reaction compartments without the need for external instruments or an immiscible oil phase. The LabCap platform enables quantitative detection of clinically relevant biomarkers, including C-reactive protein (CRP) and N-terminal pro-B-type natriuretic peptide (NT-proBNP). By adjusting the incubation protocol, assay speed and sensitivity can be tuned to meet different analytical requirements. A periodic medium exchange protocol enables biomarker detection at concentrations as low as 1 ng/mL, whereas prolonged static incubation extends detection to 0.1 ng/mL. In addition, LabCap offers practical advantages, including low fabrication cost (<{euro}1 per device), low reagent consumption (<100 L per assay step), and minimal wash-buffer usage (1 mL). These results demonstrate that LabCap is a simple, cost-effective, and versatile platform for biomarker detection.

bioengineering↗

bioRxiv2026

Hepatobiliary Progenitor-like Reprogramming in Liver Metastases

Metastatic progression requires cancer cells to adapt to the unique constraints of distant organ microenvironments, yet the mechanisms that drive organ-specific adaptations remain poorly understood. Here, we show that the liver actively rewrites metastatic cancer cell identity, driving tumor cells toward a hepatobiliary progenitor-like state. Through integrated transcriptomic, proteomic, metabolomic, and epigenomic analyses of patient-derived rapid-autopsy samples and experimental models, we identify this state as selectively enriched in liver metastases. It is characterized by co-activation of hepatic and biliary/progenitor regulators HNF4A and SOX9 and is observed across multiple epithelial cancers, indicating a conserved response to the hepatic niche. Mechanistically, hepatocyte-derived TGF-{beta} and hypoxia converge to activate a HIF-1-ACLY axis, increasing nuclear acetyl-coenzyme A availability and histone acetylation at hepatic lineage regulatory elements to drive hepatobiliary reprogramming. This coordinated niche-response program can be captured transcriptionally and is associated with inferior overall survival. Disruption of this pathway suppresses hepatic reprogramming and impairs liver metastatic fitness. These findings identify the liver as an active determinant of metastatic cell fate, linking microenvironmental signaling to metabolic and chromatin remodeling programs that enable lineage plasticity. More broadly, they reveal organ-specific reprogramming as a fundamental principle of metastasis and a therapeutic vulnerability in liver metastases.

cancer biology↗