Biology subjects

Kong, Y.

Publications and source records attributed to Kong, Y..

At least 19 recordsLinked to original sources

bioRxiv2026

Spatiotemporal transcriptomic dynamic across the auditory pathway from young to old age in 5xFAD Alzheimer disease mice

Auditory dysfunction can precede clinical dementia, but the molecular progression of Alzheimer disease (AD) pathology from the sensory periphery to auditory cortex remains poorly resolved. We performed bulk RNA sequencing of auditory cortex (AC), inferior colliculus (IC), cochlear nucleus (CN), and cochlea from 5xFAD and wild-type mice at postnatal day 50 (P50), 8 months, 11 months, and 16 months. Age-specific genotype effects and Genotype x Age interactions were evaluated using DESeq2, followed by Hallmark, KEGG, and Gene Ontology gene-set enrichment analyses and a cross-region synthesis of interaction trajectories. At P50, AC, IC, and cochlea showed coordinated suppression of mitochondrial metabolism, translation, RNA processing, and proteostasis, whereas CN displayed the opposite metabolic and biosynthetic profile together with reduced synaptic and adhesion programs. At 8 months, inflammatory interactions converged across all four regions, including interferon, complement, IL6-JAK-STAT3, and broader immune-response pathways. This coordination fractured at 11 months: AC and IC retained inflammatory and negative synaptic shifts, whereas CN and cochlea frequently changed in the opposite direction, including transient positive shifts in synaptic programs. By 16 months, immune interactions converged again, while metabolic, proteostatic, and synaptic trajectories remained region dependent; CN opposed AC, IC, and cochlea in several major metabolic programs. These findings define a distributed, asynchronous response rather than a monotonic bottom-up or top-down progression. The resulting spatiotemporal map links early metabolic stress, intermediate central-peripheral decoupling, and late inflammatory convergence, providing a molecular framework for evaluating peripheral to central auditory gain and temporal-processing measures as candidate indicators of AD progression.

neuroscience↗

bioRxiv2026

Abbapolin inhibitors of the PLK1 PBD as Prostate Cancer Therapeutics, in vivo activity and synergy with androgen therapy

Polo-like kinase 1 (PLK1) is an established therapeutic target in cancer; however, ATP-competitive kinase inhibitors have shown limited clinical success because of toxicity, acquired resistance, and incomplete inhibition of non-catalytic PLK1 functions. Targeting the Polo-box domain (PBD), which regulates PLK1 localization and substrate recognition, represents an alternative therapeutic strategy but has been hindered by the lack of selective, cell-active small molecules. Here, the optimization and biological characterization of abbapolins, a series of non-peptidic PLK1 PBD inhibitors developed using the REPLACE strategy are described. Structure-guided optimization and screening across the NCI-60 cancer cell panel identified compounds with preferential activity against prostate cancer cells. Proteomic analyses demonstrated that cellular sensitivity correlated with PLK1 protein abundance, supporting an on-target mechanism of action. Abbapolins directly engaged PLK1 in cells, induced selective degradation of endogenous PLK1, and suppressed long-term clonogenic growth. Lead compounds demonstrated favorable pharmacokinetic properties and significantly inhibited prostate tumor growth in xenograft models without detectable systemic toxicity. PLK1 abundance was significantly reduced in treated tumors and correlated with tumor response, identifying PLK1 degradation as a potential pharmacodynamic biomarker. Abbapolins also synergized with enzalutamide in castration- resistant prostate cancer cells, supporting their potential as combination therapies for advanced disease. Collectively, these studies establish selective inhibition of the PLK1 Polo-box domain as a viable therapeutic strategy, provide in vivo proof-of-concept for the REPLACE approach, and identify abbapolins as promising leads for advanced prostate cancer.

cancer biology↗

bioRxiv2026

Upregulation of ATP-purinergic P2x2 receptors in the cochlea over-amplifies hearing sensitivity leading to hyperacusis and attenuation by antagonists

Hearing hypersensitivity (hyperacusis) is a common hearing stress and can cause many psychological diseases, e.g., anxiety, learning disabilities, and attention-deficit/hyperactivity disorder (ADHD). Here, we report an unexpected finding that the upregulation of P2x2 ATP-purinergic receptors in the cochlea links to hyperacusis generation. We found that P2x2 expression in the cochlea but not in auditory centers was upregulated in the hyperacusis generated by Cx26 deficiency. Overexpression of P2x2 in the cochlea also caused hyperacusis. Conversely, downregulation of P2x2 expression or administration of P2x2 antagonists attenuated hyperacusis. We further found that upregulation of P2x2 receptors in the cochlea increased outer hair cell (OHC) electromotility through the post-transcription functional modulation to potentiate active cochlear amplification leading to hearing hypersensitivity. Such enhancements in OHC electromotility and active cochlear amplification were also suppressed by P2x2 receptor antagonists. Overall, these findings demonstrate that P2x2-mediated ATP-purinergic signaling in the cochlea plays a critical role in hyperacusis generation; targeting P2x2 receptors can attenuate hyperacusis stress, which may also offer a therapeutic strategy for other related psychological comorbidities. Significance statementHearing hypersensitivity is a common hearing stress and can cause many other psychological disorders. However, little is known about the underlying genetic and cellular mechanisms. Also, it lacks efficient drugs for their treatments in the clinic. In this study, we found that upregulation of P2x2 ATP-purinergic receptors in the cochlea can potentiate outer hair cell electromotility, which is an active cochlear amplifier in mammals and can increase hearing sensitivity and frequency selectivity, through post-transcription functional modulation to enhance active cochlear amplification leading to hearing hypersensitivity. These enhancements can be inhibited by administrations of P2x2 receptor antagonists both in vitro and in vivo. These findings revealed a new genetic and cellular mechanism underlying hyperacusis generation and opened a new avenue to develop an efficient therapy for this common hearing stress and other associated psychological comorbidities.

physiology↗

bioRxiv2026

Conserved Cell Type Signatures Across the Brainstem and Spinal Cord in the Mouse Central Nervous System

Understanding how cell types are organized across the central nervous system (CNS) is key to uncovering neural function. Here, we integrate single-nucleus Multiome (RNA+ATAC) sequencing, spatial transcriptomics, and computational analyses to map conserved cell type signatures in the adult mouse brainstem and spinal cord. We identify a shared core of neuronal and non-neuronal cell types, alongside region-specific specializations reflecting distinct functions. Spatial data reveal conserved cellular niches across the brainstem-spinal cord boundary, indicating a continuous organizational logic. Cross-region comparisons uncover recurrent gene expression modules and signaling programs that may support shared circuit features. Chromatin accessibility profiling highlights cell-type-specific regulatory programs and implicates Hox transcription factors in positional identity. Notably, cell-type and positional identities are largely orthogonal, with varying regional influence across neuronal classes: motor neurons show strong positional coupling, whereas glutamatergic and GABAergic interneurons show minimal entrainment. This work provides a reference for the shared molecular architecture of these CNS regions.

neuroscience↗

bioRxiv2026

Iterative structural homology search identifies new substrates of the protein O-fucosyltransferases POFUT3 and POFUT4

O-fucosylation plays an essential role in controlling protein folding, secretion and protein-protein interactions within the extracellular space. Recently, we identified a new form of protein O-fucosylation occurring on the N-terminal Elastin Microfibril Interaction (EMI) domain of several secreted proteins, mediated by two previously uncharacterized protein O-fucosyltransferases, POFUT3 (FUT10) and POFUT4 (FUT11). As all POFUT enzymes (POFUT1-4) are highly specific for the three-dimensional (3D) structure of their substrate protein domains, we postulated that structural homologues of these domains in other proteins may also be O-fucosylated. Here, we employed iterative protein structural homology searches as a novel strategy for identifying EMI-like domains that may serve as potential substrates for POFUT3/4. We discovered that microfibrillar-associated protein 2 and 5 (MFAP2/MFAP5) contain EMI-like domains and are O-fucosylated at high stoichiometry in human tissues. Unexpectedly, we showed that only POFUT3 is both necessary and sufficient for MFAP2/MFAP5 O-fucosylation, despite POFUT4 also having strong protein-protein interactions with MFAP2/MFAP5. Finally, we determined that O-fucosylation of MFAP2/MFAP5 is required for their efficient secretion, similar to other EMI domain-containing proteins. Together, these data demonstrate the power of sensitive structural homology analysis in identifying new enzyme-substrate relationships and protein-protein interactions.

biochemistry↗

bioRxiv2026

Guidance for high-quality functional gene embeddings from large language models

Large language models (LLMs) are increasingly used to generate gene embeddings, yet systematic benchmarks of prompting strategies and practical guidance for obtaining biologically meaningful representations remain limited. Here we present GEbench, an evaluation framework for assessing LLM-derived gene embeddings across different tasks, prompting strategies, and LLM architectures. GEbench revealed that embedding quality depends primarily on whether the input text contains explicit functional information, rather than on sparse gene identifiers or model size. Identifier-based embeddings showed weak biological organization, whereas embeddings derived from functional descriptions consistently achieved stronger functional separation and predictive performance. Notably, Self-Des, which extracts embeddings from model-generated gene function descriptions, enabled locally deployable LLMs to generate high-fidelity representations that approach the quality of expert-curated databases. Genome-scale analyses further supported these findings, indicating that explicit functional descriptions are an effective design principle for generating high-quality gene embeddings from LLMs.

bioinformatics↗

bioRxiv2026

Traveling waves support rhythmic attentional search

Brain activity unfolds across space and time, giving rise to spatiotemporal dynamics that can manifest as cortical traveling waves -smooth phase shifts propagating across the cortex. Although traveling waves have been observed across species and measurement scales, their functional role in human cognition remains largely inferred from correlational evidence. In healthy humans, large-scale neural dynamics must be studied non-invasively, which provides limited access to their neural origins. Here, we tested whether global traveling waves causally contribute to inter-areal communication during attention. Using transcranial magnetic stimulation (TMS), we induced long-range traveling waves detectable with electroencephalography and assessed their neural and behavioral consequences during an attentional search task. Double-pulse TMS applied over the right frontal eye field transiently disrupted ongoing global waves and selectively induced direction- and frequency-specific traveling waves propagating toward the occipital visual cortex. These TMS-induced anterior-to-posterior theta traveling waves were rhythmically modulated by stimulation latency relative to search-trial onset. Critically, behavioral performance exhibited the same rhythmic pattern, with improved attentional search performance when TMS-induced traveling waves were more prominent. Together, these findings provide causal evidence that large-scale traveling waves support inter-areal communication during rhythmic visual attention.

neuroscience↗

bioRxiv2026

G3DCT: An Interpretable Spatial Grid-based Framework with Temporal Convolution-Transformer for EEG Artifact Identification

Electroencephalography (EEG) serves as a fundamental tool in modern neurology, cognitive neuroscience, and brain-computer interfaces, but its practical application is often compromised by artifacts. Physiological artifacts are particularly intractable due to overlapping spectral features with neural signals, hindering reliable EEG interpretation. In this work, we propose Grid-based 3D Convolution-Transformer (G3DCT), an interpretable deep learning framework for EEG artifact identification. The framework embeds multi-channel EEG signals into fixed grids to leverage electrode spatial topology, employs parallel multi-branch temporal convolutions and Transformers to handle complex artifacts, and incorporates an attention module to visualize scalp activation patterns, which enhances physiological interpretability. Our evaluation on three datasets demonstrates that G3DCT outperforms existing state-of-the-art models. For challenging combined artifacts, it secures a gain of 2.8% in F1-score over the second-best model. These results demonstrate that G3DCT provides an efficient and robust solution for EEG artifact identification, which has the potential to enhance the reliability of EEG-based applications in practice.

neuroscience↗

bioRxiv2025

Susceptibility to Task-irrelevant Auditory Distractors in Relation to Visual Working Memory in Children With and Without ADHD

ObjectiveAttention-deficit/hyperactivity disorder (ADHD) is a prevalent neurodevelopmental disorder in children and is often associated with increased distractibility. Previous research has reported that susceptibility to task-irrelevant visual distractions is associated with visual working memory (WM) capacity. However, how neural responses to task-irrelevant auditory distractors are related to visual WM capacity in children with and without ADHD remains poorly understood. MethodsIn this study, we collected electroencephalography (EEG) signals from 72 children with ADHD and 88 typically developing (TD) children across two experiments, during which they performed visual tasks of varying difficulty while task-irrelevant auditory distractors were presented. The mismatch negativity (MMN) amplitude was measured as a neural index of susceptibility to auditory distractors, and the K score was assessed as a behavioral indicator of visual WM capacity. ResultsTD children showed opposite patterns across the two experiments: under low audiovisual competition, those with higher visual working memory capacity were more susceptible to task-irrelevant sounds, whereas under high competition, children with lower capacity showed greater susceptibility to distraction. In contrast, children with ADHD showed a stable association, with lower visual WM capacity consistently predicting higher susceptibility to task-irrelevant auditory distractors regardless of competition level. ConclusionsThese findings provide novel evidence that susceptibility to task-irrelevant auditory distraction is closely related to visual WM capacity in both children with and without ADHD, but the patterns of this relationship differ between typical and atypical neurodevelopment and are modulated by audiovisual competition.

neuroscience↗

bioRxiv2025

A Generative Foundation Model for Antibody Design

Antibodies are indispensable components of the immune system, yet the design of high-affinity antibodies remains a time-consuming and experimentally intensive process. To address this challenge, we present IgGM, a novel generative foundation model designed to accelerate high-affinity antibody engineering. IgGM learns the complex relationships underlying the binding interactions between antigens and antibodies, as well as the mapping between antibody sequences and structures. By conditioning on different inputs, IgGM supports a wide range of antibody design tasks, including complex structure prediction, inverse design, affinity maturation, framework optimization, humanization, and de novo antibody design. It is compatible with both conventional antibodies and nanobodies, and allows user-defined CDR loop lengths for flexible design. To prioritize candidates, we introduce a frequency-based computational screening strategy that enhances design efficiency. Extensive evaluation through both in silico benchmarks and in vitro experiments across diverse antigens such as PD-L1, Protein A, TNF-, IL-33, SARS-CoV-2 RBD and its variants demonstrates that IgGM consistently generates antibodies or nanobodies with high measured affinity. These results underscore IgGMs versatility and effectiveness as a powerful tool for next-generation antibody discovery and optimization.

bioinformatics↗

bioRxiv2025

AI-Supported Extraction of Functional Tissue Unit Properties for Human Reference Atlas Construction

The Human Reference Atlas (HRA) effort brings together experts from more than 25 international consortia to capture the multiscale organization of the human body--from large anatomical organ systems (macro) to the single-cell level (micro). Functional tissue units (FTU, meso) in 10 organs have been detailed and 2D illustrations have been created by experts. Comprehensive FTU property characterization is essential for the HRA, but manual review of the vast number of scholarly publications is impractical. Here, we introduce Large-Model Retrieval-Augmented Generation for HRA FTUs (HRAftu-LM-RAG), an AI-driven framework for scalable and automated extraction of FTU-relevant properties from scholarly publications. This validated framework integrates Large Language Models for textual reasoning, Large Vision Models for visual interpretation, and Retrieval Augmented Generation for knowledge grounding, offering a balanced trade-off between accuracy and processing efficiency. We retrieved 244,640 PubMed Central publications containing 1,389,168 figures for 22 FTUs and identified 617,237 figures with microscopy and schematic images. From these images and associated text, we automatically extracted 331,189 scale bars and 1,719,138 biological entity mentions, along with donor metadata such as sex and age. The resulting data facilitates the design, review, and approval of future FTU illustrations during HRA construction.

bioinformatics↗

bioRxiv2025

ChatMDV: Democratising Bioinformatics Analysis Using Large Language Models

BackgroundThe rapid advancement in single-cell, spatial omics, imaging, and genomic technologies requires robust analytical and visualisation platforms capable of managing complex biological data. Tools such as Multi-Dimensional Viewer (MDV) offer comprehensive interfaces for data exploration, but still require manual configuration and computational expertise to generate visualisation outputs, limiting accessibility for many users. ResultsWe present ChatMDV, a natural language interface integrated with MDV that allows users to generate high-quality interactive visualisations through natural language commands. ChatMDV employs a retrieval-augmented generation (RAG) pipeline combined with large language models (LLMs) to translate user queries into reproducible Python code and interactive output. This approach enables exploratory and targeted analysis in diverse biological domains. We demonstrate ChatMDVs capabilities using three datasets of increasing complexity: the Peripheral Blood Mononuclear Cells 3K (PBMC3K) dataset, the lung cancer atlas dataset hosted at the Human Cell Atlas and the longitudinal TAURUS study single-cell RNA-sequencing (scRNA-seq) dataset. ConclusionsBy bridging the gap between natural language processing and bioinformatics visualisation, ChatMDV reduces technical barriers, enhances reproducibility, and supports more inclusive scientific inquiry. Its modular design and adherence to FAIR (Findability, Accessibility, Interoperability, and Reuse) principles make it a scalable and adaptable framework for accelerating biological data analysis. Key PointsO_LIChatMDV enables users to create interactive visualisations from biological datasets using natural language. C_LIO_LIThe system combines large language models with MDVs graphical platform to simplify data exploration. C_LIO_LIIt supports reproducibility, adaptability, and FAIR data practices, making it suitable for a wide range of users and use cases. C_LI

bioinformatics↗

bioRxiv2025

piR-bmo-796514 Facilitates the Proliferation of Exogenous DNA Virus (Baculovirus) by Targeting the Host E3 Ubiquitin Ligase RNF181

PIWI-interacting RNAs (piRNAs), a class of 23-31 nucleotide non-coding RNAs, are known for silencing transposons and endogenous retroviruses that reside in animal genomes. However, the mechanisms by which host piRNAs affect exogenous viral infections, particularly those by DNA viruses, remain poorly understood. Here, we demonstrate that infection by Bombyx mori nucleopolyhedrovirus (BmNPV), a large DNA virus, induces significant upregulation of silkworm host piR-bmo-796514, which facilitates viral proliferation by suppressing the expression of E3 ubiquitin ligase RNF181. We further reveal that RNF181 exerts antiviral activity through ubiquitin-mediated degradation of Integrin 2b-like, a cellular membrane protein that interacts with viral GP64 protein to mediate BmNPV entry. This study unveils a previously unrecognized regulatory axis connecting host derived piRNAs with exogenous DNA virus infection, providing further mechanistic insights into the modulation of exogenous viral pathogenesis through the reprogramming of the piRNA pathway. Our findings not only advance the understanding of the immune escape mechanism of exogenous viruses but also provide new insights for the development of oligonucleotide antiviral drugs that target proviral piRNAs.

immunology↗

bioRxiv2025

Improving Cellular Senescence Detection with Weak Gene Markers in Single-Cell RNA-seq vi Iterative Imputation

BackgroundCellular senescence represents a stable cell cycle arrest state that plays critical roles in tissue aging and age-related pathologies. Although single-cell RNA sequencing (scRNA-seq) enables comprehensive profiling of millions of cells in aged tissues, reliably identifying senescent cells remains challenging due to the weak and non-specific expression of their marker genes. Existing computational methods can detect active cell states through gene set scoring, but their performance for senescence genes has not been rigorously evaluated. ResultsIn this study, we show that senescence genes display weak, non-specific expression patterns across different tissues and are susceptible to dropout events in scRNA-seq. Current scoring approaches suffer intrinsic limitations in single-cell detection using weakly expressed markers. Simply expanding the gene set of weak markers failed to improve detection accuracy. To overcome these limitations, we developed ICE (Imputation-based Cell Enrichment), a computational framework that combines expression imputation with iterative marker refinement. ICE substantially improved detection precision in pancreatic cells with weakly expressed markers, increasing it from 56% to 98%. Using consensus markers, ICE identified senescent fibro-adipogenic progenitors (FAPs) in muscle tissue, characterized by elevated expression of senescence-associated secretory phenotype (SASP) genes. When applied to individual senescence markers (CDKN1A/p21, CDKN2A/p16, ATF3, and MX1), ICE successfully identified marker-specific cell populations. These included stressed {beta} cells in aging and type-I interferon-responsive microglia in Alzheimers disease (AD). ConclusionsOur study introduces ICE, a rigorous framework for detecting cell states defined by weakly expressed markers at the single-cell level. This tool enables the reliable identification of senescence-associated populations, facilitating a deeper characterization of their heterogeneity and temporal dynamics across diverse human tissues and disease contexts.

genomics↗

bioRxiv2025

A synergistic generative-ranking framework for tailored design of therapeutic single-domain antibodies

Single-domain antibodies (sdAbs) have emerged as powerful therapeutic agents due to their small size, high stability, and superior tissue penetration. However, unlike conventional monoclonal antibodies (mAbs), sdAbs lack an Fc domain, limiting their functional versatility and manufacturability. To address this challenge, we developed TFDesign-sdAb, a deep learning-based generative-ranking framework that enables rational engineering of sdAbs with tailored functionalities. Our framework integrates a structure-aware diffusion model (IgGM) for large-scale candidate generation and a fine-tuned sorter (A2binder) that evaluates and prioritizes them based on predicted functionality. Unlike traditional CDR-focused approaches, TFDesign-sdAb optimizes both complementarity-determining regions (CDRs) and framework regions (FRs), allowing sdAbs to acquire new functional properties while maintaining antigen specificity. We validated our approach by conferring Protein A binding to human VHs and nanobodies that originally lacked this feature, achieving high expression rates, strong binding affinities, and successful purification via industry-standard Protein A affinity chromatography. High-resolution structural characterization (1.49 [A] and 2.0 [A]) of the redesigned sdAb-Protein A complexes revealed conserved FR-mediated binding motifs that recapitulate natural Fc-Protein A interactions, validating the accuracy of our model. Furthermore, our pipeline streamlined the antibody engineering process, achieving a 100% success rate in generating Protein A-binding sdAbs while maintaining their original antigen-binding affinity. This work demonstrates the power of AI-driven design in overcoming long-standing limitations in antibody engineering and presents a scalable, generalizable solution for enhancing sdAb functionality.

bioinformatics↗

bioRxiv2025

Promotion of new expression of connexin gene Cx46 (GJA3) in the cochlea after Cx26 (GJB2) deficiency

Connexin 26 (Cx26, GJB2) mutations induce a high incidence of hearing loss, responsible for 70-80% of nonsyndromic hearing loss. The pathological changes mainly locate in the cochlea. However, the genetic changes in the cochlea after deficiency of Cx26 remail unclear, which hampers to fully understand the underlying deafness mechanisms to develop therapeutic interventions. In this study, we employed bulk Poly(A) RNA-Seq technique and found that Cx26 deficiency could cause many genes up-regulating and down-regulating in the cochlea. A significant change was that Cx46 (GJA3), which is like Cx26 but expresses in the eye rather than the ear normally, had a remarkable upregulation and occurred in the cochlea after Cx26 deficiency. Immunofluorescent staining confirmed that Cx46 had expression in the cochlea and integrated into the gap junction networks among the cochlear supporting cells and in the cochlear lateral wall at the same location as Cx26 expression. Moreover, newly expressed Cx46 could be found in the same gap junctional plaques with Cx26. In addition, this promotion of new Cx46 expression is Cx26-specific; there was no promotion of Cx46 expression in the cochlea after deletion of Cx30 (GJB6), which also predominantly co-expresses with Cx26 in the cochlea. These data demonstrated that Cx26 deficiency could promote Cx26-like Cx46 expression in the cochlea for compensation. This finding also provides a new cue for developing a genetic approach to treat this common hereditary deafness induced by GJB2 mutations. HighlightO_LINew Cx46 compensatively expresses in the cochlea after Cx26 deficiency C_LIO_LICx46 expression occurs in the same location as Cx26 in the cochlea C_LIO_LICx46 promotion is Cx26-specific, no expression in the Cx30 KO cochlea C_LI

genetics↗

bioRxiv2025

SCOIGET: Predicting Spatial Tumor Evolution Pattern by Inferring Spatial Copy Number Variation Distributions

Constructing a comprehensive spatiotemporal map of tumor heterogeneity is essential for understanding tumor evolution, with copy number variation (CNV) as a significant feature. Existing studies often rely on tools originally developed for single-cell data, which fail to utilize spatial information. Our study aims to develop a model that fully leverages spatial omics data to elucidate spatio-temporal changes in tumor evolution. Here, we introduce SCOIGET (Spatial COpy number Inference by Graph on Evolution of Tumor), a novel framework using graph neural networks with graph attention layers to learn spatial neighborhood features of gene expression and infer copy number variations. This approach integrates spatial multi-omics features to create a comprehensive spatial map of tumor heterogeneity. Notably, SCOIGET achieves a substantial reduction in error metrics (e.g., mean squared error, cosine similarity, and distance measures) and produces superior clustering performance as indicated by higher Silhouette Scores compared to existing methods. Our model significantly enhances the efficiency and accuracy of tumor evolution depiction, capturing detailed spatial and temporal changes within the tumor microenvironment. It is versatile and applicable to various downstream tasks, demonstrating strong generalizability across different spatial omics technologies and cancer types. This robust performance improves research efficiency and provides valuable insights into tumor progression. In conclusion, SCOIGET offers an innovative solution by integrating multiple features and advanced algorithms, providing a detailed and accurate representation of tumor heterogeneity and evolution, aiding in the development of personalized cancer treatment strategies. Key PointsO_ST_ABS1. Innovative Framework for Spatially Contextualized CNV InferenceC_ST_ABSIntroduces SCOIGET, a graph-based model that integrates spatial omics data with graph neural networks and attention mechanisms to accurately infer spatial copy number features. 2. Detailed Tumor Heterogeneity MappingConstructs representations of tumor evolution, capturing heterogeneity and clonal dynamics at both cellular and subcellular resolutions. 3. Versatile and Robust PerformanceOutperforms existing methods across multiple datasets, demonstrating reliability and adaptability to diverse spatial omics platforms and cancer types. 4. Broad Downstream ApplicationsEnables tasks such as tumor subclone identification, clustering, and evolutionary trajectory analysis, facilitating precision oncology strategies.

bioinformatics↗

bioRxiv2025

Cutaneous lupus features specialized stromal niches and altered retroelement expression

Cutaneous Lupus is an inflammatory skin disease causing highly morbid inflamed skin and hair loss. In order to investigate the pathophysiology of cutaneous lupus, we performed single-cell RNA and spatial sequencing of lesional and non-lesional cutaneous lupus skin compared to healthy controls. Pathway enrichment analyses of lesional keratinocytes revealed elevated responses to type I interferon, type II interferon, tumor necrosis factor, and apoptotic signaling. Detailed clustering demonstrated unique fibroblasts specific to lupus skin with likely roles in inflammatory cell recruitment and fibrosis. We also evaluated the association of retroelement expression with type I interferons in the skin. We observed increased retroelement expression which correlated with interferon-stimulated genes across multiple cell types. Moreover, we saw elevated expression of genes involved in RIG-I and cGAS-STING pathways, which transduce elevated nucleic acid signals. Treatment of active cutaneous lupus with Anifrolumab reduced RIG-I and cGAS-STING pathways in addition to the most abundant retroelement family, L2b. Our studies better define type I interferon-mediated immunopathology in cutaneous lupus and identify an association between retroelement expression and interferon signatures in cutaneous lupus.

immunology↗