Biology subjects

Wang, J.

Publications and source records attributed to Wang, J..

At least 91 records · Page 5Linked to original sources

bioRxiv2026

MAPK signaling links BRD2 chromatin occupancy to PI3K/AKT inhibitor sensitivity

Bromodomain and extra-terminal (BET) proteins, BRD2, BRD3, BRD4, and BRDT, couple histone acetylation to transcription by recruiting elongation and transcription factor complexes to chromatin. Although BET proteins are promising therapeutic targets, the functions of individual family members remain incompletely understood. We identify BRD2 as a co-targetable vulnerability with PI3K/AKT inhibition in breast cancer. Pan-BET inhibition and BRD2 knockout synergized with PI3K pathway inhibitors in breast cancer cell lines, patient-derived organoids, and in vivo models. BRD2 knockout impaired proliferation of triple-negative breast cancer cells and upregulated signaling and stress-response pathways, including the DNA damage response. Mechanistically, BRD2 is phosphorylated at Ser37 by the mitogen- and stress-activated kinases MSK and RSK, and Ser37 phosphorylation is required for chromatin binding and reader function. Finally, mechanistic digital twin modeling identified BETi-PI3Ki regimens that maintained efficacy while reducing drug exposure. Together, these findings identify BRD2 as a phosphorylation-dependent, co-targetable vulnerability in PI3K-inhibited breast cancer.

cancer biology↗

bioRxiv2026

Unsupervised alignment reveals shared but locally refined colour qualia structure from toddlerhood to adulthood

Whether subjective colour experience (e.g., experience of 'red') is shared across children and adults remains a foundational question in developmental psychology and consciousness research. To test this, we compared the relational structures of their colour experiences and identified the mapping that best preserved these structures. Using pairwise similarity judgements for 13 basic colours, we applied Gromov Wasserstein optimal transport (GWOT), an unsupervised method requiring no prespecified stimulus experience correspondence to compare toddlers, preschool children, and adults. Preschoolers' and adults' group-averaged structures perfectly aligned, whereas toddlers' structure did not fully align with either older group. However, removing specific colours, particularly those with relatively late acquired linguistic boundaries, such as light blue-restored near-perfect alignment. Moreover, toddlers with greater colour-word knowledge showed closer correspondence with the adult similarity structure. These findings suggest that the global relational geometry of colour experience is largely established by toddlerhood, with limited local differences linked to colour-language acquisition.

neuroscience↗

bioRxiv2026

Collateral Immune Cell Signaling Compromises the Efficacy of T-cell Engaging Therapies for Cardiac Fibrosis

Cardiac fibrosis is causally linked to heart failure progression and survival. Currently, there are no approved treatments that directly target cardiac fibrosis. Recent studies have identified a subset of activated cardiac fibroblasts distinct from myofibroblasts that are marked by fibroblast activation protein (FAP) expression, emerge in the injured and diseased heart through inflammatory signaling, and contribute to fibrosis. Using a genetic mouse model, we demonstrate the potential benefits of FAP+ fibroblast depletion following myocardial infarction. Unexpectedly, while FAP targeted bispecific T-cell engaging antibodies (BiTE(R) molecules) effectively eliminate FAP+ fibroblasts from the heart, they surprisingly lead to accelerated deterioration of cardiac function, enhanced remodeling, and increased scar size. FAP BiTE(R) molecules elicit a robust cytokine response within the heart with prominent activation of interferon gamma (IFNg) and CD40 ligand pathways. Target cell killing was independent of IFNg; and CD40L signaling and blockade of these pathways was sufficient to unmask the protective therapeutic effects of FAP+ fibroblast depletion. Mechanistically, we reveal that IFNg; signaling to fibroblasts drives the differentiation of an independent lineage of activated fibroblasts not typically found in the infarcted heart, which are responsible for the harmful effects of FAP BiTE(R) molecules. Collectively, these findings highlight a previously unrecognized cardiac liability of BiTE(R) molecules and inform the design of the next generation of therapeutics.

immunology↗

bioRxiv2026

Autonomous MTOR activation in COPD airway epithelium impairs resolution through persistent mucus cell metaplasia and lysosome dysfunction

Background: COPD is associated with persistent airway epithelial mucous cell metaplasia (MCM), mucin hypersecretion, and airway obstruction. Cytokines, such as IL-13, are well-known inflammatory drivers of airway MCM development. However, less is known about the factors that contribute to the impaired resolution of MCM in COPD. We hypothesized that MTOR activation in COPD airway epithelial cells (AECs) impairs autophagy and contributes to the delayed resolution of MCM. Methods: AEC from COPD and non-diseased donors were grown under air-liquid interface (ALI) conditions and treated with IL-13 to promote MCM. Airway sections from COPD lung explants or non-diseased lung donors were utilized for immunohistochemical and immunostaining. Lysosomes were assessed using molecular probes and immunostaining. Results: There was persistent MTOR-dependent MUC5AC immunostaining and epithelial hypertrophy in COPD AEC, which did not resolve after IL-13 withdrawal. MTOR substrate phosphorylation of RBS6, S6K1, and ULK1 was significantly elevated under baseline conditions, and at multiple timepoints independent of IL-13. Pharmacologic activation of MTOR led to increased IL-13-mediated MUC5AC levels in normal AEC but less robustly in COPD derived AEC. We hypothesized that persistent MTOR activation would reduce lysosome function and abundance in disease. COPD airways had reduced lysosome markers, LAMP1 and LAMP2 and fewer functional lysosomes by live-cell reporter probes. This lysosome deficiency in COPD AEC was partially rescued with MTOR inhibition. Conclusions: We provide evidence to support an axis of autonomous MTOR activation and impaired lysosome function in the COPD airway epithelium. Persistent MTOR signaling is a molecular driver that contributes to persistent MCM.

pathology↗

bioRxiv2026

stEDGE enables edge-guided multiscale reconstruction of hierarchical spatial domains and transition interfaces in spatial transcriptomics

Spatial transcriptomic technologies enable high-resolution mapping of tissue architecture, yet most computational methods still represent tissues as flat spatial partitions, limiting their ability to resolve spatial domain boundaries, gradual transition regions and nested hierarchies. Here we present stEDGE, an edge-guided and interpretable framework for multiscale reconstruction of spatial domain hierarchies and transition-associated states in spatial transcriptomics. Unlike conventional domain-first approaches, stEDGE first estimates local boundary structure and uses it to guide the reconstruction of fine-grained spatial domains. We further introduce a domain transition index (DTI) to quantify domain-level transition propensity and integrate DTI with inter-domain similarity and boundary strength to organize fine domains into a coherent multilevel hierarchy. A tree-guided gene attribution strategy then distinguishes shared parent-level programs from branch-specific specialization across hierarchical spatial states. Across 15 benchmarked tissue sections spanning diverse tissues, technologies and spatial resolutions, stEDGE reconstructs developmental, inflammatory, tumor and brain architectures beyond conventional domain partitioning. Applied to cell-resolved Xenium profiling of fibrotic human lung, stEDGE further reveals lesion-associated remodeling as a coherent multiscale hierarchy in which remodeling interfaces coexist with a stable macrophage-associated airway/lumen state and spatially organized TLS-like lymphoid niches. Together, stEDGE provides a unified framework for modeling how stable compartments, domain boundaries, remodeling interfaces, localized niches and multiscale gene programs are jointly organized across spatial scales.

bioinformatics↗

bioRxiv2026

Single-cell multiomic QTL mapping reveals state-dependent genetic regulation and associated gene during cellular senescence

How cellular senescence reshapes inherited regulatory effects across chromatin and transcription, and eventually contribute to non-coding risk loci of complex diseases, remains elusive. We generated single-cell multiome ATAC-RNA profiles from proliferating and replicatively senescent primary HUVECs derived from 100 genotyped donors. Alongside state-resolved eQTL and caQTL mapping, we implemented covariance-aware multivariate QTL mapping to identify chromatin accessibility-expression QTLs (caeQTLs), modeling accessibility and expression as a joint phenotype. Joint analysis recovered moderate, asymmetric and modality-distributed associations missed by single-modality scans, revealed senescence-associated regulatory programs, and prioritized candidate causal variants and effector genes at cardiovascular loci. Fine-mapping, chromatin-state annotation and heritability enrichment, together with independent SNP-to-gene algorithms, provided convergent orthogonal support. Mechanistic dissection revealed that rs2019090 modulates PDGFD expression and endothelial phenotypes through senescence-amplified, allele-specific, HMGA1-associated enhancer-promoter regulation. This study establishes senescence-resolved joint multiomic QTL mapping as a framework for narrowing the missing regulation gap in complex disease genetics.

genetics↗

bioRxiv2026

Maleic acid adjuvates BCG to induce CD4+CD8+ T cells and sterilize tuberculosis

Anti-tuberculosis (TB) immunity typically emphasizes CD4+ T and CD8+ T cells that only provide limited protection against Mycobacterium tuberculosis (Mtb) infection. The anti-TB function of CD4+CD8+ T cells remains unexplored, mostly due to the dogma that ThPOK and Runx3 antagonize each other to block their development and their scarcity. Here, we show that immunization of BCG (Bacillus Calmette-Gu&eacuterin) with Complete Freund's Adjuvant (CFA) markedly induced CD4+CD8+ T cells through the gut microbiota Clostridium butyricum or its metabolite maleic acid. Mtb-specific CD4+CD8+ T cells exhibited a broad T-cell receptor repertoire and sterilized Mtb infection by inducing SLAMF1 and neutrophil responses. Mechanistically, maleic acid interacted with PAK2 to promote STAT5 phosphorylation at Ser127, thus upregulating Ets1 expression. Direct binding of Ets1 to the Runx3 and ThPOK promoters orchestrated their expression to redirect the CD8+ T cell differentiation towards the CD4+CD8+ lineage. Moreover, immunization of BCG plus Clostridium butyricum or maleic acid sterilized Mtb infection in mouse models. These findings establish CD4+CD8+ T cells as superior immune effectors against Mtb, a concept that could fundamentally redirect the current paradigm for anti-TB vaccine development.

microbiology↗

bioRxiv2026

Connectivity allometry is a robust organizing principle of the human functional connectome

A defining feature of the human brain is its multiscale organization, in which regional processes are integrated into coherent whole-brain network architecture. How local functional organization adapts to variation in this global architecture, however, remains largely unknown. Here, we addressed this question by applying an allometric scaling framework to resting-state functional magnetic resonance imaging data from four large-scale datasets spanning different cultures, cognitive states, developmental stages, and clinical conditions. We found that human functional networks were organized according to a robust and spatially heterogeneous connectivity allometry, whereby regional functional connectivity scales nonlinearly with whole-brain connectivity strength. This scaling architecture closely followed the cortical sensorimotor-association hierarchy, with lower-order systems exhibiting supralinear scaling and higher-order systems exhibiting sublinear scaling. Connectivity allometry was further associated with multiscale neurobiological organization, including regional metabolic properties, neurotransmitter receptor distributions, and transcriptomic landscapes, indicating that local-global functional scaling is embedded within fundamental biological gradients of cortical organization. Moreover, the scaling pattern and its biological associations were highly reproducible across independent cross-cultural cohorts. Importantly, connectivity allometry remained remarkably stable across working memory conditions regardless of cognitive load, emerged by late childhood, and was broadly preserved in children and adolescents with autism spectrum disorder despite region-specific alterations. Together, these findings establish connectivity allometry as a previously unrecognized organizational principle of the human functional connectome and provide a quantitative framework linking regional functional organization to whole-brain network architecture in health and disease.

neuroscience↗

bioRxiv2026

Cross-species spatial profiling links progranulin to an immune suppressive niche in brain metastasis

Immune checkpoint inhibitors (ICI) have revolutionized the treatment of brain metastasis (BM), demonstrating intracranial response rates and durability not previously seen with other therapies. However, approximately 50% of patients do not respond to ICI, and the brain-specific interactions that shape anti-tumor immunity remain poorly understood. We profiled five syngeneic BM models using spatial transcriptomics, identifying myeloid-rich niches enriched for interferon-responsive and disease-associated microglia (DAM)-like programs. Ligand-receptor colocalization analyses identified progranulin (PGRN) as a candidate mediator of these niches. Host- or tumor-cell Grn loss reduced BM burden, and Grn-deficient macrophages exhibited altered metabolic programs and tumor-cell engulfment in vitro. Across independent human BM datasets, GRN expression was associated with conserved lysosomal and DAM-like myeloid programs, and GRN-high myeloid regions colocalized with immunosuppressive signatures and dysfunctional CD8+ T cell states. These cross-species findings identify PGRN as a candidate mediator of the BM immune niche and support further investigation of its therapeutic relevance.

cancer biology↗

bioRxiv2026

Multi-model biological and sequence information fusion for gene regulatory network inference from single-cell transcriptomics

Identification of transcription factor target gene interactions and construction of the gene regulatory networks (GRNs) are essential for understanding the molecular mechanisms underlying transcriptional gene regulation. Large scale single cell transcriptomics across different tissues offers unprecedented resolution of cellular diversity and regulatory dynamics by capturing gene expression heterogeneity. However, existing methods often lack effective multimodal integration and fail to fully exploit the hierarchical structure in Gene Ontology (GO) and gene sequence level representations, which limits their ability for predictive performance and biological interpretability. We present scMGFGRN, a multi-model deep learning framework that integrates single-cell transcriptomic profiles with GO hierarchical relationships, gene sequences by leveraging denoising auto encoders, graph attention feature extraction and pertained DNA language model to capture multi-source dependencies within multi-model biological knowledge, while its gated multi head attention module effectively identifies informative regulatory signatures and integrate complementary features from different sources to predict accurate gene regulatory networks. Benchmarking on the seven datasets of human and mouse demonstrates that scMGFGRN outperforms state of the art methods in identifying GRNs. Further analyses reveal that scMGFGRN effectively identifies novel TF gene interactions (TGIs) and reconstructs cell type specific GRNs. Interpretability analysis reveals the contribution patterns of heterogeneous biological sources, demonstrating the ability of scMGFGRN to integrate transcriptomic profiles with multi model structure information.

bioinformatics↗

bioRxiv2026

Genetically-encoded discovery and development of peptide-macrocycle imaging agents for PD-L1

The unique cell surface composition of tumor cells forms the molecular basis for many targeting and cell-based therapies. Here, we describe the development of novel peptide-based targeting agents for programmed death ligand 1 (PD-L1). Molecular imaging by peptide agents, coupled with therapeutic intervention using the same modality, represents a critical advancement in cancer management. Whole-body PET imaging of PD-L1 expression offers a superior alternative to traditional immuno-histochemistry, making PD-L1 radiodiagnostic imaging a highly sought-after modality. PD-L1 targeting modalities developed for clinical imaging to date can be divided into antibodies, protein domains, and small macrocyclic peptides with fewer than 20 amino acids. The latter modalities can address many challenges seen in antibody-based targeting vectors. All potent PD-L1 targeting peptide modalities reported to date rely extensively on non-canonical amino acids (ncAAs). Here, we report a comprehensive structure-activity relationship (SAR) analysis of a family of macrocycles discovered from an Sx2Cx8Cx2 phage-display library composed entirely of natural amino acids (x represents 19 natural amino acids excluding Cys). Using >10,000 variants in ''focused'' phage-display libraries, we optimized these macrocycles to achieve single-digit-nanomolar potency in protein- and cell-based assays. En route to this optimization, the activity of 216 synthetic macrocycles towards PD-L1 was measured in five distinct assays; two leads have been evaluated by imaging in tumor xenografts in mice, and the X-ray structure of one advanced lead in complex with PD-L1 has been determined at 2.78 [A] resolution. This publication demonstrates the development potential of PD-L1-targeting macrocycles that do not require extensive incorporation of ncAAs and the democratization of discovery by mapping the optimization path to single-digit-nanomolar assets for targeted radiopharmaceuticals via canonical phage-display technology.

pharmacology and toxicology↗

bioRxiv2026

Engineering human myelin microphysiological systems for testing patient treatment response in multiple sclerosis

Multiple sclerosis (MS) is an autoimmune disease of the central nervous system characterized by neuroinflammation, demyelination, and neurodegeneration, associated with a complex interplay between the innate and adaptive immune systems. Currently, no cure is available for MS, and personalized disease-modifying treatment remains largely limited, partially due to the lack of preclinical human models that can faithfully recapitulate disease pathology and evaluate treatment responses at the individual-patient level. Here, we report a human myelin microphysiological system (myelin MPS) platform that recaptures disease phenotype and treatment response for testing patient treatment response. By culturing neural organoids on 3D-printed devices containing directional microfibers, followed by coculture with oligodendrocyte progenitor cells, 96 myelin MPS models can be generated within a conventional well plate. Using this myelin MPS platform, autologous T cells and monocytes from MS patients induced substantially greater demyelination than those from healthy donors, accompanied by expansion of proinflammatory T-cell subsets and increased myelin uptake by monocytes/macrophages after coculture with these healthy myelinating neural tissues. Integration of imaging and flow-cytometric features distinguished healthy-donor, untreated-MS, responder, and nonresponder profiles following treatment with prednisone, glatiramer acetate, interferon {beta}-1a, or dimethyl fumarate. Thus, the myelin MPS platform provides a scalable, human pathophysiology-relevant platform for functional phenotyping and individualized treatment-response evaluation in MS.

bioengineering↗

bioRxiv2026

Clustered structural variant hotspots enable oncogenic addiction and plasticity in osteosarcoma

The genomic landscape of osteosarcoma, the most common bone cancer worldwide, is among the most structurally complex of all human malignancies. The identification of recurrent and functionally consequential patterns has thus remained a challenge. Across 236 whole-genome sequencing osteosarcoma samples, we uncovered five genomic hotspots of clustered structural variation collectively altered in 58% of tumors. Four were associated with amplification of oncogenes ( MYC , CCND3 , CCNE1 , CDK4) , while the fifth mapped largely upstream of TP53 . Hotspot events showed coordinated patterns of co-occurrence and mutual exclusivity with each other and with tumor suppressor alterations, suggesting genomic context-specific selection. We found localized transcriptional dysregulation at hotspot event loci, and single cells harboring these events converged on a neural crest-like program, linking these structural alterations to a less differentiated cell state. These events were also detectable non-invasively through liquid biopsies and displayed ongoing structural evolution throughout disease progression, a finding with potential clinical utility. Our results provide novel insight into how complex rearrangements shape oncogenesis in osteosarcoma, with broader relevance to other cancers characterized by complex genomes.

cancer biology↗

bioRxiv2026

Cardiomyocytes upregulated PD-L1 expression to alleviate cardiac injury induced by irradiation combined with anti-PD-1 antibody: an in vitro and in vivo study

Objective: Preclinical studies suggest that irradiation combined with anti-PD-1 antibody (iRT) exacerbates cardiac injury in mice, partly through CD8 T-cell-mediated mechanisms. We investigated radiation-induced PD-L1 expression in cardiomyocytes and explored its potential role in iRT-associated cardiac injury. Methods: AC16 cells were exposed to different doses of irradiation. PD-L1 expression was assessed at different time points by flow cytometry, qRT-PCR, western blotting, and immunofluorescence. Cell viability, apoptosis, and cytokine levels were evaluated. PD-L1 was knocked down using siRNA to assess its function. PBMCs or CD8 T cells were co-cultured with irradiated or non-irradiated AC16 cells at different E:T ratios, with or without PD-1 blockade. A C57BL/6J mouse model of iRT-induced myocardial injury was established, and myocardial PD-L1 expression and T-cell infiltration were evaluated. Results: Irradiation upregulated PD-L1 expression in AC16 cells, with increased membrane and cytoplasmic signals at 48 h and prominent nuclear-associated fluorescence at 72 h. Irradiation increased IL-6, MCP-1, CCL5, and CXCL10 release, decreased IL-10, reduced cell viability, and increased apoptosis. PD-L1 knockdown further increased inflammatory cytokine and chemokine release but did not significantly alter apoptosis or further reduce viability in irradiated AC16 cells. In the presence of a high density of activated CD8 T cells, disruption of PD-1/PD-L1 signaling was associated with a further reduction in AC16 cell viability. In vivo, myocardial PD-L1 expression was increased, whereas CD8 T-cell infiltration remained limited and focal. Conclusion: PD-L1 upregulation in cardiomyocytes may exert an adaptive protective and immunoregulatory role during iRT-associated injury, potentially by limiting inflammatory mediator release and modulating susceptibility to activated CD8 T-cell mediated injury. CD8 T-cell density and activation are the key issues.

cancer biology↗

bioRxiv2026

Seasonal influenza vaccine strain selection by quantifying viral fitness

The long-standing challenge of seasonal influenza vaccines providing poor protection is attributed to the rapid and continuous evolution of the virus. In theory, the recommendation of vaccine strain is to predict the dominant strain with best fitness in the upcoming season. Here, we develop FutureFlu, a biologically-grounded framework that quantifies the fitness score of influenza variants in upcoming seasons, by integrating metrics on three levels: molecular genetic divergence, individual immune escape, and population-scale transmission dynamics. The fitness scores of influenza variants present strong positive correlation with their actual observed frequencies in the next seasons. Validation across 24 seasons of three influenza subtypes shows FutureFlu recommends antigenically matched vaccine strains more frequently than annual recommendations, particularly for challenging subtypes: 83.3% versus 45.8% seasons for A/H3N2, and 75.0% versus 33.3% seasons for B/Victoria. Furthermore, FutureFlu significantly outperforms the currently used methods in vaccine strain selection whether or not there is available antigenic data from hemagglutination inhibition (HI) assay, which provides a valuable supplement for WHO vaccine recommendation. To support global public health implementation, an open online platform (futureflu.com.cn) has been established to offer real-time viral fitness predictions and vaccine recommendations.

evolutionary biology↗

bioRxiv2026

High-throughput physics-based enzyme engineering

Enzyme engineering aims to tailor natural enzymes for industrial and therapeutic applications, yet physically grounded rational design has been limited by a trade-off between accuracy and cost, leaving the field heavily dependent on expert intuition. Here we present a scalable physics-based framework that combines field-aware machine learning with molecular mechanics to capture enzyme electrostatics at quantum-mechanical accuracy while enabling efficient, atomistic exploration of reaction free-energy landscapes. Coupled with microkinetic modelling, the framework translates molecular free-energy landscapes into catalytic rates and selectivity across competing, multistep reaction pathways. Applied to a newly engineered oxidative amidase (OxiAm), the framework predicts catalytic rate constants with near-experimental accuracy, quantitatively resolves the selectivity between hydrolysis and aminolysis, and generalizes across substrates, mutations and enzyme homologues. Transition-state ensemble analysis further reveals the reaction mechanism and guides the design of enzyme variants for pharmaceutical synthesis. By bringing chemical accuracy and high-throughput sampling to enzyme catalysis, this approach shifts rational design from static, empirical practice toward dynamic, free-energy-driven design, and should accelerate the engineering of biocatalysts.

biophysics↗

bioRxiv2026

Mural β3-integrin signposts Stroma6, a gene signature predicting early relapse in low-risk and chemoresistant breast cancer

The Oncotype DX (ODX) assay guides adjuvant chemotherapy in ER+/HER2- breast cancer but overlooks drivers from the tumour stroma, leaving some low-risk and chemotherapy-spared patients vulnerable to rapid relapse. Here, we show that perivascular mural {beta}3-integrin protein expression predicts early (3-year) relapse in ODX low-risk patients (HR = 15.80, P = 0.010), from which we derived a translatable 6-gene stromal signature, termed Stroma6. High Stroma6 expression predicted early recurrence in the ODX low-risk discovery cohort, with zero early relapses in the low-expression group. External validation in the METABRIC dataset confirmed that Stroma6 independently predicts rapid recurrence in ODX low-risk patients (HR = 11.68, P = 0.002). Furthermore, Stroma6 utility extends to clinical chemoresistance, independently predicting early events in a pan-subtype cohort with residual disease following neoadjuvant chemotherapy (HR = 2.29, P = 0.003). Ultimately, Stroma6 is a robust prognostic signature identifying patients at high risk of early recurrence across diverse clinical contexts.

cancer biology↗

bioRxiv2026

Accurate and scalable decontamination of imaging-based spatial transcriptomics via optimal transport

Imaging-based spatial transcriptomics enables molecule-resolved profiling of gene expression and tissue organization in situ. However, segmentation errors, transcript spillover and three-dimensional cell overlap can introduce misassigned transcripts into cell-level expression profiles, compromising biological interpretation and obscuring genuine signals. Existing methods either remove suspect expression at the cost of signal loss or lack a biologically grounded criterion for transcript assignment. Here we present CellDot, an optimal-transport framework that determines the fate of each transcript by retaining it in its host cell, reassigning it to a plausible neighboring cell or removing it as background. By integrating reference-guided expression compatibility with spatial information and data-adaptive constraints, CellDot enables accurate and traceable molecule-level correction while preserving biologically meaningful variation. In evaluations across multiple human tumor datasets, CellDot exhibited superior performance compared to existing decontamination methods, successfully restoring spatial expression patterns that matched independent cross-platform measurements. Moreover, it significantly enhanced the recovery of cellular states, intercellular communication, and spatial niche programs. Our experiments using real data demonstrated CellDot's scalability and established it as the only method applicable to a whole-transcriptome Atera dataset, underscoring its distinct advantages in the field of spatial transcriptomics.

bioinformatics↗