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PMC13160972 | Multidimensional dissection of shared genetic susceptibility in ulcerative colitis and colorectal cancer: novel insights from integrative single-cell and multi-omics analysis | 0 | Ulcerative colitis (UC) patients carry a 2.5-fold increased risk of colorectal cancer (CRC), yet the shared multi-scale genetic architecture remains poorly understood. | Abstract | [] |
PMC13160972 | Multidimensional dissection of shared genetic susceptibility in ulcerative colitis and colorectal cancer: novel insights from integrative single-cell and multi-omics analysis | 1 | We constructed an integrative framework across tissue, cellular, and variant levels to systematically dissect the pathogenic evolution of this comorbidity across spatiotemporal dimensions. | Abstract | [] |
PMC13160972 | Multidimensional dissection of shared genetic susceptibility in ulcerative colitis and colorectal cancer: novel insights from integrative single-cell and multi-omics analysis | 2 | We integrated GWAS data from 100,204 CRC cases and 12,160 UC patients with tissue-specific MAGMA enrichment, embryonic spatial mapping (gsMap), and multidimensional single-cell prioritization (ECLIPSER, CELLECT, scDRS). | Abstract | [] |
PMC13160972 | Multidimensional dissection of shared genetic susceptibility in ulcerative colitis and colorectal cancer: novel insights from integrative single-cell and multi-omics analysis | 3 | We further resolved cell-specific co-expression patterns using hdWGCNA and identified high-confidence causal variants and genes through Bayesian fine-mapping (eCAVIAR, fastenloc) and Open4Gene analysis. | Abstract | [] |
PMC13160972 | Multidimensional dissection of shared genetic susceptibility in ulcerative colitis and colorectal cancer: novel insights from integrative single-cell and multi-omics analysis | 4 | Genetic susceptibility for both diseases was significantly enriched in the terminal ileum and transverse colon, anchored to E16.5 embryonic gut programs. | Abstract | [
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PMC13160972 | Multidimensional dissection of shared genetic susceptibility in ulcerative colitis and colorectal cancer: novel insights from integrative single-cell and multi-omics analysis | 5 | CD4 + T cells emerged as the core immune hub in UC, exhibiting profound immunometabolic polarization (Th17/IL-17 axis and Warburg effect), while progenitors were identified as the primary cellular origin for CRC malignancy. | Abstract | [
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PMC13160972 | Multidimensional dissection of shared genetic susceptibility in ulcerative colitis and colorectal cancer: novel insights from integrative single-cell and multi-omics analysis | 6 | Pathological progression was characterized by a transition from chronic inflammatory stress toward p53-mediated genomic instability, epithelial-mesenchymal transition (EMT), and vascular remodeling. | Abstract | [] |
PMC13160972 | Multidimensional dissection of shared genetic susceptibility in ulcerative colitis and colorectal cancer: novel insights from integrative single-cell and multi-omics analysis | 7 | We prioritized Tier 1 candidate genes—ARPC5, PTGER4, CIB1, PREX1, and S100A10—as key mediators of the comorbidity association between inflammation and cancer. | Abstract | [] |
PMC13160972 | Multidimensional dissection of shared genetic susceptibility in ulcerative colitis and colorectal cancer: novel insights from integrative single-cell and multi-omics analysis | 8 | These findings partially support a “genetic programming-microenvironment triggering” hypothesis, where regional vulnerabilities established by embryonic developmental programs are activated by postnatal insults, though its broad applicability warrants caution. | Abstract | [
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PMC13160972 | Multidimensional dissection of shared genetic susceptibility in ulcerative colitis and colorectal cancer: novel insights from integrative single-cell and multi-omics analysis | 9 | This study provides a comprehensive multi-scale molecular framework for understanding UC-CRC comorbidity, offering potential targets for risk stratification and therapeutic intervention. | Abstract | [] |
PMC13219086 | A clinically relevant SLC2A1-associated malignant epithelial cell state predicts prognosis and immunotherapy response in lung adenocarcinoma | 0 | Lung adenocarcinoma (LUAD) remains a leading cause of cancer-related mortality, with therapeutic resistance largely driven by unresolved malignant epithelial heterogeneity within the tumor microenvironment. | Abstract | [] |
PMC13219086 | A clinically relevant SLC2A1-associated malignant epithelial cell state predicts prognosis and immunotherapy response in lung adenocarcinoma | 1 | However, the epithelial cell states that underlie poor prognosis and immunotherapy resistance remain incompletely defined. | Abstract | [] |
PMC13219086 | A clinically relevant SLC2A1-associated malignant epithelial cell state predicts prognosis and immunotherapy response in lung adenocarcinoma | 2 | We performed an integrative multi-omics analysis combining large-scale single-cell RNA sequencing, spatial transcriptomics, and bulk transcriptomic data with clinical outcomes. | Abstract | [] |
PMC13219086 | A clinically relevant SLC2A1-associated malignant epithelial cell state predicts prognosis and immunotherapy response in lung adenocarcinoma | 3 | The Scissor algorithm was applied to identify prognosis-associated epithelial cell states, followed by construction of a risk score model. | Abstract | [] |
PMC13219086 | A clinically relevant SLC2A1-associated malignant epithelial cell state predicts prognosis and immunotherapy response in lung adenocarcinoma | 4 | External validation was conducted across multiple independent cohorts, including immunotherapy-treated datasets. | Abstract | [] |
PMC13219086 | A clinically relevant SLC2A1-associated malignant epithelial cell state predicts prognosis and immunotherapy response in lung adenocarcinoma | 5 | We identified a prognostically relevant Scissor⁺ malignant epithelial cell state associated with adverse survival. | Abstract | [] |
PMC13219086 | A clinically relevant SLC2A1-associated malignant epithelial cell state predicts prognosis and immunotherapy response in lung adenocarcinoma | 6 | This state was characterized by activation of MYC, epithelial–mesenchymal transition, hypoxia, and NF-κB signaling, and was linked to an immunosuppressive tumor microenvironment. | Abstract | [] |
PMC13219086 | A clinically relevant SLC2A1-associated malignant epithelial cell state predicts prognosis and immunotherapy response in lung adenocarcinoma | 7 | Based on this state, we developed a Scissor⁺ epithelial cell–derived risk score (SERS), which demonstrated robust and reproducible prognostic performance across multiple cohorts and was associated with reduced responsiveness to immunotherapy. | Abstract | [] |
PMC13219086 | A clinically relevant SLC2A1-associated malignant epithelial cell state predicts prognosis and immunotherapy response in lung adenocarcinoma | 8 | Further analyses identified SLC2A1 as a key gene associated with this malignant epithelial state. | Abstract | [] |
PMC13219086 | A clinically relevant SLC2A1-associated malignant epithelial cell state predicts prognosis and immunotherapy response in lung adenocarcinoma | 9 | Functional experiments confirmed that SLC2A1 promotes tumor cell proliferation, migration, and invasion. | Abstract | [] |
PMC13219086 | A clinically relevant SLC2A1-associated malignant epithelial cell state predicts prognosis and immunotherapy response in lung adenocarcinoma | 10 | In addition, cell–cell communication analysis suggested a potential SLC2A1–CAF–collagen signaling axis linking epithelial cell states with stromal interactions. | Abstract | [] |
PMC13219086 | A clinically relevant SLC2A1-associated malignant epithelial cell state predicts prognosis and immunotherapy response in lung adenocarcinoma | 11 | This study defines a clinically relevant malignant epithelial cell state in LUAD and establishes a framework linking cell states, molecular features, and microenvironmental interactions. | Abstract | [] |
PMC13219086 | A clinically relevant SLC2A1-associated malignant epithelial cell state predicts prognosis and immunotherapy response in lung adenocarcinoma | 12 | These findings provide potential biomarkers for prognostic stratification and immunotherapy response prediction in LUAD. | Abstract | [] |
PMC13279529 | Single-cell Technologies in Atherosclerosis: Uncovering Cellular Heterogeneity, Mechanisms, and Therapeutic Opportunities | 0 | This review highlights recent advances in single-cell analysis technologies and their application in clarifying the cellular and molecular complexity of atherosclerosis, redefining our understanding of vascular biology and immune cell functioning within the atherosclerotic plaque. | Abstract | [
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PMC13279529 | Single-cell Technologies in Atherosclerosis: Uncovering Cellular Heterogeneity, Mechanisms, and Therapeutic Opportunities | 1 | Single-cell RNA sequencing (scRNA-seq), single-cell ATAC-seq, and spatial transcriptomics have revealed an unforeseen diversity of immune and vascular cell states in human and experimental prototypes of atherosclerosis. | Abstract | [] |
PMC13279529 | Single-cell Technologies in Atherosclerosis: Uncovering Cellular Heterogeneity, Mechanisms, and Therapeutic Opportunities | 2 | These techniques have led to the finding of novel macrophage and smooth muscle cell (SMC) phenotypes, distinct endothelial dysfunction signatures, and oligoclonal T cell populations. | Abstract | [
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PMC13279529 | Single-cell Technologies in Atherosclerosis: Uncovering Cellular Heterogeneity, Mechanisms, and Therapeutic Opportunities | 3 | By integrating transcriptomic, epigenomic, proteomic, and spatial data, researchers have clarified key mechanisms of disease progression and identified cell-specific molecular pathways responsive to targeted therapy. | Abstract | [] |
PMC13279529 | Single-cell Technologies in Atherosclerosis: Uncovering Cellular Heterogeneity, Mechanisms, and Therapeutic Opportunities | 4 | Single-cell methods are changing our understanding of atherosclerosis by determining the heterogeneity, plasticity, and functional states of plaque-resident cells. | Abstract | [
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PMC13279529 | Single-cell Technologies in Atherosclerosis: Uncovering Cellular Heterogeneity, Mechanisms, and Therapeutic Opportunities | 5 | These understandings contribute for the development of novel biomarkers, precision diagnostics, and targeted immunomodulatory strategies, with the ultimate goal of improving risk stratification and personalized treatment in atherosclerotic cardiovascular disease. | Abstract | [] |
PMC13152973 | Multivariable genome-wide analysis elucidates the shared genetic architecture, immunosenescence features, and gut-origin therapeutic targets of ulcerative colitis-associated multisystem inflammation | 0 | Over 25% of patients with ulcerative colitis (UC) develop extraintestinal manifestations (EIMs), resulting in significant systemic morbidity. | Abstract | [] |
PMC13152973 | Multivariable genome-wide analysis elucidates the shared genetic architecture, immunosenescence features, and gut-origin therapeutic targets of ulcerative colitis-associated multisystem inflammation | 1 | We define the shared genetic foundation of these manifestations as the UC-associated Multisystem Inflammatory Genetic Architecture (UC-MIGA). | Abstract | [] |
PMC13152973 | Multivariable genome-wide analysis elucidates the shared genetic architecture, immunosenescence features, and gut-origin therapeutic targets of ulcerative colitis-associated multisystem inflammation | 2 | This study aims to identify shared genomic drivers and actionable immunosenescence therapeutic targets across the UC-EIM spectrum. | Abstract | [] |
PMC13152973 | Multivariable genome-wide analysis elucidates the shared genetic architecture, immunosenescence features, and gut-origin therapeutic targets of ulcerative colitis-associated multisystem inflammation | 3 | We applied genomic structural equation modeling (SEM) to seven European-ancestry GWAS datasets (UC, deep vein thrombosis, ankylosing spondylitis, primary sclerosing cholangitis, pyoderma gangrenosum, interstitial lung disease, and erythema nodosum) to identify a shared latent genetic factor (F1). | Abstract | [] |
PMC13152973 | Multivariable genome-wide analysis elucidates the shared genetic architecture, immunosenescence features, and gut-origin therapeutic targets of ulcerative colitis-associated multisystem inflammation | 4 | Post-SEM analyses included FUMA mapping, SuSIE/FINEMAP fine-mapping, FUSION/FOCUS transcriptome-wide studies, MAGMA enrichment, CELLECT deconvolution, LDSC partitioned heritability, and single-cell eQTL Mendelian randomization (MR). | Abstract | [] |
PMC13152973 | Multivariable genome-wide analysis elucidates the shared genetic architecture, immunosenescence features, and gut-origin therapeutic targets of ulcerative colitis-associated multisystem inflammation | 5 | UC exhibited the highest standardized factor loading (0.9801) on F1, justifying its use as a representative proxy for UC-MIGA in downstream analyses. | Abstract | [] |
PMC13152973 | Multivariable genome-wide analysis elucidates the shared genetic architecture, immunosenescence features, and gut-origin therapeutic targets of ulcerative colitis-associated multisystem inflammation | 6 | UC-telomere relationships were assessed via tissue-specific eQTL/sQTL enrichment across 49 GTEx tissues, spatial transcriptomics (gsMap), single-cell profiling (GSE214695, GSE163974), hdWGCNA, and colocalization analyses (eCAVIAR, fastENLOC). | Abstract | [] |
PMC13152973 | Multivariable genome-wide analysis elucidates the shared genetic architecture, immunosenescence features, and gut-origin therapeutic targets of ulcerative colitis-associated multisystem inflammation | 7 | SEM identified substantial genetic overlap (CFI = 1.0, SRMR = 0.17). | Abstract | [] |
PMC13152973 | Multivariable genome-wide analysis elucidates the shared genetic architecture, immunosenescence features, and gut-origin therapeutic targets of ulcerative colitis-associated multisystem inflammation | 8 | Within the UC-MIGA framework, we identified 17,005 SNPs (P ≤ 1 × 10⁻2⁰⁰), 2,622 risk loci, and 152 high-confidence effector genes. | Abstract | [] |
PMC13152973 | Multivariable genome-wide analysis elucidates the shared genetic architecture, immunosenescence features, and gut-origin therapeutic targets of ulcerative colitis-associated multisystem inflammation | 9 | Pathways implicated Th17/Treg imbalance and inflammasome signaling. | Abstract | [] |
PMC13152973 | Multivariable genome-wide analysis elucidates the shared genetic architecture, immunosenescence features, and gut-origin therapeutic targets of ulcerative colitis-associated multisystem inflammation | 10 | Super-enhancer regions showed exceptional heritability enrichment (80.16%, fold = 4.79, p = 0.0007). | Abstract | [] |
PMC13152973 | Multivariable genome-wide analysis elucidates the shared genetic architecture, immunosenescence features, and gut-origin therapeutic targets of ulcerative colitis-associated multisystem inflammation | 11 | MR identified 35 causal immune cell-gene associations. | Abstract | [] |
PMC13152973 | Multivariable genome-wide analysis elucidates the shared genetic architecture, immunosenescence features, and gut-origin therapeutic targets of ulcerative colitis-associated multisystem inflammation | 12 | UC-telomere analyses revealed convergence in colon-specific DNA repair-mitochondrial energetics-telomere maintenance pathways, with B cells prioritized as the core cell type. | Abstract | [
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PMC13152973 | Multivariable genome-wide analysis elucidates the shared genetic architecture, immunosenescence features, and gut-origin therapeutic targets of ulcerative colitis-associated multisystem inflammation | 13 | Colocalization identified NKX2-3 and LINC01475 as high-confidence shared candidates. | Abstract | [] |
PMC13152973 | Multivariable genome-wide analysis elucidates the shared genetic architecture, immunosenescence features, and gut-origin therapeutic targets of ulcerative colitis-associated multisystem inflammation | 14 | Embryonic intestinal enrichment supported the developmental origins of this systemic axis. | Abstract | [
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PMC13152973 | Multivariable genome-wide analysis elucidates the shared genetic architecture, immunosenescence features, and gut-origin therapeutic targets of ulcerative colitis-associated multisystem inflammation | 15 | UC-MIGA represents a genetically coherent architecture driven by super-enhancer-mediated epigenetic dysregulation, Th17/Treg imbalance, and immunosenescence features, including telomere dysfunction and B-cell exhaustion. | Abstract | [] |
PMC13152973 | Multivariable genome-wide analysis elucidates the shared genetic architecture, immunosenescence features, and gut-origin therapeutic targets of ulcerative colitis-associated multisystem inflammation | 16 | The ‘developmental vulnerability-environmental trigger’ model explains the gut-origin inflammatory cascade underlying extraintestinal manifestations, with UC-telomere analysis providing a genomic foundation for systemic therapeutic strategies targeting the inflammation-aging nexus. | Abstract | [] |
PMC13273311 | Optimal gene panel selection for targeted spatial transcriptomics experiments | 0 | Spatial transcriptomics analysis is a powerful approach for dissecting the structure of tissue microenvironment and uncovering the mechanism of cell–cell communications. | Abstract | [] |
PMC13273311 | Optimal gene panel selection for targeted spatial transcriptomics experiments | 1 | However, existing technologies are limited by either spatial resolution or gene coverage. | Abstract | [] |
PMC13273311 | Optimal gene panel selection for targeted spatial transcriptomics experiments | 2 | Most single-cell-resolution technologies target only a few hundred preselected genes, whose choice plays an important role in the overall analysis. | Abstract | [] |
PMC13273311 | Optimal gene panel selection for targeted spatial transcriptomics experiments | 3 | It remains a challenge to optimally design a gene panel to maximize the utility of spatial transcriptomics profiling. | Abstract | [] |
PMC13273311 | Optimal gene panel selection for targeted spatial transcriptomics experiments | 4 | To fill this gap, we introduce a novel method, named ReconST, to automatically design optimal gene panels for spatial transcriptomics profiling. | Abstract | [] |
PMC13273311 | Optimal gene panel selection for targeted spatial transcriptomics experiments | 5 | ReconST leverages information from existing scRNA-seq data and identifies the optimal subset of genes by using a gated autoencoder. | Abstract | [] |
PMC13273311 | Optimal gene panel selection for targeted spatial transcriptomics experiments | 6 | By using a high-coverage mouse brain MERFISH dataset and a fetal lung dataset as the reference benchmarks, we showed that ReconST outperforms existing methods in terms of reconstruction accuracy, spatial pattern preservation, and computing efficiency. | Abstract | [] |
PMC13273311 | Optimal gene panel selection for targeted spatial transcriptomics experiments | 7 | As such, ReconST provides a useful and generally applicable tool for optimal gene panel design, which in turn can significantly enhance the utility of spatial transcriptomics profiling in a wide range of biomedical investigations. | Abstract | [] |
PMC13257420 | Multi-Dimensional Transcriptomics Reveals the Prominent Role of Neuroinflammation in Alzheimer’s Disease | 0 | Alzheimer’s Disease (AD), the most common form of dementia, is pathologically defined by extracellular beta-amyloid (Aβ) plaques and intraneuronal neurofibrillary tangles (NFTs), accompanied by chronic neuroinflammation. | Abstract | [] |
PMC13257420 | Multi-Dimensional Transcriptomics Reveals the Prominent Role of Neuroinflammation in Alzheimer’s Disease | 1 | Recent advances in single-cell RNA sequencing (scRNA-seq/snRNA-seq) and spatial transcriptomics have provided unprecedented resolution for unraveling the cellular and molecular landscape of neuroinflammation in AD. | Abstract | [] |
PMC13257420 | Multi-Dimensional Transcriptomics Reveals the Prominent Role of Neuroinflammation in Alzheimer’s Disease | 2 | While scRNA-seq enables high-throughput profiling of cellular heterogeneity across brain regions, spatial transcriptomics preserves tissue architecture to map cell-type-specific gene expression within its anatomical context. | Abstract | [
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PMC13257420 | Multi-Dimensional Transcriptomics Reveals the Prominent Role of Neuroinflammation in Alzheimer’s Disease | 3 | This review synthesizes the neuroinflammatory mechanisms of AD, outlines the technical evolution and comparative capabilities of single-cell and spatial omics platforms, including resolution, throughput, and compatibility with multiple sample types, and critically evaluates findings from studies in both animal models a... | Abstract | [
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PMC13257420 | Multi-Dimensional Transcriptomics Reveals the Prominent Role of Neuroinflammation in Alzheimer’s Disease | 4 | These approaches have revealed state-specific transitions in microglia and astrocytes, including shifts in transcriptional programs, metabolic reprogramming, and pro-inflammatory polarization across disease stages. | Abstract | [
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PMC13257420 | Multi-Dimensional Transcriptomics Reveals the Prominent Role of Neuroinflammation in Alzheimer’s Disease | 5 | Notably, spatial transcriptomic analyses demonstrate pronounced regional heterogeneity: periplaque microenvironments exhibit distinct immune-cell compositions and gene expression signatures. | Abstract | [] |
PMC13257420 | Multi-Dimensional Transcriptomics Reveals the Prominent Role of Neuroinflammation in Alzheimer’s Disease | 6 | Collectively, these omics technologies are redefining the cellular basis of AD progression and hold the potential to impact the discovery of early diagnostic biomarkers and precision therapeutic targets. | Abstract | [] |
PMC13257420 | Multi-Dimensional Transcriptomics Reveals the Prominent Role of Neuroinflammation in Alzheimer’s Disease | 7 | Keywords: Alzheimer’s disease, neuroinflammation, single-cell RNA sequencing, spatial transcriptomics, microglia, astrocyte | Abstract | [
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PMC13187092 | Multi-Omics reveals SPP1 + malignant and CXCR4+ TAM crosstalk predicts immunotherapy response in lung adenocarcinoma | 0 | Lung adenocarcinoma (LUAD), a common lung cancer subtype, is significantly influenced by the immune microenvironment. | Abstract | [] |
PMC13187092 | Multi-Omics reveals SPP1 + malignant and CXCR4+ TAM crosstalk predicts immunotherapy response in lung adenocarcinoma | 1 | Immune checkpoint inhibitors have shown limited efficacy in Lung adenocarcinoma due to the immunosuppressive tumor microenvironment (TME). | Abstract | [] |
PMC13187092 | Multi-Omics reveals SPP1 + malignant and CXCR4+ TAM crosstalk predicts immunotherapy response in lung adenocarcinoma | 2 | Identifying predictive biomarkers for immunotherapy response remains an urgent clinical need. | Abstract | [] |
PMC13187092 | Multi-Omics reveals SPP1 + malignant and CXCR4+ TAM crosstalk predicts immunotherapy response in lung adenocarcinoma | 3 | Multi-Omics data of LUAD were analyzed to investigate the immune microenvironment in LUAD. | Abstract | [] |
PMC13187092 | Multi-Omics reveals SPP1 + malignant and CXCR4+ TAM crosstalk predicts immunotherapy response in lung adenocarcinoma | 4 | Single cell RNA-seq was used for exploring the intercellular communication mechanisms in TME. | Abstract | [] |
PMC13187092 | Multi-Omics reveals SPP1 + malignant and CXCR4+ TAM crosstalk predicts immunotherapy response in lung adenocarcinoma | 5 | Spatial transcriptomic analysis confirmed the spatial co-localization of SPP1+ Malignant and CXCR4+ TAM, while in vitro experiments validated the functions of biomarker. | Abstract | [
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PMC13187092 | Multi-Omics reveals SPP1 + malignant and CXCR4+ TAM crosstalk predicts immunotherapy response in lung adenocarcinoma | 6 | This study delineated the cellular heterogeneity and dynamic shifts within the LUAD tumor microenvironment, resolving the malignant transformation trajectory. | Abstract | [] |
PMC13187092 | Multi-Omics reveals SPP1 + malignant and CXCR4+ TAM crosstalk predicts immunotherapy response in lung adenocarcinoma | 7 | Crucially, we identified SPP1⁺ malignant and CXCR4⁺ TAM crosstalk as a driver of exhaustion of CD8T, which induced poor immunotherapy response. | Abstract | [
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PMC13187092 | Multi-Omics reveals SPP1 + malignant and CXCR4+ TAM crosstalk predicts immunotherapy response in lung adenocarcinoma | 8 | Moreover, this study indicated that the immune escape potential of patients in high infiltration of SPP1+ malignant and CXCR4+ TAM increased, and the efficacy of immune checkpoint suppressive therapy might be poorer. | Abstract | [
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PMC13187092 | Multi-Omics reveals SPP1 + malignant and CXCR4+ TAM crosstalk predicts immunotherapy response in lung adenocarcinoma | 9 | Spatial transcriptomics confirmed co-localization of SPP1+ Malignant and CXCR4+ TAM, while in vitro experiments demonstrated that CXCR4 plays an important role in the functions of LUAD cells. | Abstract | [
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PMC13187092 | Multi-Omics reveals SPP1 + malignant and CXCR4+ TAM crosstalk predicts immunotherapy response in lung adenocarcinoma | 10 | This study uncovers the SPP1⁺ malignant and CXCR4⁺ TAM crosstalk as a novel TME-driven resistance mechanism and provides a potential biomarker for stratifying LUAD patients likely to benefit from immunotherapy. | Abstract | [] |
PMC13187092 | Multi-Omics reveals SPP1 + malignant and CXCR4+ TAM crosstalk predicts immunotherapy response in lung adenocarcinoma | 11 | Keywords: Tumor-associated macrophages, Prognosis, Immune microenvironment, Immunotherapy, Biomarker | Abstract | [] |
PMC13190926 | Integrating single-cell and spatial transcriptomics to decipher the neuro-immune microenvironment of breast cancer brain metastasis: a key regulatory axis, prognostic model, and drug discovery | 0 | Breast cancer brain metastasis (BCBM) is a lethal complication of advanced disease, facilitated by a specialized neuro-immune microenvironment, whereas its molecular regulators and spatial dynamics remain poorly understood. | Abstract | [] |
PMC13190926 | Integrating single-cell and spatial transcriptomics to decipher the neuro-immune microenvironment of breast cancer brain metastasis: a key regulatory axis, prognostic model, and drug discovery | 1 | This study aimed to resolve cellular heterogeneity and intercellular signaling networks crosstalk in BCBM microenvironment by using integrated single-cell RNA sequencing (scRNA-seq) single-cell and spatial transcriptomics to identify key regulators, build a prognostic model, and computationally screen for potential the... | Abstract | [] |
PMC13190926 | Integrating single-cell and spatial transcriptomics to decipher the neuro-immune microenvironment of breast cancer brain metastasis: a key regulatory axis, prognostic model, and drug discovery | 2 | We analyzed public scRNA-seq and 10× Visium spatial transcriptomics datasets. | Abstract | [] |
PMC13190926 | Integrating single-cell and spatial transcriptomics to decipher the neuro-immune microenvironment of breast cancer brain metastasis: a key regulatory axis, prognostic model, and drug discovery | 3 | Cell landscapes were resolved with Seurat, communication networks were inferred with CellChat, and spatial mapping was performed with Tangram. | Abstract | [] |
PMC13190926 | Integrating single-cell and spatial transcriptomics to decipher the neuro-immune microenvironment of breast cancer brain metastasis: a key regulatory axis, prognostic model, and drug discovery | 4 | A prognostic risk model was developed from bulk RNA sequencing (RNA-seq) data from The Cancer Genome Atlas-Breast Cancer (TCGA-BRCA), the Gene Expression Omnibus (GEO) datasets using Least Absolute Shrinkage and Selection Operator-Cox (LASSO-Cox) regression and validated in an independent cohort. | Abstract | [] |
PMC13190926 | Integrating single-cell and spatial transcriptomics to decipher the neuro-immune microenvironment of breast cancer brain metastasis: a key regulatory axis, prognostic model, and drug discovery | 5 | Potential small-molecule inhibitors were screened by molecular docking (AutoDock Vina) against AlphaFold-predicted target structures. | Abstract | [] |
PMC13190926 | Integrating single-cell and spatial transcriptomics to decipher the neuro-immune microenvironment of breast cancer brain metastasis: a key regulatory axis, prognostic model, and drug discovery | 6 | The BCBM microenvironment exhibited high heterogeneity, with macrophages serving as the central signaling hub. | Abstract | [
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PMC13190926 | Integrating single-cell and spatial transcriptomics to decipher the neuro-immune microenvironment of breast cancer brain metastasis: a key regulatory axis, prognostic model, and drug discovery | 7 | A novel regulatory axis, interleukin-18 and myosin light chain kinase (IL-18/MYLK), was found to be specifically upregulated and co-localized at the tumor-brain interface. | Abstract | [] |
PMC13190926 | Integrating single-cell and spatial transcriptomics to decipher the neuro-immune microenvironment of breast cancer brain metastasis: a key regulatory axis, prognostic model, and drug discovery | 8 | A risk-score model based on the IL-18/MYLK axis demonstrated robust prognostic value in both training and validation cohorts. | Abstract | [] |
PMC13190926 | Integrating single-cell and spatial transcriptomics to decipher the neuro-immune microenvironment of breast cancer brain metastasis: a key regulatory axis, prognostic model, and drug discovery | 9 | The model further revealed that the upregulation of IL-18 and MYLK was associated with better overall survival. | Abstract | [] |
PMC13190926 | Integrating single-cell and spatial transcriptomics to decipher the neuro-immune microenvironment of breast cancer brain metastasis: a key regulatory axis, prognostic model, and drug discovery | 10 | Virtual screening identified the MEK inhibitor, PD98059, as a high-affinity dual inhibitor of IL-18 and MYLK. | Abstract | [] |
PMC13190926 | Integrating single-cell and spatial transcriptomics to decipher the neuro-immune microenvironment of breast cancer brain metastasis: a key regulatory axis, prognostic model, and drug discovery | 11 | This study delineates the neuro-immune landscape of BCBM progression and proposes the IL-18/MYLK axis as a critical driver of neuroinflammation and cytoskeletal remodeling. | Abstract | [] |
PMC13190926 | Integrating single-cell and spatial transcriptomics to decipher the neuro-immune microenvironment of breast cancer brain metastasis: a key regulatory axis, prognostic model, and drug discovery | 12 | The prognostic model and the candidate compound PD98059 provide avenues for novel targeted therapeutic strategies. | Abstract | [] |
PMC13190926 | Integrating single-cell and spatial transcriptomics to decipher the neuro-immune microenvironment of breast cancer brain metastasis: a key regulatory axis, prognostic model, and drug discovery | 13 | Keywords: Breast cancer brain metastasis (BCBM), single-cell RNA sequencing (scRNA-seq), spatial transcriptomics, interleukin-18 (IL-18), myosin light chain kinase (MYLK) | Abstract | [] |
PMC13244270 | Tumor heterogeneity as a driver of drug resistance and its implications for personalized therapy | 0 | Tumors are highly dynamic diseases characterized by significant heterogeneity. | Abstract | [] |
PMC13244270 | Tumor heterogeneity as a driver of drug resistance and its implications for personalized therapy | 1 | They consist of multiple cellular populations with distinct properties that respond differently to therapeutic pressure. | Abstract | [] |
PMC13244270 | Tumor heterogeneity as a driver of drug resistance and its implications for personalized therapy | 2 | This heterogeneity may arise from spatial variation across tumor regions (spatial heterogeneity) as well as from temporal changes during tumor evolution and treatment (temporal heterogeneity). | Abstract | [] |
PMC13244270 | Tumor heterogeneity as a driver of drug resistance and its implications for personalized therapy | 3 | As a consequence, drug-resistant subclones often emerge under therapy and contribute to treatment failure. | Abstract | [] |
PMC13244270 | Tumor heterogeneity as a driver of drug resistance and its implications for personalized therapy | 4 | Advances in single-cell and spatial multi-omics technologies enable precise quantification of tumor heterogeneity, supporting detailed investigation of how heterogeneity contributes to chemoresistance and informing the development of personalized therapeutic strategies. | Abstract | [] |
PMC13244270 | Tumor heterogeneity as a driver of drug resistance and its implications for personalized therapy | 5 | In this review, we summarize the evolutionary dynamics underlying the emergence of tumor drug resistance and examine the molecular mechanisms responsible for failure of targeted therapies. | Abstract | [] |
PMC13244270 | Tumor heterogeneity as a driver of drug resistance and its implications for personalized therapy | 6 | We highlight how advances in single-cell and spatial multi-omics have significantly improved our ability to elucidate these processes. | Abstract | [] |
PMC13244270 | Tumor heterogeneity as a driver of drug resistance and its implications for personalized therapy | 7 | We further suggest that addressing tumor drug resistance may require a shift from static, single-target approaches toward dynamic, biology-informed personalized strategies. | Abstract | [] |
PMC13244270 | Tumor heterogeneity as a driver of drug resistance and its implications for personalized therapy | 8 | Integrating high-resolution multi-omics monitoring with functional validation could enable identification of subclonal vulnerabilities, support adaptive treatment adjustment, and contribute to more durable clinical responses. | Abstract | [] |
PMC13244270 | Tumor heterogeneity as a driver of drug resistance and its implications for personalized therapy | 9 | Keywords: Tumor heterogeneity, drug resistance, single-cell omics, spatial omics, personalized therapy, targeted therapy | Abstract | [] |
PMC13147954 | Spatial multi‐omics identifies a NOTCH3‐mediated capillary–mCAF crosstalk driving immune exclusion in hepatocellular carcinoma | 0 | Fibrosis induced immune exclusion is a hepatocellular carcinoma (HCC) hallmark, underscoring the key role of cancer‐associated fibroblasts (CAFs) in immune regulation. | Abstract | [] |
PMC13147954 | Spatial multi‐omics identifies a NOTCH3‐mediated capillary–mCAF crosstalk driving immune exclusion in hepatocellular carcinoma | 1 | Through HCC spatial multi‐omics data and integrating pan‐cancer scRNA‐seq profiles of CAFs under immune checkpoint blockade (ICB) treatment, we characterized a potential crosstalk between capillaries and CAFs mediated by the NOTCH signaling pathway. | Abstract | [
{
"end": 199,
"entity_group": "Cell_Tissue",
"score": 0.9998899698257446,
"start": 188,
"word": "capillaries"
},
{
"end": 208,
"entity_group": "Cell_Tissue",
"score": 0.7969785332679749,
"start": 204,
"word": "cafs"
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] |
End of preview. Expand in Data Studio
CeLLaTe-BenchMark-predictions-best-model-candidate-1
Dataset Summary
This is a benchmark dataset containing generated NER predictions produced using one of CeLLaTe NER current production candidate model:
Mardiyyah/CeLLaTe-ner-2class-gaz-tapt-pubmedbert-tokenizer-adapted-combinedData-lr_3.89
This dataset was created as part of rigorous testing intended to support the productionalisation of the developed CeLLaTe NER models.
The raw input data is a set of 50 abstract-only examples. Reference information on the benchmark set composition and construction can be found here:
OTAR3088/CeLLaTe-benchMark-set-abstractonly
Dataset Description
This dataset contains model-generated predictions over the abstract-only benchmark set. It is intended to support downstream human review and comparative evaluation of candidate NER systems.
Dataset Motivation
The purpose of generating this dataset is to:
- support in-house domain-expert review of model prediction quality
- assess whether additional post-processing is required
- examine annotation quality and entity boundary correctness
- compare the current production candidate against other leading model candidates using an LLM-as-a-judge workflow
Intended Uses
This dataset is intended for:
- benchmarking model outputs
- domain-expert review
- qualitative error analysis
- LLM-assisted ranking of competing model outputs
- post-processing evaluation
It is not a gold-standard annotated corpus and should not be used as ground truth.
Data Fields
The dataset contains model predictions generated from the abstract-only benchmark set. Depending on the dataset representation, records may include:
- the input abstract text
- predicted entity spans
- predicted entity labels
- prediction confidence scores
- model metadata
Task Information
This dataset is designed for 2-class biomedical NER with the following labels:
CellLineCell_Tissue
Source Data
The benchmark inputs originate from:
OTAR3088/CeLLaTe-benchMark-set-abstractonly
Generation Details
Predictions were generated using the following model:
Mardiyyah/CeLLaTe-ner-2class-gaz-tapt-pubmedbert-tokenizer-adapted-combinedData-lr_3.89
This dataset was created to serve as one of the candidate outputs in a comparative evaluation workflow, alongside two other high-performing models identified during development.
Limitations
- This dataset contains model predictions, not manually curated annotations.
- Performance on this dataset should be interpreted as benchmark output quality, not final biological truth.
- Final deployment decisions should consider both quantitative results and qualitative review by domain experts.
- Boundary correctness and label consistency may require additional post-processing.
Considerations for Use
When using this dataset, consider evaluating:
- exact entity boundary correctness
- false positives and false negatives
- consistency of label assignment
- whether span post-processing improves output quality
- agreement between model predictions and expert judgement
Citation
If you use this dataset or derive results from it, please cite:
OTAR3088/CeLLaTe-benchMark-set-abstractonlyMardiyyah/CeLLaTe-ner-2class-gaz-tapt-pubmedbert-tokenizer-adapted-combinedData-lr_3.89
Acknowledgements
This dataset was generated as part of the CeLLaTe NER model productionalisation workflow.
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