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The RNA helicase DDX21 cooperates with ETS1 and FLI1 in cell cycle, immune evasion, and snoRNA processing in activated B-cell-like diffuse large B-cell lymphoma cells
Diffuse large B-cell lymphoma (DLBCL) is a clinically and biologically heterogeneous disease, with the activated B-cell-like (ABC) subtype showing inferior outcomes. The ETS transcription factors ETS1 and FLI1 are recurrently gained and functionally relevant in DLBCL, yet their pathogenic role remains to be fully elucidated. Here, we describe their cooperation with the RNA regulatory machinery, demonstrating that the RNA helicase DDX21 is a central effector of the ETS1/FLI1 transcriptional...
Transcriptomic, Specific Marker, and Pathway Analysis of Smooth Muscle Cell Foam Cells Compared to Macrophage Foam Cells in Human Atherosclerosis
BACKGROUND: Smooth muscle cells (SMCs) comprise the majority of cells in human atherosclerotic lesions and are thought to be a major source of cholesterol-overloaded foam cells in human and mouse atheromas. However, the transcriptomic profile, specific markers, and biologic itinerary of SMC foam cells relative to macrophage foam cells remain poorly defined. METHODS: Single-cell RNA sequencing (scRNA-seq) was performed on fresh coronary artery segments from heart transplant recipients with...
Single-Cell Multi-Omics Dissection of Malignant Evolutionary Mechanisms and Construction of a Prognostic Model for Clear Cell Renal Cell Carcinoma
Clear cell renal cell carcinoma (ccRCC) exhibits pronounced heterogeneity across WHO histological grades, yet systematic single-cell multi-omics studies characterizing these transitions remain limited. We integrated scRNA-seq and scATAC-seq data across ccRCC WHO grades to establish a multi-omics framework encompassing tumor cells and immune populations. Using pseudotime trajectory analysis and machine learning ensembles, we developed a prognostic signature (CBG) from core nodes of...
Single-cell multimodal profiling of pan-cancer cell lines uncovers gene regulatory principles underlying intrinsic cell states and environmental features
Cancer arises from extensive genetic and epigenetic alterations that reshape chromatin, transcriptional regulation, and malignant cell states. To systematically chart cancer-intrinsic regulatory programs, we constructed a pan-cancer single-cell transcriptomic and epigenomic atlas encompassing 60 human cell lines representing 16 tissue origins and 20 cancer types, comprising 240,957 single-nucleus RNA-seq and 223,347 single-nucleus ATAC-seq profiles. Integrative analyses revealed extensive...
GC-MoE: Genomics-Guided Cell-Type-Specific Mixture of Experts for Histology-Based Single-Cell Spatial Transcriptomics
Announce Type: new Abstract: Histology-based single-cell spatial transcriptomics (ST) estimation aims to predict gene expression for individual cells from histopathological images and cell locations, reducing the need for costly single-cell ST measurements. Unlike existing histology-to-ST methods that mainly predict spot-level profiles for local regions containing multiple cells, this task requires modeling cell-to-cell expression variability, which is strongly structured by cell type. We...
Modeling in vitro cell-to-cell spread of hepatitis C viral infection using an agent-based approach
Mechanisms that lead to viral chronicity are poorly understood, but cell-to-cell spread has been implicated in the establishment of chronic infections. We previously developed mathematical models to explore the nature of hepatitis C virus (HCV) cell-to-cell spread in vitro and quantified the effect of inhibiting individual host factors involved. However, the previous models were not designed to (i) address cell proliferation, (ii) account for differences in cell size, and (iii) did not...
CellClick: an interactive platform for adjustable and accurate cell type annotation in single-cell and spatial omics data
Single-cell omics and spatial omics technologies are nowadays widely used in biological and medical research. In both single-cell and spatial omics data analysis, accurate cell type annotation is a key step for downstream analysis and scientific discoveries. However, high-quality cell annotation usually requires multiple rounds of manual analysis for result refinement, which poses great challenges to most researchers.
Decoding Hierarchical Cell-Cell Communication in Spatial Multi-Omics with CellSTIC
Cell-cell communication helps to coordinate tissue development, homeostasis, and immune responses, but identifying signaling interactions within intact tissues remains difficult. Although single-cell transcriptomics has enabled systematic inference of ligand-receptor interactions, dissociation disrupts spatial context and limits the identification of bona fide local signaling and region-specific communication programs. Spatial transcriptomics and spatial multi-omics offer the opportunity to...
Organoid-T cell co-cultures functionally stratify tumor-reactive T cells and their responses to immune checkpoint inhibitors
Tumor-reactive T cells (TRTs) are critical for anti-tumor immunity but are incompletely captured by current assays, which fail to reproduce tumor-specific antigen diversity. Here, we show that multiplex functional profiling of patient-derived tumor organoid-T cell co-cultures (PDOTs) enables robust identification of TRTs across CD8, CD4, and double-negative (DN) T cell populations. Single activation markers underestimated TRT responses, whereas integrated analysis revealed broader functional...
Differential Transcript Usage Reveals Isoform-Level Remodeling of Tumor Biology in Clear Cell Renal Cell Carcinoma
Clear cell renal cell carcinoma (ccRCC) is characterized by transcriptional reprogram-ming driven by hypoxia signaling, metabolic rewiring, and immune modulation. While gene-level analyses have defined key features of ccRCC biology, they do not capture isoform-level variation arising from alternative splicing. Differential transcript usage (DTU) represents an additional regulatory layer that may influence protein function, pathway activity, and clinical outcomes, yet its role in ccRCC...