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EBNA1BP2 identified as potential prognostic biomarker for multiple tumor types in pan-cancer analysis.
BACKGROUND: Epstein-Barr virus (EBV) infection has been closely linked to the development of various types of cancer. EB nuclear antigen 1 binding protein 2 (EBNA1BP2) is a crucial molecule for stable isolation of EBV in latent infection. However, the role of EBNA1BP2 in multiple tumor types is remains unclear. In this study, we comprehensively analyzed the functional characteristics of EBNA1BP2 and investigate its potential as a prognostic biomarker in pan-cancer. METHODS: We utilized data from TCGA (The Cancer Genome Atlas) and GEO (Gene Expression Omnibus) databases and employed various bioinformatics analysis tools, including TIMER2.0, HPA, GEPIA2.0, PrognoScan, cBioPortal, CancerSEA, and BioGRID to explore the expression pattern, prognostic value, immune infiltration, and methylation level of EBNA1BP2 in pan-cancer. Additionally, we conducted enrichment analysis of genes associated with EBNA1BP2 to identify potential biological functions and pathways. RESULTS: Our analysis revealed that EBNA1BP2 expression was significantly higher in tumor tissues compared to tumor-adjacent tissues. We observed that lower expression of EBNA1BP2 in adrenocortical carcinoma (ACC), brain lower grade glioma (LGG), sarcoma (SARC), and uterine carcinosarcoma (UCS) was significantly associated with improved overall survival (OS) and disease-free survival (DFS). Furthermore, the promoter methylation level of EBNA1BP2 was downregulated in the majority of cancer types. At the single-cell level, EBNA1BP2 was found to be positively correlated with cell cycle and DNA repair processes, while negatively correlated with hypoxia. Additionally, EBNA1BP2 was associated with the infiltration of immune cells such as B cells, cancer-associated fibroblast cells, and CD8+ T cells. Gene enrichment analysis indicated that EBNA1BP2 was mainly involved in nucleoplasm and RNA binding pathways. CONCLUSION: Our findings suggest that EBNA1BP2 may serve as a potential prognostic biomarker for survival in pan-cancer. Further experimental studies are needed to validate these findings and explore the underlying mechanisms by which EBNA1BP2 contributes to tumorigenesis.
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Single-Cell Transcriptome Reveals Aquaporin-Mediated Carbon Nanosol-Induced Growth Promotion of Plants.
Carbon nanosol (CNS) is a novel carbon nanomaterial with the potential for enhancing plant growth, yet the underlying mechanism remains unclear. Application of 10 mg L-1 CNS significantly promotes plant growth, increasing fresh mass by 59.51%. Track of fluorescent labeling CNS reveals that it is rapidly absorbed by roots and entered the vascular bundle and cortex within 2 h. A single-cell transcriptomic atlas of tobacco roots response to CNS treatment is generated, which comprises 7,897 cells representing 13 distinct cell types. CNS is found to affect gene expression in a cell type-specific manner, suggesting the heterogeneity of plant response to CNS. Further pseudo-time trajectory analysis reveals that most cell types undergo cell fate transitions toward a more mature state under CNS treatment. In addition, aquaporin proteins NIPs and TIPs are found to be activated and significantly upregulated in epidermal, cortical, and endodermal cells. Further genetic and physiological findings reveal that growth enhance effect of CNS for tip1;1 and tip2;1 mutants is significantly weakened compared to the wild type, indicating that aquaporins play an important role in CNS-mediated plant growth promotion. Overall, these results provide new insights into the mechanism by which CNS promotes plant growth at the single-cell level.
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Integrated single-cell RNA sequencing analysis reveals distinct cellular and transcriptional modules associated with survival in lung cancer.
Lung adenocarcinoma (LUAD) and squamous carcinoma (LUSC) are two major subtypes of non-small cell lung cancer with distinct pathologic features and treatment paradigms. The heterogeneity can be attributed to genetic, transcriptional, and epigenetic parameters. Here, we established a multi-omics atlas, integrating 52 single-cell RNA sequencing and 2342 public bulk RNA sequencing. We investigated their differences in genetic amplification, cellular compositions, and expression modules. We revealed that LUAD and LUSC contained amplifications occurring selectively in subclusters of AT2 and basal cells, and had distinct cellular composition modules associated with poor survival of lung cancer. Malignant and stage-specific gene analyses further uncovered critical transcription factors and genes in tumor progression. Moreover, we identified subclusters with proliferating and differentiating properties in AT2 and basal cells. Overexpression assays of ten genes, including sub-cluster markers AQP5 and KPNA2, further indicated their functional roles, providing potential targets for early diagnosis and treatment in lung cancer.
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Multi-species single-cell transcriptomic analysis of ocular compartment regulons.
The retina is a widely profiled tissue in multiple species by single-cell RNA sequencing studies. However, integrative research of the retina across species is lacking. Here, we construct the first single-cell atlas of the human and porcine ocular compartments and study inter-species differences in the retina. In addition to that, we identify putative adult stem cells present in the iris tissue. We also create a disease map of genes involved in eye disorders across compartments of the eye. Furthermore, we probe the regulons of different cell populations, which include transcription factors and receptor-ligand interactions and reveal unique directional signalling between ocular cell types. In addition, we study conservation of regulons across vertebrates and zebrafish to identify common core factors. Here, we show perturbation of KLF7 gene expression during retinal ganglion cells differentiation and conclude that it plays a significant role in the maturation of retinal ganglion cells.
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Deciphering the distinct transcriptomic and gene regulatory map in adult macaque basal ganglia cells.
BACKGROUND: The basal ganglia are a complex of interconnected subcortical structures located beneath the mammalian cerebral cortex. The degeneration of dopaminergic neurons in the basal ganglia is the primary pathological feature of Parkinson's disease. Due to a lack of integrated analysis of multiomics datasets across multiple basal ganglia brain regions, very little is known about the regulatory mechanisms of this area. FINDINGS: We utilized high-throughput transcriptomic and epigenomic analysis to profile over 270,000 single-nucleus cells to create a cellular atlas of the basal ganglia, characterizing the cellular composition of 4 regions of basal ganglia in adult macaque brain, including the striatum, substantia nigra (SN), globus pallidum, and amygdala. We found a distinct epigenetic regulation on gene expression of neuronal and nonneuronal cells across regions in basal ganglia. We identified a cluster of SN-specific astrocytes associated with neurodegenerative diseases and further explored the conserved and primate-specific transcriptomics in SN cell types across human, macaque, and mouse. Finally, we integrated our epigenetic landscape of basal ganglia cells with human disease heritability and identified a regulatory module consisting of candidate cis-regulatory elements that are specific to medium spiny neurons and associated with schizophrenia. CONCLUSIONS: In general, our macaque basal ganglia atlas provides valuable insights into the comprehensive transcriptome and epigenome of the most important and populous cell populations in the macaque basal ganglia. We have identified 49 cell types based on transcriptomic profiles and 47 cell types based on epigenomic profiles, some of which exhibit region specificity, and characterized the molecular relationships underlying these brain regions.
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Integrated proteomic and single-nucleus transcriptomic profiling identifies prognostic markers and therapeutic targets in glioblastoma.
Glioblastoma (GBM) is the most aggressive primary malignant brain tumor in adults and remains associated with marked heterogeneity and poor prognosis. To identify prognostic biomarkers and characterize their cellular contexts, we integrated public proteomic and single-nucleus transcriptomic datasets. Protein expression data from the TCPA GBM cohort were used to construct a prognostic model by univariate and multivariable Cox regression analyses, followed by Kaplan-Meier survival, time-dependent ROC, and nomogram analyses. Single-nucleus RNA-seq data from GSE138794 were used to define the cellular distribution of model proteins and to perform marker-centered functional analyses. A four-protein signature consisting of BCL2, CTNNB1, CHEK2, and NDRG1_pT346 was established. The derived risk score significantly stratified patients into high- and low-risk groups with distinct overall survival and progression-free survival outcomes, and remained independently associated with prognosis after adjustment for clinical covariates. In the single-cell atlas, inferCNV-guided refinement identified malignant glioma cells and further resolved them into Glioma_MES, Glioma_PN, and Glioma_CL states. The four prognostic markers showed distinct cellular preferences: BCL2 and NDRG1 were mainly enriched in oligodendroglial-related populations and selected glioma states, whereas CHEK2 and CTNNB1 were more highly expressed in myeloid-associated populations. Among the four markers, only CHEK2- and NDRG1-defined malignant glioma subgroups showed sufficient transcriptional divergence for downstream analysis. CHEK2-positive glioma cells were enriched for DNA replication, chromosome segregation, DNA damage response, and checkpoint-related programs, whereas NDRG1-positive glioma cells were characterized by hypoxia response, glycolysis, and metabolic adaptation. CellChat analysis further revealed distinct communication patterns for CHEK2- and NDRG1-associated malignant glioma cells.
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An immunometabolism-related signature for renal clear cell carcinoma diagnosis and therapeutic target.
Kidney renal clear cell carcinoma (KIRC) lacks sensitive early diagnostic markers and effective therapeutic guidance. Given the tight crosstalk between tumor metabolism and immunity, we investigated immunometabolism for biomarker discovery. Transcriptomes from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus were integrated. Immunometabolism-related genes were screened by weighted gene co-expression network analysis and differential expression, followed by three machine learning algorithms (least absolute shrinkage and selection operator, Support Vector Machine-Recursive Feature Elimination (SVM-RFE), and random forest) to select features and build a diagnostic model. Performance was validated in external cohorts. Multi-omics correlation, immune infiltration, drug-sensitivity, and survival analyses were conducted. Functional assays were performed in vitro and in vivo. Six biomarkers-ABCB1, Acyl-CoA Dehydrogenase Short/Branched Chain (ACADSB), PLA2G6, AKR1C3, PANK1, and Lactate Dehydrogenase B (LDHB)-were identified. The model showed strong discrimination (AUC 0.976 in TCGA; 0.902 in GSE126964; and 0.916 in GSE36895). The genes correlated with immune checkpoints, cytokine signaling, T-cell infiltration, and clinical parameters. Drug analyses suggested cisplatin and sunitinib downregulated oncogenic targets. Silencing ABCB1 or AKR1C3, or overexpressing LDHB, suppressed KIRC cell proliferation and migration in vitro; LDHB overexpression combined with sorafenib significantly reduced tumor growth in vivo. We propose a robust immunometabolism-based diagnostic model and six experimentally supported biomarkers for KIRC, providing mechanistic insight into tumor-immune interactions and potential avenues for personalized therapy.
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Decoding transcriptional identity in developing human sensory neurons and organoid modeling.
Dorsal root ganglia (DRGs) play a crucial role in processing sensory information, making it essential to understand their development. Here, we construct a single-cell spatiotemporal transcriptomic atlas of human embryonic DRG. This atlas reveals the diversity of cell types and highlights the extrinsic signaling cascades and intrinsic regulatory hierarchies that guide cell fate decisions, including neuronal/glial lineage restriction, sensory neuron differentiation and specification, and the formation of neuron-satellite glial cell (SGC) units. Additionally, we identify a human-enriched NTRK3+/DCC+ nociceptor subtype, which is involved in multimodal nociceptive processing. Mimicking the programmed activation of signaling pathways in vivo, we successfully establish functional human DRG organoids and underscore the critical roles of transcriptional regulators in the fate commitment of unspecialized sensory neurons (uSNs). Overall, our research elucidates the multilevel signaling pathways and transcription factor (TF) regulatory hierarchies that underpin the diversity of somatosensory neurons, emphasizing the phenotypic distinctions in human nociceptor subtypes.
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Machine Learning Identifies Key Gene Markers Related to Fetal Retina Development at Single-Cell Transcription Level.
PURPOSE: The retina is part of the central nervous system, and its function is vision. During the embryonic development of the fetus, it diversifies the seven major types of cells from a retinal progenitor cell. The purpose of this study is to investigate essential features that are necessary for the development of the fetal retina. METHODS: We generated a comprehensive single-cell transcriptional atlas of the human retina by leveraging datasets from the Chan Zuckerberg Initiative Single-Cell Biology collection of human fetal retinas. The eight critical types of retinal cells were investigated, including amacrine, bipolar, cone, horizontal, Müller glia, retinal ganglion, rod, and retinal progenitor cells. We evaluated a total of 36,503 gene features across three developmental stages (early, middle, and late) for each cell type. Using seven feature ranking algorithms and incremental feature selection method, we identified key gene features, constructed efficient classifiers and classification rules. RESULTS: For amacrine cells, RELN and DAB1 are critical; for bipolar cells, ANK3 and RIMS2; for cone cells, PDE6H and FRMPD2; for horizontal cells, NFIA; for Müller glial cells, WIF1 and TF; for retinal ganglion cells, IL1RAPL2 and PCP4; for rod cells, RIMS2 and NRG1; and for retinal progenitor cells, BTG1. These gene features bring into focus the pattern of gene regulation and developmental pathways of the retinal cells for deeper insights into retinal development. CONCLUSIONS: This study explored molecular features related to the development of the fetal retina and their potential roles in certain pathways, which may provide novel insights into retinal development and contribute to a better understanding of other retinal diseases.
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Changes in Nucleus Pulposus Cell Atlas and the Role of SPP1 During Intervertebral Disc Degeneration: Single-Cell Sequencing Analysis.
BACKGROUND: The nucleus pulposus (NP) plays a central role in the pathogenesis of intervertebral disc degeneration (IVDD); however, its internal cellular heterogeneity and molecular mechanisms have not yet been elucidated. METHODS: ScRNA-seq was used to evaluate the structure of the NP at different degenerative stages in the same individual with IVDD. Unsupervised clustering of cells based on gene expression profiles was performed using the Seurat package and passed to uniform manifold approximation and projection (UMAP) for cluster visualization. A rat disc degeneration model and an in vitro human NP cell degeneration model were established to validate the scRNA-seq identification results. RESULTS: Six NP subclusters and immune cells were identified and their distribution and functional differences between healthy and degenerative states were investigated. Immune cells were present only in degenerated NPs and may trigger NP degeneration. Cellular communication within the NP was altered by the intervention of immune cells. Secreted phosphorylated protein 1 (SPP1), secreted by immune cells, plays a major role and is a key molecule in NP degeneration. The results of in vivo animal experiments and in vitro cellular experiments showed that the expression of SPP1 was increased in degenerating NPs. High expression of SPP1 promoted NP degeneration, whereas inhibition of its expression attenuated degeneration. CONCLUSIONS: Cytoarchitectural changes in NP were revealed by scRNA-seq. SPP1 is involved in the pathogenesis of disc degeneration and may be a new target for intervention in IVDD.