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Found: 4 934
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TOMM5 is associated with oral cancer progression: a multi-omics analysis from single-cell atlas to in vitro validation.
AIMS: Translocase of Outer Mitochondrial Membrane 5 (TOMM5), a mitochondrial outer membrane translocase subunit implicated in tumorigenesis, remains unexplored in oral cancer. Herein, we aimed to decipher the role of TOMM5 in oral cancer. METHODS: This study comprehensively explored the expression profile, clinical significance, and functional roles of TOMM5 in oral carcinogenesis with global RNA-seq and microarray datasets. In vitro experiments were performed for evaluating the impact of TOMM5 knockdown on the biological functions of oral cancer cells. Distribution heterogeneity of TOMM5 expression and related cellular trajectory was analyzed through scRNA-seq. The therapeutic implications of TOMM5 for oral cancer were analyzed through drug sensitivity prediction and tumor immune dysfunction and exclusion (TIDE) scoring. RESULTS: TOMM5 was significantly overexpressed in oral cancer tissues and demonstrated moderate diagnostic accuracy. TOMM5 knockdown significantly suppressed aggressive biological behaviors of oral cancer cells. ScRNA-seq data revealed predominant TOMM5 expression in B cells, decreasing with differentiation, and linked distinct pathway activities to specific cellular compartments. High TOMM5 expression was linked to reduced immune cell infiltration and sensitivity to Paclitaxel/Vincristine. CONCLUSIONS: Overexpressed TOMM5 shows potential as a biomarker in oral cancer, correlating with tumor progression and immune infiltration.
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Single-nuclei RNA sequencing unveils astrocyte and oligodendrocyte lineage cells in post-stroke human brain.
BACKGROUND: Ischemic stroke (IS) induces profound, region-specific shifts in cellular composition and gene expression, particularly within glial populations such as astrocytes, oligodendrocytes, and oligodendrocyte precursor cells (OPCs). These glial responses are central to post-stroke neuroprotection, axonal stability, and myelin repair. METHODS: We performed single-nucleus RNA sequencing (snRNA-seq) on surgically obtained human cortical tissues: two IS cases (superficial frontotemporal peri-infarct cortex resected during decompressive craniectomy within ∼24 h of onset) and three comparator samples (cortical tissue from craniocerebral trauma surgery). Key glial transcriptional alterations were validated in a mouse photothrombotic middle cerebral artery occlusion (pMCAO) model using Western blot (WB), quantitative PCR (qPCR), and immunofluorescence. RESULTS: We analyzed 23,638 nuclei, resolving eight major cell types. IS samples showed relative increases in astrocytes and OPCs and decreases in mature oligodendrocytes, consistent with reactive gliosis and oligodendrocyte loss. Differential expression identified NMNAT2, HIF3A, NRP1, SEZ6L, and GPM6A as key upregulated genes enriched in astrocyte and oligodendrocyte lineage cells. Pseudotime analysis indicated a shift of OPCs toward earlier lineage states and trajectories consistent with remyelination after IS. Synaptic pathway enrichment with unchanged PSD95 and SYN levels suggests transcriptional glial-neuronal regulation rather than large-scale synaptic protein alteration. Validation by WB, qPCR, and IF confirmed the translational relevance of these findings across species. CONCLUSIONS: This study provides a peri-infarct human cortical snRNA-seq atlas after IS, revealing coordinated glial transcriptional responses that promote cellular adaptation and repair. The upregulation of NMNAT2, HIF3A, NRP1, SEZ6L, and GPM6A highlights potential therapeutic targets for enhancing neuroprotection and remyelination after stroke.
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Mapping the cellular biogeography of human bone marrow niches using single-cell transcriptomics and proteomic imaging.
Non-hematopoietic cells are essential contributors to hematopoiesis. However, heterogeneity and spatial organization of these cells in human bone marrow remain largely uncharacterized. We used single-cell RNA sequencing (scRNA-seq) to profile 29,325 non-hematopoietic cells and discovered nine transcriptionally distinct subtypes. We simultaneously profiled 53,417 hematopoietic cells and predicted their interactions with non-hematopoietic subsets. We employed co-detection by indexing (CODEX) to spatially profile over 1.2 million cells. We integrated scRNA-seq and CODEX data to link predicted cellular signaling with spatial proximity. Our analysis revealed a hyperoxygenated arterio-endosteal neighborhood for early myelopoiesis, and an adipocytic localization for early hematopoietic stem and progenitor cells (HSPCs). We used our CODEX atlas to annotate new images and uncovered mesenchymal stromal cell (MSC) expansion and spatial neighborhoods co-enriched for leukemic blasts and MSCs in acute myeloid leukemia (AML) patient samples. This spatially resolved, multiomic atlas of human bone marrow provides a reference for investigation of cellular interactions that drive hematopoiesis.
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Single-cell RNA sequencing of human liver reveals hepatic stellate cell heterogeneity.
BACKGROUND & AIMS: The multiple vital functions of the human liver are performed by highly specialised parenchymal and non-parenchymal cells organised in complex collaborative sinusoidal units. Although crucial for homeostasis, the cellular make-up of the human liver remains to be fully elucidated. Here, single-cell RNA-sequencing was used to unravel the heterogeneity of human liver cells, in particular of hepatocytes (HEPs) and hepatic stellate cells (HSCs). METHOD: The transcriptome of ~25,000 freshly isolated human liver cells was profiled using droplet-based RNA-sequencing. Recently published data sets and RNA in situ hybridisation were integrated to validate and locate newly identified cell populations. RESULTS: In total, 22 cell populations were annotated that reflected the heterogeneity of human parenchymal and non-parenchymal liver cells. More than 20,000 HEPs were ordered along the portocentral axis to confirm known, and reveal previously undescribed, zonated liver functions. The existence of 2 subpopulations of human HSCs with unique gene expression signatures and distinct intralobular localisation was revealed (i.e. portal and central vein-concentrated GPC3 + HSCs and perisinusoidally located DBH + HSCs). In particular, these data suggest that, although both subpopulations collaborate in the production and organisation of extracellular matrix, GPC3 + HSCs specifically express genes involved in the metabolism of glycosaminoglycans, whereas DBH + HSCs display a gene signature that is reminiscent of antigen-presenting cells. CONCLUSIONS: This study highlights metabolic zonation as a key determinant of HEP transcriptomic heterogeneity and, for the first time, outlines the existence of heterogeneous HSC subpopulations in the human liver. These findings call for further research on the functional implications of liver cell heterogeneity in health and disease. LAY SUMMARY: This study resolves the cellular landscape of the human liver in an unbiased manner and at high resolution to provide new insights into human liver cell biology. The results highlight the physiological heterogeneity of human hepatic stellate cells.
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Spatially resolved single-cell atlas of ascidian endostyle provides insight into the origin of vertebrate pharyngeal organs.
The pharyngeal endoderm, an innovation of deuterostome ancestors, contributes to pharyngeal development by influencing the patterning and differentiation of pharyngeal structures in vertebrates; however, the evolutionary origin of the pharyngeal organs in vertebrates is largely unknown. The endostyle, a distinct pharyngeal organ exclusively present in basal chordates, represents a good model for understanding pharyngeal organ origins. Using Stereo-seq and single-cell RNA sequencing, we constructed aspatially resolved single-cell atlas for the endostyle of the ascidian Styela clava. We determined the cell composition of the hemolymphoid region, which illuminates a mixed ancestral structure for the blood and lymphoid system. In addition, we discovered a cluster of hair cell-like cells in zone 3, which has transcriptomic similarity with the hair cells of the vertebrate acoustico-lateralis system. These findings reshape our understanding of the pharynx of the basal chordate and provide insights into the evolutionary origin of multiplexed pharyngeal organs.
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Single-cell spatial analysis stratifies lung adenocarcinoma with rare actionable mutations and reveals immune-modulatory cellular crosstalk.
Lung adenocarcinoma (LUAD) harboring distinct actionable oncogenic mutations exhibits differential responses to immune checkpoint inhibitors (ICI); however, the underlying mechanisms remain elusive. Here, we report comprehensive single-cell spatial atlases of tumors from 38 LUAD patients, predominantly harboring rare actionable oncogenes. Stratifying patients by consensus meta-programs (MP) reveals ICI-MP-H (high) and ICI-MP-L (low) subgroups. The ICI-MP-H group exhibits significant enrichment of the E3-IFI6 epithelial subpopulation, which displays high expression of interferon- and antigen presentation-related genes. Spatially, E3-IFI6 is adjacent to the Ma-MHC myeloid subpopulation; both co-enrich in a specific niche and likely interact via the APP-CD74 axis. Functional assays confirm that IFI6 overexpression in LUAD cell lines promotes proinflammatory macrophage activation. Our study systematically characterizes the features of the tumor ecosystem for different driver oncogene mutations, providing a theoretical basis for future clinical implementation of ICI therapy in patients with LUAD carrying rare mutations.
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Single-cell transcriptomics reveals tumor microenvironment changes and prognostic gene signatures in hepatocellular carcinoma.
BACKGROUND: Hepatocellular Carcinoma (HCC) is the most common type of primary liver cancer, accounting for the majority of liver cancer cases. Hepatocellular Carcinoma not only exhibits high heterogeneity but also possesses an immune-suppressive tumor microenvironment that promotes tumor evasion, posing substantial difficulties for efficient therapy. Our aim is to utilize single-cell RNA transcriptome data to investigate the dynamic changes in the tumor microenvironment during the malignant progression of HCC, the communication among immune cells, and the marker genes associated with patient prognosis. METHODS: We constructed expression matrices from open single-cell RNA transcriptome data (GSE149614) of HCC patients (representing stages I-IV), establishing single-cell RNA transcriptional atlases for different stages of HCC progression. For each stage, we conducted cell subgroup analysis to identify cell types at each stage. Horizontally, we explored the dynamic changes of the same cell type across different stages, performing trajectory analysis and prognosis analysis. Vertically, we investigated pairwise comparisons of different stages of HCC progression, probing the dynamic alterations in tumor microenvironment immune cell signaling pathways. Finally, potential drugs for the treatment of HCC were predicted based on relevant genes. FINDINGS: As the HCC advances towards increased malignancy, there is a shift in the predominant composition of the tumor microenvironment, with a decline in the dominance of hepatic cells. Tumor-infiltrating immune cells migrate and accumulate within the tumor microenvironment, where T cells and myeloid cells display distinct patterns of change. Genes associated with cancer-associated fibroblasts (CAFs) and T cells are correlated with adverse patient outcomes. In the late stages of HCC, the tumor microenvironment is infiltrated by more myeloid-derived suppressor cells (MDSCs), and a prognostic model constructed based on genes related to myeloid cells can predict patient outcomes. Additionally, in the analysis of transcription factors, YY1 and MYC are found to be highly expressed. Cell communication analysis among tumor-infiltrating immune cells reveals significant differences in the main signaling pathways at different stages of HCC progression. Finally, drug sensitivity analysis based on key genes identifies Acetalax, Allopurinol, and Amonafide as potential candidates for HCC treatment.
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Single-cell transcriptomic analysis of neuroepithelial cells and other cell types of the gills of zebrafish (Danio rerio) exposed to hypoxia.
The fish gill is a multifunctional organ involved in numerous physiological processes, such as gas exchange and sensing of hypoxia by respiratory chemoreceptors, called neuroepithelial cells (NECs). Many studies have focused on zebrafish (Danio rerio) to investigate the structure, function and development of the gills, yet the transcriptomic profile of most gill cells remains obscure. We present the results of a comprehensive transcriptomic analysis of the gills of zebrafish using single-cell RNA sequencing (scRNA-seq). Gill cells from ETvmat2:EGFP zebrafish were individually labelled before scRNA-seq library construction using 10× Genomics Chromium technology. 12,819 cells were sequenced with an average depth of over 27,000 reads per cell. We identified a median of 485 genes per cell and 16 cell clusters, including NECs, neurons, pavement cells, endothelial cells and mitochondrion-rich cells. The identity of NECs was confirmed by expression of slc18a2, encoding the vesicular monoamine transporter, Vmat2. Highly differentially-expressed genes in NECs included tph1a, encoding tryptophan hydroxylase, sv2 (synaptic vesicle protein), and proteins implicated in O2 sensing (ndufa4l2a, cox8al and epas1a). In addition, NECs and neurons expressed genes encoding transmembrane receptors for serotonergic, cholinergic or dopaminergic neurotransmission. Differential expression analysis showed a clear shift in the transcriptome of NECs following 14 days of acclimation to hypoxia. NECs in the hypoxia group showed high expression of genes involved in cell cycle control and proliferation. The present article provides a complete cell atlas for the zebrafish gill and serves as a platform for future studies investigating the molecular biology and physiology of this organ.
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Exploratory Single-Cell Analysis of NK-Annotated Cells Across Marrow Compartments in Prostate Cancer Bone Metastasis.
Prostate cancer preferentially colonizes bone, where marrow compartments differ in tissue structure and immune composition. We reanalyzed a 920,521-cell integrated prostate cancer atlas containing 38,842 NK-annotated cells from 126 sample identifiers, focusing on one bone-marrow cohort of 16 subjects and 32 samples. Distal marrow from patients with bone metastasis was compared with nonmalignant marrow from unrelated hip-replacement controls, while complete within-patient pairs were used for local comparisons. Sample- or subject-level composition, pseudobulk expression, pathway, and microenvironment analyses treated biological units, not cells, as replicates. The inherited CytokNKs_GZMH label was more frequent in distal marrow than in controls (25.4% versus 2.0%; centered log-ratio effect 2.82; false-discovery rate 0.0367). Paired tumor-versus-distal comparisons showed higher relative abundance of ImmSuppNKs_CREM and lower proportions of several other inherited labels at the 10% false-discovery threshold. A pooled comparison identified 62 differential genes within RegNKs_IL7R and generated a 24-gene exploratory program; distal-only models had no genes meeting the joint cutoff. Frequent T-cell- and myeloid-marker detection precluded assignment of this population as a validated NK subset. Program separation within the discovery cohort was subject to gene-selection bias and did not establish predictive performance. Full-atlas analyses described compartment-associated composition differences and candidate ligand-receptor expression pairs. Donor characteristics, treatment, sampling site, specimen processing, and annotation uncertainty remain unresolved sources of confounding. These findings are hypothesis-generating associations in recovered NK-annotated cells, not evidence of a metastasis-specific field effect, a regulatory NK population, or clinical utility.
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Differential cellular communication inference framework for large-scale single-cell RNA-sequencing data.
Single-cell transcriptomics data have been widely used to characterize biological systems, particularly in studying cell-cell communication, which plays a significant role in many biological processes. Despite the availability of various computational tools for inferring cellular communication, quantifying variations across different experimental conditions at both intercellular and intracellular levels remains challenging. Moreover, available methods are in general limited in terms of flexibility in analyzing different experimental designs and the ability to visualize results in an easily interpretable way. Here, we present a generalizable computational framework designed to infer and support differential cellular communication analysis across two experimental conditions from large-scale single-cell transcriptomics data. The scSeqCommDiff tool employs a statistical and network-based computational approach for characterizing altered cellular cross-talk in a fast and memory-efficient way. The framework is complemented with CClens, a user-friendly Shiny app to facilitate interactive analysis of inferred cell-cell communication. Validation through spatial transcriptomics data, comparison with other tools, and application to large-scale datasets (including a cell atlas) confirms the reliability, scalability, and efficiency of the framework. Moreover, the application to a single-nucleus transcriptomics dataset shows the validity and ability of the proposed workflow to support and unravel alterations in cell-cell interactions among patients with amyotrophic lateral sclerosis and healthy subjects.