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Found: 4 939
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Decoding the hypoxic tumor microenvironment in colorectal cancer for prognostic modeling and therapeutic target discovery.
BACKGROUND: Hypoxia is a hallmark of the colorectal cancer (CRC) tumor microenvironment (TME) that drives malignant progression, chemoresistance, and immune evasion. However, the cellular heterogeneity underpinning hypoxic responses in CRC and its impact on prognosis remain incompletely understood. METHODS: We integrated single-cell RNA sequencing data from 15 CRC samples (GSE166555 and GSE221575) to delineate hypoxic and normoxic cell populations and identify hypoxia-related genes (HRGs). Weighted gene co-expression network analysis (WGCNA) and enrichment profiling elucidated key biological processes associated with hypoxia. Cell-cell communication networks were inferred using CellChat, and transcription factor regulatory modules were reconstructed via SCENIC and GRNBoost2. A hypoxia-based prognostic signature was developed from unique H3 cluster genes using univariate Cox and Lasso regression on The Cancer Genome Atlas (TCGA; n = 606) and validated in GSE39582 (n = 579). Drug sensitivity correlations were derived from the GDSCv2 database. Finally, in vitro assays assessed the functional role of GIPC2, a model gene, in CRC cell lines. RESULTS: Single-cell profiling uncovered eight distinct hypoxic clusters, with H3 exhibiting the highest hypoxia scores and enrichment in glycoprotein metabolic and angiogenesis pathways. The eight-gene prognostic model stratified patients into high- and low-risk groups with significantly different overall survival in both TCGA (P = 0.0026) and validation cohorts (P = 0.011). Drug analysis highlighted associations of model genes with PI3K/MTOR and apoptosis pathways. GIPC2 knockdown in LS180 and HT-29 cells markedly inhibited proliferation, migration, and invasion, while inducing apoptosis and reversing EMT phenotypes. CONCLUSIONS: We present a robust hypoxia-related gene signature that accurately predicts CRC patient prognosis and nominate GIPC2 as a potential biomarker and therapeutic target, offering new insights into hypoxia-driven CRC biology and personalized treatment strategies.
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Molecular and spatial signatures of human and rat corpus cavernosum physiopathological processes at single-cell resolution.
The composition and cellular heterogeneity of the corpus cavernosum (CC) microenvironment have been characterized, but the spatial heterogeneity at the molecular level remains unexplored. In this study, we integrate single-cell RNA sequencing (scRNA-seq) and spatial transcriptome sequencing to comprehensively chart the spatial cellular landscape of the human and rat CC under normal and disease conditions. We observe differences in the proportions of cell subtypes and marker genes between humans and rats. Based on the analysis of the fibroblast (FB) niche, we also find that the enrichment scores of mechanical force signaling vary across different regions and correlate with the spatial distribution of FB subtypes. In vitro, the soft and hard extracellular matrix (ECM) induces the differentiation of FBs into apolipoprotein (APO)+ FBs and cartilage oligomeric matrix protein (COMP)+ FBs, respectively. In summary, our study provides a cross-species and physiopathological transcriptomic atlas of the CC, contributing to a further understanding of the molecular anatomy and regulation of penile erection.
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Single-Cell Nuclear Sequencing Atlas Revealed the Induction of Parkinson's Disease by RELN+ Neuron 3 and the Gene Regulatory Network of MSRA.
AIMS: To determine the cell types that promoted the progression of Parkinson's disease (PD) using the substantia nigra in the brain tissues derived from patients with PD and normal controls. BACKGROUND: PD is an incurable neurodegenerative disease that threatens the physical activity of the aging population, and the complex molecular mechanisms remain be comprehensively elucidated. OBJECTIVE: To describe potential disease-promoting cell types in PD and to provide a theoretical basis. METHODS: Single-cell nuclear sequencing data of nine PD samples and control samples from Gene Expression Omnibus (GEO) were included, and heterogeneous cell subpopulations in the substantia nigra were identified by annotation analysis. Potential pathogenic cell subpopulations of PD were determined based on the expression data of marker genes. Cell differentiation trajectories and communication networks were generated by Pseudotime trajectory analysis and cell communication analysis. Furthermore, single- cell regulatory network inference and clustering (SCENIC) analysis was conducted to determine the regulatory network of transcription factor-target genes in PD. RESULTS: Among the nine cell subpopulations classified, RELN+neuron 3 showed reduced abundance and dopamine secretion capacity in PD and was therefore considered as a promoter of PD pathogenesis and progression. The regulatory network of MSRA action was involved in the developmental process of cells in the central nervous system, indicating that MSRA and its targets might serve as potential therapeutic targets for PD. RELN+neuron 3 had two directions of differentiation, specifically, branch 1 exhibited a high apoptotic profile and branch 2 exhibited a high cell death profile. In addition, the intensity of EPHA and EPHB signaling was attenuated between RELN+neuron 3 and other cell subpopulations. CONCLUSION: To conclude, this study identified a subpopulation of RELN+neuron 3 cells with markedly reduced abundance in the brain substantia nigra in PD. The MSRA-involved gene regulatory networks was considered as a novel therapeutic network for PD.
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Mesoscale molecular architecture of the human striatum across cell types and lifespan.
The human striatum is a central hub for a diverse array of motor, cognitive, and affective behaviors, yet it lacks obvious cytoarchitectural boundaries that define functional territories. Here, we uncover a robust and molecularly defined mesoscale architecture in the human striatum. Using Slide-tags, a scalable single-nucleus spatial transcriptomics technology, we profiled 1.1 million cells across the full span of the anterior striatum of 19 postmortem donors, spatially mapping all striatal populations. Our data uncover a natural subdivision of the striatum into six zones, each defined by molecularly distinct populations of medium spiny neurons, and featuring spatially coordinated neuron-astrocyte signaling. Relative to MSNs in ventral zones, MSNs in dorsal zones exhibit higher expression of genes for synaptic remodeling and plasticity via ephrin and TGF-beta, while the ventral zone is defined by greater expression of semaphorin, protein chaperone, and hedgehog signaling pathways. By imputing zonal identities onto a larger single-nucleus RNA-seq cohort of 131 donors, we find that the dorsal zones exhibit greater age-related transcriptional changes, and that overall, the gene-expression differences that define spatial zonation patterns are attenuated with advancing age. This atlas provides a mesoscale molecular definition of human striatal anatomy, linking cell type identity to functional specialization and aging susceptibility.
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Integrated multi-omics single cell atlas of the human retina.
Single-cell sequencing has revolutionized the scale and resolution of molecular profiling of tissues and organs. Here, we present an integrated multimodal reference atlas of the most accessible portion of the mammalian central nervous system, the retina. We compiled around 2.4 million cells from 55 donors, including 1.4 million unpublished data points, to create a comprehensive human retina cell atlas (HRCA) of transcriptome and chromatin accessibility, unveiling over 110 types. Engaging the retina community, we annotated each cluster, refined the Cell Ontology for the retina, identified distinct marker genes, and characterized cis-regulatory elements and gene regulatory networks (GRNs) for these cell types. Our analysis uncovered intriguing differences in transcriptome, chromatin, and GRNs across cell types. In addition, we modeled changes in gene expression and chromatin openness across gender and age. This integrated atlas also enabled the fine-mapping of GWAS and eQTL variants. Accessible through interactive browsers, this multimodal cross-donor and cross-lab HRCA, can facilitate a better understanding of retinal function and pathology.
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A distinct tumor microenvironment makes anaplastic thyroid cancer more lethal but immunotherapy sensitive than papillary thyroid cancer.
Both anaplastic thyroid cancer (ATC) and papillary thyroid cancer (PTC) originate from thyroid follicular epithelial cells, but ATC has a significantly worse prognosis and shows resistance to conventional therapies. However, clinical trials found that immunotherapy works better in ATC than late-stage PTC. Here, we used single-cell RNA sequencing (scRNA-Seq) to generate a single-cell atlas of thyroid cancer. Differences in ATC and PTC tumor microenvironment components (including malignant cells, stromal cells, and immune cells) leading to the polarized prognoses were identified. Intriguingly, we found that CXCL13+ T lymphocytes were enriched in ATC samples and might promote the development of early tertiary lymphoid structure (TLS). Last, murine experiments and scRNA-Seq analysis of a treated patient's tumor demonstrated that famitinib plus anti-PD-1 antibody could advance TLS in thyroid cancer. We displayed the cellular landscape of ATC and PTC, finding that CXCL13+ T cells and early TLS might make ATC more sensitive to immunotherapy.
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Atlas-Guided Discovery of Transcription Factors for T Cell Programming.
CD8+ T cells differentiate into diverse states that shape immune outcomes in cancer and chronic infection. To systematically define the transcription factors (TFs) driving these states, we built a comprehensive atlas integrating transcriptional and epigenetic data across nine CD8+ T cell states and inferred TF activity profiles. Our analysis catalogued TF activity fingerprints, uncovering regulatory mechanisms governing selective cell state differentiation. Leveraging this platform, we focused on two transcriptionally similar but functionally opposing states critical in tumor and viral contexts: terminally exhausted T cells (TEXterm), which are dysfunctional, and tissue-resident memory T cells (TRM), which are protective. Global TF community analysis revealed distinct biological pathways and TF-driven networks underlying protective versus dysfunctional states. Through in vivo CRISPR screening integrated with single-cell RNA sequencing (in vivo Perturb-seq), we delineated that TFs selectively govern TEXterm. We identified HIC1 and GFI1 as shared regulators of TEXterm and TRM differentiation and KLF6 as a unique regulator of TRM. Importantly, we discovered novel TEXterm single-state TFs, including ZSCAN20 and JDP2 with no prior known function in T cells. Targeted deletion of these TFs enhanced tumor control and synergized with immune checkpoint blockade. Consistently, their depletion in human T cells reduces the expression of inhibitory receptors and improves effector function. By decoupling exhaustion-selective from protective TRM programs, our platform enables more precise engineering of T cell states, advancing rational design of effective immunotherapies.
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The transcriptional regulation of SOX2 on FOXA1 gene and its application in diagnosis of human breast and lung cancers.
BACKGROUND: Recent study demonstrated the important contribution of SOX2 to tumorigenesis and metastasis properties of various types of cancers and strongly supported the concept that SOX2 can be used as an effective marker for diagnosis and predicting prognosis of cancer patients. However, our previous RNA-Seq results from human lung cancer cell line A549 showed that some oncogenes, including FOXA1 are negatively regulated by SOX2. METHODS: To further verify the transcriptional regulation effect of SOX2 on FOXA1 and elucidate its application in the diagnosis of human lung and breast cancer, we performed real-time RT-PCR and Western blotting to test the regulation effect of SOX2 on the expression of FOXA1 gene. OncoPrint analysis was used to reveal the alteration of SOX2 and FOXA1 genes in breast invasive carcinoma cases and lung squamous cell carcinoma cases from the Cancer Genome Atlas (TCGA) data portal. Immunohistochemistry staining was performed to test the expression of SOX2 and FOXA1 in human breast and lung carcinoma. RESULTS: The results showed that there is an inhibitory effect of SOX2 on the expression of FOXA1 gene. In addition, these two genes are altered in 5.8% of 484 breast invasive carcinoma cases and 46.4% of 179 lung squamous cell carcinoma cases from the Cancer Genome Atlas (TCGA) data portal, which showed an increased percentage of carcinoma cases when compared with single gene alteration. Immunohistochemistry staining of SOX2 and FOXA1 in human breast and lung carcinoma further revealed the mutual complementary effect of these two proteins in the diagnosis of carcinoma. CONCLUSIONS: Our study revealed SOX2 as a negative upstream regulator for FOXA1 gene and demonstrated SOX2 and FOXA1 as effective dual markers in improving the diagnosis efficiency for human lung and breast tumor.
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A spatiotemporal molecular atlas of mouse spinal cord injury identifies a distinct astrocyte subpopulation and therapeutic potential of IGFBP2.
Spinal cord injury (SCI) triggers a cascade of intricate molecular and cellular changes that determine the outcome. In this study, we resolve the spatiotemporal organization of the injured mouse spinal cord and quantitatively assess in situ cell-cell communication following SCI. By analyzing existing single-cell RNA sequencing datasets alongside our spatial data, we delineate a subpopulation of Igfbp2-expressing astrocytes that migrate from the white matter (WM) to gray matter (GM) and become reactive upon SCI, termed Astro-GMii. Further, Igfbp2 upregulation promotes astrocyte migration, proliferation, and reactivity, and the secreted IGFBP2 protein fosters neurite outgrowth. Finally, we show that IGFBP2 significantly reduces neuronal loss and remarkably improves the functional recovery in a mouse model of SCI in vivo. Together, this study not only provides a comprehensive molecular atlas of SCI but also exemplifies how this rich resource can be applied to endow cells and genes with functional insight and therapeutic potential.
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Itaconate-Related Gene Signatures as Prognostic Markers in Colon Cancer: Insights From Transcriptomic and Spatial Analysis.
Colon cancer is one of the most prevalent malignant tumors. Accurate evaluation of patient prognosis and optimization of treatment strategies continue to be major research focuses in colon cancer. Based on The Cancer Genome Atlas (TCGA) database, this study is the first to comprehensively analyze the expression, biological roles, and prognosis of itaconate and Hallmark pathway-related genes in colon cancer using bulk transcriptomics, single-cell transcriptomics, and spatial transcriptomics data. Through strict screening in 448 colon cancer patients from TCGA database (training set) and 7 colon cancer prognostic models from the Gene Expression Omnibus (GEO) database (including 1473 cases in the validation set), 10 prognosis-related genes (TIMP1, FJX1, CD36, CXCL1, ETS2, CDKN2A, INHBB, PLEC, TUBB2, and P4HA1) were selected. The optimal prognostic prediction model (Enet [alpha = 0.2]) was constructed and validated, which showed good prognostic predictive value in both the training and validation sets (average C-index > 0.7) and was superior to previous conventional clinical features and 22 prognostic models developed by researchers in the past 4 years. ScRNAseq (GSE225857) and spatial transcriptomics analyses clarified the cell-specific expression and spatial distribution characteristics of these genes in the tumor microenvironment (TME), with high functional scores mainly enriched in epithelial and stromal cells. Tissue microarray (TMA) showed that the high-risk group had higher tumor mutation burden (TMB) and higher expression of immune checkpoint genes, suggesting higher sensitivity to immunotherapy. Drug sensitivity analysis identified four potentially effective drugs, such as sepantronium bromide, which had better effects on high-risk patients. This study provides a theoretical basis and new targets for precise prognosis and stratified treatment of colon cancer.