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Cellular and Molecular Architecture of Renin-Angiotensin System Signaling in the PVN Under Cardiometabolic Stress.
The hypothalamic paraventricular nucleus (PVN) integrates neuroendocrine and autonomic signals that regulate blood pressure and metabolism. Although the renin-angiotensin system (RAS) is implicated in neurogenic hypertension and obesity, cell-type-specific expression and regulation of its components within the PVN remain poorly understood. Here, we employed single-nucleus RNA sequencing (snRNA-seq) to profile the transcriptomic landscape of the PVN in male mice under baseline conditions and in models of DOCA-salt-induced hypertension and high-fat diet (HFD)-induced obesity. We identified major PVN cell types, including neurons, astrocytes, precursor oligodendrocytes, oligodendrocytes, microglia and endothelial cells, and further resolved eight transcriptionally distinct neuronal subtypes. Expression of RAS-related genes was highly cell-type specific: Agt (angiotensinogen) was enriched in astrocytes, whereas Ace (angiotensin-converting enzyme), Atp6ap2 (also known as the (pro)renin receptor [PRR]), Agtr1a (angiotensin II type 1a receptor, aka AT1aR), Lnpep (leucyl/cystinyl aminopeptidase, aka angiotensin 4 receptor [AT4R]), and the Mas1 proto-oncogene were predominantly expressed in neurons. DOCA-salt treatment increased the proportion of GABAergic and vasopressin neurons and enhanced neuronal Agt and Atp6ap2 expression, while reducing astrocytic Agt, suggesting activation of a vasoconstrictive RAS axis. HFD exposure increased excitatory and stress-responsive neuronal subtypes (glutamatergic, vasopressin, corticotropin-releasing hormone) and upregulated Atp6ap2, Agtr1b, Lnpep, and Mas1 in vasopressin neurons, while downregulating multiple RAS genes in GABAergic neurons. These findings reveal dynamic, cell-type-specific remodeling of RAS signaling in the PVN in response to hypertensive and metabolic stress, providing a transcriptomic atlas of RAS expression in the PVN and identifying potential cellular targets for therapeutic strategies addressing cardiometabolic disorders.
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High Expression Levels of SIGLEC9 Indicate Poor Outcomes of Glioma and Correlate With Immune Cell Infiltration.
OBJECTIVE: This study aimed to investigate the diagnostic value and underlying mechanisms of sialic acid-binding Ig-like lectin 9 (SIGLEC9) in gliomas. PATIENTS AND METHODS: The Cancer Genome Atlas (TCGA) and the Chinese Glioma Genome Atlas (CGGA) databases were used to analyze the association of SIGLEC9 expression levels with tumor stages and survival probability. Immunohistochemical staining of SIGLEC9 and survival analysis were performed in 177 glioma patients. Furthermore, related mechanisms were discovered about SIGLEC9 in glioma tumorigenesis, and we reveal how SIGLEC9 functions in macrophages through single-cell analysis. RESULTS: TCGA and CGGA databases indicated that patients with high SIGLEC9 expression manifested a significantly shorter survival probability than those with low SIGLEC9 expression. SIGLEC9 was upregulated significantly in malignant pathological types, such as grade III, grade IV, mesenchymal subtype, and isocitrate dehydrogenase wild-type gliomas. The immunohistochemical staining of tissue sections from 177 glioma patients showed that high-SIGLEC9-expression patients manifested a significantly shorter survival probability than low-SIGLEC9-expression patients with age ≧60 years, grade IV, glioblastoma multiforme, alpha thalassemia/intellectual disability syndrome X-linked loss, and without radiotherapy or chemotherapy. Furthermore, the SIGLEC9 expression level was positively correlated with myeloid-derived suppressor cell infiltration and neutrophil activation. The SIGLEC9 expression was also positively correlated with major immune checkpoints, such as LAIR1, HAVCR2, CD86, and LGALS9. Through single-cell analysis, we found that the SIGLEC9 gene is related to the ability of macrophages to process antigens and the proliferation of macrophages. CONCLUSION: These findings suggested that SIGLEC9 is a diagnostic marker of poor outcomes in glioma and might serve as a potential immunotherapy target for glioma patients in the future.
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Cellular heterogeneity landscape in laryngeal squamous cell carcinoma.
Laryngeal squamous cell carcinoma (LSCC) is a highly malignant tumor originated from respiratory system. Although there have been many improvements in therapy until now, reducing the high mortality remains difficult. Understanding the cellular heterogeneity of LSCC could contribute to improve this problem. Single-cell RNA sequencing was applied to dissect the cell composition and molecular characteristics of LSCC tissues. Immunohistochemistry staining of the LSCC tissues was performed to identify the spatial location of tumor cells. Survival analysis of marker genes was executed in The Cancer Genome Atlas to verify the correlation between each cell clusters and patients' prognosis. The LSCC tissue cells were finely grouped into various clusters, including tumor cells, immune cells, epithelial cells, fibroblasts and endothelial cells. Notably, in tumor cells, keratinocyte-like cells were in the core of tumor while malignant proliferating cells were located at the tumor edge. The malignant proliferating cells were correlated with poor prognosis. In summary, this is the first study to delineate a landscape of the LSCC intratumor heterogeneity. Our work might help researchers have a better understanding for tumor progression.
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Crystal structure and immune single-cell atlas provide insights into the functional divergence of type I IFNs in fish.
Type I interferons (IFNs) are central antiviral cytokines in vertebrates, yet the mechanisms underlying their functional diversification in early vertebrates remain unclear. Teleost fish, whose IFN repertoires expanded through whole-genome duplication, provide a powerful model to address this question. Here, we systematically characterize grass carp (Ctenopharyngodon idella) IFNd to elucidate the mechanisms underlying its functional divergence from IFNa. IFNd used the same receptors of IFNa to activate JAK-STAT pathway, albeit with significantly lower antiviral potency than IFNa. Structural analysis revealed significant differences in F helix length and key receptor-binding residues between IFNa and IFNd. Furthermore, single-cell RNA sequencing demonstrated high heterogeneity among immune cell subpopulations responding to IFNa and IFNd, Notably, the signaling pathways enriched by differentially expressed genes in monocytes and macrophages were distinct for the 2 cytokines. Together, our findings link ligand structural conformation and receptor-binding composition to IFN signaling strength and immune cell specificity, providing mechanistic insight into the functional diversification of type I IFNs in lower vertebrates.
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Association of glioma CD44 expression with glial dynamics in the tumour microenvironment and patient prognosis.
Because of the heterogeneity of lower-grade gliomas (LGGs), patients show various survival outcomes that are not reliably predicted by histological classification. The tumour microenvironment (TME) contributes to the initiation and progression of brain LGGs. Identifying potential prognostic markers based on the immune and stromal components in the TME will provide new insights into the dynamic modulation of these two components of the TME in LGGs. We applied ESTIMATE to calculate the ratio of immune and stromal components from The Cancer Genome Atlas database. After combined differential gene expression analysis, protein-protein interaction network construction and survival analysis, CD44 was screened as an independent prognostic factor and subsequently validated utilizing data from the Chinese Glioma Genome Atlas database. To decipher the association of glioma cell CD44 expression with stromal cells in the TME and tumour progression, RT-qPCR, cell viability and wound healing assays were employed to determine whether astrocytes enhance glioma cell viability and migration by upregulating CD44 expression. Surprisingly, M1 macrophages were identified as positively correlated with CD44 expression by CIBERSORT analysis. CD44+ glioma cells were further suggested to interact with microglia-derived macrophages (M1 phenotype) via osteopontin signalling on the basis of single-cell sequencing data. Overall, we found that astrocytes could elevate the CD44 expression level of glioma cells, enhancing the recruitment of M1 macrophages that may promote glioma stemness via osteopontin-CD44 signalling. Thus, glioma CD44 expression might coordinate with glial activities in the TME and serve as a potential therapeutic target and prognostic marker for LGGs.
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[A novel glycolysis-related prognostic risk model for colorectal cancer patients based on single-cell and bulk transcriptomic data].
Objective To explore the prognostic value of glycolysis-related genes in colorectal cancer (CRC) patients and formulate a novel glycolysis-related prognostic risk model. Methods Single-cell and bulk transcriptomic data of CRC patients, along with clinical information, were obtained from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases. Glycolysis scores for each sample were calculated using single-sample Gene Set Enrichment Analysis (ssGSEA). Kaplan-Meier survival curves were generated to analyze the relationship between glycolysis scores and overall survival. Novel glycolysis-related subgroups were defined among the cell type with the highest glycolysis scores. Gene enrichment analysis, metabolic activity assessment, and univariate Cox regression were performed to explore the biological functions and prognostic impact of these subgroups. A prognostic risk model was built and validated based on genes significantly affecting the prognosis. Gene Set Enrichment Analysis (GSEA) was conducted to explore differences in biological processes between high- and low-risk groups. Differences in immune microenvironment and drug sensitivity between these groups were assessed using R packages. Potential targeted agents for prognostic risk genes were predicted using the Enrichr database. Results Tumor tissues showed significantly higher glycolysis scores than normal tissues, which was associated with a poor prognosis in CRC patients. The highest glycolysis score was observed in epithelial cells, within which we defined eight novel glycolysis-related cell subpopulations. Specifically, the P4HA1+ epithelial cell subpopulation was associated with a poor prognosis. Based on signature genes of this subpopulation, a six-gene prognostic risk model was formulated. GSEA revealed significant biological differences between high- and low-risk groups. Immune microenvironment analysis demonstrated that the high-risk group had increased infiltration of macrophages and tumor-associated fibroblasts, along with evident immune exclusion and suppression, while the low-risk group exhibited higher levels of B cell and T cell infiltration. Drug sensitivity analysis indicated that high-risk patients were more sensitive to Abiraterone, while low-risk patients responded to Cisplatin. Additionally, Valproic acid was predicted as a potential targeted agent. Conclusion High glycolytic activity is associated with a poor prognosis in CRC patients. The novel glycolysis-related prognostic risk model formulated in this study offers significant potential for enhancing the diagnosis and treatment of CRC.
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Spatiotemporal transcriptomic characteristics of immune and metabolic dysregulation during mouse brain aging.
BACKGROUND: Aging and its associated neurodegenerative diseases were increasingly recognized as one of the greatest global health threats. Brain aging involved a multitude of pathological changes, including immune inflammation and metabolic dysregulation. METHODS: We systematically characterized spatiotemporal heterogeneity and dynamic gene expression profiles related to immune and metabolic dysfunction during mouse brain aging. By analyzing differentially expressed genes and conducting functional enrichment and gene set enrichment analysis, we constructed a spatiotemporal transcriptomic atlas of aging-associated metabolic and immune features. We further performed transcription factor enrichment analysis, regulatory network construction, weighted gene co-expression network analysis, and single-cell deconvolution analysis to further reveal underlying mechanisms. RESULTS: Our results showed that, throughout aging, most brain regions underwent widespread immune-inflammatory activation with distinct timing and magnitude: svz exhibited the strongest activation at 26 months, th peaks at 21 months, while olf maintained low immune activation. In terms of metabolic function, different regions responded oppositely to oxidative stress and compensatory mechanisms: mPTP pathway's genes were significantly upregulated in th but downregulated in cor. Moreover, each brain region possessed its own unique regulatory network, and the H3K27-methyltransferase activity of the PRC2 complex displayed region-dependent age dynamics, suggesting these epigenetic differences (especially ent and olf) might serve as novel targets for anti-aging interventions. CONCLUSIONS: This work presented a high-resolution spatiotemporal transcriptomic atlas of mouse brain aging, revealed regionally staggered immune activation, contrasted metabolic adaptations, and illustrated PRC2-mediated epigenetic remodeling during brain aging. These insights advanced our understanding of brain aging mechanisms and identified region-specific therapeutic targets for precision interventions in neurodegenerative diseases.
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TE-SCALE: a comprehensive database for exploring transposable element expression across human cancers at single-cell resolution.
Transposable elements (TEs) are repetitive DNA sequences typically silenced in normal tissues. Their dysregulation in cancer can significantly impact oncogene activation and tumorigenesis. However, due to their repetitive nature, TEs are often excluded from gene-centric single-cell analyses. Although recent advances have enabled single-cell TE quantification, a systematic resource for exploring single-cell TE dynamics in cancer has remained lacking. To address this, we developed TE-SCALE (https://ngdc.cncb.ac.cn/te-scale/), a single-cell database for integrative analysis and visualization of TE expression across human cancers. It incorporates over 1.3 million cells from 330 samples across 20 cancer types and 12 tissue origins. Built on our in-house pipeline scTEfinder, TE-SCALE provides a comprehensive pan-cancer TE expression atlas, enabling multi-scale exploration from tissue to cell population, supported by well-curated TE annotations. The platform offers three key analytical modules: differential TE expression, TE-gene co-expression network, and functional enrichment analysis. A user-friendly web interface supports flexible browsing, searching, analysis, and data download. Notably, TE-SCALE identifies tumor-specific TEs preferentially expressed in particular cancer types or disease states, underscoring their potential as biomarkers for diagnosis, monitoring, and immunotherapeutic targeting. Collectively, TE-SCALE provides an essential resource for decoding TE biology in cancer and expedites its translation into clinical applications.
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Whole-Body Single-Cell Sequencing Reveals Transcriptional Domains in the Annelid Larval Body.
Animal bodies comprise diverse arrays of cells. To characterize cellular identities across an entire body, we have compared the transcriptomes of single cells randomly picked from dissociated whole larvae of the marine annelid Platynereis dumerilii. We identify five transcriptionally distinct groups of differentiated cells, each expressing a unique set of transcription factors and effector genes that implement cellular phenotypes. Spatial mapping of cells into a cellular expression atlas, and wholemount in situ hybridization of group-specific genes reveals spatially coherent transcriptional domains in the larval body, comprising, for example, apical sensory-neurosecretory cells versus neural/epidermal surface cells. These domains represent new, basic subdivisions of the annelid body based entirely on differential gene expression, and are composed of multiple, transcriptionally similar cell types. They do not represent clonal domains, as revealed by developmental lineage analysis. We propose that the transcriptional domains that subdivide the annelid larval body represent families of related cell types that have arisen by evolutionary diversification. Their possible evolutionary conservation makes them a promising tool for evo-devo research.
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A pan-cancer atlas of therapeutic T cell targets.
T-cell-based immunotherapies have revolutionized cancer treatment, yet only a minority of patients are eligible for these approaches, significantly constrained by the limited knowledge of tumor-specific antigens. Here we present ImmunoVerse, a comprehensive map of T cell targets across 21 cancer types, revealing actionable tumor-specific targets in 89% of tumors analyzed. To define the repertoire of actionable T cell targets, we conducted an exhaustive pan-cancer analysis, integrating data from 7,188 RNA-Seq, 1,771 immunopeptidomes from 512 biological samples and 208 single-cell cancer datasets using novel AI methods, and compared these against 17,384 normal samples covering 51 tissues. Our analysis uncovered 62 viable surface protein targets and 28,446 tumor-specific HLA-presented antigens, deriving from 11 distinct molecular events, across 21 tumor types. Among these, we identified 5,928 previously uncharacterized neoantigens, new tumor self-antigens, peptides derived from tumor-specific cryptic ORFs, tumor-associated microbial targets and a novel splicing-derived PMEL peptide (sPMEL) with enhanced abundance and safety compared to the canonical clinical targets. We successfully expanded sPMEL-specific T cells, validating the therapeutic potential of these targets in functional assays. We highlight 153 promising new tumor targets and experimentally validate 19 targets representing six antigen classes. In addition to being the most comprehensive atlas of targets in scope, ImmunoVerse offers the most extensively annotated resource with key parameters for target selection, providing critical insights for therapeutic prioritization and clinical translation. To catalyze therapeutic development, we released our pan-cancer target atlas through an interactive web portal (https://www.immuno-verse.com) and made the accompanying toolkits available to the scientific community. This work redefines the landscape of therapeutic T cell targets and provides a foundational resource to unlock immunotherapy development across multiple cancers previously considered intractable.