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Decoding the prognostic significance of integrator complex subunit 9 (INTS9) in glioma: links to TP53 mutations, E2F signaling, and inflammatory microenvironments.
INTRODUCTION: Gliomas, a type of brain neoplasm, are prevalent and often fatal. Molecular diagnostics have improved understanding, but treatment options are limited. This study investigates the role of INTS9 in processing small nuclear RNA (snRNA), which is crucial to generating mature messenger RNA (mRNA). We aim to employ advanced bioinformatics analyses with large-scale databases and conduct functional experiments to elucidate its potential role in glioma therapeutics. MATERIALS AND METHODS: We collected genomic, proteomic, and Whole-Exon-Sequencing data from The Cancer Genome Atlas (TCGA) and Chinese Glioma Genome Atlas (CGGA) for bioinformatic analyses. Then, we validated INTS9 protein expression through immunohistochemistry and assessed its correlation with P53 and KI67 protein expression. Gene Set Enrichment Analysis (GSEA) was performed to identify altered signaling pathways, and functional experiments were conducted on three cell lines treated with siINTS9. Then, we also investigate the impacts of tumor heterogeneity on INTS9 expression by integrating single-cell sequencing, 12-cell state prediction, and CIBERSORT analyses. Finally, we also observed longitudinal changes in INTS9 using the Glioma Longitudinal Analysis (GLASS) dataset. RESULTS: Our findings showed increased INTS9 levels in tumor tissue compared to non-neoplastic components, correlating with high tumor grading and proliferation index. TP53 mutation was the most notable factor associated with upregulated INTS9, along with other potential contributors, such as combined chromosome 7 gain/10 loss, TERT promoter mutation, and increased Tumor Mutational Burden (TMB). In GSEA analyses, we also linked INTS9 with enhanced cell proliferation and inflammation signaling. Downregulating INTS9 impacted cellular proliferation and cell cycle regulation during the function validation. In the context of the 12 cell states, INTS9 correlated with tumor-stem and tumor-proliferative-stem cells. CIBERSORT analyses revealed increased INTS9 associated with increased macrophage M0 and M2 but depletion of monocytes. Longitudinally, we also noticed that the INTS9 expression declined during recurrence in IDH wildtype. CONCLUSION: This study assessed the role of INTS9 protein in glioma development and its potential as a therapeutic target. Results indicated elevated INTS9 levels were linked to increased proliferation capacity, higher tumor grading, and poorer prognosis, potentially resulting from TP53 mutations. This research highlights the potential of INTS9 as a promising target for glioma treatment.
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Association of DNA damage repair related genes with prostate cancer: A multi-omics Mendelian Randomization analysis.
The relationship between prostate cancer and DNA damage repair remains incompletely elucidated. This study employs Mendelian Randomization to explore the causal relationships between DNA Damage Repair-related gene methylation, expression, and protein abundance and prostate cancer risk. A comprehensive analysis was conducted on 2736 DNA Damage Repair-related genes identified from the GeneCards database using Summary-data-based Mendelian Randomization. The study utilized quantitative trait loci datasets from multiple European cohorts, alongside Genome-Wide Association Studies data. Candidate gene expression patterns in prostate cancer tissue were further examined using the Human Protein Atlas and Tumor Immune Single-cell Hub 2 databases. Summary-data-based Mendelian Randomization analysis identified significant associations of genetically predicted RPA2 and POLI with prostate cancer risk. Immunohistochemical analyses from the human protein atlas database confirmed RPA2 and POLI expression in prostate cancer tissue, while single-cell sequencing data from the tumor immune single-cell hub 2 database indicated differential expression across distinct cellular subpopulations. Our study reveals a genetically inferred causal role for DDR-related genes RPA2 and POLI in prostate cancer risk. These findings may enhance the understanding of the molecular mechanisms linking DNA Damage Repair-related genes and prostate cancer.
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Single-cell transcriptomic data reveal the cellular heterogeneity of glutamine metabolism in gastric premalignant lesions and early gastric cancer.
Glutamine metabolism is a hallmark of cancer metabolism. This study aims to perform a comprehensive and systematic single-cell profile of glutamine metabolism in premalignant and malignant gastric lesions. We use single-cell transcriptomics data from chronic atrophic gastritis (CAG) and early gastric cancer (EGC) lesions and investigate glutamine metabolism features at the single-cell level. Experiments are implemented to validate the expression and biological role of ERO1LB in gastric cancer (GC). A single-cell atlas based on 22511 cells from premalignant and early-malignant gastric lesions is established. Among these cells, epithelial cells constitute the dominant cell population in both CAG and EGC lesions. The activity of glutamine metabolism is higher in epithelial cells from EGC lesions than in those from CAG lesions. Among the epithelial cell subpopulations, glutamine metabolism is more active in the epithelial cell subpopulation cluster_4 in EGCs than in CAG lesions. As a key marker gene of this subpopulation, ERO1LB is experimentally proven to be overexpressed in human GC tissue lesions. In both in vitro and in vivo experiments, overexpression of ERO1LB in GC cells increases glutamine metabolism, facilitates cell growth and migration and prevents cell apoptosis, and vice versa. This study provides insight into the cellular heterogeneityof glutamine metabolism within the gastric mucosa in premalignant and malignant gastric lesions and identifies ERO1LB as a key orchestrator of glutamine metabolism, which may help to identify markers for GC prevention and contribute to our understanding of GC pathogenesis.
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Renal enhanced CT images reveal the tandem mechanism between tumor cells and immunocytes based on bulk/single-cell RNA sequencing.
Metabolic reprogramming is essential for establishing the tumor microenvironment (TME). Glutamine has been implicated in cancer metabolism, but its role in clear cell renal carcinoma (ccRCC) remains unknown. Transcriptome data of patients with ccRCC and single-cell RNA sequencing (scRNA-seq) data were obtained from The Cancer Genome Atlas (TCGA, 539 ccRCC samples and 59 normal samples) database and GSE152938 (5 ccRCC samples). Differentially expressed genes related to glutamine metabolism (GRGs) were obtained from the MSigDB database. Consensus cluster analysis distinguished metabolism-related ccRCC subtypes. LASSO-Cox regression analysis was used to construct a metabolism-related prognostic model. The ssGSEA and ESTIMATE algorithms evaluated the level of immune cell infiltration in the TME, and the immunotherapy sensitivity score was obtained from TIDE. Cell-cell communication analysis was used to observe the distribution and effects of the target genes in the cell subsets. An image genomics model was constructed using imaging feature extraction and a machine learning algorithm. Results: Fourteen GRGs were identified. Overall survival and progression-free survival rates were lower in metabolic cluster 2, compared with those in cluster 1. The matrix/ESTIMATE/immune score in C1 decreased, but tumor purity in C2 increased. Immune cells were more active in the high-risk group, in which CD8 + T cells, follicular helper T cells, Th1 cells, and Th2 cells were significantly higher than those in the low-risk group. The expression levels of immune checkpoints were also significantly different between the two groups. RIMKL mainly appeared in epithelial cells in the single-cell analysis. ARHGAP11B was sparsely distributed. The imaging genomics model proved effective in aiding with clinical decisions. Glutamine metabolism plays a crucial role in the formation of immune TMEs in ccRCC. It is effective in differentiating the risk and predicting survival in patients with ccRCC. Imaging features can be used as new biomarkers for predicting ccRCC immunotherapy.
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Single-Cell Atlas of Human Ovaries Reveals The Role Of The Pyroptotic Macrophage in Ovarian Aging.
Female fecundity declines in a nonlinear manner with age during the reproductive years, even as ovulatory cycles continue, which reduces female fertility, disrupts metabolic homeostasis, and eventually induces various chronic diseases. Despite this, the aging-related cellular and molecular changes in human ovaries that occur during these reproductive years have not been elucidated. Here, single-cell RNA sequencing (scRNA-seq) of human ovaries is performed from different childbearing ages and reveals that the activation of the pyroptosis pathway increased with age, mainly in macrophages. The enrichment of pyroptotic macrophages leads to a switch from a tissue-resident macrophage (TRM)-involve immunoregulatory microenvironment in young ovaries to a pyroptotic monocyte-derived macrophage (MDM)-involved proinflammatory microenvironment in middle-aged ovaries. This remolded ovarian immuno-microenvironment further promotes stromal cell senescence and accelerated reproductive decline. This hypothesis is validated in a series of cell and animal experiments using GSDMD-KO mice. In conclusion, the work expands the current understanding of the ovarian aging process by illustrating a pyroptotic macrophage-involved immune mechanism, which has important implications for the development of novel strategies to delay senescence and promote reproductive health.
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UCP1 modulates immune infiltration level and survival outcome in ovarian cancer patients.
BACKGROUND: The uncoupling proteins (UCPs) are critical genes associated with tumorigenesis and chemoresistance. However, little is known about the molecular mechanism of the UCPs in ovarian cancer (OV). MATERIAL AND METHODS: UCPs expression analysis was conducted using Gene Expression Profiling Interactive Analysis (GEPIA), and its potential in clinical prognosis was analyzed using Kaplan- Meier analyses. The influence of UCPs on immune infiltration was analyzed by TIMER. In addition, the correlation between UCPs expression and molecular mechanisms was investigated by TIMER and Cancer Single-cell State Atlas (CancerSEA). RESULTS: UCP1, UCP2, UCP3 and UCP5 expression levels correlated with a favorable prognosis and tumor progression. Moreover, UCP1 expression correlated to several immune cell markers and regulated tumorigenesis, such as tumor invasion, EMT, metastasis and DNA repair. In addition, UCP1 potentially involved in genes expression of SNAI2, MMP2, BRCA1 and PARP1. CONCLUSIONS: These results implied a critical role of UCP1 in the prognosis and immune infiltration of ovarian cancer. In addition, UCP1 expression participated in regulating multiple oncogenes and tumorigenesis.
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Establishment and validation of a novel risk model based on CD8T cell marker genes to predict prognosis in thyroid cancer by integrated analysis of single-cell and bulk RNA-sequencing.
Papillary thyroid cancer (PTC) is a histological type of thyroid cancer, and CD8T is important for the immune response. The single-cell RNA data were acquired from Gene Expression Omnibus. SingleR package was used for cluster identification, and CellChat was exploited to evaluate the interaction among several cell types. Bulk RNA data obtained from the cancer genome atlas were used for determination of prognosis using Kaplan-Meier and Receiver Operating Characteristic curve. The Gene Ontology and Kyoto Encyclopedia of Genes and Genomes analysis were applied for assessment of function enrichment. The drug sensitivity was calculated in Gene Set Cancer Analysis. The regulatory network was constructed by STRING and Cytoscape. We identified 23 cell clusters and 10 cell types. Cell communication results showed CD8T cell was vital among all immune cell types. Enrichment analysis found the marker genes of CD8T cell was enriched in some signal pathways related to tumor development. Overall, FAM107B and TUBA4A were considered as hub genes and used to construct a risk model. Most immune checkpoint expressions were upregulated in tumor group. Tumor mutation burden results indicated that prognosis of PTC was not related to the mutation of hub genes. Drug sensitivity analysis showed some drugs could be effectively used for the treatment of PTC, and regulatory network identified some targets for the immunotherapy. A 2-gene model of PTC was developed based on the single-cell RNA and bulk RNA data. Besides, we found CD8T was essential for the immune response in PTC.
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Single-Nucleus RNA Sequencing Reveals Muscle Fiber Cell Heterogeneity During Human Skeletal Muscle Aging.
Aging impairs skeletal muscle mass and function, but the cell-type-resolved transcriptional states and intercellular signaling changes in human muscle aging remain incompletely mapped. Here, we constructed a single-nucleus RNA sequencing (snRNA-seq) atlas of human vastus lateralis muscle from adult (22-60 years) and elderly (99-101 years) male donors. We identified a comprehensive cellular census and discovered a profound reorganization of the myofiber transcriptional landscape. Aging was characterized by a shift from robust "young" states (MYLK4+ type II, LRP1B+ type I fibers) to dysfunctional "old" states (RYR3+ type II, RYR3+ type I fibers), accompanied by a marked emergence of hybrid fiber subtypes. We mechanistically linked these hybrid fibers to key aging pathologies: RUNX1+ hybrid fibers displayed a transcriptional signature of denervation, while SAA1+ hybrid fibers exhibited features of fatty infiltration, correlated with an expansion of fibro/adipogenic progenitors (FAPs). Pseudotime trajectory analysis supported the progression from young to degenerative or adipogenic fates. The aged microenvironment was globally altered, featuring impaired metabolic activity in muscle stem cells, compromised immune surveillance and function decline of vascular compartments. Critically, cell-cell communication analysis revealed enhanced BMP and Laminin signaling from FAPs to myofibers in aged tissue. Our work provided a high-resolution roadmap of human skeletal muscle aging, establishing denervation and FAP-driven fatty infiltration as key cellular mechanisms driving functional decline, and revealing novel targets for therapeutic intervention.
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Integrative cross-tissue and spatially resolved single-cell profiling uncovers tumour-educated inflammatory remodelling of tissue-resident macrophage ecosystem with immunotherapeutic prognostic significance in pan-cancer.
BACKGROUND: Tissue-resident macrophages (TRMs) exhibit dual roles in tumor progression, yet their functional reprogramming within the tumor microenvironment (TME) remains a critical unresolved question. METHODS: We integrated single-cell and spatial transcriptomics from a pan-cancer atlas of 1.39 million cells across five malignancies with 2,318 bulk RNA-seq samples to investigate macrophage states. A TRM inflammatory remodeling signature (TIR-Sig) was developed for clinical biomarker validation. RESULTS: We identified a conserved inflammatory TRM subtype (iTRM) characterized by CXCL8/IL1B/IL6 co-expression that correlates with poor clinical outcomes. Crucially, both TRMs and monocyte-derived tumor-associated macrophages (Mono-TAMs) underwent convergent differentiation into functionally similar inflammatory phenotypes, establishing iTRM as a universal tumor-educated state. Further integration analysis revealed an iTRM-enriched TME subtype which featured coordinated infiltration of neutrophils and cancer-associated fibroblasts (CAFs), forming a 'cold tumor' ecosystem associated with immune checkpoint blockade (ICB) resistance and poor prognosis. The derived TRM inflammatory remodeling signature (TIR-Sig) demonstrated dual clinical utility: it predicted patient survival (HR = 19.86, p < .001) and stratified ICB responders (AUC = .706). CONCLUSION: This study establishes phenotypic links between tissue-resident and recruited macrophages through inflammatory reprogramming within TME, provides a unifying framework for pan-cancer macrophage plasticity in TME, delivers a clinically actionable biomarker suite (TIR-Sig), and provides potential therapeutic targets for TME remodeling. KEY POINTS: Cross-tissue single-cell atlas of tissue-resident macrophages (TRMs). Identification of conserved inflammatory TRM phenotype (iTRM) in pan-cancer. Dynamic convergence of TRM and monocyte-derived macrophage lineages. TRM inflammatory remodelling signature (TIR-Sig) with clinical potential.
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Endometriosis-related alterations in the endometrium revealed by integrated single-cell and AI-powered approaches.
Endometriosis, affecting 1 in 9 women, presents treatment and diagnostic challenges. To address these issues, we generated a comprehensive single-cell atlas of endometrial tissue, comprising 466,371 cells from 35 endometriosis and 25 non-endometriosis donors without exogenous hormonal treatment. Detailed analysis reveals significant gene expression changes and altered receptor-ligand interactions present in the endometrium of endometriosis patients, including increased inflammation, adhesion, proliferation, cell survival, and angiogenesis in various cell types. These alterations may enhance endometriosis lesion formation and identify potential therapeutic targets. Using ScaiVision, we trained neural network models to predict endometriosis of varying disease severity (median AUC = 0.83), including one model based solely on a set of 11 genes confirmed as dysregulated in endometriosis patients through differential expression analysis. In conclusion, our findings reveal numerous pathway and ligand-receptor changes in the endometrium of endometriosis patients, offering insights into pathophysiology, potential targets for improved treatments, and predictive models for enhanced outcomes in endometriosis management. Our models, while not yet externally validated, can serve as a tool for hypothesis generation and starting point for further clinical development.