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Machine learning and multi-omic empowered risk stratification and therapeutic framework targeting nucleotide metabolism and mast cell for stomach adenocarcinoma patients.
BACKGROUND: Mast cell and nucleotide metabolism(NM) encodes the Stomach adenocarcinoma (STAD) progression and tumor immune microenvironment(TME) heterogeneity. Research targeting deciphering NM-mast cell axis in STAD can pave the way for the deeper understanding of STAD pathogenesis. METHODS: STAD stomach tissue bulk profiles(GSE26899 and GSE10326) were utilized for identification of Mast cell and nucleotide metabolism(MNM)-associated shared differentially expressed genes(DEGs) via integrative bioinformatic analysis, including Limma, ssGSEA and WGCNA. Next, Lasso-cox regression was cross-employed for elaboration of predictive model and MNM-associated hub gene identification in TCGA-STAD and GSE84437 bulk profiles for STAD patients. Besides, deep learning algorithm(SOM) was utilized for risk stratification for STAD patients in TCGA-STAD dataset. Indeed, we also elucidated the molecular and immune heterogeneity of hub gene at bulk(TCGA-STAD cohort) and single-cell transcriptomic(GSE158937) levels of STAD patients, especially in virtual malignant cells at spatial and temporal manners. Besides, GSCA database with ridge regression were cross-performed for identification of optimal therapeutic framework for STAD patient treatment and then validated by molecular docking. Finally, in vitro study examined the relationship between hub gene and STAD cancer cell proliferation, growth and metastasis. RESULTS: MNM can guide the STAD patient prognostic forecasting and risk stratification. Particularly, UCK2 can be considered as MNM-associated hub gene involved in STAD pathogenesis proved by in silico and in vitro studies. Indeed, HG-5-113-01 should be considered as drug reproposing framework targeting UCK2 for the treatment of STAD. CONCLUSION: Our study first discovered the integration of MNM mechanisms and predictive roles for STAD patients by combining artificial intelligence(AI) and multi-omic studies.
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Spatial transcriptomics and single-nucleus RNA sequencing reveal a transcriptomic atlas of adult human spinal cord.
Despite the recognized importance of the spinal cord in sensory processing, motor behaviors, and neural diseases, the underlying organization of neuronal clusters and their spatial location remain elusive. Recently, several studies have attempted to define the neuronal types and functional heterogeneity in the spinal cord using single-cell or single-nucleus RNA sequencing in animal models or developing humans. However, molecular evidence of cellular heterogeneity in the adult human spinal cord is limited. Here, we classified spinal cord neurons into 21 subclusters and determined their distribution from nine human donors using single-nucleus RNA sequencing and spatial transcriptomics. Moreover, we compared the human findings with previously published single-nucleus data of the adult mouse spinal cord, which revealed an overall similarity in the neuronal composition of the spinal cord between the two species while simultaneously highlighting some degree of heterogeneity. Additionally, we examined the sex differences in the spinal neuronal subclusters. Several genes, such as SCN10A and HCN1, showed sex differences in motor neurons. Finally, we classified human dorsal root ganglia (DRG) neurons using spatial transcriptomics and explored the putative interactions between DRG and spinal cord neuronal subclusters. In summary, these results illustrate the complexity and diversity of spinal neurons in humans and provide an important resource for future research to explore the molecular mechanisms underlying spinal cord physiology and diseases.
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Using Gjd3-CreEGFP mice to examine atrioventricular node morphology and composition.
The atrioventricular node (AVN) coordinates the timing of atrial and ventricular contraction to optimize cardiac performance. To study this critical function using mouse genetics, however, new reagents are needed that allow AVN-specific manipulation. Here we describe a novel Gjd3-CreEGFP mouse line that successfully recombines floxed alleles within the AVN beginning at E12.5. These mice have been engineered to express CreEGFP under the control of endogenous Gjd3 regulatory elements without perturbing native protein expression. Detailed histological analysis of Gjd3-CreEGFP mice reveals specific labeling of AVN cardiomyocytes and a subset of cardiac endothelial cells. Importantly, we show that Gjd3-CreEGFP mice have preserved cardiac mechanical and electrical function. In one application of our newly described mouse line, we provide a three-dimensional (3D) view of the AVN using tissue clearing combined with confocal microscopy. With this 3D model as a reference, we identify specific AVN sub-structures based on marker staining characteristics. In addition, we use our Gjd3-CreEGFP mice to guide microdissection of the AVN and construction of a single-cell atlas. Thus, our results establish a new transgenic tool for AVN-specific recombination, provide an updated model of AVN morphology, and describe a roadmap for exploring AVN cellular heterogeneity.
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Immunological and pathological characteristics of brain parenchymal and leptomeningeal metastases from non-small cell lung cancer.
Brain parenchymal metastases (BM) and leptomeningeal metastases (LM) represent distinct subtypes of central nervous system metastases (CNSm) from lung cancer, posing significant clinical challenges. The local immune landscape of LM remains elusive. Herein, we utilized single-cell RNA sequencing to build a cell atlas of LM, and systematically examine the immune profiling and cell heterogeneity between BM and LM. Our analysis reveals that BM has more CXCL9+ macrophages, CXCL13+CD4+ T cells and B cells than LM, exhibiting the presence of tertiary lymphoid (TLS) structures, which is associated with a favorable response to tyrosine kinase inhibitors (TKI). Conversely, a remarkably immunosuppressive tumor microenvironment (TME) is detected in LM, characterized by lymphocyte depletion and a concurrent enrichment of SPP1+ macrophages, compared to BM. Furthermore, we identified significant blood-brain barrier (BBB) cell discrepancies between BM and LM, and substantial phenotypic reprogramming of BBB cells in CNSm. This reprogramming encompassed alterations in transporter gene expression, extracellular matrix production and dysregulated cell-cell interactions, potentially contributing to the metastatic process. In summary, this study highlights the divergent cellular and molecular landscapes of BM vs LM, offering critical insights into potential therapeutic targets and informing the development of improved treatment strategies for non-small cell lung cancer patients with CSNm.
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Spatial and cell type transcriptional landscape of human cerebellar development.
The human neonatal cerebellum is one-fourth of its adult size yet contains the blueprint required to integrate environmental cues with developing motor, cognitive and emotional skills into adulthood. Although mature cerebellar neuroanatomy is well studied, understanding of its developmental origins is limited. In this study, we systematically mapped the molecular, cellular and spatial composition of human fetal cerebellum by combining laser capture microscopy and SPLiT-seq single-nucleus transcriptomics. We profiled functionally distinct regions and gene expression dynamics within cell types and across development. The resulting cell atlas demonstrates that the molecular organization of the cerebellar anlage recapitulates cytoarchitecturally distinct regions and developmentally transient cell types that are distinct from the mouse cerebellum. By mapping genes dominant for pediatric and adult neurological disorders onto our dataset, we identify relevant cell types underlying disease mechanisms. These data provide a resource for probing the cellular basis of human cerebellar development and disease.
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Integrative bioinformatics and experimental validation of the prognostic and functional relevance of XDH and ITPA in non-small cell lung cancer.
Purine metabolism has been implicated in tumor biology and immune regulation, but the clinical and biological relevance of purine metabolism-related genes in non-small cell lung cancer (NSCLC) remains incompletely defined. Transcriptomic data from The Cancer Genome Atlas (TCGA) and the Genotype-Tissue Expression (GTEx) project, together with TCGA clinical data, were analyzed to identify differentially expressed purine metabolism-related genes and assess their prognostic associations. Immune infiltration was evaluated using single-sample gene set enrichment analysis (ssGSEA), and single-cell transcriptomic datasets were analyzed to characterize the cellular context of candidate genes. Stemness features and drug sensitivity were assessed using transcriptome-based computational models. XDH and ITPA protein expression was examined by Western blotting and immunohistochemistry (IHC) in an independent NSCLC cohort and in cell models. Stable knockdown of XDH or ITPA was performed in H1299 cells, with key functional findings further evaluated in A549 cells. Cisplatin sensitivity was assessed using cell-viability dose-response assays in H1299 and A549 cells. Several purine metabolism-related genes were upregulated in NSCLC and associated with overall survival (OS). XDH and ITPA showed higher protein expression in tumor tissues and were associated with adverse clinicopathological features and poorer survival. Higher expression of these genes was also associated with altered immune infiltration patterns. The messenger RNA-based stemness index (mRNAsi) was associated with ITPA and XDH expression in different directions, whereas higher XDH expression was associated with higher predicted half-maximal inhibitory concentration (IC50) values for cisplatin. Knockdown of XDH or ITPA attenuated proliferative, clonogenic, migratory, and invasive phenotypes in H1299 cells, with key findings reproduced in A549 cells. XDH knockdown also reduced the experimentally determined cisplatin IC50 in both H1299 and A549 cells. XDH and ITPA may represent candidate prognostic and functionally relevant purine metabolism-related genes in NSCLC. The integrated clinical, computational, and cellular findings support their association with NSCLC progression-related phenotypes, while the underlying molecular mechanisms and broader clinical applicability require further investigation.
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E2F1 Promotes the Occurrence of Head and Neck Squamous Cell Carcinoma and Serves as a Prognostic Biomarker.
Head and neck squamous cell carcinoma (HNSCC) is a common malignant tumor occurring in various sites such as the oral cavity, pharynx, larynx, and nasal cavity. This study aimed to explore the biological functions and prognostic value of E2F transcription factor 1 (E2F1) in HNSCC. Transcriptome and single-cell sequencing (scRNA-seq) data of HNSCC patients were analyzed using data from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO). All samples were divided into high and low expression groups based on the expression levels of E2F1. A risk model was constructed based on Lasso-Cox regression, and the differences between the two groups in terms of prognosis were explored. The scRNA-seq data of HNSCC samples were analyzed using the Seurat package to identify cell types. AUCell was used to score different types of cells, and subsequently, the interaction pathways between the high-scoring cell population and other cell populations were explored using the CellChat package. The expression level of E2F1 in tumor tissues was higher than that in normal tissues, which was confirmed by in vitro experiments. Analysis of transcriptome data from TCGA revealed significant differences in overall survival (OS) between the high and low expression groups. Prognostic genes were selected based on DEGs between the two groups, and a risk model was constructed. Subsequently, a nomogram model was constructed based on clinical factors and risk scores, which exhibited good predictive performance. The expression landscape of prognostic genes in different cell types was explored using scRNA-seq data of HNSCC samples. Dendritic cell populations were identified as high-scoring cell populations, and the pathways of interaction between this cell population and other cell populations were explored. We identified E2F1 as an independent prognostic factor closely associated with the prognosis and immune response of HNSCC.
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Cells of the adult human heart.
Cardiovascular disease is the leading cause of death worldwide. Advanced insights into disease mechanisms and therapeutic strategies require a deeper understanding of the molecular processes involved in the healthy heart. Knowledge of the full repertoire of cardiac cells and their gene expression profiles is a fundamental first step in this endeavour. Here, using state-of-the-art analyses of large-scale single-cell and single-nucleus transcriptomes, we characterize six anatomical adult heart regions. Our results highlight the cellular heterogeneity of cardiomyocytes, pericytes and fibroblasts, and reveal distinct atrial and ventricular subsets of cells with diverse developmental origins and specialized properties. We define the complexity of the cardiac vasculature and its changes along the arterio-venous axis. In the immune compartment, we identify cardiac-resident macrophages with inflammatory and protective transcriptional signatures. Furthermore, analyses of cell-to-cell interactions highlight different networks of macrophages, fibroblasts and cardiomyocytes between atria and ventricles that are distinct from those of skeletal muscle. Our human cardiac cell atlas improves our understanding of the human heart and provides a valuable reference for future studies.
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Tuberous sclerosis complex 2 deficiency in cardiomyocytes exacerbates cardiac remodeling in diabetic mice.
BACKGROUND: Based on gene expression profiles from the BioGPS database, Tuberous sclerosis complex 2 (Tsc2) exhibited the highest expression in mouse cardiac tissues. Herein, we investigated the potential functional role of Tsc2 in diabetic cardiomyopathy. METHODS AND RESULTS: Cardiac-specific Tsc2 deletion exacerbated myocardial fibrosis and cardiac dysfunction in streptozotocin-induced diabetic mice. Whole-transcriptomic analysis combined with single cell-sequencing analysis from the Human Protein Atlas database demonstrated that Tsc2 deletion enhanced Angiopoietin-like protein 7 (Angptl7) expression in cardiomyocytes under hyperglycemia. Recombinant adeno-associated virus serotype 9 carrying Angptl7 shRNA under cardiac troponin T promoter substantially reversed Tsc2 deletion-induced cardiac remodeling and dysfunction in diabetic mice. Mechanistically, the study demonstrated that cardiomyocyte-released Angptl7 activated β-Catenin in fibroblasts and promoted cardiac fibrosis through a paracrine mechanism. Furthermore, chronic supplementation with leucine, an essential branched-chain amino acid, led to adverse cardiac remodeling and dysfunction through Angptl7 activation in diabetic mice. CONCLUSIONS: Our findings demonstrate that Tsc2 deficiency in cardiomyocytes disrupts cardiac homeostasis and contributes to the progression of diabetic cardiomyopathy. The results also suggest that targeting Angptl7 represents a potential therapeutic strategy for diabetic cardiomyopathy, particularly in patients with Tsc2 mutation.
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Integrated multi-omics analysis and functional validation reveal the role of TRIM2 as a potential novel biomarker in breast cancer.
BACKGROUND: Breast cancer (BRCA) remains a major global health challenge due to its high recurrence rates and resistance to therapy, underscoring the need for reliable biomarkers and novel therapeutic targets. Tripartite motif-containing protein 2 (TRIM2), an E3 ubiquitin ligase, has been implicated in tumorigenesis across multiple cancers, yet its role in BRCA remains poorly understood. METHODS: We integrated multi-omics datasets from TCGA, GEO, and METABRIC, and validated TRIM2 expression using proteomic data from the Proteomic Data Commons and Human Protein Atlas. Single-cell RNA sequencing was employed to characterize the transcriptional heterogeneity and cell–cell interaction patterns of TRIM2+ tumor cells. Ubiquitin-proteomic and proteomic profiling were conducted to identify TRIM2-regulated substrates. Drug sensitivity prediction and molecular docking were applied to assess TRIM2-related therapeutic responses, and in vitro experiments were performed to validate its biological functions. RESULTS: We found that TRIM2 is consistently downregulated in BRCA tissues at both transcriptomic and proteomic levels, with low expression significantly associated with advanced stage and poor overall survival. Clinically, elevated TRIM2 expression correlated with improved responsiveness to immunotherapy. Drug sensitivity and molecular docking analyses identified 64 TRIM2-sensitive compounds, including five with strong binding affinities, suggesting potential for targeted therapeutic development. Genomic alterations and promoter hypermethylation were identified as potential mechanisms driving TRIM2 dysregulation. Multi-layered functional enrichment analyses, including transcriptomic, proteinomic, and ubiquitin-proteomic profiling, suggested that TRIM2 regulates cancer- and immune-related pathways including TGF-β, Hippo, TNF, and IL-17 signaling pathways. Single-cell RNA sequencing further demonstrated that TRIM2+ and TRIM2− tumor cell subpopulations engage in distinct cell–cell interactions, highlighting TRIM2’s role in shaping tumor-immune communication. Functional assays confirmed that TRIM2 suppresses BRCA cell proliferation and anchorage-independent growth in vitro. Immune profiling revealed that high TRIM2 expression is associated with enhanced immune checkpoint activity, greater infiltration of antitumor immune cells, and increased immune recruitment scores. CONCLUSIONS: Collectively, our findings identify TRIM2 as a potential tumor suppressor and novel prognostic biomarker in BRCA, with potential utility for guiding personalized immunotherapy and targeted treatment strategies.