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A single-cell atlas of bovine skeletal muscle reveals mechanisms regulating intramuscular adipogenesis and fibrogenesis.
BACKGROUND: Intramuscular fat (IMF) and intramuscular connective tissue (IMC) are often seen in human myopathies and are central to beef quality. The mechanisms regulating their accumulation remain poorly understood. Here, we explored the possibility of using beef cattle as a novel model for mechanistic studies of intramuscular adipogenesis and fibrogenesis. METHODS: Skeletal muscle single-cell RNAseq was performed on three cattle breeds, including Wagyu (high IMF), Brahman (abundant IMC but scarce IMF), and Wagyu/Brahman cross. Sophisticated bioinformatics analyses, including clustering analysis, gene set enrichment analyses, gene regulatory network construction, RNA velocity, pseudotime analysis, and cell-cell communication analysis, were performed to elucidate heterogeneities and differentiation processes of individual cell types and differences between cattle breeds. Experiments were conducted to validate the function and specificity of identified key regulatory and marker genes. Integrated analysis with multiple published human and non-human primate datasets was performed to identify common mechanisms. RESULTS: A total of 32 708 cells and 21 clusters were identified, including fibro/adipogenic progenitor (FAP) and other resident and infiltrating cell types. We identified an endomysial adipogenic FAP subpopulation enriched for COL4A1 and CFD (log2FC = 3.19 and 1.92, respectively; P < 0.0001) and a perimysial fibrogenic FAP subpopulation enriched for COL1A1 and POSTN (log2FC = 1.83 and 0.87, respectively; P < 0.0001), both of which were likely derived from an unspecified subpopulation. Further analysis revealed more progressed adipogenic programming of Wagyu FAPs and more advanced fibrogenic programming of Brahman FAPs. Mechanistically, NAB2 drives CFD expression, which in turn promotes adipogenesis. CFD expression in FAPs of young cattle before the onset of intramuscular adipogenesis was predictive of IMF contents in adulthood (R2 = 0.885, P < 0.01). Similar adipogenic and fibrogenic FAPs were identified in humans and monkeys. In aged humans with metabolic syndrome and progressed Duchenne muscular dystrophy (DMD) patients, increased CFD expression was observed (P < 0.05 and P < 0.0001, respectively), which was positively correlated with adipogenic marker expression, including ADIPOQ (R2 = 0.303, P < 0.01; and R2 = 0.348, P < 0.01, respectively). The specificity of Postn/POSTN as a fibrogenic FAP marker was validated using a lineage-tracing mouse line. POSTN expression was elevated in Brahman FAPs (P < 0.0001) and DMD patients (P < 0.01) but not in aged humans. Strong interactions between vascular cells and FAPs were also identified. CONCLUSIONS: Our study demonstrates the feasibility of beef cattle as a model for studying IMF and IMC. We illustrate the FAP programming during intramuscular adipogenesis and fibrogenesis and reveal the reliability of CFD as a predictor and biomarker of IMF accumulation in cattle and humans.
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Low level exposure to BDE-47 facilitates the development of prostate cancer through TOP2A/LDHA/lactylation positive feedback circuit.
2,2',4,4'-tetra brominated diphenyl ether (BDE-47) is one of the most widely distributed congeners of polybrominated diphenyl ethers. While the relationships between BDE-47 exposure and other hormone-dependent cancers (such as breast cancer) are well established, no previous study has examined whether BDE-47 exposure is related to the development of prostate cancer (PCa). Through bulk and single-cell RNA sequencing (scRNA-seq) analyses, as well as in vitro and in vivo experiments, this study aims to investigate the effect of BDE-47 exposure on PCa progression. Herein, we found that low dose BDE-47 promoted the growth of PCa cells (PC3 and LNCaP) in a dose-dependent manner in vitro and in vivo. Based on Comparative Toxicogenomics Database (CTD) and The Cancer Genome Atlas (TCGA), we obtained 34 BDE-47-related and PCa-related genes through screening and overlapping. These genes were significantly enriched in fatty acid metabolism-related gene ontology (GO) terms, which were also enriched for genes targeting BDE-47 obtained from the UniProt. Through scRNA-seq data, certain cell type-specific expression was observed for CYP2E1, PIK3R1, FGF2, and TOP2A in PCa tissues from men. Molecular docking simulation showed that BDE-47 was tightly bound to the protein residues of AOX1, PIK3R1, FGF2, CAV2, CYP2E1 and TOP2A. Further screening in terms of patient overall survival, receiver operating characteristics curve (ROC) curve and Gleason score grading system narrowed the candidate genes down to TOP2A. Mechanistically, the growth-promoting effect of BDE-47 on PCa cells could be reversed by TOP2A inhibitor. RNA-seq followed by experimental verification demonstrated that TOP2A promoted PCa progression through upregulating LDHA and glycolysis. Furthermore, lactate upregulated TOP2A transcription through lactylation of H3K18la in PCa cells, which could be rescued by LDHA knockdown. Taken together, low dose BDE-47 triggered PCa progression through TOP2A/LDHA/lactylation positive feedback circuit, thus revealing epigenetic shifting and metabolic reprogramming underpinning BDE-47-induced carcinogenesis of the prostate.
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A single-cell transcriptomic atlas characterizes ageing tissues in the mouse.
Ageing is characterized by a progressive loss of physiological integrity, leading to impaired function and increased vulnerability to death1. Despite rapid advances over recent years, many of the molecular and cellular processes that underlie the progressive loss of healthy physiology are poorly understood2. To gain a better insight into these processes, here we generate a single-cell transcriptomic atlas across the lifespan of Mus musculus that includes data from 23 tissues and organs. We found cell-specific changes occurring across multiple cell types and organs, as well as age-related changes in the cellular composition of different organs. Using single-cell transcriptomic data, we assessed cell-type-specific manifestations of different hallmarks of ageing-such as senescence3, genomic instability4 and changes in the immune system2. This transcriptomic atlas-which we denote Tabula Muris Senis, or 'Mouse Ageing Cell Atlas'-provides molecular information about how the most important hallmarks of ageing are reflected in a broad range of tissues and cell types.
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Anterior gradient-2 regulates cell communication by coordinating cytokine-chemokine signaling and immune infiltration in breast cancer.
Anterior gradient-2 (AGR2) is crucial to breast cancer progression. However, its role in the tumor immune microenvironment remains unclear. RNA sequencing expression profiles and associated clinical information were downloaded from The Cancer Genome Atlas and Gene Expression Omnibus databases, respectively. The AGR2 expression patterns were verified using clinical samples of breast cancer. Based on single-cell transcriptomic data, AGR2 expression patterns were identified and cell communication analysis was carried out. Furthermore, the roles of AGR2 in breast tumor progression were explored by a series of functional experiments. We found that DNA methylation was an important mechanism for regulating the expression patterns of AGR2. Patients with AGR2 low expression displayed an immune "hot" and immunosuppressive phenotype characterized by high abundance of tumor immune cell infiltration and increased enrichment scores for transforming growth factor-β (TGF-β) and epithelial-mesenchymal transition pathways, whereas patients with AGR2 high expression showed an opposite immunologic feature with a lack of immune cell infiltration, suggestive of an immune "cold" and desert phenotype. Moreover, single-cell analysis further revealed that AGR2 in malignant cells alters cell-cell interactions by coordinating cytokine-chemokine signaling and immune infiltration. Notably, two immunotherapy cohorts revealed that AGR2-coexpressed genes could serve as prognostic indicators of patient survival. In conclusion, AGR2 could promote breast cancer progression by affecting the tumor immune microenvironment. Patients with AGR2 low expression could be suitable for combination treatment with immune checkpoint inhibitor agents and TGF-β blockers. Therefore, this study provides a theoretical foundation for developing a strategy for personalized immunotherapy to patients with breast cancer.
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Roles of cathepsin S expression levels on the prognosis and tumour microenvironment in clear cell renal cell carcinoma.
BACKGROUND: Increasing evidence suggests a link between the enzyme cathepsin S (CTSS) and tumour development. However, the potential involvement and molecular functions of CTSS in clear cell renal cell carcinoma (ccRCC) remain unclear. METHODS: We downloaded original data from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases and integrated them using R. Kaplan-Meier plots of integrated expression scores were used to analyse survival outcomes. Additionally, we investigated mRNA expression, clinicopathological features, immune infiltrates, and single-cell sequencing analysis of CTSS in ccRCC. In vitro experiments were conducted with qRT-PCR and IHC staining. RESULTS: CTSS transcriptomic and proteomic levels were higher in ccRCC than in para-cancerous tissues. Low CTSS expression was correlated with poor prognosis in patients with ccRCC. Our data demonstrated that the expression of CTSS was strongly correlated with immune cell infiltration levels and gene markers of immune cells, chemokines, and receptors. Single-cell sequencing analysis demonstrated that CTSS expression was detectable in monocytes/macrophages. Finally, certain chemicals were confirmed to affect CTSS expression. CONCLUSION: Our findings indicate that CTSS offers promise as a prognostic biomarker and novel immune-related therapeutic target for ccRCC.
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Integrative Single-Cell Epigenomic Atlas Annotates the Regulatory Genome of the Adult Mouse Brain.
Histone modifications underpin the cell-type-specific gene regulatory networks that drive the remarkable cellular heterogeneity of the adult mammalian brain. Here, we profiled four histone modifications jointly with transcriptome in 2.5 million nuclei across multiple adult mouse brain regions. By integrating these data with existing maps of chromatin accessibility, DNA methylation, and 3D genome organization, we established a unified regulatory framework for over 100 brain cell subclasses. This integrative epigenomic atlas annotates 81% of the genome, defining distinct active, primed, and repressive states. Notably, active chromatin states marked by combinatorial histone modifications more precisely identify functional enhancers than chromatin accessibility alone, while Polycomb- and H3K9me3-mediated repression contributes prominently to cell-type-specific regulation. Finally, this multi-modal resource enables deep learning models to predict epigenomic features and gene expression from DNA sequences. This work provides a comprehensive annotation of the mouse brain regulatory genome and a framework for interpreting non-coding variation in complex tissues.
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Identification and validation of ZAP70 as a potential biomarker associated with T cell infiltration in lung adenocarcinoma.
BACKGROUND: Zeta-chain-associated protein kinase 70 kDa (ZAP70) is a tyrosine kinase essential for T cell activation and differentiation and it is predominantly expressed in T cells. However, its clinical relevance and relationship with the immune microenvironment in lung adenocarcinoma (LUAD) remain unclear. Therefore, this study aimed to investigate the expression profile of ZAP70 in LUAD, evaluate its prognostic significance, and explore its correlation with the tumor immune microenvironment. METHODS: Transcriptomic and clinical data for LUAD were obtained from The Cancer Genome Atlas (TCGA) and supplemented with Gene Expression Omnibus (GEO), Clinical Proteomic Tumor Analysis Consortium (CPTAC) data, and Human Protein Atlas (HPA) resources. The messenger RNA (mRNA) and protein levels of ZAP70 were further validated in seven paired LUAD and adjacent normal tissues. RESULTS: Pan-cancer analysis revealed heterogeneous ZAP70 expression, with significantly reduced mRNA and protein levels in lung cancer, including LUAD. In LUAD, low ZAP70 expression was associated with advanced T stage, stage IV disease, M1 metastasis, and inferior overall survival, first progression, and post-progression survival. The Tumor Immune Estimation Resource (TIMER) analysis showed that higher ZAP70 expression correlated with increased infiltration of multiple immune cell types. Single-cell transcriptomic profiling demonstrated that ZAP70 was predominantly expressed in T cells, with LUAD tissues displaying altered T cell subset composition and an increased proportion of ZAP70low T cells compared with normal lung. Functional enrichment indicated that ZAP70-related genes were involved in cell cycle and immune-related pathways. Consistently, quantitative real-time polymerase chain reaction (qRT-PCR) and Western blot assays confirmed reduced ZAP70 expression in LUAD tissues, particularly in patients with more advanced disease. CONCLUSIONS: These findings suggest that ZAP70 may serve as a potential biomarker and therapeutic target in LUAD, warranting further mechanistic and prospective clinical studies.
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Ancient ubiquitous protein 1 (AUP1) is a prognostic biomarker connected with TP53 mutation and the inflamed microenvironments in glioma.
INTRODUCTION: Glioblastoma (GBM) is the most common and lethal brain tumor. The current treatment is surgical removal combined with radiotherapy and chemotherapy, Temozolomide (TMZ). However, tumors tend to develop TMZ resistance which leads to therapeutic failure. Ancient ubiquitous protein 1 (AUP1) is a protein associated with lipid metabolism, which is widely expressed on the surface of ER and Lipid droplets, involved in the degradation of misfolded proteins through autophagy. It has recently been described as a prognostic marker in renal tumors. Here, we aim to use sophisticated bioinformatics and experimental validation to characterize the AUP1's role in glioma. MATERIAL AND METHODS: We collected the mRNA, proteomics, and Whole-Exon-Sequencing from The Cancer Genome Atlas (TCGA) for bioinformatics analyses. The analyses included the expression difference, Kaplan-Meier-survival, COX-survival, and correlation to the clinical factors (tumor mutation burden, microsatellite instability, and driven mutant genes). Next, we validated the AUP1 protein expression using immunohistochemical staining on the 78 clinical cases and correlated them with P53 and KI67. Then, we applied GSEA analyses to identify the altered signalings and set functional experiments (including Western Blot, qPCR, BrdU, migration, cell-cycle, and RNAseq) on cell lines when supplemented with small interfering RNA targeting the AUP1 gene (siAUP1) for further validation. We integrated the single-cell sequencing and CIBERSORT analyses at the Chinese Glioma Genome Atlas (CGGA) and Glioma Longitudinal AnalySiS (GLASS) dataset to rationale the role of AUP1 in glioma. RESULTS: Firstly, the AUP1 is a prognostic marker, increased in the tumor component, and correlated with tumor grade in both transcriptomes and protein levels. Secondly, we found higher AUP1 associated with TP53 status, Tumor mutation burden, and increased proliferation. In the function validation, downregulated AUP1 expression merely impacted the U87MG cells' proliferation instead of altering the lipophagy activity. From the single-cell sequencing and CIBERSORT analyses at CGGA and GLASS data, we understood the AUP1 expression was affected by the tumor proliferation, stromal, and inflammation compositions, particularly the myeloid and T cells. In the longitudinal data, the AUP1 significantly dropped in the recurrent IDH wildtype astrocytoma, which might result from increased AUP1-cold components, including oligodendrocytes, endothelial cells, and pericytes. CONCLUSION: According to the literature, AUP1 regulates lipophagy by stabilizing the ubiquitination of lipid droplets. However, we found no direct link between AUP1 suppression and altered autophagy activity in the functional validation. Instead, we noticed AUP1 expression associated with tumor proliferation and inflammatory status, contributed by myeloid cells and T cells. In addition, the TP53 mutations seem to play an important role here and initiate inflamed microenvironments. At the same time, EGFR amplification and Chromosome 7 gain combined 10 loss are associated with increased tumor growth related to AUP1 levels. This study taught us that AUP1 is a poorer predictive biomarker associated with tumor proliferation and could report inflamed status, potentially impacting the clinical application.
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Identification of NK cell marker genes based on single-cell sequencing to establish a prognostic signature in breast cancer.
BACKGROUND: Tumor-infiltrating natural killer (NK) cells are pivotal in modulating tumor progression, either by promoting or inhibiting neoplastic development. Nevertheless, the implications of NK cells in breast carcinoma remain inadequately understood. This investigation aimed to delineate the impact of NK cells on both the prognosis and the immune infiltration landscape in breast cancer. METHODS: NK cell marker genes were identified using single-cell sequencing data from breast cancer available in the Gene Expression Omnibus (GEO) database. A prognostic model was constructed based on data from The Cancer Genome Atlas (TCGA) and subsequently validated with the GEO dataset. Disparities in immune cell infiltration between low-risk and high-risk cohorts, as stratified by the prognostic model, were examined. Additionally, genes differentially expressed between these cohorts were subjected to enrichment analysis. RESULTS: A total of 29 NK cell marker genes were identified through single-cell sequencing, and a prognostic model was subsequently developed using machine learning techniques based on the TCGA data. This model demonstrated robust predictive performance when applied to both TCGA and GEO datasets. Notably, a significant difference in immune infiltration was observed between the low-risk and high-risk groups. The findings were further validated through enrichment analysis. CONCLUSIONS: In summary, we constructed a prognostic signature characterized by strong predictive performance, which has elucidated the critical role of NK cells in the pathogenesis of breast cancer. Furthermore, this model offers a predictive index and identifies a novel therapeutic target for the advancement of immunotherapeutic strategies in the clinical management of breast cancer patients.
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Immune gene patterns and characterization of the tumor immune microenvironment associated with cancer immunotherapy efficacy.
Although immunotherapy has revolutionized cancer management, most patients do not derive benefits from it. Aiming to explore an appropriate strategy for immunotherapy efficacy prediction, we collected 6251 patients' transcriptome data from multicohort population and analyzed the data using a machine learning algorithm. In this study, we found that patients from three immune gene clusters had different overall survival when treated with immunotherapy (P < 0.001), and that these clusters had differential states of hypoxia scores and metabolism functions. The immune gene score showed good immunotherapy efficacy prediction (AUC was 0.737 at 20 months), which was well validated. The immune gene score, tumor mutation burden, and long non-coding RNA score were further combined to build a tumor immune microenvironment signature, which correlated more strongly with overall survival (AUC, 0.814 at 20 months) than when using a single variable. Thus, we recommend using the characterization of the tumor immune microenvironment associated with immunotherapy efficacy via a multi-omics analysis of cancer.