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The combined prognostic model of copper-dependent to predict the prognosis of pancreatic cancer.
Purpose: To assess the prognostic value of copper-dependent genes, copper-dependent-related genes (CDRG), and CDRG-associated immune-infiltrating cells (CIC) for pancreatic cancer. Methods: CDRG were obtained by single-cell analysis of the GSE156405 dataset in the Gene Expression Omnibus (GEO) database. In a ratio of 7:3, we randomly divided the Cancer Genome Atlas (TCGA) cohort into a training cohort and a test cohort. Tumor samples from the GSE62452 dataset were used as the validation cohort. CIBERSORT was used to obtain the immune cell infiltration. We identified the prognostic CDRG and CIC by Cox regression and the least absolute selection operator (LASSO) method. The clinical significance of these prognostic models was assessed using survival analysis, immunological microenvironment analysis, and drug sensitivity analysis. Results: 536 CDRG were obtained by single-cell sequencing analysis. We discovered that elevated LIPT1 expression was associated with a worse prognosis in pancreatic cancer patients. EPS8, CASC8, TATDN1, NT5E, and LDHA comprised the CDRG-based prognostic model. High infiltration of Macrophages.M2 in pancreatic cancer patients results in poor survival. The combined prognostic model showed great predictive performance, with the area under the curve (AUC) values being basically between 0.7 and 0.9 in all three cohorts. Conclusion: We found a cohort of CDRG and CIC in patients with pancreatic cancer. The combined prognostic model provided new insights into the prognosis and treatment of pancreatic cancer.
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Multi-omics integrated analysis reveals the molecular mechanism of tail fat deposition differences in sheep with different tail types.
BACKGROUND: The accumulation of tail fat in sheep is a manifestation of adaptive evolution to the environment. Sheep with different tail types show significant differences in physiological functions and tail fat deposition. Although these differences reflect the developmental mechanism of tail fat under different gene regulation, the situation of sheep tail fat tissue at the single cell level has not been explored, and its molecular mechanism still needs to be further elucidated. RESULTS: Here, we characterized the genomic features of sheep with different tail types, detected the transcriptomic differences in tail adipose tissue between fat-tailed and thin-tailed sheep, established a single-cell atlas of sheep tail adipose tissue, and screened potential molecular markers (SESN1, RPRD1A and RASGEF1B) that regulate differences in sheep tail fat deposition through multi-omics integrated analysis. We found that the differential mechanism of sheep tail fat deposition not only involves adipocyte differentiation and proliferation, but is also closely related to cell-specific communication networks (When adipocytes act as signal outputters, LAMININ and other signal pathways are strongly expressed in guangling large tailed sheep and hu sheep), including interactions with immune cells and tissue remodeling to drive the typing of tail fat. In addition, we revealed the differentiation trajectory of sheep tail adipocytes through pseudo-time analysis and constructed the cell communication network of sheep tail adipose tissue. CONCLUSIONS: Our results provide insights into the molecular mechanisms of tail fat deposition in sheep with different tail types, and provide a deeper explanation for the development and functional regulation of adipocytes.
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Skeletal muscle regeneration failure in ischemic-damaged limbs is associated with pro-inflammatory macrophages and premature differentiation of satellite cells.
BACKGROUND: Chronic limb-threatening ischemia (CLTI), a severe manifestation of peripheral arterial disease (PAD), is associated with a 1-year limb amputation rate of approximately 15-20% and substantial mortality. A key feature of CLTI is the compromised regenerative ability of skeletal muscle; however, the mechanisms responsible for this impairment are not yet fully understood. In this study, we aim to delineate pathological changes at both the cellular and transcriptomic levels, as well as in cell-cell signaling pathways, associated with compromised muscle regeneration in limb ischemia in both human tissue samples and murine models of CLTI. METHODS: We performed single-cell transcriptome analysis of ischemic and non-ischemic muscle from the same CLTI patients and from a murine model of CLTI. In both datasets, we analyzed gene expression changes in macrophage and muscle satellite cell (MuSC) populations as well as differential cell-cell signaling interactions and differentiation trajectories. RESULTS: Single-cell transcriptomic profiling and immunofluorescence analysis of CLTI patient skeletal muscle demonstrated that ischemic-damaged tissue displays a pro-inflammatory macrophage signature. Comparable results were observed in a murine CLTI model. Moreover, integrated analyses of both human and murine datasets revealed premature differentiation of MuSCs to be a key feature of failed muscle regeneration in the ischemic limb. Furthermore, in silico inferences of intercellular communication and in vitro assays highlight the importance of macrophage-MuSC signaling in ischemia induced muscle injuries. CONCLUSIONS: Collectively, our research provides the first single-cell transcriptome atlases of skeletal muscle from CLTI patients and a murine CLTI model, emphasizing the crucial role of macrophages and inflammation in regulating muscle regeneration in CLTI through interactions with MuSCs.
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Construction and validation of immune-associated lncRNA model for predicting immune status and therapeutic reactions of triple-negative breast cancer.
OBJECTIVE: The immune status of the tumor microenvironment significantly impacts the clinical prognosis of triple-negative breast cancer (TNBC). The involvement of long noncoding RNAs (lncRNAs) in tumor immune infiltration is widely acknowledged. Therefore, it is crucial to explore the role of significant immune-related lncRNAs in TNBC. METHODS: We acquired RNA, single-cell sequencing, and clinical information on TNBC from The Cancer Genome Atlas (TCGA) and the Gene Expression Omnibus (GEO) databases. To identify immune-related lncRNAs, immune infiltration subgroups were determined and verified using single-sample gene-set enrichment analysis, non-negative matrix factorization, and weighted gene co-expression network analysis. CIBERSORTx, deconvolution, drug sensitivity, and Scissor analyses revealed that differences in cell type and drug efficacy were associated with immune grouping. RESULTS: TNBC samples were classified into immune-desert (cold) and immune-inflamed (hot) subgroups based on a lncRNA model (including LINC01550, LY86-AS1, LINC00494, LINC00877, CHRM3-AS2, HCP5, MIR155HG, and PIK3CD-AS1). Furthermore, using in vitro experiments, we found that LINC01550 promoted malignant phenotypes, including proliferation, survival, and migration of TNBC. The immune-inflamed subgroup exhibited significantly lower half-maximal inhibitory concentration values for common anti-tumor drugs, including palbociclib, ribociclib, mitoxantrone, and sorafenib (T-test, P < 0.001). This may be related to the fact that the immune-inflamed subgroup has more plasmacytoid dendritic cells (pDCs) and B cells than those in immune-desert subgroups (P < 0.001). CONCLUSIONS: Differences in specific cell infiltration can lead to increased sensitivity of the immune-inflamed subgroup to anti-tumor drugs. The proposed lncRNA model holds great promise to assess the immune landscapes and therapeutic reactions of TNBC patients.
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Uncovering the transcriptional hallmarks of endothelial cell aging via integrated single-cell analysis.
Endothelial cells (ECs) are critical regulators of vascular function and exhibit tissue-specialized roles. During aging, these cells become dysfunctional, resulting in increased susceptibility to cardiovascular disease. Although single-cell transcriptomics has revealed extensive endothelial heterogeneity, a comprehensive atlas of human EC transcriptomes over the course of the adult human lifespan has been lacking. Here, we present the Human Aging Endothelial Cell Atlas (HAECA), a harmonized single-cell transcriptomic compendium of over 375,000 ECs from 12 human tissues throughout adulthood. We identified age-associated transcriptional shifts, including a decline in angiogenic gene expression in venous ECs and widespread alterations in extracellular matrix and mechanotransduction-associated signatures. Furthermore, we uncovered a p21-linked transcriptional program in ECs, which we linked to cellular senescence in both in vitro and in vivo models. Together, our study provides a high-resolution transcriptomic reference of the human endothelium across tissues and age.
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Stemness signatures reflect prognostic disturbances in gastric cancer.
BACKGROUND: Tumors characterized by high cellular stemness often have unfavorable clinical outcomes, primarily due to their heightened potential for metastasis and resistance to chemotherapy. Among the model genes, the clinical relevance and prognostic significance of Niemann-Pick type C2 (NPC2) in gastric cancer (GC) remained largely unexplored. AIM: To identify stemness-associated genes in GC. METHODS: In this study, epithelial cells were categorized as either tumor or normal epithelial cells using the infer copy number variation method. Stemness scores were calculated for both cell types. The hierarchical Weighted Gene Co-expression Network Analysis identified two gene modules with the strongest association with stemness. Prognostically significant stemness-related genes were pinpointed using univariate Cox regression based on The Cancer Genome Atlas dataset. A predictive model related to stemness was constructed using Least Absolute Shrinkage and Selection Operator regression followed by multivariate Cox analysis. RESULTS: Functional roles of NPC2 were validated using single-cell and bulk RNA sequencing data. Further experimental validation revealed that elevated NPC2 expression promoted tumor cell stemness, invasiveness, migratory ability, and resistance to standard chemotherapeutic agents. Importantly, high NPC2 expression correlated with poorer overall survival in GC patients. CONCLUSION: In summary, the proposed model offers prognostic insights that outperform traditional clinical staging and may inform more tailored therapeutic approaches for gastric cancer management.
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Dysregulation of phosphoenolpyruvate carboxykinase in cancers: A comprehensive analysis.
BACKGROUND: Phosphoenolpyruvate carboxykinase (PEPCK) plays a crucial role in gluconeogenesis, glycolysis, and the tricarboxylic acid cycle by converting oxaloacetate into phosphoenolpyruvate. Two distinct isoforms of PEPCK, specifically cytosolic PCK1 and mitochondrial PCK2, have been identified. Nevertheless, the comprehensive understanding of their dysregulation in pan-cancer and their potential mechanism contributing to signaling transduction pathways remains elusive. METHODS: We conducted comprehensive analyses of PEPCK gene expression across 33 diverse cancer types using data from The Cancer Genome Atlas (TCGA). Multiple public databases such as HPA, TIMER 2.0, GEPIA2, cBioPortal, UALCAN, CancerSEA, and String were used to investigate protein levels, prognostic significance, clinical associations, genetic mutations, immune cell infiltration, single-cell sequencing, and functional enrichment analysis in patients with pan-cancer. PEPCK expression was analyzed about different clinical and genetic factors of patients using data from TCGA, GEO, and CGGA databases. Furthermore, the role of PCK2 in Glioma was examined using both in vitro and in vivo experiments. RESULTS: The analysis we conducted revealed that the expression of PEPCK is involved in both clinical outcomes and immune cell infiltration. Initially, we verified the high expression of PCK2 in GBM cells and its role in metabolic reprogramming and proliferation in GBM. CONCLUSION: Our study showed a correlation between PEPCK (PCK1 and PCK2) expression with clinical prognosis, gene mutation, and immune infiltrates. These findings identified two possible predictive biomarkers across different cancer types, as well as a comprehensive analysis of PCK2 expression in various tumors, with a focus on GBM.
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Indirubin and Retinoic Acid Show Binding Affinity to Monocyte Biomarker CSF3R in Parkinson's Disease.
BACKGROUND: This study integrated multi-omics data analysis to elucidate key molecular alterations associated with monocytes in Parkinson's disease (PD) so as to identify novel biomarkers. METHODS: Single-cell and chip datasets were derived from Gene Expression Omnibus (GEO) database. Single cell atlas of PD peripheral blood was delineated by Seurat package. CellChat was utilized for cell-cell communication analysis. Critical modules and Hub genes were screened by hdWGCNA. Differentially expressed genes (DEGs) between PD and control samples were recognized via Limma package, which were intersected with Hub genes to identify monocyte-related biomarkers. Functional enrichment analysis was conducted using GSEA_4.2.2 software. Targeted drugs of biomarkers were predicted to establish molecular docking models by AutoDocktools. RESULTS: The single-cell data revealed that 10 cell subpopulations were identified in PD peripheral blood, of which CD8 + T cell and monocyte were relatively abundant and exhibited close intercellular communication. Thereafter, hdWGCNA screened two critical modules (Monocyte-M2, Monocyte-M5) and 20 Hub genes. Two monocyte-related biomarkers (CSF3R, IFITM3) were identified in PD peripheral blood, which were mainly involved in the immuno-inflammatory and neuronal-relevant pathways. Molecular docking models displayed that CSF3R could stably bind to Indirubin and Retinoic acid. CONCLUSION: This study is the first to combine single-cell sequencing with hdWGCNA to identify two biomarkers closely associated with monocytes in peripheral blood from PD patients, while also predicting potential target drugs. These findings provide new evidence for elucidating the immunopathological mechanisms of PD and offer potential directions for future development of peripheral immune-based diagnostic strategies and targeted therapies.
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Immune infiltration and clinical significance analyses of the cancer-associated fibroblast-related signature in skin cutaneous melanoma.
BACKGROUND: Skin cutaneous melanoma (SKCM) is one of the most aggressive cancers with high mortality rates. Cancer-associated fibroblasts (CAFs) play essential roles in tumor growth, metastasis and the establishment of a pro-tumor microenvironment. This study aimed to establish a CAF-related signature for providing a new perspective for indicating prognosis and guiding therapeutic regimens of SKCM patients. METHODS: In this study, the CAF-related genes were screened out based on melanoma-associated fibroblast markers identified from single-cell transcriptome analysis in the Gene Expression Omnibus (GEO) database and a CAF-related module identified from weighted gene co-expression analysis using The Cancer Genome Atlas (TCGA) dataset. We extracted these gene expression data of SKCM samples from TCGA and constructed a prognostic CAF-related signature. The prediction abilities of the signature for survival prognosis, tumor immune landscape and responses to chemo-/immunotherapies were evaluated in the TCGA-SKCM cohort. RESULTS: We suggested that CAFs were significantly involved in the clinical outcomes of SKCM. A 10-gene CAF-related model was constructed, and the high-CAF risk group exhibited immunosuppressive features and worse prognosis. Patients with high CAF score were more likely to not respond to immune checkpoint inhibitors but were more sensitive to some chemotherapeutic agents, suggesting a potential approach of chemotherapy/anti-CAF combination treatment to improve the SKCM patient response rate of current immunotherapies. CONCLUSIONS: The CAF-related risk score could serve as a robust prognostic indicator and personal assessment of this score could uncover the degree of immunosuppression and provide treatment strategies to improve outcomes in clinical decision-making in SKCM patients.
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A comprehensive analysis of the role of QPRT in breast cancer.
To explore the clinical role of QPRT in breast cancer. The gene expression, methylation levels and prognostic value of QPRT in breast cancer was analyzed using TCGA data. Validation was performed using the data from GEO dataset and TNMPLOT database. Meta analysis method was used to pool the survival data for QPRT. The predictive values of QPRT for different drugs were retrieved from the ROC plot. The expression differences of QPRT in acquired drug-resistant and sensitive cell lines were analyzed using GEO datasets. GO and KEGG enrichment analysis were conducted for those genes which were highly co-expressed with QPRT in tissue based on TCGA data and which changed after QPRT knockdown. Timer2.0 was utilized to explore the correlation between QPRT and immune cells infiltration, and the Human Protein Atlas was used to analyse QPRT's single-cell sequencing data across different human tissues. The expression of QPRT in different types of macrophages, and the expression of QPRT were analysed after coculturing HER2+ breast cancer cells with macrophages. Additionally, TargetScan, Comparative Toxicogenomics and the connectivity map were used to research miRNAs and drugs that could regulate QPRT expression. Cytoscape was used to map the interaction networks between QPRT and other proteins. QPRT was highly expressed in breast cancer tissue and highly expressed in HER2+ breast cancer patients (P < 0.01). High QPRT expression levels were associated with worse OS, DMFS, and RFS (P < 0.01). Two sites (cg02640602 and cg06453916) were found to be potential regulators of breast cancer (P < 0.01). QPRT might predict survival benefits in breast cancer patients who received taxane or anthracycline. QPRT was associated with tumour immunity, especially in macrophages. QPRT may influence the occurrence and progression of breast cancer through the PI3K-AKT signalling pathway, Wnt signalling pathway, and cell cycle-related molecules.