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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.
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Single-cell RNA sequencing of OSCC primary tumors and lymph nodes reveals distinct origin and phenotype of fibroblasts.
Desmoplasia in fibroblasts within metastatic lymph nodes (MLNs) serves as an indicator of extranodal extension (ENE), which led mortality in oral squamous cell carcinoma (OSCC). However, systematic studies on fibroblasts in MLNs are lacking. Therefore, this study characterized the differences in phenotype, function, and origin of fibroblasts between primary tumors (PTs) and lymph nodes (LNs) in OSCC. We generated single-cell maps of PTs and paired MLNs and draining LNs from three OSCC patients. The transcriptomic atlas, pseudotime analysis, intercellular communication networks and enrichment analysis of the single cells were characterized. Phenotype and function heterogeneity of fibroblast cells between PTs and MLNs were further verified in vitro. Among 44,052 fibroblasts, we identified two distinct subpopulations of cancer-associated myofibroblastic cells (mCAFs): RGS4+ mCAF1 and COMP + mCAF2. Notably, they exhibited distinct distributions, with mCAF1 predominantly localized in the PTs and mCAF2 in the MLNs. Moreover, pseudotime analysis revealed their distinct origins: mCAF1 originated from inherent normal myofibroblastic cells in the PT, whereas mCAF2 originated from fibroblastic reticular cells in the LNs. Further functional experiments using primary fibroblasts revealed that, compared to mCAF1, mCAF2 in MLNs exhibited weaker crosstalk with immune cells but enhanced extracellular matrix activity, which is closely linked to ENE formation in OSCC. Additionally, we identified two fibroblast subgroups in a transforming state, indicating a potential epithelial-mesenchymal transition. Our research offers profound insights into the heterogeneity of fibroblasts between the PT and MLN in OSCC, serving as an essential resource for future drug discovery endeavors.
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Single-cell transcriptomic atlas of the human testis across the reproductive lifespan.
Testicular aging is associated with declining reproductive health, but the molecular mechanisms are unclear. Here we generate a dataset of 214,369 single-cell transcriptomes from testicular cells of 35 individuals aged 21-69, offering a resource for studying testicular aging and physiology. Machine learning analysis reveals a stronger aging response in somatic cells compared to germ cells. Two waves of aging-related changes are identified: the first in peritubular cells of donors in their 30s, marked by increased basement membrane thickness, indicating a priming state for aging. In their 50s, testicular cells exhibit functional changes, including altered steroid metabolism in Leydig cells and immune responses in macrophages. Further analyses reveal the impact of body mass index on spermatogenic capacity as age progresses, particularly after age 45. Altogether, our findings illuminate molecular alterations during testis aging and their relationship with body mass index, providing a foundation for future research and offering potential diagnostic markers and therapeutic targets.
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An Integrative Model of Cellular States, Plasticity, and Genetics for Glioblastoma.
Diverse genetic, epigenetic, and developmental programs drive glioblastoma, an incurable and poorly understood tumor, but their precise characterization remains challenging. Here, we use an integrative approach spanning single-cell RNA-sequencing of 28 tumors, bulk genetic and expression analysis of 401 specimens from the The Cancer Genome Atlas (TCGA), functional approaches, and single-cell lineage tracing to derive a unified model of cellular states and genetic diversity in glioblastoma. We find that malignant cells in glioblastoma exist in four main cellular states that recapitulate distinct neural cell types, are influenced by the tumor microenvironment, and exhibit plasticity. The relative frequency of cells in each state varies between glioblastoma samples and is influenced by copy number amplifications of the CDK4, EGFR, and PDGFRA loci and by mutations in the NF1 locus, which each favor a defined state. Our work provides a blueprint for glioblastoma, integrating the malignant cell programs, their plasticity, and their modulation by genetic drivers.
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Population-scale gene expression analysis reveals the contribution of expression diversity to the modern wheat improvement.
Gene expression diversity is crucial for crop breeding, yet population genomics has focused primarily on sequence polymorphisms. A single reference genome for RNA-seq cannot handle introgression bias. Here, we conduct RNA-seq for 328 wheat lines, including landraces and elite cultivars from China and the United States, to investigate the expression variation underlying agronomic traits. Leveraging pan-genome resources, we identify 23,296 more transcripts than using the Chinese Spring reference. We construct a pan-gene regulatory atlas through eQTL analysis, revealing the tight regulation of introgressed genes. We identify 299 high-confidence candidate genes for 34 agronomic traits and resistance to 8 Blumeria graminis f. sp. tritici isolates, more than one-fifth of which were absent from the Chinese Spring. Utilizing the Kenong 9204 mutant library, 73.7% of the candidates show significant phenotypic effects. Our work mitigates the reference bias and highlights the impact of breeding-driven directional expression changes on wheat adaptation and improvement.
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Novel macrophage-related gene prognostic index for glioblastoma associated with M2 macrophages and T cell dysfunction.
This study aims to construct a Macrophage-Related Gene Prognostic Index (MRGPI) for glioblastoma (GBM) and explore the underlying molecular, metabolic, and immunological features. Based on the GBM dataset from The Cancer Genome Atlas (n = 156), 13 macrophage-related hub genes were identified by weighted gene co-expression network (WGCNA) analysis. 5 prognostic genes screened by Kaplan-Meire (K-M) analysis and Cox regression model were used to construct the MRGPI, including GPR84, NCF2, HK3, LILRB2, and CCL18. Multivariate Cox regression analysis found that the MRGPI was an independent risk factor (HR = 2.81, CI95: 1.13-6.98, p = 0.026), leading to an unfavorable outcome for the MRGPI-high group, which was further validated by 4 validation GBM cohorts (n = 728). Thereafter, the molecular, metabolic, and immune features and the clinical implications of the MRGPI-based groups were comprehensively characterized. Gene set enrichment analysis (GSEA) found that immune-related pathways, including inflammatory and adaptive immune response, and activated eicosanoid metabolic pathways were enriched in the MRGPI-high group. Besides, genes constituting the MRGPI was primarily expressed by monocytes and macrophages at single-cell scope and was associated with the alternative activation of macrophages. Moreover, correlation analysis and receiver operating characteristic (ROC) curves revealed the relevance between the MRGPI with the expression of immune checkpoints and T cell dysfunction. Thus, the responsiveness of samples in the MRGPI-high group to immune checkpoint inhibitors (ICI) was detected by algorithms, including Tumor Immune Dysfunction and Exclusion (TIDE) and Submap. In contrast, the MRGPI-low group had favorable outcome, was less immune active and insensitive to ICI. Together, we have developed a promising biomarker to classify the prognosis, metabolic and immune features for GBM, and provide references for facilitating the personalized application of ICI in GBM.
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A single-cell atlas of the normal and malformed human brain vasculature.
Cerebrovascular diseases are a leading cause of death and neurologic disability. Further understanding of disease mechanisms and therapeutic strategies requires a deeper knowledge of cerebrovascular cells in humans. We profiled transcriptomes of 181,388 cells to define a cell atlas of the adult human cerebrovasculature, including endothelial cell molecular signatures with arteriovenous segmentation and expanded perivascular cell diversity. By leveraging this reference, we investigated cellular and molecular perturbations in brain arteriovenous malformations, which are a leading cause of stroke in young people, and identified pathologic endothelial transformations with abnormal vascular patterning and the ontology of vascularly derived inflammation. We illustrate the interplay between vascular and immune cells that contributes to brain hemorrhage and catalog opportunities for targeting angiogenic and inflammatory programs in vascular malformations.