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Pan-cancer analysis of UBE2T with a focus on prognostic and immunological roles in lung adenocarcinoma.
BACKGROUND: Ubiquitin-conjugating enzyme E2 T (UBE2T) is a potential oncogene. However, Pan-cancer analyses of the functional, prognostic and predictive implications of this gene are lacking. METHODS: We first analyzed UBE2T across 33 tumor types in The Cancer Genome Atlas (TCGA) project. We investigated the expression level of UBE2T and its effect on prognosis using the TCGA database. The correlation between UBE2T and cell cycle in pan-cancer was investigated using the single-cell sequencing data in Cancer Single-cell State Atlas (CancerSEA) database. The Weighted Gene Co-expression Network analysis (WGCNA), Univariate Cox and Least absolute shrinkage and selection operator (LASSO) Cox regression models, and receiver operating characteristic (ROC) were applied to assess the prognostic impact of UBE2T-related cell cycle genes (UrCCGs). Furthermore, the consensus clustering (CC) method was adopted to divide TCGA-lung adenocarcinoma (LUAD) patients into subgroups based on UrCCGs. Prognosis, molecular characteristics, and the immune panorama of subgroups were analyzed using Single-sample Gene Set Enrichment Analysis (ssGSEA). Results derived from TCGA-LUAD patients were validated in International Cancer Genome Consortium (ICGC)-LUAD data. RESULTS: UBE2T is highly expressed and is a prognostic risk factor in most tumors. CancerSEA database analysis revealed that UBE2T was positively associated with the cell cycle in various cancers(r > 0.60, p < 0.001). The risk signature of UrCCGs can reliably predict the prognosis of LUAD (AUC1 year = 0.720, AUC3 year = 0.700, AUC5 year = 0.630). The CC method classified the TCGA-LUAD cohort into 4 UrCCG subtypes (G1-G4). Kaplan-Meier survival analysis demonstrated that G2 and G4 subtypes had worse survival than G3 (Log-rank test PTCGA training set < 0.001, PICGC validation set < 0.001). A comprehensive analysis of immune infiltrates, immune checkpoints, and immunogenic cell death modulators unveiled different immune landscapes for the four subtypes. High immunophenoscore in G3 and G4 tumors suggested that these two subtypes were immunologically "hot," tending to respond to immunotherapy compared to G2 subtypes (p < 0.001). CONCLUSIONS: UBE2T is a critical oncogene in many cancers. Moreover, UrCCG classified the LUAD cohort into four subgroups with significantly different survival, molecular features, immune infiltrates, and immunotherapy responses. UBE2T may be a therapeutic target and predictor of prognosis and immunotherapy sensitivity.
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Single-cell and spatially resolved omics reveal transcriptional and metabolic signatures of ovarian endometriomas.
Endometriosis involves ectopic growth of endometrial-like tissue, yet the spatial transcriptomic and metabolic landscape of ovarian endometriomas remains poorly understood. This investigation presents a comprehensive multi-omics analysis of ovarian endometriomas incorporating single-cell RNA sequencing in conjunction with Digital Spatial Profiler-Whole Transcriptome Atlas for spatial transcriptomics, and non-targeted Matrix-Assisted Laser Desorption/Ionization-Mass Spectrometry Imaging for spatially resolved metabolomics. Our integrated analysis confirms the importance of cell adhesion, ECM-receptor interaction, and focal adhesion pathways in disease context. We identify XBP1, VCAN, and CLDN7 as key markers in epithelial cells, and THBS1 in perivascular cells. Spatially resolved metabolomics further reveals altered activity of cytochrome P450 enzymes, lipoprotein particles, and cholesterol metabolism in mesenchymal regions, along with several undefined metabolites enriched in epithelial areas of endometriomas compared to ovarian cortex controls. These findings reveal potential markers and metabolic pathways linked to ovarian endometriomas, offering a foundation for future diagnostic and therapeutic strategies.
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Single-cell analysis of human adipose tissue identifies depot and disease specific cell types.
The complex relationship between metabolic disease risk and body fat distribution in humans involves cellular characteristics which are specific to body fat compartments. Here we show depot-specific differences in the stromal vascual fraction of visceral and subcutaneous adipose tissue by performing single-cell RNA sequencing of tissue specimen from obese individuals. We characterize multiple immune cells, endothelial cells, fibroblasts, adipose and hematopoietic stem cell progenitors. Subpopulations of adipose-resident immune cells are metabolically active and associated with metabolic disease status and those include a population of potential dysfunctional CD8+ T cells expressing metallothioneins. We identify multiple types of adipocyte progenitors that are common across depots, including a subtype enriched in individuals with type 2 diabetes. Depot-specific analysis reveals a class of adipocyte progenitors unique to visceral adipose tissue, which shares common features with beige preadipocytes. Our human single-cell transcriptome atlas across fat depots provides a resource to dissect functional genomics of metabolic disease.
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An anoikis-related signature predicts prognosis and immunotherapy response in gastrointestinal cancers.
BACKGROUND: Gastrointestinal (GI) cancers have high incidence rates and mortality rates. Anoikis is a special type of cell apoptosis, and anoikis resistance has been reported to be associated with tumor malignancy. We aimed to explore the roles of anoikis-related genes (ARGs) in the GI cancer prognosis. METHODS: We extracted RNA sequencing and clinical data from The Cancer Genome Atlas and Gene Expression Omnibu databases for patients with esophageal cancer, gastric cancer, colon cancer and rectal cancer and identified ARGs from GeneCards and Harmonizome. Anoikis-related patterns were identified via unsupervised clustering analysis. We constructed a prognostic signature (Anoscore) based on prognostic ARGs through univariate, LASSO, and multivariate Cox regression analyses. The model was validated and evaluated using Kaplan-Meier analysis, receiver operating characteristic curves, univariate Cox regression analysis, multivariate Cox regression analysis, column charts, and calibration curves. We also performed a single-cell sequencing analysis of candidate genes via TISCH2. A correlation analysis between the Anoscore, the tumor microenvironment and drug sensitivity was conducted in GI cancers. The expression and function of some candidate genes were validated in vitro. RESULTS: In terms of prognostic ARGs, two anoikis-related patterns, ARG clusters A and B, were identified. ARG cluster B had a worse prognosis than did ARG cluster A. Subsequently, the Anoscore was developed as an independent prognostic factor. It demonstrated the robust predictive capability for the prognosis of patients with GI cancers. Notably, patients with high Anoscores exhibited poor outcomes. In addition, we established a nomogram (Ano-nomogram) based on the Anoscore and clinicopathological factors of patients to predict the 3-year and 5-year survival probabilities. Moreover, patients with high Anoscores had higher levels of immune cell infiltration and higher immune checkpoint expression. The drug sensitivity analysis revealed that patients with high or low Anoscores were sensitive to different chemotherapies and targeted drugs. S100A11 and TLR3, representative candidate genes, exhibited different expression patterns and biological functions. CONCLUSION: This study highlighted the significant potential of the Anoscore in predicting prognosis and guiding the selection of personalized therapeutic regimens for patients with GI cancers.
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Kurarinone regulates Th17/Treg balance and ameliorates autoimmune uveitis via Rac1 inhibition.
INTRODUCTION: Autoimmune uveitis (AU) is a severe intraocular autoimmune disorder with a chronic disease course and a high rate of blindness. Kurarinone (KU), a major component of the traditional Chinese medicine Sophorae Flavescentis Radix, possesses a wide spectrum of activities and has been used to treat several inflammation-related diseases. OBJECTIVE: We aimed to investigate the effects of KU on AU and its modulatory mechanisms. METHODS: We used an experimental autoimmune uveitis (EAU) animal model and characterized the comprehensive immune landscape of KU-treated EAU mice using single-cell RNA sequencing (scRNA-seq). The retina and lymph nodes were analyzed. The siRNAs and selective inhibitors were used to study the signaling pathway. The effect of KU on peripheral blood mononuclear cells (PBMCs) from uveitis patients was also examined. RESULTS: We found that KU relieved chorioretinal lesions and immune cell infiltration in EAU model mice. Subsequent single-cell analysis revealed that KU downregulated the EAU-upregulated expression of inflammatory and autoimmune-related genes and suppressed pathways associated with immune cell differentiation, activation, and migration in a cell-specific manner. KU was implicated in restoring T helper 17 (Th17)/regulatory T (Treg) cell balance by alleviating inflammatory injury and elevating the expression of modulatory mediators in Tregs, while simultaneously ameliorating excessive inflammation by Th17 cells. Furthermore, Rac1 and the Id2/Pim1 axis potentiated the pathogenicity of Th17 cells during EAU, which was inhibited by KU treatment, contributing to the amelioration of EAU-induced inflammation and treatment of AU. In addition, KU suppressed inflammatory cytokine production in activated human PBMCs by inhibiting Rac1. Integration of the glucocorticoid-treated transcriptome suggests that KU has immunomodulatory effects on lymphocytes. CONCLUSION: Our study constructed a high-resolution atlas of the immunoregulatory effects of KU treatment on EAU and identified its potential therapeutic mechanisms, which hold great promise in treating autoimmune disorders.
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Tumor-derived Parathyroid Hormone-Related Protein Is Associated with Suppression of Cytochrome P450 Expression: Evidence From Multimodal Transcriptomics.
Cancer cachexia is frequently associated with altered pharmacokinetics and increased chemotherapy toxicity due to the downregulation of cytochrome P450 (CYP) enzymes. However, the molecular mechanisms driving this broad metabolic suppression remain poorly understood. This study investigated whether tumor-derived parathyroid hormone-related protein (PTHrP) is associated with, and may contribute to, suppression of multiple CYP families. In a rat cachexia model, protein expression of CYP3A, CYP1A, CYP2C, CYP2D, and CYP2E1 was significantly downregulated in both the liver and small intestine. Consistent with these changes, pharmacokinetic analyses using a CYP substrate cocktail demonstrated markedly increased AUC and reduced clearance for probe drugs. In vitro experiments showed that PTHrP treatment reduced these CYP isoforms in primary rat hepatocytes. In human data sets, analysis of The Cancer Genome Atlas (TCGA) hepatocellular carcinoma (HCC) data set revealed a significant negative correlation between PTHrP and CYP gene expression, together with enrichment of NF-κB-related transcriptional programs. Furthermore, multimodal analysis using single-cell RNA sequencing and spatial transcriptomics demonstrated that PTHrP-high tumor regions exhibit suppressed xenobiotic metabolism. Additionally, in breast cancer liver metastases, high tumor PTHrP expression correlated with reduced CYP expression in surrounding nontumor hepatocytes, consistent with a possible paracrine relationship. Collectively, these results support an association between tumor-derived PTHrP and suppression of drug-metabolizing programs. They further suggest that PTHrP may be one contributing factor, but not definitive proof of a principal suppressor, and should therefore be considered a candidate biomarker requiring further mechanistic and clinical validation.
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SLC14A1 is a new biomarker in renal cancer.
BACKGROUND: Renal cancer is one of the common malignant tumors of the urinary tract, prone to distant metastasis and drug resistance, with a poor clinical prognosis. SLC14A1 belongs to the solute transporter family, which plays a role in urinary concentration and urea nitrogen recycling in the renal, and is closely associated with the development of a variety of tumors. METHODS: Transcription data for renal clear cell carcinoma (KIRC) were obtained from the public databases Gene Expression Omnibus database (GEO) and The Cancer Genome Atlas (TCGA), and we investigated the differences in SLC14A1 expression in cancerous and normal tissues of renal cancer, its correlation with the clinicopathological features of renal cancer patients. Then, we verified the expression levels of SLC14A1 in renal cancer tissues and their Paracancerous tissues using RT-PCR, Western-blotting and immunohistochemistry. Finally, we used renal endothelial cell line HEK-293 and renal cancer cell lines 786-O and ACHN to explore the effects of SLC14A1 on the biological behaviors of renal cancer cell proliferation, invasion and metastasis using EDU, MTT proliferation assay, Transwell invasion assay and scratch healing assay. RESULTS: SLC14A1 was lowly expressed in renal cancer tissues and this was further validated by RT-PCR, Western blotting, and immunohistochemistry in our clinical samples. Analysis of KIRC single-cell data suggested that SLC14A1 was mainly expressed in endothelial cells. Survival analysis showed that low levels of SLC14A1 expression were associated with a better clinical prognosis. In biological behavioral studies, we found that upregulation of SLC14A1 expression levels inhibited the proliferation, invasion, and metastatic ability of renal cancer cells. CONCLUSION: SLC14A1 plays an important role in the progression of renal cancer and has the potential to become a new biomarker for renal cancer.
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A novel enterocyte-related 4-gene signature for predicting prognosis in colon adenocarcinoma.
BACKGROUND: Colon adenocarcinoma (COAD) is a fatal disease, and its cases are constantly increasing worldwide. Further, the therapeutic and management strategies for patients with COAD are still unsatisfactory due to the lack of accurate patient classification and prognostic models. Therefore, our study aims to identify prognostic markers in patients with COAD and construct a cell subtype-specific prognostic model with high accuracy and robustness. METHODS: Single-cell transcriptomic data of six samples were retrieved from the Gene expression omnibus (GEO) database. The cluster annotation and cell-cell communication analysis identified enterocytes as a key player mediating signal communication networks. A four-gene signature prognostic model was constructed based on the enterocyte-related differentially expressed genes (ERDEGs) in patients with COAD of the Cancer Genome Atlas cohort. The prognostic model was validated on three external validation cohorts from the GEO database. The correlation between immune cell infiltration, immunotherapy response, drug sensitivity, and the four-gene signature prognostic model was investigated. Finally, immunohistochemistry (IHC) was performed to determine the expression of the four genes. RESULTS: We found that the proportion of epithelial cells was obviously large in COAD samples. Further analysis of epithelial cells showed that the activity of the enterocytes was highest in the cell-cell communication network. Based on enterocyte data, 30 ERDEGs were identified and a 4-gene prognostic model including CPM, CLCA4, ELOVL6, and ATP2A3 was developed and validated. The risk score derived from this model was considered as an independent variable factor to predict overall survival. The patients were divided into high- and low-risk groups based on the median riskscore value. The correlation between immune cell infiltration, immunotherapy response, immune status, clinical characteristics, drug sensitivity, and risk score was analyzed. IHC confirmed the expression of signature genes in tissues from normal individuals, patients with polyps, and COAD. CONCLUSION: In this study, we constructed and validated a novel four-gene signature prognostic model, which could effectively predict the response to immunotherapy and overall survival in patients with COAD. More importantly, this model provides useful insight into the management of colon cancer patients and aids in designing personalized therapy.
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Identification of the shared gene MXD3 signatures and biological mechanism in patients with hip pain and prostate cancer.
Prostate cancer (PRAD) is recognized as having a significant effect on systemic illnesses. This study examined possible immune cells, metabolic pathways, and genes that may explain the interaction between PRAD and hip pain. We used information retrieved from the Cancer Genome Atlas and the Gene Expression Omnibus databases. To find common genes, we utilized differential expression analysis and weighted gene co-expression network analysis. The genes that were shared were subjected to pathway enrichment studies using Gene Ontology and the Kyoto Encyclopedia of Genes and Genomes. Additionally, hub genes were analyzed using LASSO regression, and a receiver operating characteristic curve was generated based on the screening outcomes. The genes for the nodes were chosen in a protein-protein interaction network that was built. Single-sample gene-set enrichment analysis was performed to identify the differentially expressed genes. Immunohistochemistry staining confirmed hub gene expression, and single-sample gene-set enrichment analysis assessed immune cell infiltration. We concluded by comparing MAX dimerization protein 3 (MXD3) and MAX interactor 1 (MXI1) expression in tumor tissues using Uniform Manifold Approximation and Projection and violin plots in the Tumor lmmune Single-cell Hub database. After analyzing the intersection of the differentially expressed genes and weighted gene co-expression network analysis-significant module genes, we determined that MXD3 was the best shared diagnostic biomarker for PRAD and hip pain. One potential predictor of PRAD development was the MXI1 node gene, which was found in the protein-protein interaction network. The analyses revealed that MXD3 had a relatively positive correlation with neutrophil and T-helper cell infiltration levels, whereas MXI1 had a negative correlation with mast and Tgd cell levels. Tumors had lower levels of MXI1 expression and higher levels of MXD3 expression compared to normal tissues. Endothelial cells, induced pluripotent stem cells, and smooth muscle cells were all found to express MXI1. This is the first study to investigate the close genetic link between hip pain and PRAD using bioinformatics technologies. The 2 most significant genes involved in crosstalk between PRAD and hip pain were MXD3 and MXI1. The immunological responses triggered by T cells, mast cells, and neutrophils may be crucial in the relationship between PRAD and hip pain.
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Pan-cancer analysis and experimental verification of cytochrome B561 as a prognostic and therapeutic biomarker in breast cancer.
OBJECTIVE: This study investigates Cytochrome B561 (CYB561) expression in Pan-Cancer, its relationship with immune invasion, and its prognostic value in Breast Cancer (BRCA) patients. METHODS: Data from The Cancer Genome Atlas (TCGA) were analyzed. CYB561 expression in normal and tumor tissues was examined, with correlations to immune invasion, mutation, and immune checkpoints. Wilcoxon rank-sum test assessed expression differences. Gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses were conducted. Logistic regression, Kaplan-Meier, and Cox regression analyses evaluated clinicopathological features and survival outcomes. A Cox multivariate analysis-based Nomogram predicted CYB561's prognostic impact. CYB561 knockout in breast cancer cells assessed functional effects. Single-cell RNA sequencing identified prognostic biomarkers. RESULTS: CYB561 was highly expressed in most tumors. BRCA showed the highest correlation with ESTIMATE scores and significant negative correlation with immune checkpoints. High CYB561 expression correlated with specific clinicopathological features and survival outcomes. The nomogram predicted BRCA prognosis. CYB561 knockout inhibited breast cancer cell proliferation. Seven predictive agents for CYB561 inhibition were identified. CONCLUSIONS: CYB561 exhibits aberrant expression in tumors, particularly in BRCA, and serves as a predictive marker for immune-related therapies and a prognostic indicator in BRCA.