Your browser does not allow saving data (e.g. private mode): bookmarks will be lost when the tab closes.
Search PubMed
Keywords, author, journal, years — results from PubMed, abstracts with Russian translation, bookmarks in your browser.
Found: 4 939
Page 398 of 494-
Identification and validation of prognostic signature genes of bladder cancer by integrating methylation and transcriptomic analysis.
Being a frequent malignant tumor of the genitourinary system, Bladder Urothelial Carcinoma (BLCA) has a poor prognosis. This study focused on identifying and validating prognostic biomarkers utilizing methylation, transcriptomics, and clinical data from The Cancer Genome Atlas Bladder Urothelial Carcinoma (TCGA BLCA) cohort. The impact of altered differentially methylated hallmark pathway genes was subjected to clustering analysis to observe changes in the transcriptional landscape on BLCA patients and identify two subtypes of patients from the TCGA BLCA population where Subtype 2 was associated with the worst prognosis with a p-value of 0.00032. Differential expression and enrichment analysis showed that subtype 2 was enriched in immune-responsive and cancer-progressive pathways, whereas subtype 1 was enriched in biosynthetic pathways. Following, regression and network analyses revealed Epidermal Growth Factor Receptor (EGFR), Fos-related antigen 1 (FOSL1), Nuclear Factor Erythroid 2 (NFE2), ADP-ribosylation factor-like protein 4D (ARL4D), SH3 domain containing ring finger 2 (SH3RF2), and Cadherin 3 (CDH3) genes to be the most significant prognostic gene markers. These genes were used to construct a risk model that separated the BLCA patients into high and low-risk groups. The risk model was also validated in an external dataset by performing survival analysis between high and low-risk groups with a p-value < 0.001 and the result showed the high group was significantly associated with poor prognosis compared to the low group. Single-cell analyses revealed the elevated level of these genes in the tumor microenvironment and associated with immune response. High-grade patients also tend to have a high expression of these genes compared to low-grade patients. In conclusion, this research developed a six-gene signature that is pertinent to the prediction of overall survival (OS) and might contribute to the advancement of precision medicine in the management of bladder cancer.
-
Identifying a CD8T cell signature in the tumor microenvironment to forecast gastric cancer outcomes from sequencing data.
BACKGROUND: The tumor microenvironment (TME) could be critical in carcinogenesis, immune evasion, and treatment response. TME-related genes are limited in their ability to predict gastric cancer (GC) outcomes. We utilized data from The Cancer Genome Atlas (TCGA) to investigate the functional roles of TME-related genes in GC. METHODS: We acquired single-cell data, bulk sequencing data, and clinical characteristics of GC patients from the TCGA database. The CD8T cell genes associated with the TME were selected for bioinformatic analysis in GC. Tumor classification of GC was established through consistent cluster analysis. We then evaluated the prognosis and immune cell infiltration in connection with a CD8T cell-related model for GC. RESULTS: The single-cell messenger RNA (mRNA) sequencing (scRNA-Seq) dataset of GSE134520 was utilized to investigate the pathogenesis and disease-specific cell types in GC. Interestingly, compared to healthy tissue, the proportions of CD8Tex cells, malignant cells, and gland mucous increased in GC, whereas the proportion of pit mucous decreased in GC. Since CD8Tex cells may play a vital role in pancreatic adenocarcinoma (PAAD), based on the 612 differentially expressed genes (DEGs) involved in CD8Tex cells, TCGA-GC patients were stratified into low- and high-risk groups. The downregulated DEGs in the low-risk G1 group were associated with proteoglycans in cancer, the cGMP-PKG signaling pathway, focal adhesion, and cell adhesion molecules (CAMs), whereas the upregulated DEGs were associated with viral protein interaction with cytokine and cytokine receptors, the tumor necrosis factor (TNF) signaling pathway, the interleukin (IL)-17 signaling pathway, and the chemokine signaling pathway. Combined with univariate Cox analysis, we ultimately identified 23 CD8T cell-related prognostic genes: TCIM, AADAC, SLC2A3, ZNF331, TSC22D3, CMTM3, ZFP36, VIM, CLDND1, GABARAPL1, SOCS3, RGS1, TCEAL9, RGS2, CD59, SPRY1, EMP3, ZEB2, PDE4B, GLIPR1, ERRFI1, and LBH. Using the Cox regression model to prioritize the 23 CD8T cell-related genes, we finally selected 7 genes: CXCR4, AADAC, SLC2A3, CMTM3, RGS2, CD59, and ZEB2. CONCLUSIONS: CD8T cell-related genes have a strong association with tumor classification and immune response in GC patients. A CD8T cell-related signature demonstrated robust prognostic predictive performance for GC. Our findings may reveal novel insights into the diagnosis and treatment of GC.
-
Glioma hexokinase 3 positively correlates with malignancy and macrophage infiltration.
BACKGROUND: Glioma is the main subtype of primary central nervous system (CNS) tumor with high malignancy and poor prognosis under current therapeutic approaches. Glycolysis and suppressive tumor microenvironment (TME) are key markers of glioma with great importance for aggressive features of glioma and inferior clinical outcomes. Hexokinase 3 (HK3) is an important rate-limiting enzyme in glycolysis, but its function in glioma remains unknown. METHODS: This study comprehensively assessed the expression distribution and immunological effect of HK3 via pan-cancer analysis based on datasets from Genotype Tissue Expression (GTEx), Cancer Cell Line Encyclopedia (CCLE), and The Cancer Genome Atlas (TCGA). Furthermore, it explored the malignant phenotype and genomic landscape between low-HK3 and high-HK3 expression groups in gliomas from Chinese Glioma Genome Atlas (CGGA) and TCGA. Moreover, data from the TIMER website predicted the relationship between macrophage infiltration and HK3 expression. Also, single-cell sequencing data were used to validate the relationship. RESULTS: For pan-cancer patients, HK3 was expressed in various cancers. The results showed that HK3 was highly expressed in gliomas and positively correlated with tumor-infiltrating immune cells (TIICs), immune checkpoints, immunomodulators, and chemokines. Meanwhile, HK3 expression was highest in normal immune cells and tissues. In gliomas, the expression of HK3 was found to be closely correlated with the malignant clinical characteristics and the infiltration of macrophages. Also, HK3 was proven to be positively associated with macrophage through single-cell sequencing data and immunohistochemistry techniques. Finally, it is predicted that samples with high HK3 expression are often malignant entities and also significant genomic aberrations of driver oncogenes. CONCLUSIONS: This is the first comprehensive research to figure out the relationship between HK3 and TME characteristics in gliomas. HK3 is positively associated with macrophage infiltration and can induce the immunosuppressive TME and malignant phenotype of gliomas.
-
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.
-
PD-L1 and PD-L2 Expression in Cervical Cancer: Regulation and Biomarker Potential.
PD-1/PD-L1 immune checkpoint inhibitors show potential for cervical cancer treatment. However, low response rates suggest that patient selection based on PD-L1 protein expression is not optimal. Here, we evaluated different PD-L1 detection methods and studied transcriptional regulation of PD-L1/PD-L2 expression by The Cancer Genome Atlas (TCGA) mRNAseq analysis. First, we determined the copy number of the PD-L1/PD-L2 locus by fluorescence in situ hybridization (FISH), PD-L1 mRNA expression by RNA in situ hybridization (RNAish), and PD-L1/PD-L2 protein expression by immunohistochemistry (IHC) on tissue microarrays containing a cohort of 60 patients. Additionally, distribution of PD-L1/PD-L2 was visualized based on flow cytometry analysis of single-cell suspensions (n = 10). PD-L1/PD-L2 locus amplification was rare (2%). PD-L1 mRNA expression in tumor cells was detected in 56% of cases, while 41% expressed PD-L1 protein. Discordant scores for PD-L1 protein expression on tumor cells between cores from one patient were observed in 27% of cases. Interestingly, with RNAish, PD-L1 heterogeneity was observed in only 11% of the cases. PD-L2 protein expression was found in 53%. PD-L1 mRNA and protein expression on tumor cells were strongly correlated (p < 0.001). PD-L1 and PD-L2 protein expression showed no correlation on tumor cells (p = 0.837), but a strong correlation on cells in stromal fields (p < 0.001). Co-expression of PD-L1 and PD-L2 on macrophage-like populations was also observed with flow cytometry analysis. Both PD-L1 and PD-L2 TCGA transcript levels strongly correlated in the TCGA data, and both PD-L1 and PD-L2 strongly correlated with interferon gamma (IFNG) expression/transcript levels (p < 0.0001). Importantly, patients with high PD-L1/PD-L2/IFNG transcript levels had a survival advantage over patients with high PD-L1/PD-L2 and low IFNG expression. Based on these findings, we conclude that PD-L1/PD-L2 expression in cervical cancer is mainly associated with interferon induction and not gene amplification, which makes FISH unsuitable as biomarker. The heterogeneous PD-L1 and PD-L2 expression patterns suggest IHC unreliable for patient selection. RNAish, in conjunction with interferon signaling evaluation, seems a promising technique for immune checkpoint detection. These results warrant further investigation into their prognostic and predictive potential.
-
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.
-
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.
-
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.
-
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.
-
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.