Dissecting the roles and clinical potential of YY1 in the tumor microenvironment

Yin-Yang 1 (YY1) is a member of the GLI-Kruppel family of zinc finger proteins and plays a vital dual biological role in cancer as an oncogene or a tumor suppressor during tumorigenesis and tumor progression. The tumor microenvironment (TME) is identified as the “soil” of tumor that has a critical role in both tumor growth and metastasis. Many studies have found that YY1 is closely related to the remodeling and regulation of the TME. Herein, we reviewed the expression pattern of YY1 in tumors and summarized the function and mechanism of YY1 in regulating tumor angiogenesis, immune and metabolism. In addition, we discussed the potential value of YY1 in tumor diagnosis and treatment and provided a novel molecular strategy for the clinical diagnosis and treatment of tumors

Cathepsin G promotes arteriovenous fistula maturation by positively regulating the MMP2/MMP9 pathway

Background Arteriovenous fistula (AVF) is currently the preferred vascular access for hemodialysis patients. However, the low maturation rate of AVF severely affects its use in patients. A more comprehensive understanding and study of the mechanisms of AVF maturation is urgently needed.Methods and results In this study, we downloaded the publicly available datasets (GSE119296 and GSE220796) from the Gene Expression Omnibus (GEO) and merged them for subsequent analysis. We screened 84 differentially expressed genes (DEGs) and performed the functional enrichment analysis. Next, we integrated the results obtained from the degree algorithm provided by the Cytohubba plug-in, Molecular complex detection (MCODE) plug-in, weighted gene correlation network analysis (WGCNA), and Least absolute shrinkage and selection operator (LASSO) logistic regression. This integration allowed us to identify CTSG as a hub gene associated with AVF maturation. Through the literature search and Pearson’s correlation analysis, the genes matrix metalloproteinase 2 (MMP2) and MMP9 were identified as potential downstream effectors of CTSG. We then collected three immature clinical AVF vein samples and three mature samples and validated the expression of CTSG using immunohistochemistry (IHC) and double-immunofluorescence staining. The IHC results demonstrated a significant decrease in CTSG expression levels in the immature AVF vein samples compared to the mature samples. The results of double-immunofluorescence staining revealed that CTSG was expressed in both the intima and media of AVF veins. Moreover, the expression of CTSG in vascular smooth muscle cells (VSMCs) was significantly higher in the mature samples compared to the immature samples. The results of Masson’s trichrome and collagen I IHC staining demonstrated a higher extent of collagen deposition in the media of immature AVF veins compared to the mature. By constructing an in vitro CTSG overexpression model in VSMCs, we found that CTSG upregulated the expression of MMP2 and MMP9 while downregulating the expression of collagen I and collagen III. Furthermore, CTSG was found to inhibit VSMC migration.Conclusions CTSG may promote AVF maturation by stimulating the secretion of MMP2 and MMP9 from VSMCs and reducing the extent of medial fibrosis in AVF veins by inhibiting the secretion of collagen I and collagen III

Antioxidant protection of a polysaccharide produced by Chaetomium globosum CGMCC 6882 on H2O2-challenged HepG2 cells

Effective utilization of waste kitchen oil (WKO) is important to environmental protection and economic development. Presently, an endophytic fungus Chaetomium globosum CGMCC 6882 polysaccharide (CGP-WKO) was successfully produced through submerged fermentation with the sole carbon source of WKO. CGP-WKO had a yield of 1.53 ± 0.27 g/L and contained 95.85 % ± 3.02 % carbohydrate and 2.94 % ± 0.62 % protein. Structural feature analysis indicated that CGP-WKO contained glucose, glucosamine, mannose, rhamnose, galactose, fructose, and glucuronic acid in a molar ratio of 30.38: 1.34: 32.22: 9.68: 1.59: 0.62: 3.73. The weight-averaged molecular weight of CGP-WKO was 26.64 kDa, and its polydispersity was 1.48. Moreover, antioxidant capacity detection in vitro demonstrated that when the concentration of CGP-WKO was 1.0 mg/mL, its scavenging effects against 1,1-diphenyl-2-picrylhydrazyl; 2,2′-azinobis-di-(3-ethyl-benzothiazolin-6-sulfonic acid) diammonium salt; and hydroxyl and superoxide radicals were 45.89 % ± 1.89 %, 55.89 % ± 1.12 %, 29.02 % ± 2.61 %, and 52.76 % ± 2.12 %, respectively; and the IC50 values were 6.4612, 0.8888, 13.8585, and 0.9398 mg/mL, respectively. CGP-WKO increased the content of superoxide dismutase, catalase, and glutathione peroxidase and reduced malondialdehyde content in H2O2-challenged HepG2 cells. Overall, the present work indicated that CGP-WKO can be used as an antioxidant agent in the food, cosmetics, and pharmaceutical industries

Deciphering the molecular and clinical characteristics of TREM2, HCST, and TYROBP in cancer immunity: A comprehensive pan-cancer study

Background: Hematopoietic cell signal transducer (HCST) and tyrosine kinase-binding protein (TYROBP) are triggering receptors expressed on myeloid cells 2 (TREM2), which are pivotal in the immune response to disease. Despite growing evidence underscoring the significance of TREM2, HCST, and TYROBP in certain forms of tumorigenesis, a comprehensive pan-cancer analysis of these proteins is lacking. Methods: Multiple databases were synthesized to investigate the relationship between TREM2, HCST, TYROBP, and various cancer types. These include prognosis, methylation, regulation by long non-coding RNAs and transcription factors, immune signatures, pathway activity, microsatellite instability (MSI), tumor mutational burden (TMB), single-cell transcriptome profiling, and drug sensitivity. Results: TREM2, HCST, and TYROBP displayed extensive somatic changes across numerous tumors, and their mRNA expression and methylation levels influenced patient outcomes across multiple cancer types. long non-coding RNA (lncRNA) -messenger RNA (mRNA) and TF-mRNA regulatory networks involving TREM2, HCST, and TYROBP were identified, with lncRNA MEG3 and the transcription factor SIP1 emerging as potential key regulators. Further immune analyses indicated that TREM2, HCST, and TYROBP play critical roles in immune-related pathways and macrophage differentiation, and may be significantly associated with TGF-β and SMAD9. Furthermore, the expression of TREM2, HCST, and TYROBP correlated with the immunotherapy markers TMB and MSI, and influenced sensitivity to immune-targeted drugs, thereby indicating their potential as predictors of immunotherapy outcomes. Conclusion: This study offers valuable insights into the roles of TREM2, HCST, and TYROBP in tumor immunotherapy, suggesting their potential as prognostic markers and therapeutic targets for various cancers

The Emerging Roles and Clinical Potential of circSMARCA5 in Cancer

Circular RNAs (circRNAs) are a type of endogenous non-coding RNA and a critical epigenetic regulation way that have a closed-loop structure and are highly stable, conserved, and tissue-specific, and they play an important role in the development of many diseases, including tumors, neurological diseases, and cardiovascular diseases. CircSMARCA5 is a circRNA formed by its parental gene SMARCA5 via back splicing which is dysregulated in expression in a variety of tumors and is involved in tumor development with dual functions as an oncogene or tumor suppressor. It not only serves as a competing endogenous RNA (ceRNA) by binding to various miRNAs, but it also interacts with RNA binding protein (RBP), regulating downstream gene expression; it also aids in DNA damage repair by regulating the transcription and expression of its parental gene. This review systematically summarized the expression and characteristics, dual biological functions, and molecular regulatory mechanisms of circSMARCA5 involved in carcinogenesis and tumor progression as well as the potential applications in early diagnosis and gene targeting therapy in tumors

The relationships between the expression levels of NSUN2 and TILs or immune-related gene.

(A) Expression analysis between NSUN2 and TILs including B cells, CD4+ T cells, CD8+ T cells, neutrophils, macrophages and dendritic cells. (B) The correlation between the expression levels of NSUN2 and neutrophils. (C) The relationships between the expression levels of NSUN2 and follicular helper T cells, common lymphoid progenitors and MDSCs. (D) The correlation between the expression levels of NSUN2 and immune checkpoint genes. (E) The correlation between the expression levels of NSUN2 and immune-regulated genes (*PPPP<0.0001).</p

Correlation analysis between NSUN2 and molecular subtype in different cancer types.

(A) In LIHC. (B) In HNSC. (C) In BRCA. (D) In ESCA. (E) In OV. (F) In LGG. (G) In ACC. (H) In PCPG. (I) In KIRP. (J) In UCEC. (K) In STAD. (L) In PRAD. (TIF)</p

The survival curve of NSUN2 by the Kaplan‒Meier plotter database.

(A) OS in LIHC cohorts. (B) RFS in LIHC cohorts. (C) OS in KIRP cohorts. (D) RFS in KIRP cohorts. (E) OS in THCA cohorts. (F) RFS in THCA cohorts. (G) OS in UCEC cohorts. (H) OS in KIRC cohorts. (I) OS in LUAD cohorts. OS, overall survival. RFS, relapse-free survival. Red line, high expression of NSUN2. Black line, low expression of NSUN2.</p

Coexpression analysis of NSUN2-related genes in LIHC, LUAD and HNSC, and analysis between NSUN2 expression and the levels of immune cells.

(A-C) KEGG pathway analysis of NSUN2-related gene in LIHC, LUAD and HNSC cohorts. (D) Expression analysis between NSUN2 and TILs including B cells, CD8+ T cells, CD4+ T cells, macrophages, neutrophils and dendritic cells based on the TIMER database. (E) The subcellular localization prediction of NSUN2. (TIF)</p