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Background: Atherosclerosis (AS) is a chronic inflammatory disease with a significant contributor to mortality worldwide. Regulatory T cells (Tregs) are atheroprotective. However, the potential pathways and genes associated with atherosclerotic plaque progression in Tregs remain largely unknown. Therefore, this study aimed to identify critical target genes and pathways of Tregs associated with the progression of AS. Methods: The gene expression data and single cell RNA-seq data of AS were downloaded from the Gene Expression Omnibus (GEO) database. Initially, we quantified CD4+ T cell proportions in non-plaque and plaque tissues using cell infiltration by estimation of RNA sequences (CIBERSORT) analysis, identifying pivotal transcription factors regulating the number of Tregs in atherosclerotic plaque. Subsequently, we identified significantly differential expressed genes of Tregs during the progression of atherosclerotic plaque and investigated the key pathways and transcription factors for these differentially expressed genes using gene ontology (GO) analysis and transcription factor enrichment analysis (TFEA), respectively. We also employed high dimensional weighted gene co-expression network analysis (hdWGCNA) and cell-cell communication analysis to elucidate the modules and cascade reaction of Tregs in the progression of AS. The key genes diagnostic potential was assessed via receiver operating characteristic (ROC) curve analysis. Finally, the target genes were validated in AS model using Ldlr−/− mice. Results: We found that the proportion of Tregs significantly decreased, and Th2 cells showed a significant increase in atherosclerotic plaque compared to that in non-plaque arterial tissues. The five transcription factors (TEFC, IRF8, ZNF267, KLF2, and JUNB), identified as key targets associated with the function and the number of Tregs driving the progression of AS, primarily regulate immune response, ubiquitination, cytokine production, and T-cell differentiation pathways. ZNF267 may mainly involve in regulating ubiquitination, TGF-beta, and MAPK pathways of Tregs to regulate the function and the number of Tregs during the progress of AS. Interestingly, we found that IRF8 and ZNF267 as potential biomarkers were upregulated in circulating CD4+ T cells in patients with atherosclerotic coronary artery disease. Moreover, we also found that the changes of the function and the number of Tregs could modulate endothelial cell and smooth muscle cell functions to counteract AS through ligand–receptor pairs such as the MIF signaling pathway. Finally, we validated that two of the five transcription factors were also upregulated in mice atherosclerotic plaque through AS model using Ldlr−/− mice. Conclusion: Our results indicate that the transcription factors TEFC, IRF8, ZNF267, KLF2, and JUNB in Tregs could be potential targets for the clinical management of AS. [ABSTRACT FROM AUTHOR]

Background: Triple-negative breast cancer (TNBC) is a heterogeneous disease with a worse prognosis. Despite ongoing efforts, existing therapeutic approaches show limited success in improving early recurrence and survival outcomes for TNBC patients. Therefore, there is an urgent need to discover novel and targeted therapeutic strategies, particularly those focusing on the immune infiltrate in TNBC, to enhance diagnosis and prognosis for affected individuals. Methods: The gene co-expression network and gene ontology analyses were used to identify the differential modules and their functions based on the GEO dataset of GSE76275. The Weighted Gene Co-Expression Network Analysis (WGCNA) was used to describe the correlation patterns among genes across multiple samples. Subsequently, we identified key genes in TNBC by assessing genes with an absolute correlation coefficient greater than 0.80 within the eigengene of the enriched module that were significantly associated with breast cancer subtypes. The diagnostic potential of these key genes was evaluated using receiver operating characteristic (ROC) curve analysis with three-fold cross-validation. Furthermore, to gain insights into the prognostic implications of these key genes, we performed relapse-free survival (RFS) analysis using the Kaplan-Meier plotter online tool. CIBERSORT analysis was used to characterize the composition of immune cells within complex tissues based on gene expression data, typically derived from bulk RNA sequencing or microarray datasets. Therefore, we explored the immune microenvironment differences between TNBC and non-TNBC by leveraging the CIBERSORT algorithm. This enabled us to estimate the immune cell compositions in the breast cancer tissue of the two subtypes. Lastly, we identified key transcription factors involved in macrophage infiltration and polarization in breast cancer using transcription factor enrichment analysis integrated with orthogonal omics. Results: The gene co-expression network and gene ontology analyses revealed 19 modules identified using the dataset GSE76275. Of these, modules 5, 11, and 12 showed significant differences between in breast cancer tissue between TNBC and non-TNBC. Notably, module 11 showed significant enrichment in the WNT signaling pathway, while module 12 demonstrated enrichment in lipid/fatty acid metabolism pathways. Subsequently, we identified SHC4/KCNK5 and ABCC11/ABCA12 as key genes in module 11 and module 12, respectively. These key genes proved to be crucial in accurately distinguishing between TNBC and non-TNBC, as evidenced by the promising average AUC value of 0.963 obtained from the logistic regression model based on their combinations. Furthermore, we found compelling evidence indicating the prognostic significance of three key genes, KCNK5, ABCC11, and ABCA12, in TNBC. Finally, we also identified the immune cell compositions in breast cancer tissue between TNBC and non-TNBC. Our findings revealed a notable increase in M0 and M1 macrophages in TNBC compared to non-TNBC, while M2 macrophages exhibited a significant reduction in TNBC. Particularly intriguing discovery emerged with respect to the transcription factor FOXM1, which demonstrated a significant regulatory role in genes positively correlated with the proportions of M0 and M1 macrophages, while displaying a negative correlation with the proportion of M2 macrophages in breast cancer tissue. Conclusion: Our research provides new insight into the biomarkers and immune infiltration of TNBC, which could be useful for clinical diagnosis of TNBC. [ABSTRACT FROM AUTHOR]

Cancer poses a significant public health challenge worldwide, and timely screening has the potential to mitigate cancer progression and reduce mortality rates. Currently, early identification of most tumors relies on imaging techniques and tissue biopsies. However, the use of low-cost, highly sensitive, non-invasive detection methods for early cancer screening has become more attractive. Extracellular Vesicles (EVs) released by all living cells contain distinctive biological components, such as nucleic acids, proteins, and lipids. These vesicles play crucial roles in the tumor microenvironment and intercellular communication during tumor progression, rendering liquid biopsy a particularly suitable method for diagnosis. Nevertheless, challenges related to purification methods and validation of efficacy currently hinder its widespread clinical implementation. These limitations underscore the importance of refining isolation techniques and conducting comprehensive investigations on EVs. This study seeks to evaluate the potential of liquid biopsy utilizing blood-derived EVs as a practical, cost-effective, and secure approach for early cancer detection. [ABSTRACT FROM AUTHOR]

Background: Atherosclerosis (AS) is a chronic inflammatory disease with a significant contributor to mortality worldwide. Regulatory T cells (Tregs) are atheroprotective. However, the potential pathways and genes associated with atherosclerotic plaque progression in Tregs remain largely unknown. Therefore, this study aimed to identify critical target genes and pathways of Tregs associated with the progression of AS., Methods: The gene expression data and single cell RNA-seq data of AS were downloaded from the Gene Expression Omnibus (GEO) database. Initially, we quantified CD4 + T cell proportions in non-plaque and plaque tissues using cell infiltration by estimation of RNA sequences (CIBERSORT) analysis, identifying pivotal transcription factors regulating the number of Tregs in atherosclerotic plaque. Subsequently, we identified significantly differential expressed genes of Tregs during the progression of atherosclerotic plaque and investigated the key pathways and transcription factors for these differentially expressed genes using gene ontology (GO) analysis and transcription factor enrichment analysis (TFEA), respectively. We also employed high dimensional weighted gene co-expression network analysis (hdWGCNA) and cell-cell communication analysis to elucidate the modules and cascade reaction of Tregs in the progression of AS. The key genes diagnostic potential was assessed via receiver operating characteristic (ROC) curve analysis. Finally, the target genes were validated in AS model using Ldlr -/- mice., Results: We found that the proportion of Tregs significantly decreased, and Th2 cells showed a significant increase in atherosclerotic plaque compared to that in non-plaque arterial tissues. The five transcription factors (TEFC, IRF8, ZNF267, KLF2, and JUNB), identified as key targets associated with the function and the number of Tregs driving the progression of AS, primarily regulate immune response, ubiquitination, cytokine production, and T-cell differentiation pathways. ZNF267 may mainly involve in regulating ubiquitination, TGF-beta, and MAPK pathways of Tregs to regulate the function and the number of Tregs during the progress of AS. Interestingly, we found that IRF8 and ZNF267 as potential biomarkers were upregulated in circulating CD4+ T cells in patients with atherosclerotic coronary artery disease. Moreover, we also found that the changes of the function and the number of Tregs could modulate endothelial cell and smooth muscle cell functions to counteract AS through ligand-receptor pairs such as the MIF signaling pathway. Finally, we validated that two of the five transcription factors were also upregulated in mice atherosclerotic plaque through AS model using Ldlr -/- mice., Conclusion: Our results indicate that the transcription factors TEFC, IRF8, ZNF267, KLF2, and JUNB in Tregs could be potential targets for the clinical management of AS., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest. The author(s) declared that they were an editorial board member of Frontiers, at the time of submission. This had no impact on the peer review process and the final decision., (Copyright © 2025 Zhang, Lu, Qiu, Qin, Shan, Xie, Yi and Yu.)