Anxiety disorder is a prevalent psychiatric disease and imposes a significant influence on cardiovascular disease (CVD). Numerous evidence support that anxiety contributes to the onset and progression of various CVDs through different physiological and behavioral mechanisms. However, the exact role of nuclei and the association between the neural circuit and anxiety disorder in CVD remains unknown. Several anxiety-related nuclei, including that of the amygdala, hippocampus, bed nucleus of stria terminalis, and medial prefrontal cortex, along with the relevant neural circuit are crucial in CVD. A strong connection between these nuclei and the autonomic nervous system has been proven. Therefore, anxiety may influence CVD through these autonomic neural circuits consisting of anxiety-related nuclei and the autonomic nervous system. Neuromodulation, which can offer targeted intervention on these nuclei, may promote the development of treatment for comorbidities of CVD and anxiety disorders. The present review focuses on the association between anxiety-relevant nuclei and CVD, as well as discusses several non-invasive neuromodulations which may treat anxiety and CVD.

Background: Lymphocyte-specific protein tyrosine kinase (LCK), an encoded Src family protein tyrosine kinase, performs a pivotal molecular signaling role in the selection and maturation processes during T-cell development. Although aberrant LCK expression is known to have a significant association with carcinogenesis, the underlying role of LCK in breast cancer (BC) is still obscure.Methods: An analysis of the levels of LCK mRNA expression in BC was performed, and the value of LCK expression for predicting the prognosis of patients with BC was studied using various online data resources, which included Oncomine, Gene Expression Profiling Interactive Analysis (GEPIA), and UALCAN. The web-based NetworkAnalyst tool was utilized to investigate the functional network of differentially expressed LCK. LinkedOmics was employed to identify the genes with which LCK has correlations in BC, together with the kinases, microRNAs, and transcription factors (TFs) potentially targeted by LCK in BC. The expression levels of LCK and its significantly correlated genes in BC were investigated with the Human Protein Atlas (HPA). Results:We observed a significant difference in the level of LCK mRNA expression between BC patients and healthy individuals, and a higher LCK expression was associated with poor overall survival (OS). The functional enrichment results revealed that the differential expression of LCK was mainly involved in the regulation of immune response and inflammatory response in BC. The expression of significantly related genes, such as inducible T-cell kinase (ITK), CD5, CD96, CD247, SH2 domain containing 1A (SH2D1A), phosphatidylinositol-4,5-bisphosphate 3-kinase (PIK3CD), Src-like-adaptor 2 (SLA2), and interleukin 2 receptor (IL2RG), was associated with poor OS in patients with BC. Regulatory network analysis found that LCK regulated immune cells, cancer progression, apoptosis, and cell cycle signal transduction through cancerrelated kinases (ITK and MAPK3), miRNAs (miR-345 and miR-524), and TFs (AP1, SRF, and E2F1).Conclusions: This study presents new perspectives on the differential expression and prognostic value of LCK in BC. Our observations will provide a basis for further study on the oncogenic and regulatory roles of LCK in BC.

Introduction Amplification of the 11q13.3 locus has been observed in various tumors. This study sought to determine the correlation of gene amplification at the 11q13.3 locus with the immune status and survival of breast cancer. Methods Amplification of the 11q13.3 locus was characterized by analyzing a publicly available database from the cBioPortal platform (TCGA). The correlation of amplified genes with immune cell infiltration in breast cancer was further analyzed using the TIMER2.0 platform. Immunohistochemical staining was used to determine the expression levels of Cyclin D1 (CCND1), Fas-associated death domain (FADD) and P53 in 156 clinical breast cancer samples. Results This study revealed that amplification of the 11q13.3 amplicon in breast cancer is likely more frequently detected in luminal B breast cancer. Moreover, high expression or amplification of CCND1 , fibroblast growth factor 3 ( FGF3 ), fibroblast growth factor 4 ( FGF4 ), fibroblast growth factor 19 ( FGF19 ) and FADD was inversely correlated with the abundance of CD4+ T cells and dendritic cell infiltration in breast cancer ( P < 0.05). Data analysis also demonstrated that high expression of CCND1, FGF4 and FADD mRNA levels was closely correlated with shorter recurrence-free survival (RFS) in patients with breast cancer ( P < 0.05). The results of immunohistochemical staining from clinical samples further confirmed that high expression of CCND1 and FADD was frequently detected in luminal B and high-grade breast cancer with shorter metastasis-free survival times ( P < 0.05). Conclusion This study demonstrated that coamplification of genes located on the 11q13.3 amplicon is frequently detected in luminal B subtype breast cancer and is closely associated with worse survival in patients with breast cancer. Moreover, coamplification of the CCND1-FGF locus might decrease antitumor immune activity in breast cancer, indicating that coamplification of the 11q13.3 amplicon is likely to be a key determinant of therapeutic resistance and accelerate the aggressive evolution of breast cancer.

Background Triple-negative breast cancer (TNBC) is the most heterogenous and aggressive subtype of breast cancer. Chemotherapy remains the standard treatment option for patients with TNBC owing to the unavailability of acceptable targets and biomarkers in clinical practice. Novel biomarkers and targets for patient stratification and treatment of TNBC are urgently needed. It has been reported that the overexpression of DNA damage-inducible transcript 4 gene (DDIT4) is associated with resistance to neoadjuvant chemotherapy and poor prognosis in patients with TNBC. In this study, we aimed to identify novel biomarkers and therapeutic targets using RNA sequencing (RNA-seq) and data mining using data from public databases. Methods RNA sequencing (RNA-Seq) was performed to detect the different gene expression patterns in the human TNBC cell line HS578T treated with docetaxel or doxorubicin. Sequencing data were further analyzed by the R package “edgeR” and “clusterProfiler” to identify the profile of differentially expressed genes (DEGs) and annotate gene functions. The prognostic and predictive value of DDIT4 expression in patients with TNBC was further validated by published online data resources, including TIMER, UALCAN, Kaplan–Meier plotter, and LinkedOmics, and GeneMANIA and GSCALite were used to investigate the functional networks and hub genes related to DDIT4, respectively. Results Through the integrative analyses of RNA-Seq data and public datasets, we observed the overexpression of DDIT4 in TNBC tissues and found that patients with DDIT4 overexpression showed poor survival outcomes. Notably, immune infiltration analysis showed that the levels of DDIT4 expression correlated negatively with the abundance of tumor-infiltrating immune cells and immune biomarker expression, but correlated positively with immune checkpoint molecules. Furthermore, DDIT4 and its hub genes (ADM, ENO1, PLOD1, and CEBPB) involved in the activation of apoptosis, cell cycle, and EMT pathways. Eventually, we found ADM, ENO1, PLOD1, and CEBPB showed poor overall survival in BC patients. Conclusion In this study, we found that DDIT4 expression is associated with the progression, therapeutic efficacy, and immune microenvironment of patients with TNBC, and DDIT4 would be as a potential prognostic biomarker and therapeutic target. These findings will help to identify potential molecular targets and improve therapeutic strategies against TNBC.

Background Triple-negative breast cancer (TNBC) is the most heterogenous and aggressive subtype of breast cancer. Chemotherapy remains the standard treatment option for patients with TNBC owing to the unavailability of acceptable targets and biomarkers in clinical practice. Novel biomarkers and targets for patient stratification and treatment of TNBC are urgently needed. In this study, we aimed to identify novel biomarkers and therapeutic targets using RNA sequencing (RNA-seq) and data mining using data from public databases. Methods RNA-sequencing (RNA-Seq) was performed to detect the different gene expression patterns in the human TNBC cell line HS578T treated with docetaxel or doxorubicin. Raw data were analyzed using the R package “edgeR” to identify the profile of differentially expressed genes (DEGs) and functionally annotated through R package “clusterProfiler.” The prognostic and predictive value of DNA damage-inducible transcript 4 gene (DDIT4) expression in patients with TNBC was further studied using published online data resources, including TIMER, UALCAN, and Kaplan-Meier Plotter. LinkedOmics and GeneMANIA were used to investigate the genes and functional networks related to DDIT4. GSCALite was used to analyze the pathway activities of DDIT4 and its hub genes. Results Through the integrative analyses of RNA-Seq data and public datasets, we observed the overexpression of DDIT4 in TNBC tissues(p<0.01) and found that patients with DDIT4 overexpression showed poor survival outcomes (p<0.05). Notably, immune infiltration analysis showed that the levels of DDIT4 expression correlated negatively with the abundance of tumor-infiltrating immune cells and immune biomarker expression (p<0.05), but correlated positively with immune checkpoint molecules (p<0.01). Furthermore, DDIT4 and its hub genes (ADM, ENO1, PLOD1, and CEBPB) involved in the activation of Apoptosis, Cell Cycle and EMT pathways. Eventually, we found ADM, ENO1, PLOD1 and CEBPB showed poor overall survival in BC patients (p<0.01). Conclusion In this study, we found that DDIT4 expression is associated with the progression, therapeutic efficacy, and immune microenvironment of patients with TNBC, and DDIT4 would be as a potential prognostic biomarker and therapeutic target. These findings will help to identify potential new molecular targets and improve therapeutic strategies against TNBC.