Causal Relationships Between Gut Microbiota, Inflammatory Cells/Proteins, and Subarachnoid Hemorrhage: A Multi-omics Bidirectional Mendelian Randomization Study and Meta-analysis.

Subarachnoid hemorrhage (SAH) is a neurological emergency that can lead to fatal outcomes. It occurs when bleeding happens in the subarachnoid space, a small gap between the arachnoid and pia mater. This condition results from the rupture of diseased or damaged blood vessels at the brain's base or surface. This study combined various omics approaches with Mendelian randomization analysis, including MR-IVW, MR Egger, MR weight median, and MR weight mode, to generate preliminary results. It also employed reverse Mendelian randomization, treating SAH as the exposure. Finally, a meta-analysis was conducted to summarize these findings. The study found positive correlations between SAH and both GBPA-Pyridoxal 5 phosphate biosynthesis I (OR=1.48, 95% CI, 1.04-2.12) and GBPA-glucose biosynthesis I (OR=0.68, 95% CI, 0.52-0.90). Increased levels of urokinase-type plasma activator were also associated with SAH (OR=1.17, 95% CI, 1.04-1.32). Associations were observed with SAH for CD80 on CD62L+ plasmacytoid dendritic cells, CD80 on plasmacytoid dendritic cells, CD123 on CD62L+ plasmacytoid dendritic cells, and SSC-A on plasmacytoid dendritic cells. This study, through Mendelian randomization and meta-analysis, established links between SAH and four inflammatory cells, one inflammatory protein, and two gut microbiota-related pathways. These findings suggest potential treatment targets for SAH, highlighting the importance of modulating gut microbiota and utilizing anti-inflammatory drugs in its management.

Exploring the interplay of gut microbiota, inflammation, and LDL-cholesterol: a multiomics Mendelian randomization analysis of their causal relationship in acute pancreatitis and non-alcoholic fatty liver disease.

BACKGROUND: Acute pancreatitis and non-alcoholic fatty liver disease are both serious diseases in the digestive system. The pathogenesis of both diseases is extremely complex closely and it related to gut microbiota, inflammation, and blood fat. There is a close relationship between gut microbiota and blood lipids. METHODS: In this study, we used three types of exposure: 412 gut microbiota, 731 inflammatory cells, and 91 inflammatory proteins (pqtls), with LDL-C as an intermediary and acute pancreatitis and non-alcoholic fatty liver disease as outcomes. We mainly used MR-IVW, co-localization analysis, and reverse MR analysis methods for analysis. RESULTS: 7 gut microbiota, 21 inflammatory cells, and 3 inflammatory proteins can affect LDL-C levels. LDL-C is associated with acute pancreatitis and non-alcoholic fatty liver disease. CONCLUSIONS: Three omics were used: 412 gut microbiota, 731 inflammatory cells, and 91 inflammatory proteins (pqtls). It explains the causal relationship between multiomics, LDL- cholesterol, acute pancreatitis, and non-alcoholic fatty liver disease.

Acetyl-cinobufagin suppresses triple-negative breast cancer progression by inhibiting the STAT3 pathway.

BACKGROUND: The incidence of breast cancer (BC) worldwide has increased substantially in recent years. Epithelial-mesenchymal transition (EMT) refers to a crucial event impacting tumor heterogeneity. Although cinobufagin acts as an effective anticancer agent, the clinical use of cinobufagin is limited due to its strong toxicity. Acetyl-cinobufagin, a pre-drug of cinobufagin, was developed and prepared with greater efficacy and lower toxicity. METHODS: A heterograft mouse model using triple negative breast cancer (TNBC) cell lines, was used to evaluate the potency of acetyl-cinobufagin. Signal transducer and stimulator of transcription 3 (STAT3)/EMT involvement was investigated by gene knockout experiments using siRNA and Western blot analysis. RESULTS: Acetyl-cinobufagin inhibited proliferation, migration, and cell cycle S/G2 transition and promoted apoptosis in TNBC cells in vitro. In general, IL6 triggered the phosphorylation of the transcription factor STAT3 thereby activating the STAT3 pathway and inducing EMT. Mechanistically, acetyl-cinobufagin suppressed the phosphorylation of the transcription factor STAT3 and blocked the interleukin (IL6)-triggered translocation of STAT3 to the cell nucleus. In addition, acetyl-cinobufagin suppressed EMT in TNBC by inhibiting the STAT3 pathway. Experiments in an animal model of breast cancer clearly showed that acetyl-cinobufagin was able to reduce tumor growth. CONCLUSIONS: The findings of this study support the potential clinical use of acetyl-cinobufagin as a STAT3 inhibitor in TNBC adjuvant therapy.

ß, ß-Dimethylacrylshikonin potentiates paclitaxel activity, suppresses immune evasion and triple negative breast cancer progression via STAT3Y705 phosphorylation inhibition based on network pharmacology and transcriptomics analysis.

BACKGOUND: Triple negative breast cancer (TNBC) is an extremely aggressive and rapidly progressing cancer, wherein existing therapies provide little benefit to patients. ß, ß-Dimethylacrylshikonin (DMAS), an active naphthoquinone derived from comfrey root, has potent anticancer activity. However, the antitumor function of DMAS against TNBC remains to be proved. PURPOSE: Explore effects of DMAS on TNBC and clarify the mechanism. STUDY DESIGN: Network pharmacology, transcriptomics and various cell functional experiments were applied to TNBC cells to explore the effects of DMAS on TNBC. The conclusions were further validated in xenograft animal models. METHODS: MTT, EdU, transwell, scratch tests, flow cytometry, immunofluorescence, and immunoblot were utilized to assess the activity of DMAS on three TNBC cell lines. The anti-TNBC mechanism of DMAS was clarified by overexpression and knockdown of STAT3 in BT-549 cells. In vivo efficacy of DMAS was analysed using a xenograft mouse model. RESULTS: In vitro analysis revealed that DMAS inhibited the G2/M phase transition and suppressed TNBC proliferation. Additionally, DMAS triggered mitochondrial-dependent apoptosis and reduced cell migration by antagonizing epithelial-mesenchymal transition. Mechanistically, DMAS exerted its antitumour effects by inhibiting STAT3Y705 phosphorylation. STAT3 overexpression abolished the inhibitory effect of DMAS. Further studies showed that treatment with DMAS inhibited TNBC growth in a xenograft model. Notably, DMAS potentiated the sensitivity of TNBC to paclitaxel and inhibited immune evasion by downregulating the immune checkpoint PD-L1. CONCLUSIONS: For the first time, our study revealed that DMAS potentiates paclitaxel activity, suppresses immune evasion and TNBC progression by inhibiting STAT3 pathway. It has the potential as a promising agent for TNBC.

A Novel Approach: Combining Prognostic Models and Network Pharmacology to Target Breast Cancer Necroptosis-Associated Genes.

Breast cancer (BC) accounts for the highest proportion of the all cancers among women, and necroptosis is recognized as a form of caspase-independent programmed cell death. We created prognostic signatures using univariate survival analysis, and lasso regression, to assess immune microenvironments between subgroups. We then used network pharmacology to bind our drugs to target differentially expressed genes (DEGs). A signature comprising a set of necroptosis-related genes was established to predict patient outcomes based on median risk scores. Those above and below the median were classified as high-risk group (HRG) and low-risk group (LRG), respectively. Patients at high risk had lower overall survival, and poorer predicted tumor, nodes, and metastases stages (TNM). The novel prognostic signature can effectively predict the prognosis of breast cancer patients docking of ß,ß-dimethyl acryloyl shikonin (DMAS) to possible targets to cure breast cancer. We found that all current prognostic models do not offer suitable treatment options. In additional, by docking drugs DMAS that have been initially validated in our laboratory to treat breast cancer. We hope that this novel approach could contribute to cancer research.

Downstream Neighbor of Son Overexpression is Associated With Breast Cancer Progression and a Poor Prognosis.

PURPOSE: The incidence rate of breast cancer (BC) has increased annually. Downstream neighbor of son (DONSON) critically affects cell cycle progression and maintains stable genomic properties; however, its relevant effects on BC growth and progression require in-depth investigation. METHODS: DONSON upregulation was validated in public databases. DONSON expression in matched BC and adjacent tissues and cell lines (MDA-MB-231, BT-549, and HS-578T) was determined using quantitative reverse transcription polymerase chain reaction. In vitro apoptosis, invasion, migration, and proliferation tests were performed to ascertain the functions of DONSON in BC cell lines. Then, using western blot analysis, the levels of DONSON downstream proteins were determined. RESULTS: Compared to the control, DONSON was expressed at higher levels in BC tissues and cell lines. DONSON knockdown facilitated apoptosis and limited proliferation, migration, invasion, and S/G2 transition of BC cells in vitro. Furthermore, DONSON overexpression promoted BC cell proliferation and inhibited apoptosis in vitro. Moreover, DONSON knockdown reduced cyclin A1 and cyclin-dependent kinase 2 levels. Moreover, DONSON knockdown limited the progression of epithelial-mesenchymal transition. CONCLUSION: DONSON critically affects BC growth and serves as a possible target and marker for the efficacy of subsequent therapies.

Amino Acid Metabolism-Related lncRNA Signature Predicts the Prognosis of Breast Cancer.

Background and Purpose: Breast cancer (BRCA) is the most frequent female malignancy and is potentially life threatening. The amino acid metabolism (AAM) has been shown to be strongly associated with the development and progression of human malignancies. In turn, long noncoding RNAs (lncRNAs) exert an important influence on the regulation of metabolism. Therefore, we attempted to build an AAM-related lncRNA prognostic model for BRCA and illustrate its immune characteristics and molecular mechanism. Experimental Design: The RNA-seq data for BRCA from the TCGA-BRCA datasets were stochastically split into training and validation cohorts at a 3:1 ratio, to construct and validate the model, respectively. The amino acid metabolism-related genes were obtained from the Molecular Signature Database. A univariate Cox analysis, least absolute shrinkage and selection operator (LASSO) regression, and a multivariate Cox analysis were applied to create a predictive risk signature. Subsequently, the immune and molecular characteristics and the benefits of chemotherapeutic drugs in the high-risk and low-risk subgroups were examined. Results: The prognostic model was developed based on the lncRNA group including LIPE-AS1, AC124067.4, LINC01655, AP005131.3, AC015802.3, USP30-AS1, SNHG26, and AL589765.4. Low-risk patients had a more favorable overall survival than did high-risk patients, in accordance with the results obtained for the validation cohort and the complete TCGA cohort. The elaborate results illustrated that a low-risk index was correlated with DNA-repair-associated pathways; a low TP53 and PIK3CA mutation rate; high infiltration of CD4+ T cells, CD8+ T cells, and M1 macrophages; active immunity; and less-aggressive phenotypes. In contrast, a high-risk index was correlated with cancer and metastasis-related pathways; a high PIK3CA and TP53 mutation rate; high infiltration of M0 macrophages, fibroblasts, and M2 macrophages; inhibition of the immune response; and more invasive phenotypes. Conclusion: In conclusion, we attempted to shed light on the importance of AAM-associated lncRNAs in BRCA. The prognostic model built here might be acknowledged as an indispensable reference for predicting the outcome of patients with BRCA and help identify immune and molecular characteristics.