Tbxt alleviates senescence and apoptosis of nucleus pulposus cells through Atg7 mediated autophagy activation during intervertebral disc degeneration.

Intervertebral disc degeneration (IDD) is a significant cause of low back pain, characterized by excessive senescence and apoptosis of nucleus pulposus cells (NPCs). However, the precise mechanisms behind this senescence and apoptosis remains unclear. This study aimed to investigate the role of Tbxt in IDD both in vitro and in vivo, using a hydrogen peroxide (H2O2)-induced NPCs senescence and apoptosis model, as well as a rat acupuncture IDD model. Firstly, the expression of p16 and cleaved-caspase 3 significantly increased in degenerated human NPCs, accompanied by a decrease in Tbxt expression. Knockdown of Tbxt exacerbated senescence and apoptosis in the H2O2-induced NPCs degeneration model. Conversely, upregulation of Tbxt alleviated these effects induced by H2O2. Mechanistically, bioinformatic analysis revealed that the direct downstream target genes of Tbxt were highly enriched in autophagy-related pathways and overexpression of Tbxt significantly activated autophagy in NPCs. Moreover, the administration of the autophagy inhibitor, 3-methyladenine, impeded the impact of Tbxt on the processes of senescence and apoptosis in NPCs. Further investigation revealed that Tbxt enhances autophagy by facilitating the transcription of ATG7 through its interaction with a specific motif within the promoter region. In conclusion, this study suggests that Tbxt mitigates H2O2-induced senescence and apoptosis of NPCs by activating ATG7-mediated autophagy.

Brachyury promotes extracellular matrix synthesis through transcriptional regulation of Smad3 in nucleus pulposus.

Metabolic dysfunction of the extracellular matrix (ECM) is one of the primary causes of intervertebral disc degeneration (IVDD). Previous studies have demonstrated that the transcription factor Brachyury (Bry) has the potential to promote the synthesis of collagen II and aggrecan, while the specific mechanism is still unknown. In this study, we used a lipopolysaccharide (LPS)-induced model of nucleus pulposus cell (NPC) degeneration and a rat acupuncture IVDD model to elucidate the precise mechanism through which Bry affects collagen II and aggrecan synthesis in vitro and in vivo. First, we confirmed Bry expression decreased in degenerated human nucleus pulposus (NP) cells (NPCs). Knockdown of Bry exacerbated the decrease in collagen II and aggrecan expression in the lipopolysaccharide (LPS)-induced NPCs degeneration in vitro model. Bioinformatic analysis indicated that Smad3 may participate in the regulatory pathway of ECM synthesis regulated by Bry. Chromatin immunoprecipitation followed by quantitative polymerase chain reaction (ChIP-qPCR) and luciferase reporter gene assays demonstrated that Bry enhances the transcription of Smad3 by interacting with a specific motif on the promoter region. In addition, Western blot and reverse transcription-qPCR assays demonstrated that Smad3 positively regulates the expression of aggrecan and collagen II in NPCs. The following rescue experiments revealed that Bry-mediated regulation of ECM synthesis is partially dependent on Smad3 phosphorylation. Finally, the findings from the in vivo rat acupuncture-induced IVDD model were consistent with those obtained from in vitro assays. In conclusion, this study reveals that Bry positively regulates the synthesis of collagen II and aggrecan in NP through transcriptional activation of Smad3.NEW & NOTEWORTHY Mechanically, in the nucleus, Bry enhances the transcription of Smad3, leading to increased expression of Smad3 protein levels; in the cytoplasm, elevated substrate levels further lead to an increase in the phosphorylation of Smad3, thereby regulating collagen II and aggrecan expression. Further in vivo experiments provide additional evidence that Bry can alleviate IVDD through this mechanism.

Identification of new co-diagnostic genes for sepsis and metabolic syndrome using single-cell data analysis and machine learning algorithms.

Sepsis, a serious inflammatory response that can be fatal, has a poorly understood pathophysiology. The Metabolic syndrome (MetS), however, is associated with many cardiometabolic risk factors, many of which are highly prevalent in adults. It has been suggested that Sepsis may be associated with MetS in several studies. Therefore, this study investigated diagnostic genes and metabolic pathways associated with both diseases. In addition to microarray data for Sepsis, PBMC single cell RNA sequencing data for Sepsis and microarray data for MetS were downloaded from the GEO database. Limma differential analysis identified 122 upregulated genes and 90 downregulated genes in Sepsis and MetS. WGCNA identified brown co-expression modules as Sepsis and MetS core modules. Two machine learning algorithms, RF and LASSO, were used to screen seven candidate genes, namely, STOM, BATF, CASP4, MAP3K14, MT1F, CFLAR and UROD, all with an AUC greater than 0.9. XGBoost assessed the co-diagnostic efficacy of Hub genes in Sepsis and MetS. The immune infiltration results show that Hub genes were expressed at high levels in all immune cells. After performing Seurat analysis on PBMC from normal and Sepsis patients, six immune subpopulations were identified. The metabolic pathways of each cell were scored and visualized using ssGSEA, and the results show that CFLAR plays an important role in the glycolytic pathway. Our study identified seven Hub genes that serve as co-diagnostic markers for Sepsis and MetS and revealed that diagnostic genes play an important role in immune cell metabolic pathway.

Comprehensive analysis of senescence-associated genes in sepsis based on bulk and single-cell sequencing data.

Background: Sepsis is a pathological state resulting from dysregulated immune response in host during severe infection, leading to persistent organ dysfunction and ultimately death. Senescence-associated genes (SAGs) have manifested their potential in controlling the proliferation and dissemination of a variety of diseases. Nevertheless, the correlation between sepsis and SAGs remains obscure and requires further investigation. Methods: Two RNA expression datasets (GSE28750 and GSE57065) specifically related to sepsis were employed to filter hub SAGs, based on which a diagnostic model predictive of the incidence of sepsis was developed. The association between the expression of the SAGs identified and immune-related modules was analyzed employing Cell-type Identification By Estimating Relative Subsets Of RNA Transcripts (CIBERSORT) and Microenvironment Cell Populations-counter (MCP-counter) analysis. The identified genes in each cohort were clustered by unsupervised agreement clustering analysis and weighted gene correlation network analysis (WGCNA). Results: A diagnostic model for sepsis established based on hub genes (IGFBP7, GMFG, IL10, IL18, ETS2, HGF, CD55, and MMP9) exhibited a strong clinical reliability (AUC = 0.989). Sepsis patients were randomly assigned and classified by WGCNA into two clusters with distinct immune statuses. Analysis on the single-cell RNA sequencing (scRNA-seq) data revealed high scores of SAGs in the natural killer (NK) cells of the sepsis cohort than the healthy cohort. Conclusion: These findings suggested a close association between SAGs and sepsis alterations. The identified hub genes had potential to serve as a viable diagnostic marker for sepsis.

Construction of a prognostic model for triple-negative breast cancer based on immune-related genes, and associations between the tumor immune microenvironment and immunological therapy.

BACKGROUND: Triple-negative breast cancer (TNBC) is the subtype of breast cancer with the worst prognosis, and it is highly heterogeneous. There is growing evidence that the tumor immune microenvironment (TIME) plays a crucial role in tumor development, maintenance, and treatment responses. Notably however, the full effects of the TIME on prognosis, TIME characteristics, and immunotherapy responses in TNBC patients have not been fully elucidated. METHODS: Gene Expression Omnibus and The Cancer Genome Atlas data were used to data analysis. Single-cell sequencing and tissue microarray analysis were used to investigate gene expression. The concentrations and distributions of immune cell types were determined and analyzed using the CIBERSORT strategy. Tumor immune dysfunction and exclusion score and the IMvigor210 cohort were used to estimate the sensitivity of TNBC patients with different prognostic statuses to immune checkpoint treatment. RESULTS: Five immune-related genes associated with TNBC prognosis (IL6ST, NR2F1, CKLF, TCF7L2, and HSPA2) was identified and a prognostic evaluation model was constructed based on those genes. The respective areas under the curve of the prognostic nomogram model at 3 and 5 years were 0.791 and 0.859. The group with a lower nomogram score, with a better prognosis survival status and clinical treatment benefit rate. CONCLUSION: A prognostic model for TNBC that was closely related to the immune landscape and therapeutic responses was constructed. This model may help clinicians to make more precise and personalized treatment decisions pertaining to TNBC patients.