Anterior Gradient 2 is a Significant Prognostic Biomarker in Bone Metastasis of Breast Cancer.

Background: The study aimed to detect DEGs associated with BRCA bone metastasis, filter prognosis biomarkers, and explore possible pathways. Methods: GSE175692 dataset was used to detect DEGs between BRCA bone metastatic cases and non-bone metastatic cases, followed by the construction of a PPI network among DEGs. The main module among the PPI network was then determined and pathway analysis on genes within the module was performed. Through performing Cox regression, Kaplan-Meier, nomogram, and ROC curve analyses using GSE175692 and GSE124647 datasets at the same time, the most significant prognostic biomarker was gradually filtered. Finally, important pathways associated with prognostic biomarkers were explored by GSEA analysis. Results: The 74 DEGs were detected between bone metastasis and non-bone metastasis groups. A total of 15 nodes were included in the main module among the whole PPI network and they mainly correlated with the IL-17 signaling pathway. We then performed Cox analysis on 15 genes using two datasets and only enrolled the genes with p < 0.05 in Cox analysis into the further analyses. Kaplan-Meier analyses using two datasets showed that the common biomarker AGR2 expression was related to the survival time of BRCA metastatic cases. Further, the nomogram determined the greatest contribution of AGR2 on the survival probability and the ROC curve revealed its optimal prognostic performance. More importantly, high expression of AGR2 prolonged the survival time of BRCA bone metastatic patients. These results all suggested the importance of AGR2 in metastatic BRCA. Finally, we performed the GSEA analysis and found that AGR2 was negatively related to IL-17 and NF-kß signaling pathways. Conclusion: AGR2 was finally determined as the most important prognostic biomarker in BRCA bone metastasis, and it may play a vital role in cancer progression by regulating IL-17 and NF-kB signaling pathways.

Pharmacological activation of PPAR gamma ameliorates vascular endothelial insulin resistance via a non-canonical PPAR gamma-dependent nuclear factor-kappa B trans-repression pathway.

Vascular endothelial insulin resistance (IR) is a critically initial factor in cardiocerebrovascular events resulted from diabetes and is becoming a worldwide public health issue. Thiazolidinediones (TZDs) are clinical insulin-sensitizers acting through a canonical peroxisome proliferator-activated receptor gamma (PPARγ)-dependent insulin trans-activation pathway. However, it remains elusive whether there are other mechanisms. In current study, we investigated whether TZDs improve endothelial IR induced by high glucose concentration or hyperglycemia via a non-canonical PPARγ-dependent nuclear factor-kappa B (NF-κB) trans-repression pathway. Our results showed that pre-treatment with TZDs dramatically decrease the susceptibility of endothelial cell to IR, while post-treatment notably improve the endothelial IR both in vitro and in vivo. Moreover, TZDs substantially increase the levels of endothelial nitric oxide synthase (eNOS) and inhibitory κB alpha (IκBα), whereas decrease those of the phosphorylated inhibitory κB kinase alpha/beta (phosphor-IKKα/ß) and the cytokines including tumor necrosis factor alpha (TNFα), interleukin-6 (IL-6), soluble intercellular adhesion molecule-1 (sICAM-1) and soluble vascular cellular adhesion molecule-1 (sVCAM-1), suggesting that TZDs act indeed through a PPARγ-dependent NF-κB trans-repression pathway. These findings highlighted a non-canonical mechanism for TZDs to ameliorate endothelial IR which might provide a potential strategy to prevent and treat the diabetic vascular complications clinically.