RESUMEN
The identification of network targets is one of the core issues used to reveal the molecular mechanism of traditional Chinese medicine (TCM) and is also the grand challenge of modernization of TCM. In this study, a protein-protein interaction (PPI) network was constructed based on the integration of network pharmacology and metabolomics, which was used as an effective approach to elucidate the relationship between disease pathway proteins and the targets of active small-molecule compounds. The intermolecular transfer process of the drug effect of active compounds in Salvia miltiorrhiza (SM) was revealed and visualized using the PPI network. Our study indicates that PTGS2 was the most important disease protein regulated by the active compounds in SM. Furthermore, the drug targets that can be linked to PTGS2 were regarded as direct targets and the direct targets of the active compounds were identified, respectively. Western blot and co-immuno precipitation (Co-IP) were used to verify the results of the network analysis and reveal the intermolecular transfer process of the effect of Tan IIA. Biological validation revealed that Tan IIA-EDN1-PTGS2-anandamide was a major intervention way of Tan IIA on early atherosclerosis (AS). This work provides a new perspective for the discovery of drug targets and the specific approaches regulated by the active compounds in SM on disease pathway proteins, which is beneficial for understanding the mechanism of action of bioactive compounds and expanding their clinical applications.
RESUMEN
Objective: To explore the clinical application value of prognostic nutritional index(PNI) for predicting overall survival(OS) in patients with advanced non-small cell lung cancer (NSCLC). Methods: 123 patients with histologically confirmed non-small cell lung cancer were enrolled in this study, and their clinical and laboratory data were reviewed. The PNI was calculated as 10×serum albumin value+ 5×total lymphocyte countin peripheral blood.Univariate and multivariate analyses were used to identify the potential prognostic factors for advanced NSCLC. Results: PNI of the 123 NSCLC patients was 46.24±6.56. PNI was significantly associated with age, weight loss and pleural effusion (P<0.05). However, it showed no relationship with sex, smoking, hemoptysis, chest pain, dyspnea, histological type, clinical stage, and administration of chemotherapy (P>0.05). The median OS of the 123 patients was 19.5 months. The median OS in the higher PNI group (PNI≥46.24) and lower PNI group(PNI<46.24) were 25.2 months and 16.4 months, respectively.The 1-year survival rates were 80.6% and 63.9%, and 2-year survival rates were 54.8% and 19.6%, respectively (P<0.01). Univariate analysis showed that PNI, age, dyspnea, and weight loss were related to the OS of the advanced NSCLC patients (P<0.05). Multivariate analysis identified PNI as an independent prognostic factor for OS of advanced NSCLC (P<0.001). Conclusion: PNI can be easily calculated, and may be used as a relatively new prognostic indicator for advanced NSCLC in clinical practice.