Aurantio-obtusin, an anthraquinone compound, isolated from dried seeds of Cassia obtusifolia L. (syn. Senna obtusifolia; Fabaceae) and Cassia tora L. (syn. Senna tora). Although the biological activities of Semen Cassiae have been reported, the anti-inflammatory mechanism of aurantio-obtusin, its main compound, on RAW264.7 cells, remained unknown. We investigated the anti-inflammatory effect of aurantio-obtusin on lipopolysaccharide- (LPS)-induced RAW264.7 cells in vitro and elucidated the possible underlying molecular mechanisms. Nitric oxide production (NO) and prostaglandin E2 (PGE2) were measured by the Griess colorimetric method and enzyme-linked immunosorbent assay (ELISA), respectively. Protein expression levels of cyclooxygenase 2 (COX-2) were monitored by cell-based ELISA. Interleukin 6 (IL-6) and tumor necrosis factor-alpha (TNF-α) synthesis were analyzed using ELISA. The mRNA expression of nitric oxide synthase (iNOS), COX-2, and the critical pro-inflammatory cytokines (IL-6 and TNF-α) were detected by quantitative real-time PCR. Aurantio-obtusin significantly decreased the production of NO, PGE2, and inhibited the protein expression of COX-2, TNF-α and IL-6, which were similar to those gene expression of iNOS, COX-2, TNF-α and IL-6 (p < 0.01). Consistent with the pro-inflammatory gene expression, the Aurantio-obtusin efficiently reduced the LPS-induced activation of nuclear factor-κB in RAW264.7 cells. These results suggested that aurantio-obtusin may function as a therapeutic agent and can be considered in the further development of treatments for a variety of inflammatory diseases. Further studies may provide scientific evidence for the use of aurantio-obstusin as a new therapeutic agent for inflammation-related diseases.
The tumor microenvironment (TME) is of great clinical significance for predicting the therapeutic effect of tumors. Nonetheless, there was no systematic analysis of cellular interactions in the TME of head and neck cancer (HNSC). This study used gene expression data from 816 patients with HNSC to analyze the scores of 22 immune cells. On this basis, we have established a novel TMEscore-based prognostic risk model. The relationship between TMEscore and clinical and genomic characteristics was analyzed. The sample was divided into risk-H and risk-L groups based on the prognosis risk model of TMEscore, with significant differences in overall survival between the two groups (log rank p < 0.001). In terms of clinical features, the TMEscore is closely related to the T staging, Grade, and HPV. As for genomic characteristics, the genomic features of the Risk-H samples are a low expression of immune-related genes and high-frequency mutations of TP53 and CEP152. This model was validated in an external test set, in which the prognosis for Risk-H group and Risk-L group was also significantly different (log rank p = 0.017). A quantitative method of TME infiltration pattern is established, which may be a potential predictor of HNSC prognosis.
Salvia miltiorrhiza, known as Danshen, has attracted worldwide interest for its substantial effects on coronary heart disease (CHD). Danshensu (DSS) is one of the main active ingredients of Danshen on CHD. Although it has been proven to have a good clinical effect on CHD, the action mechanisms remain elusive. In the current study, a coexpression network-based approach was used to illustrate the beneficial properties of DSS in the context of CHD. By integrating the gene expression profile data and protein-protein interactions (PPIs) data, two coexpression protein interaction networks (CePIN) in a CHD state (CHD CePIN) and a non-CHD state (non-CHD CePIN) were generated. Then, shared nodes and unique nodes in CHD CePIN were attained by conducting a comparison between CHD CePIN and non-CHD CePIN. By calculating the topological parameters of each shared node and unique node in the networks, and comparing the differentially expressed genes, target proteins involved in disease regulation were attained. Then, Gene Ontology (GO) enrichment was utilized to identify biological processes associated to target proteins. Consequently, it turned out that the treatment of CHD with DSS may be partly attributed to the regulation of immunization and blood circulation. Also, it indicated that sodium/hydrogen exchanger 3 (SLC9A3), Prostaglandin G/H synthase 2 (PTGS2), Oxidized low-density lipoprotein receptor 1 (OLR1), and fibrinogen gamma chain (FGG) may be potential therapeutic targets for CHD. In summary, this study provided a novel coexpression protein interaction network approach to provide an explanation of the mechanisms of DSS on CHD and identify key proteins which maybe the potential therapeutic targets for CHD.
Background: This study aimed to investigate the intrinsic mechanisms of Qishen granules (QSG) in the treatment of HF, and to provide new evidence and insights for its clinical application. Material/Methods: Information on QSG ingredients was collected from Traditional Chinese medicine systems pharmacology (TCMSP), TCM@Taiwan, TCMID, and Batman, and input into SwissTargetPrediction to identify the compound targets. HF-related targets were detected from Therapeutic Target Database (TTD), Disgenet-Gene, Drugbank database, and Online Mendelian Inheritance in Man (OMIM) database. The overlap targets of QSG and HF were identified for pathway enrichment analysis by utilizing the Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis. The protein-protein interaction (PPI) network of QSG-HF was constructed, following by the generation of core targets, construction of core modules, and KEGG analysis of the core functional modules. Results: There were 1909 potential targets predicted from the 243 bioactive compounds in QSG which shared 129 common targets with HF-related targets. KEGG pathway analysis of common targets indicated that QSG could regulated 23 representative pathways. In the QSG-HF PPI network analysis, 10 key targets were identified, including EDN1, AGT, CREB1, ACE, CXCR4, ADRBK1, AGTR1, BDKRB1, ADRB2, and F2. Further cluster and enrichment analysis suggested that neuroactive ligand-receptor interaction, cGMP-PKG signaling pathway, renin secretion, vascular smooth muscle contraction, and the renin-angiotensin system might be core pathways of QSG for HF. Conclusions: Our study elucidated the possible mechanisms of QSG from a systemic and holistic perspective. The key targets and pathways will provide new insights for further research on the pharmacological mechanism of QSG.
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