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.

Background: Sarcomas, cancers originating from mesenchymal cells, are comprehensive tumors with poor prognoses, yet their tumorigenic mechanisms are largely unknown. In this study, we characterize infiltrating immune cells and analyze immune scores to identify the molecular mechanism of immunologic response to sarcomas.Method: The “CIBERSORT” algorithm was used to calculate the amount of L22 immune cell infiltration in sarcomas. Then, the “ESTIMATE” algorithm was used to assess the “Estimate,” “Immune,” and “Stromal” scores. Weighted gene co-expression network analysis (WGCNA) was utilized to identify the significant module related to the immune therapeutic target. Gene ontology (GO) enrichment and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses were performed using the “clusterProfiler” package in R for annotation and visualization.Results: Macrophages were the most common immune cells infiltrating sarcomas. The number of CD8 T cells was negatively associated with that of M0 and M2 macrophages, and positively associated with M macrophages in sarcomas samples. The clinical parameters (disease type, gender) significantly increased with higher Estimate, Immune, and Stromal scores, and with a better prognosis. The blue module was significantly associated with CD8 T cells. Functional enrichment analysis showed that the blue module was mainly involved in chemokine signaling and the PI3K-Akt signaling pathway.CD48, P2RY10andRASAL3were identified and validated at the protein level.Conclusion: Based on the immune cell infiltration and immune microenvironment, three key genes were identified, thus presenting novel molecular mechanisms of sarcoma metastasis.

Objective. The mechanism of Panax notoginseng in treating myocardial fibrosis (MF) was investigated using network pharmacology. Methods. Effective ingredients and potential targets of Panax notoginseng were screened in relevant databases to construct a compound-target network. Targets of MF were then screened to select common targets and construct a protein-protein interaction network. This was followed by Gene Ontology and pathway enrichment analyses. Molecular docking then verified the results of network analysis. Results. A total of 14 effective ingredients and 119 potential targets for MF were predicted. Quercetin, beta-sitosterol, and gossypetin were speculated to be the main active ingredients. The mechanism of action may be related to AGE-RAGE, proteoglycans, and IL-17 signaling pathways. Five key targets (IL6, ALB, AKT1, TNF, and VEGFA) may be involved in the treatment of MF using Panax notoginseng. Conclusions. This study embodies the complex network relationship of multicomponents, multitargets, and multipathways of Panax notoginseng in treating MF and provides a novel method for further research on this herbs mechanism.

Inflammation, a protective response against infection and injury, involves a variety of biological processes. Sophorae Flavescentis (Kushen) is a promising Traditional Chinese Medicine (TCM) for treating inflammation, but the pharmacological mechanism of Kushen’s anti-inflammatory effect has not been fully elucidated. The bioactive compounds, predicted targets, and inflammation-related targets of Kushen were obtained from open source databases. The “Component-Target” network and protein–protein interaction (PPI) network were constructed, and hub genes were screened out by topological analysis. Gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses were performed on genes in the PPI network. Furthermore, nitric oxide (NO) production analysis, RT-PCR, and western blot were performed to detect the mRNA and protein expression of hub genes in LPS-induced RAW264.7 cells. An immunofluorescence assay found that NF-κB p65 is translocated. A total of 24 bioactive compounds, 465 predicted targets, and 433 inflammation-related targets were identified and used to construct “Component-Targets” and PPI networks. Then, the five hub genes with the highest values-IL-6, IL-1β, VEGFA, TNF-α, and PTGS2 (COX-2)- were screened out. Enrichment analysis results suggested mainly involved in the NF-κB signaling pathway. Moreover, experiments were performed to verify the predicted results. Kushen may mediate inflammation mainly through the IL-6, IL-1β, VEGFA, TNF-α, and PTGS2 (COX-2), and the NF-κB signaling pathways. This finding will provide clinical guidance for further research on the use of Kushen to treat inflammation.

Background: Osteosarcoma (OS) is a common malignant bone tumor originating in the interstitial tissues and occurring mostly in adolescents and young adults. Energy metabolism is a prerequisite for cancer cell growth, proliferation, invasion, and metastasis. However, the gene signatures associated with energy metabolism and their underlying molecular mechanisms that drive them are unknown. Methods: Energy metabolism-related genes were obtained from the TARGET database. We applied the “NFM” algorithm to classify putative signature gene into subtypes based on energy metabolism. Key genes related to progression were identified by weighted co-expression network analysis (WGCNA). Based on least absolute shrinkage and selection operator (LASSO) Cox proportional regression hazards model analyses, a gene signature for the predication of OS progression and prognosis was established. Robustness and estimation evaluations and comparison against other models were used to evaluate the prognostic performance of our model. Results: Two subtypes associated with energy metabolism was determined using the “NFM” algorithm, and significant modules related to energy metabolism were identified by WGCNA. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) suggested that the genes in the significant modules were enriched in kinase, immune metabolism processes, and metabolism-related pathways. We constructed a seven-gene signature consisting of SLC18B1, RBMXL1, DOK3, HS3ST2, ATP6V0D1, CCAR1, and C1QTNF1 to be used for OS progression and prognosis. Upregulation of CCAR1, and C1QTNF1 was associated with augmented OS risk, whereas, increases in the expression SCL18B1, RBMXL1, DOK3, HS3ST2, and ATP6VOD1 was correlated with a diminished risk of OS. We confirmed that the seven-gene signature was robust, and was superior to the earlier models evaluated; therefore, it may be used for timely OS diagnosis, treatment, and prognosis. Conclusions: The seven-gene signature related to OS energy metabolism developed here could be used in the early diagnosis, treatment, and prognosis of OS.