Examining the effector mechanisms of Xuebijing injection on COVID-19 based on network pharmacology.

BACKGROUND: Chinese medicine Xuebijing (XBJ) has proven to be effective in the treatment of mild coronavirus disease 2019 (COVID-19) cases. But the bioactive compounds and potential mechanisms of XBJ for COVID-19 prevention and treatment are unclear. This study aimed to examine the potential effector mechanisms of XBJ on COVID-19 based on network pharmacology. METHODS: We searched Chinese and international papers to obtain the active ingredients of XBJ. Then, we compiled COVID-19 disease targets from the GeneCards gene database and via literature searches. Next, we used the SwissTargetPrediction database to predict XBJ's effector targets and map them to the abovementioned COVID-19 disease targets in order to obtain potential therapeutic targets of XBJ. Cytoscape software version 3.7.0 was used to construct a "XBJ active-compound-potential-effector target" network and protein-protein interaction (PPI) network, and then to carry out network topology analysis of potential targets. We used the ClueGO and CluePedia plugins in Cytoscape to conduct gene ontology (GO) biological process (BP) analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) signaling pathway enrichment analysis of XBJ's effector targets. We used AutoDock vina and PyMOL software for molecular docking. RESULTS: We obtained 144 potential COVID-19 effector targets of XBJ. Fourteen of these targets-glyceraldehyde 3-phosphate dehydrogenase (GAPDH), albumin (ALB), tumor necrosis factor (TNF), epidermal growth factor receptor (EGFR), mitogen-activated protein kinase 1 (MAPK1), Caspase-3 (CASP3), signal transducer and activator of transcription 3 (STAT3), MAPK8, prostaglandin-endoperoxide synthase 2 (PTGS2), JUN, interleukin-2 (IL-2), estrogen receptor 1 (ESR1), and MAPK14 had degree values > 40 and therefore could be considered key targets. They participated in extracellular signal-regulated kinase 1 and 2 (ERK1, ERK2) cascade, the T-cell receptor signaling pathway, activation of MAPK activity, cellular response to lipopolysaccharide, and other inflammation- and immune-related BPs. XBJ exerted its therapeutic effects through the renin-angiotensin system (RAS), nuclear factor κ-light-chain-enhancer of activated B cells (NF-κB), MAPK, phosphatidylinositol-4, 5-bisphosphate 3-kinase (PI3K)-protein kinase B (Akt)-vascular endothelial growth factor (VEGF), toll-like receptor (TLR), TNF, and inflammatory-mediator regulation of transient receptor potential (TRP) signaling pathways to ultimately construct a "drug-ingredient-target-pathway" effector network. The molecular docking results showed that the core 18 effective ingredients had a docking score of less than - 4.0 with those top 10 targets. CONCLUSION: The active ingredients of XBJ regulated different genes, acted on different pathways, and synergistically produced anti-inflammatory and immune-regulatory effects, which fully demonstrated the synergistic effects of different components on multiple targets and pathways. Our study demonstrated that key ingredients and their targets have potential binding activity, the existing studies on the pharmacological mechanisms of XBJ in the treatment of sepsis and severe pneumonia, could explain the effector mechanism of XBJ in COVID-19 treatment, and those provided a preliminary examination of the potential effector mechanism in this disease.

The Prognostic Value of Autophagy-Related Markers Bclin-1 and LC-3 in Colorectal Cancers: A Systematic Review and Meta-analysis.

OBJECTIVE: At present, the relationship between autophagosomes and the prognosis of various cancers has become a subject of active investigation. A series of studies have demonstrated the correlation between autophagy microtubule-associated protein light chain 3 (LC-3), Beclin-1, and colorectal cancer (CRC). Since autophagy has dual regulatory roles in tumors, the results of this correlation are also uncertain. Hence, we summarized the relationship between Beclin-1, LC-3, and CRC using systematic reviews and meta-analysis to clarify their prognostic significance in it. METHODS: PubMed, EMBASE, Cochrane Library, and Web of Science databases were searched online up to April 1, 2019. The quality of the involving studies was assessed against the Newcastle-Ottawa Scale (NOS). Pooled hazard ratio (HR) and 95% confidence interval (CI) in a fixed or random effects model were used to assess the strength of correlation between Beclin-1, LC-3, and CRC. RESULTS: A total of 9 articles were collected, involving 2,297 patients. Most literatures scored more than 6 points, suggesting that the quality of our including research was acceptable. Our finding suggested that the expression of Beclin-1 was not associated with overall survival (HR = 0.68, 95% CI (0.31-1.52), P=0.351). Nonetheless, LC-3 expression exerted significant impact on OS (HR = 0.51, 95% CI (0.35-0.74), P < 0.05). Subgroup analysis exhibited that Beclin-1 expression was associated with OS at TNM stage III (HR = 0.04, 95% CI = 0.02-0.08, P < 0.05), surgical treatment (HR = 1.53, 95% CI (1.15-2.02), P=0.003), and comprehensive treatment (HR = 0.27 95% CI (0.08-0.92), P=0.036), respectively. Similarly, the results showed the increased LC-3 expression in CRC was related to OS in multivariate analyses (HR = 0.44, 95% CI (0.34-0.57), P < 0.05), stages (HR = 0.51, 95% CI (0.35-0.74), P < 0.05), and comprehensive treatment (HR = 0.44, 95% CI (0.34-0.57), P < 0.05). CONCLUSIONS: Autophagy-related proteins of LC-3 might be an important marker of CRC progression. However, since the number of the original studies was limited, more well-designed, large-scale, high-quality studies are warranted to provide more convincing and reliable information.

Nomogram to predict overall survival and disease-specific survival with appendiceal mucinous adenocarcinoma.

To predict the survival of appendiceal mucinous adenocarcinoma (AMA) by prognostic nomogram.A total of 3234 patients with AMA were collected from the Surveillance, Epidemiology, and End Results (SEER) database from 1973 to 2015. Univariate and multivariate Cox proportional hazards (PH) regression analyses were used to generate independent prognostic factors. These variables were included in the nomogram to predict overall survival (OS) and disease-specific survival (DSS) at 1-, 3-, and 5- years. These data are validated both internally and externally. The consistency index (C-index) and calibration chart were used to estimate the accuracy of the nomogram.The study cohort was randomly divided into the training (n = 2155) and validation group (n = 1799). According to univariate and multivariate analyses, age at diagnosis, marital status, sex, histological differentiation, SEER extent of disease, number of local lymph nodes examined, whether they were positive, and surgical methods were independent prognostic factors for OS and DSS. These factors were incorporated into the nomogram. Internal validation in the training cohort showed that the C-index values for nomogram predictions of OS and DSS were 0.73 (95% CI 0.70-0.76) and 0.77 (95% CI 0.73-0.81), respectively. Similarly, the corresponding C-index values in the external validation cohort were 0.76 (95% CI 0.70-0.81) and 0.75 (95% CI 0.71-0.80). The Calibration plots revealed that the actual survival and nomogram prediction had a good consistency.Build a nomogram in the SEER database to predict OS and DSS in patients with AMA. It can provide accurate and personalised survival prediction for clinicians and patients.