Comprehensive Molecular Analyses of a TNF Family-Based Gene Signature as a Potentially Novel Prognostic Biomarker for Cervical Cancer

Network Pharmacology-Integrated Molecular Docking Reveals the Expected Anticancer Mechanism of Picrorhizae Rhizoma Extract

This study sought to explore the anticancer mechanism of Picrorhizae Rhizoma (PR) extract based on network pharmacology and molecular docking. The potential chemicals of PR were screened through the Traditional Chinese Medicine Systems Pharmacology (TCMSP) database and relevant literatures. Corresponding targets of active ingredients were found with the help of the UniProtKB database, and therapeutic targets for cancer action were screened with the help of the GeneCards database. We used Cytoscape software to construct the compound-target-pathway network of PR extract. We utilized the STRING database to obtain the protein-protein interaction (PPI) network. We used DAVID database combining Gene Ontology (GO) analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis. Finally, molecular docking was employed for initial efficacy checking. We have identified 16 potential active components of PR through screening, involving 112 disease action targets. Utilizing the GeneCards database, 112 intersecting targets between PR extract and cancer were found, which mainly exerts anticancer effects by regulating tumor necrosis factor (TNF), recombinant caspase 3 (CASP3), c-Jun NH2-terminal kinase (JNK)/JUN, epidermal growth factor receptor (EGFR), and estrogen receptor-1 (ESR1) with some other target genes and pathways associated with cancer. The major anticancer species are prostate cancer, colorectal cancer, small cell lung cancer, etc. In the molecular docking study, herbactin had a strong affinity for TNF. Based on network pharmacology and molecular docking studies, PR and their compounds have demonstrated potential anticancer activities against several key targets. Our preliminary findings provide a strong foundation for further experiments with PR constituents.

Identification of potential predictive biomarkers and biological pathways and the correction with immune infiltration in the activation of Crohn's disease

Crohn's disease (CD), a subtype of inflammatory bowel disease (IBD), has increasing prevalence in the world. Due to the lack of cure strategy, most patients with CD develop progressive disease companying with a series of serious complications. Therefore, exploring molecular mechanism differences between active and inactive CD will help in the screening of predict markers and therapeutic targets. In this study, we analyzed differentially expressed genes (DEGs) and molecular pathways through between active and inactive CD patients. In addition, the abundance of 22 immune cell types were assessed by using the CIBERSORT. The hub DEGs were screened out by the CytoHubba in Cytoscape, followed by the least absolute shrinkage and selection operator (LASSO) regression. Finally, the clinical predictive model was constructed by binary logistic regression model. The diagnostic efficacy was tested by receiver operating characteristic (ROC) curve and verified in independent datasets. The results showed that there were 137 DEGs between the active and inactive CD. Most of them were involved in regulating the immunity process. In addition, the decreased abundance of CD8 T cells and the increased abundance of M0, M1 macrophages, and neutrophils were closely related to CD activation. CXCL9, C3AR1, IL1B, and TLR4 were the hub gene and can be applied to the prediction of CD activation. Our results provided important targets for the prediction of CD activation and the selection of therapeutic targets.