Background:This study used network pharmacology method and cell model to assess the effects of Radix Astragali (RA) on cholangiocarcinoma (CCA) and to predict core targets and molecular mechanisms.
Material/Methods:We performed an in vitro study to assess the effect of RA on CCA using CCK8 assay, the Live-Cell Analysis System, and trypan blue staining. The components and targets of RA were analyzed using the Traditional Chinese Medicine Systems Pharmacology database, and genes associated with CCA were retrieved from the GeneCards and OMIM platforms. Protein-protein interactions were analyzed with the STRING platform. The componentstargets-disease network was built by Cytoscape. The TIMER database revealed the expression of core targets with diverse immune infiltration levels. GO and KEGG analyses were performed to identify molecular-biology processes and signaling pathways. The predictions were verified by Western blotting.
Results:Concentration-dependent antitumor activity was confirmed in the cholangiocarcinoma QBC939 cell line treated with RA. RA contained 16 active compounds, with quercetin and kaempferol as the core compounds. The most important biotargets for RA in CCA were caspase 3, MAPK8, MYC, EGFR, and PARP. The TIMER database revealed that the expression of caspase3 and MYC was related with diverse immune infiltration levels of CCA.The results of Western blotting showed RA significantly influenced the expression of the 5 targets that network pharmacology predicted.
Conclusions:RA is an active medicinal material that can be developed into a safe and effective multi-targeted anticancer treatment for CCA.
Colon adenocarcinoma (COAD) is one of the most common malignant tumors. Tumor mutation burden (TMB) has become an independent biomarker for predicting the response to immune checkpoint inhibitors (ICIs). miRNAs play an important role in cancer-related immune regulation. However, the relationship between miRNA expression and TMB in COAD remains unclear. Therefore, the transcriptome profiling data, clinical data, mutation annotation data, and miRNA expression profiles for cases of COAD were downloaded from the TCGA database. Subsequently, 323 COAD cases were randomly divided into training and test sets. The differential expression of miRNAs in the high and low TMB groups in the training set was obtained as a signature using the least absolute shrinkage and selection operator (LASSO) logistic regression and verified in the test set. Based on the LASSO method, principal component analysis (PCA), and ROC, we found that the signature was credible because it can discriminate between high and low TMB levels. In addition, the correlation between the 18-miRNA-based signature and immune checkpoints was performed, followed by qRT-PCR, to measure the relative expression of 18 miRNAs in COAD patients. The miRNA-based model had a strong positive correlation with TMB and a weak positive correlation with CTLA4 and CD274 (PD-L1). However, no correlation was observed between the model and SNCA (PD-1). Finally, enrichment analysis of the 18 miRNAs was performed to explore their biological functions. The results demonstrated that 18 miRNAs were involved in the process of immunity and cancer pathways. In conclusion, the 18-miRNA-based signature can effectively predict and discriminate between the different TMB levels of COAD and provide a guide for its treatment with ICIs.
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