Identification of Molecular Targets and Underlying Mechanisms of Xiaoji Recipe against Pancreatic Cancer Based on Network Pharmacology.
Comput Math Methods Med
; 2022: 4640849, 2022.
Article
en En
| MEDLINE
| ID: mdl-36118824
Traditional Chinese medicine (TCM) is applied in the anticancer adjuvant therapy of various malignancies and pancreatic cancer included. Xiaoji recipe consists several TCM materials with anticancer activities. In our work, we intended to analyze the molecular targets as well as the underlying mechanisms of Xiaoji recipe against pancreatic cancer. A total of 32 active components and 522 potential targets of Xiaoji recipe were selected using the TCMSP and SwissTargetPrediction databases. The potential target gene prediction in pancreatic cancer was performed using OMIM, Disgenet, and Genecards databases, and totally, 998 target genes were obtained. The component-disease network was constructed using the Cytoscape software, and 116 shared targets of pancreatic cancer and Xiaoji recipe were screened out. As shown in the protein-protein interaction (PPI) network, the top 20 hub genes such as TP53, HRAS, AKT1, VEGFA, STAT3, EGFR, and SRC were further selected by degree. GO and KEGG functional enrichment analysis revealed that Xiaoji recipe may affect pancreatic cancer progression by targeting the PI3K/AKT and MAPK signaling pathways. Moreover, we performed in vitro assays to explore the effect of Xiaoji recipe on pancreatic cancer cells. The results revealed that Xiaoji recipe suppressed the viability and migration and promoted the apoptosis of pancreatic cancer cells via the inactivation of PI3K/AKT, MAPK, and STAT3 pathways. The findings of our study suggested the potential of Xiaoji recipe in the targeting therapy of pancreatic cancer.
Texto completo:
1
Bases de datos:
MEDLINE
Medicinas Tradicionales:
Medicinas_tradicionales_de_asia
/
Medicina_china
Asunto principal:
Neoplasias Pancreáticas
/
Fosfatidilinositol 3-Quinasas
Tipo de estudio:
Diagnostic_studies
/
Prognostic_studies
Idioma:
En
Revista:
Comput Math Methods Med
Año:
2022
Tipo del documento:
Article
País de afiliación:
China