Mechanism of Fuzheng Kang'ai Formula Regulating Tumor Microenvironment in Non-Small Cell Lung Cancer.
10.1007/s11655-021-3451-1
- Author:
Yun-Ling TIAN
1
,
2
;
Song-Bo FU
3
;
Bo LI
3
;
Ling-Yan YUAN
3
;
Zhi-Tong BING
4
Author Information
1. Department of Endocrinology and Metabolism, the First Hospital of Lanzhou University, Lanzhou, 730000, China. yunlingtian7318@
2. com.
3. Department of Endocrinology and Metabolism, the First Hospital of Lanzhou University, Lanzhou, 730000, China.
4. Evidence Based Medicine Center, School of Basic Medical Science of Lanzhou University, Lanzhou, 730000, China.
- Publication Type:Journal Article
- Keywords:
Chinese medicine;
Fuzheng Kang’ai Formula;
lung adenocarcinoma;
network pharmacology;
prognosis;
tumor microenvironment
- MeSH:
Actins;
Adenocarcinoma of Lung/pathology*;
Carcinoma, Non-Small-Cell Lung/metabolism*;
Chromosomal Proteins, Non-Histone;
DNA-Binding Proteins;
Drugs, Chinese Herbal/therapeutic use*;
Humans;
Lung Neoplasms/metabolism*;
Tumor Microenvironment
- From:
Chinese journal of integrative medicine
2022;28(5):425-433
- CountryChina
- Language:English
-
Abstract:
OBJECTIVE:To study the mechanism of Chinese herbal medicine Fuzheng Kang'ai Formula (, FZKA) on tumor microenvironment (TME).
METHODS:CIBERSORTx was used for analysis of TME. Traditional Chinese Medicine Systems Pharmacology and Analysis Platform was applied to identify compounds-targets network and the Cancer Genome Atlas (TCGA) was employed to identify the differential expression genes (DEGs) between tumor and paracancerous tissues in lung adenocarcinoma (LUAD) from TCGA-LUAD. Additionally, DEGs with prognosis in LUAD was calculated by univariable and multivariate Cox regression. The core targets of FZKA were analyzed in lung adenocarcinoma TME. Protein-protein interaction database was employed to predict down-stream of target. Quantitative reverse transcription polymerase chain reaction was employed for biological experiment in A549, H1299 and PC9 cell lines.
RESULTS:The active and resting mast cells were significantly associated with prognosis of LUAD (P<0.05). Of the targets, CCNA2 as an important target of FZKA (hazard ratio=1.41, 95% confidential interval: 1.01-2.01, P<0.05) was a prognostic target and significantly associated with mast cells. CCNA2 was positively correlated with mast cell activation and negatively correlated with mast cell resting state. BCL1L2, ACTL6A and ITGAV were down-stream of CCNA2, which were validated by qRT-PCR in A549 cell.
CONCLUSION:FZKA could directly bind to CCNA2 and inhibit tumor growth by regulating CCNA2 downstream genes and TME of NSCLC closely related to CCNA2.
