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. 2022 May;28(5):425-433.
doi: 10.1007/s11655-021-3451-1. Epub 2021 Sep 21.

Mechanism of Fuzheng Kang'ai Formula Regulating Tumor Microenvironment in Non-Small Cell Lung Cancer

Yun-Ling Tian  1 , Song-Bo Fu  2 , Bo Li  2 , Ling-Yan Yuan  2 , Zhi-Tong Bing  3   4   5
Affiliations

Mechanism of Fuzheng Kang'ai Formula Regulating Tumor Microenvironment in Non-Small Cell Lung Cancer

Yun-Ling Tian et al. Chin J Integr Med. 2022 May.

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.

Keywords: Chinese medicine; Fuzheng Kang’ai Formula; lung adenocarcinoma; network pharmacology; prognosis; tumor microenvironment.

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