The pharmacological mechanism of Chinese herbs effective in treating advanced ovarian cancer: Integrated meta-analysis and network pharmacology analysis

Ze Yang; Xiang Wang; Wei Hong; Shiyi Zhang; Yang Yang; Yongliang Xia; Ruiwen Yang

doi:10.3389/fphar.2022.1040641

The pharmacological mechanism of Chinese herbs effective in treating advanced ovarian cancer: Integrated meta-analysis and network pharmacology analysis

Front Pharmacol. 2022 Nov 9:13:1040641. doi: 10.3389/fphar.2022.1040641. eCollection 2022.

Authors

Ze Yang¹, Xiang Wang², Wei Hong¹, Shiyi Zhang¹, Yang Yang³, Yongliang Xia⁴, Ruiwen Yang⁴

Affiliations

¹ The First Clinical Medical College, Zhejiang Chinese Medical University, Hangzhou, China.
² Department of Orthopedics, Tongde Hospital of Zhejiang Province, Hangzhou, China.
³ Department of Traditional Chinese Medicine, Neighborhood Good Doctor No. 6 Street Clinic, Hangzhou, China.
⁴ Health Management Center, The First Affiliated Hospital of Zhejiang Chinese Medical University (Zhejiang Provincial Hospital of Chinese Medicine), Hangzhou, China.

Abstract

Background: Advanced ovarian cancer (AOC) develops rapidly, adding to difficulties in treatment. Traditional Chinese medicine (TCM) plays a significant role in the treatment of AOC, and so to explore the efficacy and safety of TCM in the treatment of AOC and its effective targets, we performed the following review. Methods: The major databases were searched for randomized controlled trials of TCM for the treatment of AOC. A meta-analysis of the efficacy of Chinese herbs on AOC was conducted using RevMan 5.4 software. Active compounds and target genes were acquired using the TCMSP database. The main targets of AOC were obtained through the GenCards, OMIM, TTD, and DrugBank databases. A protein-protein interaction network carried out on the STRING platform was used to select core genes. The Metascape platform was applied to achieve GO and KEGG enrichment analysis. Results: A total of 24 studies were included. Meta-analysis shows the TCM group improved the overall response rate (OR = 2.71; 95% CI = [2.14, 3.44], Z = 8.25, p < 0.00001), overall survival (OR = 2.93, 95% CI = [2.03, 4.24], Z = 5.72, p < 0.00001), and progression-free survival (OR = 5.36, 95% CI = [5.03, 5.69], Z = 31.88, p < 0.00001) of AOC patients, as well as reducing many adverse events. There were 120 compounds, 246 herb target genes, and 1503 disease targets extracted. The 10 most important components were quercetin, kaempferol, 7-methoxy-2-methyl isoflavone, formononetin, isorhamnetin, hederagenin, stigmasterol, luteolin, 7-O-methylisomucronulatol, and calycosin. The 20 core targets were TP53, STAT3, JUN, AKT1, MAPK3, RELA, MAPK1, ESR1, IL6, FOS, MAPK14, TNF, CDKN1A, RB1, CCND1, EGFR, STAT1, MDM2, MAPK8, and CAV1. KEGG enrichment analysis showed that there are many pathways directly related to different types of tumors, such as in pathway cancer and prostate cancer. Conclusion: Our article reveals TCM is effective and safe against AOC and that Chinese herbs exert effects on the disease through multi-target, multi-component, and multi-pathway mechanisms. Systematic Review Registration: (www.crd.york.ac.uk/PROSPERO/), identifier (CRD42022369731).

Keywords: advanced ovarian cancer; meta-analysis; network pharmacology analysis; review; traditional Chinese medicine.

Publication types

Systematic Review