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. 2018 Nov 6;18(1):293.
doi: 10.1186/s12906-018-2347-x.

Investigate the mechanisms of Chinese medicine Fuzhengkangai towards EGFR mutation-positive lung adenocarcinomas by network pharmacology

Zhitong Bing  1   2   3 , Zhiyuan Cheng  1   2 , Danfeng Shi  4 , Xinkui Liu  5 , Jinhui Tian  1   2 , Xiaojun Yao  4 , Jingyun Zhang  1   2 , Yongfeng Wang  6 , Kehu Yang  7   8
Affiliations

Investigate the mechanisms of Chinese medicine Fuzhengkangai towards EGFR mutation-positive lung adenocarcinomas by network pharmacology

Zhitong Bing et al. BMC Complement Altern Med. .

Abstract

Background: Chinese traditional herbal medicine Fuzhengkangai (FZKA) formulation combination with gefitinib can overcome drug resistance and improve the prognosis of lung adenocarcinoma patients. However, the pharmacological and molecular mechanisms underlying the active ingredients, potential targets, and overcome drug resistance of the drug are still unclear. Therefore, it is necessary to explore the molecular mechanism of FZKA.

Methods: A systems pharmacology and bioinformatics-based approach was employed to investigate the molecular pathogenesis of EGFR-TKI resistance with clinically effective herb formula. The differential gene expressions between EGFR-TKI sensitive and resistance cell lines were calculated and used to find overlap from targets as core targets. The prognosis of core targets was validated from the cancer genome atlas (TCGA) database by Cox regression. Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment is applied to analysis core targets for revealing mechanism in biology.

Results: The results showed that 35 active compounds of FZKA can interact with eight core targets proteins (ADRB2, BCL2, CDKN1A, HTR2C, KCNMA1, PLA2G4A, PRKCA and LYZ). The risk score of them were associated with overall survival and relapse free time (HR = 6.604, 95% CI: 2.314-18.850; HR = 5.132, 95% CI: 1.531-17.220). The pathway enrichment suggested that they involved in EGFR-TKI resistance and non-small cell lung cancer pathways, which directly affect EGFR-TKI resistance. The molecular docking showed that licochalcone a and beta-sitosterol can closely bind two targets (BCL2 and PRKCA) that involved in EGFR-TKI resistance pathway.

Conclusions: This study provided a workflow for understanding mechanism of CHM for against drug resistance.

Keywords: Fuzhengkangai formula; Herbal medicines; Molecular docking; Systems pharmacology.

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Figures

Fig. 1
Fig. 1
Flowchart of data analysis
Fig. 2
Fig. 2
A compound node and a protein node are linked if the protein is targeted by the corresponding compound. Node size is proportional to its degree
Fig. 3
Fig. 3
The information of DEGs and pathway of DEGs. a Volcano plot represents DEGs. b Heatmap of DEGs between sensitive and resistance groups. c KEGG enrichment of DEGs
Fig. 4
Fig. 4
Expression of core genes and subnetwork of core genes. a Heatmap of core genes in EGFR-TKI resistance and sensitive groups. b boxplot of each core gene between two groups. c Subnetwork of compounds and targets. The triangles represent different compounds and different color represent herbs that include the compounds. d The compound-pathway interaction network is constructed by compound and the pathway that consisted of core targets. Red lines represent compounds directly related to drug resistance
Fig. 5
Fig. 5
Core genes prognostic validation in LUAD with EGFR-mutation cohort. a Kaplan-Meier survival curve of sensitive and resistance groups for overall survival. b RS distribution in all mutation patients. c AUC of ROC for predicting RS of OS (AUC = 0.853). d Kaplan-Meier survival curve of sensitive and resistance groups for disease free survival. e RS distribution in all mutation patients with disease free survival information. f AUC of ROC for predicting RS of DFS (AUC = 0.746)
Fig. 6
Fig. 6
KEGG enrichment of core genes. a KEGG pathway enrichment of core genes. b. EGFR tyrosine kinase inhibitor resistance pathway. c Non-small cell lung cancer pathway
Fig. 7
Fig. 7
The binding sites of PRKCA and BCL2. a Three-dimension structure of PRKCA. b Three-dimension structures of BCL2. The proteins are shown in green cartoon and the co-crystalized inhibitors are shown in orange sticks
Fig. 8
Fig. 8
The interactive modes of beta-sitosterol, beta-carotene, licochalcone a with BCL2. a beta-sitosterol binding on the pocket of BCL2. b beta-carotene binding on the pocket of BCL2. c licochalcone a binding on the pocket of BCL2. d the three-dimensional representation of the binding mode of licochalcone a with BCL2. The residues in the binding site are shown in green sticks and licochalcone a is shown in orange sticks. e the electrical characteristics of the surrounding residues of licochalcone a and the interaction between licochalcone a and BCL2. The green, cyan, red, blue circles represent hydrophobic, polar, negative-charged, positive-charged residues
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