ORIGINAL RESEARCH article

Front. Pharmacol., 18 November 2020

Sec. Ethnopharmacology

Volume 11 - 2020 | https://doi.org/10.3389/fphar.2020.558471

A Combined Phytochemistry and Network Pharmacology Approach to Reveal the Effective Substances and Mechanisms of Wei-Fu-Chun Tablet in the Treatment of Precancerous Lesions of Gastric Cancer

  • 1. Key Laboratory of Liver and Kidney Diseases (Ministry of Education), Institute of Liver Diseases, Shuguang Hospital, Shanghai University of Traditional Chinese Medicine, Shanghai, China

  • 2. Central Research Institute, Shanghai Pharmaceuticals Holding Co., Ltd., Shanghai, China

  • 3. The MOE Key Laboratory for Standardization of Chinese Medicines and the SATCM Key Laboratory for New Resources and Quality Evaluation of Chinese Medicines, Institute of Chinese Materia Medica, Shanghai University of Traditional Chinese Medicine, Shanghai, China

  • 4. Shanghai Zhonghua Pharmaceutical Co., Ltd., Shanghai, China

  • 5. Huqingyutang Chinese Medicine Modernization Research Institute of Zhejiang Province, Hangzhou, China

Abstract

Wei-Fu-Chun (WFC) tablet is a commercial medicinal product approved by China Food and Drug Administration, which is made of Panax ginseng C.A.Mey., Citrus aurantium L., and Isodon amethystoides (Benth.). WFC has been popularly used for the treatment of precancerous lesions of gastric cancer (PLGC) in clinical practice. In this study, a UHPLC-ESI-Q-TOF/MS method in both positive and negative ion mode was employed to rapidly survey the major constituents of WFC. 178 compounds including diterpenoids, triterpenes, sesquiterpenes, flavonoids, saponins, phenylpropanoids, lignans, coumarins, organic acids, fatty acids, quinones, and sterols, were identified by comparing their retention times, accurate mass within 5 ppm error, and MS fragmentation ions. In addition, 77 absorbed parent molecules and nine metabolites in rat serum were rapidly characterized by UHPLC-ESI-Q-TOF/MS. The network pharmacology method was used to predict the active components, corresponding therapeutic targets, and related pathways of WFC in the treatment of PLGC. Based on the main compounds in WFC and their metabolites in rat plasma and existing databases, 13 active components, 48 therapeutic targets, and 61 pathways were found to treat PLGC. The results of PLGC experiment in rats showed that WFC could improve the weight of PLGC rats and the histopathological changes of gastric mucosa partly by inhibiting Mitogen-activated protein kinase (MAPK) signaling pathway to increase pepsin secretion. This study offers an applicable approach to identify chemical components, absorbed compounds, and metabolic compounds in WFC, and provides a method to explore bioactive ingredients and action mechanisms of WFC.

Introduction

Traditional Chinese medicine (TCM) is based on the principle of holism, that is, all the body systems are interconnected. Thus, TCM treatments can be multi-target, multi-link, and with minimal side-effects in the prevention and treatment of precancerous lesions of gastric cancer (PLGC), among other diseases. The Wei-Fu-Chun (WFC) tablet, a well-known Chinese herbal preparation, is composed of three herbs: P. ginseng (HS: 131 g), C. aurantium (ZQ: 250 g), and I. amethystoides (XCC: 2,500 g). Dosage of these herbs was derived from Chinese Pharmacopoeia, 2020 edition. In the first part of this edition, WFC was mentioned to tonify spleen qi, promote blood circulation and detoxification, and to have been employed to treat PLGC in clinic for many years (Jin et al., 2015). PLGC is a group of diseases with pathological features of intestinal metaplasia or dysplasia based on chronic atrophic gastritis (Correa et al., 1975). PLGC is an important stage in the development of superficial gastritis to gastric cancer. According to the Chinese Cancer Statistics released by the Chinese Cancer Registry, the mortality rate of gastric cancer ranked second in China, following lung cancer. (Chen et al., 2016). Therefore, clinically halting the progression of PLGC to gastric cancer or reversing it has been the focus of current academic research. Some studies investigated the mechanisms of WFC to treat gastritis in vitro or in vivo (Zhao et al., 2012; Huang et al., 2014). However, no studies on the action mechanism of WFC in the treatment of PLGC have been conducted so far. With the prominence of network pharmacology in system biology, this distinct and novel approach to the study of complex analytical systems is becoming more widely known and more frequently used in the field of drug research. The role of network pharmacology includes uncovering the functions of TCM, providing scientific evidence for TCM, and establishing TCM as a scientifically-proven field (Ma et al., 2016). Here, we attempted to explore the action mechanisms of WFC in the treatment of PLGC using network pharmacology and experimental studies.

In this paper, a reliable and rapid ultra-high performance liquid chromatography coupled with electrospray ionization quadrupole time-of-flight mass spectrometry (UHPLC-ESI-Q-TOF/MS) method was established to profile complex compounds in WFC and describe their absorption behavior and metabolites in plasma samples after oral administration of WFC. The network pharmacology method was used to construct the pharmacology-network of the “origins-components-targets-pathways” of WFC to systematically predict the active components, targets, and signaling pathways that may treat PLGC. In addition, animal experiment was used to verify the prediction and clarify the mechanisms of action. This study provides a reference for further research and exploration of pharmacodynamics material basis and mechanisms of WFC.

Experimental Materials and Methods

Chemicals and Reagents

Drug samples of WFC were obtained from Huqingyutang Pharmaceutical Co., Ltd (Hangzhou, China, batch No. 17066174). HPLC-grade acetonitrile, methanol, and formic acid were purchased from Fisher Scientific (Santa Clara, United States). Ultrapure water was prepared using a Millipore Alpha-Q water system (Millipore, United States). All other reagents were of analytical grade. For animal experiments, the drugs were suspended in sterilized 0.5% carboxymethylcellulose sodium. Vitacoenzyme tablets (0.8 g) was purchased from Beihai Sunshine Pharmaceutical Co., Ltd (Guangxi, China, Lot no. 102029), and Pepsin kit from Nanjing Jiancheng Bioengineering Research Institute (Nanjing, China). MNNG was purchased from TOKYO Chemical Industry Co., Ltd (Tokyo, Japan). Ranitidine hydrochloride capsule was brought from Zhejiang Kangenbei Pharmaceutical Co., Ltd (Zhenjiang, China). TAKARA RNA reverse transcription kits were from Takara Biomedical Technology (Beijing) Co., Ltd (Beijing, China); TOYOBO amplification kit was purchased from toyo textile (Shanghai) biotechnology co., Ltd (Shanghai, China). Primers to amplify the genes ß-actin, Pi3k, Akt1, Mapk11, Fas, Mapk8, caspase3, Mapk14, Tp53, and Vegfα were designed by Shanghai Guanchun Biotechnology Co., Ltd (bioTNT) (Shanghai, China) (Table 1).

TABLE 1

Gene official symbolForward primer sequenceReverse primer sequenceProduct length (bp)
β-Actin5′ CCT CTA TGC CAA CAC AGT 3′5′ AGC CAC CAA TCC ACA CAG 3′155
Pi3k5′ CAT CAA TGG CAA CAC TCT AAG 3′5′ AGG ACA GGT GGA TAC GAA AT 3′97
Akt15′ TTC TCA GTG GCA CAA TGT CAG 3′5′ GGA TGA AGG TGT TGG G 3′64
Mapk115′ CAA CCC TCT GGC TGT AGA CCT 3′5′ CGC ACT GAC TCT CTG GTC ACT 3′67
Faslg5′ TGC CTC CAC TAA GCC CTC TA 3′5′ CCT AAC CCC ATT CCA ACC AG 3′100
Mapk85′ AGT GAG CAG AGC AGG CAT AGT 3′5′ CAG GAG CAG CAC CAT TCT TAC 3′108
Caspase35′ ATG TGT GAA CTT GGT TGG CTT 3′5′ AGA AAC AAA TGC TGG ATC 3′90
Mapk145′ ACA CCC CCT GCT TAT CTC A 3′5′ AAG TTC ATC TTC GGC ATC TG 3′89
Tp535′ CAT CTT CCG TCC CTT CTC AAA 3′5′ AGA CTT GGC TGT CCC TGA CTG 3′83
Vegfα5′ TTT CGG GAA CTA GAC CTC TCA 3′5′ TCA GGC TTT CTG GAT TAA GGA 3′102
Foxo45′ GTC TTT GTC AGC AGG AGA AGG 3′5′ GAG GTG GTG GTG TAT CAG AGG 3′80

Sequence of gene primers.

Ethics Statement

All feeding conditions were in compliance with the Chinese Animal Welfare Law and the relevant regulations of Fudan University and Shanghai University of Traditional Chinese Medicine Experimental Animal Ethics Committee. Wistar rats from the Experimental Animal Center of Shanghai University of Traditional Chinese Medicine were recruited to establish the model of gastric precancerous lesions. Animal license Code: SYXK Shanghai 2014-008. Ethics No.: PZSHUTCM19039006.

Animal Handling

Animal Model for Drug Metabolism Experiment in Rats

Ten specific pathogen-free male Sprague-Dawley rats (200 g) were provided by the Experimental Animal Center of Shanghai University of Traditional Chinese Medicine. Rats were housed in an animal room (24 ± 2°C, 60 ± 5% relative humidity) with the setting of a 12 h dark/12 h light cycle. Before the experiment, rats were given water and fed standard laboratory food for acclimatization for a week. Rats were fasted for 12 h before the sample collection but still had access to water throughout the experiment. WFC (dissolved in purified water) was orally administered to six rats at a dose of 4.0 g/kg (capsule powder/body weight) twice a day consecutively for 7 days to accumulate as many absorbed components as possible. Four rats were assigned to the blank control group. Whole blood samples (0.5 ml) were collected from the sub-orbital vein and placed in heparinized polythene tubes at 15, 30, 60, 90, and 120 min after the last drug administration. Plasma was separated immediately by centrifugation at 12,000 rpm for 10 min at 4°C. All samples were immediately stored at −80°C until further analysis.

Pharmacological Experiment of Precancerous Lesions of Gastric Cancer Model in Rats

Fifty 7-week-old male Wistar rats (171 ± 10 g, SPF Grade) were obtained from the Experimental Animal Center of Shanghai University of Traditional Chinese Medicine. All rats were supported and observed in research facility under alternating light and dark conditions (12 h:12 h). After 3 days of adaptive feeding, all rats were divided into five groups, normal group (N group), model group (M group), high-dose group (WH group), low-dose group (WL group), and control group (VM group), stratified randomly according to the body weight of 10 rats in each group. Based on literature modeling methods (Lin et al., 2019) and with the exception of the N group rats, all rats were given 100 mg/L methyl nitroguanidine aqueous solution drink and 0.3 g/L ranitidine fodder each day, and alternatively gavage fed 150 g/L sodium chloride solution at 56°C and 30% ethanol at 10 ml/kg. All model rats were starved and had satiation disorder. After 4 weeks, drugs were administered by gavage. Drug dosage was as follows: Rats in WH group and WL group were given WFC at 1.44 g/kg and 0.72 g/kg, respectively, and VM group was given vatacoenayme at 0.6 g/kg each day. Rats in N group were given gastric gavage of 10 ml/kg of normal saline. After fasting for 12 h at the end of the 16th week, all rats were sacrificed for sample collection.

Plasma Sample Preparation

All plasma samples from the experimental rats were combined into one sample so as to eliminate the individual variability in each experiment. To get the whole information of absorbed components and metabolites, equivalent plasma was taken from the five time points to form mixture as the analysis plasma. An aliquot of 3 ml of methanol was added to 1 ml of plasma and vortex-mixed for 3 min to precipitate proteins (PPT). After centrifugation at 12,000 rpm for 10 min, the supernatant was transferred into a clean tube and evaporated to dryness under a gentle stream of nitrogen at room temperature. The residue was re-dissolved in 200 μl initial mobile phase through vortex-mixing and ultrasonic processing. The resulting solution was centrifuged at 12,000 rpm for 10 min, and 5 μl of the supernatant was injected into the LC-MS system for analysis. The blank plasma sample was prepared as the drug-containing sample.

Preparation and Observation of Animal Samples of Precancerous Lesions of Gastric Cancer Model

Pepsin Detection and Histopathology Observation

Body weight and autonomic activity of rats were observed. Detection of pepsin was conducted in accordance with the kit instructions of Nanjing Jiancheng biological engineering institute. The gastric tissues of rats were subjected to tissue dehydration and paraffin discharge operations after being fully fixed with formaldehyde. The embedded tissues were cut into 0.04 μm blank tissue slices for HE staining and histomorphologic study of gastric mucosa under microscope (100×). Inflammatory cell infiltration, ulcer formation, glandular atrophy, basement membrane thickening, and dysplasia were observed.

Real-Time Polymerase Chain Reaction

According to operating manual, gastric tissues were extracted by “one-step” Trizol method and concentrations were calculated. Obtained RNA templates were reverse-transcribed into c-DNA using TAKARA RNA Reverse Transcription Kit. Next, RT-qPCR was performed following TOYOBO Amplification Kit instructions. Here, each well contained a PCR reaction volume of 10 μl (SYBR Green master mix 5 μl, forward primer 1 μl, reverse primer 1 μl, c-DNA sample 1 μl, and diethylpyrocarbonate 2 μl). ß-Actin was used as an endogenous control gene. PCR reaction consisted of 45 cycles as follows: 50°C for 2 min → 95°C for 1 min → 95°C for 15 s → 60°C for 1 min → 95°C for 15 s → 60°C for 1 min. 2−∆Ct represents the expression level of the tested genes relative to the normal group of genes.

Ultra-High Performance Liquid Chromatography and Mass Conditions

Chromatographic Conditions

UHPLC-MS conditions and data processing were described as previously reported (Wang et al., 2019). Chromatographic separations were performed on an Acquity UHPLC system (Waters, United States) equipped with a binary solvent delivery system and an autosampler. The extracts were separated using an Acquity UHPLC BEH C18 RP column (1.7 μm, 100 mm × 2.1 mm i. d.; Waters, United States) in which the column temperature was maintained at 45°C to avoid excessive column pressure. The autosampler temperature was fixed at 4°C. The mobile phase consisted of 0.1% formic acid in deionized water (mobile phase A) and acetonitrile (mobile phase B). Separation was conducted with the following gradient elution: 0–3.5 min, 5–20% B; 3.5–8.0 min, 20% B; 8.0–15.0 min, 20–30% B; 15.0–21.0 min, 30–50% B; 21.0–26.0 min, 50–95% B; 26.0–28.0 min, 95% B; 28.0–28.1 min, 95–5% B; and 28.1–32.0 min, 5% B for equilibration of the column. The flow rate was set at 0.3 ml/min, and an aliquot of 5 μl was set as injection volume.

Mass Spectrometric Conditions

MS detection was performed using Acquity Synapt G2 Q-TOF tandem mass spectrometer (Waters, United Kingdom) connected to the UHPLC system by an ESI interface and controlled by MassLynx version 4.1 (Waters, United Kingdom). The ESI source was operated in both positive (ESI+) and negative (ESI−) ionization modes. The optimized conditions to trigger maximum response of metabolites were listed as follows: capillary voltage, −2.5 kV (ESI−) or +3 kV (ESI+); sample cone, −25 V (ESI−) or +30 V (ESI+); extraction cone, −4.0 V (ESI−) or +4.0 V (ESI+); source temperature, 120°C; desolation temperature, 350°C; cone gas (nitrogen) flow, 50 L/h; and desolvation gas (nitrogen) flow, 600 L/h. Argon was used as collision gas. Leucine-enkephalin (2 ng/ml) was used as the lock mass generating a reference ion at m/z of 554.2615 (ESI−) or 556.2771 (ESI+) by a lock spray at 5 μl/min to acquire accurate mass during analysis.

Data were collected in a centroid mode. MSE approach was conducted with two scan functions. In function 1, the following parameters were set: m/z 50–1,500; scan duration, 0.3 s; interscan delay, 0.024 s; and collision energy ramp, 4 V. In function 2, the following parameters were set: m/z 50–1,500; scan duration, 0.3 s; interscan delay, 0.024 s; and collision energy ramp, 10–30 V. In MSE, MS, and MS/MS data can be acquired almost simultaneously in a single analytical run. Data acquisition and processing were conducted using Waters MassLynx version 4.1.

Data Processing

Construction of In-House Library

By comprehensive document retrieval, information about compounds in the three crude medicinal materials and WFC prescription was collected to form an in-house library of WFC. The in-house library content was described with respect to the known global phytochemical constituents and the metabolites database, including the English name, structure, molecular formula, characteristic fragment ions, all accurate monoisotopic mass values of the related chemical formula, and original source.

MassLynx Processing Approach for Analysis of Wei-Fu-Chun Phytochemical Constituents, Absorbed Compounds and Metabolites

Mass data processing was carried out using MassLynx 4.1, including extracted ion chromatograms (EIC) using a narrow mass window of 0.01 Da, calculation of EIC with mass errors within 5 ppm, and fraction isotope abundance value of 1.0. In particular, EIC were also applied to distinguish mixed peaks eluted almost at the same retention time. Target chemical structures were analyzed and confirmed based on EIC, accurately measured mass value, fragment behavior, and elution order, which were all compared with the in-house library data. Furthermore, WFC components in drug-containing samples were also determined by comparing the retention time and mass data with blank samples. By comparing postdose rat serum, pre-dose rat serum, and the extracts of WFC by UHPLC-ESI-Q-TOF/MS, absorbed compound profile of rat serum was obtained and analyzed. During the same retention time, peaks appeared in the drug-containing sample and the extracts sample of WFC, but were absent in the control sample or the peaks in the drug-containing sample were five folds greater than that in the control sample, which was extracted as absorption compound. These candidates were further collated and culled by serious MS spectra analysis to conform the true absorbed compounds.

Active Chemical Compositions of Wei-Fu-Chun and Potential Targets

According to the results of chemical profiling and metabolic study of WFC, we selected absorbed parent molecules and metabolites in rat serum as candidate compounds. The candidate compounds were paired one-to-one with protein targets using Stitch 5.0 database (http://stitch.embl.de/). We set the parameter to “Homo sapiens” with confidence greater than 0.4, and deleted candidate compounds without corresponding targets. Active components and corresponding potential targets were obtained.

Identifying Precancerous Lesion of Gastric Cancer Related Targets in Wei-Fu-Chun

“Precancerous lesion of gastric cancer” was used as a keyword to search Genecards (https://www.genecards.org/) and OMIM database (http://www.omim.org/) separately and to retrieve therapeutic targets for PLGC. Precancerous lesions of gastric cancer -associated target proteins were collected.

Targets GO-Enrichment and Pathways Enrichment Analysis

The targets of WFC in the treatment of PLGC corresponding to the selected active components were input into DAVID 6.8 database (https://david.ncifcrf.gov/) for GO enrichment analysis, and in KEGG database (http://www.genome.jp/kegg) for pathway enrichment analysis. The parameters were set to p < 0.5 and FDR < 0.05.

Network Construction and Its Features

We input the active component-target pair obtained from String database (http://string-db.org/cgi/input.pl) into Cytoscape 3.1, set the properties of the active components and targets, selected the most suitable node distribution form, and generated the active component-target interaction map. The primary pathway, biological processes, cellular components and molecular functions of p < 0.05 were selected. Visualize the network of “origins-components-targets-pathways” with the Merge feature of Cytoscape 3.1.

Statistical Analysis

SPSS 21.0 statistical software was used for data statistics and analysis. Data measurement was expressed as mean ± standard errors (±SEM). One-way ANOVA was used for comparison among groups, and LSD-t test for further two-paired comparison. A p-value <0.05 indicated a significant statistical difference between two groups.

Results

Sample Acquisition and LC-MS Conditions of Developed Method

Nowadays, UHPLC-ESI-Q-TOF/MS capable of high resolution, high sensitivity and high accuracy have been proven to be an excellent technique for quantitative and qualitative analysis of multi-components and metabolites in complex mixture especially in TCM formulas. Here, UHPLC-ESI-Q-TOF/MS has shown superior performance, in terms of high mass resolution and accurate mass measurement, fast scan speed and wide dynamic range of mass analyzer, as well as efficient separation capability and speed of UHPLC. The acquisition of dependable biological samples for UHPLC-ESI-Q-TOF/MS analysis played a crucial part in the comprehensive in vivo screening of WFC compounds. Primarily, all the possible components should be contained in the collected crude samples and have adequate levels to be detected, taken into account that drug administration method and collection time influence sample content (Zhang et al., 2017).

LC-MS conditions were optimized to enable samples to obtain the best instrumental performance. Both positive and negative ion modes were employed to screen as many potential compounds as possible, but the negative ion mode provided higher signal intensity and the ability to detect more peak signals. Different mobile phase systems and gradient programs were emphasized and investigated to achieve good ionization and separation behavior. A mixture of 0.1% aqueous formic acid and acetonitrile was nally chosen as the preferred mobile phase. This was because acetonitrile had stronger eluting power and the retention behavior of flavonoids on the reversed-phase column was easily affected by pH (increasing pH enhanced the ionization of flavonoids and could reduce the retention in a reversed-phase separation). Thus, small amounts of formic acids were normally included in the solvent to suppress ionization of phenolic or carboxylic groups, hence improving the resolution and reproducibility of each separation. Formic acid buffer have been used as part of the mobile phase for optimizing the analysis time and enhancing separation (Wang et al., 2019). Many components, especially flavonoids and ginsenosides, gave prominent molecular adductive ions when formic acid was used. The results indicated that the proposed method was acceptable and adequate for the comprehensive study of WFC.

Analysis of Wei-Fu-Chun Phytochemistry Components, Absorbed Components, and Metabolites by UHPLC-ESI-Q-TOF/MS

The base peak intensity (BPI) chromatograms of WFC extract at negative and positive ion modes are shown in Figure 1 and Table 2. A total of 178 compounds were identified or tentatively characterized, including 70 terpenes (56 diterpenoids, 12 triterpene, and 2 sesquiterpenes), 51 flavonoids, 33 saponin, six phenylpropanoids, four lignans, three coumarins, three organic acids, two fatty acid, one quinones, one sterol, and four unknown compounds. Structurally related compounds shared analogous MS response and fragment behavior. All compounds were characterized based on their ECs, MS data, and retention behavior with the help of the constructed in-house library and additional literature. The library made the workflow significantly more effective when one was familiar with the detailed information of these extensively investigated molecules and allowed the characterization of these compounds even when reference standards were not available. The calculated correct monoisotopic mass values of quasimolecular ions and rational fragment ions were especially critical to screen the various compounds fast and firmly. There were many isomers inevitably existing in the complex natural compounds and the tiny difference of the mass spectra made them difficult to distinguish. In this case, the electronic effect and their hydrophilicity should be considered (Li et al., 2015). The detailed identified information, including chemical formula, observed mass values of quasi-molecular ions, mass error, and botanical source, is listed in Table 2. A chemical library, including 569 compounds in WFC, was established. By matching against the chemical library, 178 ingredients in WFC were identified. Among them, 93 compounds belonged to XCC, 51 to ZQ, 31 to HS. Three compounds were unknown, meaning that the herb(s) from which they came remained undetermined. In addition, 77 absorbed parent molecules and nine metabolites in rat serum were characterized by UHPLC-ESI-Q-TOF/MS.

FIGURE 1

TABLE 2

NoRT (min)IdentificationFormula(M − H)-(M + H)+Other adduct ions in negative mode (−) or positive mode (+)Structure classPlant material
MeasppmMeasppm
10.80Quinic acidC7H12O6191.0548−4.2——(−)165.0378Organic acidsZQ
20.88KaempferolC15H10O6——287.05622.1—FlavonoidsZQ
30.93Ginsenoside Re4C47H80O18——933.54472.6—SaponinHS
41.97Flavogadorinin BC23H24O11475.1237−0.6———FlavonoidsXCC
5*3.35Ferulic acidC10H10O4193.0496−2.6———Organic acidsXCC
6*3.46Vicenin IIC27H30O15593.1489−2.9595.16670.7(+)577.1447, (+)505.1375FlavonoidsZQ
73.56SucroseC12H22O11341.10850.3———SaccharideXCC
83.58Naringenin-7-O-sophoroseC27H32O15595.16874.0597.1794−4.2—FlavonoidsZQ
94.05Hubeirubesin BC24H32O6415.21261.2———DiterpenoidsXCC
10*4.08Apigenin-7-O-glucuronideC21H18O11445.07914.5447.09515.4—FlavonoidsXCC
114.11Methyl rosmarinateC19H18O8373.0897−7.0———PhenylpropanoidsXCC
12*4.14Vicenin ⅢC26H28O14563.1383−3.2565.1539v3.2—FlavonoidsXCC
134.24Stellarin-2C28H32O16——625.17964.3—FlavonoidsZQ
14*4.34Trichorabdal HC22H28O7403.1738−4.7405.19212.0—DiterpenoidsXCC
15*4.45Glucosyl-naringinC33H42O19741.22713.9743.24071.1(−)609.1470FlavonoidsZQ
164.47RutinC27H30O16609.14753.1611.1607−0.8(+)303.0536FlavonoidsXCC
17*4.53Naringenin-7-O-triglycosideC33H42O19741.2239−0.4743.24283.9(−)427.1591FlavonoidsZQ
184.54Hyuganoside Ⅱ/hyuganoside ⅤC20H28O10427.16152.6429.17671.4(−)265.1102PhenylpropanoidsZQ
194.56EriocitrinC27H32O15595.16833.4——(−)287.0508FlavonoidsZQ
204.56IsovitexinC21H20O10431.09943.7———FlavonoidsZQ
214.64Notoginsenoside R1C47H80O18——933.54381.6—SaponinHS
224.64EpinodosinolC20H26O6361.1644−1.9———DiterpenoidsXCC
23*4.66Oreskaurin BC22H30O6389.1956−2.1———DiterpenoidsXCC
244.72UnknownC27H44O11543.28202.8——(−)463.0919, 544.2788——
25*4.78NeoeriocitrinC27H32O15595.16782.5597.18240.8—FlavonoidsZQ
26*4.79Limonin-17-β-D-glucopyranosideC32H42O14649.2494−0.3———TriterpeneZQ
27*4.863′-Methoxyl isovitexinC22H22O11461.10840463.1232−1.7(+)427.1087FlavonoidsZQ
284.87HenryinC22H32O6391.2112−2.3———DiterpenoidsXCC
295.06Melissoidesin KC24H36O8451.23412———DiterpenoidsXCC
30*5.08(+)-Rabdosiin or (−)-rabdosiinC36H30O16717.14610.7719.16170.7(−)519.0913PhenylpropanoidsXCC
31*5.17LoquatosideC20H22O11——439.1230−2.3—FlavonoidsZQ
325.35NarirutinC27H32O14579.1713−0.2581.1866−0.7(+)435.1089, (+)273.0668FlavonoidsZQ
33*5.37Kamebacetal AC21H30O5361.2004−3.0363.2163−2.2—DiterpenoidsXCC
34*5.38(+)-Rabdosiin or (−)-rabdosiinC36H30O16717.14610.7719.16170.7(−)519.0913PhenylpropanoidsXCC
355.40Narirutin-4′-glucosideC33H42O19741.2217−3.4———FlavonoidsZQ
365.43MiscanthosideC21H22O11449.1080−0.9———FlavonoidsZQ
375.70RhoifolinC27H30O14——579.1710−0.7(+)273.0814FlavonoidsZQ
38*5.76NaringinC27H32O14579.17394.3581.18700(+)273.0774FlavonoidsZQ
39*5.83VitexinC21H20O10431.0961−3.9433.11442.1—FlavonoidsXCC
405.91NaringeninC15H12O5271.06060———FlavonoidsZQ
415.91EnmenolC20H30O6365.19711.9———DiterpenoidsXCC
42*6.25HesperidinC28H34O15609.18444.1611.1957−3.1(+)449.1443, (+) 303.0813FlavonoidsZQ
43*6.3Caffeic acidC9H8O4179.0339−2.8181.05041.7—Organic acidsXCC
446.32LadaneinC17H14O6313.071−0.6———FlavonoidsXCC
456.32Rosmarinic acidC18H16O8359.07783.1———PhenylpropanoidsXCC
466.32CirsiliolC17H14O7329.065−3.3———FlavonoidsXCC
476.33DanshensuC9H10O5197.0445−2.5———PhenylpropanoidsXCC
48*6.60Lushanrubescensin FC21H32O7395.2070———DiterpenoidsXCC
496.63THDOC20H28O4331.19120.9333.20783.6—DiterpenoidsXCC
506.72(+)-1-HydroxypinoresinolC20H22O7373.12880.3———LignansXCC
51*6.81LariciresinolC20H24O6359.1479−4.5361.1634−4.7—LignansXCC
526.83NeohesperidinC28H34O15609.18291.6611.1970−1.0(+)449.1426, (+)303.0884FlavonoidsZQ
536.83Hesperetin-5-O-glucosideC22H24O11——465.1381−3.4—FlavonoidsZQ
54*6.86HesperetinC16H14O6301.0704−2.7303.08741.6—FlavonoidsZQ
55*6.92LHMGC29H32O17——653.17220.6(+)347.0763FlavonoidsZQ
56*7.08Nomilinic acid glucosideC34H48O16711.2845−2.7713.3016−0.7—TriterpeneZQ
57*7.14Hesperetin-7-O-glucosideC22H24O11463.12471.5465.14133.4—FlavonoidsZQ
587.48PedalitinC16H12O7315.05204.8317.06702.8—FlavonoidsXCC
59*7.90Sudachinoid AC26H34O9——491.22983.5—SesquiterpenesZQ
607.90MeranzinC15H16O4——261.11394.6(−)189.0572CoumarinsZQ
618.00Deacetyl nomilin glucosideC34H46O15693.2727−4.5———TriterpeneZQ
62*8.247-O-6″-MalonylnaringinC30H34O17——667.18770.4—FlavonoidsZQ
63*8.49LasiodoninC20H28O6363.18151.9———DiterpenoidsXCC
648.81Hebeirubescensin H or GC20H28O7——381.19−3.4—DiterpenoidsXCC
659.78Effusanin AC20H28O5347.1855−0.9———DiterpenoidsXCC
6610.26SesaminC20H18O6353.1031.4———LignansXCC
6710.33Obacunone 17-O-β-D-glucosideC32H42O13633.2539−1.3———TriterpenesZQ
6810.78Ginsenoside Rg1C42H72O14——801.4998−0.2(−)845.4928 [M + HCOO]−SaponinHS
6910.79SchaftosideC26H28O14563.1389−2.1565.1584.1—FlavonoidsXCC
7010.93Ginsenoside ReC48H82O18945.53532.6947.5560−2.0(−)991.5504 [M + HCOO]−SaponinHS
71*11.40Excisanin AC20H30O5349.20211.7351.21936.3—FlavonoidsXCC
7211.52Rabdosinate/Gesneroidin CC28H38O10533.2367−3.8———DiterpenoidsXCC
73*11.72Melissoidesin TC24H36O7435.23963.0437.2491−11—DiterpenoidsXCC
7411.99NeoponcirinC28H34O14593.1849−3.5595.2009−3.0—FlavonoidsZQ
75*12.36SodoponinC22H32O7407.20761.5409.2215−2.7(−)285.0743DiterpenoidsXCC
7612.64PoncirinC28H34O14593.18740.7595.2017−1.7—FlavonoidsZQ
77*12.67Rabdophyllin HC24H36O9467.22810———DiterpenoidsXCC
78*13.09Glaucocalyxin AC20H28O4331.19213.6333.20670.3—DiterpenoidsXCC
7913.14LasiokaurinC22H30O7405.19314.4———DiterpenoidsXCC
80*13.43Oreskaurin CC20H30O5349.20201.4———DiterpenoidsXCC
81*13.73OridoninC20H28O6363.18265.0365.1955−2.5—DiterpenoidsXCC
82*14.27FumotonaringinC28H34O14593.18761.0595.20473.4—FlavonoidsZQ
8315.67NHMGC33H40O18——725.2277−2.2—FlavonoidsZQ
8415.92Coetsoidin AC22H26O6385.16653.6387.1806−0.5—DiterpenoidsXCC
85*16.43Ginsenoside RfC42H72O14799.48325.8801.4992−1.0(−)845.4948 [M + HCOO]−SaponinHS
8616.54Melissoidesin NC22H32O5375.21853.7———DiterpenoidsXCC
8716.60EpoxybergamottinC21H22O5——355.1542−0.8—CoumarinsZQ
8816.61Melissoidesin PC22H34O6393.22923.8———DiterpenoidsXCC
89*16.65IsosinensetinC20H20O7371.11423.0373.1283−1.1—FlavonoidsZQ
90*17.0320(S) or 20(R)-Notoginsenoside R2C41H70O13769.47712.0771.4866−3.8(−)815.4809 [M + HCOO]−SaponinHS
9117.44Ent-abierubesin AC20H32O5351.21730.6———DiterpenoidsXCC
92*17.46Ginsenoside Ra2C58H98O261,209.63093.41,211.6406−1.6(−)1,255.6528 [M + HCOO]−SaponinHS
93*17.53Melissoidesin UC26H38O8477.2478−2.1479.2637−1.7—DiterpenoidsXCC
9417.5920(S)-Ginsenoside RdC48H82O18945.5407−1.7947.5563−1.7—SaponinHS
95*17.62Ginsenoside Rb1C54H92O231,107.59853.11,109.6107−0.1(−)1,153.6080 [M + HCOO]−SaponinHS
96*17.6220(S)-Ginsenoside Rg2C42H72O13783.49384.6785.50854.3(−)829.4987, 621.3106SaponinHS
9717.75Malonyl ginsenoside Rb1C57H94O26——1,195.61493.1—SaponinHS
98*17.78Ginsenoside Ra3/nootoginsenoside FaC59H100O27——1,241.6506−1.9—SaponinHS
99*17.86Ginsenoside Rb2C53H90O221,077.5875−0.81,079.5979−2.1(−)1,123.5891 [M + HCOO]−SaponinHS
100*17.92Ginsenoside Rb3/ginsenoside RcC53H90O221,077.58751.21,079.5975−2.5(−)1,123.5913 [M + HCOO]−SaponinHS
10117.94Ginsenoside Ra1C58H98O261,209.6241−1.31,077.5929−1.8(−)1,255.6307 [M + HCOO]−SaponinHS
10218.04AuranetinC20H20O7——373.1275−3.2—FlavonoidsZQ
103*18.07Ginsenoside RoC48H76O19955.49110.8———SaponinHS
104*18.245-DemethylnobiletinC20H20O8387.1078−0.5389.122−4.1—FlavonoidsZQ
10518.25LimoninC26H30O8469.18691.5471.2009−2.1—TriterpeneZQ
106*18.30Malonyl-notoginsenoside R4C62H102O301,325.6366−0.91,327.6525−0.7—SaponinHS
10718.33Tetramethyl-O-isoscutellareinC19H18O6——343.118−0.6—FlavonoidsZQ
108*18.85Pomiferin FC20H28O3315.1955−1.6317.2102−4.7—DiterpenoidsXCC
10918.95Ginsenoside Rs1C55H92O23——1,121.61493.7—SaponinHS
11018.97Ginsenoside Rs2C55H92O231,119.6171−0.81,121.6077−2.8(−)1,165.5997 [M + HCOO]−SaponinHS
111*18.99Quinquenoside R1C56H94O241,149.60640.61,151.62402.3—SaponinHS
112*19.0220(R)-Ginsenoside RdC48H82O18945.54300.1——(−)991.5479, 621.7865SaponinHS
113*19.05Malonyl-ginsenoside ReC51H84O211,031.5408−1.81,033.5574−0.9—SaponinHS
11419.12Obacunoic acidC26H32O8471.2017−0.4———TriterpeneZQ
115*19.20Nomilinic acidC28H36O10531.2222−1.5533.2375−2.3(−)427.2114TriterpeneZQ
11619.23ShikokianinC24H32O8447.2003−3.6———DiterpenoidsXCC
117*19.30AngustifolinC21H28O6375.1806−0.5377.1962−0.5—TriterpeneXCC
11819.41Gossypetin hexamethyl etherC21H22O8——403.13950.5(+)373.0964FlavonoidsZQ
11919.68Melissoidesin LC22H32O4359.22220———DiterpenoidsXCC
12019.76β-SitosterolC29H50O413.3776−1.7———TriterpeneXCC
12120.223-MethoxynobiletinC22H24O9——433.15020.7—FlavonoidsZQ
122*20.24Rabdosichuanin DC24H34O8449.21923.8451.2311−4.7—DiterpenoidsXCC
12320.60Melissoidesin QC24H36O7435.23932.3———DiterpenoidsXCC
124*20.6620(R)-Acetyl ginsenoside RdC50H84O19987.5709−0.4989.57243.9(−)1,033.5579 [M + HCOO]−SaponinHS
125*20.73Tangeretin/pentamethoxyflavoneC20H20O7——373.12982.9(+)343.0821FlavonoidsZQ
12620.98Glaucocalyxin D？C22H30O5373.20283.5———DiterpenoidsXCC
12721.03Ginsenoside Rg6C42H70O12765.47991.3767.49571.4(−)811.4885, 459.3017SaponinHS
12821.26Malonyl-ginsenoside Ra2/Ra1C61H100O29——1,297.64693.1—SaponinHS
129*21.31Ginsenoside Rk1C42H70O12765.47092.6767.49541.0(−)811.4865, 603.1678SaponinHS
13021.40Leukamenin EC22H32O5375.21853.7———DiterpenoidsXCC
13121.547HPFC20H20O8——389.12483.1—FlavonoidsZQ
132*22.3520(S)-Ginsenoside Rg3C42H72O13783.49062.3——(−)829.4968, 621.3106SaponinHS
133*22.46UnknownC44H52O4643.3774−2.0645.3930−2.2———
134*22.57Glaucocalyxin BC22H30O5373.20242.4———DiterpenoidsXCC
13523.97Ginsenoside F4C42H70O12765.47614.1767.49530.9(−)811.4877, 459.8965SaponinHS
13624.06Ent-abierubesin BC20H34O6369.2267−2.7———DiterpenoidsXCC
13724.09Ginsenoside Rg5C42H70O12765.4846−1.0767.4927−2.5(−)811.4836, 603.1898SaponinHS
13824.17Rabdosin BC24H32O8447.20241.1———DiterpenoidsXCC
13924.32Corosolic AcidC30H48O4471.3470−0.8473.3618−2.7—TriterpeneXCC
14024.58Hexamethoxyflavone（Nobiletin）C21H22O8401.1217−4.7403.1392−0.2(−)371.2429, 315.2524, 239.1493FlavonoidsZQ
14124.82Melissoidesin RC26H38O8477.2472−3.4479.2633−2.5—DiterpenoidsXCC
142*24.88Lophanic acidC20H32O3319.2267−1.9321.24330.9—DiterpenoidsXCC
14325.00Melissoidesin IC22H34O6393.22893.1———DiterpenoidsXCC
14425.13Naringenin-7-O-glucoside（Prunin）C21H22O10433.1133−0.5———FlavonoidsZQ
145*25.13Melissoidesin MC22H34O5377.2318−2.7———DiterpenoidsXCC
146*25.33Isoscoparin CC20H32O3319.22781.6321.24434.0—DiterpenoidsXCC
14725.35Rabdosin EC20H26O7377.16030.8———DiterpenoidsXCC
14825.38Melissoidesin JC24H36O7435.2365−4.1———DiterpenoidsXCC
14925.46Eriocalyxin A/Eriocalyxin BC20H24O5343.15511.7———DiterpenoidsXCC
150*25.707alpha-HydroxystigmasterolC29H48O2——429.3711−5.1—SterolXCC
151*25.89UnknownC20H24O5343.15460.3345.1701−0.3———
152*25.94Oreskaurin AC22H28O8419.1705−0.2421.18681.4—DiterpenoidsXCC
15326.32Dipropyl octadecanedioateC24H46O4397.3301−4.3399.3456−4.5—Fatty acidXCC
15426.43Taibaijaponicain AC21H30O7393.1909−1.0395.20782.0—DiterpenoidsXCC
15526.82Gossypetin Hexamethyl EtherC21H22O8401.1217−4.7———FlavonoidsZQ
15626.85FriedelinC30H50O425.3775−1.9———SaponinXCC
157*27.00Ent-abierubesin D/ent-Abierubesin CC20H32O4335.2213−2.7337.23862.1—DiterpenoidsXCC
158*27.11RabdolasionalC22H30O7405.1934.2———DiterpenoidsXCC
15927.11IsoschaftosideC26H28O14563.14111.8———FlavonoidsXCC
16027.17Hebeirubescensin KC20H30O5349.2000−4.3———DiterpenoidsXCC
161*27.18Melissoidesin OC24H34O6417.2261−3.8419.2418−3.8—DiterpenoidsXCC
16227.18EpipinoresinolC20H22O6357.13421.1———LignansXCC
16327.20Micranthin CC20H28O5347.1853−1.4———DiterpenoidsXCC
16427.262,6-DimethoxybenzoquinoneC8H8O4167.0337−4.2———QuinonesXCC
165*27.33Acetylursolic AcidC32H50O4497.36412.0———TriterpeneXCC
16627.34TetracosylferulateC34H58O4529.42610.8———Phenolic acidsXCC
16727.45EsculetinC9H6O4177.0184−2.3———CoumarinsXCC
16827.60Rabdoinflexin B/rabdokunmin CC20H30O5349.20252.9———DiterpenoidsXCC
16927.66TeuclatriolC15H28O3255.1954−2.4———SesquiterpenesXCC
17027.91Isoscoparin AC22H34O4361.23790———DiterpenoidsXCC
171*28.02Dibutyl terephthalateC16H22O4277.1427−4.7279.16011.8—Fatty acidXCC
172*28.15Notoginsenoside FeC47H80O17——917.54952.3—TriterpeneHS
173*28.20Isoscoparin BC21H36O4351.2531−1.1353.2681−3.1—DiterpenoidsXCC
174*28.60DaucosterolC35H60O6575.43191.2577.4431−6.4—TriterpeneXCC
17528.69Forrestin BC24H36O8451.2318−3.1———DiterpenoidsXCC
17628.77Vinaginsenoside R16C47H80O17——917.54780.4—SaponinHS
17728.88Maoyecrystal LC24H34O8449.2169−1.3451.2327−1.1—DiterpenoidsXCC
178*29.67QuercetinC15H10O7301.03593.7303.0502−1.0—FlavonoidsXCC

Characterization of chemical constituents of WFC Tablet by UHPLC-ESI-Q-TOF/MS.

In the identification column, the compounds marked with * are the components absorbed into blood circulation. In the other adduct ions column, ions (+) were detected in positive mode, ions (−) were detected in negative mode. For the plant material column: HS, Radix Ginseng Rubra; ZQ, Fructus aurantii; XCC, Isodon amethystoides; 49: THDO, 7α,10α,14β-10,14,18-trihydroxykaura-11,16-dien-15-one; 55: LHMG, limocitrin-3-O-(3-hydroxy-3-methylglutarate)-glucoside; 83: NHMG, natsudaidain-3-O-(3-hydroxy-3-methylglutarate)-glucoside; 131: 7HPF, 7-hydroxyl-4′,3,5,6,8-pentamethoxy-flavone.

Identification of Diterpenoids, Triterpene, and Sesquiterpenes

Diterpenoids are the major bioactive constituents of XCC. About 500 new diterpenoids (mainly ent-kauranoids) with different oxygenations and cleavage patterns have been isolated and characterized from plants of the genus Isodon. In our study, 70 terpenes, including 56 diterpenoids, 12 triterpene, and two sesquiterpenes, were detected and identified in WFC, by means of UHPLC-ESI-Q-TOF/MS in both negative and positive mode according to the literatures (Zhou et al., 2009; Jin et al., 2010). The accurate mass measurements and elemental compositions of molecular ions and main product ion were shown in Table 2. In this study, all terpenes from XCC were ionized as deprotonated molecules [M − H]− in negative mode, however, only part of the terpenes were detected in positive mode.

Identification of Flavonoids

Fifty-one flavonoids and their glycosides in WFC (39 from ZQ, 12 from XCC) were detected according to the literature (Fabre et al., 2001; Shi et al., 2007; Zhang et al., 2012), most of them having a common structure of C6-C3-C6. Their cleavage regularity in extracts has been well described. Simply, for aglycones, the main MS/MS behavior involved RDA fragmentation pathway and losses of small neutral molecules and radicals from [M − H]−, CO (28 Da), CO2 (44 Da), H2O (18 Da), and CH3 (15 Da) that are useful for determining the presence of specific functional groups; for flavonoid glycosides, the cleavage at the glycosideic linkages in positive and negative ion mode both could happen and produce the same fragmentations with low m/z as the fragmentations obtained in their aglycone. For example, flavone glycosides were characterized by the successive losses of an apiose residue C5H8O4 (132 Da), pentose residue (146 Da), hexose residue (162 Da), glucuronic acid (176 Da), rutinoside or glycoside neohesperidin (308 Da).

Compound 15 showed [M − H]− ion at m/z 741, and identical fragmentations at m/z 609, which lost an apiose residue (132 Da). Here, compound 15 was identified as Glucosyl-naringin (Table 2). Compound 18 showed [M − H]− ion at m/z 427, and identical fragmentations at m/z 265, which lost a hexose residue (162 Da). Compound 18 was identified as hyuganoside II or V. Compounds 19, 32, and 38 showed [M − H]− ion at m/z 595, 579, 579, and identical fragmentations at m/z 287, 271, 271, which lost a hexose residue (308 Da). Compound 19 was identified as eriocitrin. Both compounds 32 and 38 showed [M − H]− ion at m/z 579 [M + H]+ ion at m/z 581, and identical fragmentations at m/z 271 (negative) and 273 (positive), which lost a hexose residue (308 Da), as well as identical fragmentations at m/z 435 (positive), which lost a pentose residue (146 Da) of 38. Thus, 32 and 38 were deemed narirutin and naringin based on the fragmentations and appearance time. Compounds 42 and 52 were identified as hesperidin and neohesperidin, as both lost a hexose residue (308 Da) at negative and positive conditions (Li et al., 2004). Compound 57 showed identical [M − H]− ion at m/z 463, and fragmentation at m/z 301 and 286, suggesting that compound 57 had a hexose residue (162 Da), and CH3 (15 Da) in its aglycone. Compound 57 was identified as hesperetin-7-O-glucoside. Other flavonoids were tentatively identified based on the positive and negative parent ion and previous literature report.

Identification of Saponin

Thirty-two saponins (31 from HS) were detected and identified in WFC, by matching the empirical molecular formula and fragment ions with reported MS data of saponins in HS, ZQ, and XCC (Liu et al., 2006; Dan et al., 2009; Zhang et al., 2012). The detailed information was shown in Table 2. Most ginsenosides were liable to form [M − H]− ion and [M + HCOO]− ion in the negative mode and [M + H]+ ion in positive mode. The main pathway for mass spectrometry cleavage of ginsenosides to lose the glycosyl groups to form the parent ion of m/z 459 (diol type) and m/z 475 (triol type). For example, in the case of compounds 127 and 135, m/z 459 was detected in negative mode. The second point is the characteristic fragment ion formed by glycosylation. For compounds 96, 132, and 112, the same fragment m/z 621 lost one or two glucoses from parent ion. Fragment m/z 603 of compounds 129 and 137 lost one glucose from parent ion.

Identification of Phenylpropanoids

Six phenylpropanoids were detected in WFC. They were methyl rosmarinate (11), hyuganoside II/hyuganoside V (18) (+)-rabdosiin or (−)-rabdosiin (30, 34), rosmarinic acid (45), danshensu (47) (Zhang et al., 2012). Compound 18 showed [M − H]− ion at m/z 427.1615, and identical fragmentations at m/z 265, which lost a glucose residue (162 Da).

Identification of Lignans

Four lignans were detected in WFC, which were (+)-1-hydroxypinoresinol (50), Lariciresinol (51), sesamin (66), and Epipinoresinol (162). All of the four compounds were from XCC. They were liable to form [M − H]− ion in the negative mode and [M + H]+ ion in positive mode.

Identification of Coumarins

Meranzin (60) and Epoxybergamottin (87) were identified from ZQ, and Esculetin (86) was identified from XCC. Meranzin (60) showed a protonated molecule at m/z 261.1139 [M + H]+, with a molecular formula C15H16O4. MS/MS fragmentation appeared in m/z 189.0572 [M + H-C4H7O]+ (Tsujimoto et al., 2019). The MS fragmentation was typical for the fragmentation pattern of meranzin.

Identification of Organic Acids, Fatty Acid, Quinones, Sterol, and Unknown Compounds

Three organic acid, two fatty acid, one quinones, one sterol, and four unknown compounds were identified.

UHPLC-ESI-Q-TOF/MS Analysis of Compounds in Wei-Fu-Chun Absorbed into Blood Circulation

The absorbed compounds were explored based on the hypothesis that the active constituents were those absorbed into tissue (Zhao et al., 2010). By comparing post-dose rat serum, pre-dose rat serum, and the extracts of WFC by UHPLC-ESI-Q-TOF/MS, an absorbed compounds profile of rat serum was obtained and analyzed. The 77 parent molecules in the positive- and negative-ion mode were summarized in Figure 2 and Table 2 and marked with an asterisk (*). Of these 77 parent molecules, there were 24 diterpenoids (23 from XCC, one from ZQ), 20 flavonoids (15 from ZQ, five from XCC), 17 saponins (all are ginsenoside from HS), five triterpenes (three from XCC, two from ZQ), two phenylpropanoids (both are from XCC), two organic acids (both are from XCC), one sesquiterpenes (from ZQ), one sterol (from XCC), one fatty acid (from XCC), and two unknown compounds. Taken together, the most absorbed compounds were terpene from XCC, flavonoids from ZQ, and saponins from HS.

FIGURE 2

Tentative Identification of the Wei-Fu-Chun Metabolites in Rats

Some drug components could be further metabolized by a variety of metabolic enzymes in the body and form phase I or phase II metabolites, which are highly related to the curative effect and drug elimination. Drug metabolites usually kept the core structure of the parent drug after biotransformation, hence the obtained candidate metabolites were further identified by comparing the change in molecular mass (△M), the retention time, and MS2 spectral with their parent drugs. Metabolites of all 178 compounds were tentatively predicted in rat plasma according to their molecular weights and literature reports; however, only the metabolites of limonin, ginsenoside Rg1, ginsenoside Rb3, oridonin were found in our study. M1 eluted at 1.07 min was observed at m/z 455.1891, which is 16 Da (−O) lower than limonin. M2 eluted at 1.08 min and the positive ion was observed at m/z 485.1989, which was 14 Da (+CH2) higher than limonin. The peak elution of M4 was at 4.34 min and the positive ion was observed at m/z 489.2314, which was 18 Da (A-ring lactone) higher than that of the parent drug limonin. The two metabolites (M3 and M5) of ginsenoside Rg1 were observed at m/z 859.4590 and 861.4748 in negative mode, which were 14 Da (+O-2H) and 16 Da (+O) higher than limonin (Wang et al., 2016). Oridonin + OH (M9) and +2OH (M8) compounds were observed at m/z 379.1540 and 395.1656.

Network Pharmacology Approach to Predict the Compounds and Action Mechanisms of Wei-Fu-Chun Against Precancerous Lesions of Gastric Cancer

Identification of Active Chemical Compositions, Candidate Targets and Biological Processes for Wei-Fu-Chun Against Precancerous Lesions of Gastric Cancer

The efficacy of TCM is based on the overall regulation of multiple active ingredients acting on different disease-related targets through multiple pathways (Li and Zhang, 2013). Therefore, we collected 86 candidate compounds (Tables 2, 3) and 105 potential targets. 13 active components and 48 protein targets to treat PLGC were then obtained. Detailed information of these therapeutic targets was described in Tables 4, 5 separately.

TABLE 3

NumberRT (min)IdentificationFormulaTheoretical mass (m/z)Experimental mass (m/z) (+)/(−)Error (ppm)Fragment ionsPossible original compound
M11.07Limonin-OC26H30O7455.2070455.2051 (+)−1.9315.1348, 409.1765Limonin
M21.08Limonin + CH2C27H34O8485.2175485.2159 (+)−1.6453.1816, 187.1044Limonin
M34.33Ginsenoside (Rg1+O-2H)C42H70O15859.4697859.4690−0.1651.2668, 633.2964Ginsenoside Rg1
M44.34Limonoate A-ring lactoneC26H32O9489.2125489.2122 (+)−0.3421.2219, 95.0884Limonin
M54.386Ginsenoside (Rg1+O)C42H72O15861.4853861.4748−2.0—Ginsenoside Rg1
M621.29Ginsenoside CKC36H62O8621.4366621.43831.7459.2689, 160.9794Ginsenoside Rb3
M723.22Ginsenoside M2′C41H70O12753.4789753.48263.7799.4698, 293.1731Ginsenoside Rb3
M823.89Oridonin+2OHC20H28O8395.1706395.1696−1.0347.2173, 329.1415Oridonin
M926.59Oridonin + OHC20H28O7379.1757379.1740−1.7361.1645, 349.2100, 325.1804, 299.2557Oridonin

UHPLC-ESI-Q-TOF/MS data obtained in negative and positive ion detection mode for identification of WFC metabolites.

M1, M2, and M4 were detected in positive mode. The rest was detected in negative mode.

TABLE 4

IDCompound nameMolecular formulaMolecular weightPlant materialClassification
C1Caffeic acidC9H8O4180.159HSOrganic acids
C2Ginsenoside RfC42H72O14801.024HSSaponin
C3Ginsenoside Rb1C54H92O231,109.307HSSaponin
C4TangeretinC20H20O7372.373HSFlavonoids
C5Ginsenoside Rg1C42H72O14801.024HSSaponin
C6Ferulic AcidC10H10O4194.186XCCOrganic acids
C7NaringinC27H32O14580.539XCCFlavonoids
C8HesperidinC28H34O15610.565XCCFlavonoids
C9HesperetinC16H14O6302.282XCCFlavonoids
C10Glaucocalyxin AC20H28O4332.44XCCDiterpenoids
C11OridoninC20H28O6364.438XCCDiterpenoid
C12QuercetinC15H10O7302.238XCCFlavonoids
C13VitexinC21H20O10432.381ZQFlavonoids

Representative active compounds in WFC.

HS, Radix Ginseng Rubra; ZQ, Fructus aurantii; XCC, Isodon amethystoides.

TABLE 5

IDFull name of proteinShort name of protein
P1Mitogen-activated protein kinase 1MAPK1
P2Arachidonate 5-lipoxygenaseALOX5
P3Macrophage migration inhibitory factorMIF
P4Catechol O-methyltransferaseCOMT
P5Prostaglandin G/H synthase 2PTGS2
P6Interleukin-1 betaIL1B
P7Interferon gammaIFNG
P8Interleukin-4IL4
P9Proheparin-binding EGF-like growth factorHBEGF
P10Caspase-3CASP3
P11RAC-alpha serine/threonine-protein kinaseAKT1
P12Retinoblastoma-associated proteinRB1
P13Mitogen-activated protein kinase 14MAPK14
P14Nuclear factor erythroid 2-related factor 2NFE2L2
P15Cytochrome P450 1A1CYP1A1
P16Protein kinase C beta typePRKCB
P17Pyruvate kinase PKMPKM
P18Vascular endothelial growth factor AVEGFA
P19Matrix metalloproteinase-9MMP9
P20Retinoblastoma-like protein 2RBL2
P21Cytochrome cCYCS
P22CholecystokininCCK
P23Dipeptidyl peptidase 4DPP4
P24Peroxisome proliferator-activated receptor gammaPPARG
P25Peroxisome proliferator-activated receptor alphaPPARA
P26NAD(P)H dehydrogenase [quinone] 1NQO1
P27Growth hormone secretagogue receptor type 1GHSR
P28B-cell lymphoma 6 proteinBCL6
P29Cellular tumor antigen p53TP53
P30Glucose-6-phosphate 1-dehydrogenaseG6PD
P31T-lymphocyte activation antigen CD80CD80
P32Heme oxygenase 1HMOX1
P33Sterol O-acyltransferase 1SOAT1
P34Cyclin-dependent kinase 2CDK2
P35Cyclin-dependent kinase 4CDK4
P36Neurogenic locus notch homolog protein 1NOTCH1
P37Tumor necrosis factor ligand superfamily member 6FASLG
P38Cytochrome P450 3A4CYP3A4
P39Nitric oxide synthase, inducibleNOS2
P40Nitric oxide synthase, brainNOS1
P41Mitogen-activated protein kinase 8MAPK8
P42Poly [ADP-ribose] polymerase 1PARP1
P43NAD-dependent protein deacetylase sirtuin-1SIRT1
P44Cytochrome P450 1B1CYP1B1
P45Induced myeloid leukemia cell differentiation protein Mcl-1MCL1
P46Serine/threonine-protein kinase pim-1PIM1
P47Angiotensin-converting enzymeACE
P48Hypoxia-inducible factor 1-alphaHIF1A

Potential protein targets of representative active compounds in WFC against PLGC.

Enrichment Analysis of Candidate Targets for Wei-Fu-Chun Against Precancerous Lesions of Gastric Cancer

To further explore the possible functions of the 48 therapeutic targets and reveal the relationship between active components and their underlying targets in PLGC, we performed pathway enrichment analysis on PLGC-related protein targets and obtained the main related signaling pathways of target proteins (p-value < 0.01). The 61 anti-PLGC pathways of WFC were listed in Table 6. These therapeutic targets were mainly distributed in PI3K/Akt pathway, MAPK pathway, vascular endothelial growth factor (VEGF) pathway, hypoxia-inducible factor-1 (HIF-1) pathway, and tumor necrosis factor (TNF) pathway, and FoxO pathway. In addition, According to the GO enrichment analysis results, we found that the functions of therapeutic targets were involved in multiple biological processes such as peptide chain serine phosphorylation, RNA polymerase II promoter transcription, cellular hypoxia, apoptosis, vascular endothelial cell migration, macrophage differentiation, vascular endothelial growth factor receptor, chemokine biosynthesis, cell proliferation, and nitric oxide biosynthesis (Figure 3).

TABLE 6

NO.Pathway IDPathway descriptionCountGenesP-Value
1hsa05161Hepatitis B12AKT1, MAPK1, CASP3, MMP9, CYCS, TP53, FASLG, MAPK8, RB1, CDK4, CDK2, PRKCB1.77E−09
2hsa05200Pathways in cancer17PTGS2, MMP9, PPARG, CYCS, TP53, FASLG, RB1, CDK4, CDK2, PRKCB, AKT1, MAPK1, CASP3, HIF1A, VEGFA, MAPK8, NOS21.94E−09
3hsa05219Bladder cancer7MAPK1, MMP9, VEGFA, TP53, HBEGF, RB1, CDK42.41E−07
4hsa05142Chagas disease (American trypanosomiasis)9AKT1, MAPK1, ACE, MAPK14, IFNG, IL1B, FASLG, MAPK8, NOS23.38E−07
5hsa05145Toxoplasmosis9AKT1, MAPK1, CASP3, MAPK14, CYCS, IFNG, MAPK8, ALOX5, NOS25.21E−07
6hsa05205Proteoglycans in cancer11AKT1, MAPK1, CASP3, HIF1A, MAPK14, MMP9, VEGFA, TP53, HBEGF, FASLG, PRKCB5.64E−07
7hsa05222Small cell lung cancer8AKT1, PTGS2, CYCS, TP53, RB1, NOS2, CDK4, CDK21.24E−06
8hsa05206MicroRNAs in cancer12NOTCH1, CASP3, CYP1B1, MCL1, PTGS2, HMOX1, MMP9, VEGFA, PIM1, TP53, SIRT1, PRKCB1.92E−06
9hsa04068FoxO signaling pathway9AKT1, MAPK1, RBL2, MAPK14, FASLG, BCL6, MAPK8, SIRT1, CDK22.35E−06
10hsa04066HIF-1 signaling pathway8AKT1, MAPK1, HIF1A, HMOX1, VEGFA, IFNG, NOS2, PRKCB2.84E−06
11hsa05212Pancreatic cancer7AKT1, MAPK1, VEGFA, TP53, MAPK8, RB1, CDK43.92E−06
12hsa04668TNF signaling pathway8AKT1, MAPK1, CASP3, PTGS2, MAPK14, MMP9, IL1B, MAPK85.88E−06
13hsa05140Leishmaniasis7IL4, MAPK1, PTGS2, MAPK14, IFNG, IL1B, NOS26.60E−06
14hsa05164Influenza A9AKT1, MAPK1, MAPK14, CYCS, IFNG, IL1B, FASLG, MAPK8, PRKCB1.64E−05
15hsa05152Tuberculosis9AKT1, MAPK1, CASP3, MAPK14, CYCS, IFNG, IL1B, MAPK8, NOS21.86E−05
16hsa05162Measles8IL4, AKT1, IFNG, TP53, IL1B, FASLG, CDK4, CDK22.46E−05
17hsa05223Non-small cell lung cancer6AKT1, MAPK1, TP53, RB1, CDK4, PRKCB3.17E−05
18hsa04370VEGF signaling pathway6AKT1, MAPK1, PTGS2, MAPK14, VEGFA, PRKCB4.81E−05
19hsa05210Colorectal cancer6AKT1, MAPK1, CASP3, CYCS, TP53, MAPK85.21E−05
20hsa05230Central carbon metabolism in cancer6PKM, AKT1, MAPK1, HIF1A, G6PD, TP536.08E−05
21hsa05214Glioma6AKT1, MAPK1, TP53, RB1, CDK4, PRKCB6.55E−05
22hsa04664Fc epsilon RI signaling pathway6IL4, AKT1, MAPK1, MAPK14, MAPK8, PRKCB8.15E−05
23hsa05133Pertussis6MAPK1, CASP3, MAPK14, IL1B, MAPK8, NOS21.30E−04
24hsa05168Herpes simplex infection8CASP3, CYCS, IFNG, TP53, IL1B, FASLG, MAPK8, CDK21.87E−04
25hsa05132Salmonella infection6MAPK1, MAPK14, IFNG, IL1B, MAPK8, NOS22.11E−04
26hsa04380Osteoclast differentiation7AKT1, MAPK1, MAPK14, PPARG, IFNG, IL1B, MAPK82.13E−04
27hsa04010MAPK signaling pathway9AKT1, MAPK1, CASP3, MAPK14, TP53, IL1B, FASLG, MAPK8, PRKCB2.32E−04
28hsa05014Amyotrophic lateral sclerosis5CASP3, NOS1, MAPK14, CYCS, TP533.22E−04
29hsa05203Viral carcinogenesis8PKM, MAPK1, CASP3, RBL2, TP53, RB1, CDK4, CDK23.75E−04
30hsa04151PI3K-akt signaling pathway10IL4, AKT1, MAPK1, MCL1, RBL2, VEGFA, TP53, FASLG, CDK4, CDK23.83E−04
31hsa04932Non-alcoholic fatty liver disease (NAFLD)7AKT1, PPARA, CASP3, CYCS, IL1B, FASLG, MAPK84.60E−04
32hsa04660T Cell receptor signaling pathway6IL4, AKT1, MAPK1, MAPK14, IFNG, CDK45.02E−04
33hsa04620Toll-like receptor signaling pathway6AKT1, MAPK1, CD80, MAPK14, IL1B, MAPK86.56E−04
34hsa04210Apoptosis5AKT1, CASP3, CYCS, TP53, FASLG7.36E−04
35hsa04919Thyroid hormone signaling pathway6AKT1, MAPK1, NOTCH1, HIF1A, TP53, PRKCB9.49E−04
36hsa04115p53 signaling pathway5CASP3, CYCS, TP53, CDK4, CDK29.86E−04
37hsa04722Neurotrophin signaling pathway6AKT1, MAPK1, MAPK14, TP53, FASLG, MAPK80.001150085
38hsa04071Sphingolipid signaling pathway6AKT1, MAPK1, MAPK14, TP53, MAPK8, PRKCB0.001150085
39hsa05218Melanoma5AKT1, MAPK1, TP53, RB1, CDK40.001226145
40hsa05169Epstein-Barr virus infection6AKT1, MAPK14, TP53, MAPK8, RB1, CDK20.001238565
41hsa05220Chronic myeloid leukemia5AKT1, MAPK1, TP53, RB1, CDK40.001291966
42hsa05332Graft-vs.-host disease4CD80, IFNG, IL1B, FASLG0.001326903
43hsa05143African trypanosomiasis4IFNG, IL1B, FASLG, PRKCB0.001326903
44hsa05160Hepatitis C6AKT1, MAPK1, PPARA, MAPK14, TP53, MAPK80.001818362
45hsa05330Allograft rejection4IL4, CD80, IFNG, FASLG0.001854692
46hsa04914Progesterone-mediated oocyte maturation5AKT1, MAPK1, MAPK14, MAPK8, CDK20.002598619
47hsa04012ErbB signaling pathway5AKT1, MAPK1, HBEGF, MAPK8, PRKCB0.002598619
48hsa04940Type I diabetes mellitus4CD80, IFNG, IL1B, FASLG0.002677073
49hsa05215Prostate cancer5AKT1, MAPK1, TP53, RB1, CDK20.002709164
50hsa04912GnRH signaling pathway5MAPK1, MAPK14, HBEGF, MAPK8, PRKCB0.003060147
51hsa04913Ovarian steroidogenesis4CYP1B1, CYP1A1, PTGS2, ALOX50.004158486
52hsa04723Retrograde endocannabinoid signaling5MAPK1, PTGS2, MAPK14, MAPK8, PRKCB0.004453312
53hsa05231Choline metabolism in cancer5AKT1, MAPK1, HIF1A, MAPK8, PRKCB0.004453312
54hsa05146Amoebiasis5CASP3, IFNG, IL1B, NOS2, PRKCB0.005288502
55hsa04621NOD-like receptor signaling pathway4MAPK1, MAPK14, IL1B, MAPK80.006056193
56hsa04726Serotonergic synapse5MAPK1, CASP3, PTGS2, ALOX5, PRKCB0.006223084
57hsa00140Steroid hormone biosynthesis4CYP3A4, CYP1B1, CYP1A1, COMT0.006678959
58hsa04650Natural killer cell mediated cytotoxicity5MAPK1, CASP3, IFNG, FASLG, PRKCB0.008653181
59hsa04110Cell cycle5RBL2, TP53, RB1, CDK4, CDK20.009153158
60hsa05211Renal cell carcinoma4AKT1, MAPK1, HIF1A, VEGFA0.009543869
61hsa05120Epithelial cell signaling in Helicobacter pylori infection4CASP3, MAPK14, HBEGF, MAPK80.009945007

KEGG pathways regulated by WFC against PLGC.

FIGURE 3

Construction of Pharmacology-Network for Wei-Fu-Chun Against Precancerous Lesions of Gastric Cancer

Using the Cytoscape 3.1 software, we constructed an “origins-components-targets-pathways” pharmacology network of WFC (Figure 4). This network depicted the relationship between 61 pathways, 48 therapeutic targets, 13 active components and corresponding plant materials. The network also consisted of 64 nodes and 75 edges, of which Ginsenoside Rb1 (C3, degree = 7), Naringin (C7, degree = 9), Hesperidin (C8, degree = 8), Hesperetin (C9, degree = 7), and Oridonin (C11, degree = 8) had high degrees and were centrally located in the network, suggesting that these active compounds may be the key components of WFC in the treatment of PLGC.

FIGURE 4

Model Test Results of Precancerous Lesions of Gastric Cancer

The speed of weight gain in the model group was much lower than that in the normal group. At the end of the fourth week, the weight of the high dose group, the low dose group, and the Vitacoenzyme group showed a rising trend after the simultaneous modeling and administration of the high dose group, the low dose group, and the vitamin enzyme group (Figure 5A). The increase rate of the high dose group was higher than that of the other two groups. The weight of the model group increased and then decreased until the end of the model. Compared with the normal group, there was a significant statistical difference in the activity value of pepsin in the normal group and the model group (p < 0.05). Compared with the model group, the activity value of pepsin in the high-dose group was significantly different (p < 0.05). There was no significant difference in protease activity between the low dose group and the model group. There was also no significant difference in pepsin activity between the high-dose group and the normal group (p > 0.05) (Figure 5B). The histopathology of gastric mucosa was demonstrated by hematoxylin eosin staining. Atrophic glands, intestinal metaplasia and lymphocyte infiltration were shown in the model group, and compared with the model group, the above pathological manifestations were alleviated in varying degrees (Figure 5C). RT-PCR results showed that mRNA expression of VEGF, FOXO4, AKT, TP53, FAS, MAPK8, MAPK11, and MAPK14 in the model group was significantly up-regulated compared with that in the N group (p < 0.05)., while mRNA expression of interleukin-10 (interleukin-10, il-10) was down-regulated (p < 0.01). mRNA expressions of VEGF, FOXO4, AKT, TP53, FAS, MAPK8, MAPK11, and MAPK14 were all significantly down-regulated in the WFC high dose group (p < 0.05) (Figure 6).

FIGURE 5

FIGURE 6

Discussion

WFC, an herbal prescription with three medicines, may contain thousands of compounds, however, naringin is the only maker compound of WFC in 2015 edition of “Chinese Pharmacopoeia.” In this study, we hypothesized that unilateral factors and single targets are insufficient to demonstrate the complex mechanisms of WFC. The network pharmacology method used in this study is a novel methodology based on the construction of multilayer networks of disease phenotype-gene-drug to predict drug targets in a holistic manner and promote efficient drug discovery (Liu and Sun, 2012). This method represents a breakthrough in comparison with the traditional herbal medicine research pattern “gene target-disease” and initiates the new pattern of “multiple genes multiple targets-complex diseases” (Hopkins, 2008; Ma et al., 2016). With this method, we proved that XCC was the critical ingredient involved in the treatment of PLGC, which corresponded to the constituents of WFC with 86.8% weight of XCC in WFC. HS was also a major herb that regulated PLGC. Moreover, WFC is a multiple-component complex system. (Zhang et al., 2012) unambiguously identified or tentatively characterized 46 components in WFC tablet, including 26 saponins, 10 flavonoids, and 10 other compounds. However, it is not enough to understand the chemical components of WFC, which makes it rather difficult to define the functions of this herbal medicine from material basis and chemical properties. Therefore, a chemical fingerprint analysis of WFC was necessary. Compared with the material basis of the three herbs in WFC, a chemical fingerprint analysis of WFC was fully carried out by means of UHPLC-ESI-Q-TOF/MS. Finally, a total of 178 compounds were identified in WFC, including 93 compounds (70 terpene) originally from I. amethystoides, 51 compounds from Fructus aurantii, 31 compounds from red ginseng, which basically demonstrated the material basis in WFC. However, the main components’ content and dose-effect relationship should be further investigated.

In network pharmacology studies, there were 86 candidate compounds (77 absorbed components and nine metabolites) and 105 potential targets. Thirteen active components and 48 protein targets were selected to explore the effect of WFC against PLGC. The results showed that PI3K/Akt pathway, MAPK pathway, VEGF pathway, HIF-1 pathway, TNF pathway, and FOXO pathway may be involved as the anti-PLGC pathways of WFC. In addition, ginsenoside Rb1, naringin, hesperidin, hesperetin, and oridonin may be the key components of WFC in the treatment of PLGC. Ginsenoside Rb1was shown to exert anti-inflammatory effects in Modulating TLR-4 dimerization and NF-kB/MAPKs signaling pathways (Gao et al., 2020). Ginsenoside Rb1 also enhanced the phagocytic capacity of macrophages for bacteria via activation of the p38/Akt pathway, which may be a useful pharmacological adjuvant for the treatment of bacterial infections in clinically relevant conditions (Xin et al., 2019). Moreover, naringin induced autophagy-mediated growth inhibition by downregulating the PI3K/Akt/mTOR cascade via activation of MAPK pathways in AGS cancer cells (Raha et al., 2015). As for hesperetin, it induced apoptosis in human glioblastoma cells via p38 MAPK activation (Li et al., 2020). Finally, oridonin’s anticancer effects on colon cancer were mediated via BMP7/p38 MAPK/p53 signaling (Liu et al., 2018). Overall, this suggested that MAPK pathway, PI3K/Akt pathway, and p38/Akt pathway may be the key pathways of WFC treating PLGC.

To verify the network pharmacology prediction results, in vivo rat experiments were carried out. Pepsin is formed by pepsinogen stimulated by gastric acid. Pepsin is mainly secreted by the main cells. Atrophy of gastric glands and metaplasia of intestinal epithelium reduce the main cells. From superficial gastritis, atrophic gastritis/dysplasia to gastric cancer, pepsinogen in pathological tissues decreases and then pepsin activity decreases. In chronic atrophic gastritis patients with or without intestinal metaplasia, pepsinogen I often decreased (Terasawa et al., 2014). In this experiment, WFC restored pepsin activity in the rat model of PLGC.

MAPK is the main transmitter of intracellular and extracellular signals. P38 and JNK are the important parts of its four major subgroups. JNK pathway and p38 pathway mediate the transmission of cytokines and inflammatory mediators and participate in cell cycle, apoptosis, and migration. This process plays an important role in the development of precancerous lesions to gastric cancer. JNK mainly exists in the cytoplasm and accumulates rapidly and significantly in the nucleus after being activated by the superior kinase. The activation of transcription factors in the nucleus includes TP53, c-Jun and so on (Liu and Lin, 2005), and then produces biological effects. The positive rate of JNK expression in gastric cancer was 75%, and it positively correlated with the size of the tumor and the early and late stage of the tumor (Wang, 2009). Helicobacter pylori can stimulate the invasion of AGS gastric cancer cells through JNK signaling pathway (Díaz-Serrano et al., 2018). Inhibition of JNK pathway can enhance the antitumor effect of trail on MGC803 gastric cancer cells (Liu et al., 2011). P38 has five isomers, p38 α (p38), p38 ß 1, p38 ß 2, p38 γ, p38 δ. 38 α, and p38 ß tissues are widespread. P38 pathway plays an important role in cell cycle regulation and can induce cell cycle. The inhibition of p38 pathway may be one of the mechanisms of synergistic antitumor effect of Adriamycin and monomer PA-2 (Liang et al., 2020). In gastric cancer patients with high expression of lncRNA-aoc4p, inhibiting the expression of lncRNA-aoc4p could reduce the expression level of JNK and p38 protein and inhibit cell proliferation, migration, and invasion (Qu et al., 2019). FOXO4, as a member of the FOXO family of transcription factors, is regulated by microRNA in a variety of cancer cells, and its abnormal expression is closely related to gastrointestinal tumors (Gross et al., 2008; Liu et al., 2020). The current study further proved the therapeutic effect of WFC on PLGC in rats, and preliminarily explored and verified the results of network pharmacology. The detection results of MAPK pathway genes p38 α, p38 β, JNK and its upstream and downstream factors TP53 and VEGF α, as well as FOXO4 and AKT genes showed consistency. We believe that MAPK pathway is involved in the mechanism of action of WFC on PLGC, which needs to be further explored.

Conclusion

In conclusion, a simple and reliable UHPLC–ESI-Q-TOF/MS technique was established to profile complex compounds in WFC and describe their absorption behavior in plasma samples after oral administration of WFC. A total of 178 compounds were identified. In addition, 77 absorbed compounds of parent molecules in WFC were detected. Among these compounds, the most absorbed ones were terpenes from XCC, flavonoids from ZQ and saponins from HS. The current study supplemented previous WFC research, and MS data contributed to the identification of allied natural compounds. The screening of in vivo absorbed and metabolic compounds provided constructive material basis for further research on the pharmacology and curative mechanisms of WFC. Moreover, the network pharmacology method was used to predict the active components, corresponding therapeutic targets, and related pathways of WFC in the treatment of PLGC. Finally, based on the major compounds of WFC and their metabolites in rat plasma and existing databases, 13 active components, 48 therapeutic targets, and 61 pathways were found to act against PLGC. The results from rat experiment showed that WFC could improve the weight of PLGC rats and the gastric mucosa histopathological changes partly by inhibiting MAPK signaling pathway to increase pepsin secretion.

This study offered an applicable approach for the identification of chemical components, absorbed compounds, and metabolic compounds of WFC, and provided a method to explore bioactive ingredients and action mechanisms of WFC.

Funding

This work was supported by Science and Technology Commission of Shanghai Municipality (Nos. 15DZ1900104 and 15DZ1900100 to MS and GY); the fourth batch of Chinese medicine (basic) talents of the State Administration of TCM (No. 2017-124 to MS); Construction of Postgraduate Innovation Course in Shanghai University of Traditional Chinese Medicine (No. 2017 to MS); and Natural Science Foundation of Shanghai (No. 20ZR1458100 to HW).

Statements

Data availability statement

The raw data supporting the conclusions of this manuscript will be made available by the authors, without undue reservation, to any qualified researcher.

Ethics statement

All feeding conditions were in compliance with the Chinese Animal Welfare Law and the relevant regulations of Fudan University and Shanghai University of Traditional Chinese Medicine Experimental Animal Ethics Committee. Wistar rats from the Experimental Animal Center of Shanghai University of Traditional Chinese Medicine were recruited to establish the model of gastric precancerous lesions. Animal license Code: SYXK Shanghai 2014-008. Ethics No.: PZSHUTCM19039006.

Author contributions

HW, RW, and DX contributed equally. HW conducted the experimental part of the main component analysis of WFC. Network pharmacology was mainly analyzed by RW, DX performed most of the pharmacological experiments, analyzed the data, and participated in the manuscript draft. LD and XL helped complete animal feeding and analysis of the main components in plasma of Weifuchun tablets. YB, XC, and BN polished the manuscript. SW, KL, and WC monitored the drug quality and helped complete the data collation. GY and MS directed the study, and drafted and finalized the manuscript. All authors read and approved the final manuscript.

Conflict of interest

HW, RW, XL, KL and GY were employed by Shangai Pharmaceuticals Holding Co., Ltd.. LD was employed by Shanghai Zhonghua Pharmaceuticals Co., Ltd. WC were employed by Huqingyutang Chinese Medicine Medernization Research Institute of Zhejiang Province. The remaining authors declare that the research was conducted in the absence of any commercial or financial relationships that could be constructed as a potential conflict of interest.

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Summary

Keywords

Wei-Fu-Chun tablet, precancerous lesions of gastric cancer, network pharmacology, effective substances and mechanism, UHPLC-ESI-Q-TOF/MS

Citation

Wang H, Wu R, Xie D, Ding L, Lv X, Bian Y, Chen X, Nisma Lena BA, Wang S, Li K, Chen W, Ye G and Sun M (2020) A Combined Phytochemistry and Network Pharmacology Approach to Reveal the Effective Substances and Mechanisms of Wei-Fu-Chun Tablet in the Treatment of Precancerous Lesions of Gastric Cancer. Front. Pharmacol. 11:558471. doi: 10.3389/fphar.2020.558471

Received

26 May 2020

Accepted

21 September 2020

Published

18 November 2020

Volume

11 - 2020

Edited by

Raffaele Capasso, University of Naples Federico II, Italy

Reviewed by

Xiao Liu, Nanjing University of Chinese Medicine, China

Xi rui He, Zunyi Medical University, China

Updates

Copyright

© 2020 Wang, Wu, Xie, Ding, Lv, Bian, Chen, Nisma Lena, Wang, Ye and Sun.

This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

*Correspondence: Mingyu Sun, ; Guan Ye,

†These authors have contributed equally to this work

This article was submitted to Ethnopharmacology, a section of the journal Frontiers in Pharmacology

Disclaimer

All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article or claim that may be made by its manufacturer is not guaranteed or endorsed by the publisher.

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