Journal of Ethnopharmacology 330 (2024) 118228

Available online 19 April 2024

0378-8741/© 2024 The Authors. Published by Elsevier B.V. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/bync-nd/4.0/).

Revealing the mechanism of ethyl acetate extracts of Semen Impatientis

against prostate cancer based on network pharmacology

and transcriptomics

Bintao Hu a,b

, Chengwei Wang a,b

, Yue Wu a,b

, Chenglin Han a,b

, Jihong Liu a,b

,

Ruibao Chen a,b,**, Tao Wang a,b,*

a Department of Urology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430030, China b Institute of Urology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430030, China

ARTICLE INFO

Handling Editor: Dr. Y Min

Keywords:

Ethyl acetate extracts of semen impatientis

Prostate cancer

Network pharmacology

Transcriptomics

ATF3

AR

ABSTRACT

Ethnopharmacological relevance: Prostate cancer (PCa) is the most common malignancy of the male genitourinary

system and currently lacks effective treatment. Semen Impatientis, the dried ripe seed of Impatiens balsamina L., is

described by the Chinese Pharmacopoeia as a traditional Chinese medicine (TCM) and is used in clinical practice

to treat tumors, abdominal masses, etc. In our previous study, the ethyl acetate extracts of Semen Impatientis

(EAESI) was demonstrated to be the most effective extract against PCa among various extracts. However, the

biological effects of EAESI against PCa in vivo and the specific antitumor mechanisms involved remain unknown.

Aim of the study: In this study, we aimed to investigate the antitumor effect of EAESI on PCa in vitro and in vivo

by performing network pharmacology analysis, transcriptomic analysis, and experiments to explore and verify

the underlying mechanisms involved.

Materials and methods: The antitumor effect of EAESI on PCa in vitro and in vivo was investigated via CCK-8, EdU,

flow cytometry, and wound healing assays and xenograft tumor models. Network pharmacology analysis and

transcriptomic analysis were employed to explore the underlying mechanism of EAESI against PCa. Activating

transcription factor 3 (ATF3) and androgen receptor (AR) were confirmed to be the targets of EAESI against PCa

by RT‒qPCR, western blotting, and rescue assays. In addition, the interaction between ATF3 and AR was

assessed by coimmunoprecipitation, immunofluorescence, and nuclear–cytoplasmic separation assays.

Results: EAESI decreased cell viability, inhibited cell proliferation and migration, and induced apoptosis in AR+

and AR− PCa cells. Moreover, EAESI suppressed the growth of xenograft tumors in vivo. Network pharmacology

analysis revealed that the hub targets of EAESI against PCa included AR, AKT1, TP53, and CCND1. Transcriptomic analysis indicated that activating transcription factor 3 (ATF3) was the most likely critical target of

EAESI. EAESI downregulated AR expression and decreased the transcriptional activity of AR through ATF3 in

AR+ PCa cells; and EAESI promoted the expression of ATF3 and exerted its antitumor effect via ATF3 in AR+ and

AR− PCa cells.

Conclusions: EAESI exerts good antitumor effects on PCa both in vitro and in vivo, and ATF3 and AR are the

critical targets through which EAESI exerts antitumor effects on AR+ and AR− PCa cells.

1. Introduction

Prostate cancer (PCa) is the most prevalent malignant tumor of the

male genitourinary system; it has the second highest incidence rate

among all malignant tumors affecting males worldwide, following only

lung cancer. It is also one of the leading causes of cancer-related deaths

in men globally, ranking fifth among all male cancers in terms of mortality rate (Sung et al., 2021). Due to the unspecific symptoms in the

early stage of PCa, patients usually develop advanced disease by the

time the noticeable symptoms manifest (Layman et al., 2019). As the

* Corresponding author. Department of Urology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430030, China.

** Corresponding author. Department of Urology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430030,

China.

E-mail addresses: chen0211090@163.com (R. Chen), 2005tj0548@hust.edu.cn (T. Wang).

Contents lists available at ScienceDirect

Journal of Ethnopharmacology

journal homepage: www.elsevier.com/locate/jethpharm

https://doi.org/10.1016/j.jep.2024.118228

Received 19 December 2023; Received in revised form 30 March 2024; Accepted 18 April 2024

Journal of Ethnopharmacology 330 (2024) 118228

2

androgen receptor (AR) signaling pathway plays a driving role in the

development of PCa (Lonergan and Tindall, 2011), androgen deprivation therapy (ADT) serves as the first-line treatment for prostate cancer.

However, ADT has severe side effects, and the majority of PCa cases

treated with ADT progress to metastatic castration-resistant PCa

(Schatten, 2018). Once PCa metastasizes, patient survival rate decreases

significantly, and drug therapy becomes less effective (Boudadi and

Antonarakis, 2016). Therefore, there is an urgent demand for a new and

effective alternative treatment modality for PCa.

Traditional Chinese medicine (TCM) is characterized by multicomponents and multi-targets, and has been proven to be effective

and to have fewer side effects over thousands of years of practice (Yu

et al., 2018). TCM could benefit patients in the following ways:

improving symptoms and quality of life, reducing drug resistance and

disease recurrence, and extending survival time (Jiang and Hua, 2009).

It is widely accepted as the dominant modality of complementary and

alternative treatment for cancer patients (Xiang et al., 2019). Semen

Impatientis, the dried ripe seed of Impatiens balsamina L., is a TCM

officially recorded in the Chinese Pharmacopoeia; it has therapeutic

effects on tumors, abdominal masses, amenorrhea, bone and prostate

hyperplasia, and so on (Ma, 2007). It has been reported that Semen

Impatientis is commonly used in clinical practice for treating malignant

tumors (Li, 2016; Wu, 2019), and extracts of Semen Impatientis have

been shown to inhibit the growth of cancer cells (Wu et al., 2017).

Moreover, in modern pharmacological research, multiple extracted

components of Impatiens balsamina L. have been reported to have antitumor activity (Daud et al., 2021; Shin et al., 2015; Wang and Lin,

2012). Similarly, in our previous research, various extracts of Semen

Impatientis such as water extracts, petroleum ether extracts, ethanol

extracts, butanol extracts, and ethyl acetate extracts, all inhibited the

growth of PCa cells, but ethyl acetate extracts of Semen Impatientis

(EAESI) exhibited the strongest inhibitory effect (Wang et al., 2017).

However, the biological effects of EAESI on PCa in vivo and the specific

antitumor mechanisms involved remain unknown, and further exploration is warranted.

Network pharmacology is an important methodology for constructing interactive models of ‘drug-target-disease’ networks to reveal the

complex mechanisms of drugs in diseases from a systematic and integrative viewpoint (Hopkins, 2008). The characteristics of network

pharmacology resonate well with the multicomponent and multitarget

mechanisms of TCMs, making it a powerful tool for studying TCMs,

identifying drug targets and accelerating drug development (Gong et al.,

2018; Zhang et al., 2013, 2017). In addition to network pharmacology,

transcriptomics, an analytical method for studying gene transcription

and transcriptional regulation, is also an effective approach for revealing

changes in gene expression after drug treatment and identifying the

critical targets through which TCMs exert their effects on diseases (Li, H.

et al., 2020). It is widely used for revealing molecular pathogenesis (Li,

L. et al., 2020), determining the functions of unknown genes (Shi et al.,

2021), identifying drug targets (Liu et al., 2021), and so on.

Therefore, in this study, in addition to investigating the effect of

EAESI on PCa in vivo and in vitro, network pharmacology and transcriptomic analyses were employed to identify the critical targets of

EAESI in PCa, and subsequent experiments were conducted for validation. The flowchart of the present study is shown in Fig. 1. This study on

the effect and underlying mechanism of EAESI provides experimental

evidence for its clinical application and may contribute to the development of an alternative target for PCa therapy.

Fig. 1. The flowchart of this study.

B. Hu et al.

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2. Materials and methods

2.1. Chemicals and antibodies

Semen Impatientis was authenticated by Professor Yufeng Ding

(Tongji Medical College, Huazhong University of Science and Technology). A representative specimen was deposited in the Faculty of Pharmaceutical Sciences, Tongji Medical College, Huazhong University of

Science and Technology, Wuhan, China (specimen number P20020713).

The preparation of EAESI was described in detail in our previous

research (Wang et al., 2017). Briefly, Semen Impatientis was macerated

in 95% ethanol, filtered, and distilled, and EAESI was then obtained. The

primary antibodies used in this study included anti-AR (Cell Signaling

Technology, Massachusetts, USA; #5153s), anti-Histone-H3

(#17168-1-AP), anti-Ki-67 (#27309-1-AP), anti-BAX (#50599-2-Ig),

anti-Bcl 2 (#26593-1-AP) (Proteintech, Wuhan, China), anti-TMPRSS2

(#DF7917), anti-KLK3 (#AF0246) (Affinity Biosciences, Jiangsu,

China), anti-GAPDH (Boster, Wuhan, China; #A00227-1), anti-control

IgG (#AC005), anti-β-actin (#AC026) (ABclonal, Wuhan, China), and

anti-ATF3 (Abcam, Cambridge, UK; #ab254268) antibodies. The secondary antibody used was HRP-conjugated AffiniPure goat anti-rabbit

IgG (H + L) (Boster, Wuhan, China; #BA1054).

2.2. Ultra-high-performance liquid chromatography tandem mass

spectrometry (UHPLC- MS/MS) analysis

The chemical components of EAESI were identified through UHPLCMS/MS analysis, which was entrusted to Shanghai Biotree Biomedical

Technology Co., Ltd. (Shanghai, China). The specific experimental steps

are summarized as follows: extract EAESI samples with 1000 μl of

methanol extract, then subject it to ultrasound and centrifugation. After

that, filter the solution with a 0.22 μm microporous filter. The obtained

filtrate is used for UHPLC-MS/MS analysis. The LC separation was

completed through a Waters UPLC BEH C18 column and a UHPLC system (Vanquish, Thermo Fisher Scientific). Subsequently, based on the

information dependent acquisition mode, MS/MS data was obtained

using the Q Exactive Focus mass spectrometer coupled with Xcalibur

software.

2.3. Cell culture

The human prostate cancer cell lines LNCaP, 22Rv1, PC-3, and

DU145 were purchased from Procell Life Science & Technology Co., Ltd.

(Wuhan, China). LNCaP, 22Rv1, and DU145 cells were cultured in

RPMI-1640 medium (Boster, Wuhan, China; #PYG0006) containing

10% fetal bovine serum (FBS) (GIBCO, USA; #10099141C) and 1%

penicillin‒streptomycin (Servicebio, Wuhan, China; #G4003), while

PC-3 cells were cultured in complete F12K medium (Boster, Wuhan,

China; #PYG0036). All the cultured cells were incubated at 37 ◦C in a

5% CO2 incubator.

2.4. CCK-8 assay

A Cell Counting Kit-8 (CCK-8) (Yeasen, Shanghai, China;

#40203ES60) assay was used to evaluate the viability of PCa cells

treated with various concentrations of EAESI according to the manufacturer’s protocol. PCa cells were seeded in 96-well plates at a density

of approximately 5000 cells per well. When the cells grew to 60–70%

confluence, they were treated with various concentrations of EAESI for

24 h and then incubated with CCK-8 solution for 2 h at 37 ◦C. Cell

viability was determined by measuring the absorbance at 450 nm in a

microplate reader (Thermo Scientific, Shanghai, China).

2.5. 5-Ethynyl-2′-deoxyuridine (EdU) assay

The Cell-Light EdU Apollo 567 In Vitro Kit (RI-BOBIO, Guangzhou,

China; #C10310-1) was used to perform an EdU assay to evaluate the

effect of EAESI on cell proliferation. The experimental protocol was as

follows: after EAESI treatment for 24 h, PCa cells were incubated with

EdU solution for 2 h. Subsequently, the cells were fixed with 4% paraformaldehyde and stained with Apollo fluorescent dyes and Hoechst

33,342 reagent. After completing the staining step, images were acquired with a fluorescence microscope.

2.6. Flow cytometry for cell cycle and apoptosis

PCa cells were seeded in 6-well plates and treated with different

concentrations of EAESI for 24 h. For cell cycle analysis, the cells were

collected, fixed with 70% ethanol overnight at 4 ◦C, and stained with

RNase A and PI solution for 30 min at 37 ◦C (Yeasen, Shanghai, China;

#40301ES50). For apoptosis analysis, the cells were collected with

EDTA-free trypsin (Boster, Wuhan, China; #PYG0067) and stained with

Annexin V-FITC and PI staining solution (Yeasen, Shanghai, China;

#40302ES50) for 15 min at room temperature (RT). After staining, a

CytoFlex cytometer (Beckman Coulter, USA) was used to detect the cell

cycle distribution and apoptosis. The raw cell cycle and apoptosis data

were analyzed using ModFit and FlowJo software, respectively.

2.7. Wound healing assay

When the confluence of PCa cells cultured in 6-well plates reached

90%, the cell layers were scratched with 200 μL pipette tips, and images

of the scratches were acquired under a microscope. In addition, marker

lines were drawn on the back of the 6-well plate to ensure that the position of the image acquired at each time point under the microscope

was consistent. After treatment with EAESI for 24 h, images of the

scratches were acquired. The area of the scratch wounds at both time

points was measured by ImageJ software, and the wound healing rate

was calculated according to this information.

2.8. Animal experiments

All animal experiments in this study conformed to the State Council

of China-approved Regulations for the Administration of Affairs Concerning Experimental Animals and were approved by the Laboratory

Animal Welfare & Ethics Committee of Tongji Hospital of Huazhong

University of Science and Technology (TJH-202107002). Approximately 1.5 × 106 PC-3 cells were collected and subcutaneously injected

into the right flank region of male BALB/c nude mice at 6 weeks of age.

When the diameter of the xenograft tumors reached 5 mm, all the mice

were randomly divided into 5 groups (n = 6) and administered 100 μl of

EAESI at different concentrations (0, 0.02, 0.06, 0.12, or 0.24 g/mL) by

gavage once a day. After treatment with different concentrations of

EAESI, the xenograft tumors were measured every four days with calipers to construct tumor growth curves. The tumor volume was calculated as 0.5 × length × width × width. After 21 days of EAESI treatment,

each group of mice and the corresponding harvested tumor tissues were

weighed and photographed.

2.9. Immunohistochemistry (IHC)

Xenograft tumor tissues were fixed with 4% paraformaldehyde for

24–48 h, embedded in paraffin, and then sliced into 5 μm thick paraffin

sections. Afterward, the paraffin sections were deparaffinized and

rehydrated using xylene and ethanol. After antigen retrieval, the slides

were treated with 3% H2O2 to block endogenous peroxidase activity,

blocked with 10% goat serum for 30 min, incubated with a primary

antibody overnight at 4 ◦C and a secondary antibody at RT for 1 h, and

then incubated with DAB solution. Image-Pro Plus 6.0 software was used

for quantitative evaluation.

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2.10. TUNEL assay

The TUNEL assay was performed according to the instructions of the

TMR (Red) TUNEL Cell Apoptosis Detection Kit (Servicebio, Wuhan,

China; #G1502-50 T). First, the paraffin sections were deparaffinized

and rehydrated using xylene and ethanol. Next, proteinase K working

solution and equilibration buffer were added for 10 min at RT. The slides

were then incubated with TUNEL reaction solution for 1 h at 37 ◦C.

Finally, DAPI solution was added to stain the nuclei. The slides were

photographed under a fluorescence microscope, and the images acquired were analyzed by ImageJ software.

2.11. Network pharmacology analysis

Network pharmacology is an effective approach for analyzing TCMs

to unveil the principles of small molecule regulation and predict TCM

targets (Wang et al., 2021; Zhang et al., 2019). The Chinese name of

Semen Impatientis was searched in the Traditional Chinese Medicine

Systems Pharmacology (TCMSP) platform (https://tcmsp-e.com/tcmsp.

php) to obtain the ingredients and related targets. With the screening

conditions of oral bioavailability (OB) ≥ 30% and drug-likeness (DL) ≥

0.18, bioactive ingredients and their corresponding related targets were

identified. In addition, PCa-related targets were obtained from the

public databases GeneCards (https://www.genecards.org/), DrugBank

(https://go.drugbank.com/), Online Mendelian Inheritance in Man

(OMIM) (https://omim.org/), and Therapeutic Target Database (TTD)

(https://db.idrblab.net/ttd/). The drug-related targets and PCa-related

targets were then intersected to obtain the common targets. The common targets were utilized to construct a protein‒protein interaction

(PPI) network by setting the minimum required interaction score to

“highest confidence” (0.900) in the STRING database (https://string-db.

org/). Additionally, the bioactive ingredients and common targets were

used to construct a bioactive ingredient‒target interaction network with

Cytoscape 3.7.0 software. To identify the hub targets for PCa, topological analysis of the PPI network was conducted with the cytoNCA plug-in

of Cytoscape. The following parameters were selected to evaluate the

topological features: betweenness centrality (BC), closeness centrality

(CC), degree centrality (DC), eigenvector centrality (EC), local average

connectivity-based method (LAC), and network connectivity (NC). The

hub targets in the network were identified based on the median value of

each parameter. The above databases were accessed in March 2022.

2.12. Western blotting (WB)

PCa cells were collected with RIPA buffer (#AR0102) supplemented

with PMSF (#AR1178) and phosphatase inhibitors (#AR1183) (Boster,

Wuhan, China). The protein concentration was then measured with a

BCA protein concentration kit (Boster, Wuhan, China; #AR1189). Total

protein (20 μg) was separated by 10% SDS‒PAGE and then transferred

to PVDF membranes. The protein-containing membranes were blocked

with 5% nonfat milk at RT for 1.5 h and incubated with a primary

antibody at 4 ◦C overnight. After washing with TBST three times, the

membranes were incubated with a secondary antibody at RT for 1 h.

Finally, the membranes were immersed in reagents from an enhanced

chemiluminescence (ECL) kit (Servicebio, Wuhan, China; #G2014-100

ML) and then visualized and photographed with a ChemiDocTM MP

Imaging System (Bio-Rad). The images were analyzed by Image Lab 6.1

software to evaluate protein expression.

2.13. Reverse transcription and quantitative PCR (RT‒qPCR)

Total RNA extracted with RNAiso Plus reagent (Takara, Dalian,

China; #9108) was reverse transcribed into cDNA using a cDNA Synthesis Kit (Yeasen, Shanghai, China; #11137ES10) according to the

manufacturer’s instructions. Subsequently, the cDNA was amplified and

analyzed with qPCR SYBR Green Master Mix reagents (Yeasen,

Shanghai, China; #11202ES03) and a QuantStudio 6 Flex instrument

(Applied Biosystems). The primers were synthesized by Beijing Tsingke

Biotech Co., Ltd, and the corresponding sequences were added in

Table S1.

2.14. Transcriptome sequencing

PC3 cells treated with DMSO or 0.10 mg/mL EAESI were collected

with RNAiso Plus reagent (Takara, Dalian, China; #9108) and sent to

BGI Genomics Co., Ltd. For transcriptome sequencing. The transcriptome sequencing data were then processed and analyzed to identify

differentially expressed genes (DEGs) through the Dr. Tom network

platform provided by BGI Genomics. Next, the DEGs were visualized on

heatmaps and volcano plots and subjected to GO term and KEGG

pathway enrichment analyses with R software packages.

2.15. Immunofluorescence analysis

22Rv1 cells were seeded on round coverslips (Biosharp, Hefei, China;

#BS-24-RC) that were placed in 6-well plates. When the cell confluence

reached approximately 50%, the 22Rv1 cells were treated with different

concentrations of EAESI. Thereafter, the cells were fixed with 4%

paraformaldehyde for 30 min at RT, permeabilized with 0.5% Triton X100 solution for 20 min, and blocked with goat serum for 1 h. After these

procedures, the cells were incubated with primary antibodies overnight

at 4 ◦C, with secondary antibodies for 1 h at RT, and then with DAPI

solution for 10 min to stain the nuclei. Each of the above steps was

followed by washing with phosphate-buffered saline (PBS) three times

for 5 min each. Finally, the fluorescently labeled cells were observed and

imaged in random fields of view at 200× magnification under an

OLYMPUS BX51 fluorescence microscope.

2.16. Nuclear–cytoplasmic separation assay

The nuclear–cytoplasmic separation assay was conducted according

to the protocol of the Nuclear-Cytosol Extraction Kit (Applygen, Beijing,

China; #P1200-50). Briefly, cells treated with EAESI for 24 h were lysed

with Cytosol Extraction Buffer A (CEB-A). After vigorous oscillation and

centrifugation, the cytoplasmic protein component was obtained from

the supernatant. CEB-A and Cytosol Extraction Buffer B (CEB-B) were

then added to the remaining precipitate. After the mixture was centrifuged, nuclear extraction buffer (NEB) was added to the precipitate.

After another round of centrifugation, the nuclear protein was acquired

from the supernatant. The cytoplasmic and nuclear proteins were then

utilized for WB analysis.

2.17. Coimmunoprecipitation

The coimmunoprecipitation assay was performed according to the

instructions of the coimmunoprecipitation kit (Biolinkedin, Shanghai,

China; #IK-1004). Cells treated with DMSO or EAESI were lysed using

an IP lysis mixture containing PMSF and phosphatase inhibitors. After

centrifugation, the required lysates were divided into three groups: the

Input, IgG, and IP groups. Equal amounts of IgG and a specific primary

antibody were added to the IgG and IP groups, respectively. Thereafter,

the lysates from the IgG and IP groups were incubated with the corresponding antibodies overnight at 4 ◦C. The beads were then added to the

complex for 2 h at RT. After washing three times with lysis buffer, the

precipitated proteins were added to SDS‒PAGE sample loading buffer

and boiled for 10 min at 100 ◦C.Finally, the proteins were subjected to

WB analysis.

2.18. Statistical analysis

All experiments conducted in the present study were independently

repeated three times for statistical analysis, and the experimental data

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are presented as the means ± standard deviations. The statistical analysis was conducted using GraphPad Prism 9.5.0 software. Comparisons

between two groups were performed by the independent t-test or Mann‒

Whitney U test, while comparisons among more than two groups were

performed by one-way ANOVA or the Kruskal‒Wallis H test. A calculated P value less than 0.05 was considered to indicate a statistically

significant difference.

3. Results

3.1. Components analysis of EAESI

To identify chemical components of EAESI, UHPLC-MS/MS was used

for analyzing EAESI samples. A total of 218 compounds in EAESI were

identified, which mainly included 37 Triterpenoids, 35 Flavonoids, 17

Sesquiterpenoids, 16 Isoflavonoids, and 11 Lignans. The chemical

composition of all compounds in EAESI was demonstrated by the total

positive ion chromatograms (Fig. 2A) and negative ion chromatograms

(Fig. 2B). The main compounds in EAESI included Glabrone, Solasodine,

Aurantiamide, cis-9,10-Epoxystearic acid, Peimine, Scutellarein, DSorbitol, Coumestrol, Isoimperatorin, and Calenduloside E.

3.2. EAESI inhibits the proliferation and decreases the viability of both

AR+ and AR− PCa cells

AR is one of the main factors driving PCa development and progression, and PCa cells can be classified into two types based on the

presence or absence of AR expression: AR+ and AR− PCa cells. Therefore, to explore the effect of EAESI and the related underlying

mechanisms, LNCaP and 22Rv1 cells were selected to represent AR+ PCa

cells, and PC-3 and DU145 cells were selected to represent AR− PCa cells

for follow-up experiments. Light microscopy revealed that EAESI can

affect the cellular state in a concentration-dependent manner (Fig. 3A).

To confirm the cytotoxicity of EAESI in PCa cells, a CCK-8 assay was

used to detect the viability of PCa cells treated with various concentrations of EAESI. Strikingly, the viability of both AR+ and AR− PCa cells

decreased in a concentration-dependent manner (Fig. 3B). The IC50

values of EAESI in LNCaP, 22Rv1, PC-3, and DU145 cells were 0.12,

0.10, 0.06, and 0.24 mg/mL, respectively. Considering the different

IC50 values in the PCa cell lines mentioned above, four concentrations

were used to explore the effects of EAESI on PCa cells: 0, 0.04, 0.1, and

0.2 mg/mL. An EdU assay was then used to evaluate the effect of EAESI

on cell proliferation. As shown in Fig. 3C–E, EAESI significantly

inhibited cell proliferation in a concentration-dependent manner.

Furthermore, flow cytometry was employed to explore the mechanism

by which EAESI inhibits cell proliferation. As indicated by the data in

Fig. 3F, the proportions of G0/G1-phase LNCaP and PC-3 cells were

significantly increased following EAESI treatment for 24 h. Thus, these

findings suggested that EAESI suppresses the growth of PCa cells

regardless of the AR expression status by inducing G0/G1-phase arrest.

3.3. EAESI inhibits migration and invasion and induces apoptosis in both

AR+ and AR− PCa cells

To assess the effect of EAESI on the migration capacity of PCa cells,

scratch wounds were made on LNCaP, 22Rv1, PC-3, and DU145 cell

monolayers when they reached an appropriate confluence. After treatment with different concentrations of EAESI, the migration of each cell

Fig. 2. Identification of chemical components of EAESI by ultra-high performance liquid chromatography tandem mass spectrometry. Total ion chromatography in

positive (A) and negative (B) ion modes for EAESI samples are shown.

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Fig. 3. EAESI inhibited the growth of both AR+ and AR- PCa cells. (A) Cellular changes were observed under a light microscope at 100× magnification after

treatment with EAESI at different concentrations for 24 h. (B) Cell viability was determined by a CCK-8 assay after treating PCa cells with EAESI at various concentrations for 24 h. (C–D) An EdU assay was employed to evaluate the effect of different concentrations of EAESI on the proliferative activity of LNCaP (C) and PC3

(D) cells. (E) Statistical analysis of the percentage of EdU-positive LNCaP and PC-3 cells. (F) LNCaP and PC-3 cells treated with the indicated concentrations of EAESI

were subjected to flow cytometric and quantitative analyses to determine the percentages of cells in various phases of the cell cycle. The data are presented as the

means ± standard deviations (SDs). *P < 0.05, **P < 0.01, ***P < 0.001 compared with the 0 mg/mL group.

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line was significantly inhibited only at a specific concentration. Among

the cell lines, 22Rv1 and PC-3 cells exhibited increased sensitivity to

EAESI (Fig. 4A, Fig. S1). Furthermore, PCa cell invasion was also

inhibited after EAESI treatment (Fig. 4B). In addition, to verify the

proapoptotic role of EAESI in PCa cells, flow cytometry was utilized to

detect the proapoptotic effect of EAESI on PCa cells. As shown in Fig. 4C,

EAESI promoted PCa cell apoptosis in a concentration-dependent

manner. Similarly, PC-3 cells were more sensitive to EAESI than were

LNCaP cells (Fig. 4C). Mechanistically, EAESI regulated the expression

of the apoptotic proteins BAX and BCL2 (Figs. S2A–B).

3.4. EAESI suppresses the growth of xenograft tumors in vivo

According to the above results, EAESI had a significant inhibitory

effect on the growth of PCa cells in vitro. To facilitate clinical translation

and application, the antitumor effect of EAESI was assessed in animals. A

xenograft tumor model was established by subcutaneously injecting PCa

cells into male nude mice. When the xenograft tumors reached to a

specific size, the tumor size was recorded, and drug treatment was

administered. Fig. 5A and B shows the xenograft tumors in the nude

mice and after harvesting from the mice after EAESI was orally administered for 21 days. The tumors in the high-concentration group were

noticeably smaller than those in the other groups. In contrast, the

weights of the mice in each group after oral administration of EAESI

were not significantly different (Fig. 5C). Moreover, hematoxylin and

eosin (H&E) staining showed that EAESI caused no significant changes

in the liver or kidney tissues of the mice, indicating that EAESI has no

apparent toxicity (Fig. S3). However, the tumor weight significantly

decreased after high-concentration EAESI treatment (Fig. 5D). Moreover, the tumors grew significantly more slowly in the highconcentration group than in the low-concentration group during

EAESI treatment (Fig. 5E). To verify the molecular mechanism of growth

inhibition, proliferation markers and apoptosis were examined. The

percentage of Ki-67-positive cells in tumor tissues decreased significantly with increasing EAESI concentration (Fig. 5F–G), while the percentage of TUNEL-positive cells in tumor increased with increasing

concentration (Fig. 5H–I). In the IHC results, BAX protein expression

was upregulated after EAESI treatment, while BCL2 protein expression

was downregulated (Fig. S2C). The aforementioned findings suggested

that EAESI is capable of suppressing the growth of PCa tumors in vivo,

consistent with its inhibitory effects on PCa cells.

3.5. Network pharmacology analysis reveals AR as the target of EAESI in

PCa

These findings indicate that EAESI has a good inhibitory effect on

PCa. As TCMs are characterized by multiple targets, a network pharmacology approach was utilized to investigate the critical targets of

EAESI in PCa. However, EAESI is the ethyl acetate extracts of Semen

Impatientis, and no related data are available in the TCMSP database. In

our previous study, EAESI was demonstrated to be the most effective

extract of Semen Impatientis against PCa cells (Wang et al., 2017).

Fig. 4. EAESI suppressed migration and invasion and promoted apoptosis in both AR+ and AR- PCa cells in a concentration-dependent manner. (A) The migration

capacity of LNCaP and PC-3 cells treated with the indicated concentrations of EAESI (0, 0.04, 0.10, and 0.20 mg/mL) was evaluated by wound healing assays and

compared across the concentrations. (B) Transwell invasion assays detecting the changes in invasion ability of LNCaP and PC-3 cells after treatment with different

concentrations of EAESI. (C) The promotion of PCa cell apoptosis by treatment with various concentrations of EAESI was examined by flow cytometry, and the

apoptosis rates were quantified and compared across the concentrations. The data are presented as the means ± SDs. *P < 0.05, **P < 0.01, ***P < 0.001 compared

with the 0 mg/mL group.

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Fig. 5. Different concentrations of EAESI inhibited the growth of xenograft tumors. (A–B) The sizes of xenograft tumors treated with different concentrations of

EAESI in vivo in male nude mice (A) and ex vivo (B). (C–D) The weights of the animals (C) and xenograft tumors (D) were measured on the 21st day after cell

implantation and compared across the tested concentrations. (E) The growth curves of xenograft tumors in mice treated with different concentrations of EAESI are

displayed. (F) The proliferative activity of xenograft tumors in mice treated with different concentrations of EAESI was evaluated by immunohistochemical staining

for Ki-67. (G) The percentage of Ki-67-positive cells determined by immunohistochemistry was compared across the tested drug concentrations. (H–I) Apoptosis in

xenograft tumors was detected by a TUNEL assay (H), and the positive rates were used for comparative quantitative analysis (I). The data are presented as the means

± SDs. *P < 0.05, **P < 0.01, ***P < 0.001 compared with the 0 mg/mL group.

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Therefore, Semen Impatientis, as recorded in the TCMSP database, was

used to represent EAESI to investigate its targets. According to the

TCMSP database, there are a total of 47 ingredients in Semen Impatientis. According to the screening conditions of OB ≥ 30% and DL ≥

0.18, 9 bioactive ingredients were identified. After the removal of

duplicate targets, 167 drug-related targets were retrieved. Information

on the bioactive compounds of Semen Impatientis, including the molecule ID, molecule name, OB, DL, and corresponding target number, is

listed in Table 1.

To identify disease-related targets for PCa, we searched and integrated data from multiple databases, such as DrugBank, GeneCards,

OMIM, and the TTD. As a result of this analysis, a total of 10,064 targets

were identified after deduplication and merging (Fig. 6A). Subsequently,

the drug-related targets and disease-related targets were intersected,

and 157 common targets were identified and considered potential targets of Semen Impatientis in PCa (Fig. 6B). Afterward, Cytoscape software was used to construct a compound–target network to show the

links between the bioactive compounds of Semen Impatientis and the

overlapping targets. The network diagram showed that the compound

quercetin had the most targets in PCa and that PTGS1 and PTGS2 were

the targets associated with more bioactive compounds (Fig. 6C). In

addition, the common targets were imported into the STRING database

to explore protein–protein interactions. A PPI network with a confidence

score of >0.9 was then constructed, as shown in Fig. 6D. Furthermore,

network topology analysis was performed for the aforementioned PPIs.

According to the median BC/CC/DC/EC/LAC/NC scores calculated with

the cytoNCA plug-in of Cytoscape, hub targets were identified as the

most likely potential targets through which Semen Impatientis acts on

PCa, as shown in Fig. 6E. Hence, it could also be inferred that EAESI may

inhibit prostate cancer through these hub targets, which included AR,

AKT1, MAPK1, TP53, and CCND1. Among these hub targets, AR is one of

the major drivers of PCa development, and the main treatment strategies

for PCa are closely related to AR. Therefore, it is essential to explore

whether EAESI can affect PCa by modulating AR. The RT‒qPCR and WB

results showed a significant reduction in AR expression after EAESI

treatment. TMPRSS2 and PSA, the transcriptional targets of AR, also

showed significant reductions in mRNA and protein expression levels

after drug intervention (Fig. 6F–G). The above findings indicated that

EAESI inhibited not only the expression of AR but also the transcriptional activity of AR. Furthermore, the results of cellular thermal shift

assay (CETSA) indicated that EAESI could increase the thermal stabilization of AR (Fig. S8), which suggested that AR is the direct target of

EAESI.

3.6. Transcriptomic analysis indicated that EAESI may inhibit PCa

through ATF3

Since AR is not expressed in some prostate cancer cells and since

EAESI can inhibit the malignant behavior of these cells, it was necessary

to explore the non-AR-related molecular mechanisms of EAESI. RNA

sequencing was thus used to detect alterations in mRNA expression in

EAESI-treated PC-3 cells lacking AR expression. The differential changes

after EAESI treatment were visualized in a heatmap (Fig. 7A). The three

upregulated and three downregulated genes with the greatest changes in

mRNA expression, as shown in the volcano plot, were ATF3, ATP6V0D2,

and GDF15 and DCSTAMP, G6PC, and PCDHA7, respectively (Fig. 7B).

Subsequently, GO and KEGG enrichment analyses of the differentially

expressed genes were performed. Fig. 7C shows the results of the GO

enrichment analysis. This analysis demonstrated that EAESI-related

genes are associated with DNA replication, focal adhesion, transcription coregulator activity, DNA-binding transcription factor binding, etc.

KEGG enrichment analysis revealed that EAESI-related genes are associated with focal adhesion, cellular senescence, the cell cycle, DNA

replication, etc. (Fig. 7D). The results of GO and KEGG enrichment analyses might explain why EAESI can suppress PCa.

Among the top differentially expressed genes, ATF3 had the greatest

change in expression and is thus the most likely target of EAESI in PCa.

To verify the role of ATF3 in PCa, ATF3 was searched in the TIMER

database to explore the associations between its expression and multiple

cancers. As shown in Fig. S5A, ATF3 was significantly downregulated in

most cancer tissues, including PCa tissues, compared to the corresponding adjacent normal tissues. Moreover, ATF3 expression was

correlated with T and N stage in PCa and decreased with increasing T

and N stage (Figs. S5B–C). Higher ATF3 expression was associated with a

longer progression-free interval (PFI), indicating a better prognosis

(Fig. S5D). Considering the combined results of the above analyses,

ATF3 is expected to be a target of EAESI in PCa. Therefore, we investigated whether EAESI can affect the expression of ATF3 in PCa. As a

result, regardless of AR expression status in PCa, the level of ATF3

mRNA expression in PCa cells was significantly increased with

increasing drug concentration (Fig. 7E). The same pattern was observed

for the protein expression level (Fig. 7F). IHC experiments on xenograft

tumors in nude mice further confirmed that EAESI increased ATF3

expression (Fig. S6). Moreover, CETSA experiments revealed that ATF3

is a direct target of EAESI (Fig. S8).

3.7. ATF3 reverses the inhibitory effect of EAESI on PCa

To investigate the role of ATF3 in the inhibitory effect of EAESI on

PCa, three siRNAs were designed based on the ATF3 gene sequence to

silence ATF3 expression. The silencing efficiency was determined by WB

analysis and is presented in Fig. 8A. Si-1 and si-3, which target ATF3,

significantly reduced ATF3 expression. Therefore, si-1 was chosen for

subsequent experiments and is hereafter referred to as siATF3. As shown

in Fig. 8B–D, siATF3 not only increased the viability of PCa cells but also

reversed the inhibitory effect of EAESI on cell viability. Moreover,

decreased ATF3 expression increased the ability of PCa cells to migrate

and attenuated the inhibition of cell migration induced by EAESI

(Fig. 8E–F). In terms of apoptosis, decreased ATF3 expression significantly inhibited the promotion of apoptosis induced by EAESI, although

it did not significantly suppress apoptosis (Fig. 8G). Taken together,

these findings indicated that decreased ATF3 expression diminished the

effects of EAESI on PCa. In other words, EAESI exerts its antitumor effects by upregulating ATF3 expression.

3.8. EAESI promotes the nuclear expression of ATF3 and its interaction

with AR to decrease the transcriptional activity of AR

As related literature indicates that ATF3 can interact with AR and

prevent AR from binding to androgen response elements (Wang et al.,

2012), to confirm the associations between ATF3 and AR in our

research, we first explored the effect of EAESI on the distribution of

ATF3 in PCa cells. As shown in Fig. 9A, the expression of ATF3 significantly increased after EAESI treatment, and ATF3 was mainly distributed in the nucleus. A nuclear–cytoplasmic separation assay further

Table 1

The bioactive compounds of Semen Impatientis and related information.

MollD MolName OB DL Target

numbers

MOL000358 beta-sitosterol 36.91 0.75 28

MOL000422 kaempferol 41.88 0.24 55

MOL000449 Stigmasterol 43.83 0.76 27

MOL008597 balsaminone B 37.07 0.62 0

MOL008598 cis-5,8,11,14,17-

Eicosapentaenoic acid methyl

ester

47.13 0.24 2

MOL008599 Ethyl oleate 32.4 0.19 1

MOL008600 glycerol-1-(9-octadecenoate) 34.13 0.3 0

MOL008601 Methyl arachidonate 46.9 0.23 2

MOL000098 quercetin 46.43 0.28 138

Abbreviations: MolID, molecule ID; MolName, molecular name; OB, oral

bioavailability; DL, drug-likeness.

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Fig. 6. Network pharmacology analysis and experiments were utilized to explore the molecular mechanism of EAESI in PCa. (A) Disease-related targets for PCa were

selected from DrugBank, GeneCards, OMIM, and the TTD. (B) Venn diagram showing the intersection of the drug targets and the disease-related targets. (C) A

compound–target network was constructed. (D) The common targets of Semen Impatientis and PCa were used to construct the PPI network. (E) Topological analysis

of the PPI network was employed to identify the hub genes. (F–G) The impacts of EAESI on the expression and transcriptional activity of AR in LNCaP and 22RV1 cells

were evaluated by RT‒qPCR (F) and Western blot (G) assays. The data are presented as the means ± SDs. *P < 0.05, **P < 0.01, ***P < 0.001 compared with the 0

mg/mL group.

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Fig. 7. Identification and validation of ATF3 as a target of EAESI based on RNA sequencing analysis of EAESI-treated PC-3 cells. (A) Heatmap showing the top 30

significantly upregulated and downregulated DEGs. (B) Volcano plot showing the DEGs; the top 3 upregulated and downregulated DEGs are marked. (C) The DEGs

were subjected to GO enrichment analysis. (D) The bubble chart presents the results of KEGG enrichment analysis of the DEGs. (E–F) The expression of ATF3 induced

by various concentrations of EAESI in LNCaP, 22Rv1, PC-3, and DU145 cells was measured by western blotting (E) and real-time quantitative PCR (F). The data are

presented as the means ± SDs. *P < 0.05, **P < 0.01, ***P < 0.001 compared with the 0 mg/mL group.

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supported this finding (Fig. 9B), as it revealed that EAESI induced an

increase in ATF3 expression in both the cytoplasm and nucleus, with a

more pronounced increase in the nucleus. Subsequently, a co-IP assay

was conducted to verify the interactions between ATF3 and AR. The

protein complexes immunoprecipitated by either the anti-ATF3 or

anti-AR antibody contained both the ATF3 and AR proteins. Moreover,

the increased expression of ATF3 induced by EAESI bound to more AR

proteins (Fig. 9C). Therefore, ATF3 interacts with AR. Considering that

EAESI decreases the transcriptional activity of AR and that ATF3 can

prevent AR from binding to androgen response elements, whether the

upregulation of ATF3 is involved in the repressive effect of EAESI on AR

transcriptional activity remains to be investigated. The mRNA and

protein expression levels of AR and its target gene PSA following

treatment with siATF3 or EAESI were subsequently measured. As indicated in Fig. 9D–E, siATF3 did not significantly change the expression

levels of AR or its target gene, while it significantly reversed the

inhibitory effect of EAESI on AR transcriptional activity. Therefore, it

could be deduced that EAESI decreases the transcriptional activity of AR

through ATF3. In summary, EAESI promotes the expression of ATF3 in

the nucleus, which promotes its binding to AR and decreases the transcriptional activity of AR.

4. Discussion

Prostate cancer is the most common malignancy in males worldwide,

second only to lung cancer, and is the fifth most common cause of

cancer-related death in men worldwide; thus, it affects the health of

millions of men (Sung et al., 2021). The main treatment options for PCa

patients include active surveillance, radical prostatectomy, radiotherapy, ADT, chemotherapy, immunotherapy, or a combination of

these options. The selection of treatment regimen depends on numerous

factors, such as histologic grade, molecular characteristics, clinical

tumor stage, metastasis status, and patient characteristics (Rebello et al.,

2021; Sandhu et al., 2021). Moreover, the currently recommended

Fig. 8. ATF3 reversed the inhibitory effects of EAESI on cell viability and migration and the proapoptotic effects of EAESI on PCa cells. (A) Three siRNAs were

designed to silence ATF3 expression, and the silencing efficiency was evaluated by Western blot analysis. (B–D) A CCK-8 assay was used to determine the effect of

silencing ATF3 expression alone or in combination with EAESI on the viability of 22RV1 (B), PC-3 (C), and DU145 (D) cells. (E–F) A wound healing assay was used to

assess the effect of silencing ATF3 expression alone or in combination with EAESI on the migration of 22Rv1 (E) and PC-3 (F) cells. (G) Flow cytometry was utilized to

examine the effect of silencing ATF3 expression alone or in combination with EAESI treatment on apoptosis. The data are presented as the means ± SDs. *P < 0.05,

**P < 0.01, ***P < 0.001 compared with the siNC group unless otherwise specified. M represents the EAESI.

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Journal of Ethnopharmacology 330 (2024) 118228

13

treatment options for PCa patients can cause specific adverse effects. For

example, long-term treatment with ADT leads to loss of bone density and

muscle mass, and docetaxel treatment can cause sensory polyneuropathy and edema (Rebello et al., 2021). Despite these treatments,

the disease still progresses, and many patients succumb to the disease

(Teo et al., 2019). In recent decades, because of their effective antitumor

activity, fewer number of side effects, and beneficial effects on cancer

patients, TCMs have become a mainstream modality of complementary

and alternative treatment for cancer (Chen et al., 2008, 2015).

Regarding the mechanisms underlying their benefits, TCMs can modulate cancer stem cells, the tumor microenvironment, and the expression

of oncogenes and tumor suppressor genes to combat cancer (Xiang et al.,

2019). In addition, it has been confirmed that the addition of TCMs to

radiotherapy, chemotherapy, or immunotherapy regimens can increase

the efficacy of these treatments while reducing their side effects (Liu

et al., 2018; Lu et al., 2016; Nik Nabil et al., 2018). Moreover, TCMs can

regulate the immune microenvironment and immune function in the

body. For example, Xuanfei Baidu Decoction can downregulate the

expression of proinflammatory factors and immune cell infiltration in

mice (Wang et al., 2022). Acteoside, which is derived from Rehmannia

glutinosa, can regulate the expression of inflammatory factors and the

proliferation of splenic lymphocytes in vivo (Gao et al., 2023). Therefore, the development of TCM holds promise for improving PCa therapy

and clinical outcomes for PCa patients.

Fig. 9. EAESI promoted ATF3 entry into the nucleus to inhibit the transcriptional activity of AR. (A) Immunofluorescence staining showing the effect of EAESI at

different concentrations (0, 0.1, and 0.2 mg/mL) on the distribution of ATF3 in PCa cells. (B) Nuclear–cytoplasmic fractionation assays revealed the effect of 0.1 mg/

mL EAESI on the distribution of ATF3. (C) Coimmunoprecipitation assays indicated that ATF3 interacts with AR. (D) LNCaP and 22Rv1 cells were treated with

siATF3, EAESI, or both, and the protein expression of AR and its downstream target was assessed to determine the effect of ATF3 on the transcriptional activity of AR.

M represents EAESI.

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14

Semen Impatientis, the dried ripe seed of Impatiens balsamina L., is

documented in the Chinese Pharmacopoeia as a TCM for medicinal

purposes. Domestic and international research on Semen Impatientis has

focused mostly on its extracts. Modern pharmacological studies have

reported that extracts of Semen Impatientis have antioxidant, antiinflammatory, analgesic, and antimicrobial effects; promote transdermal absorption; stimulate uterine smooth muscle; and improve

hemorheological properties (Linglei Kong, 2018). In addition to the

above effects, the extracts of Semen Impatientis also showed good

antitumor activity. For instance, balsaminone A and balsaminone B,

both of which were extracted from Semen Impatientis, were reported to

exert significant inhibitory effects on the growth of A549 human lung

cancer cells, revealing that the underlying mechanism of these inhibitory effects may be the induction of cell cycle arrest (Hui Pei, 2011).

Similarly, quercetin in Semen Impatientis inhibits the proliferation of

human breast cancer cells by decreasing signal transduction activity

(Singhal et al., 1995).Similarly, in our previous research, multiple extracts of Semen Impatientis all showed antiproliferative activity against

human PCa cells, among which the ethyl acetate extracts—namely,

EAESI—exhibited the strongest inhibitory effect (Wang et al., 2017). To

expand upon previous research, as LNCaP and PC-3 cell lines are more

commonly used in PCa-related research and are more sensitive to EAESI,

we primarily selected LNCaP and PC-3 cell lines from the previous ones

to represent AR+ and AR− PCa cells, respectively, in this study. In the

present study, we further confirmed the cytotoxicity of EAESI in PCa

cells. EAESI affected the cellular state, viability, and proliferation of PCa

cells with or without AR expression in a concentration-dependent

manner. The inhibition of cell proliferation was caused by

EAESI-induced G0/G1-phase arrest. Moreover, EAESI induced apoptosis

and suppressed the migration of PCa cells in a concentration-dependent

manner. Taken together, extensive research indicates that the extracts of

Semen Impatientis have antitumor properties. However, little is known

about its antitumor effect in vivo. Thus, we developed a xenograft tumor

model in male nude mice and investigated the antitumor effect of EAESI

in vivo. The results showed that EAESI slowed PCa growth in vivo by

suppressing cell proliferation and inducing apoptosis during the 21-day

drug treatment. Additionally, it did not affect the body weight of the

animals and did not cause significant toxicity to the liver or kidneys,

which was consistent with the low toxicity of Semen Impatientis

recorded in the Chinese Pharmacopoeia (Linglei Kong, 2018).

Considering the good antitumor properties and low toxicity of EAESI,

the mechanism of its antitumor activity is significant to be investigated.

Since network pharmacology approach resonates well with the multicomponent and multitarget characteristics of TCMs and has become the

mainstream method for exploring the mechanisms of TCMs from a

global perspective (Zhang et al., 2017), we utilized network pharmacology to reveal the antitumor mechanisms of EAESI in this study.

However, Semen Impatientis, not EAESI, is recorded in the public

TCMSP database commonly used in network pharmacology analysis. As

EAESI has been demonstrated to be the most effective extract of Semen

Impatientis (Wang et al., 2017), the relevant information about Semen

Impatientis could represent the data for EAESI. Nine bioactive ingredients and 167 drug-related targets were then identified from the

TCMSP database. Among the bioactive ingredients, most have been reported to possess antitumor properties (Imran et al., 2019; Manosroi

et al., 2012; Vo et al., 2020; Zhang et al., 2022), indicating the reliability

of the data in the TCMSP database. Subsequently, 157 potential targets

of EAESI in PCa were identified after intersecting drug-related and

disease-related targets from DrugBank, GeneCards, OMIM, and the TTD.

Following the construction of the PPI network and topology analysis, 14

hub targets were identified: AR, AKT1, TP53, MAPK1, PPARA, CCND1,

MYC, JUN, FOS, EGFR, VEGFA, IL6, RELA, and TNF. Consistently, our

previous research demonstrated that EAESI significantly decreased the

levels of phospho-ERK and phospho-AKT, although it had no impact on

the levels of total ERK and AKT (Wang et al., 2017). Among the hub

targets, AR is the driver of PCa tumorigenesis and progression, and

targeting the AR signaling pathway is a widely used and effective

therapeutic strategy in clinical practice (Nevedomskaya et al., 2018).

Therefore, it is significant to explore whether EAESI is effective in

suppressing the AR signaling pathway. As demonstrated in this study,

EAESI not only decreased AR expression but also decreased the transcriptional activity of AR, suggesting that EAESI could be an effective

agent for PCa treatment.

Because network pharmacology analysis identified the targets of

Semen Impatientis rather than EAESI in PCa cells from bioinformatic

data, transcriptomic analysis was employed to further explore the specific mechanism of action of EAESI. In addition, since EAESI significantly inhibited the growth and migration of PCa cells with or without

AR expression, to reveal the universal inhibitory mechanism of EAESI,

we performed RNA sequencing on EAESI-treated PC-3 cells lacking AR

expression. The results of enrichment analyses of the differentially

expressed genes revealed that EAESI treatment could cause changes in

the following processes in PCa cells: DNA replication, the cell cycle,

focal adhesion, cellular senescence, transcriptional coregulator activity,

and DNA-binding transcription factor binding. From another perspective, these findings suggested that EAESI inhibits the growth and

migration of PCa cells. Among the differentially expressed genes, the

ATF3 gene showed the greatest fold change in expression, indicating

that ATF3 might be the critical target for the antitumor activity of EAESI.

ATF3, a member of the ATF/cAMP response element-binding (CREB)

family, acts as a transcription factor that binds to the promoters of its

target genes to regulate their expression (Lu et al., 2006). In addition, it

can interact with other proteins to modify cellular processes independent of its transcriptional activity (Wu et al., 2010). ATF3 has been

demonstrated to produce stimulatory or inhibitory effects by cooperating with other proteins to form homodimers or heterodimers, which rely

on the status of the cell and the promoter (Chen et al., 1994; Hai and

Curran, 1991). Extensive studies indicate that ATF3 plays a significant

role in oncogenesis and has dual effects. ATF3 acts as either a tumor

suppressor or an oncogene to affect the biological behavior of cancer

cells (Chen et al., 2022). In PCa, it was reported that decreasing ATF3

expression could activate AKT signaling and promote MMP9 expression

in vivo and in vitro, thereby promoting the proliferation and increasing

the invasiveness of PCa cells (Wang et al., 2015). Additionally, ATF3 can

induce apoptosis in PCa cells (Huang et al., 2008). On the other hand,

ATF3 was also reported to induce the proliferation and stimulate the

metastasis of PCa cells (Bandyopadhyay et al., 2006; Pelzer et al., 2006).

The dual role of ATF3 in PCa might be due to the regulation of target

genes based on the type of stimulus and/or the cell type (Ku and Cheng,

2020). In our study, bioinformatic analysis of ATF3 expression in

various tumors was conducted. The results showed that most tumor

tissues exhibited low expression of ATF3 compared to adjacent normal

tissues and that lower expression of ATF3 was positively correlated with

a higher stage and a shorter PFI in PCa. Furthermore, cellular experiments indicated that reduced ATF3 expression promoted the proliferation and migration and inhibited the apoptosis of PCa cells. According to

the above results, our research suggested that ATF3 acts as a tumor

suppressor in PCa. Additionally, ATF3 was demonstrated to reverse the

antitumor effects of EAESI, indicating that ATF3 is a target through

which EAESI exerts its effect. Moreover, CETSA experiments indicated

that both ATF3 and AR are the direct targets of EAESI. Previously reported literature has demonstrated that ATF3 is associated with most of

the hub targets that were identified as targets of EAESI in PCa by

network pharmacology analysis in this study, such as CCND1, TNF, IL-6,

P53, AKT, AR, MYC, JUN, and FOS (Chen et al., 2022; Ku and Cheng,

2020). For example, ATF3 downregulates the expression of CCND1, IL-6,

TNF, and P53 and inhibits AKT and AR expression. Moreover, ATF3 has

been proven to be the target of c-myc and can interact with Jun and

c-FOS (Rohini et al., 2018). Considering the association of ATF3 with

most hub targets and the finding that it exhibited the greatest fold

change in expression among the differentially expressed genes, it can be

concluded that ATF3 is the critical target by which EAESI exerts

B. Hu et al.

Journal of Ethnopharmacology 330 (2024) 118228

15

antitumor effects in PCa.

As Wang et al. reported that ATF3 can directly interact with AR and

consequently suppress the transcriptional activity of AR (Wang et al.,

2012), we further confirmed the interaction between ATF3 and AR in

the present study and found that EAESI induced increased expression of

ATF3 in the nucleus and increased the binding of ATF3 to AR.

Furthermore, our results revealed that silencing ATF3 expression

reversed the inhibitory effect of EAESI on AR transcriptional activity,

suggesting that EAESI decreases AR transcriptional activity via ATF3. In

summary, EAESI increases the expression of ATF3 in the nucleus and

promotes its binding with AR, thereby decreasing the transcriptional

activity of AR. Surprisingly, silencing ATF3 expression did not significantly alter the transcriptional activity of AR in PCa. This may be

attributed to the low expression of ATF3 in PCa cells and the role of

intracellular negative feedback regulation.

In our study, ATF3 and AR were identified as targets of EAESI, and

EAESI was found to decrease the viability of both AR+ and AR− PCa cells

by regulating the expression of ATF3 or AR. Surprisingly, there was no

significant correlation between the IC50 values of EAESI and the AR

expression level across PCa cells. One possible explanation is that

different PCa cells have different gene expression responsiveness after

drug treatment, as evidenced by the varying ATF3 expression levels in

different PCa cells following EAESI treatment. Another potential reason

is that different PCa cells have different gene expression profiles, and the

expression levels of identical genes vary among different PCa cells. As a

TCM, EAESI exhibits multitarget effects, and its inhibitory effects on

different PCa cells depend on multiple targets. This may explain why the

data cannot be solely attributed to the ATF3 and AR targets.

In the present study, we investigated the antitumor effects of EAESI

on PCa in vitro and in vivo and explored the underlying mechanism by

integrating network pharmacology and transcriptomic data. To our

knowledge, this is the first study to explore the antitumor effect of EAESI

in vivo and provide a reference for the oral dosage of EAESI for PCa

treatment. Moreover, the antitumor mechanism of EAESI was explored

from a systemic perspective, and it was revealed for the first time that

ATF3 is the critical target of EAESI in PCa, which provides an experimental basis for the application of EAESI in the treatment of PCa and for

the development of a novel targeted therapy. Admittedly, our research

has several limitations. For example, the main antitumor bioactive

compounds were not further isolated and purified from EAESI. In

addition, no systemic drug toxicity studies were conducted in mice. The

pharmacological properties of EAESI were not compared with those of

first-line drugs for PCa treatment, and the advantages and disadvantages

of EAESI have not been fully elucidated. Since high concentrations of

EAESI can induce many cells to undergo apoptosis, using the same drug

concentration for both migration and apoptosis assays cannot determine

whether EAESI inhibits cell migration by blocking live cells or by

inducing apoptotic cell death. Additionally, no interactions between

ATF3 and other hub targets, except for AR, were explored in investigating the anti-PCa mechanisms of EAESI.

5. Conclusions

In this study, EAESI was verified to have antitumor effects on PCa

both in vitro and in vivo, and ATF3 was demonstrated by transcriptomic

analysis and experiments to be the critical target through which EAESI

exerts its antitumor effects on AR+ and AR− PCa cells. In addition, EAESI

was found to downregulate AR expression and decrease the transcriptional activity of AR via ATF3 in PCa, suggesting that EAESI is an

effective drug for the treatment of PCa.

Funding

This work was supported by the Natural Science Foundation of Hubei

Province granted to Ruibao Chen (Grant number 2017CFB714) and the

Medical Youth Top Talent Program of Hubei Province granted to Tao

Wang (Grant number yxljrcpp021).

CRediT authorship contribution statement

Bintao Hu: Conceptualization, Formal analysis, Investigation,

Methodology, Writing – original draft. Chengwei Wang: Data curation,

Formal analysis, Methodology, Software. Yue Wu: Data curation, Validation, Visualization. Chenglin Han: Validation, Visualization. Jihong

Liu: Project administration, Supervision. Ruibao Chen: Conceptualization, Funding acquisition, Resources, Supervision, Writing – review &

editing. Tao Wang: Conceptualization, Funding acquisition, Project

administration, Resources, Supervision, Writing – review & editing.

Declaration of competing interest

The authors declare that they have no known competing financial

interests or personal relationships that could have appeared to influence

the work reported in this paper.

Data availability

Data will be made available on request.

Acknowledgments

The authors acknowledge the staff of the animal facility for feeding

the nude mice in this study, and acknowledge the AJE team for polishing

this manuscript.

Abbreviations

ADT androgen deprivation therapy

AR androgen receptor

ATF3 activating transcription factor 3

CETSA cellular thermal shift assay

CO-IP coimmunoprecipitation

DEGs differentially expressed genes

DL drug-likeness

EAESI ethyl acetate extracts of Semen Impatientis

FBS fetal bovine serum

H&E hematoxylin and eosin

IHC immunohistochemistry

OB oral bioavailability

OMIM Online Mendelian Inheritance in Man

PBS phosphate buffered saline

PCa prostate cancer

PFI progression-free interval

PPI protein-protein interaction

RT room temperature

SD standard deviation

TCM traditional Chinese medicine

TCMSP Traditional Chinese Medicine Systems Pharmacology

TTD Therapeutic Target Database

UHPLC-MS/MS ultra-high-performance liquid chromatography

tandem mass spectrometry

WB western blot

Appendix A. Supplementary data

Supplementary data to this article can be found online at https://doi.

org/10.1016/j.jep.2024.118228.

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