Abstract
This study aimed to investigate the underlying mechanisms by which
dandelion extract inhibits the proliferation of breast cancer
MDA-MB-231 cells. Dandelion root and leaf extracts were prepared using
a heat reflux method and subjected to solvent gradient extraction to
obtain fractions with different polarities. MTT assays revealed that
the ethyl acetate fraction exhibited the strongest inhibitory effect on
cell proliferation. LC-MS analysis identified 12 potential active
compounds, including sesquiterpenes such as Isoalantolactone and
Artemisinin, which showed significantly lower toxicity toward normal
mammary epithelial MCF-10A cells compared to tumor cells (p < 0.01).
Mechanistic studies demonstrated that the extract induced apoptosis in
a dose-dependent manner, with an apoptosis rate as high as 85.04%, and
significantly arrested the cell cycle at the S and G2/M phases.
Label-free quantitative proteomics identified 137 differentially
expressed proteins (|FC| > 2, p < 0.05). GO enrichment analysis
indicated that these proteins were mainly involved in cell cycle
regulation and apoptosis. KEGG pathway analysis revealed that the
antitumor effects were primarily mediated through the regulation of
PI3K-Akt (hsa04151), JAK-STAT (hsa04630), and PPAR (hsa03320) signaling
pathways. Moreover, differential proteins such as PI3K, AKT1S1, SIRT6,
JAK1, SCD, STAT3, CASP8, STAT2, STAT6, and PAK1 showed strong
correlation with the core components of the EA-2 fraction of dandelion.
Molecular docking results demonstrated that these active compounds
exhibited strong binding affinities with key target proteins such as
PI3K and JAK1 (binding energy < −5.0 kcal/mol). This study elucidates
the multi-target, multi-pathway synergistic mechanisms by which
dandelion extract inhibits breast cancer, providing a theoretical basis
for the development of novel antitumor agents.
1. Introduction
Breast cancer is one of the most common cancers among women worldwide,
with its incidence steadily increasing since the 20th century. In 2020,
there were more than 2.2 million new breast cancer cases globally,
accounting for 11.7% of all cancer cases in women [[38]1]. China has
become one of the countries with the fastest-growing incidence of
breast cancer, with approximately 400,000 new cases reported annually
[[39]2,[40]3]. Currently, the main treatments for breast cancer include
surgery, radiotherapy, chemotherapy, and targeted endocrine/molecular
therapy [[41]4]. Although these approaches can significantly reduce
tumor burden, their side effects—such as immunosuppression, hair loss,
and nausea—often impact patients’ quality of life. Moreover, resistance
and toxicity have emerged as major obstacles to chemotherapy [[42]5].
Triple-negative breast cancer (TNBC) is a highly aggressive subtype of
breast cancer that lacks expression of estrogen receptor (ER),
progesterone receptor (PR), and human epidermal growth factor receptor
2 (HER2), and is thus associated with higher invasiveness, metastasis,
and poor prognosis [[43]6]. Therefore, identifying new therapeutic
strategies is particularly crucial for TNBC patients. Numerous studies
have shown that bioactive compounds extracted from various traditional
medicinal plants have attracted widespread attention as important
sources of anticancer drugs [[44]7].
Many natural compounds play important roles in cancer treatment by
inhibiting cancer cell proliferation and inducing apoptosis. For
instance, phytochemicals such as resveratrol and quercetin suppress
cancer cell proliferation and promote apoptosis by regulating cell
cycle and apoptosis-related pathways [[45]8]. Cell proliferation is
governed by multiple signaling pathways, particularly those involving
cell cycle regulatory proteins, cyclin-dependent kinases (CDKs), and
inhibitory factors such as p21 and p27 [[46]9]. On the other hand,
apoptosis, as a type I programmed cell death (PCD), is also modulated
by cell cycle-associated proteins. Numerous studies have demonstrated
that certain compounds can inhibit cancer cell proliferation by
blocking cyclins and their associated kinases, while also enhancing
apoptosis by regulating apoptosis-related proteins such as p53, the
Bcl-2 family, and caspases [[47]10,[48]11,[49]12]. Therefore, natural
phytochemicals can simultaneously suppress tumor cell proliferation and
accelerate cancer cell death through apoptosis, showcasing their
tremendous potential as promising anticancer agents.
Dandelion (Taraxacum officinale) has a sweet-bitter taste and a cold
nature, and it enters the liver and stomach meridians. It is rich in
sterols, flavonoids, phenolic acids, and volatile oils. It exhibits
significant antioxidant, anti-inflammatory, antibacterial, and
antitumor activities [[50]13]. However, current research on the use of
dandelion in the treatment of female breast hyperplasia and breast
cancer is limited. Most studies have focused on crude extracts, and the
specific active components responsible for the therapeutic effects
remain unclear. Moreover, issues such as low concentrations of
effective constituents, poor efficacy, and unclear mechanisms of action
still exist. Therefore, this study focuses on screening the active
components in dandelion leaves and roots using breast cancer cells as
the research model, aiming to identify clearly defined anti-breast
cancer compounds and preliminarily explore their mechanisms of action.
This work is intended to provide a theoretical basis for the clinical
treatment of breast cancer and lay the foundation for the development
and application of related natural medicines in the future.
2. Materials and Methods
2.1. Plant Materials
Dandelion was purchased from the Hanzhong Chinese Herbal Medicine
Market in Shaanxi Province.
2.2. Chemicals and Reagents
MDA-MB-231 and MCF-10A cell lines (Sangon Biotech Co., Ltd., Shanghai,
China); fetal bovine serum (FBS, Cat# 11011–8611, Zhejiang Tianhang
Biotechnology Co., Ltd., Hangzhou, China); trypsin cell dissociation
solution (Cat# 25200–056,Thermo Fisher Scientific China Co., Ltd.,
Shanghai, China); penicillin-streptomycin solution 100× (Cat# C0222,
Beyotime Biotechnology Co., Ltd., Shanghai, China); MTT, 96-well
culture plates, T25 cell culture flasks, and cryogenic vials (Sangon
Biotech Co., Ltd., Shanghai, China); Hoechst 33342 dye (Solarbio Life
Sciences, Beijing, China); absolute ethanol and ethyl acetate
(analytical grade, Tianjin Fuyu Fine Chemical Co., Ltd., Tianjin,
China); complete growth medium for MCF-10A human mammary epithelial
cells (Cat# M171500, Thermo Fisher Scientific Co., Ltd., Shanghai,
China); Annexin V-FITC apoptosis detection kit (Beyotime Biotechnology
Co., Ltd., Shanghai, China). All solvents used for chemical analysis
were of analytical grade.
2.3. Preparation of Crude Extracts from Dandelion Roots and Leaves
A total of 30 g each of dandelion root and leaves were pulverized and
passed through a No. 2 sieve. The powdered materials were separately
extracted twice by heat reflux using either water or anhydrous ethanol,
each lasting 2 h. The extracts were filtered, and the filtrates were
combined. After concentration under reduced pressure, aqueous and
ethanolic extracts of dandelion roots and leaves were obtained in the
form of thick extracts.
2.4. Isolation of Ethanol Extract from Dandelion Root
The ethanol extract of dandelion root was concentrated by rotary
evaporation to obtain a crude extract. The extract was dispersed and
dissolved in an appropriate amount of water, followed by extraction
with ethyl acetate five times until the supernatant showed no
significant turbidity, yielding an ethyl acetate fraction and an
aqueous fraction. Both fractions were filtered, and the solvents were
removed to obtain the ethyl acetate extract and aqueous extract,
respectively. Subsequently, the components were analyzed using the AKTA
pure 25 system with Sephadex G-10 as the stationary phase.
2.5. LC-MS Analysis
The dandelion extracts were subjected to non-targeted analysis using
LC-MS, and data processing was performed with Compound Discoverer™ 3.0
software, providing information such as predicted chemical names,
chemical formulas, molecular weights, retention times, maximum
chromatographic peak areas, and mzVault best match scores.
Chromatographic separation was performed using a Waters
ultra-performance liquid chromatography (UPLC) system (AcQuity UPLC,
Waters Corporation, Milford, MA, USA). Based on the chemical properties
of the compounds, a Waters HSS T3 column (100 mm × 2.1 mm, 1.8 μm) was
used. The injection volume was 2 μL, the column temperature was
maintained at 40 °C, and the flow rate was set at 0.3 mL/min. The
mobile phase consisted of solvent A (0.1% formic acid in water) and
solvent B (0.1% formic acid in acetonitrile/isopropanol). The gradient
elution program was as follows: 0–2 min, 90% A; 2–6 min, 90–40% A; 6–15
min, 40% A; 15.1–17 min, 10% A.
Mass spectrometry was detected using a Q Exactive high-resolution mass
spectrometer (Thermo Fisher Scientific, Waltham, MA, USA). Samples were
analyzed in both positive and negative ionization modes using
electrospray ionization (ESI) under selected ion monitoring (SIM) mode.
Optimized MS parameters were as follows: sheath gas flow rate, 40 arb;
auxiliary gas flow rate, 10 arb; spray voltage, +3000 V; capillary
temperature, 350 °C; and ion transfer tube temperature, 320 °C.
Q Exactive 2.9 software was used for mass spectrometer control.
Xcalibur 4.1 was used for data acquisition. Chromatographic peak
extraction, alignment, and compound identification were performed using
Compound Discoverer 3.0 software. The MS/MS fragmentation and secondary
structure analysis were conducted using MS Frontier 7.0. All software
packages were obtained from Thermo Fisher Scientific (USA).
2.6. Cell Culture of MDA-MB-231
MDA-MB-231 cells were cultured at 37 °C under a CO[2]-free atmosphere
in a medium of L-15 supplemented with 10% fetal bovine serum and 1%
penicillin-streptomycin. MCF-10A cells were cultured at 37 °C in a
humidified atmosphere containing 5% CO[2] in a complete medium
consisting of DMEM/F12 (1:1) supplemented with 5% horse serum, 10 µg/mL
insulin, 20 ng/mL epidermal growth factor, 100 ng/mL cholera toxin, and
0.5 µg/mL hydrocortisone.
2.7. MTT Assay for Cell Viability
MDA-MB-231 cells in the logarithmic growth phase were harvested by
trypsinization, collected, and counted to prepare a cell suspension.
The cell density was adjusted to 0.5–1 × 10^5 cells/mL, and 100 µL of
the suspension was seeded into each well of a 96-well culture plate.
The cells were incubated overnight at 37 °C in a 5% CO[2] incubator to
allow for adherence, followed by treatment with dandelion extracts.
Each well received 100 µL of the extract solution, and cells were
incubated for 24 h. Each treatment group included six replicate wells,
with a blank group (medium only) and a control group (cells with
medium) set up simultaneously.
After incubation, the culture medium was removed, and the wells were
washed once with sterile PBS. Then, 200 µL of serum-free MEM medium and
10 µL of 0.5% MTT solution were added to each well. The plates were
incubated for 4 h at 37 °C. After incubation, the supernatant was
discarded, and 150 µL of DMSO was added to each well. The plates were
gently shaken for 10 min to dissolve the formazan crystals completely.
Absorbance was measured at 490 nm using a microplate reader. Cell
viability and the half-maximal inhibitory concentration (IC50) were
subsequently calculated.
2.8. Hoechst Staining
Hoechst staining was performed to examine nuclear fragmentation and
apoptotic cell morphology. After treatment, cells were fixed with 4%
paraformaldehyde for 30 min and stained with Hoechst 33,342 fluorescent
dye for 10 min. Following staining, cells were washed three times with
sterile PBS and observed under an Olympus IX71 inverted fluorescence
microscope (Olympus Corporation, Tokyo, Japan).
2.9. Detection of Apoptosis and Cell Cycle in MDA-MB-231 Cells by Annexin
V/PI Dual Staining
Flow cytometry was used to detect the levels of apoptosis in cells
subjected to different treatments. Briefly, cells were harvested by
trypsinization and centrifuged at 300× g for 5 min at 4 °C. The cell
pellets were washed twice with pre-cooled PBS, centrifuged, and
resuspended in a binding buffer. The apoptotic staining solution was
added, and the cells were incubated at room temperature in the dark for
15 min. After incubation, the cells were rewashed with binding buffer,
resuspended, and analyzed by flow cytometry. Data were collected and
analyzed using FlowJo V10.0 software to determine apoptosis and
necrosis rates.
For cell cycle analysis, treated cells were washed twice with
pre-cooled PBS, digested with trypsin, and collected by centrifugation.
After washing with PBS, cells were resuspended and incubated with 2 µL
of RNase A at 37 °C in a water bath for 30 min. Subsequently, 50 µL of
propidium iodide (PI) staining solution was added, and the cells were
incubated at room temperature in the dark for 20 min. Cell cycle
distribution was then analyzed using flow cytometry, and the data were
processed with ModFit 5.0 software.
2.10. Preparation of Samples for Proteomic Analysis
Cells in the logarithmic growth phase were seeded into culture dishes
at a density of 2–3 × 10^6 cells per dish. After normal incubation
until cell confluence reached approximately 80%, the old medium was
discarded, and the cells were washed once with PBS. Then, 10 mL of
medium containing 2 mg/mL EA-2 was added to each dish for the
experimental group, while a blank control group was established in
parallel. Each group included three biological replicates. The cells
were incubated for 24 h in a humidified incubator.
Following incubation, the medium was removed, and adherent cells were
digested with trypsin. The digested cells and residual medium were
collected into centrifuge tubes and centrifuged at 1000× g for 5 min to
harvest the cells. The cell pellets were resuspended in PBS and
counted, ensuring each group contained 1–2 × 10^7 cells. Cells were
centrifuged again at 1000× g for 5 min, and the resulting cell pellets
were rapidly frozen in liquid nitrogen and subsequently stored at −80
°C for further proteomic analysis.
2.11. Protein Identification and Quantification
Proteomic analysis was performed using an aQExactive mass spectrometer
(Thermo Fisher Scientific, Waltham, MA, USA) for label-free
quantitative proteomics analysis. Protein identification and
quantification were carried out by searching the raw mass spectrometry
data against the relevant protein annotation database using MaxQuant
1.5.3.17 software. The protein quantification algorithm used was LFQ
(Label-Free Quantification). The specific parameters used for database
searching and quantification in MaxQuant are summarized in
[51]Supplementary Table S1. Detailed steps of the analysis are provided
in [52]Supplementary Section S1.
2.12. Molecular Docking
The ligand–protein docking studies were conducted with CB-Dock2
[[53]14]. Compound structures were acquired from PubChem in SDF format
and energy-minimized. Protein structures were retrieved from RCSB PDB,
hydrogenated, and dehydrated. CB-Dock2 computed the binding affinities
(kcal/mol), with the most favorable docking poses selected based on
energy scores.
2.13. Data Analysis
Data were analyzed using Excel 2016, GraphPad Prism 9, and FlowJo V10
software. Experimental data are presented as means ± standard deviation
(
[MATH: x¯ :MATH]
± S) from three independent replicates.
3. Results
3.1. Effect of Dandelion Extract on the Viability of Human Breast Cancer
MDA-MB-231 Cells
Dandelion extracts were categorized into four types: dandelion root
aqueous extract (DR-AE), dandelion root ethanol extract (DR-EE),
dandelion leaf aqueous extract (DL-AE), and dandelion leaf ethanol
extract (DL-EE). These four extracts were applied to MDA-MB-231 cells
at concentrations of 0, 1, 2, and 3 mg/mL for 24 h, and cell viability
was measured by OD at 490 nm using a microplate reader. Among the four
extracts, only DR-EE showed significant inhibition of MDA-MB-231 cell
viability at 3 mg/mL (p < 0.01), indicating that the anti-breast cancer
activity of dandelion is primarily concentrated in the root, with DR-EE
exhibiting a significant inhibitory effect at this concentration
([54]Figure 1A). Based on this result, DR-EE was selected for further
investigation. The extract was partitioned using ethyl acetate, and
after solvent removal, two fractions were obtained: the ethyl acetate
(EA) fraction and the aqueous (H[2]O) fraction. To assess their
biological activity, both fractions were applied to MDA-MB-231 cells,
and OD490 nm values were measured. Compared with the control group,
both the EA and H[2]O fractions showed significant inhibitory effects
on cell proliferation (p < 0.05, p < 0.01), with the EA fraction
exhibiting a more pronounced effect (p < 0.01) ([55]Figure 1B).
Figure 1.
[56]Figure 1
[57]Open in a new tab
Effects of dandelion extracts on the viability of MDA-MB-231 Cells.
(A). Screening of the effects of different dandelion root and leaf
extracts on MDA-MB-231 cell viability. (B). Comparative analysis of the
EA and aqueous (H[2]O) fractions of dandelion root on MDA-MB-231 cell
viability. (C). Inhibitory effects of different fractions on MDA-MB-231
cell viability. (D). Chromatogram of the EA fraction from dandelion
root. (E). Chromatogram of the H[2]O fraction from dandelion root.
(Data are presented as the mean ± SD (n = 3), and statistical
significance was assessed by one-way ANOVA. * p < 0.05, ** p < 0.01,
*** p < 0.001 vs. control group).
Subsequently, the EA and H[2]O fractions were separated using Sephadex
G-10 gel chromatography, and the eluates were monitored at 230 nm using
an AKTA pure 25 system ([58]Figure 1D,E). Seven major fractions were
collected and applied to MDA-MB-231 cells. Among them, EA-1, EA-2,
EA-3, and H[2]O-2 significantly inhibited cell proliferation compared
to the control (p < 0.05), with EA-2 (the second subfraction of the
ethyl acetate extract) exhibiting the most significant inhibitory
effect (p < 0.001) ([59]Figure 1C). Therefore, the ethyl acetate
fraction was identified as having potent inhibitory activity on human
breast cancer MDA-MB-231 cells, and the most effective fraction, EA-2,
was selected for subsequent analyses.
3.2. Identification of EA-2 Compound Components
High-performance liquid chromatography–tandem mass spectrometry (LC-MS)
was used to analyze the EA-2 sample, and the total ion chromatogram and
mass spectrometry data were obtained ([60]Figure 2A,B). The analysis
identified 12 major chemical components in the sample, including
Betaine, (R)-Mandelic acid, Azelaic acid, Arglabin, and others. The
corresponding MS/MS spectra for each element are shown in
[61]Supplementary Figure S1. As shown in [62]Table 1, most of these
components exhibit anti-inflammatory activity and may represent
potential active ingredients responsible for inhibiting the
proliferation of MDA-MB-231 breast cancer cells.
Figure 2.
[63]Figure 2
[64]Open in a new tab
Total ion chromatogram (TIC) of EA-2 in positive ion mode (A) and
negative ion mode (B) from LC-MS analysis.
Table 1.
Mass spectrometry identification results of potential compounds in
EA-2.
No. Compound Rt (min) Molecular Formula Quantifier Ion mzVault Best
Match
Type m/z
1 Betaine 0.587 C[5]H[11]NO[2] [M + H]^+ 118.0865 84.6
2 (R)-Mandelic acid 3.027 C[8]H[8]O[3] [M − H]^− 151.0399 77.9
3 Azelaic acid 5.057 C[9]H[16]O[4] [M − H]^− 187.0974 85.3
4 Arglabin 5.806 C[15]H[18]O[3] [M + H]^+ 247.1329 76.7
5 Dehydrocostus lactone 5.258 C[15]H[18]O[2] [M + H]^+ 231.1380 93.5
6 Arteannuin 6.071 C[15]H[20]O[3] [M + H]^+ 249.1479 83.5
7 Nicotinic acid 0.819 C[6]H[5]NO[2] [M + H]^+ 124.0395 80.6
8 Atractylenolide II 4.757 C[15]H[20]O[2] [M + H]^+ 233.1532 83.7
9 Parthenolide 6.068 C[15]H[20]O[3] [M + H]^+ 249.1099 90.3
10 Linderalactone 4.699 C[15]H[16]O[3] [M + H]^+ 245.1172 89.0
11 Artemisinic acid 5.261 C[15]H[22]O[2] [M + H]^+ 235.1693 84.6
12 Isoalantolactone 4.762 C[15]H[20]O[2] [M − H]^− 233.1535 86.2
[65]Open in a new tab
To better understand their chemical properties and potential biological
relevance, these compounds were further categorized based on their
structural classes and reported bioactivities, as shown in [66]Table 2.
The identified compounds include sesquiterpene lactones (e.g.,
Arglabin, dehydrocostus lactone, parthenolide), atypical sesquiterpenes
(e.g., arteannuin, artemisinic acid), organic acids, and amino acid
derivatives. Notably, many of these compounds have been reported to
exhibit anti-inflammatory, antitumor, or pro-apoptotic activities,
suggesting their potential contribution to the inhibitory effect of
EA-2 on MDA-MB-231 breast cancer cells.
Table 2.
Major compound categories and their bioactivities.
Category Members Main Biological Activities
Sesquiterpene lactones Arglabin, Dehydrocostus lactone, Atractylenolide
II, Parthenolide, Isoalantolactone, Linderalactone Anti-inflammatory
[[67]15,[68]16], antitumor [[69]17,[70]18,[71]19], apoptosis induction
[[72]20,[73]21]
Sesquiterpenes (atypical) Arteannuin, Artemisinic acid Antimalarial
[[74]22], anti-inflammatory [[75]23,[76]24], anticancer [[77]25]
Organic acids (R)-Mandelic acid, Azelaic acid, Nicotinic acid
Antibacterial [[78]26], anti-inflammatory [[79]27,[80]28]
Amino acid derivatives Betaine Cytoprotective [[81]29], antioxidant
[[82]30], metabolic regulation [[83]31]
[84]Open in a new tab
3.3. Effect of EA-2 on the Viability of Normal Mammary Epithelial Cells
To investigate whether EA-2 could be a potential anti-breast cancer
drug and whether it has toxic side effects on normal mammary epithelial
cells, the viability of MDA-MB-231 and MCF-10A cells after drug
treatment was compared. The cell viability in the MDA-MB-231 group was
significantly lower than that in the MCF-10A group (* p < 0.05). At a
drug concentration of 2 mg/mL, the viability of MDA-MB-231 cells was
0.26 ± 0.06, while the viability of MCF-10A cells was 0.7 ± 0.06,
indicating that EA-2 has no toxic side effects on human mammary
epithelial cells ([85]Figure 3A).
Figure 3.
[86]Figure 3
[87]Open in a new tab
In vitro growth inhibition of MDA-MB-231 breast cancer cells by EA-2.
(A). Comparison of the growth effects of EA-2 on MDA-MB-231 cells and
MCF-10A mammary epithelial cells. (B). Concentration–time effect
relationship of EA-2 on the growth of MDA-MB-231 cells. (C).
Half-maximal inhibitory concentration (IC50) of EA-2 on human breast
cancer cells at different time points (data are presented as the mean ±
SD (n = 3), and statistical significance was assessed by two-way ANOVA
* p < 0.05, vs. control group).
3.4. Concentration–Time Effect of EA-2 on MDA-MB-231 Cell Growth
When MDA-MB-231 breast cancer cells were treated with different drug
concentrations, the growth of MDA-MB-231 cells was significantly
inhibited as the concentration increased. At a concentration of 1.5
mg/mL, the cell viability of MDA-MB-231 cells at 12 h, 24 h, 36 h, and
48 h was 0.72 ± 0.11, 0.53 ± 0.12, 0.51 ± 0.10, and 0.32 ± 0.11,
respectively, indicating that with the extension of treatment time,
cell viability gradually decreased (* p < 0.05, ** p < 0.01). At the
same time, the cell viability showed a decreasing trend with increasing
drug concentration, as shown in [88]Table 2. When the concentration
reached 2.0 mg/mL, further increases in drug concentration (e.g., 2.5
mg/mL) did not result in significant changes in cell viability at the
same time points, indicating that 2.0 mg/mL for 24 h was the optimal
inhibitory condition ([89]Figure 3B).
3.5. EA-2 Inhibits the Proliferation of MDA-MB-231 Breast Cancer Cells In
Vitro
EA-2 (0, 1, 1.5, 2, 2.5, 3 mg/mL) was applied to MDA-MB-231 cells for
12, 24, 36, and 48 h, and the cancer cell proliferation ability was
assessed by MTT assay. Compared with the control group, EA-2
significantly reduced the survival rate of MDA-MB-231 cells (* p <
0.05, ** p < 0.01) in a dose-dependent manner. The half-maximal
inhibitory concentrations (IC50) were 1.577, 1.124, 1.032, and 0.821
mg/mL, respectively ([90]Figure 3C). As the treatment time increased,
the IC50 gradually decreased, but there was no significant difference
between the IC50 values at 36 h and 48 h compared to 24 h (p > 0.05).
This suggests that prolonging the treatment time did not significantly
enhance the inhibitory effect of EA-2 ([91]Table 3). For subsequent
experiments, a 24 h treatment duration and concentrations of 0.5, 1,
1.5, and 2 mg/mL were selected as the conditions.
Table 3.
Comparison of cell viability and IC50 values over time (
[MATH: x¯ :MATH]
± S, n = 3).
Time (hours) Cell Viability IC50 (mg/mL)
12 0.72 ± 0.11 1.577 ± 0.23
24 0.53 ± 0.12 * 1.124 ± 0.18 *
36 0.51 ± 0.10 * 1.032 ± 0.12 *
48 0.32 ± 0.11 ** 0.821 ± 0.20 *
[92]Open in a new tab
Data are presented as the mean ± SD (n = 3), and statistical
significance was assessed by one-way ANOVA. * p < 0.05, ** p < 0.01,
vs. 12 h.
3.6. Effect of EA-2 on the Morphology of MDA-MB-231 Breast Cancer Cells
The morphology of MDA-MB-231 breast cancer cells was observed under a
microscope. The corresponding microscopic images of each treatment
group are shown in [93]Supplementary Figure S2. The control group
consisted of cells cultured in a normal medium. In contrast, the
experimental groups were treated with different concentrations of EA-2
(0.5 mg/mL, 1 mg/mL, 1.5 mg/mL, 2 mg/mL) for 24 h. In the control
group, the cells exhibited clear nuclear borders, a rhomboid shape, and
tight adherent distribution, growing in clusters with good conditions.
Significant morphological changes were observed in the experimental
groups with increasing drug concentrations. At 0.5 mg/mL, the cells
tended to become more rounded. At 1 mg/mL, intercellular connections
weakened, and cell rounding was more pronounced. At 1.5 mg/mL and 2
mg/mL, the cells became distinctly rounded and detached, with
intercellular connections almost completely destroyed, resulting in a
scattered distribution.
3.7. Hoechst Staining Observation of EA-2-Induced Apoptosis in MDA-MB-231
Cells
Hoechst staining was used to observe the apoptosis of MDA-MB-231 cells.
As shown in [94]Figure 4A–E, the control group exhibited round and
oval-shaped nuclei with uniform staining, weak blue fluorescence
intensity, and consistent distribution. In contrast, after treatment
with 1 mg/mL EA-2, the nuclear morphology showed significant changes,
including nuclear condensation, nuclear fragmentation, and chromatin
aggregation. Meanwhile, the blue fluorescence intensity was markedly
enhanced, indicating that EA-2 treatment could induce apoptosis in
MDA-MB-231 cells. To better visualize the nuclear morphological
alterations at each concentration, representative enlarged regions are
presented in [95]Figure 4F, clearly showing features such as nuclear
condensation, chromatin aggregation, and fragmentation. These images
provide more intuitive evidence of EA-2 induced apoptosis in a
concentration-dependent manner.
Figure 4.
[96]Figure 4
[97]Open in a new tab
EA-2 increases fluorescence intensity and causes nuclear structural
changes in MDA-MB-231 cells. (A). Control group. (B–E). Different
concentrations of the EA-2 treatment groups. In the control group, the
nuclear morphology is normal with uniform staining. In the treatment
groups, after 24 h of treatment, the cells exhibit apoptotic
characteristics such as nuclear condensation, chromatin aggregation,
and nuclear fragmentation. Scale bar 200 μm. (F). Enlarged views of
representative nuclear regions at each EA-2 concentration, highlighting
typical apoptotic features such as chromatin condensation and
fragmentation. Scale bar 25 μm. White arrows indicate nuclear body
fragments.
3.8. Effect of EA-2 on Apoptosis Rate of MDA-MB-231 Cells
Cell apoptosis was detected using the Annexin V-FITC/PI dual staining
method. After 24 h of treatment with different concentrations,
apoptosis in MDA-MB-231 cells was analyzed by flow cytometry. The
results, as shown in [98]Figure 5A–E, indicate that EA-2 significantly
affects the apoptosis of MDA-MB-231 cells. As the concentration
increased, the proportions of early (Q2 region) and late apoptotic
cells (Q3 region) gradually increased, while the proportion of live
cells (Q4 region) decreased. This suggests that EA-2 effectively
induces apoptosis in MDA-MB-231 cells at higher concentrations. The
results ([99]Figure 5F) further show that the concentration of EA-2 is
positively correlated with the percentage of apoptosis, and this
indicates that the anti-apoptotic effect of EA-2 is
concentration-dependent. Statistical analysis shows significant
differences between different concentration groups (* p < 0.05),
confirming that EA-2 induces apoptosis in breast cancer cells.
Figure 5.
[100]Figure 5
[101]Open in a new tab
Effect of EA-2 on apoptosis rate of MDA-MB-231 cells at different
concentrations. (A–E). Apoptosis of MDA-MB-231 cells treated with
different concentrations of EA-2. (F). Statistical analysis of
apoptosis results. (Data are presented as the mean ± SD (n = 3),
and statistical significance was assessed by one-way ANOVA. * p < 0.05,
** p < 0.01, **** p < 0.0001, vs. control group).
3.9. Effect of EA-2 on Cell Cycle Distribution of MDA-MB-231 Cells
Flow cytometry results ([102]Figure 6A–E) show that after treatment
with different concentrations of EA-2, the cell cycle distribution of
MDA-MB-231 cells was significantly altered. Compared with the control
group, all dose groups reduced the proportion of cells in the G0/G1
phase (* p < 0.05) and increased the proportion of cells in the S phase
(* p < 0.05) and G2/M phase. However, the increase in the G2/M phase
cell population was not statistically significant (p > 0.05),
suggesting that EA-2 induces cell cycle arrest in the S and G2/M phases
([103]Figure 6F). EA-2 inhibits cell proliferation to some extent by
altering the cell cycle distribution of MDA-MB-231 cells, particularly
by blocking the cells in the S phase, indicating its potential
anticancer effect.
Figure 6.
[104]Figure 6
[105]Open in a new tab
Impact of different concentrations of EA-2 on the cell cycle
distribution of MDA-MB-231 cells. (A–E). Distribution of MDA-MB-231
cells in the cell cycle under different concentrations of EA-2
treatment. (F). Statistical analysis of cell cycle distribution. (Data
are presented as the mean ± SD (n = 3), and statistical
significance was assessed by two-way ANOVA * p < 0.05, ** p < 0.01,
**** p < 0.0001, vs. control group).
3.10. Differential Protein Identification and Quantification Analysis
We performed label-free quantitative proteomics to analyze the
differential protein expression between EA-2-treated MDA-MB-231 cells
and untreated MDA-MB-231 breast cancer cells. Mass spectrometry data
were analyzed using MaxQuant software (v1.5.3.17), with both protein
and peptide identifications controlled at a false discovery rate (FDR)
of ≤ 0.01. A total of 5577 proteins were identified. Differentially
expressed proteins (DEPs) were defined by a fold change > 2 or < 0.5
(i.e., |log[2]FC| ≥ 1) and a p-value < 0.05. Based on these criteria,
137 DEPs were identified, including 76 upregulated and 61 downregulated
proteins ([106]Figure 7A–C). Hierarchical clustering analysis revealed
significant differences between the groups ([107]Figure 7D). Gene
Ontology (GO) analysis ([108]Figure 7E) showed that these differential
proteins were primarily localized to the cell membrane and organelles,
as well as involved in metabolic and regulatory pathways. Kyoto
Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis
([109]Figure 7F) indicated that the differential proteins were mainly
enriched in the PPAR signaling pathway, JAK-STAT signaling pathway,
PI3K-Akt signaling pathway, and MAPK signaling pathway. The cooperative
effect of multiple signaling pathways stimulates apoptosis and inhibits
proliferation in breast cancer cells. Subsequently, the expression
levels of differentially expressed proteins—including PI3K, AKT1S1,
SIRT6, JAK1, SCD, STAT3, CASP8, STAT6, PAK1, and FABP4—were
significantly downregulated. These results suggest that EA-2 may induce
apoptosis and inhibit cell proliferation in breast cancer cells through
the coordinated action of multiple signaling pathways.
Figure 7.
[110]Figure 7
[111]Open in a new tab
Differential protein expression analysis. (A). Statistical chart of
protein expression differences between groups. (B). Volcano plot of
protein expression differences between the experimental and control
groups. (C). Bar chart of quantitative protein expression differences.
(D). Clustering analysis of differentially expressed proteins. (E). GO
annotation analysis of differentially expressed proteins. (F). KEGG
metabolic pathway enrichment analysis of differentially expressed
proteins.
3.11. Validation Analysis of Interactions Between Major Active Compounds and
Potential Targets
Based on KEGG pathway enrichment analysis, the JAK-STAT, PI3K-Akt, and
PPAR signaling pathways were identified as key regulatory pathways. To
further validate the interactions between active compounds and core
targets, molecular docking was performed between the major bioactive
constituents of dandelion and key differential proteins within these
pathways, including PI3K, PAK1, JAK1, STAT3, and FABP4. The results
demonstrated that the binding energies of most compound–target
interactions were below −5 kcal·mol^−1 ([112]Table 4), suggesting
strong binding affinities. Among the compounds, Arteannuin,
Atractylenolide II, and Arglabin exhibited particularly strong binding
capabilities. Structural analysis revealed that these three compounds
have relatively low molecular weights—282.3, 327.4, and 246.3 Da,
respectively—and all belong to the class of terpenoids. This structural
feature may contribute to their enhanced ability to bind target active
sites and penetrate cellular membranes.
Table 4.
Molecular docking results of major active compounds in EA-2 with
potential targets.
Active Compounds Binding Energy/ (kcal·mol^−1)
PI3K PAK1 JAK1 STAT3 FABP4
Betaine −4.2 −3.2 −3.6 −3.5 −4.5
(R)-Mandelic acid −6.6 −5.3 −5.9 −5.3 −4.6
Azelaic acid −5.9 −4.8 −3.5 −5.4 −4.2
Arglabin −7.9 −6.1 −8.7 −6.7 −8.6
Dehydrocostus lactone −7.8 −6.9 −8.5 −6.7 −7.0
Arteannuin −8.4 −7.3 −9.3 −7.5 −8.9
Nicotinic acid −5.6 −3.8 −4.8 −4.6 −4.9
Atractylenolide II −8.2 −6.8 −7.8 −6.8 −6.5
Parthenolide −7.9 −4.2 −7.5 −6.7 −7.4
Linderalactone −8.1 −6.6 −7.8 −6.6 −8.1
Artemisinic acid −7.5 −6.1 −7.2 −6.6 −5.5
Isoalantolactone −8.3 −6.8 −8.6 −6.4 −6.1
[113]Open in a new tab
Furthermore, analysis of their lipid–water partition coefficients
(LogP) showed values of 2.93, 2.37, and 4.12, respectively, all falling
within the optimal range of 2–5. This suggests favorable lipophilicity
for tissue permeability and potential bioavailability in tumor
environments. Notably, previous studies have confirmed the significant
antitumor effects of Arteannuin and Arglabin, with derivatives of
Arglabin already approved for clinical treatment of breast cancer in
Kazakhstan. The results suggest that these compounds may represent the
principal active constituents in dandelion responsible for its
inhibitory effects on breast cancer. This finding is highly consistent
with the KEGG pathway enrichment results, further indicating that these
compounds may exert their biological effects by modulating the
identified signaling pathways.
3.12. MTT Evaluation of Bioactive Compounds on MDA-MB-231 Breast Cancer Cells
To further validate the bioactivity of the identified compounds,
Dehydrocostus lactone, Arteannuin, and Atractylenolide II were selected
for individual testing based on their superior molecular docking
results. MTT assays were performed to determine their inhibitory
effects on the proliferation of MDA-MB-231 cells. The results showed
that Dehydrocostus lactone exhibited strong cytotoxicity against
MDA-MB-231 cells in a dose- and time-dependent manner, with IC[50]
values of 20 μM at 24 h and 8.79 μM at 48 h ([114]Figure 8A).
Arteannuin also demonstrated significant inhibition in a dose- and
time-dependent manner, with IC[50] values of 37.15 μM (24 h) and 5.33
μM (48 h) ([115]Figure 8B). In contrast, Atractylenolide II showed no
obvious inhibitory effect on cell viability under the same conditions,
indicating a weaker impact on breast cancer cell viability and
suggesting it is not a major antitumor active compound ([116]Figure
8C).
Figure 8.
[117]Figure 8
[118]Open in a new tab
Inhibitory effects of three representative compounds identified from
EA-2 on the viability of MDA-MB-231 cells. (A). Dehydrocostus lactone.
(B). Arteannuin. (C). Atractylenolide II. They were evaluated for their
antiproliferative activity using MTT assays at 24 h and 48 h. (Data are
presented as the mean ± SD (n = 3), and statistical significance was
assessed by two-way ANOVA, ** p < 0.01, *** p < 0.001, vs. control
group).
In addition to the three tested compounds, the remaining nine compounds
identified in the EA-2 composition—Arglabin, Parthenolide,
Isoalantolactone, Linderalactone, Artemisinic acid, (R)-Mandelic acid,
Azelaic acid, Nicotinic acid, and Betaine—also possess reported
antitumor activities, particularly against breast cancer and MDA-MB-231
cells. For example, Arglabin has been found to exert antitumor effects
by inhibiting farnesyltransferase and has been approved in Kazakhstan
as an anticancer drug for the treatment of breast cancer, ovarian
cancer, and lung cancer [[119]32]. Parthenolide may inhibit
angiogenesis by reducing the secretion of angiogenic factors from
MDA-MB-231 breast cancer cells, thereby interfering with endothelial
cell proliferation, migration, and tube formation, ultimately
suppressing tumor growth [[120]33]. Isoalantolactone and
Linderalactone, both sesquiterpene lactones, exhibit inhibitory effects
on triple-negative breast cancer [[121]34,[122]35]. Artemisinic acid,
as an artemisinin-type sesquiterpene, inhibits breast cancer cell
growth in a dose-dependent manner [[123]36]. Although small molecule
organic acids such as (R)-Mandelic acid, Azelaic acid, and Nicotinic
acid are not classical anticancer agents, their reported
anti-inflammatory, antimicrobial, or antioxidant properties may help
modulate the tumor microenvironment or enhance the bioavailability of
other active compounds.
In summary, Dehydrocostus lactone, Arteannuin, and Arglabin are likely
the primary active components responsible for the antiproliferative
effects of EA-2. While the other compounds vary in potency and
mechanisms, they may play supportive roles in the overall effect. This
interplay reflects the intrinsic complexity of EA-2 and supports its
potential as a multi-component therapeutic candidate for breast cancer
intervention.
4. Discussion
Breast cancer is the most commonly diagnosed malignant tumor among
women worldwide and poses a serious threat to women’s health.
Epidemiological data indicate a continuous increase in its incidence,
making breast cancer the leading cause of cancer-related mortality
among women [[124]37]. Among them, specific molecular subtypes such as
TNBC lack effective targeted therapeutic strategies, and the
development of acquired resistance induced by chemotherapy and targeted
therapies further reduces treatment response rates [[125]38]. It is
noteworthy that conventional chemotherapeutic agents are often
associated with dose-limiting toxicities, including bone marrow
suppression and cardiotoxicity, which severely affect patients’
treatment tolerance and long-term prognosis [[126]39]. Therefore, there
is an urgent need to identify safer and more effective adjuvant
therapeutic agents, which has become a pressing priority in the field
of breast cancer treatment.
Existing studies have confirmed that dandelion exhibits multiple
biological activities, including anti-inflammatory, antioxidant, and
immunomodulatory effects. Its polyphenols and flavonoids exert
significant antitumor effects in various malignancy models by
regulating cell cycle arrest, inducing apoptosis, and inhibiting
epithelial–mesenchymal transition (EMT) [[127]40,[128]41]. However, the
precise molecular mechanisms and regulatory networks of dandelion
extracts against breast cancer cells remain incompletely understood,
and its application in precision breast cancer therapy requires
systematic preclinical validation. In view of this, the present study
further systematically investigated the selective inhibitory effects
and molecular mechanisms of dandelion extracts on TNBC MDA-MB-231
cells. The results demonstrated that dandelion root alcohol extracts
significantly inhibited the proliferation of MDA-MB-231 cells, with the
ethyl acetate (EA-2) fraction exhibiting the strongest antitumor
activity, suggesting that this fraction may be enriched with the
principal active components against breast cancer. LC-MS analysis
successfully identified 12 potential active compounds, mainly including
sesquiterpene lactones (e.g., Arglabin, dehydrocostus lactone,
parthenolide), atypical sesquiterpenes (e.g., arteannuin, artemisinic
acid), organic acids, and amino acid derivatives.
Among them, Isoalantolactone significantly inhibits human breast cancer
cell proliferation, and its activity is related to the
α-methylene-γ-lactone group in its molecular structure, which can
interfere with DNA replication in cancer cells through alkylation
[[129]42,[130]43]. Artemisinin exerts inhibitory effects on TNBC
MDA-MB-231 cells by generating reactive oxygen species (ROS) via
iron-mediated oxidative stress, effectively inducing apoptosis
[[131]44]. Parthenolide can inhibit the NF-κB pathway, reducing
inflammatory factor release and indirectly suppressing the tumor
microenvironment [[132]45,[133]46]. Importantly, the extract
effectively inhibits tumor cells without obvious toxicity to MCF-10A
normal mammary epithelial cells, demonstrating good selective
inhibition. The MTT assay accurately assessed the inhibitory effect on
cell proliferation, showing that within a low concentration range
(0.5–2 mg/mL), dandelion extract did not significantly affect normal
cell viability (p > 0.05), whereas it exhibited significant inhibitory
effects on MDA-MB-231 breast cancer cells at equivalent concentrations,
suggesting that dandelion extract may reduce the side effects of
conventional chemotherapy on normal tissues.
Cell cycle analysis using PI staining combined with flow cytometry
revealed significant changes in cell cycle distribution in MDA-MB-231
cells after 24 h treatment with EA-2, with notable increases in the
proportions of cells in S and G2/M phases. This indicates that EA-2 may
induce DNA damage accumulation and S phase arrest by inhibiting key
enzymes involved in DNA synthesis such as DNA polymerase or
topoisomerase, or by inducing replication stress. Previous studies have
confirmed that anticancer drugs can block mitotic progression by
inhibiting the activity of the CDK1/Cyclin B complex, thereby inducing
G2/M phase arrest, leading to a significant increase in the G2/M
population and suppressing breast cancer cell proliferation
[[134]47,[135]48,[136]49,[137]50]. Additionally, G2/M arrest may
enhance cellular sensitivity to DNA damage signals, further promoting
apoptosis in cancer cells [[138]51].
LFQ is a widely used high-throughput protein analysis technique in
biomedical mechanism research [[139]52]. This study applied label-free
quantitative proteomics to systematically analyze the effects of EA-2
treatment on the protein expression profile of triple-negative breast
cancer MDA-MB-231 cells. Mass spectrometry detected a total of 5577
proteins, among which 137 showed significant differential expression.
Among them, 76 proteins were upregulated, including RIT1 and FABP4,
while 61 proteins were downregulated, involving key regulatory
molecules such as PI3K, AKT1S1, SIRT6, JAK1, SCD, STAT3, and CASP8.
Bioinformatics analysis revealed that these differentially expressed
proteins were significantly enriched in three key KEGG pathways. In the
PI3K-Akt signaling pathway, upstream regulators RIT1 and PAK1 promote
activation of PI3K/Akt, thereby regulating cell survival and cell cycle
progression [[140]53,[141]54]. We observed significant upregulation of
upstream regulatory factors such as PAK1 and RIT1, while mTORC1
negative regulator AKT1S1 and metabolic regulator SIRT6 were
downregulated, suggesting that EA-2 may inhibit cell proliferation and
induce programmed cell death by interfering with the pro-survival
PI3K-Akt-mTOR signaling axis. In the JAK-STAT signaling pathway, JAK1
indirectly regulates cell proliferation and apoptosis through
activation of downstream STAT factors; the significant downregulation
of STAT family member STAT3 and apoptosis-related protein CASP8
indicates that EA-2 may suppress tumor cell proliferation and
anti-apoptotic capacity by blocking JAK-STAT3 signaling transduction.
In the PPAR signaling pathway, the upregulation of PPARγ and its target
gene FABP4, along with the significant downregulation of lipid
synthesis enzyme SCD, reveals that EA-2 may remodel tumor cell lipid
metabolism by activating the PPARγ pathway [[142]55,[143]56]. This
study systematically reveals that the active components in dandelion
extract EA-2 may achieve multi-dimensional regulation of proliferation,
apoptosis, and metabolic reprogramming in MDA-MB-231 breast cancer
cells through multi-target and multi-pathway mechanisms. These findings
not only provide a solid scientific basis for the application of
dandelion in breast cancer treatment but also lay an important
theoretical foundation for the development of multi-pathway synergistic
therapies targeting triple-negative breast cancer.
5. Conclusions
This study focused on the inhibitory effects of dandelion extract on
breast cancer cells and systematically explored its impact on the
proliferation, apoptosis, and cell cycle of MDA-MB-231 cells, along
with its underlying molecular mechanisms. The results demonstrated that
the dandelion root extract exhibited significant anti-proliferative
effects against breast cancer cells, with the EA-2 fraction effectively
inhibiting MDA-MB-231 cell proliferation, inducing cell cycle arrest
and promoting apoptosis. Proteomics-based analysis revealed that EA-2
exerts its effects by modulating the JAK-STAT, PI3K-Akt, and PPAR
signaling pathways, as well as lipid metabolism-related pathways,
thereby synergistically suppressing proliferation and promoting
apoptosis in breast cancer cells. The underlying mechanisms involve the
regulation of key proteins such as PI3K, PAK1, JAK1, SIRT6, and FABP4,
disrupting the survival capacity and metabolic homeostasis of
MDA-MB-231 cells. This study provides a theoretical foundation for
understanding the molecular mechanisms underlying the anti-breast
cancer effects of dandelion extract and offers an experimental basis
and reference for the development of novel therapeutic strategies for
breast cancer treatment.
Abbreviations
The following abbreviations are used in this manuscript:
LC-MS Liquid chromatography–tandem mass spectrometry
TNBC Triple-negative breast cancer
ER Estrogen receptor
PR Progesterone receptor
HER2 Human epidermal growth factor receptor 2
CDKs Cyclin-dependent kinases
PCD Programmed cell death
FBS Fetal bovine serum
ESI Electrospray ionization
TIC Total ion chromatograms
HRMS Human epidermal growth factor receptor 2
IC50 Half-maximal inhibitory concentration
PI Propidium iodide
LFQ Label-Free Quantification
DR-AE Dandelion root aqueous extract
DR-EE Dandelion root ethanol extract
DL-AE Dandelion leaf aqueous extract
DL-EE Dandelion leaf ethanol extract
EA Ethyl acetate
EA-2 The second subfraction of the ethyl acetate extract
FDR False discovery rate
DEPs Differentially expressed proteins
GO Gene Ontology
KEGG Kyoto Encyclopedia of Genes and Genomes
LogP Partition coefficients
EMT Epithelial–mesenchymal transition
ROS Reactive oxygen species
UPLC Ultra-performance liquid chromatography
SIM Selected ion monitoring
SDT Lysis buffer composed of SDS, DTT, and Tris-HCl
SDS Sodium dodecyl sulfate
DTT Dithiothreitol
BCA Bicinchoninic Acid Assay
FASP Filter-aided sample preparation
IAA Iodoacetamide
DDA Data-dependent acquisition
HCD Higher-energy collisional dissociation
FC Fold change
KAAS KEGG Automatic Annotation Server
[144]Open in a new tab
Supplementary Materials
The following supporting information can be downloaded at
[145]https://www.mdpi.com/article/10.3390/biology14080910/s1,
Supplementary Figure S1: Untargeted qualitative analysis and
identification of herbal chemical constituents based on LC-MS.
Supplementary Figure S2: EA-2-induced growth inhibition and
morphological changes in MDA-MB-231 breast cancer cells. Supplementary
Table S1: MaxQuant Identification and Quantification Parameters.
[146]biology-14-00910-s001.zip^ (5.1MB, zip)
Author Contributions
W.M.: Conceptualization, Investigation, Writing–original draft,
Methodology. P.Z.: Formal analysis, Data curation. Y.C.: Investigation,
Visualization. D.Y.: Investigation. G.Z.: Software, Validation. H.X.:
Modifying the manuscript. D.Z.: Investigation, Modifying the
manuscript, Methodology. Y.L.: Conceptualization, Supervision, Funding
acquisition. All authors have read and agreed to the published version
of the manuscript.
Institutional Review Board Statement
Not applicable.
Informed Consent Statement
Not applicable.
Data Availability Statement
The data supporting this study’s findings are available from the
corresponding authors upon reasonable request.
Conflicts of Interest
Author Haijun Xu was employed by the Shaanxi Sanbafule Sci&Tech Co.,
Ltd. The remaining authors declare that the research was conducted in
the absence of any commercial or financial relationships that could be
construed as a potential conflict of interest.
Funding Statement
The Shaanxi Provincial Department of Science and Technology Project
(No. 2023-CX-PT-24, No. 2023-YBSF-017), the Key Research and
Development Program of Shaanxi Province (No. 2024SF-ZDCYL -02-13),
Qinba Bioresources and Ecological Environment National Key Laboratory
(No. SLGPT2019KF04-05), and the Doctoral Talent Start-up Program (No.
SLGRCQD012).
Footnotes
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References