Abstract
Non-small cell lung cancer (NSCLC) is among the most prevalent cancers
and a leading cause of cancer-related mortality globally. Extracellular
vesicles (EVs) derived from NSCLC play a pivotal role in lung cancer
progression. Our findings reveal a direct correlation between the
abundance of EVs and the transfection efficiencies. Co-culturing two
different lung cancer cell lines could enhance EVs formation, cell
proliferation, migration and tumorigenicity. mRNA chip and metabolic
analyses revealed significant alterations in the FOXO signaling pathway
and unsaturated fatty acid metabolism within tumor tissues derived from
co-cultured cells. Shotgun lipidomics studies and bioinformatics
analyses guided our attention towards 4-Hydroxynonenal (4-HNE) and
FOXO4. Elevating 4-HNE or FOXO4 levels could reduce the formation of
EVs and impede cell growth and migration. While silencing FOXO4
expression lead to an increase in cell cloning rate and enhanced
migration. These findings suggest that regulating the production of
4-HNE and FOXO4 might provide an effective therapeutic approach for the
treatment of NSCLC.
graphic file with name 41419_2024_6948_Figa_HTML.jpg
Subject terms: Cancer microenvironment, Non-small-cell lung cancer,
Non-small-cell lung cancer
Introduction
Lung cancer is one of the most frequently cancers leading cause of
cancer-related deaths worldwide and non-small cell lung cancer (NSCLC)
is a main histological subtype (85% of lung cancer cases) [[42]1].
There is increasing evidence that the tumor microenvironment (TME) is
closely related to the development of cancer [[43]2]. The impact of
tumor-released extracellular vesicles (EVs) on persistent cellular
proliferation and resistance to cell death, stimulation of
angiogenesis, facilitation of invasion and metastasis, evasion of
immune response, and modification of TME underscores their significance
as central regulators in cancer mechanisms [[44]3, [45]4]. Metastasis
of NSCLC is the main cause of death, the specific mechanism of NSCLC
metastasis remains to be further studied.
EVs are a heterogeneous population of cell-derived membrane vesicles
that are secreted by various cell types [[46]4]. Two main types of EVs
are distinguished based on their biogenesis, known as exosomes and
ectosomes. Exosomes are small EVs of endosomal origin released by the
exocytosis of multivesicular bodies and amphisomes. Ectosomes are
formed via the budding and blebbing of the plasma membrane [[47]5,
[48]6]. This process is accompanied by molecular rearrangements at the
periphery of the plasma membrane, resulting in modifications to its
lipid and protein compositions [[49]4]. EVs released by NSCLC cells can
drive invasion and permeability in non-tumorigenic lung epithelial
cells [[50]7].
The biogenesis and release of EVs have been shown to increase in
various stressful conditions including hypoxia, senescence or oncogene
activation [[51]8, [52]9]. Oxidative stress conditions influence the
release and the molecular cargo of EVs that, in turn, modulate the
redox status of target cells [[53]9]. To cope with abnormal energy and
redox environments, tumor cells upregulate the expression of
antioxidant proteins, aiming to detoxify heightened levels of reactive
oxygen species (ROS). This process enables the establishment of a redox
equilibrium, all the while sustaining pro-tumorigenic signaling and
fortifying resistance to apoptosis [[54]10]. Overproduction of these
ROS, can disrupt cell signaling, and in turn change the volume and
composition of EVs [[55]11]. Accompanied by provoke oxidation of
polyunsaturated fatty acids (PUFAs) in cellular membranes through free
radical chain reactions and form lipid hydroperoxides as primary
products. A study reported that adipocytes respond to oxidative stress
by rapidly and robustly releasing EVs [[56]12]. Tumor cells upregulate
their lipid metabolism machinery to meet the increased energy demand
[[57]13]. Tumor cells regulate intercellular lipid exchange by forming
EVs, which may be an effective pathway for them to resist lipid
peroxidation death caused by hypoxia-induced oxidative stress.
Lipid peroxidation is a process under which oxidants such as free
radicals attack lipids which containing carbon-carbon double bond(s),
especially PUFAs, almost all tumor cells have an imbalance in this
process [[58]14]. In terms of EVs trafficking, it should be mentioned
that the lipid composition of EVs membranes may play a role in
conferring vesicles stability or to facilitate uptake into recipient
cells [[59]15]. Among lipid peroxidation products, 4-HNE represents one
of the most bioactive and well-studied lipid alkenals [[60]16]. A study
reported, 4-HNE promotes the release of microvesicles from perivascular
cells into the circulation [[61]17]. Prolonged exposure to oxygen
fractions exceeding 0.8 (O[2] fractions) has been shown to induce the
production of ROS, leading to the development of pulmonary edema and
proliferative fibrosis in animal models [[62]18]. 4-HNE was reported to
implicate in this type of acute lung injury. It interacts with various
mitochondrial targets, forming adducts that result in mitochondrial
dysfunction and disruption of cellular bioenergetics [[63]19]. 4-HNE
has a dual and hormetic effect, low concentrations (about 0.1–5
micromolar) are beneficial to cells, promoting proliferation,
differentiation, antioxidant defense and compensatory mechanisms, high
concentrations (about 10–20 micromolar) trigger toxic pathways leading
to cell death. Overproduction of 4-HNE may ultimately compromise
membrane integrity and lead to cell death via a process known as
ferroptosis [[64]20]. 4-HNE, a marker of lipid peroxidation, is closely
associated with lung tumor size and stage. Lung tumors exhibiting
higher degree of malignancy tend to show lower level of lipid
peroxidation [[65]21]. Inhibiting the excessive production of 4-HNE in
tumor tissue maybe is necessary to maintain the survival of tumor
cells.
FOXOs are recognized as tumor suppressors due to their confirmed roles
in inducing cell cycle arrest, DNA damage repair, and scavenging of ROS
[[66]22]. Numerous histopathological investigations have highlighted an
association between decreased FOXO4 expression and heightened cancer
metastasis [[67]23, [68]24]. It activates the cell cycle-dependent
kinase inhibitor p27, which in turn inhibits cell cycle-dependent
kinases (CDKs) and blocks G1 cell cycle progression in tumors [[69]25].
In hypoxic tumor environments, FOXO4 downregulates hypoxia-inducible
factor 1α (HIF-1α), thereby suppressing responses to hypoxia such as
the expression of glucose transporter type 1 (GLUT-1), erythropoietin
(EPO), and vascular endothelial growth factor. These factors are
involved in glucose metabolism, erythropoiesis, and angiogenesis, all
of which are crucial for tumor development [[70]26]. Furthermore,
downregulation of FOXO4 is significantly associated with low-grade
lymph node metastases and stage III and IV tumors in colorectal cancer
[[71]27]. Another important function of FOXO4 is the role in cellular
responses to oxidative stress. On one hand, FOXO4 regulates the
cellular oxidative state by facilitating detoxification through the
transcriptional activation of antioxidative enzymes, including
superoxide dismutase and catalase. On the other hand, ROS modulate
FOXO4 activity, either by activating the upstream regulatory pathways
of FOXO4 or by sensing the cellular redox potential [[72]28].
In the present study, we armed to the effects of 4-HNE on EVs
formation, tumor cell growth, and migration, and we also found that
FOXO4 activity positively correlated with 4-HNE levels. Under
conditions of oxidative stress, whether 4-HNE interacts with FOXO4 to
affect the biogenesis and development of EVs, thereby regulating the
growth and metastasis of tumor cells, has not been reported. This is
the focus of this study.
Results
The extracellular vesicles of lung cancer cells influence transfection
efficiency and positively correlate with tumor growth
As depicted in Fig. [73]1a, six lung cancer cell lines underwent
transfection with the PEGFP-C1 vector by using liposomes. The number of
green fluorescent cells per unit area was counted, and the result
showed a notably higher green fluorescent protein (GFP) expression in
95D cells transfected with the pEGFP-C1 vector, in contrast to the
lower expression observed in HCC827 cells (Fig. [74]1b). Concurrently,
scanning electron microscopy (SEM) highlighted a morphological
contrast; HCC827, H460, and A549 cells, characterized by a flat
morphology, exhibited fewer EVs compared to the spherical H1299, H838,
and 95D cells (Fig. [75]1c). These EVs are crucial for direct cellular
connections, facilitating gap junctional intercellular communication
and metabolic coupling among adjacent cells [[76]29]. To further
observations, HCC827 and 95D stable cell lines were subcutaneously
inoculated into nude mice (Fig. [77]1d). Post 30 days, the development
of subcutaneous tumors was assessed. Our findings indicate that the 95D
cell line significantly accelerated tumor growth (Fig. [78]1e).
Fig. 1. The transfection efficiency in lung cancer cell lines positively
correlated with the number of extracellular vesicles and tumor cell growth.
[79]Fig. 1
[80]Open in a new tab
a Green fluorescent protein (GFP) expression in human lung cancer cell
lines following transfection with the pEGFP-C1 vector via lipofection.
The magnification was 200×. b Quantitative analysis of GFP expression
levels across different groups, evaluated using one-way analysis of
variance (*p < 0.05 versus H1299 group, ^#p < 0.05 versus H838 group,
^p < 0.05 versus 95D group). c Scanning electron microscopy images
revealing varied structural characteristics of cell membrane surface of
human lung cancer cell lines. Scale bar = 10 μm. d HCC827 and 95D cells
were subcutaneously implanted into the right flanks of nude mice, as
detailed in the Methods section. e Tumors were excised and photographed
30 days post-injection.
Co-culturing of cells enhances information exchange and accelerates cell
growth and migration
To investigate whether cell lines with different morphologies can
exchange information through EVs, thereby affecting cellular growth. We
analyzed the cell surface morphology of co-cultured cells using SEM.
The results showed that the two lung cancer cell lines could contact
each other through EVs (Fig. [81]2a). A549 is an epithelial cell that
was isolated from the lung of male with carcinoma. H1299 cell line was
established from a lymph node metastasis of the lung from a patient who
had received prior radiation therapy. Lymph nodes are frequent sites
for lung cancer metastasis. the co-culture of A549 and H1299 cells is
intended to simulate the lung cancer microenvironment more
realistically. Here, we found there was an increase in the production
of EVs between the A549 and H1299 co-cultured cells as co-culture time
progressed (Fig. [82]2b). Following ‘AH cells’ refer to the co-cultured
combination of A549 and H1299 cells. Next, the AH cells were
transfected with the PEGFP-C1 vector. Statistical analysis indicated
that the longer the cells were co-cultured, the higher the transfection
efficiency in AH cells (Fig. [83]2c, d). In the cell scratch assay, the
co-cultured AH cells also demonstrated a faster migration rate (Fig.
[84]2e, f).
Fig. 2. Accelerated effects of intercellular communication on migration and
proliferation.
[85]Fig. 2
[86]Open in a new tab
a Scanning electron microscope (SEM) images showcasing structural
interactions between co-cultured lung cancer cells over 3 days. H838
(&) cells mixed with A549 (#) cells, H838 (&) cells mixed with HCC827
($) cells and A549 (#) cells mixed with H1299 (Δ) cells demonstrate
intercellular connections (red arrows). Scale bar = 10 μm. b
Time-course SEM images of A549 (#) and H1299 (Δ) cells co-cultured for
3, 6, and 9 days, highlighting progressive structural intercellular
connectivity and increased formation of EVs (red arrows). Scale
bar = 10 μm. c After co-culturing A549 and H1299 cells (referred to as
AH) for 1, 2, 3, and 4 days, the cells were transfected with the PEGFP
expression vector using lipofection. As the co-culture period
increased, the transfection efficiency of the co-cultured cells also
increased. the magnification was 100×. d Quantitative analysis of
transfection efficiency, using one-way ANOVA reveals significant
differences over time (*p < 0.05 versus 0 day group, ^#p < 0.05 versus
1 day group, ^p < 0.05 versus 2 day group, ^+p < 0.05 versus 3 day
group). e The cell scratch assay images depicting the migration of
A549, H1299, and co-cultured A549 + H1299 (referred to as AH) cells at
0, 12, 24, and 36 h. f Statistical evaluation of cell migration rates,
expressed as a function of distance migrated over time, compares the
migratory capacity of A549, H1299, and AH cells using one-way ANOVA.
Accelerated tumor growth in nude mice inoculated with co-culture cells
To investigate the biological effects of co-cultured cells on tumor
growth in vivo, equal amounts of A549, H1299, and AH cells were
suspended in saline and injected into nude mice (Fig. [87]3a). After 30
days, all three cell types had formed tumors in the mice. These tumors
were then dissected, photographed, and weighed for analysis (Fig.
[88]3b). There were significant statistical differences in tumor weight
among the A549, H1299, and AH groups (Fig. [89]3c). Subsequently, tumor
tissues from different groups were sent to a sequencing company for RNA
microarray analysis. Based on the raw transcriptome data, we conducted
venn analyses to identify genes that were exclusively upregulated or
downregulated in the AH group compared to the A549 and H1299 groups.
Specifically, there were 440 genes co-up-regulated (fold change >1.2,
p < 0.05) in both AH vs A549 group (comprising 6350 up-regulated genes)
and AH vs H1299 group (comprising 1249 up-regulated genes).
Additionally, 766 genes were co-down-regulated (Fold Change >1.2,
p < 0.05) in the comparisons of AH vs A549 group (4358 down-regulated
genes) and AH vs H1299 group (2156 down-regulated genes), as
illustrated in Fig. [90]3d.
Fig. 3. Mixed tumor cells accelerate tumor growth in tumorigenesis
experiments.
[91]Fig. 3
[92]Open in a new tab
a A549 cells, H1299 cells, and co-cultured A549 + H1299 (referred to as
AH) cells were subcutaneously implanted into the right flanks of nude
mice, as outlined in the methods section. b Tumors were excised 30 days
post-injection and photographed. c The weight of the tumors in each
experimental group was statistically analyzed using one-way ANOVA
(*p < 0.05 versus A549 group, ^#p < 0.05 versus H1299 group). d Venn
diagrams illustrate the number of upregulated and downregulated genes
in tumor tissues comparing AH versus A549 and AH versus H1299 groups.
Compared to A549 and H1299 groups, there are 440 upregulated and 766
downregulated genes in AH group. e KEGG pathway enrichment analysis of
differentially expressed genes, with varying colors representing
distinct pathways. p < 0.05 was considered statistically significant.
f–h Gene ontology (GO) term distributions for biological process (BP),
cellular component (CC), and molecular function (MF) categories are
shown. Orange indicates upregulated genes, and blue indicates
downregulated genes. p < 0.05 was considered statistically significant.
To elucidate the potential biological functions of co-up-regulated and
co-down-regulated genes (440 + 766), we employed the DAVID database for
Kyoto Encyclopedia of Genes and Genomes (KEGG) and Gene Ontology (GO)
functional enrichment analysis. KEGG pathway enrichment analysis showed
that genes were mainly involved in 8 signaling pathways (Fig. [93]3e).
In the AH tumor tissues, we identified 248 GO terms with p < 0.05. We
visualized the top 6 ranked terms in biological processes (BP),
cellular components (CC), and molecular functions (MF). The GO analysis
revealed a significant enrichment of pathways related to the function
of EVs. For instance, in BP, there were processes like
ubiquitin-independent protein catabolic process via the multivesicular
body sorting pathway, mitochondrion transport along microtubule (Fig.
[94]3f). In CC, we observed ER-mitochondrion membrane contact site,
Golgi-associated vesicle, multivesicular body membrane (Fig. [95]3g).
In MF, cation transmembrane transporter activity, mitogen-activated
protein kinase kinase binding (Fig. [96]3h). The abundant presence of
pathways closely related to EVs in the GO functional enrichment
analysis partially explains the relationship between tumor growth and
EVs function in the AH group (Supplementary Table [97]3).
Lipid peroxidation is closely related to the progression of NSCLC
Metabolic transformation is a distinguishing feature of cancer, and the
metabolism of cancer is governed by inherent cellular factors and the
availability of metabolites within the TME [[98]30]. In this study, a
UPLC-Q/TOF-MS-based metabolomics approach was used to systematically
evaluate metabolic transformation in tumor. Based on the statistical
results from UPLC-Q/TOF-MS, the differential metabolites with a
p < 0.05 (see Supplementary Tables [99]4–[100]7) were subjected to
pathway analysis through the MetaboAnalyst 5.0 website. The results
revealed a significant enrichment in the biosynthesis of unsaturated
fatty acids in the tumor tissues of the AH group (Fig. [101]4a,
Supplymental Fig. [102]1a, b).
Fig. 4. Reduced levels of lipid peroxidation product 4-HNE in mixed-cell
formed tumors.
[103]Fig. 4
[104]Open in a new tab
a Histogram representation of metabolism pathway enrichment derived
from differential metabolites between two groups. The top 8 pathways
are listed on the right. Biosynthesis of unsaturated fatty acids
changed most significantly. b Shotgun Lipidomics analysis of lipid
extracts of tumor tissues from nude mice (n = 11) implanted by A549
cells (gray bar), H1299 cells (blue bar) and AH cells (red bar) groups
was conducted by using multi-dimensional mass spectrometry-based
shotgun lipidomics, with data analyzed by student’s unpaired t-tests,
where *p < 0.05, **p < 0.01 versus A549 group. c Shotgun lipidomics
analysis of HNE species in lipid extracts from tumor tissues in nude
mice which were implanted with A549 cells, H1299 cells, and AH cells
groups. With data analyzed by student’s unpaired t-tests, where
*p < 0.05 versus AH group. d Venn diagram depicting the commonality
between genes differentially expressed in AH cells and genes associated
with HNE metabolism, identifying 20 genes shared between the two
datasets. e Hierarchical clustering heatmap illustrating expression
patterns of the 20 genes set among A549, H1299 and AH cells. f
Validation of 20 genes against TCGA LUAD data via GEPIA; eight of the
20 overlapping genes showed significant correlation with NSCLC tumor,
validating the reliability of the study findings. (*p < 0.01). g
Overall survival analyses of genes (CCNB1, QPCT, CDK5R1, PDPK1, APP,
PTPN11, NR3C2, and IL6ST) via Kmplot. p < 0.05 was considered
statistically significant.
To identify the specific changes in lipid metabolites in the tumor,
shotgun lipidomics was employed for the quantitative analysis of
lipidomes in the tumor. Shotgun lipidomics analysis revealed that in
the lipid extracts from tumor tissues of the AH group, the levels of
sphingomyelin (SM) and phosphatidylcholine (PC) remained relatively
stable; however, there was an increase in the content of
phosphatidylinositol (PI) and ceramide (CER), while the levels of
phosphatidylethanolamine (PE) and HNE decreased (Fig. [105]4b). Among
these lipid metabolites, lipid peroxidation products of the HNE class
have captured our attention. Compared to A549 tumors, the content of
HNE was significantly reduced in H1299 tumors and further decreased in
AH tumors. The results indicate that the level of HNE is inversely
proportional to tumor growth rate (Fig. [106]4b). We conducted a
precise analysis of the HNE compounds, and the results showed that the
levels of 4-HNE, 4-hydroxy-dodecatrienal (4-HDTE),
4-hydroxy-2E,6Z-dodecadienal (4-HDDE) were the lowest in the tumors of
the AH group (Fig. [107]4c). Lipid peroxidation initiates the formation
of various reactive carbonyl compounds (RCCs), including HNE [[108]31].
Briefly, 4-HNE, is generated by peroxidation of n-6 PUFAs, such as
arachidonic, linoleic. 4-HDDE is exclusively produced from
12-lipxoygenase metabolites of arachidonic acid. 4-hydroxy-2E-hexenal
(4-HHE) is the peroxidative product of n-3 PUFAs. Other HNE species,
e.g., 4-hydroxynondienal (4-HNDE) and 4-HDTE can also be produced
through peroxidation of PUFAs [[109]32]. 4-HNE and 4-HDDE are not only
reduced in H1299 group tumors, but are further decreased in AH group
tumors, suggesting that the peroxidation of arachidonic acid is
involved in regulating tumor growth.
To identify genes associated with HNE production in AH tumors, we
conducted a search for the canonical SMILES structural formulae of HNE
using PubChem. Both the STITCH website and the SwissTargetPrediction
website were utilized to screen for datasets with target prediction
capabilities. As a result, we obtained 410 target genes that are
implicated in the regulation of HNE. We conducted a venn analysis
between AH group’s differentially expressed genes (440 co-up-regulated
and 766 co-down-regulated) and 410 HNE regulatory genes from these
sites, identifying 20 shared genes (Fig. [110]4d). A heatmap analysis
was conducted utilizing OmicStudio tools to illustrate the expression
patterns of these 20 genes in A549, H1299, and AH group tumors (Fig.
[111]4e).
Lung adenocarcinoma (LUAD) is the histological type of NSCLC. We
analyzed the data of LUAD from the TCGA database on the GEPIA website
for the aforementioned 20 genes. The results showed that among these
genes, 8 genes exhibited statistically significant differential
expression in NSCLC (Fig. [112]4f). Subsequently, we conducted survival
analysis on these eight genes (Fig. [113]4g). The overall survival
analysis by Kmplot indicated that high expression of CCNB1 and CDK5R1
in NSCLC cancer tissues is associated with poor prognosis in patients,
while high expression of PDPK1, PTPN11, NR3C2 and IL6ST in NSCLC cancer
tissues is associated with improved prognosis in patients.
The levels of 4-HNE and FOXO4 are reduced in AH group tumor and NSCLC samples
To investigate the relationship between the 4-HNE and tumor growth, we
analy association between the target genes of HNE and the 1206 genes
(440 co-upregulated genes and 766 co-downregulated genes) by the STRING
database. The interaction map of top 57 ranked proteins encoded by the
genes were selected to construct a protein-protein interaction (PPI)
network which involved in the regulation of HNE (Fig. [114]5a). Target
genes that are highly interconnected with nodes in a module have been
considered as functionally significant. Furthermore, the functional
KEGG pathways of the 57 genes were explored using the DAVID online
database, with the FOXO signaling pathway ranking first (Fig. [115]5b).
We performed RT-PCR analysis on FOXO4 genes and found that FOXO4
expression was significantly downregulated in tumor tissues which were
inoculated with AH cells (Fig. [116]5c). Meanwhile, when A549, H1299
and AH cells were cultured in vitro, FOXO4 mRNA expression was also
significantly downregulated in AH cells (Fig. [117]5d).
Immunohistochemistry (IHC) results showed that compared to A549 group
tumors, not only was the expression of FOXO4 and 4-HNE reduced in H1299
group tumors, but it was further decreased in AH group tumors (Fig.
[118]5e–g). The hematoxylin and eosin (H&E) staining of tumor tissues
showed that A549 group tumor cells had regular morphology with clear
cell boundaries. H1299 group tumor cells exhibited irregular
morphology, yet their cell boundaries were still relatively clear. In
the AH group tumors, however, there were many cells with indistinct
cell boundaries, which may be associated with the abundant formation of
EVs among them (Fig. [119]5h).
Fig. 5. Decreased 4-HNE and FOXO4 levels in tumor tissues of the AH group and
in NSCLC samples.
[120]Fig. 5
[121]Open in a new tab
a Protein-protein interaction (PPI) network illustrating connections
between 58 proteins implicated in the regulation of HNE metabolism. b
KEGG pathway analysis of 57 genes, conducted using the DAVID online
database. c The relative mRNA expression levels of FOXO4 in tumor
tissues inoculated with A549, H1299, and AH cells were quantified using
RT-qPCR (*p < 0.05 versus A549 group). d Evaluation of the relative
mRNA expression levels of FOXO4 in A549, H1299, and AH cells by RT-qPCR
(*p < 0.05 versus A549 group, ^#p < 0.05 versus H1299 group). e
Immunohistochemical staining for 4-HNE and FOXO4 in tumor tissues, with
representative images captured at 40× magnification. f, g Quantitative
analysis of the stained positive area per field conducted using ImageJ
software (NIH), with data presented as the mean of 9 fields ±SD (n = 3)
and analyzed by one-way ANOVA (*p < 0.05 versus A549 group, ^#p < 0.05
versus H1299 group). h Histopathological examination of mouse tumor
tissues using H&E staining. Scale bar = 100 µm. i FOXO4 gene expression
validated in NSCLC versus normal tissue using the [122]GSE21933
dataset, showing significantly reduced mRNA levels in NSCLC
(****p < 0.0001). j Confirmation of FOXO4 gene expression levels using
TCGA LUAD data available in GEPIA. k Validation of FOXO4 protein
expression in LUAD versus normal tissue using IHC data from The Human
Protein Atlas.
To investigate the expression of FOXO4 in NSCLC tumors, we analyzed the
expression of FOXO4 from the GEO database [123]GSE21933, and the
results showed a significant decrease in FOXO4 mRNA in NSCLC tumors
(Fig. [124]5i). We further analyzed the TCGA data and found the results
is consistent (Fig. [125]5j). Furthermore, IHC staining data from the
Human Protein Atlas database corroborate that FOXO4 protein expression
in NSCLC tumors aligns with the transcriptional levels of FOXO4 in
these tumors (Fig. [126]5k).
4-HNE and FOXO4 jointly reduce the formation of EVs and inhibit the growth
and migration of co-culture lung cancer cells
In this section, we explored the mutual regulation of FOXO4 and 4-HNE
and examined their impacts on tumor cell proliferation, migration, and
EVs formation. Colony formation assay results showed that compared to
individual A549 and H1299 cells, the number of colonies significantly
increased in cells co-cultured with both A549 and H1299 (Fig. [127]6a).
The expression of FOXO4 and 4-HNE was significantly reduced in
co-cultured AH cells (Fig. [128]6b), To assess the impact of 4-HNE on
EVs formation, we exposed AH cells to varying concentrations of 4-HNE
and subsequently conducted SEM observations. The results demonstrated
that as the concentration of 4-HNE increased, there was a corresponding
decrease in the number of EVs on the surface of AH cells (Fig.
[129]6c). Concurrently, the results from the colony formation assay and
lipofectamine transfection experiments demonstrated that with
increasing concentrations of 4-HNE, there was a significant decrease in
both colony formation capability (Fig. [130]6d) and transfection
efficiency (Fig. [131]6e, [132]f). Cell scratch assay demonstrated that
with increasing concentrations of 4-HNE, there was a notable decrease
in the migration (Fig. [133]6g, [134]h). To further investigate the
potential relationship between 4-HNE and FOXO4, a dual-luciferase
reporter assay revealed that the transcriptional activity of FOXO4
enhanced in correlation with the rising concentrations of 4-HNE (Fig.
[135]6i). Additionally, RT-qPCR results indicated that the mRNA levels
of FOXO4 increased with increasing concentrations of 4-HNE (Fig.
[136]6j). A dose-dependent increase in the protein expression levels of
FOXO4 was also observed when adding 4-HNE (Fig. [137]6k).
Fig. 6. Impact of 4-HNE and FOXO4 on EV formation and the oncogenic
attributes of co-cultured lung cancer cells.
[138]Fig. 6
[139]Open in a new tab
a Comparative analysis of colony formation in A549, H1299, and AH cell
lines. b Quantification and relative expression levels of FOXO4 and
4-HNE proteins in A549, H1299, and AH cells by Western Blot Analysis. c
The cell surface morphology of AH cells was observed by SEM after
treatment with different concentrations of 4-HNE. d Colony formation
post-4-HNE treatment: analysis of colony formation in AH cells across a
range of 4-HNE concentrations (0, 2.5, 5, 10, 20, and 30 μM). e GFP
expression in AH cells treatment with 4-HNE (0, 5, 10, and 30 μM) and
subsequent transfected with pEGFP-C1 vector. Imaging at 100×
magnification. f Quantitative analysis of the percentage of
GFP-positive cells: statistical assessment across different treatment
groups using one-way ANOVA. *p < 0.05 versus 10 μM group, ^#p < 0.05
versus 30 μM group. g, h Cell scratch assay was used to determine the
migration of AH cells treated with 4-HNE (0, 5, 10 and 30 μM) for 24 h.
Statistical analysis of the migration rate in each group was performed
using one-way analysis of variance (*p < 0.05 versus 5 μM group,
^#p < 0.05 versus 30 μM group). i Luciferase reporter assay:
transfection of FOXO4 expression plasmids and corresponding luciferase
reporter vectors into 293 T cells, followed by 4-HNE treatment (0, 5,
10, 20, and 30 μM). Luciferase activity measured at 20 h
post-treatment. Results are from three independent experiments; bar
graphs represent mean ± SD. Significance marked as *p < 0.05 versus
0 μM group, ^#p < 0.05 versus 5 μM group, ^p < 0.05 versus 10 μM group,
^+p < 0.05 versus 20 μM group. j The mRNA expression of FOXO4 in AH
cells treated with 4-HNE (0, 2.5, 5, 10, 20, and 30 μM) were detected
by RT-qPCR (*p < 0.05 versus 2.5 μM group, ^#p < 0.05 versus 20 μM
group, ^p < 0.05 versus 30 μM group). k Analysis of FOXO4 protein
levels in AH cells treated with 4-HNE (0, 2.5, 5, 10, 20, and 30 μM) by
Western Blot. l The expression of 4-HNE in AH cells which overexpressed
FOXO4 was detected by western-blot analysis. m Comparative analysis of
colony formation in AH cell lines. n Morphological examination of AH
cells post-transfection with empty vector (EV) or FOXO4 vector by SEM.
Scale bar = 10 μm. o A549 cells were transfected with three different
FOXO4-targeted shRNAs, and western-blot analysis was used to evaluate
the silencing efficiency of each shRNA. p Western-blot analysis
assessed the expression levels of 4-HNE in A549 cells following FOXO4
silencing. q The impact of FOXO4 silencing on colony formation was
examined in the A549 cell line. r, s The migration rate of A549 cells
with silenced FOXO4 or not were assessed using a cell scratch assay.
One-way ANOVA was employed to analyze the migration rates across
different groups.
To further investigate the role of FOXO4, we overexpressed FOXO4 in AH
cells. The results indicated an increase in 4-HNE protein levels (Fig.
[140]6l) and a reduction in colony formation in the FOXO4
overexpression group (Fig. [141]6m). Additionally, to assess the impact
of FOXO4 on EVs formation, we transfected AH cells with flag-FOXO4
expression plasmid and observed the EVs using scanning SEM method. SEM
images revealed a decrease in the number of EVs in cells overexpressing
FOXO4 (Fig. [142]6n). Given the significant reduction in FOXO4
expression in AH cells and its highest expression in A549 cells, we
performed a knockdown of FOXO4 in A549 cells by using shRNA method. We
initially screened for the most effective construction plasmid (Fig.
[143]6o) and subsequently conducted Western blot analysis, colony
formation assays, and scratch assays. The results demonstrated that
FOXO4 knockdown led to a decrease in 4-HNE levels (Fig. [144]6p), an
increase in the number of cell colonies (Fig. [145]6q), and enhanced
cell migration rates (Fig. [146]6r, s).
Discussion
In the past decade, EVs have emerged not only as important mediators of
intercellular communication, but also as regulators of the
microenvironment, playing a crucial role in maintaining homeostasis and
influencing disease pathogenesis, including cancer metastasis
[[147]33]. There is a potential correlation between the invasiveness of
NSCLC and the respective abilities of their EVs to induce cancerous
phenotype [[148]34]. Tumor-derived EVs promote cancer progression
through changes in epithelial/endothelial barriers and immune
regulation and includes the formation of pre-metastatic niches in
distant sites. For instance, EVs from NSCLC cell lines (Calu6 and H358
cells) notably increased invasion and disrupted an epithelial barrier
[[149]35]. EVs from NSCLC also can expedite angiogenesis and tumor
growth through a TGFβ1-dependent pathway [[150]36].
We found the more EVs on the cell surface, the higher the efficiency of
the cell in accepting liposome-transfected GFP vectors (Fig. [151]1a).
When the mice inoculated with 95D which have more EVs exhibited
significantly faster tumor growth (Fig. [152]1e). Cancer-derived EVs
facilitate bi-directional communication between cancer cells and their
surroundings that shape TME and contribute to cancer progression
[[153]37, [154]38]. EVs provide a critical link between primary tumors
and the lymphatic inflammatory microenvironment, tumor-derived EVs have
been demonstrated to disseminate rapidly through the lymphatic system
into regional lymph nodes, particularly during infection [[155]39].
Research indicates that EVs contribute to the establishment of a
pre-metastatic niche--a conducive microenvironment within target organs
that supports neoplastic implantation [[156]40–[157]42]. In this study,
A549 and H1299 cells were co-cultured to simulate a more realistic TME.
When two different cell lines are co-cultured, is there a promotion of
their respective cell vitality through the exchange of EVs? We found
the co-cultured cells exhibited faster growth rates and an increased
production of EVs (Fig. [158]2a, b). The efficiency of lipid
transfection increases with the duration of cell co-culture (Fig.
[159]2c). In the tumor-forming experiment, we also observed that tumors
formed from mixed cell inoculation exhibited the largest volume (Fig.
[160]3b). Through metabolomic analysis, we found that the contents of
lipid peroxidation products (4-HNE, 4-HDTE, 4-HDDE) (Fig. [161]4c) and
FOXO4 is significantly suppressed (Fig. [162]5c) in tumors of the AH
group.
Oxidative stress is an intricate cellular state that governs the levels
and content of released EVs. Cells release EVs to disseminate signaling
molecules and respond to stress stimuli [[163]9]. Since the early
discovery of HNE’s ability to regulate the growth of malignant cells,
HNE has been described as a biphasic growth factor, being stimulatory
at low doses and inhibitory/cytotoxic at high doses [[164]43].
Prooxidants would lead to the formation of lipid-peroxyl radicals
(ROO•), lipid peroxides (ROOH), and reactive aldehydes like 4-HNE and
malondialdehyde (MDA) [[165]44]. When lipid peroxidation occurs, it
alters the physical properties of the membrane, affecting phospholipid
dynamics, membrane shedding, fluidity, and permeability [[166]45].
4-HDTE and 4-HDDE have structures like 4-HNE, all of them are the
products of lipid peroxidation induced by oxidative stress. 4-HNE can
form covalent adducts with proteins, leading to structural changes in
proteins, so it has been described as a ‘second messenger’ in various
cellular signaling pathways [[167]45, [168]46]. In hepatocellular
carcinoma, the expression of 4-HNE is stronger in adjacent tissues than
in the tumor. Similarly, stronger expression of 4-HNE in adjacent
tissues has also been observed in metastatic lung cancer, supporting
the hypothesis that non-malignant cells near the cancer produce 4-HNE
to protect themselves from the invading cancer cell [[169]47, [170]48].
Recently, 4-HNE accumulation has been linked to ferroptosis,
characterized by increased intracellular redox-active iron and impaired
lipid peroxide repair capacity [[171]49, [172]50]. In this study, the
significant reduction of lipid peroxidation products such as 4-HNE,
4-HDTE and 4-HDDE (Fig. [173]4c) in the AH group tumors suggests that
inhibiting lipid peroxidation contributes to the formation of EVs and
the growth of tumors.
By analyzing differentially expressed genes which are associated with
the generation of HNEs in AH group tumor, FOXO4 as a target has caught
our attention. IHC results reveal that both FOXO4 and 4-HNE exhibit the
lowest expression in AH group (Fig. [174]5e). FOXOs are generally
considered tumor suppressors due to their well-known functions in cell
cycle arrest, apoptosis, DNA damage repair, and scavenging of ROS
[[175]22]. Several studies have shown an association between reduced
FOXO4 expression and heightened cancer development. Low expression of
the FOXO4 contribute to the epithelial-mesenchymal transition (EMT) in
NSCLC and miR-150 promotes cellular metastasis in NSCLC by targeting
FOXO4 [[176]23, [177]51]. FOXO4 was also downregulated in colorectal
cancer tissues compared with normal tissues. Overexpressed FOXO4
suppressed EMT and the migration of colorectal cancer cell lines
[[178]24]. Exosomal miR-128-3p overexpression could downregulate the
expression of FOXO4 in colorectal cancer cells, which led to EMT
[[179]52]. We analyzed data from the GEO database and also found that
FOXO4 is significantly downregulated in NSCLC cancer tissues (Fig.
[180]5i). Low expression of FOXO4 is associated with worse prognosis in
NSCLC cancer patients.
As is well known, the rapid growth of tumors often leads to the
formation of a hypoxic microenvironment, subsequently triggering
oxidative stress reactions. EVs released under oxidative stress contain
antioxidant molecules that regulate oxidative stress reactions in
target cells, thereby protecting cells from further damage [[181]53,
[182]54]. The abundant generation of EVs may be a crucial mechanism
ensuring rapid tumor growth. In this study, when 4-HNE is added to
cells or when FOXO4 is overexpressed, the number of EVs on the cell
surface significantly decreased. Cellular experiments showed that 4-HNE
addition to cultured cells increases FOXO4 expression and
transcriptional activity. In line with this, FOXO4 overexpression
elevated 4-HNE protein levels and reducted colony formation.
Furthermore, FOXO4 knockdown decreased 4-HNE levels, increased colony
formation and enhanced cell migration rates (Fig. [183]6). FOXO4 has
been found to cause cell cycle arrest in number of studies [[184]55,
[185]56]. Therefore, maintaining a low content of 4-HNE and FOXO4 in
tumor tissues may be an important way to sustain tumor rapid growth.
In summary, we report when two different NSCLC cells are co-cultured,
they exchange information through EVs, which promotes the deterioration
of the cells. During this process, the levels of both 4-HNE and FOXO4
are downregulated. The activity of FOXO4 is positively correlated with
the levels of 4-HNE. Both 4-HNE and FOXO4 can inhibit the formation of
EVs. Therefore, modulating the production of 4-HNE and the activity of
FOXO4 may be an effective strategy for the treatment of NSCLC.
Materials and methods
Chemical and biochemical materials
DMEM (C11995500BT, Gibco), FBS (086-150, Wisent corporation).
Lipofectamine 2000 (11668019, ThermoFisherScientific), flag-FOXO4
(17549, Addgene), Foxo NLuc luciferase reporter (178318, Addgene), pRL
Renilla Luciferase Control Reporter Vector (E2231, Promega),
Dual-Luciferase® reporter assay system (E1910, Promega). PrimeScript™
RT Master Mix (Perfect Real Time) (RR036A, TaKaRa), TB Green^®
PremixExTaq™ (Tli RNaseHPlus) (RR420A, TaKaRa). 4-HNE (HY-113466,
MedchemExpress), Rabbit Anti-4 Hydroxynonenal antibody (bs-6313R, Bioss
Antibodies). FOXO4 Polvclonal antibody (21535-1-AP, Proteintech),
β-actin Antibody (C4) (sc-47778, Santa cruz), IRDye 800CW Goat
anti-Rabbit IgG (925-32211, LICOR), IRDye 680RD Goat anti-Mouse IgG
(H + L) (926–68070, LICOR).
Cell culture
HCC827, NCI-H460, A549, NCI-H1299, NCI-H838 (all human non-small cell
lung carcinoma cells) were obtained from ATCC, and 95D (highly
metastatic lung cancer cells) were obtained from our laboratory backup.
These six cell lines were maintained in DMEM supplemented with 10% FBS,
incubated at 37 °C in a 5% CO[2] environment. For co-culturing, equal
numbers of cells were combined and cultured. AH cells used in
experiments were co-cultured for 2 weeks. All cells were regularly
tested for mycoplasma cytoplasmic contamination.
Cell transfection and fluorescence observation
Different cells were seeded in 6-well plates at 2.5 × 10^5 cells per
well. Transfection was performed with PEGFP-C1 vector using
Lipofectamine 2000, following the manufacturer’s instructions. 36 h
post-transfection, DAPI was used for nuclear staining. Fluorescence
microscopy imaging was conducted using an Axio Observer A1 inverted
microscope (AX10, Zeiss). The efficiency of liposome transfection was
determined by calculating the proportion of cells emitting green
fluorescence in the same number of cells with using ImageJ. Results are
expressed as mean ± SD from three independent experiments [[186]39].
The shRNA plasmid targeting FOXO4 was constructed using the
PGMLV-hU6-MCS-CMV-ZsGreen1-PGK-Puro-WPRE vector (2494-PGMLV- SC5)
provided by Jiman Biotechnology Company. Based on the FOXO4 gene
sequence, three appropriate target sequences for shRNA were selected
(Table [187]1). The corresponding shRNA oligonucleotides (Table [188]2)
were synthesized and then three shRNA plasmids were constructed and
packaged into lentiviruses using the GM easyTM lentivirus packaging kit
(GMeasy-10, Genomeditech), following the manufacturer’s instructions.
Cells infected with these lentiviruses were subsequently detected using
Western blot assays to identify those with the most effective knockdown
for use in further experiments. Specific target sequences and the
synthetic shRNA oligo sequences are detailed in Tables [189]1 and
[190]2.
Table 1.
The shRNA sequence for FOXO4 target.
NO. TargetSeq
NC TTCTCCGAACGTGTCACGT
shRNA1250 ACCGTGAAGAAGCCGATATGT
shRNA1914 TCAGGATCTAGATCTTGATAT
shRNA2318 CACTTAGGCTTTGTAGCAAGA
[191]Open in a new tab
Table 2.
The shRNA oligo sequence for constructing plasmid.
Oligo name Oligomeric single-stranded DNA sequence 5 ‘to 3'
Primer-NC-T
GATCTGTTCTCCGAACGTGTCACGTTTCAAGAGAACGTGACACGTTCGGAGAATTTTTTC
Primer-NC-B
AATTGAAAAAATTCTCCGAACGTGTCACGTTCTCTTGAAACGTGACACGTTCGGAGAACA
Primer-T1 GATCCACCGTGAAGAAGCCGATATGTCTCGAGACATATCGGCTTCTTCACGGTTTTTTT
Primer-B1 AATTAAAAAAACCGTGAAGAAGCCGATATGTCTCGAGACATATCGGCTTCTTCACGGTG
Primer-T2 GATCCGTCAGGATCTAGATCTTGATATCTCGAGATATCAAGATCTAGATCCTGATTTTTT
Primer-B2 AATTAAAAAATCAGGATCTAGATCTTGATATCTCGAGATATCAAGATCTAGATCCTGACG
Primer-T3 GATCCGCACTTAGGCTTTGTAGCAAGACTCGAGTCTTGCTACAAAGCCTAAGTGTTTTTT
Primer-B3 AATTAAAAAACACTTAGGCTTTGTAGCAAGACTCGAGTCTTGCTACAAAGCCTAAGTGCG
[192]Open in a new tab
Scanning electron microscope (SEM)
Cell samples were washed twice with PBS and fixed in 2.5%
glutaraldehyde at 4 °C overnight to preserve morphology. They were then
rinsed thrice with deionized water for 10 min each at room temperature.
Gradual dehydration was performed to replace cellular water content
with ethanol, which has a lower surface tension than water, preventing
deformation in the SEM vacuum chamber. This dehydration process
involved increasing ethanol concentrations: 50%, 70%, 90%, and 100%
(v/v) at room temperature. Then samples were processed in a 50%
tert-butyl alcohol and 50% ethanol mixture for 10 min, followed by 100%
tert-butyl alcohol, and then cooled to 4 °C. The final step involved
drying the samples in a vacuum before SEM observation using a Hitachi
SU8010.
Cell scratch assay
Cells were cultured in 6-well plates to approximately 90% confluence. A
20 μL sterile pipette tip was used to create a scratch in the cell
monolayers. After scratching, the cells were washed with PBS and then
incubated in DMEM containing 1% FBS. At 12, 24, and 36 h post-scratch,
images of the scratch area were captured using an inverted fluorescence
microscope (Zeiss AX10). Wound area calculated by manually tracing the
cell-free area in captured images using the ImageJ. Under normal
conditions, the wound area will decrease over time. The migration rate
can be expressed as the percentage of area reduction or wound closure.
The closure percentage will increase as cells migrate over time
[[193]57]:
[MATH: Wound
Closure%:{(At=0h−At=∆h)/At=0h}×100% :MATH]
A[t=0h] is the area of the wound measured immediately after
scrating(t = 0 h)A[t=∆h] is the area of the wound measured h hours
after the scratch is performed
Tumor formation experiment in nude mice
11-week-old C57BL/6J female nude mice were acquired from the Zhejiang
Chinese Medical University Animal Center. All procedures complied with
the ethical guidelines of the Zhejiang Chinese Medical University’s
Committee for Experimental Animal Use. All nude mouse experiments were
used by single blind method. The number of mice used in mouse
tumorigenesis experiments depends on the experimental design, study
purpose, and statistical power analysis. In general, in order to ensure
the statistical significance and repeatability of experimental results,
at least 5 to 10 mice are required in each experimental group. Refer to
ARRIVE Guide [[194]58], the number of mice selected by us all meet the
statistical requirements of mouse tumor formation test.
The first group consists of 26 nude mice randomly divided into 2 groups
by paired comparison method, with 13 mice in each group, inoculated
with HCC827 and 95D cells, respectively. The second group consists of
44 nude mice randomly divided into 4 groups by randomized block method,
with 11 mice in each group, inoculated with A549 cells, H1299 cells,
and AH cells or saline solution. Each mouse in the experimental groups
received a subcutaneous injection of 0.2 mL saline solution containing
5 × 10^6 cells in the flank. Control mice received a 0.2 mL saline
solution injection without cells. The mice were housed at 22–25 °C and
60–70% humidity, with ad libitum access to water and food.
After 30 days, mice from each group were euthanized. Tumors were rinsed
with PBS until blood-free and stored at −80 °C. The tissues underwent
UPLC-Q/TOF-MS analysis, lipidomics analyses, mRNA microarray analysis
and histopathological evaluation.
UPLC-Q/TOF-MS analysis
6 transplanted tumor tissue were randomly selected in A549, H1299, and
AH cells groups for the untargeted metabolomics analysis. 10 mg of
transplanted tumor was added to 20 μL ice ultrapure water and 180 μL
mixture of 20% methanol solution / 80% acetonitrile, vortexed and
shaken, and left to stand in room temperature for 10 min. Then
centrifuged (14000 r/min for 20 min at 4 °C), and the supernatant was
collected to desiccation and diluted with mixture of ultrapure water
and methanol solution/acetonitrile (2/8) in a ratio of 1:1. After that,
the supernatant was collected and centrifuged for 20 min at
14,000 r/min and 4 °C to obtain supernatant of a tissue homogenate for
untargeted metabolomic analysis using UPLC-Q/TOF-MS.All samples were
used as the quality control (QC) samples. The specifc chromatographic
and mass spectrometric conditions and data processing and analysis were
performed according to the previously published article [[195]59].
Here, we use the Gradient which consisted of 95% eluent B, 0–1 min;
95–1% eluent B, 1–20 min; 1% eluent B, 20–23 min. Univariate
statistical analysis with p < 0.05 was used to screen metabolites with
significant differences in A549 group, H1299 group, and AH group, and
The MetDNA website ([196]http://metdna.zhulab.cn), OSI/SMMS software
([197]http://www.5omics.com) and the online HMDB
([198]http://www.hmdb.ca/), METLIN ([199]http://metlin.scripps.edu/),
Lipid Maps ([200]www.lipidmaps.org) databases were used for substance
identification (ppm < 5). Metabolite pathway analysis was performed
using MetaboAnalyst 5.0 ([201]https://www.metaboanalyst.ca).
Shotgun lipidomics analysis of tumor tissues
For shotgun lipidomic analysis, tumor tissues were examined using a
triple-quadrupole mass spectrometer (Thermo TSQ Quantiva) equipped with
an automated nanospray ion source (TriVersa NanoMate, Advion Bioscience
Ltd.). The testing of the samples was carried out by our platform’s
laboratory technicians who specialize in operating this instrument.
Briefly, a revised protocol was used for lipid extraction from tumor
tissues [[202]60, [203]61]. Lipid extracts were resuspended in 1000 μL
of chloroform/methanol (1:1)/mg protein and stored at −20 °C for mass
spectrometry (MS) analysis [[204]62]. Derivatization of HNE was
performed followed previously established methods [[205]63]. Lipid
species were identified through multi-dimensional MS and mass spectra
were acquired using custom sequence subroutines in Xcalibur software
and [[206]64]. Data were presented as mean ± standard error of the mean
(SEM). Statistical differences between groups were assessed using
Student’s unpaired t-tests. Analysis of HNE was completed within 7
days, and other analyses within 2 weeks.
mRNA microarray analysis
Total RNA from A549, H1299, and AH group tumors was extracted using
Trizol. RNA quality and quantity were determined using a NanoDrop
ND-1000 spectrophotometer, and integrity was verified via standard
denaturing agarose gel electrophoresis. The samples were processed at
Kangchen Bio-tech company by using the Agilent Human 4 × 44K chip
array. Differential gene expression analysis was performed using Fold
Change filtering. The array data is accessible under GEO accession
number [207]GSE124112.
Upregulated and downregulated genes in AH vs A549 and AH vs H1299 were
collected, using a filter of |FC | > 1.2 and p < 0.05. Venn analysis
identified overlap genes that were either upregulated or downregulated.
To explore the function of intersecting genes, GO enrichment analysis
and KEGG pathway analysis were performed using the DAVID online
database. The gene lists were uploaded for analysis, yielding results
in biological process (BP), cellular component (CC), molecular function
(MF), and KEGG pathways.
Bioinformatics analysis
Prediction of HNE-regulated target genes: HNE is inputted into the
PubChem website to obtain the standardized SMILES structure formula.
STITCH 5.0 predictions classify manually curated information and
experimentally validated protein-chemical interactions, and in this
study, we considered chemical interactions with a STITCH confidence
score of ≥0.4 (ref. [[208]65]). Swiss Target Prediction is a web server
for identifying biological targets of bioactive small molecules,
combining 2D and 3D similarity metrics to predict the top 15 targets
[[209]66]. We entered HNE’s SMILES structure formula into the STITCH
website and SwissTargetPrediction website to search for protein
information related to HNE regulation.
Heatmap and PPI Network Construction: Gene expression in tumor tissues
was analyzed using OmicStudio’s heatmap tool. The STRING database is an
online resource whose main function is to construct functional protein
association networks [[210]67]. Differentially expressed genes from AH
tumors were entered into the STRING database to identify those most
closely associated with direct regulation of the HNE gene. Interactions
with scores >0.40 were considered significant, leading to the
identification of 58 core targets. The PPI network for these 58 target
genes was constructed using Cytoscape software, where nodes represent
genes and edges represent protein interactions.
Gene expression and survival correlation analysis in tumors: GEPIA2 is
a Web server for analyzing the RNA sequencing expression data of 483
NSCLC and 59 normal samples from the TCGA and the TCGA projects, using
a standard processing pipeline. Eight target genes (p < 0.05) were
chosen as the candidates for further analysis. Survival analysis was
conducted using the online database Kmplot, focusing on patient
survival percentages over time. Patients were classified based on
k-means clustering, and the analysis was executed using the R package
“survival”. The log-rank test assessed statistical differences between
survival curves, with p < 0.05 indicating statistical significance. The
[211]GSE21933 dataset, which includes gene expression data from tumor
of 21 NSCLC patients and normal samples, was retrieved from the GEO
database. GraphPad Prism 8 was used to analyze and identify
differentially expressed genes through one-way ANOVA. The
translational-level validation of genes was carried out using The Human
Protein Atlas database. Network Pharmacology database informationare
detailed in Table [212]3.
Table 3.
Network Pharmacology database information table.
Database URL
PubChem [213]https://pubchem.ncbi.nlm.nih.gov/
Stitch [214]http://stitch.embl.de
Swiss Target Prediction [215]http://swisstargetprediction.ch
OmicStudio’s heatmap [216]https://www.omicstudio.cn/tool
String [217]https://cn.string-db.org/
GEPIA2 [218]http://gepia.cancer-pku.cn/
Kmplot [219]http://kmplot.com/analysis/
GEO [220]http://www.ncbi.nlm.nih.gov/geo
DAVID [221]https://david.ncifcrf.gov/summary.jsp
Human Protein Atlas database [222]https://www.proteinatlas.org/
[223]Open in a new tab
Reverse transcription-quantitative PCR (RT-qPCR)
Cells were cultured in 6-well plates and total RNA was extracted using
TRIzol, following the manufacturer’s protocol. After RNA
quantification, reverse transcription was performed using PrimeScript™
RT Master Mix to synthesize cDNA. Target gene quantification was
conducted using TB Green® Premix Ex Taq™ (Tli RNaseH Plus), with GAPDH
serving as the internal control. The relative mRNA expression levels
were calculated using the 2^-ΔΔCT method. Primers for gene
amplification included:
FOXO4-F, 5-GCCAAGACAGAATGCCTCAGGATC-3;
FOXO4-R, 5-GTCCAGTCCCTCGCCCTCATC-3;
GAPDH-F, 5-TGACATCAAGAAGGTGGTGAAGCAG-3;
GAPDH-R, 5-GTGTCGCTGTTGAAGTCAGAGGAG-3.
Histopathology and immunohistochemistry
Tumor tissues were fixed in 4% paraformaldehyde and embedded in
paraffin following standard procedures. Serial sections were prepared
and subjected to H&E staining, as well as IHC. For IHC, primary
antibodies (Rabbit Anti-4-HNE and FOXO4 Polyclonal antibody) were
applied. The staining was developed using DAB substrate solution after
incubation with secondary antibody and biotin-streptavidin HRP
conjugate. Imaging of all samples was performed using a KFBIO digital
white light scanner (KF-PRO-120).
Dual-luciferase reporter assay
293 T cells were seeded in 48-well plates at 0.5 × 10^5 cells per well
and cotransfected with 0.3 μg of firefly luciferase reporter
(Luc-FOXO), 0.3 μg of flag-FOXO4, and 0.03 μg of Renilla luciferase
reporter using Lipofectamine 2000. After 24 h of transfection, cells
were treated with 4-HNE (5, 10, 20, and 30 μM) or left untreated.
Twenty hours post-treatment, cell lysates were prepared for luciferase
reporter activity analysis using the Dual-Luciferase Reporter Assay
System kit. Results are expressed as mean ± SD from three independent
experiments.
Cell colony formation assay
Cells were seeded in 6-well plates at a density of 400 cells per well,
in triplicate. The cells were cultured at 37 °C in a 5% CO[2]
environment for 14 days, with medium changes every 3 days.
Post-incubation, cells were fixed with 4% paraformaldehyde, stained
with 0.5% crystal violet, and cell colony morphologies were assessed.
Western-blotting assay
Cells were lysed using RIPA buffer to extract proteins. Protein
concentrations were determined using the BCA Protein Assay Kit (P0010,
Beyotime). Equal amounts of protein were combined with 2x SDS loading
buffer, heated at 100 °C for 10 min, separated by 10% SDS-PAGE, and
transferred onto PVDF membranes. These membranes were incubated
overnight at 4 °C with primary antibodies (rabbit anti-4-HNE, FOXO4
polyclonal, or β-actin antibody C4), followed by 2 h with corresponding
secondary antibodies at room temperature. Blots were visualized using
an Odyssey scanner (LI-COR), quantification of Western blot signal was
done by densitometry using ImageJ.
Statistical analysis of data
The data shown represent at least three independent experiments and are
expressed as mean ± SEM. Statistical analyses were conducted using
GraphPad Prism 8. p values were calculated using one-way ANOVA and
Student’s unpaired t tests, with a p value of less than 0.05 considered
statistically significant.
Supplementary information
[224]Supplemental Information^ (752KB, doc)
[225]Uncropped western blots^ (773.8KB, pptx)
Acknowledgements