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\begin{document}

\title{The role and significance of SVIL protein in the occurrence and
development of gastric cancer}



\author[1]{Meiqiong Chen}%
\author[1]{Ru Wang}%
\author[1]{Haihong Cui}%
\author[1]{Rongshan Zhang}%
\affil[1]{The 305 Hospital of PLA}%


\vspace{-1em}



  
  \date{June 16, 2024}


\begingroup
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\selectlanguage{english}
\begin{abstract}
Aim: To discuss role and significance of SVIL protein in the occurrence
and development of gastric cancer. Materials and methods: Using GSE84437
as research object and analysis by bioinformatics. In vitro study, after
knockdown SVIL in MGC-803 and SGC-7901, observing cell biological
activities including proliferation, apoptosis, invasion and migration by
MTT, flow cytometry, transwell and wound healing assay. Results: By
bioinformatics analysis, SVIL was closely correlation with gastric
cancer, low expression group was significantly better compared with high
expression groups in survival rate (P<0.001); in cell experiment, with
SVIL knockdown, MGC-803 and SGC-7901 cell proliferation were
significantly depressed with apoptosis significantly increasing
(P<0.001), meanwhile, cells invasion and migration abilities were
significantly inhibited with SVIL knockdown in MGC-803 and SGC-7901 cell
lines (P<0.001). Conclusion: SVIL overexpression might be closely
correlated with gastric cancer development.%
\end{abstract}%



\sloppy


The role and significance of SVIL protein in gastric cancer occurrence
and development

Meiqiong Chen\textsuperscript{1,\#, *}, Ru Wang\textsuperscript{2,\#},
Haihong Cui\textsuperscript{3}, Rongshan Zhang\textsuperscript{1}

\begin{enumerate}
\tightlist
\item
  Department of Pathology, The 305 Hospital of PLA, Beijing ,100017,
  China
\item
  Department of clinical laboratory, The 305 Hospital of PLA, Beijing
  ,100017, China
\item
  Department of Gastroenterology, The 305 Hospital of PLA, Beijing
  ,100017, China
\end{enumerate}

\#: The e qual contribution

*: Corresponding author

Abstract

Aim: To discuss role and significance of SVIL protein in gastric cancer
occurrence and development.

Materials and methods: Using GSE84437 as research object and analysis by
bioinformatics. In vitro study, after knockdown SVIL in MGC-803 and
SGC-7901, observing cell biological activities including proliferation,
apoptosis, invasion and migration by MTT, flow cytometry, transwell and
wound healing assay.

Results: By bioinformatics analysis, SVIL was closely correlation with
gastric cancer, low expression group significantly better in survival
rate (P<0.001); in cell experiment, with SVIL knockdown, MGC-803 and
SGC-7901 cell proliferation were significantly depressed with apoptosis
significantly increasing (P<0.001), meanwhile, cells invasion and
migration abilities were significantly inhibited with SVIL knockdown in
MGC-803 and SGC-7901 (P<0.001).

Conclusion: SVIL overexpression might be closely correlated with gastric
cancer development.

Key words: SVIL; Gastric Cancer; MGC-803; SGC-7901

Running Title: SVIL and gastric cancer

Introduction

Gastric cancer is one of the common tumors of the digestive tract. Its
incidence and mortality remain constantly high, ranking fifth and third
among all tumors, respectively, with a gradual increasing trend in China
as well {[}1{]}. Parthenogenesis of gastric cancer is a multifactorial
process that can be attributed by dietary habits, \emph{Helicobacter
pylori} (HP) infection, genetics, etc.

Patients with early gastric cancer may have no obvious clinical
symptoms, or even are asymptomatic. About \textgreater{}50\% of patients
experience metastasis upon diagnosis. Current therapeutic options for
gastric cancer include chemotherapy, radiotherapy, targeted therapy,
immunotherapy, etc. There is still an unsatisfactory 5-year survival
rate of patients with local advanced and distant metastasis, which is
less than 10\%{[}2{]}. It highlights the significance of effective
molecular marker screening in diagnosis and treatment of gastric cancer.

Supervillin (SVIL) is a myosin II- and Actin-binding peripheral membrane
protein that is generally expressed in human tissues {[}3{]}. Besides
regulating cell-substrate adhesion, cell polarization, cell diffusion
and metastasis, SVIL also involves in cell division, extracellular
matrix degradation, survival signal transduction, Integrin circulation
and other functional activities {[}4{]}. SVIL has also been reported to
participate in liver cancer occurrence and development {[}5, 6{]}.
However, it is still unclear with respect to the expression of SVIL
protein in gastric cancer tissue. In present study, relationships of
SVIL gene expression with the prognosis and clinical pathological
characteristics of gastric cancer were analyzed by sourcing gastric
cancer data from the Gene Expression Omnibus (GEO) database. Meanwhile,
via cell experiment with SVIL knockout, this study observed gastric
cancer cells' biological activity, providing possible references for
further research on SVIL mechanism.

Materials and Methods

Experimental materials

Human gastric cancer SGC-7901 and MGC-801 cells purchased from Cell Bank
of Chinese Academy of Sciences (Shanghai, China). A public gene
expression profiling dataset of GSE84437, sourced from the GEO database
of National Center for Biotechnology Information (NCBI) in United States
(http://www.ncbi.nlm.nih.gov/geo), was collected for data analysis,
including the gene expression profiles of 433 gastric cancer samples.

Bioinformatics analysis

GSE84437 was downloaded from the GEO database, with the expression of
the control gene through the annotation package of the gene platform.
Eligible data were obtained through deletion of missing data, background
correction and log2 conversion for further analysis. Dividing as high-
and low-levels based on median value of SVIL. Based on statistics of
gender, age, T stage and N stage frequency of gastric cancer patients in
each group, relationship between SVIL gene level and clinical symptoms
calculated through Chi-squared test. Furthermore, by analyzing survival
time and survival status of two groups, Kaplan-Meier (KM) survival
analysis was used to compare the overall survival differences between
groups. Univariate and multivariate Cox regression analyses were further
employed to determine the impact of SVIL gene expression on patient
survival prognosis. Differentially expressed genes (\textbar{}Fold
change\textbar{}\textgreater{}1.4-fold, P\textless{}0.05) were screened
in tissues of high- and low-expression groups, with corresponding heat
map plotted at the same time. Furthermore, using the clusterProfiler
package in Bioconductor, this study plotted the enrichment of
differentially expressed genes on the Gene Ontology (GO) and Kyoto
Encyclopedia of Genes and Genomes (KEGG) pathways, with bubble diagram
generated simultaneously.

Cell culture and grouping

SGC-7901 and MGC-803 cells were cultured in DMEM medium containing 10\%
Fetal bovine serum in an incubator (37 , 5\% CO\textsubscript{2}), with
the medium changed every 2 days. When cell confluence reached about 80\%
under the microscope, the cells were digested by trypsin, and then
prepared into single-cell suspension in DMEM medium for passage. The
cells progressed four generations in logarithmic growth phase were
randomly divided into Normal group, si-NC group, and si-SVIL group.
Except for Normal group, si-NC group and si-SVIL group were transfected
with si-negative control and si-SVIL, respectively (Keygentec, Nanjing,
China). Further experiments were continued after 24 h of cell
transfection.

Detection of SVIL gene expression in each group of cells using qRT-PCR

After centrifugation, cells were collected for the extraction of total
RNA via the addition of Trizol. With the measurement of RNA
concentration and purity, the extracted RNA were reversely transcribed
into cDNA by using reverse transcription kit. Using cDNA as a template,
PCR reaction was carried out under the following conditions:
pre-denaturation at 95  for 5 min, denaturation at 95  for 30 s,
annealing at 60  for 30 s, and elongation at 72  for 30 s, with 40
cycles in total. The expression of SVIL was calculated based on the 2
-^^CT method, and the primer sequences are shown in Table 1.

Detection of cell survival rate using MTT assay

The transfected cells were collected and prepared into single-cell
suspension at the density of 5 \selectlanguage{ngerman}×10\textsuperscript{4} /ml using DMEM
medium, after which cells were inoculated on the 96-well plate (200
\selectlanguage{greek}μ\selectlanguage{english}l/well). After 24 h of culture in the incubator, 50 \selectlanguage{greek}μ\selectlanguage{english}l 5 mg/ml of MTT
solution was added into each well for 4 h of further culture. Then, with
the supernatant discarded, 150\selectlanguage{greek}μ\selectlanguage{english}l DMSO was added into each well and mixed
well for 15 min. Finally, the absorbance (A) value was measured using
Microplate Reader at a wavelength of 490nm, and the cell survival rate
was calculated according to the formula of cell survival rate (\%)=(A
value of the experimental group/A value of the control group) \selectlanguage{ngerman}×100\%.

Flow cytometry

Cells in logarithmic growth phase were washed and re-suspend with
pre-cooled PBS solution, and then added with 70\% ethanol pre-cooled in
an ice bath to gently blow evenly, and fix overnight at 4 \selectlanguage{english}. The next
step was centrifugation at 1,000 r/min for 5 min. With repeated washing
with pre-cooled PBS, another centrifugation was performed to precipitate
cells. After the removal of the supernatant, 0.5 mL of propidium iodide
was added to fully shake and mix, followed by a warm bath at 37 \selectlanguage{english} for 30
min, and then placement at 4 \selectlanguage{english}. After filtration with 300-mesh nylon
mesh, samples were loaded for cell apoptosis detection using flow
cytometer.

Wound healing assay

After the digestion of cells in each group with trypsin, cells with
adjusted concentration were inoculated into the 6-well plate. The
optimal cell concentration should be 80\%\textasciitilde{}90\% of growth
on the second day. Sampling of each group was run in triplicate. Cells
were cultured with 1640 medium at 37 \selectlanguage{english} in an incubator containing 5\%
CO\textsubscript{2} until a monolayer of cells was formed. Scratches
were made using the vertical surface of a 100 \selectlanguage{greek}μ\selectlanguage{english}L pipette tip, forming a
cell-free growth area. After washing with serum-free medium for three
times, the scraped cells were scraped, and fresh serum-free medium were
supplemented, with the addition of Mitomycin to inhibit cell division.
The relative distance of the scratching area was observed and measured
under an inverted microscope.

Transwell assay

The diluted Matrigel was placed into the Transwell insert to form
membrane. An amount of 100 \selectlanguage{greek}μ\selectlanguage{english}L of diluted cell solution was inoculated
into the upper chamber, and 500 \selectlanguage{greek}μ\selectlanguage{english}L of culture medium containing 10\%
fetal bovine serum was added to the lower chamber, both of which were
cultured for 36 h in an incubator with 5\% CO\textsubscript{2} at 37 .
After that, the transwell insert was removed and the cells in the upper
layer of the chamber was discarded, followed by cell fixation with 4\%
paraformaldehyde for 10 min, staining with 0.1\% crystal violet, and
drying in the air after washing with PBS solution. Under the light
microscope, 4 high-power fields were selected randomly for cell counting
and averaging.

Western blotting (WB) assay

Cells washed with pre-cooled PBS three times were added with RIPA lysate
to lyse cells, and the supernatant was collected by centrifugation.
After protein concentration measurement using the BCA method, cells with
adjusted protein concentration were added with loading buffer and boiled
for denaturation. Then, 20 \selectlanguage{greek}μ\selectlanguage{english}l of protein sample was added to each well
of concentrated gel, and electrophoresis at 80V was performed until the
protein sample reached the separation gel, followed by electrophoresis
at 120V until the protein sample reached the bottom of the separation
gel. After that, wet transfer was carried out at a constant current of
0.3A for 2 h, and the PVDF membrane was taken out for sealing at room
temperature for 1 h after washing three times with TBST. The primary
antibodies of anti-SVIL (1:1,000) and anti-GAPDH (1:1,000) were added
for incubation overnight at 4 , and the secondary antibody (1:5,000)
was supplemented at room temperature for 1 h of incubation after another
washing with TBST (\selectlanguage{ngerman}×3). Following visualization using ECL, Image J was
used to analyze the grayscale values of the bands. The relative
expression level of the target protein was generated via dividing the
grayscale value of the target protein bands by that of GAPDH bands.

Statistical analysis

SPSS 22.0 statistical software was used for data analysis of this study.
The measurement data were all expressed in Mean±SD, and the comparison
of multivariate measurements was conducted using one-way analysis of
variance. Further pairwise comparison employed LSD-t-test, and the
comparison of two samples applied paired t-test. P\textless{}0.05 meant
that difference was statistically significant.

Results

The relationship between SVIL gene expression and clinical pathological
parameters in gastric cancer patients

For analyzing SVIL gene expression of 433 gastric cancer patients'
tissues, all samples were classified into high-expression group (n=216)
and low-expression group (n=217) based on the median value of SVIL
expression. Statistical analysis showed that the expression level of
SVIL was associated with age (\selectlanguage{greek}χ\selectlanguage{english}\textsuperscript{2}=5.580, P=0.018) and T
staging (\selectlanguage{greek}χ\selectlanguage{english}\textsuperscript{2}=19.800, P\textless{}0.001), but had none
obvious relationship with gender (\selectlanguage{greek}χ\selectlanguage{english}\textsuperscript{2}=0.805, P=0.370)
and N staging (\selectlanguage{greek}χ\selectlanguage{english}\textsuperscript{2}=6.500, P=0.090). There would be a
higher expression level of SVIL gene in patients with increased T
staging, as shown in Table 2.

The relationship between SVIL gene and survival prognosis of gastric
cancer patients

Survival analysis using KM revealed a negative correlation between SVIL
gene expression and patient survival in the dataset. In other words, the
survival time of patients with high expression was significantly lower
than that of patients with low expression (P \textless{} 0.05; Figure
1).

According to Cox regression analysis (Table 3), univariate analysis
indicated that age, T stage, N stage, and SVIL gene expression levels
were closely related to the overall survival of patients. While the
results of multivariate analysis suggested that SVIL gene expression was
an independent risk factor for prognosis in gastric cancer patients
{[}hazard ratio (HR)=1.30, 95\% confidence interval (CI)=1.11
\textasciitilde{} 1.52, P \textless{} 0.001{]}. SVIL can be considered
as a biomarker for predicting the overall survival of gastric cancer
patients.

Screening of SVIL-associated differentially expressed genes

Statistical analysis was conducted on microarray data of 433 samples,
with the screening of 823 differentially expressed genes, including 697
genes with high expression and 126 genes with low expression. The heat
map of the top-20 differentially expressed genes in SVIL high-expression
and low-expression groups was plotted in Figure 2. The expression of
these genes may be related to the role of SVIL.

GO and KEGG pathway enrichment analyses

GO and KEGG pathway enrichment analyses were performed to further
explore the potential mechanism of SVIL-associated genes regulating the
occurrence and development of gastric cancer. Through GO analysis, SVIL
and its associated genes showed an intimate association with
extracellular structures and tissues, extracellular matrix (ECM),
muscular system processes, cell-substrate adhesion, muscle contraction
and other molecular mechanisms (Figure 3). Meanwhile, KEGG analysis
(Figure 3) found that among 823 genes related to SVIL, 17 signal
pathways were mainly involved, including local adhesion,
phosphatidylinositol 3-kinase (PI3K)/Protein kinase B (Akt) signaling
pathway, ECM receptor interaction, vascular smooth muscle contraction,
protein digestion and absorption, etc.

The effect of SVIL knockout on cell proliferation and apoptosis

The results of MTT assay showed that compared with Normal group, si-SVIL
group had significantly reduced cell proliferation rate of SGC-7901 and
MGC-803 cells (P\textless{}0.001, Figure 4A\&4B). Meanwhile, as
indicated by the results of flow cytometry, the apoptosis rates of
SGC-7901 and MGC-803 cells in si-SVIL group was significantly increased
than those in Normal group (P\textless{}0.001, Figure 4C\&4D).

The effect of SVIL knockout on cell invasion and migration

According to the results of Transwell assay, compared with Normal group,
si-SVIL group had significantly reduced count of invasive cells of
SGC-7901 and MGC-803 (P\textless{}0.001, Figure 5A\&5B). Wound healing
assay revealed that compared with Normal group, SGC-7901 and MGC-803
cells in si-SVIL group had significant decrease in scratch healing rates
at 24 and 48 h, respectively (P\textless{}0.001 and P\textless{}0.001,
Figure 6A\&5B).

SVIL gene and protein expressions

The results of qRT PCR and western blot revealed that the gene and
protein expressions of SVIL in SGC-7901 and MGC-803 cells of si-SVIL
group were significantly reduced than those in Normal group
(P\textless{}0.001, Figure 7A-6D).

Discussion

In occurrence, gastric cancer development, and prognosis, there is an
involvement of the activation of numerous molecular signaling pathways,
among which expressions of key molecules (HER-2, PDL1, etc.) can serve
as markers for gastric cancer and molecular targets for targeted therapy
of this cancer. It suggests the importance of searching for novel and
more effective molecular markers. In our research, SVIL negatively
correlated with prognosis of gastric cancer and was an independent
prognostic indicator for this cancer. Further screening discovered 823
differentially expressed genes associated with SVIL. Through KEGG and GO
analysis, these associated genes were involved in the tumorigenesis and
development processes, such as extracellular structures and tissues,
ECM, muscle contraction process, cell-substrate adhesion, etc.
Furthermore, 6 core genes were screened through relevant software
package, and validation in database revealed that ITGAV and LAMC1 were
highly expressed in gastric cancer tissue, with statistically
significant differences. Meanwhile, the expression levels of ITGA1,
ITGAV, and LAMB1 were negatively correlated with the prognosis of
gastric cancer. Collectively, findings in this study may provide
reference for further research on the mechanism of SVIL.

SVIL has been confirmed to be involved in multiple physiological
processes of tumors. As a peripheral membrane protein that regulates
cell movement, SVIL can interact with myosin II, F-Actin and other
proteins to transmit extracellular signals intracellularly, thereby
promoting cell contraction and movement. For instance, in animal and
cell experiments, Chen X et al.{[}7{]} discovered that a novel splicing
variant of SVIL, Superllin (SV5), could promote the proliferation and
migration of tumor cells. Other researchers also detected high
expression of SVIL in liver cancer tissue. Under hypoxia, SVIL would be
up-regulated, which would eventually promote the occurrence of liver
cancer cells as well as cell migration and invasion owing to
epithelial-mesenchymal transition (EMT) induced by activating
extracellular signal regulated kinase (ERK)/p38 pathway in the
downstream of ras homologous family member A (RhoA)/Rho-associated
coiled-coil-forming protein kinase (ROCK) signaling pathway {[}6{]}.

In this study, there was an intimate correlation between high expression
of SVIL and poor prognosis in gastric cancer patients. The experiment of
SVIL knockout in gastric cancer cells was performed for further
verification. Consequently, the proliferation, invasion, and migration
abilities of gastric cancer cells were significantly inhibited after
knocking out SVIL. GO and KEGG enrichment analyses of SVIL-associated
genes indicated that these associated genes were significantly enriched
in extracellular structures and tissues, ECM, muscle contraction
process, cell-substrate adhesion and other pathways. It also offers a
new insight into the study of SVIL in gastric cancer.

Additionally, the hub genes screened in this study might explain the
role of SVIL to some extent. It has been reported that integrin was
involved in the occurrence, metastasis, proliferation and angiogenesis
of multiple tumors. Specifically, ITGAV was highly expressed in breast
cancer and can be considered as a poor prognostic marker{[}8{]}. ITGA1
might be associated with the occurrence and heterogeneity of colorectal
cancer{[}9{]}. Laminin is an important component of extracellular
matrix, with different tissue distributions and functions concerning
different tissue subtypes. Amogn them, LAMB1 and LAMC1 were respectively
confirmed to be highly expressed in colorectal cancer and endometrial
cancer, both of which were recognized to be prognostic factors and
potential therapeutic targets{[}10,11{]}. Growth arrest specific gene
protein 6 (GAX6) is a ligand of Tyro3/Axl/Mer receptor tyrosine kinase
in the receptor tyrosine kinase subfamily. Relevant research supported
that Gas6/Axl (Anexelekto)/zinc finger E-box binding homeobox 1 (ZEB1)
signaling pathway might be involved in regulating EMT, invasion, and
proliferation in gastric cancer cells, which may be a potential
therapeutic target for gastric cancer treatment{[}12{]}. Besides, PENK
had a low expression in bone tumor, and it could inhibit the metastasis
of osteosarcoma cells through PI3K/Akt signaling pathway{[}13{]}. With
respect to the above, these core genes may be critical in the
functioning of SVIL.

In conclusion, this study was conducted by analyzing microarray data
sourced from public platform, screening genes with statistical
significance, and verifying through cell experiments. Findings in this
study may contribute to the preliminary exploration of the feasibility
of subsequent projects, predicting results, and providing corresponding
theoretical evidence. This study suggests that early identification of
patients with high SVIL expression may improve the survival of gastric
cancer patients through early intervention or combined therapy. To sum
up, SVIL and its associated proteins can serve as important targets for
researching prognostic molecular markers in gastric cancer patients,
providing new directions for future research.

References:

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  Chen X, Zhang S, Wang Z, Wang F, Cao X, Wu Q, Zhao C, Ma H, Ye F, Wang
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\end{enumerate}

Figure legends

Figure 1. Curve of the relationship between SVIL gene expression level
and survival time

Figure 2. Heat map of differentially expressed genes

Figure 3. Results of GO (A) and KEGG enrichment analysis of related
genes (B)

Figure 4. The effect of SVIL knockout on cell proliferation and
apoptosis

Normal: The cells were treated with normal; si-NC: The cells were
transfected with si-negative control (NC); si-SVIL: The cells were
transfected with si-SVIL

\begin{enumerate}
\tightlist
\item
  Cell proliferation rate in different MGC803 cell groups
\item
  Cell proliferation rate in different SGC-7901 cell groups
\item
  Apoptosis rate in different MGC-803 cell groups
\item
  Apoptosis rate in different SGC-7901 cell groups
\end{enumerate}

***: P<0.001, compared with Normal group

Figure 5. The effect of SVIL knockout on cell invasion and migration

Normal: The cells were treated with normal; si-NC: The cells were
transfected with si-negative control (NC); si-SVIL: The cells were
transfected with si-SVIL

Invasion MGC-803 cell number

Invasion SGC-7901 cell number

***: P<0.001 compared with Normal

Figure 6. The effect of SVIL knockout on cell migration

Normal: The cells were treated with normal; si-NC: The cells were
transfected with si-negative control (NC); si-SVIL: The cells were
transfected with si-SVIL

Wound healing rate in different MGC-803 cell groups

Wound healing rate in different SGC-7901 cell groups

***: P<0.001 compared with Normal

Figure 7. SVIL gene and protein expressions

Normal: The cells were treated with normal; si-NC: The cells were
transfected with si-negative control (NC); si-SVIL: The cells were
transfected with si-SVIL

\begin{enumerate}
\tightlist
\item
  SVIL gene expression in different MGC-803 cell groups
\item
  SVIL gene expression in different SGC-7901 cell groups
\item
  SVIL protein expression in different MGC-803 cell groups
\item
  SVIL protein expression in different SGC-7901 cell groups
\end{enumerate}

***: P<0.001 compared with Normal

\textbf{Hosted file}

\verb`Table 1.docx`  available at \url{https://authorea.com/users/725046/articles/731520-the-role-and-significance-of-svil-protein-in-the-occurrence-and-development-of-gastric-cancer}\selectlanguage{english}
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\includegraphics[width=0.70\columnwidth]{figures/Figure-3/Figure-3}

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\includegraphics[width=0.70\columnwidth]{figures/Figure-4/Figure-4}

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\includegraphics[width=0.70\columnwidth]{figures/Figure-5/Figure-5}

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\includegraphics[width=0.70\columnwidth]{figures/Figure-6/Figure-6}

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\includegraphics[width=0.70\columnwidth]{figures/Figure-7/Figure-7}

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\textbf{Hosted file}

\verb`Table 2.docx`  available at \url{https://authorea.com/users/725046/articles/731520-the-role-and-significance-of-svil-protein-in-the-occurrence-and-development-of-gastric-cancer}

\textbf{Hosted file}

\verb`Talbe 3.docx`  available at \url{https://authorea.com/users/725046/articles/731520-the-role-and-significance-of-svil-protein-in-the-occurrence-and-development-of-gastric-cancer}

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