Fusheng Li1,2, Jia Xu3, Yue Zhu1, Liang Sun4, Renyi Zhou1. 1. Department of Orthopaedics, The First Affiliated Hospital of China Medical University, Shenyang, People's Republic of China. 2. Department of Orthopaedic Oncology, The People's Hospital of Liaoning Province, China Medical University People's Hospital, Shenyang, People's Republic of China. 3. Clinical Teaching Experimental Center, Key Laboratory of Environmental Pollution and Microecology of Liaoning Province, Shenyang Medical College, Shenyang, People's Republic of China. 4. State Key Laboratory of Radiation Medicine and Protection, School of Radiation Medicine and Protection, Soochow University, Suzhou, People's Republic of China.
Abstract
Chondrosarcoma is the second most common bone malignancy in adults, and it is often resistant to traditional chemotherapy and radiation therapy. Permanent implantation of iodine-125 (125I) seeds has been explored for the treatment of many types of cancer. In this study, the aim was to investigate the proliferative and microRNA (miRNA) effects of 125I seeds irradiation on human chondrosarcoma SW1353 cells. First, a new in vitro 125I seed irradiation model was established, and cell viability and miRNA microarray assays were performed before and after exposure to the 125I seeds. Cell proliferation was inhibited, and miRNA expression was substantially altered by irradiation exposure. The inhibition of cell proliferation was positively correlated with increased radiation doses, with cells showing the highest total radiation dose 7 days after irradiation. A total of 2549 miRNAs were detected in the SW1353 cells after exposure to 6 Gy of radiation, which included 189 differentially expressed miRNAs (98 upregulated and 91 downregulated). Four miRNAs were found to play important roles in the inhibition of cell proliferation after irradiation exposure, including miR-1224-5p, miR-492, miR-135b-5p, and miR-6839-5p. The target genes of the associated miRNAs mentioned were vascular endothelial growth factor A (VEGFA), C-X-C motif chemokine 12 (CXCL12), mitogen-activated protein kinase kinase kinase kinase 3 (MAP4K3), and apoptosis facilitator Bcl-2-like protein 14 (BCL2L14). Hence, the mitogen-activated protein kinase signaling pathway may be involved in how chondrosarcoma cells respond to 125I seed irradiation.
Chondrosarcoma is the second most common bone malignancy in adults, and it is often resistant to traditional chemotherapy and radiation therapy. Permanent implantation of iodine-125 (125I) seeds has been explored for the treatment of many types of cancer. In this study, the aim was to investigate the proliferative and microRNA (miRNA) effects of 125I seeds irradiation on humanchondrosarcomaSW1353 cells. First, a new in vitro 125I seed irradiation model was established, and cell viability and miRNA microarray assays were performed before and after exposure to the 125I seeds. Cell proliferation was inhibited, and miRNA expression was substantially altered by irradiation exposure. The inhibition of cell proliferation was positively correlated with increased radiation doses, with cells showing the highest total radiation dose 7 days after irradiation. A total of 2549 miRNAs were detected in the SW1353 cells after exposure to 6 Gy of radiation, which included 189 differentially expressed miRNAs (98 upregulated and 91 downregulated). Four miRNAs were found to play important roles in the inhibition of cell proliferation after irradiation exposure, including miR-1224-5p, miR-492, miR-135b-5p, and miR-6839-5p. The target genes of the associated miRNAs mentioned were vascular endothelial growth factor A (VEGFA), C-X-C motif chemokine 12 (CXCL12), mitogen-activated protein kinase kinase kinase kinase 3 (MAP4K3), and apoptosis facilitator Bcl-2-like protein 14 (BCL2L14). Hence, the mitogen-activated protein kinase signaling pathway may be involved in how chondrosarcoma cells respond to 125I seed irradiation.
Chondrosarcoma is a heterogeneous group of malignancies, characterized by the
production of a significant amount of extracellular matrix by tumor cells.[1] Currently, chondrosarcoma is the second most common bone malignancy in
adults. Surgical resection is the preferred treatment for patients with
chondrosarcoma, as the tumors are often resistant to conventional chemotherapy and
radiotherapy. However, radiotherapy may still be used for treating positive surgical
margins or inoperable tumors in difficult anatomical sites, such as the base of the
skull or sacrum.[1,2]Permanent implantation of iodine-125 (125I) seeds is a kind of
brachytherapy. The radioactive 125I seeds emit γ-rays at 29 keV, which
effectively destroy the double strands of DNA in tumor nuclei, resulting in the loss
of proliferative abilities. The average radiation radius of 125I seeds is
1.7 cm, which limits the off target damage to surrounding tissues when the seeds are
implanted into the tumor.[3,4] It was previously shown that cells in different phases of the cell cycle
display differences in radiation sensitivity, with cells in the G2/M phase being
most sensitive to irradiation. The long half-life of 125I seeds
(t
1/2 = 59.4 days) allows for the continuous release of γ-rays at the site
of placement. Nowadays, interstitial implantation of 125I seeds has been
used to treat prostate cancer, and some other forms of recurrent or inoperable
malignancies, such as non-small cell lung cancer, pancreatic cancer, and
intracranial gliomas.[4-8] Previously, Ren et al[3] reported the use of 125I seeds placed into the resected tumor bed
of a patient with recurrent lumbar vertebral chondrosarcoma who underwent marginal
resection. Although the pathology specimen was showed conventional low-grade
chondrosarcoma, the treatment was effective, with no signs of recurrence at the
2-year follow-up. Hence, 125I seed implantation may be an effective
approach for the treatment of inoperable chondrosarcomas.MicroRNAs (miRNAs) are a class of endogenous, small noncoding RNAs that serve as
regulators of gene expression in multicellular organisms. MicroRNAs can affect the
output of many protein-coding genes and negatively regulate the translation of
messenger RNAs (mRNAs) by attaching to complementary base pairs of the target genes,
leading to effective degradation of mRNAs.[9-12] Some studies have demonstrated that miRNAs play an important role in the
proliferation, invasion, and metastasis of cancer.[13-22]In recent years, several studies have assessed the roles of miRNAs in chondrosarcoma,
yet none of the findings have focused on the effects of 125I seeds
irradiation exposure on the miRNAs expression profiles of conventional
chondrosarcoma cells.[12,23-27] In the current study, we developed a new in vitro 125I seed
irradiation model to study the effects of 125I seed irradiation on the
proliferation of grade II chondrosarcomaSW1353 cells. Microarray analysis was
performed to detect the miRNAs expression profiles of irradiated and nonirradiated
cells. We hypothesized that miRNAs, which are significantly altered after exposure
to irradiation from 125I seeds, may play an important role in the cell
response network. In addition, we conducted an integrative analysis of miRNAs–mRNAs
regulatory networks, which could improve our understanding of 125I seed
brachytherapy in the treatment of chondrosarcoma.
Materials and Methods
Establishment of an In Vitro 125I Seed Irradiation Model
Iodine-125 seeds were provided by Beijing Zhibo Bio-Medical Technology Co, Ltd
(Beijing, China). The 125I seeds were placed onto the surface of a
polystyrene pillar, which was 50 mm high and 50 mm diameter. Next, 16 seeds were
placed equally around the circumstance of a 17.5-mm radius, and 8 seeds around
the circumstance of an 8.75-mm radius (Figure 1A). The cell dish was 5 mm away
from the top of the pillar, which contained 24 seeds (Figure 1B). When in use, the irradiator
was placed in a cylindrical container manufactured with 3-mm-thickness steel,
which had 4 ventilation holes in the upper sidewall (diameter = 5 mm). The
initial activity of the 125I seed was 0.8 mCi. The Monte-Carlo model
was used to calculate the dose distribution at various points on the cell plane.
The initial mean dose was also calculated. The differences in irradiation dose
distribution at various points on the cell plane were less than 10% (Figure 1C). As calculated,
the initial mean dose rate (D
0) was 7.802 cGy/h. The total dose (D
t) in a certain length of irradiation exposure could be calculated
using the following calculation.
Figure 1.
Development of an in vitro iodine-125 (125I) seed irradiation
model. A, Arrangement of 24 125I seeds onto the surface of a
polystyrene pillar. Sixteen seeds were equally placed around the
circumstance of a 17.5-mm radius, and 8 seeds around the circumstance of
an 8.75-mm radius. B, The 125I seed irradiation model of
cells. C, Differences in the irradiation dose distribution at various
points on the treatment cell plane were less than 10%.
Development of an in vitro iodine-125 (125I) seed irradiation
model. A, Arrangement of 24 125I seeds onto the surface of a
polystyrene pillar. Sixteen seeds were equally placed around the
circumstance of a 17.5-mm radius, and 8 seeds around the circumstance of
an 8.75-mm radius. B, The 125I seed irradiation model of
cells. C, Differences in the irradiation dose distribution at various
points on the treatment cell plane were less than 10%.In the equation, t is time in hours, λ is the
decay constant for 125I, and T is the length of
irradiation (hours). For the calculation, t
1/2 = 1425.6 hours (59.4 days). Alternatively, the length of
irradiation exposure could also be calculated if the total dose was given.[28]
Cell Culture
The humanchondrosarcomaSW1353 cell line was purchased from ZiShi Biotech Co,
Ltd (Shanghai, China). The cells were cultured in Dulbecco modified Eagle medium
supplemented with 10% fetal bovine serum (Pan Biotech, Aidenbach, Germany), 100
U/mL penicillin, and 0.1 mg/mL streptomycin. A humidified incubator with 5%
CO2 was maintained at 37°C. For the extraction of RNA, the cells
were seeded into 3.5 cm culture plates and grown to 85% confluency.
Iodine-125 Seed Irradiation
HumanchondrosarcomaSW1353 cells were divided into experimental (irradiated) and
control (nonirradiated) groups. The experimental groups were set up with a total
dose of 2, 4, 6, and 8 Gy. In the current study, there were 3 samples in the
irradiated and control groups, respectively.
Cell Viability Assay
Cells were seeded in 96-well plates at 1200 or 2500 cells/well according to the
postirradiated cultured time. The adherent cells were cultured for 24 hours and
then irradiated by the 125I seeds. After irradiation, 3 wells were
detected in each group per day for a period of 7 days. The absorbance at 570 nm
(optimal density or OD) was measured using the SpectroMax190 (Molecular Devices,
San Jose, California) according to the manufacturer’s instructions. The curve
depicting the cell growth inhibition was established, and the cell growth
inhibition rate was calculated using this formula: 1 − (irradiated group
OD/control group OD) × 100%. Experiments were performed in triplicate for
statistical analysis.
RNA Isolation and Microarray Analysis
After the cells were treated with a total dose of 6-Gy irradiation, the RNA was
extracted from SW1353 cells in the experimental and control groups within 1 hour
after irradiation. The samples were obtained and purified using the MagMAX
mirVana Total RNA Isolation Kit (Thermo Fisher Scientific, Waltham,
Massachusetts). Subsequently, the NanoDrop 2000 Spectrophotometer (Thermo Fisher
Scientific) was applied to measure the quality and quantity of total RNA at the
absorbance of 260 nm. Finally, the miRNAs expression profiles were detected
using the Agilent Human miRNA Microarray (Oebiotech, Shanghai, China), which
contained 2569 miRNA probes.
Bioinformatics Analysis
Agilent’s Feature Extraction version 10.7.1.1 software (Santa Clara, California)
was used to extract the original data obtained after chip hybridization. Next,
the original data were standardized using the quantile method. The GeneSpring GX
version 13.1 software (Agilent) was used for target gene prediction. TargetScan
(http://www.targetscan.org/), PITA (http://genie.weizmann.ac.il/pubs/mir07/mir07_data.html:), and
http://microRNA.org online databases were used to predict the
target genes of differential miRNAs. The target genes were selected for
subsequent Gene Ontology (GO; http://www.geneontology.org) and Kyoto Encyclopedia of Genes and
Genomes (KEGG; http://www.genome.jp/kegg/) analysis to determine their primary
functions. The GO included 3 major modules, including biological processes,
cellular components, and molecular functions, leading to 3 results. The pathway
analysis of the target genes was conducted in the KEGG database, which played a
crucial role in isolating the target genes enriched in each pathway. Value of
P <.05 was used as the cutoff value for both GO and KEGG
pathway analyses.The protein–protein interactions (PPIs) network of predicted target genes was
constructed by STRING (http://www.string-db.org)
and visualized by Cytoscape software version 3.7.1 (https://www.cytoscape.org). The MCODE plug-in for Cytoscape was
used to analyze the whole PPI network with a degree cutoff of 2, haircut cluster
finding, node score cutoff of 0.2, k-core of 2, and a maximum depth of 100.[29] The cutoff criteria to search for the key molecules in the SW1353 cells
treated with 125I seeds were greater than 15.
Quantitative real-time polymerase chain reaction (qRT-PCR) was conducted to
validate the results of the miRNAs microarray analysis, along with the predicted
target genes. Equal amounts of total RNA from each sample used in the miRNA
microarray assay were reverse transcribed using the miRNA First-Strand cDNA
Synthesis (Tailing Reaction; Sangon Biotechnology Co Ltd, China) and PrimeScript
RT Reagent Kit with gDNA Eraser (Perfect Real Time) from Takara Bio Inc, (Shiga,
Japan). The qRT-PCR was monitored using the ABI PRISM 7500 Sequence Detection
System (Applied Biosystems, Foster City, California). The experiment was run in
triplicate. All levels were normalized to GAPDH, and fold induction was
calculated by setting the control conditions to 1. The primers are given in
Table 1.
List of Primers for qRT-PCR.Abbreviations: miRNAs, microRNAs; qRT-PCR, quantitative real-time
polymerase chain reaction.
Statistical Analysis
Statistical analysis of the miRNA microarray data involved the 1-way analysis of
variance using the Affymetrix Expression Console TAC (Santa Clara, California),
followed by the least significant difference test. Statistics for qRT-PCR were
performed with the Student t test using SPSS version 16.0
software (IBM, Chicago, Illinois), and significant differences were considered
at P < .05.
Results
Iodine-125 Seed Irradiation Inhibits the Proliferation of Chondrosarcoma
Cells
The growth inhibition rates of cells exposed to 2, 4, 6, and 8 Gy of radiation
were calculated to investigate the effects of 125 I seed irradiation
on the proliferation of chondrosarcoma cells. In SW1353 cells, cell growth
became unstable for 2 days after exposure to 2 Gy irradiation, followed by a
gradual increase in the percentage of cell growth inhibition to 7 days
postexposure. In the group exposed to 4 Gy of radiation, a gradual increase in
cell growth inhibition was seen from after the first day to 7 days postexposure.
However, the inhibition rates experienced in the 6 and 8 Gy groups were nearly
instantaneous, with cell growth being inhibited the first day after irradiation.
As the radiation dose increased from 2 to 8 Gy, the percentage of cell growth
inhibition also increased, reaching the highest value by 7 days postexposure. As
shown in Figure 2, the
rates of cell growth inhibition for the 2, 4, 6, and 8 Gy groups were 14.64%,
17.25%, 22.41%, and 26.39% at 7 days postirradiation, respectively
(P < .05).
Figure 2.
Inhibition of SW1353 cell growth after exposure to iodine-125
irradiation. The inhibition of cell growth was dose dependent and
reached the highest levels at 7 days postirradiation. The rates for the
2, 4, 6, and 8 Gy groups were 14.64%, 17.25%, 22.41%, and 26.39% at 7
days postexposure, respectively (P < .05).
Inhibition of SW1353 cell growth after exposure to iodine-125
irradiation. The inhibition of cell growth was dose dependent and
reached the highest levels at 7 days postirradiation. The rates for the
2, 4, 6, and 8 Gy groups were 14.64%, 17.25%, 22.41%, and 26.39% at 7
days postexposure, respectively (P < .05).
Differential Expression of MiRNAs in SW1353 Cells After Irradiation
In the SW1353 cells exposed to 6 Gy of radiation, the microarray analysis
identified 2549 total miRNAs. As compared with the control group, there were 189
differentially expressed miRNAs (P < .05), including 98
upregulated and 91 downregulated miRNAs (Figure 3A). The top 15 differentially
expressed upregulated and downregulated miRNAs between the irradiated and
control groups are listed in Tables 2 and 3, respectively. The clustering
histogram revealed the different miRNAs expression profiles between the
irradiated group and control group, and the heatmap showed the top 15
differentially expressed miRNAs between irradiated and nonirradiated groups
(Figure 3B).
Figure 3.
Differentially expressed microRNAs (miRNAs) in SW1353 cells exposed to
iodine-125 (125I) seeds. A, Volcano plot. Vertical green
lines: 2-fold changes of difference multiple between the experimental
and control group; horizontal green line: P = .05. Gray
dots represent the miRNAs with P > .05. Green dots
represent miRNAs with fold-change <2 and P < .05.
Red dots represent the miRNAs with fold-change >2 and
P < .05, which are significantly upregulated
differential miRNAs. Blue dots represent the miRNAs with fold-change
<−2 and P < .05, which are significantly
downregulated differential miRNAs. B, Hierarchical cluster analysis of
the top 15 differentially expressed upregulated and downregulated miRNAs
in SW1353 cells exposed to 125I seeds. Red indicates high
relative expression, while blue indicates low relative expression.
Table 2.
Top 15 Differentially Expressed Upregulated MiRNAs Between SW1353 Cells
Exposed to Irradiation and the Control Group.
MicroRNAs
Average Expression in Control Group
Average Expression in 125I Group
Fold-Change
ANOVA (P Value)
hsa-miR-6076
−3.3
1.76
33.37
.000000102
hsa-miR-6839-5p
−3.3
1.70
32.01
.000000203
hsa-miR-1224-5p
−3.3
1.63
30.54
.0000000051
hsa-miR-6824-5p
−1.87
2.55
21.44
.03580002
hsa-miR-1469
−3.3
0.89
18.27
.000000798
hsa-miR-328-5p
−3.3
0.63
15.30
.000000478
hsa-miR-4689
−3.01
0.84
14.39
.004125495
hsa-miR-492
−3.3
−0.33
7.84
.012121474
hsa-miR-4745-5p
−2.29
0.49
6.89
.049530223
hsa-miR-629-3p
0.44
2.41
3.91
.00000143
hsa-miR-1973
1.61
2.96
2.56
.001193884
hsa-miR-4746-3p
3.09
4.13
2.06
.00000341
hsa-miR-4485-3p
3.28
4.25
1.96
.0000299
hsa-miR-135a-3p
1.52
2.48
1.95
.001470052
hsa-miR-4428
2.28
3.14
1.81
.000804
Abbreviations: ANOVA, 1-way analysis of variance; 125I,
iodine-125; miRNA, microRNA.
Table 3.
Top 15 Differentially Expressed Downregulated MiRNAs Between SW1353 Cells
Exposed to Irradiation and the Control Group.
MicroRNAs
Average Expression in Control Group
Average Expression in 125I Group
Fold-Change
ANOVA (P Value)
hsa-miR-5196-3p
1.02
−1.69
−6.58
.038893394
hsa-miR-22-5p
0.47
−1.92
−5.23
.02877958
hsa-miR-135b-5p
1.70
0.69
−2.01
.004806157
hsa-miR-18a-5p
0.94
−0.03
−1.96
.01941451
hsa-miR-21-3p
2.81
1.98
−1.78
.026309982
hsa-miR-4640-3p
1.47
0.71
−1.68
.020299722
hsa-miR-6732-3p
1.38
0.72
−1.58
.041156914
hsa-miR-4284
7.77
7.11
−1.58
.00055
hsa-miR-29b-1-5p
2.86
2.26
−1.52
.007111116
hsa-miR-523-3p
1.63
1.08
−1.46
.027703047
hsa-miR-424-5p
5.11
4.57
−1.45
.0000208
hsa-miR-19a-3p
3.44
2.91
−1.44
.010547455
hsa-miR-503-5p
2.01
1.50
−1.43
.010960225
hsa-miR-210-3p
3.75
3.27
−1.39
.03419331
hsa-miR-512-5p
3.78
3.31
−1.39
.007449524
Abbreviations: ANOVA, 1-way analysis of variance; 125I,
iodine-125; miRNAs, microRNAs.
Differentially expressed microRNAs (miRNAs) in SW1353 cells exposed to
iodine-125 (125I) seeds. A, Volcano plot. Vertical green
lines: 2-fold changes of difference multiple between the experimental
and control group; horizontal green line: P = .05. Gray
dots represent the miRNAs with P > .05. Green dots
represent miRNAs with fold-change <2 and P < .05.
Red dots represent the miRNAs with fold-change >2 and
P < .05, which are significantly upregulated
differential miRNAs. Blue dots represent the miRNAs with fold-change
<−2 and P < .05, which are significantly
downregulated differential miRNAs. B, Hierarchical cluster analysis of
the top 15 differentially expressed upregulated and downregulated miRNAs
in SW1353 cells exposed to 125I seeds. Red indicates high
relative expression, while blue indicates low relative expression.Top 15 Differentially Expressed Upregulated MiRNAs Between SW1353 Cells
Exposed to Irradiation and the Control Group.Abbreviations: ANOVA, 1-way analysis of variance; 125I,
iodine-125; miRNA, microRNA.Top 15 Differentially Expressed Downregulated MiRNAs Between SW1353 Cells
Exposed to Irradiation and the Control Group.Abbreviations: ANOVA, 1-way analysis of variance; 125I,
iodine-125; miRNAs, microRNAs.
Predicted Target Genes and MiRNA-Gene Networks Analysis
As the primary function of miRNAs is to repress the expression of target genes,[30] the correlated miRNA-target pairs were simultaneously predicted using the
TargetScan, PITA, and http://miRNA.org databases (Figure 4A). We selected
the intersection of the 3 databases to predict the target genes, and there are
only 3 miRNAs (miR-1224-5p, miR-492, and miR-135b-5p) which have target genes in
the intersection. Based on the target gene predictions, the miRNA–mRNA
regulatory interaction network was visualized between the 3 miRNAs and 375 mRNAs
(Figure 4B).
Figure 4.
Network of microRNA (miRNA) and predicted target gene. A, Target genes
database prediction of differential miRNAs. B, MicroRNA target gene
network. Green nodes stand for target genes. Hexagon nodes represent
miRNAs (red node indicate upregulated, the fold-change = 30.54; pink
node indicate upregulated, the fold-change = 7.84; blue node indicate
downregulated, the fold-change = −2.01). The lines represent the
regulatory relationship between the miRNAs and target genes.
Network of microRNA (miRNA) and predicted target gene. A, Target genes
database prediction of differential miRNAs. B, MicroRNA target gene
network. Green nodes stand for target genes. Hexagon nodes represent
miRNAs (red node indicate upregulated, the fold-change = 30.54; pink
node indicate upregulated, the fold-change = 7.84; blue node indicate
downregulated, the fold-change = −2.01). The lines represent the
regulatory relationship between the miRNAs and target genes.
Gene Ontology Analysis of Predicted Target Genes
The relationship between predicted target genes and their functions was
successfully uncovered through the GO analysis. The calculation returned an
enriched P value, and a smaller P value
indicated a higher degree of enrichment of the target gene in the GO term. In
the GO analysis, there were 145 different biological processes, 36 different
cellular components, and 46 different molecular functions identified, based on
P < .05. The top 20 biological processes, cellular
component, and molecular function GOs are shown in Figure 5A to C, respectively.
Figure 5.
Gene Ontology and pathways analysis of predicted genes. A, Top 20
differential biological processes of predicted target genes in SW1353
cells exposed to iodine-125 (125I) seeds. B, Top 20
differential cellular components of predicted target genes in SW1353
cells exposed to 125I seeds. C, Top 20 differential molecular
functions of predicted target genes in SW1353 cells exposed to
125I seeds. D, Important pathways of the predicted target
genes based on the Kyoto Encyclopedia of Genes and Genomes database.
Gene Ontology and pathways analysis of predicted genes. A, Top 20
differential biological processes of predicted target genes in SW1353
cells exposed to iodine-125 (125I) seeds. B, Top 20
differential cellular components of predicted target genes in SW1353
cells exposed to 125I seeds. C, Top 20 differential molecular
functions of predicted target genes in SW1353 cells exposed to
125I seeds. D, Important pathways of the predicted target
genes based on the Kyoto Encyclopedia of Genes and Genomes database.
Pathway Analysis of Predicted Target Genes
The top 20 significant pathways of predicted target genes were identified based
on the KEGG database, including proteoglycans in cancer, the mitogen-activated
protein kinase (MAPK) signaling pathway, cysteine and methionine metabolism,
long-term potentiation, axon guidance, prion diseases, the insulin signaling
pathway, the ErbB signaling pathway, breast cancer, adrenergic signaling in
cardiomyocytes, central carbon metabolism in cancer, the cyclic adenosine
monophosphate (cAMP) signaling pathway, epidermal growth factor receptor
tyrosine kinase inhibitor resistance, pathways in cancer, the transforming
growth factor β signaling pathway, acute myeloid leukemia, regulation of actin
cytoskeleton, the gonadotropin-releasing hormone signaling pathway, oocyte
meiosis, and the P13k-Akt signaling pathway (Figure 5D). The genes involved in these
significant pathways are shown in Table 3.
Protein–Protein Interaction Networks Analysis of Predicted Target
Genes
The PPI network of predicted target genes was constructed by STRING and
visualized by Cytoscape (Figure
6). A total of 299 genes were found to be essential genes through the
screening. Moreover, the whole PPI network was analyzed by MCODE. The cutoff
criterion was set to greater than or equal to 15, indicating that these genes
have more interactions than less studied genes in the network. The key genes
include vascular endothelial growth factor A (VEGFA),
MAPK1, CUL3, HNRNPA1, and
PPP1CC.
Figure 6.
Protein–protein interaction networks of the target genes. The area and
color of the circle represent the degree. Red represents the maximum
value, and green represents the minimum value. For the interpretation of
colors, please refer to the web version of this article.
Protein–protein interaction networks of the target genes. The area and
color of the circle represent the degree. Red represents the maximum
value, and green represents the minimum value. For the interpretation of
colors, please refer to the web version of this article.
Quantitative Real-Time Polymerase Chain Reaction Analysis of Differentially
Expressed MiRNAs and Their Target Genes
As predictions based on miRNA sequence complementarity and their target genes may
cause false-positive results,[30] qRT-PCR was performed with 10 miRNAs and 10 predicted target genes based
on the microarray, pathway, and PPI network analyses (Figure 7A and B). From the analysis, 70%
(7/10) of the validated genes showed expression trends consistent with those of
the microarray analysis. However, the expression levels of miR-4689, miR-6076,
and miR1469 were inconsistent with the microarray analysis, yet the differences
were not evident (Figure
7A).
Figure 7.
Quantitative real-time polymerase chain reaction analysis of 10
differential microRNAs (miRNAs) and their predicted target genes between
the irradiated and control groups. A, Findings from the 10 miRNAs
identified 4 key miRNAs. B, Findings from 10 predicted target genes
identified 4 essential genes. * Fold-change >2 or fold-change
<0.5.
Quantitative real-time polymerase chain reaction analysis of 10
differential microRNAs (miRNAs) and their predicted target genes between
the irradiated and control groups. A, Findings from the 10 miRNAs
identified 4 key miRNAs. B, Findings from 10 predicted target genes
identified 4 essential genes. * Fold-change >2 or fold-change
<0.5.
Discussion
Grade II chondrosarcoma show high resistance to chemotherapy and radiation therapy, a
metastatic potential and high recurrence rate, all of which are suitable
characteristics when thinking about developing adjuvant therapies.[31] SW1353, JJ012, and CH3573 are currently the most characterized conventional
grade II chondrosarcoma cell lines.[32] Among them, SW1353 is the most extensively used and is considered as the gold
standard among other cells.[33]The 125I seeds primarily emit γ-rays with strong penetrating powers,
leading to cell damage through the production of intermediate ions and free radicals
that cause double-stranded breaks in the DNA. In our study, 125I seeds
inhibited the proliferation of SW1353 cells in vitro in a dose-dependent manner,
with higher doses of radiation increasing the inhibition of cell growth.Due to the integral roles of miRNAs as gene expression regulators, we hypothesized
that miRNAs, which are significantly altered after exposure to irradiation from
125I seeds, may play an important role in the cell response network.
Among the 10 miRNAs selected for validation in our study, 4 key miRNAs, including
miR-1224-5p, miR-492, miR-135b-5p, and miR-6839-5p, were found to be differentially
expressed in the irradiated cells as compared with the control group. No previous
studies have reported on the regulatory roles of miR-1224-5p, miR-492, or
miR-135b-5p in chondrosarcoma cells,[23,25-26] yet some published documents have shown that miR-1224-5p, miR-492, and
miR-135b-5p may play important roles in the proliferation, invasion, and metastasis
of nonchondrosarcoma tumors.[13-22] To the best of our best knowledge, miR-6839-5p has not been reported in the
literature. In the current study, we hypothesized that miR-1224-5p, miR-492,
miR-135b-5p, and miR-6839-5p might play vital roles in how SW1353 cells respond to
irradiation with 125I seeds.First, miR-1224-5p serves as a potential tumor suppressor in some malignancies. The
upregulation of miR-1224-5p may decrease cell proliferation, induce apoptosis,
inhibit migration and invasion, and suppress tube formation in the endothelial cells
of humanhepatocellular carcinoma (HCC).[13] In malignant gliomas, miR-1224-5p has been shown to inhibit tumor-associated
activity by targeting the cAMP response element-binding protein
(CREB1) gene.[14]Second, miR-492 promotes the progression of prostate cancer, liver cancer,
hepatoblastoma, and cervical squamous cell carcinoma.[15-18] miR-492 represses SOCS2 expression to exert tumor-promoting functions in
prostate cancer cells, which is implicated in the regulation of HCC progression
through PTEN and AKT pathways. Hence, patients with HCC with high miR-492 and low
PTEN had poorer prognoses in the clinic.[15-16] MicroRNA-492 also regulates the metastatic potential of hepatoblastoma via
CD44 signaling.[17] In cervical squamous cell carcinomas, miR-492 overexpression has been
correlated with pelvic lymph nodes metastasis and was found to enhance the
radiosensitivity of cells.[18]Lastly, miR-135b-5p has been reported to promote carcinogenesis and tumor development
in humans,[19] including pancreatic ductal adenocarcinoma (PDAC) and gastric cancer.[20-21] The overexpression of miR-135b-5p was associated with unfavorable clinical
outcomes and poor prognosis, such as regional lymph node metastases, vascular
invasion, and tumor microthrombus in PDAC.[20] Moreover, miR-135b-5p was found to directly target frizzled-related protein 4
to regulate the Wnt/β-catenin signaling pathway in PDAC.[20] Functionally, high levels of miR-135b-5p suppress apoptosis and induce
cisplatin resistance in gastric cancer.[21] On the other hand, miR-135b-5p upregulation can increase the doxorubicin
sensitivity of breast cancer cells via anterior gradient 2 (AGR2). The
overexpression of AGR2 is involved in pathogenesis of breast cancer, including the
growth and metastasis of tumors, which is associated with poor prognoses.[22]Based on the target genes prediction, PPI networks analysis, and qRT-PCR validation,
VEGFA, C-X-C motif chemokine 12 (CXCL12), and
MAP4K3 were found to be upregulated in the irradiated group,
while Bcl-2-like protein 14 (BCL2L14) was downregulated
(P < .05). The 4 mRNAs are the target genes of miR-1224-5p,
miR-492, miR-135b-5p, and miR-6839-5p. However, one miRNA can inhibit many mRNAs,
and one mRNA can also interact with many genes through different pathways. Inside
tumor cells, miRNAs can act as either tumor promoters or suppressors, with
additional functional alterations concerning the role of their mRNA targets.[11] However, we are unable to obtain the specific miRNA–mRNA pairing information
from this study.Using the KEGG database, the top 20 pathways of the target genes were identified,
some of which are involved in cancer and radiation injury. In a previous study, Dent
et al[34] showed that several proteins in the MAPK pathway have critical roles in how
cells respond to radiation exposure. Since MAPK1 and
MAP4K3 were predicted target genes of the miRNAs differentially
expressed in the irradiated cells from this study, it is reasonable to hypothesize
that the MAPK signaling pathway may be involved in the response of chondrosarcomaSW1353 cells to 125I seed irradiation.
Limitations
In this study, we selected 10 miRNA and 10 predicted target mRNA genes for
verification. However, there may be other miRNAs that should be further studied
in the future. In addition, the specific regulatory mechanisms of miRNAs require
more attention in future studies. Lastly, additional studies are necessary to
further uncover the roles of differentially expressed miRNAs in chondrosarcoma
cells.
Conclusions
In summary, our study demonstrated that irradiation from 125I seeds
effectively inhibits the proliferation of chondrosarcoma cells in vitro, leading to
dysregulation of critical miRNAs. The effect of radiation was dose dependent, with
higher radiation doses causing more cell growth inhibition. Optimal cell growth
inhibition was reached by 7 days postexposure. Next, miR-1224-5p, miR-492,
miR-135b-5p, and miR-6839-5p were found to play important roles in the inhibition of
proliferation after exposure to radiation. VEGFA,
CXCL12, MAP4K3, and BCL2L14
were identified as potential target genes of the miRNAs. In addition, the MAPK
signaling pathway might be involved in how cells respond to irradiation. Our
findings presented here provide insight into the effects of 125I seed
irradiation on chondrosarcoma cells, along with the regulatory roles of miRNAs in
SW1353 cells exposed to radiation.
Authors: Genovefa Polychronidou; Vasilios Karavasilis; Seth M Pollack; Paul H Huang; Alex Lee; Robin L Jones Journal: Future Oncol Date: 2017-01-30 Impact factor: 3.404
Authors: Annemiek M van Maldegem; Hans Gelderblom; Emanuela Palmerini; Sander D Dijkstra; Marco Gambarotti; Pietro Ruggieri; Remi A Nout; Michiel A J van de Sande; Cristina Ferrari; Stefano Ferrari; Judith V M G Bovée; Piero Picci Journal: Cancer Date: 2014-07-03 Impact factor: 6.860
Authors: Hans Gelderblom; Pancras C W Hogendoorn; Sander D Dijkstra; Carla S van Rijswijk; Augustinus D Krol; Antonie H M Taminiau; Judith V M G Bovée Journal: Oncologist Date: 2008-03