Introduction
Ovarian cancer is one of the leading causes of cancer-related deaths in females and currently ranks fifth in causing cancer-related deaths among women. Based on a recent statistic, there are 22,280 newly diagnosed cases of ovarian cancer in the United States each year, among which 15,500 are estimated to die each year [
1]. Most tumour-related deaths in patients suffering from solid tumours are not due to the primary tumour but rather to metastasis or invasion. Most patients with ovarian cancer are diagnosed at terminal stages, and this cancer type features high invasiveness [
2].
The major reason for the high death rate is the widely metastatic spread predominantly in the abdomen [
3,
4]. Epithelial-mesenchymal transition (EMT) is a major process for the conversion of early-stage ovarian tumours to invasive and metastatic malignancies, promoting the aggressiveness of ovarian cancers, due to the loss of epithelial characteristics and acquisition of mesenchymal characteristics [
5]. Therefore, EMT is described as critical event in cancer progression and metastasis [
6], and has drawn much attention in ovarian cancer metastasis research [
7]. EMT is generally induced by developmental signalling pathways, most notably, the TGF-β pathway is regarded as a primary inducer of EMT [
6,
8].
The mouse SLFN family has been implicated in various physiological or pathological processes, including T-cell activation, thymocyte maturation, fifibroblast and tumour cell proliferation [
9‐
12]. However, the human SLFN family has not been extensively studied, with the exception of SLFN11, which is capable of suppressing HIV replication, and positively correlates with the effect of topoisome rase inhibitors on human cancer cells [
13‐
15]. There are very few studies on human SLFN5, and the results are inconsistent. For example, human SLFN5 is found at a low level in melanoma and renal cell carcinoma, and plays inhibitory roles in tumour invasion [
16,
17]. In contrast, a pro-tumorigenic role for SLFN5 has been suggested in glioblastoma, where it acts as a co-repressor with signal transducer and activator of transcription 1(STAT1) in interferon-mediated responses [
18]. SLFN5 is both an IFN-stimulated response gene and a repressor of IFN-gene transcription, suggesting the existence of a negative-feedback regulatory loop that may account for suppression of antitumor immune responses in glioblastoma. Wan et al. [
19], firstly report that SLFN5 inhibits cancer migration and invasiveness in several common cancer cell lines by repressing MT1-MMP expression via the AKT/GSK-3β/β-catenin signalling pathway, suggesting that SLFN5 plays wide inhibitory roles in various cancers. Taken together, these results suggest that the role of SLFN5 in cancer progression might be context dependent.
The role of SLFN family in immune regulation and immune cell proliferation and differentiation is closely related to a variety of autoimmune diseases [
20]. Given that tumors can be considered a state of immunodeficiency or immune dysregulation, it can be inferred that SLFN family proteins may also play an important role in tumor immunity. For instance, studies have shown that certain SLFN family protein such as SLFN5 which can inhibit the growth and invasion of cancer cells and promote cancer cells sensitivity to chemotherapeutics in some malignant tumors [
21,
22]. SLFN5 is widely expressed in normal melanocytes, renal cells, ovary cells, as well as their cancer counterparts [
23]. Although the basal expression is low in normal cells, the RNA and protein levels of SLFN5 change dramatically when malignant transformation occurs [
24]. However, the role of SLFN5 in ovarian cancer is still not yet completely determined.
The objection of this project was to explore the biological functions of SLFN5 in human ovarian cancer both in vivo and in vitro, to identify the molecular target of SLFN5 in HO-8910 and SKOV3 cell lines and to uncover the potential mechanism of SLFN5 which promotes ovarian cancer development, in an attempt to provide a novel perspective and the oretical basis for clinical early diagnosis and therapy of ovarian cancer.
Materials and methods
Data sources
The RNA-seq data for ovarian cancer patients was obtained from The Cancer Genome Atlas (TCGA), and downloaded from xena hubs
https://tcga.xenahubs.net. Epithelial-mesenchymal transition (EMT) status was defined by Da Yang et al. [
25]. Among 341 ovarian cancer patients in TCGA, 324 has EMT status, and patient characteristics was shown in Table
1.
Table 1
Clinical characteristics of study patients
Case Load | 341 | 324 |
Neoplasm staging |
Early phase | 29 (8.6) | 24 (7.5) |
Later phase | 310 (91.4) | 298 (92.5) |
TNM stage |
G1&G2 | 68 (20.4) | 67 (21.1) |
G3&G4 | 265 (79.6) | 251 (78.9) |
Age | 58.80 ± 11.13 | 58.73 ± 11.12 |
EMT |
Epithelium | 178 (54.9) | 178 (54.9) |
Mesenchyme | 146 (45.1) | 146 (45.1) |
Identification of survival-related genes
The difference of SLFN5 expression between EMT status was detected by t test and the analysis of covariance, and the latter was used to adjust for several confounding factors, such as age, stage and grade in this study. The expression of SLFN5 was divided into high-expression and low-expression groups based on the first quartile (25th quantile). The overall survival (OS) curves of two groups were estimated using Kaplan–Meier method and compared by log-rank test [
26]. Multivariate Cox proportional hazards model was used to explore the independent effect of SLFN5 expression on OS, which adjusted for confounding effects of age, stage and grade.
The co-expression genes of SLFN5 were identified using Spearman correlation, and false discovery rate (FDR) method was used to adjust for multiple comparisons [
27]. Genes with absolute correlation coefficients≧0.4 and FDR q value < 0.001 were identified as co-expression genes of SLFN5. The biological functions of these co-expression genes were explored using Gene Ontology (GO) enrichment analysis [
28] and significant GO items were selected based on FDR q value < 0.05.
Immune cells were inferred from the TCGA RNA-seq data using CIBERSORT algorithm [
29], and 22 distinct immune cells were obtained. Patients with
P value less than 0.05 were excluded from the study. Immune cells with the proportion of zero value larger than 0.5 were also excluded, and 13 immune cells were retained in the following analyses. The distribution differences of immune cells between high-expression and low-expression SLFN5 groups were detected using Wilcoxon rank sum test. All statistical analyses in this study were performed on R platform (Version: 3.6.0).
Tissue samples and ethical considerations. Tissue samples
A total of 27 human ovarian cancer tissues were obtained from patients who had surgery in the Affiliated Hangzhou First People’s Hospital of ZheJiang University School of Medicine from 2019 to 2022, and patients’ clinical data were obtained afterwards. All cases were included post review by pathologist and only where complete clinical and follow-up data was available. None of the 27 included patients underwent pre-operative local or systemic treatment. The study protocol was approved by the Institutional Review Board of the Hangzhou First People’s Hospital in China. Freshly harvested samples were immersed in RNAlater (Life Technologies, Shanghai, China) before snap freezing within 30 min post-surgery. All tissue samples were stored in liquid nitrogen until further use.
No patient had received chemotherapy before surgery. Four histological subtypes were included into the panel (serous (
n = 14), endometrioid (
n = 7), clear cell (
n = 4), and mucinous (
n = 2)). TNM classification (T = tumor,
N = lymph nodes, M = metastasis) was performed according to the Union for International Cancer Control (UICC). Lymph node involvement (N0 (
n = 11), N1 (
n = 16) and distant metastasis M0 (
n = 9), M1 (
n = 18) was evaluated. FIGO stage was determined (I, II (
n = 9), III,IV (
n = 18)) according to the criteria of the International Federation of Gynecology and Obstetrics (FIGO). Median patients’ age was 62 ± 12 years with a range between 31 and 88 years. During the study 0 deaths have been observed (The data was shown in Table
2).
Table 2
Correlation between SLFN5 expression and pathological parameters in ovarian carcinoma patients
Age at diagnosis(y) | | | | NS |
≦52 | 13 | 7 (53.8%) | 6 (46.2%) | |
> 52 | 14 | 5 (35.7%) | 9 (64.3%) | |
FIGO stage | | | | < 0.05 |
I and II | 9 | 2 (22.2%) | 7 (78%) | |
III and IV | 18 | 5 (27.8%) | 13 (72.2%) | |
Lymph node metastasis | | | | NS |
pN0/pNX | 11 | 6 (54.5%) | 5 (45.5%) | |
pN1 | 16 | 6 (37.5%) | 10 (62.5%) | |
Distant Metastasis | | | | < 0.05 |
pM0/pMX | 9 | 3 (33.3%) | 6 (66.7%) | |
pM1 | 18 | 4 (22.2%) | 14 (77.8%) | |
Histology | | | | NS |
Serous | 14 | 5 (45.45%) | 9 (56.25%) | |
Clear cell | 4 | 1 (25%) | 3 (75%) | |
Endometrioid | 7 | 2 (28.56%) | 5 (71.5%) | |
Mucinous | 2 | 1 (50%) | 1 (50%) | |
Ethical considerations
A total of 27 human ovarian cancer tissues were obtained from patients who had surgery in the Affiliated Hangzhou First People’s Hospital of ZheJiang University School of Medicine from 2019 to 2021, and patients’ clinical data were obtained afterwards. The classification of clinical staging and histological grading of ovarian cancer were determined according to the FIGO 2014 system. Approval from the research ethics committee was obtained prior to the study. In addition, written informed consent from the patients were obtained before experiment for the use of their samples.
Cell culture and treatment
Four human ovarian cancer cell lines (SKOV3, A2780, OVCAR3, HO8910), normal epithelial ovarian cells (IOSE80) were purchased from the cell bank of China Academic of Science. The SKOV3 cells were cultured in McCoy’s 5A Media (modified with tricine) supplemented with 10% fetal bovine serum (FBS). The OVCAR3 and IOSE80 cell lines were maintained in 90% RPMI 1640 with 10% FBS, and the OVCAR3 cells were cultured in 80% RPMI 1640 with 20% FBS, sodium pyruvate, and 0.01 mg/ml bovine insulin. All the cell lines were cultured in an atmosphere of 5% CO2 and 95% air at 37 °C.
Pathway enrichment analysis and literature search
Text mining was performed for the overlapping genes using Perl code. The published genes that were closely related with ovarian cancer were searched in the PubMed database. In addition, the overlapping genes were subjected to the Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis using the Database for Annotation, Visualization and Integrated Discovery (DAVID) online tool. Pathways with p < 0.05 and counts ≥ 2 were considered significant.
RNA extraction and quantitative real time polymerase chain reaction(qRT-PCR)
Total RNA was extracted from cells using the RNA iso Plus (Trizol) reagent (TaKaRa, Japan) and cDNA was synthesized using the PrimeScript™RT Master Mix(Perfect Real Time) kit (TAKARA, Japan) according to the manufacturer’s instructions. Real-time PCR was performed to evaluate the expression levels of SLFN5,SNAIL,SLUG,E-cadherin,N-cadherin,GAPDH in tumor cells. A total of 8 μl of cDNA was used as template in a final 20 μl PCR volume containing 1 μl forward primer,1 μl reverse primer, and 10 μl SYBR Premix EX Taq (2x). PCRs were run as follows: 50.0 °C for 3 min, 95.0 °C for 3 min, followed by 40 cycles of 95.0 °C for 10 s and 60.0 °C for 30 s. Following PCR, a melting curve was obtained at temperatures from 60 °C to 95 °C, at increments of 0.5 °C for 10 s. Primer sequences are listed in Table
3.
Table 3
The primer sequences in PCR analysis
SLFN5-hF | GAGGATCCCCGGGTACCGGTCGCCACCATGGGCAGCGACCCGAGCG |
SLFN5-hR | TCCTTGTAGTCCATACCGACCCACTCCTGCAGCGAGCG |
E-cadherin-hF | GCGTCCTGGCAGAGTGAATTTT |
E-cadherin-hR | GGCCTTTTGACTGTAATCACAAA |
N-cadherin-hF | ATCCTACTGGACGGTTCG |
N-cadherin-hR | TTGGCTAATGGCACTTGA |
SNAIL-hF | TCGGAAGCCTAACTACAGCGA |
SNAIL-hR | AGATGAGCATTGGCAGCGAG |
SLUG-hF | AAGCATTTCAACGCCTCCAAA |
SLUG-hR | GGATCTCTGGTTGTGGTATGACA |
FN(Fibronectin)-hF | CCATCGCAAACCGCTGCCAT |
FN(Fibronectin)-hR | CCATCGCAAACCGCTGCCAT |
GAPDH-hF | TGACAACTTTGGTATCGTGGAAGG |
GAPDH-hR | AGGCAGGGATGATGTTCTGGAGAG |
Transfection of siRNA SLFN5 siRNAs (Genechem, Shanghai, China) were used to downregulate SLFN5 expression. The two siRNA sequences were shown below:
-
SLFN5 siRNA-1: (forward)5'-GUGGUAUAUACUCCAGAGATT-3' and.
-
(reverse)5'-UUUCUGGAGUAUAUACCACTT-3';
-
SLFN5 siRNA-2: (forward)5'-GACUCAGACUCCAACGAAUTT-3'and.
-
(reverse)5'-AUUCGUUGGAGUCUGAGUCTT-3'.
SKOV3 cells、OVCAR3 cells、HO8910 cells、A2780 cells were transfected with SLFN5 siRNAs with Lipofectamine 2000 (Invitrogen, Carlsbad, CA, USA). Four to six hours post transfection, the cell culture medium was changed. After 48 h of transfection, SKOV3 cells were used for further examination.
Cell Invasion Assay(transwell)
For invasion assays, before seeding cells, 60 μl of Matrigel (BD Biosciences, San Diego, CA, USA) was placed on the upper surface of the 24-well transwell chamber (Corning, New York, USA). Cells (104) in 100 μl of RPMI 1640 medium were seeded in the upper chamber, and the lower chamber was filled with 600 μl of medium with 20% FBS. Twenty-four hours after incubation, cells were remaining on the upper surface which were removed using a cotton swab, while the invaded cells were fixed, stained and photographed. Five random fields of cells were selected and counted for further calculation.
Wound healing assay
OC cells were transfected with SLFN5-siRNA or treated with TGF-β1 and wound healing assay was performed as described previously [
30]. Briefly, highly confluent OC cells were serum starved and the wound was made through the cell monolayer using a 200 µL pipette tip. Following this, the cells were washed twice with 1X PBS to remove the non-adherent cells. The cells were then treated with TGF-β1 or transfected with SLFN5-siRNA (as mentioned) in a fresh serum-free medium. The cells were allowed to migrate for 48 h. Wound closure was monitored by visual examination and imaged every 24 h under microscope (EVOS, Invitrogen). The experiment was repeated twice.
Cell lysis and Western blot
Cells were lysed with RIPA buffer (Beyotime, Shanghai, China) to obtain total protein. Then, 30–50 μg of protein was separated in 10% SDS/PAGE gels and transferred to PVDF membranes, which were blocked with 5% fat-free milk. The membranes were then incubated overnight at 4℃ with a primary antibody and incubated at room temperature for one hour with a secondary antibody conjugated with horseradish peroxidase. In the end, the protein bands were examined with chemiluminescence assay.
Cells (600 cells/well)were seeded into 6-well plates with DMEM medium supplemented with 10% FBS and cultured for 14 days. Then, colonies were fixed with methanol at room temperature for 15 min and stained with 0.1% crystal violet for 15 min (Invitrogen, Carlsbad, CA), and the total number of visible colonies were counted.
Statistical analyses
SPSS 16.0 (IBM, USA) was used for the statistical analyses. Continuous data was expressed as the mean ± SD, and analysed by independent t-test between two groups. Among multiple groups, one-way ANOVA was applied, and Turkey test was applied as a post hoc test. The categorical data were compared via the Chi-squared or Fisher’s exact tests as appropriate. A p value < 0.05 was regarded as statistically significant.
Discussion
Ovarian cancer is one of the most mortal gynecological cancers; Since its late detection and chemoresistance, it is important to understand the pathogenesis of this malignant tumor [
32]. The early symptoms of ovarian malignant tumors are not obviously appeared because malignant ovarian tumor normally grows in secluded places. Despite advances in treatment management for ovarian cancer patients, the prognosis remains poor. The screening of potential biomarkers and a better understanding of the pathogenesis of ovarian cancer could contribute to the development of novel target therapies [
33]. Thus, in this study, we attempted to discover prognosis-related biomarkers and explore the related mechanisms underlying the development and progression of ovarian cancer.
In our study, 122 overlapping genes were identified as candidate genes related to EOC progression. After text mining, a total of 12 genes were found to be associated with EOC which are coexpression with SLFN5. GO pathway analyses showed that the translational initiation pathway (GO:0006413) was the most significant pathway involved with FAU,RBM4,POLR2G,NLRP3,TLR1,TLR6,TLR2,MRPL33, MRPS16, MRPL12,MRPL11,MRPL21,CHCHD1,TLR2 and MRPS16 have been reported to be associated with the development of ovarian cancer in previous studies [
34]. Among the Mitochondrial translational initiation pathway, the high expression of SLFN5 was closely related with poor survival of patients with ovarian cancer and SLFN5 was prominently overexpressed in the three ovarian cancer cell lines, making it a candidate gene for further analysis. To our knowledge, this is the first study to explore the clinical significance of SLFN5 in ovarian cancer.
It is well known that ovarian cancer cells are prone to metastasis; in this process, epithelial-to-mesenchymal transition (EMT) is a necessary step during detachment of tumor cells from the primary tumor site and attachment to metastatic sites [
35]. To ascertain the role of SLFN5 in migration, we observed that knockdown of SLFN5 in OVCAR3、HO-8910 and SKOV3 cells inhibited the migration of ovarian cancer cells, as assessed by scratch-wound assay. Then, we further checked the EMT markers. A switch from E-cadherin to N-cadherin is a key feature of EMT in ovarian cancer [
36]. E-cadherin is a transmembrane glycoprotein of the type-I cadherin superfamily. Its cytoplasmic part is linked to the actin cytoskeleton via the catenins.
Ovarian cancer is a significant threat to human health with high incidence and mortality among malignant tumors. Increasing findings have shown that human SLFN5 functions in malignant tumors, such as melanoma, renal cell carcinoma, and glioblastoma, where it seems to play differential roles, either inhibitory or permissive. Growing evidence tells us that human SLFN proteins are important in normal and malignant cells [
1,
2]. It has also been found to suppress migration and invasion of various cancer cell lines, including fibrosarcoma and renal clear-cell carcinoma cells, by inhibiting expression of membrane-type 1 matrix metalloproteinase(MT1-MMP), which degrades extracellular matrix, allowing cancer cells to migrate [
9]
.
Accumulating evidence in recent years has raised the possibility of important and unique functions for human SLFN proteins in normal and malignant cells [
1,
2]. SLFNs regulated the proliferation, invasion, apoptosis and chemotherapy-resistance in many types of cancer such as breast cancer which come straight to controll the transcription of ZEB1 [
37]. SLFN5 has been shown to inhibit invasion of renal clear-cell carcinoma and melanoma cells in response to IFN treatment [
21,
23]. In contrast, other studies have shown a correlation between high levels of SLFN5 and the malignant phenotype of several types of cancer [
21,
38,
39]. For example, in lung cancer, lentiviral-mediated stable knockdown and overexpression of the SLFN5 gene in a lung adenocarcinoma cell line to determine the role of human SLFN5 in growth, proliferation, and apoptosis. SLFN5 knockdown promoted lung cancer cell proliferation and growth both in vitro and in vivo, whereas overexpression of SLFN5 inhibited these processes. SLFN5 overexpression induces epithelial-mesenchymal transition through activation of the β-catenin/Snail/E-cadherin signaling pathway [
39]. In GBM, human SLFN5 promotes tumor cell migration and invasion in glioblastoma (GBM), by acting as a transcriptional repressor of IFN-generated. SLFN5-dependent transcriptional repression of STAT1 activity that may account for defective antitumor immune responses, raising the possibility of SLFN5 involvement in the pathogenesis of other malignancies as well [
24]. Importantly, we have also previously established a correlation between SLFN5 expression and glioma grade and overall prognosis of GBM patients [
24]. Moreover, intestinal metaplasia patients who overexpress SLFN5 exhibit a higher risk to develop gastric cancer [
38]. Taken together, the role of SLFN5 in tumorigenesis appears multifaceted and disease-dependent, necessitating careful characterization of SLFN5 in each individual biological context.
Ovarian cancer is one of the most common tumors of the female reproductive system [
40] which is associated with poor prognosis. EMT is a biological process during which epithelial cells acquire a mesenchymal phenotype through specific path ways. Multiple tumor microenvironment cytokines, including epidermal growth factor, endothelin 1 and bone morphogenetic protein, which regulate related signaling pathways to promote cancer development and metastasis [
40]. EMT is important in embryonic development which is related to cancer progression and metastasis [
41,
42]. EMT is indispensable to new characteristics of tumor cells required for invasiveness and vascular endosmosis during the metastasis. It is a convertible course during which the epithelial cells lose epithelial properties and acquire mesenchymal characteristics by disassembly of cell–cell junctions, loss of cell polarity, and reorganization of the cytoskeleton, thereby promoting cells to acquire increased motility. EMT can be defined according to EMT-associated markers, such as mesenchymal-specific markers, epithelial-specific markers and transcription factors [
41]. It was previously showed that unusually E-cadherin expression is closely involved in the pathogenesis and development of ovarian cancer, and research into the regulation of E-cadherin expression in ovarian cancer has become a focus of interest.
In the present study we provide evidence that SLFN5 expression increased with malignancy grade and is highest in ovarian tumors. Further, high levels of SLFN5 expression correlate with worse prognosis in ovarian cancer patients. Importantly, our data show that targeting SLFN5 blocks ovarian tumor growth both in vitro and in vivo. Nevertheless, we provide evidence that the antitumor effects observed after SLFN5 depletion are mediated, at least in part, by interfering with cell cycle progression. This is important, as ovarian tumors are characterized by the presence of cell cycle dysregulation, a hallmark of several types of cancer, [
42,
43] and the identification of SLFN5 as a new promoting factor of S phase progression may help expand the currently available armory of cell cycle inhibitors [
44,
45].
To conclude, in the present study, we found that SLFN5 is upregulated in ovarian cancer tissues but the level of SLFN5 can vary depending on TNM grade. In addition, cancer histological type may influence the expression of SLFN5. In tissue samples, we found that a higher number of patients had a high expression of SLFN5 in serous ovarian cancer compared with mucinous, clear cell, and endometrioid ovarian cancer. SLFN5 is also upregulated in ovarian cancer cell lines. SLFN5 knockdown decreases cell growth, migration, and invasion. Furthermore, TGF-β1 can increase SLFN5 expression and induce ovarian cell EMT. However, knockdown of SLFN5 inhibits EMT. Thus, SLFN5 levels may be valuable for the prognosis of metastasis and SLFN5 may be a therapeutic target for prevention and intervention of metastasis of ovarian cancer.
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