Background
Endometrial cancer (EC) is the fourth most common malignancy in women, which accounts for more than 76,000 deaths among women each year worldwide [
1]. According to the latest global cancer data from the World Health Organization in 2020, EC is one of the top 10 new cancer cases, with more than 80,000 new patients diagnosed in China. Five-year overall survival (OS) rates for EC vary according to the stage at diagnosis. Most EC patients are diagnosed in early stage and have a good prognosis with 5-year OS rates of nearly 90% [
2]. Unfortunately, roughly 30% of individuals diagnosed with advanced stage (stage III or IV) have a poor prognosis, with a worse 5-year survival rate of 60% and 20%, respectively [
3].Thus, great efforts are needed to identify new clinically feasible molecular biomarkers for EC diagnosis and then to improve the outcome of EC.
Synaptotagmin-like protein 1 (SYTL1, also named JFC1, SLP1), is a member of the synaptotagmin-like protein family of secretory factors characterized with a Rab-binding domain at N-terminal and two tandem-C2 domains at C-terminal [
4]. SYTL1 differentially regulates the secretion of prostate-specific antigen and prostatic-specific acid phosphatase [
5]. SYTL1 is involved in controlling Rab8 membrane dynamics by binding specifically to Rab8 [
6]. In granulocytes, SYTL binding to Rab27A constitutes key components of the secretory machinery of azurophilic granules [
7] and is involved in amylase secretion [
8]. In platelets, SYTL1 interacts with GTPase-activating protein Rap1GAP2 to regulate dense granule secretion [
9]. During exocytosis, SYLT1 interacting with the RhoA-GTPase-activating protein Gem-interaction protein regulates vesicular trafficking through cortical actin [
10]. Previous study was mainly focused on the function of SYTL1 about the regulation of secretion and exocytosis. However the role of SYTL1 in tumor progression remains unclear. In prostate cancer cell lines, SYTL1 is transcriptionally activated by nuclear factor-κB and up-regulated by tumor necrosis factor α[
11]. It is reported that SYTL1 binds to the plasma membrane via interacting with phosphatidylinositol 3,4,5-trisphosphate (PIP3) with ATPase capacity [
12].The phosphoinositide 3-kinase and its product PIP3 play a central role incellular physiology and mediate critical cellular processes, such as cell proliferation, survival and cytoskeletal reorganization during tumor development[
13].We guess that SYTL1 might be involved in cancer progression. Thus, the objective of the current study is to evaluate the diagnostic and prognostic value of SYTL1 expression in human EC through bioinformatics analysis and experiments.
We evaluated the diagnostic and prognostic value of SYTL1 expression in UCEC by analyzing the patients’ data from TCGA. We employed the LinkedOmics and STRING database to analyze the biological function of SYTL1. In addition, the correlation between SYTL1 expression and the methylation levels was performed by using cBioportal, UALCAN, TCGA Wanderer and MethSurv databases. We further assessed the link between SYTL1 and tumor-infiltrating immune cells by single sample GSEA method from R package GSVA. Furthermore, we carried out in vitro experiments to verify the results of bioinformatics analyisis. Our results demonstrated that SYTL1 might be a potential diagnostic and prognostic marker in EC.
Discussion
EC is the most common gynecological cancer. Five-year survival rates of EC patients are strictly related to stage at diagnosis. Metabolomics, as an emerging “omics”, has been a promising test for a non-invasive diagnosis of EC. Some reports showed that serum metabolites were able to predict the presence of EC progression and recurrence and pathological characteristics [
16]. Additionally, the increasing mortality is closely related with a poorly reproducible histological risk stratification. The TCGA molecular groups and the classic clinicopathological factors (such as myometrial invasion, histotype or lymph vascular space invasion) have been incorporated into a novel risk stratification model of EC by the European Society of Gynaecological Oncology (ESGO), the European Society for Radiotherapy and Oncology (ESTRO) and the European Society of Pathology (ESP) [
17,
18]. New reports revealed the distribution and prognostic value of the TCGA groups, and proposed the improvement in the molecular-based risk stratification [
19]. Preoperative molecular classification is very useful to guide clinical management by providing earlier and more reliable prognostic information. However, the management of MMR-deficient and no specific molecular profile carcinomas is still difficult. Therefore, the development of novel molecular biomarkers for EC diagnosis and prognosis assessment represents one of the greatest challenges.
The proteins containing the C2 domain play important roles mainly in membrane fusion, exocytosis, cellular trafficking, cell signaling and cancers [
20]. SYTL1is a member of tandem C2 domains containing proteins and it is previously revealed to induce the secretion of prostate-specific antigen by prostate cells [
5] and secretion of azurophilic granules by granulocytes [
7]. Furthermore, SYTL1 regulates exocytosis of secretory lososomes by CTL [
4] and blocks amylase secretion by pancreatic acinar cells [
8]. Through a literature search, we found that SYTL1 expression and its potential diagnostic and prognostic impact on UCEC has not been explored. In our work, we comprehensively analyzed the diagnostic and prognostic value of SYTL1 in UCEC based on TCGA data and the molecular features of protein phosphorylation, genetic alteration and DNA methylation. In our study, we found that SYTL1 is highly expressed in EC tissues than in adjacent normal tissues and SYTL1 expression is negatively associated with the SYTL1 DNA methylation. In addition, we also found that increased SYTL1 expression is correlated with various clinicopathologic characteristics and the number of immune cell infiltration. Taken together, this study indicated the potential role of SYTL1 during EC pathogenesis and revealed the value as a potential diagnostic and prognostic biomarker in EC.
To data, no research has reported a role of SYTL1 in EC. In the present study, we evaluated the SYTL1 expression profile on the basis of various databases including TCGA and HPA. According to the analysis, the expression of SYTL1 on mRNA and protein levels in UCEC tissues was higher than that in normal tissues, and the results were confirmed by in vitro experiments. Furthermore, ROC results indicated the potential diagnostic value of SYTL1 in EC (AUC = 0.801). Logistic regression analysis revealed that the expression level of SYTL1 was closely associated with the clinical parameters including age, clinical stage, histological type, and histologic grade. Univariate and multivariate analysis further showed that SYTL1 expression was an independent factor for UCEC patient’s prognosis. KM plotter analysis revealed that patients with elevated SYTL1 had longer OS, as well as clinical stage (Stage I &Stage II), histological grade (G3), and tumor invasion. Therefore, our study provided new evidence that SYTL1might be a diagnostic and prognostic biomarker for good survival in UCEC. These findings reveal the role of SYTL1 from a new perspective and enrich the research of SYTL1.
SYTL1is a member of the synaptotagmin-like protein family of secretory factors and it is mainly regulates secretion and exocytosis. Previous study indicated that SYTL1 is transcriptionally activated by nuclear factor-κB and up-regulated by tumor necrosis factor αin prostate cancer cell lines [
11]. In addition, SYTL1 could bind to the plasma membrane via interacting withPIP3 [
12]. Importantly, PIP3 play a central role in critical cellular processes, such as cell proliferation and survival during tumor development [
13]. These evidences revealed that SYTL1 might be involved in cancer progression. Our functional enrichment analysis found that SYTL1 was closely correlated with ribosome, Hippo signaling pathway, Cell cycle and RNA transport. Additionally, our in vitro experiments indicated that ectopic expression of SYTL1 affected cell proliferation and invasion in Ishikawa and AN3CA cells, which verified the results of bioinformatics analysis. In this study, KEGG functional analysis by the next high-throughput RNA-sequencing indicated that the upregulated differentially expressed genes were mainly involved in leukocyte migration, regulation of leukocyte migration, and regulation of leukocyte chemotaxis. Leukocytes migration are critical for an anti-tumor immune response [
21]. These results showed that an increase on SYTL1 expression might activate leukocyte migration and chemotaxis to suppress the progression of EC.
Previous study reported that AKT phosphorylated SYTL1 at serine 241, and the phosphorylation of SYTL1 may regulate vesicular trafficking by limiting the availability of SYTL1 to the membrane-bound Rab27A [
22]. However, little research reported the relationship between SYTL1 phosphorylation and tumorgenesis. In our research, we found at least 4 predicted phosphorylation sites in EC and a high expression level of SYTL1 phosphorylation level at the S392 locus in the primary tumors compared with normal tissues. These data revealed that the phosphorylation of SYLT1 at S392 might be involved in EC development. Several findings related to the regulation of exocytosis by protein phosphorylation have been accomplished in synaptic membrane-trafficking studies. Additional experiments are required to further evaluate the potential role of SYTL1 phosphorylation at the S392 site and to explore the related mechanism.
DNA methylation of promoter regions is an important mechanism during carcinogenesis [
23]. Aberrant DNA methylation has been reported to be an early step during EC development [
24]. Via UALCAN portal and TCGA Wanderer database, we found that the difference in promoter methylation level was statistically significant between tumor and normal tissues. We also found that the methyaltion level of nine CpG sites significantly correlated with survival probability. Therefore, it is possible that decreased methylation of SYTL1 DNA could be used as a factor in assessing prognostic confidence.
Tumor microenvironment, consists of immune cells, mesenchymal cells, endothelial cells and inflammatory mediators, has a significant impact on tumor development, chemoresistance and clinical outcomes [
25]. Previous study showed that tumor microenvironment in EC has a significant prognostic value and plays a role in resistance to treatment [
26,
27]. NK cells, DCs, macrophages and neutrophils-and adaptive B cells and T cells, including cytotoxic T lymphocyte (CD8 + T or CTL) cells, helper (CD4 + T) cells and NT K cells-immune cells are involved in EC development [
28,
29]. In our study, we found that SYTL1 expression had a significantly correlation with the number of various immune cells, including NK CD56bright cells,Th17, Neutrophils, Cytotoxic cells, NK CD56dim cells,pDC, iDC, T cells, Treg cells, Macrophages, T helper, Tcm, Tgd, Th2 and aDCs. The strongest correlation was observed between the number of NK CD56bright cells (positive correlation),Macrophages (negative correlation) and SYTL1 expression. It is also reported that RhoA-GAP GMIP associates with the secretory factor JFC1 and regulates actin remodeling and exocytosis in innate immune cells [
9]. NK cells are important factors during the pathogenesis of inflammatory and autoimmune disease [
30]. NK CD56bright cells mainly mediate antitumor response as a potential cancer immunotherapy [
31]. Macrophages are critical drivers for cancer initiation and progression, and the infiltration of macrophages in tumors closely correlates with poor prognosis [
32]. Our study indicated that SYTL1 may have a potential influence on EC immunity by regulating immune cell infiltration, ultimately affecting the patient prognosis.
Taken together, our study indicated the statistical correlation between SYTL1 expression and clinical prognosis, DNA methylation and immune cell infiltration in EC. Although these data provided evidence that SYTL1 could be used as a promising diagnostic and prognosticbiomarker in EC, it has some limitations. Firstly, more experiments need to be carried out to explore the specific function of SYTL1 in tumor microenvironment. Secondly, although we found that ectopic expression of SYTL1 modulates cell proliferation and invasion, the detailed mechanism remains unknown. Thus, further studies are needed to be performed to investigate the pathways of action of SYTL1 in EC.
Materials and methods
Data sources
The pan-cancer RNA-seq data were downloaded from the publicly available TCGA official website (
https://genomecancer.ucsc.edu/).Level 3 HTSeq-fragments per kilobase per million (FPKM) of Uterine Corpus Endometrial Carcinoma (UCEC) samples including 552 tumor tissues and 35 adjacent normal tissues were obtained from TCGA website for further analysis. The normalized microarray GSE17025 obtained from the GEO database contained 12 normal endometrium samples and 91 EC samples [
33].
Gene expression analysis
The expression of SYTL1 between tumor tissues (Cervical squamous cell carcinoma and endocervical adenocarcinoma (CESC),Ovarian cancer (OV), UCEC) and normal tissues were analyzed in GEPIA database (Gene Expression Profiling Interactive analysis,
http://gepia.cancer-pku.cn/).ENCORI (The Encyclopedia of RNA Interactomes,
http://starbase.sysu.edu.cn/) [
14] and the UALCAN portal (
http://ualcan.path.uab.edu/) [
34] databases provide the differential expression analysis of SYTL1 in UCEC. The Human Protein Atlas (
https://www.proteinatlas.org/) provides a broad amount of proteomic and transcriptome information of district human samples. Protein immunohistochemistry of SYTL1 in normal human tissues and UCEC tissues were downloaded from HPA.
Survival and clinicopathological correlation analysis
UCEC patients were divided into 2 groups (high- and low-risk groups) according to the median expression of SYTL1 in further study. The relationship between SYTL1 expression and clinicopathological characteristics was delineated using the R-package “ggplot2”. According to the high and low-risk value, a survival curve was delineated by using the R-package “survminer” and “survival”. The clinicopathological correlation analysis was mainly performed using the R-pakcage “limma” and “ggpubr”. The association between SYTL1 expression and survival was verified by Kaplan-Meier plotter tool (
http://kmplot.com/analysis/) [
35].
LinkedOmics database analysis
The LinkedOmics database (
http://www.linkedomics.org/login.php) contains multi-omics data from all 32 TCGA Cancer types and 10 CPTAC cancer cohorts [
36].We screened the differentially expressed genes linked to SYTL1in the TCGA UCEC cohort by using the “LinkFinder” module. Gene Oncology (GO) and Kyoto Encyclopedia of Gene and Genomes (KEGG) pathways were analyzed by using “Function” module.
SYTL1 DNA methylation analysis
TCGA analysis in UALCAN portal was used to analyze the SYTL1 promoter methylation levels in UCEC. TCGA Wanderer, which offers level 3 TCGA data for methylation arrays (450k Infinium chip), was employed to analyze gene expression and DNA methylation profiles from TCGA. MethSurv (
https://biit.cs.ut.ee/methsurv/) web tool was used to examine the correlation between individual probes with methylation changes and survival probability [
37].
Immune infiltration analysis using ssGSEA and TISIDB
The spearman correlation between SYTL1 and 24 types of immune cells were evaluated by suing the GSVA package in R. Furthermore, TISIDB, an online web portal for tumor and immune system interaction was used to analyze the distribution of SYTL1 expression across immune and molecular subtypes in “Subtype” module [
38].
Samples collection
A total of 4 pairs of EC and adjacent tissues were collected from patients who underwent surgical resection at Qilu Hospital of Shandong University (Qingdao) from May 2018 to October 2019. EC tissues were collected according to the inclusion criteria: ① complete pathological and clinical data, ②no hormone therapy, intrauterine device usage, chemotherapy or radiotherapy for at least 6 months prior to surgery. EC tissues were excluded according to the criteria: ① patients with malignant tumors of other systems, ② patients with metastatic cancers from other reproductive systems, ③ patients with a history of other hospital treatment. All specimens were evaluated by at least two pathologists according to the World Health Organization guidelines. This work was approved by the Ethics Committees of Qilu Hospital of Shandong University (Qingdao) ([Approval no. (KYLL(2016-KS-173). Permission from all patients was obtained prior to the surgery.
Cell culture and transfection
Human endometrial epithelial cells (hEEC, #354984), EC cell lines Ishikawa (#338359) and AN3CA (#339020) were obtained from BeNa Culture Collection (Xinyan, Henan, China). EC cell lines HEC-1-B (ZQ0364) was purchased from Shanghai Zhong Qiao Xin Zhou Biotechnology Co.,Ltd. (Shanghai, China). Cells were cultured at 37°C with 5% CO2. Ishikawa cells were incubated with Dulbecco’s modified eagle medium (DMEM) supplement with 10% fetal bovine serum (FBS). AN3CA and HEC-1-B cells were cultured with Eagle’s Minimal Essential Medium (EMEM, Gibco, Carlsbad, CA, United States) containing 10% FBS. For SYTL1 knockdown, Ishikawa cells were transfected with three small interfering RNAs targeting SYTL1 (siRNA#1, siRNA#2 and siRNA#3) and negative control (NC) siRNA. The siRNA sequences were listed as follows: NC siRNA sense: 5’-uucuccgaacgugucacgutt-3’, antisense: 5’-acgugacacguucggagaatt-3’. SYTL1 siRNA#1 sense: 5’-gcugcugugaaagagaaggaatt-3’, antisense: 5’-uuccuucucuuucacagcagctt-3’; SYTL1 siRNA#2 sense: 5’-cccuguguucaaucacaccautt-3’, antisense: 5’-auggugugauugaacacagggtt-3’; SYTL1 siRNA#3 sense: 5’-ccucccggauaagcagagcaatt-3’, antisense: 5’-uugcucugcuuauccgggaggtt-3’. For overexpression of SYTL1, AN3CA cells were infected with LV-GFP (Vector) or LV-SYTL1-GFP (SYTL1OV) (GENECHEM, Shanghai, China) according to the manufacturer’s protocol.
Western blot
Proteins were extracted from tissues by using RIPA buffer (Sigma-Aldrich; Merck KGaA). Proteins were separated by 10% sodium dodecyl sulfate-polyacrylamide electrophoresis and transferred onto polyvinylidene difluoride membrane (Roche, Basel, Switzerland). The membranes were incubated with mouse monoclonal antibodies against SYTL1 (1:1000 dilution; #sc-365,933, Santa Cruz Biotechnology, Inc.) and against GAPDH (1:1000 dilution, #ab59164, Abcam) overnight at 4 °C. After being washed with TBST, the membranes were incubated with rabbit anti-mouse IgG H&L (HRP) (1:5000 dillution; #ab6728, Abcam) at 37 °C for 1 h. The membranes were visualized using an enhanced chemiluminescence system (ImageQuant LAS4000) by the normalization to GAPDH. The band density was determined by relative densitometry using ImageJ Software version 1.50 (National Institutes of Health).
Cell counting kit-8 (CCK-8) assay
Ishikawa or AN3CA cells were seeded into 96-well plate at the density of 3,000 cells/well. After 1, 2, 3 and 4 days, 10 µL of CCK-8 reagent was added into each well and incubated at 37 °C for 1 h. The optical density value was measured at the wave length of 450 nm by using a microplate reader.
Ishikawa and AN3CA cells were seeded into a 6-well plate. After 14 d, cells were fixed with methanol for 15 min and stained with 0.1% crystal violet for 30 min.
Cell invasion assay
Invasion assay was conducted by using the 24-well transwell chambers with 8 μm proe size (COSTAR, USA). The inserted top side of the chambers containing 150 µL of the serum-free medium was inoculated with 3 × 104 cells, whereas 600 µL of the medium with 10% FBS was added to the lower chamber. After 24 h, the cells invaded to the bottom of the membrane were fixed with 4% paraformaldehyde for 30 min and stained with 0.1% crystal violet for 30 min. The stained cells were photographed and counted under a microscope using a 100× magnification.
High-throughput RNA-sequencing
AN3CA cells were infected with LV-GFP or LV-SYTL1-GFP lentiviral particles. After 48 h, total RNA was isolated by using TRIzol. Quality control of the total RNA samples were quantified using a NanoDrop ND-1000 instrument and qualified using agarose gel electrophoresis. One to two µg total RNA was used for the preparation of the sequencing library according to the following steps: ① mRNA was purified by oligo-dT magnetic beads; ② RNA-seq library was prepared after First Strand cDNA synthesis, Second Strand cDNA synthesis, End Repair, Ligate adapters and PCR amplification. ③ The completed libraries were qualified by Agilent 2100 Bioanalyzer. ④ FastQ data were obtained by high-throughput sequencing for both ends (2 × 150 bp) on Illumina HiSeq instrument.
Statistical analysis
Univariate and multivariate logistic regression analysis were performed to calculate the associate between SYTL1 expression and clinicopathological characteristics using Cox proportional hazard models. The correlation between DNA methylation probes and SYTL1 expression was tested using the Spearman (r) correlation method. All statistical analysis was performed with R statistical software (version 3.6.3) and SPSS software (version 24.0). A P value less than 0.05 is considered statistically significant.
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