Journal of Immunology Research
Volume 2021 (2021), Article ID 5574176, 21 pages
https://doi.org/10.1155/2021/5574176

Research Article

Comprehensive Analysis of Prognostic Value of MEX3A and Its Relationship with Immune Infiltrates in Ovarian Cancer

Panpan Zhang, Tong Su, and Shu Zhang

Department of Gynecology and Obstetrics, Shanghai Key Laboratory of Gynecology Oncology, Renji Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai 200127, China

Correspondence should be addressed to Shu Zhang; drzhangshu@126.com

Received 13 February 2021; Revised 3 May 2021; Accepted 20 May 2021; Published 4 June 2021

Academic Editor: Jian Song

Copyright © 2021 Panpan Zhang et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Abstract.

MEX3A is a critical RNA-binding ubiquitin ligase that is upregulated in various types of cancer. However, the correlations of MEX3A with prognosis and its molecular mechanism in ovarian cancer (OC) remain unclear. The expression level, prognostic values, and the genetic variations of MEX3A were analyzed via Gene Expression Profiling Interactive Analysis (GEPIA) Oncomine, Kaplan–Meier plotter, and cBioPortal. We used the LinkedOmics database to investigate the functions of MEX3A coexpressed genes and performed visualizing gene interaction network analysis on the GeneMANIA website. The correlations between MEX3A and cancer immune infiltration were analyzed by the Tumor Immune Estimation Resource (TIMER) site and the TISIDB database. Furthermore, in vitro analysis was performed to evaluate the biological functions of MEX3A in OC cells. Our study showed that the expression of the MEX3A in OC was higher than in normal tissues; it had the greatest prognostic value in OC, and strong physical interaction with PABPC1, LAMTOR2, KHDRBS2, and IGF2BP2, which indicated the association between MEX3A and immune infiltration. We also found that MEX3A was negatively related to infiltrating levels of several types of immune cells, including macrophages, neutrophils, dendritic cells (DCs), B cells, and CD8+ T cells. Additionally, in vitro experiments demonstrated that MEX3A promotes proliferation and migration in OC cells. Taken together, MEX3A might influence the biological functions of OC cells by regulating the immune infiltration in the microenvironment as a prognostic biomarker and a potential therapeutic target.

1. Introduction

Ovarian cancer (OC) is a common gynecological malignancy with high mortality. More than 70% of patients with OC are diagnosed with advanced-stage cancer (III and IV) [1]. Although the development of surgery and chemotherapy in ovarian cancer has been advanced in recent decades, the benefits of traditional treatment are limited [2]. Recently, immunotherapy has offered a novel and promising therapeutic strategy. Still, immunotherapy, which has been developing rapidly resulting in major breakthroughs in many areas, cannot achieve a good treatment effect because of a special tumor immune microenvironment [3]. Like many other solid tumors, OC is immunogenic, and the imbalance between immune activation and immune suppression can lead to tumorigenesis and cancer progression. Thus, it is necessary to select and identify reliable immune-related biomarkers and novel targets for immunotherapy strategies necessary to diagnose OC early.

MEX3A is an important component of the Mex3 family, which has a conserved region of about 70 amino acids, including MEX3A, MEX3B, MEX3C, and MEX3D [4]. MEX3A is a kind of RNA-binding protein (RBPs), which has the highly conserved RNA-binding domain and a C-terminal RING finger domain that are involved in posttranscriptional regulatory mechanisms [5]. Recently, MEX3A has been reported as a novel biomarker promoting proliferation and migration in various cancers such as pancreatic ductal adenocarcinoma (PDA), liver cancer, and colorectal cancer [6–8]; yet, its role in OC is still unclear.

In this study, we investigated the mRNA expression, mutation patterns, and prognosis value of MEX3A in OC for the first time based on large database analyses including Oncomine, GEPIA, cBioPortal, PrognoScan, and the Kaplan–Meier plotter. We also explored the function of the coexpression genes with MEX3A to clarify the potential mechanism in OC by GO and KEGG. In addition, we revealed the potential relationship between the expression of MEX3A and immune infiltration in the OC microenvironment via TIMER and TISIDB. We have further demonstrated that MEX3A enhanced tumor proliferation and migration in vitro. Collectively, our findings revealed the important role of MEX3A and provided a novel target and a valuable insight into the underlying mechanism between MEX3A and tumor-immune interactions in OC.

2. Materials and Methods

2.1. Oncomine Analysis

The MEX3A mRNA expression level was analyzed in OC by the Oncomine platform (http://www.oncomine.org/), a publicly accessible, online cancer microarray database with 715 data sets and 86,733 samples that allow for a powerful genome-wide expression analysis [9]. We selected avalue of 0.01 and a fold change of 2 as the threshold, and ranked genes in the top 10% as significant.

2.2. GEPIA Analysis

Gene Expression Profiling Interactive Analysis (GEPIA) is an interactive web used to analyze the RNA sequencing expression, including The Cancer Genome Atlas (TCGA) tumor sample information and Genotype-Tissue Expression (GTEx) normal sample information. GEPIA provides a series of key interactive and customizable functions by using a standard processing pipeline (http://gepia.cancer-pku.cn) [10].

2.3. cBioPortal Analysis

The cBioPortal for Cancer Genomics (http://cbioportal.org) provides an online resource to explore, visualize, and analyze complex cancer genomics and clinical profile data from TCGA [11]. In this study, the cBioPortal was used to access genetic variations in MEX3A (amplifications, deep deletions, and missense mutations), DNA copy number alterations, and mRNA expression -scores (RNA Seq V2 RSEM). The tab OncoPrint shows an overview of genetic alterations for each sample in MEX3A. Besides, coexpression datasets were analyzed according to the online instructions of cBioPortal, and the R package was used for further enrichment analysis.

2.4. LinkedOmics

LinkedOmics (http://www.linkedomics.orglogin.php) is a publicly available web tool used to provide multiomics data of 32 TCGA cancer types [12]. We used the linkInterpreter module to derive biological insights into coexpressed gene enrichment by using Pearson’s correlation coefficient. These genes were presented in volcano plots and heat maps.

2.5. Functional Enrichment Analysis

To further explore the functions of MEX3A, Gene Ontology (GO) enrichment analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis were performed in R statistical computing environment.

2.6. GeneMANIA

GeneMANIA (http://www.genemania.org) is a flexible, friendly web interface that is used for visualizing gene interaction networks and evaluating gene function [13]. It enables analysis of gene lists and prioritizes the marked genes for functional assays associated with MEX3A. The sources of the edge of the network, which represent the following bioinformatics methods, namely, physical interaction, coexpression, colocation, genetic interaction, and website prediction, were set.

2.7. TIMER Database Analysis

To obtain the MEX3A expression and correlation between MEX3A and immunity cells in TCGA datasets, an online analytical tool called “Tumor Immune Estimation Resource (TIMER)” was used. TIMER is an online dataset used for evaluating the relationship between clinical associations, mutation, SCNA, and infiltration of different immune cells (B cells, CD4+ T cells, CD8+ T cells, neutrophils, macrophages, and dendritic cells) in diverse cancer types [14]. The survival module also showed the Kaplan–Meier plotter and provided the multivariable Cox regression analysis of clinical factors (age, stage, and tumor purity). Once all conditions were defined, TIMER outputs revealed the Cox regression results, including hazard ratios (HR), 95% confidence intervals (CI), and statistical significance () automatically.

2.8. TISIDB Analysis

TISIDB (http://cis.hku.hk/TISIDB) is a user-friendly web portal, which contains a summary of 988 immune-related antitumor genes for 30 TCGA cancer types [15]. The associations between gene expression and immune features, including lymphocytes, immunomodulators, subtypes, and chemokines, were calculated by high-throughput data analysis. In this research, we used the TISIDB web to analyze the correlations between MEX3A expression and clinical stages, lymphocytes, and subtype immunomodulators in OC.

2.9. Kaplan–Meier Plotter Analysis

The Kaplan–Meier plotter (http://www.kmplot.com) is a common tool for biomarkers used to assess survival and prognosis, which includes gene expression data and survival information of 1,816 clinical tissue samples from OC patients [16]. The overall survival (OS) and progression-free survival (PFS) of OC patients were determined by dividing two groups (high vs. low expression) of patients by median. In addition, we further investigated OS and PFS of different histological subtypes (endometrioid and serous) in MEX3A by using the Kaplan–Meier method. These data were evaluated with a hazard ratio (HR), 95% confidence intervals (CI), and log-rank value.

2.10. PrognoScan Database Analysis

The relationship between MEX3A expression and prognosis in OC was analyzed by the PrognoScan database (http://www.abren.net/PrognoScan/), such as OS and PFS [17]. The threshold was adjusted to a Cox value < 0.05 or corrected value < 0.5.

2.11. Cell Culture and Transfection

The ES2 cells were obtained from the Type Culture Collection of the Chinese Academy of Sciences (Shanghai, China) and cultured in Dulbecco’s Modified Eagle’s Medium (DMEM; HyClone; GE Healthcare Life Sciences) with 10% FBS at 37°C and 5% CO₂. ES2 cells (to 70% confluence) were seeded on 6-well plates transfected with MEX3A siRNAs designed and synthesized by GenePharma (Shanghai, China), which were transfected into the cells using Lipofectamine 2000 (Invitrogen; Thermo Fisher Scientific) according to the protocols for the interference expression of MEX3A; the cells were cultured for 48 h or 72 h for further assays.

2.12. Cell Counting Kit-8 (CCK-8) Assay and Colony Formation Assays

Transfected cells were seeded on a 96-well plate at a density of cells/well. The CCK-8 solution (10 μl; Dojindo Laboratories, Kumamoto, Japan) was then added to each well of the plate. The plate was incubated for 2 h in the incubator, and the absorbance at each wavelength of 450 nm was measured using an automatic enzyme-linked immune detector.

For the colony formation assay, transfected cells were seeded into 6-well plates. One week later, the cells were fixed with 4% paraformaldehyde and stained with 0.5% (/) crystal violet. Then, cell clones were photographed and counted. These experiments were performed in triplicate.

2.13. 5-Ethynyl-2-Deoxyuridine (EdU) Staining Assay

Collected cells were seeded on 24-well plates at a density of cells/well and incubated for 24 h. According to the protocol of the EdU Kit (BeyoClick™ EDU Cell Proliferation Kit with Alexa Fluor 488; Beyotime, Shanghai, China), after transfection, EdU was added 1 : 1,000 in the cell medium for 2 h at 37°C. Cells were fixed with 4% paraformaldehyde for 15 min and treated with 0.3% Triton-X for 10 min at room temperature. Then, the cells were incubated for 30 min with a Click reaction cocktail in the dark. Nuclei were stained with Hoechst 33342 for 10 min. Photographs were taken in three randomly selected fields with an Olympus (Tokyo, Japan) microscope to analyze proliferation rates. Each experiment was performed at least three times.

2.14. Transwell Assay and Wound Healing Assay

Cells ( cells/well) were incubated in 100 μl culture medium and seeded on the Transwell inserts (Corning Glass Works; Corning, NY, USA) with 8 μm pores to determine the migration ability of the cells. A 600 μl culture medium was added to the lower chamber. After 48 h, the inserts were fixed with 95% ethanol, and 0.5% (/) crystal violet was used for staining. Migrated cells were counted in five nonoverlapping locations.

To analyze wound healing, we seeded transfected cells on 6-well plates. When the cell density reached 80-100%, we scraped cells at the bottom of the wells using a sterile 200 μl pipette tip to form a linear gap and culture treated cells with FBS-free DMEM. After 24 h, images of the wells were taken with an inverted fluorescence microscope. All assays were repeated at least three times.

2.15. Quantitative Real-Time PCR

Total RNA was extracted using the TRIzol Reagent (Invitrogen; Thermo Fisher Scientific). According to the manufacturer’s instructions, the concentration of total RNA was measured using Thermo Fisher Scientific NanoDrop ND-100. cDNA was synthesized using the SYBR PrimeScript RT-PCR Kit (Takara Bio, Inc., Japan). Real-time PCR was carried out using a Thermal Cycler Dice™ Real-Time system Tp800 (Takara Bio, Inc.). The primer sequences designed for MEX3A and β-actin are as follows (5-3): MEX3A, forward, TGGAGAACTAGGATGTTTCGGG, and reverse, GAGGCAGAGTTGATCGAGAGC; and β-actin, forward, CATGTACGTTGCTATCCAGGC, and reverse, CTCCTTAATGTCACGCACGAT. The mRNA expression of the target gene was analyzed using the method.

2.16. Western Blotting

Total protein was obtained from cells using ice-cold RIPA buffer mixed with protease inhibitor cocktails (Roche), and concentration was assayed by a BCA assay. Fifty micrograms of denatured protein was separated by 10% SDS-PAGE and transferred onto PVDF membranes. After blocking with 5% skimmed milk for 1 h at room temperature, the membranes were incubated with antibodies against MEX3A (1 : 1000; ab79046; Abcam) overnight at 4°C, followed by incubation with a secondary antibody (1 : 3,000; #A0208; Beyotime, Beijing, China) at room temperature for 1 h. The ECL detection kit was used to detect protein signals.

2.17. Immunohistochemical (IHC) Staining

MEX3A expression was assessed by IHC assay, using previously described protocol [18]. Anti-MEX3A antibody (ab79046; Abcam) was used at a 1 : 50 dilution at 4°C overnight. Rabbit immunoglobulin G (1 : 1000; ab6721; Abcam) was used as a negative control. Aperio Scanning System (Aperio Group, LLC) was employed to scan the slides, and Aperio Image Scope software (version 10.2.2.2317, Aperio Technologies) was used for further quantitative analysis.

2.18. Statistical Analyses

Survival analysis was analyzed using the Kaplan–Meier method. GO enrichment analysis and KEGG enrichment analysis were performed under an R computing environment. Statistical analyses were performed using GraphPad Prism 7.0 (GraphPad Software, La Jolla, CA, USA). Comparisons were performed by a two-tailed Student’s -test. values < 0.05 were considered statistically significant. Data were expressed as (SD).

3. Result

3.1. High Expression Level and Prognostic Value of MEX3A in Ovarian Cancer by Bioinformatics Analyses

Firstly, to determine differences in MEX3A expression in tumor and normal tissues, the MEX3A mRNA levels in different tumors and normal tissues of various cancer types were analyzed using the Oncomine database. The database, which had a total of 241 unique samples for MEX3A, and a total of 22 cancers, including brain and CNS cancer, breast cancer, colorectal cancer, and ovarian cancer, showed that MEX3A mRNA levels were significantly upregulated in various cancers, and MEX3A expression in OC was high on top 5 (Figure S1a). GEPIA analysis also revealed similar results (Figure S1b).

Next, we found that MEX3A expression in OC significantly increased between 426 cases of OC and 88 cases of normal ovarian tissues via GEPIA (Figure 1(a)). In order to clarify the results, the expression differences in OC tissues (40 samples from Renji Hospital) and normal ovarian tissues (25 samples from Renji Hospital) were also validated by IHC staining (Figure 1(c)).

(a)

(b)

(c)

(d)

Figure 1: The mRNA expression levels and prognosis of MEX3A in ovarian cancer and normal tissues. (a) Box plots show mRNA expression of MEX3A in OC tissue (red plot) and normal tissues (gray plot) from GEPIA. (b) Prognostic significance of MEX3A in OC with OS from the Kaplan–Meier plotter. (c) Representative IHC images of MEX3A expression in normal tissue and ovarian cancer. (d) Prognostic significance of MEX3A in OC with PFS from the Kaplan–Meier plotter. The red survival curve represents high MEX3A expression, and the black survival curve represents low MEX3A expression in OC. , , and .

In addition, we investigated whether MEX3A was associated with prognosis in OC patients by using the Kaplan–Meier plotter and PrognoScan. The Kaplan–Meier plotter and PrognoScan databases showed that OC patients with high MEX3A expression experienced poor OS and PFS (Figures 1(b) and 1(d), Table 1). In order to explore the prognostic value of different histologies, the database revealed that higher MEX3A expression was correlated with shorter OS and PFS both in patients with endometrioid and serous cancers (Figures S1c–e). Collectively, MEX3A can be considered as an independent prognostic biomarker linked to a poor survival rate in OC.

Table 1: Survival analysis of MEX3A mRNA in multiple cancers.

Dataset
Endpoint
Probe ID
Number
Corrected value
COX value
In (HR) HR (95% CI-low CI-up)

GSE9891
Overall survival
226346_at
278
0.013633
0.007141
0.27
1.31 (1.08-1.60)

GSE9891
Overall survival
227512_at
278
0.114667
0.022613
0.25
1.28 (1.04-1.59)

GSE17260
Overall survival
A_24_P857404
110
0.004934
0.031824
-0.1.36
0.72 (0.53-0.97)

GSE17260
Overall survival
A_32_P96036
110
0.001922
0.097382
-1.23
0.78 (0.58-1.05)

GSE17260
Progression-free survival
A_32_P96036
110
0.044430
0.338936
-0.11
0.90 (0.72-1.12)

3.2. MEX3A Expression Is Correlated with Immune Infiltration Level in OC

To better understand the underlying mechanism of MEX3A in OC, we further investigated the relationships between MEX3A and the immune system. Tumor-infiltrating immune cells (TIICs) are an important part of the tumor microenvironment and which are independent predictors of cancer survival. It is unclear whether targeting MEX3A could influence the recruitment numbers of TIICs to impact the prognosis of cancers. Through TIMER analysis, we found that most immune cells were negatively correlated with MEX3A expression (Figure 2(a)). MEX3A expression had a negative correlation with B cells, CD8+ T cells, neutrophils and dendritic cells (DCs), and macrophages. However, the expression of MEX3A had weak associations with CD4+ T cells in OC. Subsequently, we used the TISIDB database to further analyze the relationship between MEX3A expression and immune regulation. Figures 2(b) and 2(c) show the correlation between MEX3A expression and TILs, which corresponded to the results reported above. Immunomodulators can be further divided into immunoinhibitors, immunostimulators, and major histocompatibility complex (MHC) molecules. Furthermore, we assessed the correlation between MEX3A expression and diverse immunomodulators. Figures 2(d) and 2(e) indicate the correlations between MEX3A expression and immunostimulators, and the greatest correlations include C10orf54 (Spearman’s: , ), TNFRSF18 (Spearman’s: , ), TNFRSF14 (Spearman’s: , ), and TNFRSF13C (Spearman’s: , ). Figures 2(f) and 2(g) indicate correlations between MEX3A levels and immunoinhibitors, where the strongest include IL10RB (Spearman’s: , ), IDO1 (Spearman’s: , ), VTCN1 (Spearman’s: , ), and HAVCR2 (Spearman’s: , ). Correlations between MEX3A expression and MHC molecules were also explored, and the greatest correlations include B2M (Spearman’s: , ), HLA-DMA (Spearman’s: , ), HLA-DPA1 (Spearman’s: , ), and HLA-DPB1 (Spearman’s: , ) (Figures 3(h) and 3(i)). Therefore, MEX3A may be involved in negative immune regulation.

(a)

(b)

(c)

(d)

(e)

(f)

(g)

(h)

(i)

Figure 2: Correlation of MEX3A expression with immune infiltration level in OC. (a) Correlation of MEX3A expression with immune infiltration level in OC (TIMER). Spearman’s correlation of MEX3A with lymphocytes and immunomodulators (TISIDB). (b) Heat maps of correlations between MEX3A expression and TILs by TISIDB. (c) Scatterplots of correlations between MEX3A expression and top 4 TILs. (d) Heat maps of correlations between MEX3A expression and immunostimulators. (e) Scatterplots of correlations between MEX3A expression and top 4 immunostimulators. (f) Heat maps of correlations between MEX3A expression and immunoinhibitors. (g) Scatterplots of correlations between MEX3A expression and top 4 immunoinhibitors. (h) Heat maps of correlations between MEX3A expression and MHC molecules. (i) Scatterplots of correlations between MEX3A expression and top 4 MHC molecules. Red and blue represent positive and negative correlations. The color intensity is directly proportional to the strength of the correlations. , , and .

Figure 3: Gene-gene interaction network between MEX3A and correlated genes (GeneMANIA). Each node represents a gene. The node size indicates the strength of the interaction. The connecting lines between nodes represent the type of gene-gene interaction, and the line color represents the type of interaction. Node colors represent the possible biological functions of each gene.

3.3. Enrichment Analysis of Coexpression Genes Correlated with MEX3A in OC

Next, we analyzed mRNA sequencing data from OC patients in TCGA by using the function module of LinkedOmics. As shown in the volcano plot (Figure 2(a)), 2596 genes (dark red dots) showed significant positive correlations with MEX3A, and 3050 genes (dark green dots) showed significant negative correlations (). The 50 significant gene sets (such as ACTBL2, C12orf43, CCDC56, CCL27, CPNE8, FAM78B, KCTD17, and LAMB4) positively and negatively correlated with MEX3A are shown in the heat map (Figures 2(b) and 2(c)). These results indicated an important influence of MEX3A on the transcriptome level. Besides, GO term analysis showed that high expressed genes in correlation with MEX3A were mainly located in the chromatin centrosome and nuclear chromosome part, where they mostly participated in mRNA processing, covalent chromatin modification, and histone modification. Poor expressed genes were mainly located in the endosome membrane, secretory granule membrane, and side of the membrane and were involved in immune-related processing, including neutrophil and T cell activation and regulation of lymphocyte activation (Figures 4(d) and 4(e)). KEGG pathway analysis showed the most important enrichment in the herpes simplex virus 1 infection of high expressed genes and cytokine-cytokine receptor interaction of poor expressed genes (Figures 4(f) and 4(g)). These data pointed out that MEX3A might promote tumor progression by regulating immune cell response in the tumor microenvironment.

(a)

(b)

(c)

(d)

(e)

(f)

(g)

Figure 4: Genes differentially expressed in correlation with MEX3A (LinkedOmics). (a) Correlations between MEX3A and genes differentially expressed in OC. (b) Heat maps showing genes positively and negatively correlated with MEX3A in OC (Top 50). (c) Heat maps showing genes negatively correlated with MEX3A in OC. Red indicates positively correlated genes, and blue indicates negatively correlated genes. (d) Barplot representing enriched functions of the upregulated genes coexpressed with MEX3A. (e) Barplot representing enriched pathways of the upregulated genes coexpressed with MEX3A. (f) Barplot representing enriched functions of the downregulated genes coexpressed with MEX3A. (g) Barplot representing enriched pathways of the downregulated genes coexpressed with MEX3A.

3.4. Genomic Alterations of MEX3A in OC

Based on the above analysis, MEX3A is closely related to tumor immunology. In order to better understand the potential immune mechanism of MEX3A in cancer, genetic variations of MEX3A retrieved from the TCGA database (489 cases, Nature 2011) were analyzed by using the cBioPortal database. The results showed mRNA expression changes in 60 cases (16%), amplification in 38 cases (10%), a mutation in 1 case (0.3%), and multiple alterations in 19 cases (5%), in which amplification was the most common type (Figure 5(a)). Further, the expression of 771 genes was positively related to MEX3A and was increased with the amplification of MEX3A. Among these genes, LAMTOR2 had the most frequent alterations (Table 2). LAMTOR2 is essential for macrophage and dendritic cell (DC) homeostasis via mediating immune responses [19, 20]. Significantly enriched GO analysis showed that these genes encoded proteins that were mainly localized to the cornified envelope (Figures 5(b) and 5(c)). They were primarily involved in immunoglobulin binding, IgG binding, and RAGE reporter binding.

(a)

(b)

(c)

Figure 5: Analyses of genetic variations of MEX3A in OC (cBioPortal). (a) OncoPrint visual summary of variations on MEX3A. The different types of genetic alterations are represented by different colors. (b, c) Functional enrichment analyses of genes coexpressed with MEX3A.

Table 2: The expression of 771 related genes with MEX3A in cBioPortal.

Gene
LogFC
entrezID

LAMTOR2
>10
28956

RAB25
>10
57111

UBQLN4
7.9
56893

LMNA
7.86
4000

SSR2
6.9
6746

ARHGEF2
6.31
9181

RXFP4
6.27
339403

KHDC4
5.86
22889

SEMA4A
7.73
64218

SLC25A44
7.68
9673

SCARNA4
6.19
677771

SNORA80E
6.19
677823

SYT11
6.14
23208

RIT1
5.73
6016

PMF1
6.64
11243

PMF1-BGLAP
6.64
100527963

GON4L
5.68
54856

BGLAP
6.48
632

PAQR6
5.9
79957

SMG5
5.9
23381

CCT3
5.84
7203

GLMP
5.84
112770

TMEM79
5.84
84283

VHLL
5.84
391104

ASH1L-AS1
4.95
645676

DAP3
4.95
7818

MSTO1
4.95
55154

YY1AP1
4.95
55249

MSTO2P
4.73
100129405

TSACC
5.73
128229

ASH1L
4.13
55870

C1ORF61
5.67
NA

RHBG
5.67
57127

POU5F1P4
4.16
645682

LRRC71
6.98
149499

TRIM46
4.2
80128

DPM3
4.14
54344

EFNA1
4.14
1942

GBA
4.14
2629

GBAP1
4.14
2630

KRTCAP2
4.14
200185

MTX1
4.14
4580

MUC1
4.14
4582

SLC50A1
4.14
55974

THBS3
4.14
7059

ARHGEF11
6.9
9826

HDGF
5.98
3068

INSRR
5.98
3645

ISG20L2
5.98
81875

MRPL24
5.98
79590

NTRK1
5.98
4914

PEAR1
5.98
375033

PRCC
5.98
5546

RRNAD1
5.98
51093

SH2D2A
5.98
9047

FAM189B
3.99
10712

SCAMP3
3.99
10067

CLK2
3.79
1196

FDPS
3.79
2224

HCN3
3.79
57657

PKLR
3.79
5313

RUSC1
3.79
23623

RUSC1-AS1
3.79
284618

IQGAP3
5.39
128239

MEF2D
5.39
4209

CRABP2
5.9
1382

CYCSP52
6.82
360155

ETV3
6.82
2117

ETV3L
6.82
440695

EFNA4
4.19
1945

ZBTB7B
4.19
51043

ADAM15
4.02
8751

DCST1
4.02
149095

DCST1-AS1
4.02
100505666

DCST2
4.02
127579

EFNA3
4.02
1944

BCAN
5.31
63827

GPATCH4
5.31
54865

HAPLN2
5.31
60484

NAXE
5.31
128240

NES
5.31
10763

TTC24
5.31
164118

FCRL4
6.64
83417

FCRL5
6.64
83416

CKS1B
4.05
1163

FLAD1
4.05
80308

LENEP
4.05
55891

ADAR
4.58
103

KCNN3
3.88
3782

PBXIP1
3.88
57326

PMVK
3.88
10654

PYGO2
3.88
90780

SHC1
3.88
6464

CD5L
6.54
922

FCRL1
6.54
115350

FCRL2
6.54
79368

FCRL3
6.54
115352

KIRREL1
6.54
55243

CHRNB2
4.49
1141

SHE
4.23
126669

TDRD10
4.23
126668

UBE2Q1
4.23
55585

CREB3L4
3.9
148327

CRTC2
3.9
200186

DENND4B
3.9
9909

JTB
3.9
10899

RAB13
3.9
5872

RPS27
3.9
6232

SLC39A1
3.9
27173

NUP210L
3.65
91181

CD1A
6.43
909

CD1B
6.43
910

CD1C
6.43
911

CD1D
6.43
912

CD1E
6.43
913

LINC01704
6.43
646268

OR10K2
6.43
391107

OR10T2
6.43
128360

IL6R
4.01
3570

C1ORF189
3.73
NA

C1ORF43
3.73
NA

HAX1
3.73
10456

TPM3
3.73
7170

UBAP2L
3.73
9898

OR10K1
5.43
391109

OR10R2
5.43
343406

GATAD2B
3.28
57459

SLC27A3
3.28
11000

PSMD4
2.95
5710

AQP10
3.65
89872

ATP8B2
3.65
57198

C2CD4D
3.05
100191040

C2CD4D-AS1
3.05
100132111

LINGO4
3.05
339398

MRPL9
3.05
65005

OAZ3
3.05
51686

RORC
3.05
6097

TDRKH
3.05
11022

THEM5
3.05
284486

INTS3
3.17
65123

SNAPIN
3.17
23557

LYSMD1
2.87
388695

PIP5K1A
2.87
8394

SCNM1
2.87
79005

TMOD4
2.87
29765

TNFAIP8L2
2.87
79626

TNFAIP8L2-SCNM1
2.87
100534012

VPS72
2.87
6944

MNDA
4.84
4332

LCE2B
3.49
26239

LCE2C
3.49
353140

LCE2D
3.49
353141

THEM4
2.96
117145

SEMA6C
2.8
10500

ILF2
3.07
3608

NPR1
3.07
4881

OR10X1
5.31
128367

OR10Z1
5.31
128368

OR6K6
5.31
128371

OR6N1
5.31
128372

OR6N2
5.31
81442

OR6P1
5.31
128366

OR6Y1
5.31
391112

TCHH
3.2
7062

TCHHL1
3.2
126637

CGN
2.88
57530

PLEKHO1
2.88
51177

VPS45
2.88
11311

ZNF687
2.88
57592

LCE3A
3.36
353142

LCE3B
3.36
353143

LCE3C
3.36
353144

LCE3D
3.36
84648

LCE3E
3.36
353145

HORMAD1
2.6
84072

CHTOP
2.98
26097

ANP32E
2.8
81611

APH1A
2.8
51107

C1ORF54
2.8
NA

CA14
2.8
23632

CIART
2.8
148523

MRPS21
2.8
54460

POGZ
2.8
23126

NBPF18P
3.09
441908

RPTN
3.09
126638

S100A10
3.09
6281

S100A11
3.09
6282

ANXA9
2.66
8416

MINDY1
2.66
55793

PRUNE1
2.66
58497

GOLPH3L
2.54
55204

CRCT1
3.23
54544

LCE5A
3.23
254910

CELF3
2.89
11189

RIIAD1
2.89
284485

S100A1
2.89
6271

S100A13
2.89
6284

S100A14
2.89
57402

TUFT1
2.89
7286

C1ORF68
3.41
NA

LCE2A
3.41
353139

LCE4A
3.41
199834

ACKR1
4.73
2532

AIM2
4.73
9447

CADM3
4.73
57863

CADM3-AS1
4.73
100131825

FCER1A
4.73
2205

IFI16
4.73
3428

OR10J3
4.73
441911

OR6K2
4.73
81448

OR6K3
4.73
391114

PYHIN1
4.73
149628

SPTA1
4.73
6708

GABPB2
2.6
126626

OTUD7B
2.81
56957

PI4KB
2.81
5298

PSMB4
2.81
5692

RFX5
2.81
5993

S100A2
2.81
6273

SELENBP1
2.81
8991

SNX27
2.81
81609

CRNN
3.12
49860

PRPF3
2.66
9129

ADAMTSL4
2.54
54507

ADAMTSL4-AS1
2.54
574406

MCL1
2.54
4170

KPRP
3.27
448834

LCE1F
3.27
353137

S100A16
2.73
140576

BNIPL
2.59
149428

C1ORF56
2.59
NA

CDC42SE1
2.59
56882

CERS2
2.59
29956

MLLT11
2.59
10962

FLG
3.01
2312

FLG-AS1
3.01
339400

FLG2
3.01
388698

CTSS
2.48
1520

ENSA
2.48
2029

LCE1A
3.14
353131

LCE1B
3.14
353132

LCE1C
3.14
353133

LCE1D
3.14
353134

LCE1E
3.14
353135

LCE6A
3.14
448835

SPRR2C
3.14
6702

MTMR11
2.81
10903

SF3B4
2.81
10262

ARNT
2.53
405

CTSK
2.53
1513

ECM1
2.53
1893

FALEC
2.53
100874054

RPRD2
2.53
23248

SETDB1
2.53
9869

TARS2
2.53
80222

HRNR
2.91
388697

S100A3
2.73
6274

S100A4
2.73
6275

S100A5
2.73
6276

S100A6
2.73
6277

OR10J1
4.6
26476

OR10J5
4.6
127385

LOC101928009
3.03
101928009

SMCP
3.03
4184

SPRR2G
3.03
6706

SV2A
2.58
9900

PGLYRP4
2.92
57115

S100A12
2.92
6283

S100A8
2.92
6279

S100A9
2.92
6280

SPRR2A
3.05
6700

SPRR2B
3.05
6701

SPRR2E
3.05
6704

SPRR2F
3.05
6705

APCS
4.19
325

S100A7
2.82
6278

S100A7A
2.82
338324

S100A7L2
2.82
645922

LELP1
2.93
149018

LOR
2.93
4014

PGLYRP3
2.93
114771

PRR9
2.93
574414

SPRR2D
2.93
6703

NOTCH2
2.44
4853

DUSP23
3.87
54935

LMOD1
3.51
25802

TIMM17A
3.51
10440

SPRR1B
2.83
6699

SPRR4
2.83
163778

SRGAP2D
2.28
100996712

IVL
2.73
3713

SPRR1A
2.73
6698

SPRR3
2.73
6707

LY9
4.05
4063

ACP6
2.42
51205

ANKRD20A12P
2.42
100874392

ANKRD34A
2.42
284615

ANKRD35
2.42
148741

BCL9
2.42
607

BOLA1
2.42
51027

CD160
2.42
11126

CHD1L
2.42
9557

EMBP1
2.42
647121

FAM72B
2.42
653820

FAM72D
2.42
728833

FCGR1A
2.42
2209

FCGR1B
2.42
2210

FCGR1CP
2.42
100132417

FMO5
2.42
2330

GJA5
2.42
2702

GJA8
2.42
2703

GNRHR2
2.42
114814

GPR89A
2.42
653519

GPR89B
2.42
51463

HIST2H2AA3
2.42
8337

HIST2H2AB
2.42
317772

HIST2H2AC
2.42
8338

HIST2H2BA
2.42
337875

HIST2H2BC
2.42
337873

HIST2H2BE
2.42
8349

HIST2H2BF
2.42
440689

HIST2H3A
2.42
333932

HIST2H3D
2.42
653604

HIST2H4A
2.42
8370

HJV
2.42
148738

ITGA10
2.42
8515

LINC00623
2.42
728855

LINC00624
2.42
100289211

LINC00869
2.42
57234

LINC01138
2.42
388685

LINC02591
2.42
388692

LIX1L
2.42
128077

LOC102723769
2.42
102723769

LOC653513
2.42
653513

LOC728989
2.42
728989

LSP1P5
2.42
645166

NBPF10
2.42
100132406

NBPF11
2.42
200030

NBPF12
2.42
149013

NBPF13P
2.42
644861

NBPF14
2.42
25832

NBPF15
2.42
284565

NBPF17P
2.42
401967

NBPF20
2.42
100288142

NBPF25P
2.42
101929780

NBPF8
2.42
728841

NBPF9
2.42
400818

NOTCH2NLA
2.42
388677

NUDT17
2.42
200035

PDE4DIP
2.42
9659

PDIA3P1
2.42
171423

PDZK1
2.42
5174

PDZK1P1
2.42
100034743

PEX11B
2.42
8799

PFN1P2
2.42
767846

PIAS3
2.42
10401

POLR3C
2.42
10623

POLR3GL
2.42
84265

PPIAL4A
2.42
653505

PPIAL4D
2.42
645142

PPIAL4E
2.42
730262

PPIAL4G
2.42
644591

PRKAB2
2.42
5565

RBM8A
2.42
9939

RNF115
2.42
27246

SEC22B
2.42
9554

SRGAP2-AS1
2.42
100873165

TXNIP
2.42
10628

ELF3
3.31
1999

PIK3C2B
3.31
5287

CFAP45
3.6
25790

CRP
3.6
1401

FCRL6
3.6
343413

IGSF9
3.6
57549

SLAMF8
3.6
56833

SLAMF9
3.6
89886

SNHG28
3.6
284677

TAGLN2
3.6
8407

VSIG8
3.6
391123

FAM72C
2.12
554282

ADAMTS4
4.31
9507

APOA2
4.31
336

ARHGAP30
4.31
257106

B4GALT3
4.31
8703

CFAP126
4.31
257177

DEDD
4.31
9191

DUSP12
4.31
11266

F11R
4.31
50848

FCER1G
4.31
2207

FCGR2A
4.31
2212

FCGR2B
4.31
2213

FCGR2C
4.31
9103

FCGR3A
4.31
2214

FCGR3B
4.31
2215

FCRLA
4.31
84824

FCRLB
4.31
127943

HSPA6
4.31
3310

HSPA7
4.31
3311

ITLN2
4.31
142683

KLHDC9
4.31
126823

LOC101928372
4.31
101928372

MPZ
4.31
4359

NDUFS2
4.31
4720

NECTIN4
4.31
81607

NIT1
4.31
4817

NR1I3
4.31
9970

PCP4L1
4.31
654790

PFDN2
4.31
5202

PPOX
4.31
5498

RPL31P11
4.31
641311

SDHC
4.31
6391

TOMM40L
4.31
84134

TSTD1
4.31
100131187

UFC1
4.31
51506

USF1
4.31
7391

USP21
4.31
27005

ATP1A2
3.14
477

RNPEP
3.14
6051

LINC01133
3.38
100505633

PPP1R15B
3.38
84919

CD48
3.73
962

SLAMF7
3.73
57823

ATP1A4
3.19
480

IGSF8
3.19
93185

KCNJ10
3.19
3766

KCNJ9
3.19
3765

MDM4
3.19
4194

PIGM
3.19
93183

ATF6
3.9
22926

CD244
3.9
51744

ITLN1
3.9
55600

LOC101928404
3.9
101928404

OLFML2B
3.9
25903

RGS4
3.9
5999

RGS5
3.9
8490

SHISA4
3.47
149345

SLAMF1
3.47
6504

LINC01142
4.14
284688

METTL11B
4.14
149281

CASQ1
3.24
844

CENPL
3.24
91687

DARS2
3.24
55157

DCAF8
3.24
50717

GAS5
3.24
60674

GAS5-AS1
3.24
100506046

IPO9
3.24
55705

LINC00628
3.24
127841

PEA15
3.24
8682

RC3H1
3.24
149041

SERPINC1
3.24
462

SNORD44
3.24
26806

SNORD47
3.24
26802

SNORD74
3.24
619498

SNORD75
3.24
692195

SNORD76
3.24
692196

SNORD77
3.24
692197

SNORD78
3.24
692198

SNORD79
3.24
26770

SNORD80
3.24
26774

SNORD81
3.24
26769

ZBTB37
3.24
84614

C1ORF226
3.58
NA

CCDC190
3.58
339512

LOC100422212
3.58
100422212

NUF2
3.58
83540

SH2D1B
3.58
117157

SPATA46
3.58
284680

UAP1
3.58
6675

UHMK1
3.58
127933

LAMC2
2.52
3918

NMNAT2
2.52
23057

ASTN1
3.05
460

BLACAT1
3.05
101669762

FLJ31356
3.05
403150

CD84
3.31
8832

DDR2
3.31
4921

HSD17B7
3.31
51478

LRRN2
3.31
10446

NOS1AP
3.31
9722

SLAMF6
3.31
114836

FMO2
3.73
2327

FMO3
3.73
2328

FMO6P
3.73
388714

GORAB
3.73
92344

KIFAP3
3.73
22920

MROH9
3.73
80133

PRRX1
3.73
5396

ANGPTL1
2.73
9068

FAM20B
2.73
9917

LAMC1
2.73
3915

RALGPS2
2.73
55103

TOR3A
2.73
64222

ETNK2
2.88
55224

FOSL2
2.88
2355

GOLT1A
2.88
127845

IPO9-AS1
2.88
100873949

KISS1
2.88
3814

LGR6
2.88
59352

NFASC
2.88
23114

PLEKHA6
2.88
22874

PTPRVP
2.88
148713

REN
2.88
5972

SNRPE
2.88
6635

SOX13
2.88
9580

ZC3H11A
2.88
9877

ABL2
2.6
27

PLB1
2.6
151056

CNTN2
3.09
6900

DSTYK
3.09
25778

KLHDC8A
3.09
55220

KLHL20
3.09
27252

NUAK2
3.09
81788

RBBP5
3.09
5929

TMEM81
3.09
388730

ATP1B1
3.95
481

BLZF1
3.95
8548

C1ORF112
3.95
NA

CCDC181
3.95
57821

LINC00626
3.95
79100

LINC00970
3.95
101978719

METTL18
3.95
92342

NME7
3.95
29922

SCYL3
3.95
57147

SELE
3.95
6401

SELL
3.95
6402

SELP
3.95
6403

SLC19A2
3.95
10560

ARL8A
2.73
127829

C1ORF21
2.73
NA

C1ORF220
2.73
NA

CSRP1
2.73
1465

GLUL
2.73
2752

GPR37L1
2.73
9283

LINC00272
2.73
388719

LINC00303
2.73
284573

LINC01344
2.73
400799

NAV1
2.73
89796

PTPN7
2.73
5778

RPS10P7
2.73
376693

SOAT1
2.73
6646

TEDDM1
2.73
127670

TEX35
2.73
84066

ZNF648
2.73
127665

NUCKS1
2.9
64710

OCLM
2.9
10896

ODR4
2.9
54953

PBX1
2.9
5087

PDC
2.9
5132

PRG4
2.9
10216

RAB29
2.9
8934

RNU6-72P
2.9
100873775

SLC41A1
2.9
254428

TPR
2.9
7175

ARPC5
2.59
10092

LINC01686
2.59
284648

NPL
2.59
80896

PHLDA3
2.59
23612

RABGAP1L
2.59
9910

RASAL2
2.59
9462

RGS16
2.59
6004

RGS8
2.59
85397

RGSL1
2.59
353299

RNASEL
2.59
6041

TSEN15
2.59
116461

FMO1
3.14
2326

FMO4
3.14
2329

LMX1A
3.14
4009

TOP1P1
3.14
7151

ANKRD36BP1
3.54
84832

CD247
3.54
919

CREG1
3.54
8804

DPT
3.54
1805

DUSP27
3.54
92235

F5
3.54
2153

FAM78B
3.54
149297

FMO9P
3.54
116123

GPA33
3.54
10223

ILDR2
3.54
387597

LINC01363
3.54
101928484

LOC100505918
3.54
100505918

MAEL
3.54
84944

POGK
3.54
57645

POU2F1
3.54
5451

SFT2D2
3.54
375035

TADA1
3.54
117143

TBX19
3.54
9095

TIPRL
3.54
261726

XCL1
3.54
6375

XCL2
3.54
6846

BRINP2
2.73
57795

CRYZL2P
2.73
730102

GS1-279B7.1
2.73
100288079

IVNS1ABP
2.73
10625

LINC01741
2.73
101928778

RASAL2-AS1
2.73
100302401

RNU6-79P
2.73
100873779

SWT1
2.73
54823

TRMT1L
2.73
81627

ZBED6
2.73
100381270

APOBEC4
2.47
403314

DHX9
2.47
1660

LHX4
2.47
89884

LHX4-AS1
2.47
100527964

SHCBP1L
2.47
81626

ERO1B
1.97
56605

ANKRD45
2.92
339416

BRINP3
2.92
339479

COPA
2.92
1314

EEF1AKNMT
2.92
51603

GPR52
2.92
9293

LEMD1
2.92
93273

LEMD1-AS1
2.92
284576

LINC01720
2.92
440704

LOC100505716
2.92
100505716

MYOC
2.92
4653

NCSTN
2.92
23385

NHLH1
2.92
4807

PEX19
2.92
5824

PLA2G4A
2.92
5321

PRRC2C
2.92
23215

RXRG
2.92
6258

SCARNA3
2.92
677679

SUMO1P3
2.92
474338

TEX50
2.92
730159

TMCC2
2.92
9911

VAMP4
2.92
8674

VANGL2
2.92
57216

ADORA1
2.58
134

AXDND1
2.58
126859

CHI3L1
2.58
1116

CHIT1
2.58
1118

FAM163A
2.58
148753

LAX1
2.58
54900

LINC01350
2.58
101929093

MYBPH
2.58
4608

MYOG
2.58
4656

NIBAN1
2.58
116496

NPHS2
2.58
7827

PM20D1
2.58
148811

PPFIA4
2.58
8497

PPP1CB
2.58
5500

RNF2
2.58
6045

SEC16B
2.58
89866

TDRD5
2.58
163589

TOR1AIP1
2.58
26092

TOR1AIP2
2.58
163590

COLGALT2
2.35
23127

RGL1
2.35
23179

SMG7-AS1
2.35
284649

ADCY10
3.21
55811

GPR161
3.21
23432

MPC2
3.21
25874

MPZL1
3.21
9019

RCSD1
3.21
92241

SLC4A1AP
3.21
22950

SUPT7L
3.21
9913

SUGCT
>10
79783

MTR
1.99
4548

C1ORF53
2.73
NA

CDK18
2.73
5129

COP1
2.73
64326

LHX9
2.73
56956

LOC100505795
2.73
100505795

NEK7
2.73
140609

PPP1R12B
2.73
4660

PTGS2
2.73
5743

SLC9C2
2.73
284525

NCF2
2.24
4688

PLEKHG2
1.56
64857

ZFP36
1.56
7538

BTG2
2.44
7832

CACNA1E
2.44
777

CEP350
2.44
9857

CTSE
2.44
1510

EDEM3
2.44
80267

FLJ23867
2.44
NA

FMOD
2.44
2331

HMCN1
2.44
83872

LINC01136
2.44
730227

LINC01699
2.44
100287948

PAPPA2
2.44
60676

QSOX1
2.44
5768

TNNI1
2.44
7135

MT1HL1
1.92
645745

LRRC52
2.95
440699

MRPL33
2.95
9553

TNFSF18
2.95
8995

GMFG
1.52
9535

MED29
1.52
55588

PAF1
1.52
54623

SAMD4B
1.52
55095

SMG7
2.14
9887

ACTN2
1.85
88

EDARADD
1.85
128178

GPR137B
1.85
7107

HEATR1
1.85
55127

LGALS8
1.85
3964

LGALS8-AS1
1.85
100287902

NID1
1.85
4811

RYR2
1.85
6262

DENND1B
2.56
163486

GLRX2
2.56
51022

RO60
2.56
6738

SLC45A3
2.56
85414

SRGAP2
2.56
23380

SRGAP2B
2.56
647135

SRGAP2C
2.56
653464

SUCO
2.56
51430

UBE2T
2.56
29089

DNM3
2.31
26052

IER5
2.31
51278

KIAA1614
2.31
57710

LINC00260
2.31
84719

LOC284581
2.31
284581

MR1
2.31
3140

PAX8
2.31
7849

PAX8-AS1
2.31
654433

SNORA77
2.31
677843

STX6
2.31
10228

LRATD1
4.05
151354

C19ORF47
1.94
NA

ARID4B
1.79
51742

CHRM3
1.79
1131

CHRM3-AS1
1.79
100873984

GGPS1
1.79
9453

TBCE
1.79
6905

KLRF2
2.05
100431172

LINC01132
1.67
100506810

ALDH9A1
2.73
223

DCAF6
2.73
55827

KIAA0040
2.73
9674

LINC01351
2.73
101929120

LOC440700
2.73
440700

LRRC52-AS1
2.73
400794

MGST3
2.73
4259

RBKS
2.73
64080

TNFSF4
2.73
7292

TNR
2.73
7143

UCK2
2.73
7371

ATP2B4
2.2
493

RHEX
2.2
440712

SLC26A9
2.2
115019

B3GALT2
2.41
8707

BABAM2
2.41
9577

CDC73
2.41
79577

CRB1
2.41
23418

ELK4
2.41
2005

FAM72A
2.41
729533

MFSD4A
2.41
148808

MFSD4A-AS1
2.41
284578

PHF12
2.41
57649

PIGC
2.41
5279

RGS1
2.41
5996

RGS13
2.41
6003

RGS2
2.41
5997

TMEM183A
2.41
92703

TMEM183B
2.41
653659

UCHL5
2.41
51377

AGT
1.87
183

C1ORF198
1.87
NA

CAPN9
1.87
10753

COG2
1.87
22796

ZP4
1.87
57829

DYRK1B
1.47
9149

FBL
1.47
2091

IFNL2
1.47
282616

IFNL3
1.47
282617

IFNL4
1.47
101180976

NCCRP1
1.47
342897

RPS16
1.47
6217

SYCN
1.47
342898

3.5. Construction of a Gene-Gene Interaction Network

To further explore the potential mechanism of MEX3A in promoting OC progression, we constructed a gene-gene interaction network by using the GeneMANIA database. Their functions were also analyzed. MEX3A were surrounded by 20 nodes representing genes that were greatly correlated with the family in terms of physical interactions, coexpression, prediction, colocalization, pathway, genetic interactions, and shared protein domains. From the results (Figure 3), we found that PABPC1, a kind of shuttling protein from the cytoplasm to nucleus in most eukaryotes, was correlated with MEX3A for physical interactions. PABPC1 is important for protein translation initiation and decay by binding to regulatory proteins [21]. In addition, KHDRBS2 was associated with IGF2BP2 and MEX3A in terms of shared protein domains. KHDRBS2 is also an RNA-binding protein that is tyrosine phosphorylated by Src during mitosis [22]. IGF2BP2 was colocalized with STRA6. Further functional analysis revealed that most proteins were greatly correlated with skeletal system development and genitalia development.

3.6. MEX3A Promoted Ovarian Cell Proliferation, Migration, and Invasion In Vitro

To further evaluate the biological functions of MEX3A on ovarian cancer, the expression of MEX3A in different cell lines was tested, and in vitro studies were performed (Figure 6(a)). The ES2 cell line was chosen for further study. We silenced MEX3A expression by siRNA, and a nontargeting siRNA was used as a control. The efficiency was evaluated by Western blotting and RT-PCR (Figures 6(b) and 6(c)). We first studied its influence on OC growth by using CCK8 assay, clone formation assay, and EdU assay. Compared with the normal control group, MEX3A knockdown partly suppressed the proliferation of OC cells (, Figure 6(d)). Similarly, the colony number was significantly smaller than that of the control group (, Figure 6(e)). EdU is a thymidine nucleoside analogue, which is involved in DNA replication when targeting proliferating cells. The proliferation activity of ES2 cells can be analyzed with the number of red/blue fluorescence spots. Figure 6(f) shows that compared with the control group, knockdown of MEX3A significantly inhibits the EdU uptake rate, which also indicates suppressed proliferation ability. Next, we assessed the role of MEX3A knockdown on the migration ability of OC. Transwell assay and wound healing assay were performed, and the results showed that MEX3A knockdown significantly inhibited cell migration in ES2 cells in comparison to the control group (Figures 6(g) and 6(h)). Collectively, these results indicated that MEX3A could promote the proliferation and migration in OC cells.

(a)

(b)

(c)

(d)

(e)

(f)

(g)

(h)

Figure 6: MEX3A promotes proliferation, migration, and invasion of ES2 cells in vitro. (a) Relative mRNA level of MEX3A in ovarian cancer cell lines. (b, c) The mRNA and protein expression of MEX3A in MEX3A knockdown ES2 cell treated with shRNA. (d, f) The CCK-8 assay, colony formation assay, and EdU assay showed that MEX3A knockdown in ES2 cells could suppress proliferative capability. (g, h) Migration and wound healing assay were utilized to evaluate and identify metastasis ability after MEX3A knockdown in ES2 cells. The data are presented as the (). , , and .

4. Discussion

OC is usually detected during the late stages; thus, few patients are eligible for timely treatment. Identifying sensitive and specific biomarkers for improving diagnosis and accurately evaluating prognosis continues to be an important research focus. In this study, we explored a novel gene—MEX3A—which is an RNA-binding protein or an E3 ubiquitin ligase acting posttranscriptional regulation, associated with the diagnosis and prognosis of OC. MEX3A has important roles in biological processes. Its expression is associated with intestinal homeostasis by regulating intestinal differentiation and promoting high expression of intestinal stem cell markers (LGR5, BMI1, and MSI1) [23, 24]. Moreover, a few studies have evaluated the effect of MEX3A on tumors. Abnormal activation of MEX3A can promote tumor cell proliferation, metastasis, and migration in gastric cancer and pancreatic ductal adenocarcinoma, breast cancer, and osteosarcoma [6, 25–27]. For example, MEX3A may act as a tumor promoter for breast cancer by regulating PIK3CA. Also, MEX3A could combine RIG-I to promote its ubiquitylation and proteasome-dependent degradation, which is beneficial for tumorigenesis [28].

However, the mechanisms of the MEX3A function have yet to be elucidated in OC. To the best of our knowledge, this is the first study that reported the role of MEX3A in OC through bioinformatics analysis of public sequencing data to guide future research in OC.

First, the results of the prognostic analysis showed that upregulation of MEX3A mRNA expression had the greatest correlation with poor OS and PFS in OC patients. In addition, we performed a series of in vitro experiments, which proved the inhibition of OC development by MEX3A knockdown. Hence, we speculate that MEX3A is extremely important as a prognostic indicator in OC patients and can be used as a predictor of tumor proliferation and metastasis. These results are consistent with bladder cancer, lung adenocarcinoma, and glioma [29–31]. Liang et al. found that MEX3A could enhance the instability of LAMA2 mRNA to promote lung adenocarcinoma metastasis by the PI3K/AKT pathway. In addition, they reported that MEX3A exerted its ubiquitination role to induce glioma tumorigenesis.

To explore the specific mechanisms of MEX3A in OC, a comprehensive bioinformatic analysis of MEX3A has been performed. Copy number variations (CNVs) have major genomic implications in human diseases, especially cancer, which can lead to phenotypic differences [30]. We found that the major CNV type of MEX3A was amplification, which was associated with shorter survival. Besides, neighboring gene networks close to MEX3A generally showed different degrees of amplification in OC. The genes coexpressed with MEX3A were subjected to functional and pathway enrichment analyses, and the results indicated that they were mainly involved in the immune response processes during tumorigenesis and progression of ovarian cancer.

We also constructed a gene-gene interaction network. The results suggested that MEX3A interacted intensively with other genes, such as PABPC1 and LAMTOR2. PABPC1 has been reported to bind the poly(A) tails of mRNAs, regulating the stability and biofunction of lncRNAs, which have critical roles in OC progression [31, 32]. PABPC1 could promote the binding of hnRNPLL (a plasma cell-specific RBP) to the immunoglobulin mRNA and regulate switching from mIgH to sIgH in plasma cells [33]. Yu et al. reported that PABPC1 could involve innate immune surveillance by regulating the activity of NK cells [34]. LAMTOR2, a regulator/LAMTOR complex member, activates AKT/mTOR to regulate dendritic cell homeostasis [20]. They implied that MEX3A might have an essential role in immunity by combining with PABPC1. Therefore, these results suggested that MEX3A and its related genes together regulate OC progression by a complex regulatory network.

Another important aspect of this study was that MEX3A expression was related to immune infiltration in OC. Our results demonstrated a moderate to a strong relationship between MEX3A expression level and infiltration level of macrophages, neutrophils, dendritic cells (DCs), B cells, and CD8+ T cells. Furthermore, immune cell activation and immunomodulators have been known for reducing mortality rates in patients with OC. In our study, we assessed the correlation between MEX3A and the immune system via the TIMER and TISIDB database, finding that MEX3A had the greatest correlation with lymphocytes (such as B cells, CD8+ T cells, neutrophils, and dendritic cells (DCs) and macrophages), immune inhibitors (such as IL10RB, IDO1, VTCN1, and HAVCR2), immunostimulators (such as C10orf54, TNFRSF18, TNFRSF14, and TNFRSF13C), and MHC molecules (such as B2M HLA-DMA HLA-DPA1, and HLA-DPB1). Therefore, MEX3A, which is associated with these immune-related genes, may provide a new target in immune therapy for OC.

The present study has several limitations. First, most results on the transcriptional level may reflect some aspects of immune infiltration. Also, reported findings need to be confirmed with larger clinical samples and experimental data using molecular biology techniques. Finally, we plan to further deepen our understanding of the underlying mechanism of immunomodulators related to MEX3A in our future work.

In conclusion, this study demonstrated that high MEX3A expression was correlated with poor prognosis and increased immune infiltration levels in macrophages, neutrophils, dendritic cells (DCs), B cells, and CD8+ T cells in OC. Our study provides a novel insight into the potential role of MEX3A as a cancer biomarker from the perspective of tumor immunology.

Data Availability

Previously reported [RNA-Seq] TCGA data were used to support this study and are available at GEPIA (doi: 10.1093/nar/gkx247), cBioPortal (doi: 10.1126/scisignal.2004088), LinkedOmics (doi: 10.1093/nar/gkx1090), and the Kaplan–Meier plotter (doi: 10.1530/ERC-11-0329). These prior studies (and datasets) are cited at relevant places within the text as references [9–11, 15]. There is no research data used to support this study.

Conflicts of Interest

The authors declare no conflicts of interest.

Authors’ Contributions

Panpan Zhang and Tong Su contributed equally to this work.

Acknowledgments

This work was supported by the National Natural Science Foundation of China (ID 81672564 to Shu Zhang).

Supplementary Materials

Figure S1: the mRNA expression levels of MEX3A in various cancers and prognostic values of MEX3A in ovarian cancer in the Kaplan–Meier plotter. (a) The expression of MEX3A in various cancers from Oncomine. The threshold was designed with the following parameters: and . The color intensity (red or blue) is directly proportional to the significance level of upregulation or downregulation. (b) The MEX3A expression levels in different tumor types from the TCGA database were determined by GEPIA. (c, d) Prognostic significance of MEX3A in serous ovarian carcinoma. (e, f) Prognostic significance of MEX3A in endometrioid carcinoma. , , and . (Supplementary Materials)

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