Skip to main content
NCBI home page
BioMed Research International logoLink to BioMed Research International
. 2020 Sep 24;2020:7804706. doi: 10.1155/2020/7804706

EEF1D Promotes Glioma Proliferation, Migration, and Invasion through EMT and PI3K/Akt Pathway

Cheng Xie 1, Mingfeng Zhou 1, Jie Lin 1, Zhiyong Wu 2, Shengfeng Ding 1, Jie Luo 1, Zhengming Zhan 1, Yonghua Cai 1, Shuaishuai Xue 1, Ye Song 1,✉
PMCID: PMC7533006  PMID: 33029523

Abstract

Eukaryotic translation elongation factor 1δ (EEF1D), a subunit of the elongation factor 1 complex of proteins, mediates the elongation process of protein synthesis. Besides this canonical role, EEF1D was found overexpressed in many tumors, like hepatocarcinomas and medulloblastomas. In the present study, we demonstrated for the first time that EEF1D may interact with other putative proteins to regulate cell proliferation, migration, and invasion through PI3K/Akt and EMT pathways in glioma. Furthermore, knockdown of EEF1D could reduce cell proliferation and impaired epithelial-mesenchymal transition (EMT) phenotypes, including cell invasion. Taken together, these results indicate that EEF1D and its partner proteins might play a critical role in glioma and serve as a potential therapeutic target of glioma.

1. Introduction

Glioma, the most common and malignant primary brain tumor, is characterized by high-grade proliferation, invasion, and poor prognosis. Being an aggressive tumor, glioma also shows poor response to common therapeutic treatments including surgery, radiation, and conventional concomitant and adjuvant chemotherapy with temozolomide (TMZ). Although treatment methods advanced during the past decades, the median survival of glioma is still about 14.6 months and five-year survival is less than 10% [1–4]. Considering that the molecular mechanism underlying glioma is still ambiguous, it is an urgent need to unravel mechanisms of proliferation, invasion, and resistance to identify weaknesses that may be exploited using new and existing agents to increase survival from glioma.

EEF1D, as a part of the eukaryotic translation elongation factor 1 (EEF1) complex, serves as the enzymatic delivery of aminoacyl tRNAs to the ribosome and functions as a guanine nucleotide exchange factor. Based on the canonical and noncanonical functions [5, 6], emerging amounts of evidence indicate that EEF1 proteins, particularly the prototypical member EEF1D, may play a role in the control of cellular processes during tumorigenesis [6]. In 2000, Shuda et al. reported a higher level of EEF1D mRNA in hepatocarcinomas [7], and in 2008, Piltti et al. reported the correlation of EEF1D with phosphorylation of ERK of the MAP kinase pathway in chondrosarcoma [8]. Later, with advances in detection approaches, such as chromosomal comparative genomic hybridization, two-dimensional electrophoresis coupled with MALDI–TOF-MS and quantitative PCR, the upregulation of EEF1D was described by several researchers in other cancers like esophageal carcinomas [9], non-small-cell lung cancers [10], and medulloblastomas [11]. However, little has been uncovered regarding the underlying biological mechanisms correlated with EEF1D overexpression in glioma, and the involvement of EEF1D in glioma tumorigenesis has not yet been investigated.

In the present study, we found that EEF1D may play a role in the development of glioma through multiple pathways and provided new insights into the glioma initiation. We also speculated that EEF1D may be involved in multiple major cell signaling pathways simultaneously like EMT and PI3K/Akt pathways to regulate cell survival, migration, and invasion in glioma. Furthermore, EEF1D may constitute a new prospect for a therapeutic target against human glioma.

2. Materials and Methods

2.1. Bioinformatics Analysis

The genomic expression data and clinicopathological data of 163 GBM tissues, 518 LGG tissues, and 207 normal brain tissues were downloaded from The Cancer Genome Atlas (TCGA, https://tcga-data.nci.nih.gov/TCGA). The putative EEF1D-interacting proteins were subjected to functional annotation analysis using FunRich analysis tool [12, 13].

2.2. Cell Culture

The U87 and A172 glioblastoma cell lines were purchased from the American Type Culture Collection (ATCC, USA). All cell lines were cultured in Dulbecco's modified Eagle's medium (DMEM) (Hyclone, Logan, USA) supplemented with 10% fetal bovine serum (FBS, Hyclone, USA) and incubated in a humidified atmosphere under 5% CO2 at 37°C.

2.3. Collection of Clinical Samples

Clinical sample tissues were collected from patients afflicted with glioma. All samples were then confirmed pathological diagnosis and classified according to the World Health Organization (WHO) criteria. Every human tissue was obtained with advanced written informed consent from patients or their guardians before participation in the study, and approval from the Ethics Committees of Nanfang Hospital of Guangdong Province was obtained.

2.4. Western Blot

Western blot was performed as previously described. The cells or clinical tissues were washed thoroughly with PBS three times and lysed with RIPA Buffer (50 mM Tris-HCl pH 8.0, 1 mM EDTA pH 8.0, 5 mM DTT, 2% SDS) with a protease inhibitor and phosphoric-acid protease inhibitor under 4°C for 30 minutes. The protein concentration was then determined using BCA assay (Beyotime Inc., China). The proteins were separated subsequently using SDS-PAGE gel and electro-transferred to polyvinylidene difluoride membranes (Invitrogen, Carlsbad, CA). The membranes were blocked with 5% BSA and then incubated with primary antibodies, including EEF1D (PTG, USA); E-cadherin, N-cadherin, β-catenin, slug, snail, and vimentin (Cell Signaling Technology, USA); PI3K and PI3K (phosopho-Tyr467/199); Akt and p-Akt (phosphor-Ser473) (SAB, USA); and GAPDH (CWbio, China), overnight at 4°C and then incubated with horseradish peroxidase-conjugated secondary antibody for 1 h under room temperature. Finally, signals were detected using enhanced chemiluminescence reagents (Pierce, Rockford, IL, USA). All experiments were independently performed in triplicate.

2.5. IHC

For IHC, tissue sections underwent gradient ethanol dehydration and infiltration of histological samples in tissue processor, were embedded in paraffin and 4 μm thin sectioned, and were then deparaffinized in xylene. After washing thoroughly with PBS, the slides were treated with 10 mM citrate buffer for 2 minutes at 100°C to achieve antigen retrieval and treated with 3% hydrogen peroxide to block endogenous peroxidase activity. After washing thoroughly with PBS, slides were blocked with 5% BSA for 1 hour at room temperature and incubated with EEF1D primary antibody (PTG, USA) at 4°C overnight. After washing thoroughly with PBS, the slides were incubated with biotin-labeled goat anti-mouse or anti-rabbit antibodies (ZSGBbio, China) for 1 hour at room temperature. The sections were finally visualized with DAB, counterstained with hematoxylin, mounted in neutral gum, and imaged using a bright field microscope equipped with a digital camera (Leica, Germany).

2.6. Small Interfering RNA (siRNA) Transfection

Transfection of siRNA was performed according as previously described [14]. For EEF1D knockdown, siRNA targeting EEF1D along with the negative control was designed and synthesized by RiboBio (Guangzhou, China). The sequences to EEF1D were GCCGCAACAUCUUAGGGAA (siEEF1D-1), GCAACAUCUUAGGGAACAA (siEEF1D-2), and CCUUGCCCUACUGUUACUU (siEEF1D-3). Among three siRNAs targeting on EEF1D gene, the most effective one (siEEF1D) was identified by Western blot and applied for the further experiments. Glioma cells U87 and A172 were plated onto a 6-well plate at 30-50% confluence. After incubation for 6 hours at 37°C in a 5% CO2 atmosphere, siEEF1D mixed with Lipo2000 (Thermo Fisher, USA) was then transfected into cells following the manufacturer's protocol. Cells were then collected after 24-48 hours for further experiments.

2.7. Transwell and Boyden Assays

In vitro cell migration Transwell assay and invasion Boyden assay were performed according as previously described [14]. For the Transwell assay, 1 × 104 cells in 100 μl DMEM medium without FBS were seeded onto the upper chamber of the Transwell apparatus (Costar, MA), and 500 μl DMEM with 10% FBS was added into the lower chamber as a chemoattractant. After incubation for 6 hours at 37°C in a 5% CO2 atmosphere, the fibronectin-coated polycarbonate membrane insert was washed with PBS, and cells adhering to the top surface of the insert were removed with a cotton swab. Cells on the lower surface were then fixed with methanol, stained with crystal violet solution, and counted under a microscope in five predetermined fields (200x). All assays were independently repeated at least thrice. For the Boyden assay, the procedure was similar to the above one, except for the fact that the Transwell membranes were first precoated with 24 μg/μl Matrigel (R&D Systems, USA), and the cells were incubated in the Transwell apparatus for 8 hours at 37°C in a 5% CO2 atmosphere. Cells on the lower surface were counted in the same way as the cell migration assay.

2.8. Immunoprecipitation

For immunoprecipitation, glioma U87 cells were rinsed once with cold PBS and lysed with Pierce™ IP Lysis Buffer (Thermo Fisher, USA). Lysates were kept on ice for 10 minutes and centrifuged at 12,000 rpm for 15 minutes. The supernatant was then incubated for 4 hours with protein A/G beads (Bimake, China) preloaded with EEF1D antibody (PTG, USA) at room temperature. The immunoprecipitate was rinsed three times with washing buffer (Thermo Fisher, USA), suspended in SDS loading buffer and boiled for 8 minutes at 95°C. Immunoprecipitated proteins were analyzed by SDS-PAGE/Western blotting.

2.9. Liquid Chromatograph-Mass Spectrometer (LC-MS) Analysis

In brief, immunoprecipitated peptides were applied for further liquid chromatograph-mass spectrometry (LC-MS) analysis using a micro HPLC (high pressure liquid chromatography) system connected to an LCQ Deca XP-plus ESI ion-trap mass spectrometer. Chromatographic separation is performed by normal-phase HPLC on a TSK-gel Amide-80 (3 μm) column (2 × 150 mm). The LC-MS parameters were determined as described previously [15], and the mass spectra were obtained by ion monitoring based on m/z.

3. Results

3.1. Expression of EEF1D in LGG, GBM, and Nontumor Brain Tissues

By analyzing the data from TCGA database, we characterized EEF1D expression in 5 cases of nontumor brain tissues, 511 cases of LGG samples, and 156 cases of GBM samples. EEF1D expression was significantly higher in LGG and GBM samples (P < 0.01) (Figure 1(a)). Besides, consistent with TCGA results, EEF1D was increased in LGG and GBM compared to normal brain tissues by immunoblotting (Figure 1(b)). Consistently, we further confirmed higher expression in high-grade glioma than low-grade glioma using IHC staining and the IHC score (Figure 2). Moreover, we also detected higher EEF1D expression in U87 and A172 glioblastoma cell lines among six commonly used glioma cell lines (Figure 1(c)), so U87 and A172 glioblastoma cell lines were chosen for a further experiment.

Figure 1.

Figure 1

Open in a new tab

Expression of EEF1D in LGG, GBM, and nontumor brain tissues. (a) EEF1D expressions at mRNA level in normal brain tissues (N = 5), low-level glioma (LGG) (N = 511), and glioblastoma (GBM) (N = 156) were analyzed utilizing TCGA database. (b). EEF1D expressions at protein level were analyzed in clinical samples, including nontumor brain tissues (N = 3), grade I (N = 3), grade II (N = 2), grade III (N = 2), and grade IV (N = 3). (c). EEF1D expressions at protein level were analyzed in six glioma cell lines (U87, A172, U251, U118, T98, and LN229).

Figure 2.

Figure 2

Open in a new tab

Expression of EEF1D in different grade glioma tissues by immunohistology. (a) Representative immunohistochemical staining samples of different grade human glioma (A—grade I, B—grade II, C—grade III, and D—grade IV) with anti-EEF1D antibody. Scale bars: 200 μm for low magnification image and 100 μm for high magnification image. (b) The IHC score of different clinical sample tissues (including grade I (n = 14), grade II (n = 38), grade III (n = 31), and grade IV (n = 25)) was analysed by using an independent samples t test (∗∗∗P < 0.001, P = 0.0043; ∗∗∗∗P < 0.0001).

3.2. Inhibition of EEF1D Impaired Proliferation, Migration, and Invasion of Glioma Cells

To investigate the influence of EEF1D on glioma cells, we constructed siRNA targeting EEF1D gene. As expected, EEF1D expression was significantly decreased in both U87 and A172 cells after transfection with EEF1D-siRNA (Figures 3(a) and 3(b)), which in turn resulted in significant inhibition of glioma cell proliferation (Figures 3(c) and 3(d)). Transwell assay further determined that depletion of EEF1D could impair the migration capacity of U87 and A172 cells (Figures 3(e) and 3(f)) and resulted in lower invasion capacity compared to negative control group, as Boyden assays have shown (Figures 3(g) and 3(h)). In summary, these results proposed that inhibition of EEF1D could suppress the cell growth and reduce the malignant phenotype-like proliferation, migratory, and invasion of glioma cells.

Figure 3.

Figure 3

Open in a new tab

Inhibition of EEF1D impaired proliferation, migration, and invasion of glioma cells. (a) Efficacy of EEF1D-siRNA on EEF1D expression in U87 and A172 glioma cells, respectively. (b) Quantification results of (a). (c) Effect of EEF1D on proliferation of U87 and A172 glioma cells in vitro. The U87 and A172 glioma cells were subjected to CCK-8 assay for 5 d. There was a significant difference between two groups at day 5. NC: negative control siRNA-transfected cells; siEEF1D: EEF1D-siRNA transfected cells (∗∗P < 0.01 as compared with NC). (d) Quantification results of (c). (e, g) Transwell assay and Boyden assay were performed to determine cell migration and invasion in glioma U87 and A172 cell transfected with EEF1D-siRNA or negative control siRNA, respectively. NC: negative control siRNA-transfected cells; siEEF1D: EEF1D-siRNA-transfected cells (∗∗P < 0.01 as compared with NC). Scale bars: 100 μm. (f, h) Quantification results of (c) and (e) respectively.

3.3. Knockdown of EEF1D Could Regulate the Expression of EMT Markers and Suppressed the Activation of PI3K/Akt Signaling Pathway

To investigate the underlying mechanism of EEF1D, the protein levels of EMT markers and PI3K/Akt signaling pathway were measured to further determine the effects of EEF1D suppression after transfection with EEF1D-siRNA in U87 and A172 glioma cells. As shown in Figures 4(a) and 4(b), levels of the epithelial marker E-cadherin were slightly promoted, whereas the expression of mesenchymal markers including N-cadherin and Snail was significantly downregulated in U87 and A172 glioma cells following EEF1D-siRNA transfection. Further, β-catenin, a critical transcriptional factor of the EMT process, was also decreased after EEF1D knockdown. Taken together, these findings suggested that EEF1D was closely associated with the modulation of EMT progress in glioma cells, and inhibition of EEF1D could reverse the EMT characteristics of glioma cells.

Figure 4.

Figure 4

Open in a new tab

Downregulation of EEF1D could regulate the expression of EMT markers and suppressed the activation of the PI3K/AKT signaling pathway. (a) Protein levels of EMT markers were detected in U87 and A172 glioma cells by Western blot. GAPDH was also detected as the control of sample loading. NC: negative control siRNA-transfected cells. siEEF1D: EEF1D-siRNA-transfected cells. Data were based on at least three independent experiments and shown as the mean ± SD (∗∗P < 0.01 as compared with NC). (b) Quantification results of (a). (c) Protein levels of PI3K/Akt signal pathway were detected in U87 and A172 glioma cells by Western blot. GAPDH was also detected as the control of sample loading. NC: negative control siRNA-transfected cells; siEEF1D: EEF1D-siRNA-transfected cells. Data were based on at least three independent experiments and shown as the mean ± SD (∗∗P < 0.01 as compared with NC). (d) Quantification results of (c).

The PI3K/Akt pathway has been identified as a key regulator to growth and proliferation of malignant glioma cells. In the present study, Western blot results revealed that PI3K, p-PI3K, Akt, and p-Akt in glioma cells transfected with EEF1D-siRNA were significantly lower than those transfected with NC-siRNA (P < 0.05; Figure 4(c)). Thereby, the downregulation of EEF1D expression suppressed the activation of the PI3K/Akt pathway, which in turn might impede cell proliferation.

3.4. Identification of EEF1D Interacting Proteins

In order to further figure out the regulatory network of EEF1D on several signaling pathways, we carried out immunoprecipitation assays combined with LC-MS/MS to achieve qualitative and quantitative analyses of the potential EEF1D-interacting partners. As expected, EEF1D was immunoprecipitated with the EEF1D-specific antibody while no protein amounts were detected in the control IgG sample (Figure 5(a)). The top 20 putative specific interactors are listed in Table 1. Next, GO functional and KEGG pathway enrichment analyses were performed using the software of enrichment analysis tool FunRich: Functional Enrichment analysis tool [16–18]. Based on their primary biological processes, the majority of these proteins were considered involved in distinct functions. The detailed enriched GO functions for the interacting proteins are presented in Supplement Excel. In aspect of molecular function (Venkatesan, Lamfers et al.), top 10 associated functions were RNA binding, structural constituent of ribosome, structural constituent of cytoskeleton, ribonucleoprotein, translation regulator activity, et al., as displayed in Figures 5(b) and 5(c). Thus, the annotation of the biological process (BP) showed that proteins immunoprecipitated with EEF1D were mainly related to the regulation of nucleobase, nucleoside, nucleotide, and nucleic acid metabolism; signal transduction; cell growth and/or maintenance; and protein metabolism (Figures 5(d) and 5(e)). In addition, distribution of interacting proteins according to cellular component (CC) was also noted (Figures 5(f) and 5(g)). Via the biological pathway analysis, we discovered that the nucleic acid metabolism and cell growth were the most significantly enriched. Therefore, we speculated that EEF1D was likely to be involved in DNA replication and RNA synthesis through binding catalytic proteins and regulating its capacity.

Figure 5.

Figure 5

Open in a new tab

Identification of EEF1D interacting proteins. (a) Immunoprecipitation assays showing a good efficacy of specific EEF1D antibody. The top 10 enriched (b and c) molecular function (Venkatesan, Lamfers et al.) pathways, (d and e) biological process (BP) pathways, and (f and g) cellular component (CC) pathways of putative EEF1D-interacting protein from GO analysis by FunRich.

Table 1.

The putative specific interactors of EEF1D.

Accession Gene name Description Coverage Peptides PSMs Unique peptides AAs MW (kDa) calc. pI
P35579 MYH9 Myosin-9, OS = Homo sapiens, GN = MYH9, PE = 1, SV = 4 45.86734694 123 334 106 1960 226.392 5.6
Q86UP2 KTN1 Kinectin, OS = Homo sapiens, GN = KTN1, PE = 1, SV = 1 48.78408254 76 162 76 1357 156.179 5.64
Q15149 PLEC Plectin, OS = Homo sapiens, GN = PLEC, PE = 1, SV = 3 11.33646456 52 58 52 4684 531.466 5.96
A0A024RCN6 VARS VARS, OS = Homo sapiens, GN = VARS, PE = 3, SV = 1 29.2721519 41 80 41 1264 140.387 7.59
A7BI36 RRBP1 p180/ribosome receptor, OS = Homo sapiens, GN = RRBP1, PE = 2, SV = 2 29.28571429 39 55 39 1540 165.649 8.97
V9HWE1 HEL113 Epididymis luminal protein 113, OS = Homo sapiens, GN = HEL113, PE = 2, SV = 1 54.72103004 30 75 30 466 53.619 5.12
A0A0D9SF53 DDX3X ATP-dependent RNA helicase DDX3X, OS = Homo sapiens, GN = DDX3X, PE = 1, SV = 1 32.74215553 28 44 27 733 81.426 8.07
H6VRG1 KRT1 Keratin 1, OS = Homo sapiens, GN = KRT1, PE = 3, SV = 1 40.31007752 29 64 24 645 66.086 8.12
P35908 KRT2 Keratin, type II cytoskeletal 2 epidermal, OS = Homo sapiens, GN = KRT2, PE = 1, SV = 2 41.15805947 27 46 21 639 65.393 8
A0A024RBH2 CKAP4 Cytoskeleton-associated protein 4, isoform CRA_c, OS = Homo sapiens, GN = CKAP4, PE = 4, SV = 1 42.19269103 21 28 21 602 65.983 5.92
Q12965 MYO1E Unconventional myosin-Ie, OS = Homo sapiens, GN = MYO1E, PE = 1, SV = 2 17.96028881 20 27 20 1108 126.982 8.92
Q92900 UPF1 Regulator of nonsense transcript 1, OS = Homo sapiens, GN = UPF1, PE = 1, SV = 2 17.00620018 19 25 19 1129 124.267 6.61
Q9C0C2 TNKS1BP1 182 kDa tankyrase-1-binding protein, OS = Homo sapiens, GN = TNKS1BP1, PE = 1, SV = 4 13.47599769 19 19 19 1729 181.685 4.86
P13645 KRT10 Keratin, type I cytoskeletal 10, OS = Homo sapiens, GN = KRT10, PE = 1, SV = 6 30.1369863 20 40 18 584 58.792 5.21
Q9UPQ9 TNRC6B Trinucleotide repeat-containing gene 6B protein, OS = Homo sapiens, GN = TNRC6B, PE = 1, SV = 4 13.09328969 18 25 18 1833 193.883 6.76
Q1KMD3 HNRNPUL2 Heterogeneous nuclear ribonucleoprotein U-like protein 2, OS = Homo sapiens, GN = HNRNPUL2, PE = 1, SV = 1 22.75769746 18 23 18 747 85.052 4.91
P35527 KRT9 Keratin, type I cytoskeletal 9, OS = Homo sapiens, GN = KRT9, PE = 1, SV = 3 28.57142857 17 42 17 623 62.027 5.24
Q96PK6 RBM14 RNA-binding protein 14, OS = Homo sapiens, GN = RBM14, PE = 1, SV = 2 24.36472347 17 27 17 669 69.449 9.67
Q5JSZ5 PRRC2B Protein PRRC2B, OS = Homo sapiens, GN = PRRC2B, PE = 1, SV = 2 10.31852849 18 23 17 2229 242.817 8.34
A0A087WTP3 KHSRP Far upstream element-binding protein 2, OS = Homo sapiens, GN = KHSRP, PE = 1, SV = 1 30.09845288 17 28 17 711 72.982 7.71
Open in a new tab

Taken together, these results indicated that EEF1D might bind to other proteins, like the protein of the EMT and PI3K/Akt pathway, to form a functional complex to regulate the progression phenotype of glioma cells.

4. Discussion

In the present study, aberrant expression of EEF1D was confirmed in glioma samples in comparison with nontumor brain tissues. Besides, blocking the EEF1D restrained the critical EMT and PI3K/Akt pathway. Furthermore, GO functional and KEGG pathway enrichment analyses revealed that EEF1D might bind to other proteins to mediate nucleic acid metabolism and cell growth. These results indicate that EEF1D may play a critical role in glioma cell proliferation, migration, and invasion and acts as an oncogene in glioma.

Proteomic analysis shows that EEF1D is overexpressed in right-sided colon cancer [19] and correlates with the invasive status of Adriamycin-resistant variants of DLKP, a squamous lung and cancer cell line [20]. Genomic analysis in medulloblastoma also reveals that a higher EEF1D level was adversely associated with outcome [11]. Isadora et al. reported that overexpressed EEF1D leads to the modulation of proliferation via cyclin D1 and EMT and invasion in oral squamous cell carcinoma [6]. Consistently, in the present study, we found that the expression of EEF1D, as indicated both by immunohistology staining and immunoblotting, was elevated and positively correlated with glioma grade.

Besides the canonical role of EEF1D as a direct substrate for casein kinase 2 (CK2), an important regulator of cell cycle progression, apoptosis, and transcription [21, 22], EEF1D, could also participate in autoubiquitination and degradation by interacting with SIAH E3 ubiquitin protein ligase 1 (SIAH-1) [23]. Several researchers reported that gene amplification, genetic methylation, and posttranslational modification may play a role in the mechanisms of EEF1 superfamily proteins in different cancers [24].

Epithelial-mesenchymal transition (EMT), represented by remarkable morphological changes from an epithelial cobblestone phenotype to an elongated fibroblastic phenotype, provides a new insight into the potential mechanism for the glioma metastasis and invasiveness. EMT is characterized by a decreased expression of epithelial markers, such as E-cadherin, and an increased expression of mesenchymal markers, such as N-cadherin and vimentin, and transcription factors, such as slug, snail, and β-catenin [25–28]. EMT is a transcriptional process in which epithelial cells adopt mesenchymal properties by loss of cell-cell adhesion, acquisition of migratory and invasive properties, and loss of cell polarity, related to tumor initiation, invasion, metastasis to distant sites, and resistance to chemo- and/or radiotherapy [27, 28]. The PI3K/Akt signaling pathway, a well-known pathway in the regulation of tumorigenesis, tumorigenesis, is also activated in glioma [29, 30]. As an important intracellular signaling pathway, PI3K/Akt is known to be closely associated with the proliferation, migration, and progression of tumors, including glioma [31–33]. Besides, EMT pathways could cross talk with the PI3K/Akt/GSK3β pathway in glioma, through HIF-1α, PTEN, and the WNT/β-catenin pathways [28].

Our results suggested that EEF1D exerts its effect on glioma by promoting EMT and PI3K/Akt signaling pathways, which could be the potential mechanism by which EEF1D promotes tumor progression.

According to the results of GO analysis of the EEF1D interacting protein, the most enriched molecular functions were involved in the regulation of RNA binding, structural constituent of ribosome, nucleic acid metabolism, et al., which is crucial for maintaining the normal state of the cell metabolism process. RNA binding, structural constituent of ribosome, and nucleic acid metabolism were involved in the conventional DNA replication and RNA transcription process, which is extremely activated in tumor, like breast cancer, colon cancer, and glioma. Several potential targeted proteins of EEF1D, such as NFIC and RBMX, were reported to participate in the regulation of proliferation and EMT transition [25, 34, 35]. RBMX, also known as hnRNP G, was involved in various processes, like pre-mRNA splicing and posttranscriptional regulatory mechanism [36, 37], which were related to several vital processes of tumor initiation, progression, and metastasis. Alteration of the processes induced by aberrant expression of EEF1D may impair the indispensable nucleic acid metabolism and translational deregulation and finally impede tumor cell survival and progression including glioma. As for the biological process, multifarious cancer-related processes, such as nucleic acid metabolism, cell growth, protein metabolism, and mitosis, were the most common among the enriched pathways of the interacting proteins, consistent to the enriched results of the molecular function.

5. Conclusion

Overall, our results contribute to the knowledge of EEF1D effects on glioma and provide insights into the mechanism of glioma through mediating EMT and PI3K/Akt pathways. Therefore, blocking EEF1D could restrain EMT and PI3K/Akt activity resulting in the suppression of cell growth and tumor progression. However, the detailed mechanism of EEF1D on glioma progression phenotype remains elusive and needs further investigation. Overall, our data provide evidence that EEF1D might serve as a potential therapeutic target for glioma.

Acknowledgments

This study was supported by the National Nature Science Fund of China (Grant No. 81872064), Natural Science Foundation of Guangdong Province of China (Grant No. 2020A151501122), Science and Technology Program of Guangzhou, China (Grant No. 201903010048), and Outstanding Youths Development Scheme of Nanfang Hospital, Southern Medical University (Grant No. 2016J008).

Data Availability

The genomic expression data and clinicopathological data of 163 GBM tissues, 518 LGG tissues, and 207 normal brain tissues were downloaded from The Cancer Genome Atlas (TCGA, https://tcga-data.nci.nih.gov/TCGA). The putative EEF1D-interacting proteins were subjected to functional annotation analysis using FunRich analysis tool (Pathan et al. 2015).

Conflicts of Interest

All the authors declare that there was no conflict of interest.

Authors' Contributions

YS conceived and designed the experiments; CX and MZ performed the experiments; JL, ZW, and SD performed the analysis; JL, ZZ, and YC contributed to reference collecting; SX contributed to specimen collecting; CX contributed to writing. All authors have read and approved the final manuscript. Cheng Xie, Mingfeng Zhou, and Jie Lin have equally contributed to this work.

References

  • 1.Barthel F. P., Wesseling P., Verhaak R. G. W. Reconstructing the molecular life history of gliomas. Acta Neuropathologica. 2018;135(5):649–670. doi: 10.1007/s00401-018-1842-y. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 2.Buckner J., Giannini C., Eckel-Passow J., et al. Management of diffuse low-grade gliomas in adults - use of molecular diagnostics. Nature Reviews. Neurology. 2017;13(6):340–351. doi: 10.1038/nrneurol.2017.54. [DOI] [PubMed] [Google Scholar]
  • 3.Diamandis P., Aldape K. D. Insights from molecular profiling of adult glioma. Journal of Clinical Oncology. 2017;35(21):2386–2393. doi: 10.1200/JCO.2017.73.9516. [DOI] [PubMed] [Google Scholar]
  • 4.Lim M., Xia Y., Bettegowda C., Weller M. Current state of immunotherapy for glioblastoma. Nature Reviews Clinical Oncology. 2018;15(7):422–442. doi: 10.1038/s41571-018-0003-5. [DOI] [PubMed] [Google Scholar]
  • 5.Dever T. E., Green R. The elongation, termination, and recycling phases of translation in eukaryotes. Cold Spring Harbor Perspectives in Biology. 2012;4(7):p. a013706. doi: 10.1101/cshperspect.a013706. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 6.Flores I. L., Kawahara R., Miguel M. C. C., et al. EEF1D modulates proliferation and epithelial-mesenchymal transition in oral squamous cell carcinoma. Clinical Science. 2016;130(10):785–799. doi: 10.1042/CS20150646. [DOI] [PubMed] [Google Scholar]
  • 7.Shuda M., Kondoh N., Tanaka K., et al. Enhanced expression of translation factor mRNAs in hepatocellular carcinoma. Anticancer Research. 2000;20(4):2489–2494. [PubMed] [Google Scholar]
  • 8.Piltti J., Häyrinen J., Karjalainen H. M., Lammi M. J. Proteomics of chondrocytes with special reference to phosphorylation changes of proteins in stretched human chondrosarcoma cells. Biorheology. 2008;45(3-4):323–335. doi: 10.3233/BIR-2008-0481. [DOI] [PubMed] [Google Scholar]
  • 9.Ogawa K., Utsunomiya T., Mimori K., et al. Clinical significance of elongation factor-1 delta mRNA expression in oesophageal carcinoma. British Journal of Cancer. 2004;91(2):282–286. doi: 10.1038/sj.bjc.6601941. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 10.Liu Y., Chen Q., Zhang J. T. Tumor suppressor gene 14-3-3sigma is down-regulated whereas the proto-oncogene translation elongation factor 1delta is up-regulated in non-small cell lung cancers as identified by proteomic profiling. Journal of Proteome Research. 2004;3(4):728–735. doi: 10.1021/pr034127+. [DOI] [PubMed] [Google Scholar]
  • 11.De Bortoli M., Castellino R. C., Lu X.-Y., et al. Medulloblastoma outcome is adversely associated with overexpression of EEF1D, RPL30, and RPS20 on the long arm of chromosome 8. BMC Cancer. 2006;6(1):p. 223. doi: 10.1186/1471-2407-6-223. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 12.Li J., Cai T., Deng K., Wang X., Sellis T., Xia F. Community-diversified influence maximization in social networks. Information Systems. 2020;92:p. 101522. doi: 10.1016/j.is.2020.101522. [DOI] [Google Scholar]
  • 13.CAI T. A. O. T. A. O., Li J., Mian A. S., li R., Sellis T., Yu J. X. IEEE Transactions on Knowledge and Data Engineering. 2020. Target-aware Holistic Influence Maximization in Spatial Social Networks; p. p. 1. [DOI] [Google Scholar]
  • 14.Song Y., Zheng S., Wang J., et al. Hypoxia-induced PLOD2 promotes proliferation, migration and invasion via PI3K/Akt signaling in glioma. Oncotarget. 2017;8(26):41947–41962. doi: 10.18632/oncotarget.16710. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 15.Zhang H., Young S. P., Auray-Blais C., Orchard P. J., Tolar J., Millington D. S. Analysis of glycosaminoglycans in cerebrospinal fluid from patients with mucopolysaccharidoses by isotope-dilution ultra-performance liquid chromatography-tandem mass spectrometry. Clinical Chemistry. 2011;57(7):1005–1012. doi: 10.1373/clinchem.2010.161141. [DOI] [PubMed] [Google Scholar]
  • 16.Chatzileontiadou D. S. M., Samiotaki M., Alexopoulou A. N., et al. Proteomic analysis of human angiogenin interactions reveals cytoplasmic PCNA as a putative binding partner. Journal of Proteome Research. 2017;16(10):3606–3622. doi: 10.1021/acs.jproteome.7b00335. [DOI] [PubMed] [Google Scholar]
  • 17.Gao J. M., Huang L. Z., Huang Z. G., He R. Q. Clinical value and potential pathways of miR-183-5p in bladder cancer: a study based on miRNA-seq data and bioinformatics analysis. Oncology Letters. 2018;15(4):5056–5070. doi: 10.3892/ol.2018.7967. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 18.Yi H., Zheng X., Song J., Shen R., Su Y., Lin D. Exosomes mediated pentose phosphate pathway in ovarian cancer metastasis: a proteomics analysis. International Journal of Clinical and Experimental Pathology. 2015;8(12):15719–15728. [PMC free article] [PubMed] [Google Scholar]
  • 19.Shen H., Huang J., Pei H., et al. Comparative proteomic study for profiling differentially expressed proteins between Chinese left- and right-sided colon cancers. Cancer Science. 2013;104(1):135–141. doi: 10.1111/cas.12029. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 20.Keenan J., Murphy L., Henry M., Meleady P., Clynes M. Proteomic analysis of multidrug-resistance mechanisms in adriamycin-resistant variants of DLKP, a squamous lung cancer cell line. Proteomics. 2009;9(6):1556–1566. doi: 10.1002/pmic.200800633. [DOI] [PubMed] [Google Scholar]
  • 21.Gyenis L., Duncan J. S., Turowec J. P., Bretner M., Litchfield D. W. Unbiased functional proteomics strategy for protein kinase inhibitor validation and identification of bona fide protein kinase substrates: application to identification of EEF1D as a substrate for CK2. Journal of Proteome Research. 2011;10(11):4887–4901. doi: 10.1021/pr2008994. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 22.Sivan G., Aviner R., Elroy-Stein O. Mitotic modulation of translation elongation factor 1 leads to hindered tRNA delivery to ribosomes. The Journal of Biological Chemistry. 2011;286(32):27927–27935. doi: 10.1074/jbc.M111.255810. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 23.Cheng D. D., Li S. J., Zhu B., Zhou S. M., Yang Q. C. EEF1D overexpression promotes osteosarcoma cell proliferation by facilitating Akt-mTOR and Akt-bad signaling. Journal of Experimental & Clinical Cancer Research. 2018;37(1):p. 50. doi: 10.1186/s13046-018-0715-5. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 24.Liu X., Yang J., Zhang Q., Jiang L. Regulation of DNA methylation on EEF1D and RPL8 expression in cattle. Genetica. 2017;145(4-5):387–395. doi: 10.1007/s10709-017-9974-x. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 25.Huang X., Xu X., Bringas P Jr, Hung Y. P., Chai Y. Smad4-Shh-Nfic signaling cascade-mediated epithelial-mesenchymal interaction is crucial in regulating tooth root development. Journal of Bone and Mineral Research. 2010;25(5):1167–1178. doi: 10.1359/jbmr.091103. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 26.Iser I. C., Pereira M. B., Lenz G., Wink M. R. The epithelial-to-mesenchymal transition-like process in glioblastoma: an updated systematic review and in silico investigation. Medicinal Research Reviews. 2017;37(2):271–313. doi: 10.1002/med.21408. [DOI] [PubMed] [Google Scholar]
  • 27.Kahlert U. D., Nikkhah G., Maciaczyk J. Epithelial-to-mesenchymal(-like) transition as a relevant molecular event in malignant gliomas. Cancer Letters. 2013;331(2):131–138. doi: 10.1016/j.canlet.2012.12.010. [DOI] [PubMed] [Google Scholar]
  • 28.Meel M. H., Schaper S. A., Kaspers G. J. L., Hulleman E. Signaling pathways and mesenchymal transition in pediatric high-grade glioma. Cellular and Molecular Life Sciences. 2018;75(5):871–887. doi: 10.1007/s00018-017-2714-7. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 29.Huang B. S., Luo Q. Z., Han Y., Huang D., Tang Q. P., Wu L. X. MiR-223/PAX6 axis regulates glioblastoma stem cell proliferation and the chemo resistance to TMZ via regulating PI3K/Akt pathway. Journal of Cellular Biochemistry. 2017;118(10):3452–3461. doi: 10.1002/jcb.26003. [DOI] [PubMed] [Google Scholar]
  • 30.Rodríguez-García A., Samsó P., Fontova P., et al. TGF-β1 targets Smad, p38 MAPK, and PI3K/Akt signaling pathways to induce PFKFB3 gene expression and glycolysis in glioblastoma cells. The FEBS Journal. 2017;284(20):3437–3454. doi: 10.1111/febs.14201. [DOI] [PubMed] [Google Scholar]
  • 31.Li X., Wu C., Chen N., et al. PI3K/Akt/mTOR signaling pathway and targeted therapy for glioblastoma. Oncotarget. 2016;7(22):33440–33450. doi: 10.18632/oncotarget.7961. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 32.Majewska E., Szeliga M. AKT/GSK3β signaling in glioblastoma. Neurochemical Research. 2017;42(3):918–924. doi: 10.1007/s11064-016-2044-4. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 33.Venkatesan S., Lamfers M. L. M., Dirven C. M. F., Leenstra S. Genetic biomarkers of drug response for small-molecule therapeutics targeting the RTK/Ras/PI3K, p53 or Rb pathway in glioblastoma. CNS oncology. 2016;5(2):77–90. doi: 10.2217/cns-2015-0005. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 34.Fane M., Harris L., Smith A. G., Piper M. Nuclear factor one transcription factors as epigenetic regulators in cancer. International Journal of Cancer. 2017;140(12) i:2634–2641. doi: 10.1002/ijc.30603. [DOI] [PubMed] [Google Scholar]
  • 35.Nilsson J., Helou K., Kovács A., et al. Nuclear Janus-activated kinase 2/nuclear factor 1-C2 suppresses tumorigenesis and epithelial-to-mesenchymal transition by repressing Forkhead box F1. Cancer Research. 2010;70(5):2020–2029. doi: 10.1158/0008-5472.CAN-09-1677. [DOI] [PubMed] [Google Scholar]
  • 36.Martínez-Arribas F., Agudo D., Pollán M., et al. Positive correlation between the expression of X-chromosomeRBM genes (RBMX, RBM3, RBM10) and the proapoptoticBax gene in human breast cancer. Journal of Cellular Biochemistry. 2006;97(6):1275–1282. doi: 10.1002/jcb.20725. [DOI] [PubMed] [Google Scholar]
  • 37.Shin K. H., Kim R. H., Kim R. H., Kang M. K., Park N. H. hnRNP G elicits tumor-suppressive activity in part by upregulating the expression of Txnip. Biochemical and Biophysical Research Communications. 2008;372(4):880–885. doi: 10.1016/j.bbrc.2008.05.175. [DOI] [PMC free article] [PubMed] [Google Scholar]

Associated Data

This section collects any data citations, data availability statements, or supplementary materials included in this article.

Data Availability Statement

The genomic expression data and clinicopathological data of 163 GBM tissues, 518 LGG tissues, and 207 normal brain tissues were downloaded from The Cancer Genome Atlas (TCGA, https://tcga-data.nci.nih.gov/TCGA). The putative EEF1D-interacting proteins were subjected to functional annotation analysis using FunRich analysis tool (Pathan et al. 2015).

Articles from BioMed Research International are provided here courtesy of Wiley

RESOURCES