Eukaryotic translation initiation factor 3B is overexpressed and correlates with deteriorated tumor features and unfavorable survival profiles in cervical cancer patients

Abstract

OBJECTIVE:

This study aimed to detect the expression of eukaryotic translation initiation factor 3B (EIF3B) and investigate its correlation with tumor features and survival in cervical cancer patients.

METHODS:

This study retrospectively reviewed 187 cervical cancer (squamous cell carcinoma) patients underwent tumor resection. Immunohistochemistry was performed to determine the expression of EIF3B in tissue samples. Besides, disease free survival (DFS) and overall survival (OS) were calculated. The median follow-up duration was 69 months, and the last follow-up date was 2017/12/31.

RESULTS:

EIF3B expression was higher in tumor tissue compared to paired adjacent tissue (45.5% vs. 32.1%, $P=$ 0.015). Besides, EIF3B high expression was associated with higher Federation of Gynecology and Obstetrics (FIGO) Stage ( $P=$ 0.001) and presence of lymph node metastasis ( $P=$ 0.002). As to survival profiles, Kaplan-Meier curves disclosed that DFS ( $P<$ 0.001) and OS ( $P<$ 0.001) were both shorter in EIF3B high expression group compared to EIF3B low expression group. Multivariate Cox’s regression analysis disclosed that EIF3B high expression, pathological grade III (vs I/II) and FIGO Stage III/IV (vs I/II) were independent predictive factors for unfavorable DFS as well as OS in cervical cancer patients (all P value $<$ 0.05).

CONCLUSION:

EIF3B is overexpressed, and its high expression correlates with higher FIGO Stage, lymph node metastasis and unfavorable survival profiles in cervical cancer patients.

Keywords

Eukaryotic translation initiation factor 3B (EIF3B)cervical cancer survival prognosis

1. Introduction

Cervical cancer, one of the leading causes related to cancer death in women, results in 530,000 new cancer cases and 270,000 cancer-related deaths worldwide according to the 2016 global cancer statistics report, among which around 85% of these deaths happen in developing countries, and the 3-year as well as 5-year survival rates are less than 50% [1, 2, 3]. Currently, great advances have been made in diverse treatment methods for cervical cancer, including surgery, radiotherapy and chemotherapy, whereas the prognosis in advanced stage of cervical cancer is still poor [4, 5, 6]. Considering that the application of biomarkers plays a role in predicting treatment outcomes of cancer diseases, thus exploration of novel and convincing biomarkers would contribute to performing individual treatments in cervical cancer.

Eukaryotic translation initiation factors (EIFs), the indispensable regulators in the formation of protein, contribute to assembling 80S ribosomes onto mRNA with the initiator methionyl-tRNA to initiate the protein synthesis, and eukaryotic translation initiation factor 3 (EIF3) is the largest type of EIF complexes with a total molecular weight of 700 kDa and 13 subunits [7, 8]. Eukaryotic translation initiation factor 3B (EIF3B) is considered to be an important scaffolding subunit among the members of EIF3, which could interact with eukaryotic translation initiation factor 4G to result in the formation of a 48S pre-initiation complex that is able to recognize AUG start codon [9, 10, 11, 12, 13]. Accumulating evidences have revealed that EIF3B is upregulated in several cancers such as colon cancer, bladder cancer, esophageal squamous cell carcinoma and glioblastoma [12, 14, 15, 16]. Furthermore, the oncogenic effects of EIF3B have been verified in some cancer cells, such as its inhibition of caspase-3/PARP pathway in osteosarcoma cells and activation of $\beta$ -catenin signaling pathway in esophageal squamous cell carcinoma cells [14, 17]. Based on these previous studies, we speculated that aberrant expression of EIF3B might have influence on disease progression and prognosis of cervical cancer, while related research in cervical cancer is not observed. Hence, we conducted this study to detect the expression of EIF3B and explore its correlation with tumor features and prognosis in cervical cancer patients.

2. Methods

2.1 Patients

This study retrospectively reviewed 187 cervical cancer patients in the Obstetrics and Gynecology Hospital of Fudan University and the Affiliated Changzhou Matenity and Child Health Care Hospital of Nanjing Medical University underwent tumor resection between 2009/1/1 and 2013/12/31. The inclusion criteria were as follows: (1) Diagnosed as primary cervical cancer which was confirmed by pathological findings; (2) Age above 18 years; (3) Underwent tumor resection; (4) Completed baseline data before surgery is accessible from the Electronic Medical Record System (EMRS) which at least included age, human papilloma virus (HPV) status, histological type, pathological grade, Federation of Gynecology and Obstetrics (FIGO) Stage and lymph node metastasis status; (5) With completed relapse and survival data including disease free survival (DFS) and overall survival (OS); (6) Paired tumor and adjacent tissue were accessible from Sample Storehouse. Patients with the following conditions were excluded: (1) Received neoadjuvant therapy before surgery; (2) History or complicated with other cancers or hematological malignancies.

2.2 Ethics statement

This study was approved by the Ethics Committee of Obstetrics and Gynecology Hospital of Fudan University and The Affiliated Changzhou Matenity and Child Health Care Hospital of Nanjing Medical University, and written informed consents were obtained from patients or their statutory guardians.

2.3 Data collection

Several important characteristics of patients were retrieved from EMRS including: age, HPA status, pathological grade, FIGO Stage and lymph node metastasis status. Besides, DFS was calculated from the date of surgery to the date of relapse or death, and OS was calculated from the date of surgery to the data of death. The median follow-up duration was 69 months, and the last follow-up date was 2017/12/31.

2.4 Immunohistochemistry (IHC)

After acquisition of formaldehyde fixed, paraffin embedded tissue sample, IHC was performed to determine the expression of EIF3B. Only malignant epithelial cells were analyzed and counted, and benign cells were not included in our assessment in the IHC assay. As to malignant epithelial cells, their assessments were performed as follows: only the tissue sections from squamous carcinoma patients were included, and squamous carcinoma cells were used to assess for EIF3B expression. The brief process was as follows: The tissue section was firstly deparaffinized and rehydrated, and antigen was retrieved using Tris-Ethylene Diamine Tetraacetic Acid (EDTA) followed by blocking endogenous peroxidase with H ${}_{2}$ O ${}_{2}$ and then immersed with 4% bovine serum albumin. Subsequently, tissue section was incubated using rabbit monoclonal antibody to EIF3B (Abcam, USA) with a dilution of 1:100 at 4 ${}^{\circ}$ C overnight, and then incubated with horseradish peroxidase (HRP)-conjugated anti-IgG (Abcam, USA) at room temperature for 30 minutes. Afterwards, the tissue section was washed and treated with diaminobenzidine (DAB), followed by counterstaining with hematoxylin for cell nucleus staining, and then sections were dehydrated and mounted. As to measurement of EIF3B expression, the positive cells of each section were observed and counted under light microscopy by two specialists without knowing any information of the patients. In each slide, 100 cells in 5 high-power fields (HPF, $\times$ 400) were counted to evaluate the intensity of positive cells. Staining intensity was scored as 0 (negative), 1 (weak), 2 (moderate), to 3 (strong), while the grading scale for labeling frequency ranged from 0 (0%), 1 (1%–25%), 2 (26%–50%), 3 (51%–75%), and 4 (76%–100%) on the basis of the percentage of positively stained cells. Finally, Multiplying the score of staining intensity by the labeling frequency score was used to divide sections into two groups: EIF3B low expression group with final score $<=$ 3; and EIF3B high expression group with final score $>$ 3.

2.5 Statistics

Statistical analysis was performed using SPSS 21.0 software (IBM, USA). Data were mainly presented as mean $\pm$ standard deviation or count (percentage). Comparison between two independent groups was detected by Chi-square test, and comparison between two paired groups was detected by McNemar test. Kaplan-Meier (K-M) curves and log-rank test were applied to compare DFS and OS, and univariate as well as multivariate Cox’s proportional hazards regression analysis (with Forward Stepwise (Conditional LR)) were performed to determine the baseline factors affecting DFS and OS. $P<$ 0.05 was considered as significant.

3. Results

3.1 Baseline characteristics

187 cervical cancer patients with a mean age of 47.1 $\pm$ 10.5 years were enrolled in our study (Table 1). There were 42 (22.5%) patients with negative HPV status and 145 (77.5%) patients with positive HPV status. As to disease stage, 46 (24.6%), 60 (32.1) and 81 (43.3%) patients were classified as pathological grade I, pathological grade II and pathological grade III respectively, and 105 (56.1%), 44 (23.5%), 34 (18.2) and 4 (2.1%) patients were categorized as FIGO Stage I, FIGO Stage II, FIGO Stage III and FIGO Stage IV respectively. In addition, numbers of patients suffered lymph node metastasis and patients without lymph node metastasis were 35 (18.7%) and 152 (81.3%) respectively.

Table 1
Characteristics of cervical cancer (squamous carcinoma) patients

Parameters	Cervical cancer patients ( $N=$ 187)
Age (years)	47.7 $\pm$ 10.5
HPV status ( $n$ /%)
Negative	42 (22.5)
Positive	145 (77.5)
Pathological grade ( $n$ /%)
I	46 (24.6)
II	60 (32.1)
III	81 (43.3)
FIGO stage ( $n$ /%)
I	105 (56.1)
II	44 (23.5)
III	34 (18.2)
IV	4 (2.1)
Lymph node metastasis ( $n$ /%)
No	152 (81.3)
Yes	35 (18.7)

Data were presented as mean $\pm$ standard deviation or count (percentage). HPV, human papilloma virus; FIGO, Federation of Gynecology and Obstetrics.

3.2 Comparison of EIF3B expression between tumor tissue and paired adjacent tissue

We performed IHC to detect the EIF3B expression in tumor tissue and paired adjacent tissue, and divided into EIF3B high expression group and EIF3B low expression group according to the score of staining intensity. Examples of EIF3B high/low expression in tumor tissue and paired adjacent tissue was presented in Fig. 1A, and we found that EIF3B was overexpressed in tumor tissue compared to paired adjacent tissue ( $P=$ 0.015) (Fig. 1B).

Figure 1.

EIF3B expression in tumor tissue and paired adjacent tissue. Presentation of examples of EIF3B low/high expression in tumor and paired adjacent tissue (A). Comparison of EIF3B expression in tumor tissue and paired adjacent tissue (B). Comparison was detected by McNemar test. $P<$ 0.05 was considered significant. EIF3B, eukaryotic translation initiation factor 3B.

3.3 Correlation of tumor EIF3B expression with tumor features

EIF3B high expression was associated with higher FIGO Stage ( $P=$ 0.001) and presence of lymph node metastasis ( $P=$ 0.002) in cervical cancer patients (Table 2). No correlation of EIF3B with other characteristics including age ( $P=$ 0.558), HPV status ( $P=$ 0.374), histological type ( $P=$ 0.088) or pathological grade ( $P=$ 0.252) was found.

Table 2
Correlation of tumor EIF3B expression with tumor features

Parameters	EIF3B low expression	EIF3B high expression	$P$ value
Age ( $n$ /%)			0.134
$<$ 45 years	52 (60.5)	34 (39.5)
$\geqslant$ 45 years	50 (49.5)	51 (50.5)
HPV status ( $n$ /%)			0.749
Negative	22 (52.4)	20 (47.6)
Positive	80 (55.2)	65 (44.8)
Pathological grade ( $n$ /%)			0.125
I/II	63 (59.4)	43 (40.6)
III	39 (48.1)	42 (51.9)
FIGO Stage ( $n$ /%)			0.001
I/II	90 (60.4)	59 (39.6)
III/IV	12 (31.6)	26 (68.4)
Lymph node metastasis ( $n$ /%)			0.002
No	91 (59.9)	61 (40.1)
Yes	11 (31.4)	24 (68.6)

Data were presented as count (percentage), comparison was detected by Chi-square test and $P<$ 0.05 was considered as significant. HPV, human papilloma virus; FIGO, Federation of Gynecology and Obstetrics.

3.4 Survival profiles

DFS was shorter in EIF3B high expression group compared to EIF3B low expression group ( $P<$ 0.001) (Fig. 2A). Meanwhile, OS was worse in EIF3B high expression group than that in EIF3B low expression group as well ( $P<$ 0.001) (Fig. 2B).

Figure 2.

Comparison of survival profiles between EIF3B high expression group and EIF3B low expression group. EIF3B high expression was associated with reduced DFS (A). EIF3B high expression was correlated with shorter OS (B). Kaplan-Meier (K-M) curves and log-rank test were applied to compare DFS and OS. $P<$ 0.05 was considered significant. EIF3B, eukaryotic translation initiation factor 3B; DFS, disease free survival; OS, overall survival; K-M curves, Kaplan-Meier curves.

3.5 Analysis of factors affecting DFS

Univariate Cox’s regression analysis disclosed that EIF3B high expression was correlated with poor DFS ( $P<$ 0.001), besides, age $\geqslant$ 45 years ( $P=$ 0.044), pathological grade III (vs I/II) ( $P<$ 0.001), FIGO Stage III/IV (vs I/II) ( $P<$ 0.001) and lymph node metastasis ( $P<$ 0.001) were also associated with worse DFS (Table 3). In the further multivariate Cox’s regression with Forward Stepwise (Conditional LR) method analysis, EIF3B high expression ( $P=$ 0.006), pathological grade III (vs I/II) ( $P=$ 0.002) and FIGO Stage III/IV (vs I/II) ( $P=$ 0.010) were verified as independent predictive factors for unfavorable DFS in cervical cancer patients.

Table 3
Cox’s analysis for baseline features affecting DFS

Parameters	Cox’s regression model
	$P$ value	HR	95% CI
			Lower	Higher
Univariate Cox’s regression
EIF3B high expression	$<$ 0.001	2.551	1.511	4.305
Age $\geqslant$ 45 years	0.044	1.713	1.015	2.890
HPV positive	0.490	0.814	0.455	1.459
Pathological grade III (vs I/II)	$<$ 0.001	3.017	1.787	5.093
FIGO stage III/IV (vs I/II)	$<$ 0.001	3.394	2.018	5.707
Lymph node metastasis	$<$ 0.001	3.531	2.089	5.969
Multivariate Cox’s regression with Forward Stepwise (Conditional LR) method
EIF3B high expression	0.006	2.132	1.239	3.666
Pathological grade III (vs I/II)	0.002	2.412	1.383	4.205
FIGO stage III/IV (vs I/II)	0.010	2.133	1.202	3.783

Univariate and multivariate Cox’s proportional hazards regression model analyses (with Forward Stepwise (Conditional LR)) was used to analyze baseline features affecting DFS. P value $<$ 0.05 was considered significant. DFS, disease free survival; HPV, human papilloma virus; FIGO, Federation of Gynecology and Obstetrics.

3.6 Analysis of factors affecting OS

As to factors affecting OS, univariate Cox’s regression analysis showed that EIF3B high expression ( $P<$ 0.001) was associated with worse OS, meanwhile, age $\geqslant$ 45 years ( $P=$ 0.036), pathological grade III (vs I/II) ( $P=$ 0.001), FIGO Stage III/IV (vs I/II) ( $P<$ 0.001) and lymph node metastasis ( $P<$ 0.001) were also correlated with poor OS in cervical cancer patients (Table 4). In order to assess the independent predictive factors affecting OS, multivariate Cox’s regression with Forward Stepwise (Conditional LR) method was performed, which displayed that EIF3B high expression ( $P=$ 0.009), pathological grade III (vs I/II) ( $P=$ 0.030) and FIGO Stage III/IV (vs I/II) ( $P=$ 0.001) were independent factors predicting shorter OS in cervical cancer patients.

Table 4
Cox’s analysis for baseline features affecting OS

Parameters	Cox’s regression model
	$P$ value	HR	95% CI
			Lower	Higher
Univariate Cox’s regression
EIF3B high expression	$<$ 0.001	2.774	1.569	4.903
Age $\geqslant$ 45 years	0.036	1.841	1.042	3.251
HPV positive	0.179	0.664	0.365	1.207
Pathological grade III (vs I/II)	0.001	2.685	1.539	4.684
FIGO stage III/IV (vs I/II)	$<$ 0.001	4.239	2.457	7.313
Lymph node metastasis	$<$ 0.001	4.361	2.519	7.552
Multivariate Cox’s regression with Forward Stepwise (Conditional LR) method
EIF3B high expression	0.009	2.198	1.221	3.954
Pathological grade III (vs I/II)	0.030	1.930	1.064	3.502
FIGO stage III/IV (vs I/II)	0.001	2.855	1.565	5.211

Univariate and multivariate Cox’s proportional hazards regression model analyses (with Forward Stepwise (Conditional LR)) was used to analyze baseline features affecting OS. P value <0.05 was considered significant. OS, overall survival; HPV, human papilloma virus; FIGO, Federation of Gynecology and Obstetrics.

4. Discussion

In our study, we found that: (1) EIF3B was overexpressed in tumor tissue compared to paired adjacent tissue, and its high expression was associated with higher FIGO Stage and lymph node metastasis; (2) EIF3B high expression was correlated with shorter DFS and OS in cervical cancer patients independently.

EIF3B, acting as a vital scaffold subunit for EIF3 complexes, plays a crucial role in cellular and viral translation initiation [12]. According to a previous study, EIF3B overexpression stimulates total protein synthesis and enhances translational functions of several RNAs such as cycin D, Myc and ornithine decarboxylase in NIH3T3 fibroblast cells [18]. For cancers, the regulatory effect of EIF3B on cancer cells have been reported in some studies [12, 14, 17]. An interesting study reveals that knockdown of EIF3B inhibits cells proliferation and enhances cells apoptosis in U87 glioma cells via G0/G1-phase arrest [12]. Also, silencing of EIF3B induces activation of caspase-3/PARP pathway, thereby suppresses cells proliferation and increases cells death in osteosarcoma cell lines thc-27-thc181541 [17]. Another study conducts in vitro and in vivo experiments, and it discloses that EIF3B promotes cells proliferation and enhances cells invasion through activating $\beta$ -catenin signaling pathway in esophageal squamous cell carcinoma cells [14]. Concerning that EIF3B presents with oncogenic effect on the pathology of these aforementioned cancers, while its influence on cervical cancer has not been reported yet, therefore, we speculated that EIF3B might also have carcinogenic effect in cervical cancer.

Regarding the expression of EIF3B in cancers, it has been revealed to be overexpressed in several cancers such as colon cancer, bladder cancer, prostate cancer and glioblastoma [12, 14, 15, 16]. Moreover, several previous studies have been performed to investigate the correlation of EIF3B with tumor features. For instance, a recent study displays that EIF3B is overexpressed and correlates with increased tumor depth, lymph node metastasis and later histological grade in esophageal squamous cell carcinoma patients [14]. Another study shows that higher EIF3B expression is associated with elevated T stage and Furhman nulcear grade in clear cell renal cell carcinoma thc-27-thc181541 [11]. These studies indicate that EIF3B overexpression is associated with advanced disease stages in several cancers. In line with these previous studies, we found that EIF3B was overexpressed in tumor tissue compared to paired adjacent tissue, and its high expression was associated with higher FIGO Stage and lymph node metastasis in cervical cancer patients. The possible reasons might be that: (1) EIF3B was able to promote cells proliferation as well as cells invasion via stimulating some pathways including $\beta$ -catenin signaling pathway, and it further enhanced the migration to nearby tissues and deeper stromal invasion, thereby resulting in higher FIGO Stage [14]; (2) EIF3B promoted the ability of cells metastasis through facilitating some crucial steps such as the epithelial-to-mesenchymal transition, thus it enhanced lymph node metastasis in cervical cancer thc-27-thc181541 [11].

Some previous data have illuminated the prognostic value of EIF3B in cancers [11, 17]. For example, a study reveals that higher EIF3B expression predicts reduced OS in clear cell renal cell carcinoma patients, and another study displays that EIF3B high expression is correlated with poor DFS in bladder cancer patients [11, 17]. Whereas, few evidences disclose the predictive value of EIF3B in cervical cancer patients. In our study, we found that EIF3B high expression was an independent predictive factor for poor survival profiles in cervical cancer patients, and the reasons might be as follows: (1) EIF3B had the potential to promote cancer cells proliferation, enhance cells invasion and inhibit cells apoptosis via some signaling pathways such as caspase-3/PARP pathway and $\beta$ -catenin signaling pathway, therefore it might enhance tumor growth and accelerate tumor progression, suggesting that EIF3B could result in worse disease stages and shorter DFS as well as OS in cervical cancer patients [14, 17]; (2) EIF3B high expression might impair the inhibition in DNA replication of cervical cancer cells, thus it resulted in increased cells growth and further led to poor survival profiles [12]; (3) EIF3B high expression might induce the drug resistance, thereby led to worse treatment outcomes including shorter survivals.

There were some limitations existed in our study: (1) the sample size was relatively small in this study, which just enrolled 187 patients, thus the statistic power might be poor; (2) this was a retrospective study that used IHC method to determine EIF3B expression subject to the sample types, thus further studies with more methods (such as Western Blot assay for fresh tissue) to verify the results are needed; (3) in order to eliminate interferences, patients with primary cervical cancer were enrolled in our study, thus the prognostic value of EIF3B in secondary cervical cancer was still unclear.

In conclusion, EIF3B is overexpressed, and its high expression correlates with higher FIGO Stage, lymph node metastasis and unfavorable survival profiles in cervical cancer patients.

Footnotes

Acknowledgments

This study was supported by National Science Foundation of China (No. 81601235) and Technology Project of Changzhou Municipal Commission of Health and Family Planning for Young Scholars (No. QN201825).

Conflict of interest

The authors have no financial conflicts of interest.

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Eukaryotic translation initiation factor 3B is overexpressed and correlates with deteriorated tumor features and unfavorable survival profiles in cervical cancer patients

Abstract

OBJECTIVE:

METHODS:

RESULTS:

CONCLUSION:

Keywords

1. Introduction

2. Methods

2.1 Patients

2.2 Ethics statement

2.3 Data collection

2.4 Immunohistochemistry (IHC)

2.5 Statistics

3. Results

3.1 Baseline characteristics

Table 1 Characteristics of cervical cancer (squamous carcinoma) patients

Table 2 Correlation of tumor EIF3B expression with tumor features

Table 3 Cox’s analysis for baseline features affecting DFS

Table 4 Cox’s analysis for baseline features affecting OS

Footnotes

Acknowledgments

Conflict of interest

References

Table 1
Characteristics of cervical cancer (squamous carcinoma) patients

Table 2
Correlation of tumor EIF3B expression with tumor features

Table 3
Cox’s analysis for baseline features affecting DFS

Table 4
Cox’s analysis for baseline features affecting OS