Abstract

Background

   To investigate the expression and clinical significance of EFNA1 in
   broad-spectrum tumors, and to evaluate its relationship with prognosis
   and biological functions of esophageal carcinoma (ESCA).

Methods

   EFNA1 expression in various cancers was analyzed according to the data
   in the TCGA database. The clinical data were integrated, to analyze the
   relationship with ESCA clinical parameters and prognosis, and EFNA1
   expression in ESCA tissue samples was detected by immunohistochemistry
   (IHC). Based on bioinformatics, the functional background of EFNA1
   overexpression was analyzed. EFNA1 knockout cell model was established
   by EFNA1-shRNA transfecting ESCA cells, and the effect of knocking down
   EFNA1 on the proliferation of ESCA cells was detected by MTT.

Results

   Among 7563 samples from TCGA, the EFNA1 gene highly expressed in 15
   samples with common cancers and endangered the prognosis of patients
   with tumors. Its overexpression in ESCA and its influence on the
   prognosis were most significant. EFNA1 expression in 80 samples with
   ESCA and their paired samples was tested by IHC to verify its high
   expression (paired t test, P < 0.001) in ESCA tissues. It was found
   that EFNA1 expression was related to clinical factors (TNM staging, P =
   0.031; lymph node metastasis, P = 0.043; infiltration, P = 0.016).
   Meanwhile, EFNA1 was found to be an independent risk factor based on
   the COX multi-factor analysis. And to further explore the importance of
   EFNA1 in tumors, EC-9706 and ECA109 cells were screened from 8
   ESCA-related cell lines to build EFNA1 knockdown cell models. The
   results showed that EFNA1 knockdown significantly inhibited the
   proliferation of tumor cells (P < 0.05). In terms of molecular
   mechanism, EFNA1 related genes were significantly enriched in the
   proliferative pathway according to the pathway enrichment analysis. It
   was found that knocking down EFNA1 did inhibit cell proliferation based
   on cell experiments.

Conclusions

   EFNA1 overexpression in ESCA tissue is related to the prognosis of
   patients. Knocking down EFNA1 can significantly inhibit the
   proliferation of ESCA cells.

Supplementary Information

   The online version contains supplementary material available at
   10.1186/s12957-021-02362-8.

   Keywords: EFNA1; Esophageal carcinoma, Prognosis; Cell proliferation

Background

   Esophageal carcinoma (ESCA) is the eighth most common cancer and the
   sixth most common cause of cancer death in the world [[39]1]. As one of
   the common malignant tumors, the number of new and dead cases of ESCA
   ranked 7th and 6th among the tumors according to the Global Cancer
   Society Report 2018 [[40]2]. Currently, ESCA has high incidence in
   China, with higher mortality and morbidity than the global average. In
   China, the occurrence of ESCA is geographically clustered, which may be
   related to living conditions, dietary habits, and genetic
   susceptibility [[41]3]. The early symptoms of ESCA are not typical.
   Progressive dysphagia is the main complaint of most patients with ESCA,
   which is often the advanced stage of the disease [[42]4]. At present,
   surgery is the first choice for ESCA, but the tumor recurrence rate is
   high after surgery, which is easy to be distant metastasis, with poor
   long-term effect. It will also cause skeletal muscle loss and affect
   patients’ quality of life [[43]5]. Therefore, it is of great
   significance to find biomarkers for early ESCA screening and to predict
   the targets for the prognosis of ESCA.

   Eph (erythropoietin-producing hepatoma) receptor is the largest
   receptor tyrosine kinase (RTK), which can be divided into two
   subcategories according to sequence homology, including EphA1-10 and
   EphB1-6 [[44]6]. EFNs (ephrins) is a ligand for Eph receptor which can
   be divided into two subcategories according to its connection with the
   membrane, among which, EFNAs (EFNA1-5) is fixed to the membrane by
   glycosyl-phosphatidyl inositol (GPI), while EFNBs (EFNB1-3) is
   immobilized through the transmembrane protein domain [[45]7]. EFNA1 has
   about 30–40% similarity to other EFNs, which can bind to multiple EPHA
   receptors (EPHA1-5) [[46]8]. Among which, EphA2 is the most common
   receptor of EFNA1. The binding of ligand EFNA1 to receptor EphA2 can
   promote phosphorylation, which in turn regulates cell growth,
   differentiation, apoptosis, and angiogenesis, so as to be involved in
   tumorigenesis and metastasis [[47]9, [48]10]. Literature have
   documented that EFNA1 extensively involved in tumorigenesis by
   influencing tumor angiogenesis [[49]11, [50]12], malignant cell events
   [[51]13, [52]14], and invasiveness [[53]15]. Its expression is
   up-regulated in many cancers (e.g., gastric cancer [[54]16], colorectal
   cancer [[55]17], renal cancer [[56]18]), which is closely related to
   the prognosis of many cancers [[57]19, [58]20]. The study by De
   Robertis et al. has also found that EFNA1 may become a prognostic
   marker for colorectal cancer [[59]21]. Current studies have found EFNA1
   to be associated with the prognosis and progression of many tumors,
   including digestive system tumors. However, EFNA1 expression in ESCA
   and its relationship with the prognosis of patients, as well as its
   role in tumor progression, remain unclear and need further study.

   Therefore, this study first systematically analyzed EFNA1 in a variety
   of tumors and found that its high expression in ESCA is the most
   significant and is related to the prognosis in ESCA. We further
   explored the relationship between EFNA1 and the proliferation of ESCA
   cells at the cell level, providing basic theoretical basis for studying
   the pathogenesis of ESCA and prognosis evaluation of patients.

Materials and methods

Data mining

   The mRNA expression spectrum and clinical data of patients with common
   tumors and controls were downloaded from the Cancer Genome Map TCGA
   ([60]https://tcga-data.nci.nih.gov/tcga/) Database. Data were
   preprocessed by sorting, ID converting, filtering, merging, correcting
   the data from different expression spectrum and extracting clinical
   data. EFNA1 expression in each tumor was analyzed with the “meta”
   software package of R software (version 3.6.3), and the influence of
   EFNA1 expression on the prognosis of each tumor was analyzed with the
   “survival” software package of R software. Through univariate COX
   analysis, the clinical data and EFNA1 expression were analyzed, as well
   as the scanned parameters with P < 0.02. In order to predict the
   potential functions of EFNA1, the differentially expressed genes (DEGs)
   of patients with ESCA were identifies in the TCGA data with the edgeR
   package in the R software that were divided into high expression group
   and low expression group. |log2FC| > 1 and calibration P < 0.05 were
   taken as cutoff values for DEGs screening. After that, DEGs were
   analyzed with GO terms to predict their functions. The pathway with P <
   0.05 was considered statistically significant. STRING revealed that the
   interaction between these DEGs was visualized by the protein
   interaction (PPI) network.

Clinical samples

   The pathological specimens surgically removed from patients in the
   Department of Cardiothoracic Surgery, the Third Affiliated Hospital of
   Qiqihar Medical University, from December 2014 to December 2020, were
   selected as specimens for the remaining paraffin sections after
   pathological examination. Inclusion criteria are as follows: (1)
   patients undergoing surgical resection in the Thoracic Surgery
   Department of our hospital, (2) patients with pathology diagnosed as
   ESCA, and (3) patients with primary tumor foci. Exclusion criteria are
   follows: (1) patients who have received preoperative radiotherapy and
   chemotherapy, (2) patients received second operation, and (3) patients
   with severe cardiopulmonary and other basic diseases. The adjacent
   tissues were taken 2–3 cm away from the tumor and histopathologically
   confirmed to be non-cancerous tissues. Each specimen was stored in
   liquid nitrogen 15 min in vitro for subsequent experiments. This study
   has been approved by the Ethics Committee in our hospital.

Immunohistochemical (IHC) and pathological score

   Paraffin sections were baked at 60 °C for 2 h, dewaxed with xylene
   (Shanghai Sangon, China), as well as gradient ethanol dehydration, and
   were washed by PBS, which were then repaired with high pressure antigen
   for 10 min, and washed PBS again. The sections were soaked in 3%
   H[2]O[2] for 10 min to block exogenous peroxidase activity, closed with
   goat serum for 10 min (at room temperature), and then were incubated
   with added rabbit anti-human EFNA1 antibody (ab238505, Abcam, USA,
   1:100) at 4 °C overnight. The above sections were incubated with sheep
   anti-rabbit II (6926-100, Emmett Technology, China, 1:1000) at room
   temperature for 20 min and colored with added DAB (Zhongshan Jinqiao,
   Beijing) for 3 min. Hematoxylin (Shanghai Sangon, China) was added for
   re-dying for 2 min, with gradient ethanol for dehydration and resinene
   for sealing, which was placed under the microscope (Olympus, Japan) for
   observation.

   The immunopathology score was performed by 2 senior pathology
   physicians in our hospital, and the total result was given according to
   the total score of the product of dyeing area and intensity. Dyeing
   area: < 10% (0 point), 10–49% (1 point), 50–75% (2 points), > 75% (3
   points); Dyeing intensity: uncolored (0 point), pale yellow (1 point),
   brown (2 points), dark brown (3 points), the total score ≥ 4 represents
   high expression, and the total score < 4 represents low expression.

Cell culture

   Human esophageal carcinoma cell lines (EC-9706, ECA109, KYSE140,
   KYSE510, TE-10, TE-1, KYSE70) and human normal esophageal epithelial
   cell line HEEC were purchased from the Cell Bank of the Chinese Academy
   of Sciences. The cell DMEM (Corning, USA) was cultured with culture
   medium, with 10% fetal bovine serum (Thermo, USA) and 1% penicillin
   (Corning, USA). Conditions of culture: The cells were cultured in a
   constant temperature incubator at 37 °C and 5% CO[2].

Real-time fluorescence qRT-PCR experiment

   RNA was extracted with Trizol method (15596026, Invitrogen, USA), which
   was then retranscripted as cDNA with TaKaRa Mini BEST FFPE DNA
   Extraction kit (RR047A, TaKaRa, Japan). Sampling was performed with
   SYBR Premix EX Taq kit (RR420A, Takara), which was amplified with ABI
   Step One Plus TM reaction apparatus (USA). Taking GAPDH as the internal
   reference gene, reaction system: SYBR Mix 9 μL, forward primer 0.5 μL,
   reverse primer 0.5 μL, cDNA 2 μL, RNase Free dH2O 8 μL, reaction
   conditions: at 95 °C for 10 min, at 95 °C for 15 s, at 60 °C for 1 min,
   for 40 cycles. The 20 μL reaction system was taken for RT-PCR. The
   target gene (EFNA1) and the internal reference gene (GAPDH) were
   amplified under the same reaction conditions, the relative expression
   of target gene was analyzed with 2^−ΔΔCt (Table [61]1).

Table 1.

   Primer sequence list
   Primer name           Primer sequence
   EFNA1       5′-CCGCTCATCGTGCAACCTG -3′ (Forward)
               5′-ATAAGAAGGCATCAGATCG-3′ (Reverse)
   GAPDH       5′-TCCTTCAGCTTCCACGAG-3′ (Forward)
               5′-TCCTTCAGCTTCCACGAG-3′ (Reverse)
   [62]Open in a new tab

Western blot

   The total cell protein was extracted, and then was detected with BCA
   method (Beyotime, China) for protein concentrations. After preparing
   the glue, the protein was isolated with SDS-PAGE electrophoresis. With
   transfer electrophoresis device, the protein was transferred to PVDF
   membrane (Millipore, USA) by wet transfer method at 4 °C, under
   constant current of 300 mA for 90 min, and sealed with TBST solution
   containing 5%BSA at room temperature for 1 h. Rabbit anti-human EFNA1
   antibody ([63]AB124911, abcam, 1:1000), rabbit anti-human CDK2 antibody
   ([64]AB182858, abcam, 1:2000), rabbit anti-human cyclInd antibody
   (AB32503, abcam, 1:1000), and rabbit anti-human cyclIne antibody
   (AB13847, abcam, 1:500) were added for incubation at 4 °C overnight,
   which were reacted with corresponding secondary antibodies (sheep
   anti-rabbit IgG, SantaCruz, SC-2004, USA, 1:2000). The bands of
   antigen-antibody binding region were detected with chemiluminescence
   method and analyzed by ImageJ software.

Cellular transfection

   EFNA1-shRNA1 (5′CCGCGTCTTCACTGCAACG3′) and EFNA1-shRNA2
   (5′CTAGCAGAGATGACAATG3′) were purchased from Genechem Company
   (Shanghai, China). Cells were inoculated on the 6-well plates (Corning,
   USA) and cultured to a fusion of 50–70%. According to the instructions
   of Lipofectamine® 3000 Transfection kit (Invitrogen, USA), 10 μL
   transfection reagent was diluted with 250 μL serum-free medium, added
   into each hole of culture plates, and incubated for 4 h for subsequent
   experiments. The transfected EFNA1-shRNA was grouped into the
   EFNA1-shRNA group, and the transfected blank plasmid was grouped into
   the negative control (NC) group.

MTT detection

   After transfecting for 36 h, the cells were inoculated in the 96-well
   plates at 5 × 10^3 cells/hole. After inoculation for 1, 2, 3, 4, and 5
   days, 20 μL MTT solution was added to each hole and incubated for 4 h,
   the OD value was measured at 490 nm wavelength, and the cell growth
   curve was drawn.

Statistical analysis

   The experiment was performed with SPSS 24.0 (SPSS, Chicago, USA)
   software for 3 times. Measurement data materials were processed with
   paired sample t test and ANOVA. Counting data were compared with x^2
   test. α = 0.05 was taken as the test standard, and P < 0.05 was defined
   as that the difference was statistically significant.

Results

EFNA1 expression in tumor tissues and its clinical significance

   To investigate EFNA1 gene expression in tumors, the research group
   systematically analyzed 15 common tumors in the TCGA database (control
   samples > 10). In a comparison of 6872 tumors and 691 control tissues,
   EFNA1 gene was found to overexpress in most tumor tissues, especially
   in ESCA (Fig. [65]1A). After further integrating the EFNA1 gene
   expression and clinical data of 6872 patients, it was also found that
   the prognosis of patients with tumors was aggravated by EFNA1 gene
   overexpression, especially in patients with ESCA after screening (Fig.
   [66]1B).

Fig. 1.

   [67]Fig. 1
   [68]Open in a new tab

   EFNA1 expression in tumor tissue and its clinical significance. A
   Forest map of EFNA1 in 15 common cancers in TCGA. B The survival
   analysis of EFNA1 prognostic impact on multiple tumor patients, which
   was the most significant in ESCA

EFNA1 expression in ESCA clinical specimens

   In order to verify EFNA1 expression in ESCA tissues, we collected 80
   pairs of ESCA tissues and adjacent control tissues from ESCA patients
   aged 47-79, including 41 males and 39 females. The intensity of EFNA1
   expression in the samples was detected with IHC test, showing that
   EFNA1 expression in cancer tissues was significantly higher than that
   in adjacent tissues (paired t test, P < 0.001) (Fig. [69]2A, B), which
   was consistent with ESCA in TCGA (182 tumors and 286 normal tissues),
   and mRNA levels of EFNA1 were significantly higher in cancer tissues
   than those in normal tissues (P < 0.05) (Fig. [70]2C).

Fig. 2.

   [71]Fig. 2
   [72]Open in a new tab

   EFNA1 expression in ESCA clinical specimens. A, B IHC detection of
   EFNA1 expression in ESCA clinical samples. C EFNA1 expression in ESCA
   and 35 normal tissues, *P < 0.05, **P < 0.01, and ***P < 0.001

   Clinical data from patients with ESCA were further collected, to
   analyze the relationship between EFNA1 expression and ESCA clinical
   parameters, which showed that EFNA1 expression was associated with TNM
   staging (P = 0.021), lymph node metastasis (P = 0.043), and invasion
   depth (P = 0.024) (Fig. [73]3A–C, supplementary table [74]1).
   Kaplan-Meier analysis of the relationship between EFNA1 expression and
   the prognosis of patients with ESCA showed that the obviously shorter
   overall survival rate was significantly associated with high EFNA1
   expression (P = 0.0021) (Fig. [75]3D). The relationship between
   survival time and ESCA clinical parameters and EFNA1 expression was
   further analyzed. In the Cox univariate analysis, age (P = 0.037), TNM
   staging (P = 0.031), degree of invasion (P = 0.016), and EFNA1 (P =
   0.011) were associated with the prognosis of patients with ESCA. The
   results of Cox multivariate analysis showed that only the degree of
   infiltration (P = 0.041) and EFNA1 expression (P = 0.022) had
   independent significance (Table [76]2). We concluded that EFNA1 protein
   expression has been confirmed to be predictive to poor survival in
   patients with ESCA, which might be a good target for esophageal
   carcinoma therapy.

Fig. 3.

   [77]Fig. 3
   [78]Open in a new tab

   EFNA1 relationship between expression and ESCA clinical parameter
   characteristics and patient survival. A–C Relationship between EFNA1
   expression and TNM stage, lymph node metastasis, and depth of invasion.
   D In the TCGA dataset, the overall survival time of patients with ESCA
   was analyzed by Kaplan-Meier method, and it was found that the high
   EFNA1 expression was related to the poor survival rate of patients with
   ESCA

Table 2.

   Analysis of Cox univariate analysis and multivariate analysis affecting
   survival time of patients with ESCA
   Parameters Cox univariate analysis Cox multivariate analysis
   HR CI 95 % P value HR CI 95 % P value
   Age 1.736 1.120–3.214 0.037 – – –
   Gender 0.798 0 0.291–1.853 0.187 – – –
   Tumor diameter 0.575 0.258–1.786 0.423 – – –
   TNM staging 2.035 1.417–3.676 0.031 – – –
   Lymph node metastasis 0.532 0.346–1.562 = 0.412 – – –
   Infiltration degree 2.211 1.404–3.782 0.016 1.828 1.142–3.147 0.041
   Degree of differentiation 0.657 0.649–1.978 0.215 – – –
   EFNA1 expression 2.335 1.301–4.926 0.011 2.135 1.236–3.648 0.022
   [79]Open in a new tab

EFNA1 expression in ESCA cells

   To verify the importance of EFNA1 to tumor cells, 7 ESCA cell lines
   (EC-9706, ECA109, KYSE140, KYSE510, TE-10, TE-1, KYSE70) and 1 human
   normal esophageal epithelial cell (HEEC) were selected. The expression
   of EFNA1 mRNA and proteins was detected with qRT-PCR and western blot
   methods at the cellular level. The result showed that the expression of
   EFNA1 mRNA and protein was significantly higher in cancer cells than
   those in normal cells (P < 0.001) (Fig. [80]4A, B). The expression was
   the most significant in EC-9706 cell line, and the lowest in ECA109
   cell line compared with that of other ESCA cell lines. EC-9706 and
   ECA109 cell lines were selected for subsequent experiments.

Fig. 4.

   [81]Fig. 4
   [82]Open in a new tab

   Effects of silencing EFNA1 on ESCA cell proliferation. A qRT-PCR test
   of EFNA1mRNA expression in cell lines. B Western blot test of EFNA1
   protein expression in cell lines. C, D After transfection with
   EFNA1-shRNA, the expression level of EFNA1 was detected by qRT-PCR; NC
   represented the negative control group. E, F After EFNA1 was knocked
   down, the proliferation of ESCA cells changed, and the significance was
   *P < 0.05, **P < 0.01, and ***P < 0.001

   The EFNA1 low-expression ESCA cell model was built with EFNA1-shRNA,
   and the transfection efficiency was detected with qRT-PCR. The result
   showed that in EC-9706 and ECA109 cells, EFNA1 expression significantly
   decreased after EFNA1-shRNA transfection, especially in EFNA1-shRNA 1
   group, compared with NC group (P < 0.05) (Fig. [83]4C, D). EFNA1-shRNA
   1 model was selected for subsequent experiments.

   The findings in the MTT detection showed that, in EC-9706 and ECA109
   cells, the cell proliferation was significantly decreased in
   EFNA1-shRNA1 group compared with NC group (P < 0.01, P < 0.05) (Fig.
   [84]4E, F).

EFNA1 molecular mechanism affecting ESCA cell proliferation

   To explore the molecular mechanism of EFNA1 affecting ESCA cell
   proliferation, the patient cohort was divided by EFNA1 median
   expression. A total of 283 differential genes were screened with
   “edgeR” of the R package as shown in the volcanic map of Fig. [85]5A,
   including 192 upregulated and 91 downgraded. Then, the PPI network
   diagram of EFNA1 related genes was constructed by String (Fig. [86]5B),
   and it was found that EFNA1 related genes have complex protein
   interaction networks. GO enrichment analysis of DAVID pair and
   EFNA1-related genes showed that the main enrichment pathways were
   GO0045926: negative growth regulation, GO0031536: positive regulation
   of mitosis, GO0008284: positive regulation of cell proliferation, etc.
   (Fig. [87]5C), which was consistent with the results obtained from the
   above cell proliferation experiments.

Fig. 5.

   [88]Fig. 5
   [89]Open in a new tab

   EFNA1 molecular mechanisms affecting ESCA cell proliferation. A TCGA
   data EFNA1 high and low expression of the two groups do differential
   expression of volcanic map. B Network diagram of protein interactions
   of EFNA1 and 283 different genes (PPI). C GO enrichment analysis
   histogram of EFNA1 and related genes

Discussion

   EFNA1 genes are also called B61, ECKLG, EFL1, EPLG1, GMAN, LERK-1,
   LERK1, and TNFAIP4, which are located on human chromosome 1 and encode
   EPH family members. Wada et al. studied and reported that EFNA1 can
   predict the recurrence risk of patients with radical resection of liver
   cancer, which may become a prognostic marker [[90]22], and some studies
   have found that it may be related to the prognosis of cervical cancer
   [[91]23]. Studies have confirmed that EFNA1 may be associated with the
   prognosis of colorectal cancer, and single nucleotide polymorphism is
   the main factor leading to genetic susceptibility to tumors. However,
   Simonian et al. studied and found that there is no significant
   correlation between the re12904 of polymorphic loci in EFNA1 genes and
   the susceptibility to colorectal cancer, which may be related to
   specific populations [[92]24].

   Through the analysis of the related data of 15 tumors in the TCGA
   database, we found that EFNA1 overexpressed in a variety of tumors,
   especially in ESCA. Further integration analysis indicates that EFNA1
   gene overexpression worsened the prognosis of patients with cancers,
   with the greatest impact on the prognosis of patients with ESCA. Our
   immunohistochemical results suggest that EFNA1 protein expression in
   tissues with ESCA is significantly higher than that in adjacent normal
   tissues, with statistically significant differences (P < 0.001). And
   EFNA1 expression is associated with lymph node metastasis (P = 0.043),
   TNM staging (P = 0.021), and degree of invasion (P = 0.024),
   respectively. Tumor invasion is associated with ESCA staging; patients
   with ESCA with lesions confined to the mucosa have a better prognosis,
   suggesting that tumors with highly expressed EFNA1 may have a higher
   malignant biological potential. Excessive proliferation of tumor cells
   can lead to lymph node metastasis; tumors of upper esophagus are also
   prone to have lymph node metastasis [[93]25]. This study found that
   EFNA1 is associated with lymph node metastasis, suggesting that high
   EFNA1 expression may affect the proliferation and metastasis of ESCA,
   and early metastasis is also one of the common causes for failure of
   anticancer therapy in clinical practice and an important factor
   affecting the prognosis of tumor patients. Thus, upregulation of EFNA1
   expression may affect the prognosis of patients with ESCA. Our study
   showed that EFNA1 protein expression (P = 0.011) was significantly
   associated with shorter survival in patients with ESCA, except for age
   (P = 0.037), TNM staging (P = 0.031), and degree of invasion (P =
   0.016) in univariate analysis. Nevertheless, when COX multivariate
   analysis was applied, only the degree of infiltration (P = 0.041) and
   EFNA1 protein expression (P = 0.022) remained significantly associated
   with poor overall survival. At present, the main preferred treatment
   for ESCA is surgery, but postoperative tumor recurrence rate is high.
   The above results show that EFNA1, as an oncogene, may affect the
   prognosis of patients with ESCA, suggesting the poor prognosis. EFNA1
   may be an effective index to evaluate the prognosis and recurrence of
   patients with ESCA.

   Early detection and progression assessment of esophageal carcinoma
   require new biomarkers. The early symptoms of ESCA are atypical. Most
   of the patients with ESCA have progressive dysphagia as the main
   complaint, which is often the late stage of the disease. EFNA1 is a
   secreted protein of vascular endothelial cells [[94]26], which highly
   expresses in ESCA, suggesting that it may be an effective marker for
   early diagnosis and screening of ESCA.

   There is research evidence that EFNA1 is regulatory molecules for many
   malignant tumors, for example, EFNA1 induces miR-302b expression in
   malignant mesothelioma (MM) cells and inhibit the growth of tumor
   spheres by inducing apoptosis [[95]14]. EFNA1 inhibits the
   proliferation of tumor cells in NSCLC by increasing the expression of
   tumor suppressor gene cdx-2 [[96]27]. The study of Zhuo et al. found
   that knocking out EFNA1 can weaken the invasiveness of gastric cancer
   cells. In vivo experiments have confirmed that knocking out EFNA1 can
   weaken the distant metastasis ability of gastric cancer and provide a
   target for targeted therapy of gastric cancer [[97]28]. Yamamoto et al.
   studied and found that EFNA1 may be an effective index to evaluate the
   prognosis of colorectal cancer, and their cell experiments have also
   confirmed that knocking down EFNA1 can inhibit tumor proliferation,
   migration and invasion [[98]29]. The study by Kandouz et al. also
   confirmed that the EFN family may reduce the adhesion between cells and
   lead to metastasis of tumor cells [[99]30]. In this study, 8
   ESCA-related cell lines were selected. And EFNA1 expression was
   detected with qRT-PCR and WB at the ESCA cell level. The results showed
   that the expression of EFNA1 mRNA and proteins was significantly higher
   in cancer cells than that of normal cells. EFNA1 can highly express in
   ESCA cells and may play the role of oncogenes. EC-9706 cells with the
   highest EFNA1 expression and ECA109 cells with low EFNA1 expression
   were transfected with EFNA1-shRNA1 and EFNA1-shRNA2 to construct a cell
   model with low EFNA1 expression. It was found that EFNA1-shRNA1 group
   had a particularly significant decrease in EFNA1 expression, so
   EFNA1-shRNA1 was selected for subsequent experiments. Proliferation
   experiments were performed in EC-9706 and ECA109 cells transfected with
   EFNA1-shRNA1, and the results showed that knocking down EFNA1 can
   inhibit the proliferation of ESCA cells.

Conclusions

   To sum up, this study found that EFNA1 expression in ESCA tissues is
   significantly high, which is related to the prognosis of ESCA. It may
   be an independent risk factor affecting its prognosis, which provides
   an important basis for clinical evaluation of the prognosis of patients
   with ESCA. Knocking down EFNA1 can affect the biological process of
   ESCA cell proliferation at the cell level and is expected to be a new
   target for ESCA therapy. However, there are limitations in this study.
   There is no large sample research and no animal experiments. These
   problems provide directions for future research.

Supplementary Information

   [100]Additional file 1. Nomogram.^ (23.7KB, pdf)
   [101]12957_2021_2362_MOESM2_ESM.docx^ (32.9KB, docx)

   Additional file 2. EFNA1 Relationship between expression and ESCA
   characteristics of clinical parameters.

Acknowledgements