ELF3 emerges as a novel prognostic indicator implicated in gastric cancer progression and correlated with unfavorable clinical outcomes

Abstract

BACKGROUND

E74-like ETS transcription factor 3 (ELF3), a member of the ETS transcription factor family, is broadly expressed and orchestrates critical cellular processes, including proliferation, differentiation, and apoptosis. While it has been implicated in various immune-related diseases and malignancies, its specific role and clinical significance in stomach adenocarcinoma (STAD) remain poorly understood.

AIM

To elucidate the expression pattern, prognostic value, and potential immunological mechanisms of ELF3 in STAD.

METHODS

We comprehensively analyzed ELF3 expression and its prognostic implications in STAD using multiple public databases, including UALCAN, TIMER, HPA, GEPIA, and Kaplan-Meier Plotter. The correlations between ELF3 expression and immune infiltration features were investigated via the TIMER and TISIDB platforms. Furthermore, the bioinformatics findings were rigorously validated in an independent clinical cohort comprising 100 STAD patients.

RESULTS

ELF3 expression was found to be significantly upregulated in STAD tissues compared to normal controls. Clinical analysis identified ELF3 as an independent prognostic factor, with high expression levels significantly associated with poor overall survival. Moreover, elevated ELF3 expression was positively correlated with increased infiltration of immune cells and chemokines. These associations suggest that ELF3 may facilitate tumor progression by shaping an immunosuppressive tumor microenvironment.

CONCLUSION

Our findings highlight ELF3 as a promising prognostic biomarker and a potential therapeutic target for STAD. The study provides novel insights into the role of ELF3 in modulating the immune microenvironment to promote gastric cancer progression.

Key Words: E74-like ETS transcription factor 3; Stomach adenocarcinoma; Tumor; Prognosis; Immune infiltration; Biomarker

Core Tip: E74-like ETS transcription factor 3 (ELF3) is an epithelial transcription factor whose role in stomach adenocarcinoma (STAD) has been unclear. Integrating multi-database analyses with a 100-patient clinical cohort, we show that ELF3 is upregulated in STAD, independently predicts survival, and associates with immune-cell and chemokine infiltration. High ELF3 expression co-occurs with an immunosuppressive tumor microenvironment, suggesting a mechanism for disease progression. These findings position ELF3 as a practical prognostic biomarker and a rational therapeutic target to modulate antitumor immunity in STAD.

INTRODUCTION

Gastric cancer (GC) is the fifth leading cancer worldwide and the fourth leading cause of cancer-related deaths[1]. GC includes a variety of pathology types, including adenocarcinoma, squamous cell carcinoma, adenosquamous carcinoma, carcinoid carcinoma, and small cell carcinoma. Stomach adenocarcinoma (STAD) is the most common, accounting for approximately 95% of all cases[2,3]. Although neoadjuvant therapy strategies and targeted therapies have advanced in recent years, the prognosis of patients with STAD remains poor due to the complexity of cancer-related genes and their signaling pathways. The study report pointed out that the five-year survival rates of different subtypes of adenocarcinoma in patients with STAD were: Adenocarcinoma (32.9%), tubular adenocarcinoma (25.4%), adenocarcinoma of dysdifferentia (19.9%) and mucinous adenocarcinoma (19.3%)[4,5]. Future studies must identify new biomarkers and therapeutic targets to improve poor survival rates in STAD.

E74-like ETS transcription factor 3 (ELF3) is an integral member of the ESE transcription factor family, regulating various pathophysiological processes in cancer and immune system diseases[6,7]. ESE transcription factors play a key role in maintaining cell homeostasis and differentiation. Genetic alterations and dysregulation of expression of these factors have been found to be associated with cancer metastasis, highlighting their potential involvement in tumor progression[8]. ELF3 may interact with cytosolic endogenous β streptolin, synergistically regulating cell-to-cell adhesion and transcription processes. This interaction plays a key role in controlling cancer cell proliferation and may promote tumor progression[6,7,9,10]. The latest studies have shown that ELF3 is highly expressed in colorectal cancer, promoting tumor cell proliferation and invasion by enhancing β-strep protein signaling. This suggests that ELF3 plays a key role in driving the aggressive behavior of colorectal cancer cells[11]. In prostate cancer, ELF3 drives tumor progression through positive feedback loops[12]. In hepatocellular carcinoma, ELF3 overexpression is significantly associated with poor prognosis and promotes epithelial-mesenchymal metastasis (EMT) processes and tumor progression[10]. Another study highlighted that genetic mutations such as ELF3 and specific microenvironmental changes were associated with peritoneal metastasis in GC patients[13], indicating a strong relationship between ELF3 and poor prognosis in patients with STAD.

The tumor microenvironment (TME) contains a large number of tumor-infiltrating immune cells (TIICs) that are essential for tumor progression and influence patient survival outcomes[14]. Several studies have shown that the type and abundance of TIIC are closely related to the prognosis of GC patients. For example, CD4+ T cells play a key role in activating CD8+ T cells and other immune cells, helping to recognize and eliminate cancer cells and promote anti-tumor immunity. High infiltration of CD4+ T cells is often associated with a better prognosis. Conversely, regulatory T cells (Tregs) can inhibit the anti-tumor immune response within the TME, thereby promoting tumor growth. Natural killer (NK) cells directly kill tumor cells and are often associated with a more favorable prognosis. Tumor-associated macrophages (TAMs) can differentiate into different subtypes: M1 macrophages have antitumor properties, while M2 macrophages promote tumor growth, immune evasion, and angiogenesis[15-18]. Therefore, it is of great significance to study immune infiltration-related targets in STAD.

MATERIALS AND METHODS

In this study, the TIMER and UALCAN databases were used to evaluate the expression of ELF3 mRNA in STAD. We analyzed ELF3 protein levels using the HPA database and collected data from 100 STAD samples from hospitals for validation. The effect of ELF3 expression on overall survival (OS) in patients with STAD was evaluated using GEPIA and Kaplan-Meier plotter databases. In addition, we used TIMER and TISIDB databases to explore the correlation between ELF3 expression and TIICs in STAD. In addition, the relationship between ELF3 expression and TIIC gene markers was investigated using TIMER and GEPIA databases. This study provides valuable insights into the prognostic significance of ELF3 in STAD and its related role in immune infiltration, and provides support for potential new directions for targeted therapy for this malignancy.

RESULTS

Expression of ELF3 in STADs

Gene expression analysis using the TIMER database showed that ELF3 mRNA was overexpressed in multiple tumor tissues compared to its normal counterparts (Figure 1A). The expression of ELF3 in STAD was further investigated using the UALCAN database, and it was shown that ELF3 was significantly up-regulated in STAD samples (Figure 1B). The UALCAN database was also used to analyze ELF3 expression in different subgroups of STAD patients, based on ethnicity, gender, age, cancer stage, tumor grade, Helicobacter pylori infection status, and lymph node metastasis status. In addition, comparisons were made with and without mutations in TP53 expression (Figure 2). Selective nuclear expression of ELF3 has been observed in different tissues, including gastrointestinal tract, urothelial cells, squamous epithelium, and ciliated cells. Immunohistochemistry (IHC) analysis of HPA also showed that ELF3 was overexpressed in STAD tissues compared to paracancerous tissues (Figure 1C). These findings suggest that ELF3 may serve as a potential diagnostic biomarker for STAD.

Figure 1 Pan-cancer and multi-cohort analysis verifies E74-like ETS transcription factor 3 upregulation in stomach adenocarcinoma. A: E74-like ETS transcription factor 3 (ELF3) mRNA level was upregulated in various types of malignancies from the TIMER database, including stomach adenocarcinoma (STAD); B: ELF3 mRNA level was markedly increased in STAD tissues from the UALCAN database; C: ELF3 protein expression level in STAD. Immunohistochemistry images of ELF3 in STAD and normal gastric tissues in the HPA database. ^aP < 0.05, ^bP < 0.01, and ^cP < 0.001. ELF3: E74-like ETS transcription factor 3; STAD: Stomach adenocarcinoma.

Figure 2 The mRNA expression of E74-like ETS transcription factor 3 was significantly higher in stomach adenocarcinoma samples. A-H: Compared to normal samples as analyzed in relation to patients’ race, gender, age, cancer stage, tumor grade, Helicobacter pylori infection status, TP53 mutation status, and nodal metastasis status. Multiple group comparisons were performed with ANOVA followed by the Bonferroni post hoc test, detailed statistical analysis is provided in Supplementary Table 1. ELF3: E74-like ETS transcription factor 3; STAD: Stomach adenocarcinoma.

Prognostic value of ELF3 in STAD

Survival analysis using the GEPIA database showed that high ELF3 expression was associated with poor disease-free survival in patients with STAD (Figure 3A). To further evaluate this relationship, Kaplan-Meier survival curves were applied, and it was confirmed that increased ELF3 expression was consistently associated with a shorter OS in the STAD cohort (Figure 3B). The association between ELF3 expression and OS was also evaluated among different subgroups. The results showed that patients with STAD with higher ELF3 expression showed more severe OS in multiple subgroups, including stage I, stage III, stage T3, stage N2, female, intestinal type, poor differentiation, and moderate differentiation (Figure 3C-J). These findings suggest that ELF3 can be used as a reliable biomarker for predicting patients with STAD.

Figure 3 Prognostic value of E74-like ETS transcription factor 3 in stomach adenocarcinoma. A and B: High E74-like ETS transcription factor 3 expression was related to shorter disease-free survival and overall survival in stomach adenocarcinoma patients from GEPIA and Kaplan-Meier plotter databases; C-J: High E74-like ETS transcription factor 3 expression was related to worse overall survival in different subgroups, including stage I, stage III, stage T3, stage N2, female, intestinal type, poorly differentiated and moderately differentiated. ELF3: E74-like ETS transcription factor 3; HR: Hazard ratio.

Correlation between ELF3 expression and STAD sample validation

In order to verify the above preliminary conclusions and further explore the effect of ELF3 overexpression on the development of STAD, the relationship between ELF3 expression and various clinicopathological characteristics and survival data of STAD patients in this hospital was evaluated. A total of 100 histopathologically diagnosed STAD cases and their adjacent normal samples were included for comparison. The clinicopathological data of these patients are shown in Table 1. ELF3 overexpression was significantly associated with tumor-node-metastasis (TNM) stage and Ki-67 status (P = 0.008, P = 0.001). IHC analysis of the samples showed that ELF3 was higher than normal tissue expression in STAD tissues (Figure 4A). In addition, expression was validated using the GEPIA database, and the results were consistent with the above description, with ELF3 being overexpressed in STAD tissues (Figure 4B). In this study, the correlation between ELF3 expression and Ki-67 and E-cadherin expression levels was analyzed. The results showed that ELF3 was positively correlated with Ki-67 expression and negatively correlated with E-cadherin expression (Figure 4C and D). In order to further evaluate the relationship between ELF3 expression and postoperative prognosis of patients with STAD, Kaplan-Meier analysis and log-rank test were used to analyze the OS rate of 100 samples. The results showed that patients with STAD with higher ELF3 expression had a worse OS (P = 0.0164; Figure 4E), consistent with TCGA data. Univariate and multivariate Cox regression analysis was used to further determine the prognostic factors of STAD patients to verify whether ELF3 expression is an independent risk factor for STAD patients (Table 2). Univariate analysis showed that tumor size, T stage, N stage, TNM stage, ELF3 expression and vascular invasion were associated with OS in STAD patients. Variables with significant relationships (P < 0.05) were subsequently included and subsequent multivariate analyses were included. The results showed that ELF3 expression and vascular invasion were considered independent risk factors for STAD (OS: ELF3 expression-hazard ratio = 4.154, 95% confidence interval: 2.135-8.081, P < 0.001; vascular invasion heart rate = 2.313, 95% confidence interval: 1.196-4.474, P = 0.013).

Figure 4 Correlation between E74-like ETS transcription factor 3 expression and prognosis of stomach adenocarcinoma patients from the study population cohort. A: Immunohistochemistry images of E74-like ETS transcription factor 3 (ELF3) in stomach adenocarcinoma (STAD) and matched normal tissues; B: Expression was verified using the GEPIA database, and the results showed that ELF3 was overexpressed in STAD tissues; C and D: The expression of ELF3 was positively correlated with Ki-67 expression, and negatively correlated with E-cadherin expression; E: High ELF3 expression in STAD patients was related to worse survival. ^aP < 0.05. ELF3: E74-like ETS transcription factor 3; STAD: Stomach adenocarcinoma; OS: Overall survival.

Table 1 E74-like ETS transcription factor 3 and clinicopathological characteristics of gastric cancer patients (n = 100).

Variable		ELF3 expression		P value
		Low (52)	High (48)
Age (years)	< 60	18	15	0.724
	≥ 60	34	33
Gender	Male	35	29	0.478
	Female	17	19
Tumor size (cm)	< 5	31	17	0.015
	≥ 5	21	31
T stage	T1 + T2	18	4	0.090
	T3 + T4	34	42
N stage	N0 + N1	28	15	0.023
	N2 + N3	24	33
TNM stage	I + II	30	15	0.008
	III + IV	22	33
Ki-67	Low	30	20	0.001
	High	22	28
E-cadherin	Low	20	29	0.028
	High	32	19

ELF3: E74-like ETS transcription factor 3; TNM: Tumor-node-metastasis.

Table 2 Univariate and multivariate analyses of prognostic factors for overall survival of stomach adenocarcinoma patients in the study cohort.

Variables	Univariate analysis			Multivariate analysis
	HR	95%CI	P value	HR	95%CI	P value
Age (years)
< 60	Reference
≥ 60	0.901	0.526-1.544	0.704
Gender
Female	Reference
Male	1.166	0.672-2.023	0.585
Tumor size (cm)
< 5	Reference			Reference
≥ 5	2.342	1.355-4.047	0.002	1.351	0.729-2.503	0.339
T stage
T1 + T2	Reference			Reference
T3 + T4	3.427	1.366-8.594	0.009	1.117	0.402-3.100	0.832
N stage
N0 + N1	Reference			Reference
N2 + N3	2.421	1.380-4.248	0.002	0.497	0.106-2.337	0.376
TNM stage
I + II	Reference			Reference
III + IV	2.812	1.588-4.979	< 0.001	3.652	0.750-17.789	0.109
ELF3 expression
Low	Reference			Reference
High	5.148	2.793-9.488	< 0.001	4.154	2.135-8.081	< 0.001
Vascular invasion
No	Reference			Reference
Yes	2.672	1.405-5.081	0.003	2.313	1.196-4.474	0.013
Ki-67
Low	Reference
High	0.759	0.450-1.282	0.303
E-cadherin
Low	Reference
High	0.649	0.384-1.096	0.106

TNM: Tumor-node-metastasis; ELF3: E74-like ETS transcription factor 3; HR: Hazard ratio; CI: Confidence interval.

ELF3 expression in the TME

The TISCH database was used to provide detailed cell type annotations at the single-cell level to investigate the expression of ELF3 in the STAD brain sea. Figure 5A shows the expression distribution of ELF3 in different immune cell types in each dataset. In STAD_GSE134520 dataset, ELF3 is mainly expressed in glandular mucus, pit mucus, mast cells, plasma cells, malignant cells, and CD8 T cells (Figure 5B-E). In contrast, STAD_GSE167297 dataset showed that ELF3 expression was primarily confined to epithelial and plasma cells (Figure 5F-I). These findings suggest that in addition to regulating tumor cell proliferation, ELF3 may also have functional effects on immune cells and stromal cells. In addition, significant variability in ELF3 expression among different cell types may contribute to the heterogeneity of TMEs in STAD.

Figure 5 E74-like ETS transcription factor 3 expression in the tumor microenvironment of stomach adenocarcinoma at the single-cell level. A: Heatmap of E74-like ETS transcription factor 3 expression value in different cell types from two datasets in the TISCH database; B-I: The single-cell cluster maps of E74-like ETS transcription factor 3 distribution in stomach adenocarcinoma_GSE134520 and stomach adenocarcinoma_GSE167297 datasets. ELF3: E74-like ETS transcription factor 3; STAD: Stomach adenocarcinoma.

Relationship between ELF3 expression and immune infiltration

TIICs are an important component of the TME and play an important role in the progression of malignant tumors. TIICs are also important biomarkers for evaluating treatment efficacy. Investigating targets related to immune infiltration has become a key in the treatment of STAD. To explore the relationship between ELF3 expression and immune infiltration, we utilized data from the TIMER and TISIDB databases. According to the TIMER data, ELF3 was associated with B cells (r = -0.001, P < 0.001), CD8+ T cells (r = -0.155, P < 0.001), CD4+ T cells (r = -0.219, P < 0.001), macrophages (r = -0.36, P < 0.001), and neutrophils (r = -0.204, P < 0.001 under the Spearman correlation test) and dendritic cells (DC, r = -0.283, P < 0.001) were negatively correlated (Figure 6A). Meanwhile, TISIDB evaluated the relationship between ELF3 expression and the level of infiltration of 28 tumor-infiltrating lymphocytes. As shown in Figure 6B, ELF3 is significantly associated with the abundance of tumor-infiltrating lymphocytes in multiple cancer types. Notably, ELF3 expression was significantly higher than that of activated B cells (r = -0.36, P < 0.001), neonatal B cells (r = -0.347, P < 0.001), macrophages (r = -0.296, P < 0.001), mast cells (r = -0.375, P < 0.001), and NK cells (r = -0.291, P < 0.001), NKT cells (r = -0.37, P < 0.001), effector memory CD4 T cells (r = -0.443, P < 0.001), effector memory CD8 T cells (r = -0.258, P < 0.001), follicular helper T cells (r = -0.321, P < 0.001), T helper 1 cells (Th1, r = -0.328, P < 0.001), Th2 (r = -0.276, P < 0.001), and Tregs (r = -0.358, P < 0.001; Figure 6C-N). These results suggest that ELF3 directly or indirectly regulates STAD immune infiltration and TME changes.

Figure 6 Correlation between E74-like ETS transcription factor 3 expression and immune infiltrates in stomach adenocarcinoma. A: Correlation between E74-like ETS transcription factor 3 (ELF3) and abundance of 6 immune cells in TIMER; B: Heatmap of the relationship between ELF3 and abundance of 28 tumor-infiltrating lymphocytes in different tumors using the TISIDB database; C-N: ELF3 was negatively related to the abundance of activated B cells, neonatal B cells, macrophage, mast, natural killer, natural killer T, CD4 T cells, CD8 T cells, follicular helper T cells, T helper 1, T helper 2, and Tregs in stomach adenocarcinoma using the TISIDB database. ELF3: E74-like ETS transcription factor 3; STAD: Stomach adenocarcinoma.

Correlation between ELF3 expression and gene markers in immune cells

Subsequently, the correlation between ELF3 expression and different gene markers in immune cells in STAD was investigated using TIMER and GEPIA databases. After purity adjustment, ELF3 was positively correlated with CD68 of TAM, KIR3DL3 of NK cells, signal transducer and activator of transcription 1 (STAT1) of Th1, STAT6 of Th2, and interleukin 17A (IL17A) of Th17 cells. However, all CD8+ T cells, T cells, B cells, monocytes, macrophages, neutrophils, DCs, and Treg gene markers were significantly negatively correlated (Table 3). To validate these results, we evaluated the relationship between ELF3 expression and gene signatures in CD8+ T cells, T cells, B cells, monocytes, TAMs, M1 macrophages, M2 macrophages, neutrophils, NK cells, DC cells, and Tregs in the GEPIA database. The results showed that ELF3 was positively correlated with CD68 in TAM, KIR3DL3 in NK cells, STAT1 in Th1, STAT6 in Th2, STAT3 and IL17A in Th17 cells, and ELF3 was negatively correlated with most of these genetic markers (Table 4). This is consistent with the results of the TIMER database.

Table 3 Correlation between E74-like ETS transcription factor 3 and related gene markers of immune cells in TIMER.

Description	Gene markers	None correlation coefficient	P value	Purity correlation coefficient	P value
CD8+ T cell	CD8A	-0.150	0.0023	-0.124	0.0156
	CD8B	-0.135	0.0057	-0.126	0.0142
T cell	CD3D	-0.203		-0.168	0.0011
	CD3E	-0.150	0.0021	-0.112	0.0293
	CD2	-0.177		-0.139	0.0068
B cell	CD19	-0.220		-0.184
	CD79A	-0.220		-0.174
Monocyte	CD86	-0.180		-0.158	0.0021
TAM	CCL2	-0.343		-0.331
	CD68	0.168		0.201
	IL10	-0.189		-0.161	0.0017
M1 macrophage	IRF5	-0.018	0.7209	-0.012	0.8206
M2 macrophage	CD163	-0.120	0.0148	-0.099	0.0538
	VSIG4	-0.176		-0.167	0.0011
	MS4A4A	-0.211		-0.197
Neutrophils	CCR7	-0.242		-0.199
NK cell	KIR2DL1	-0.120	0.0147	-0.108	0.0359
	KIR2DL3	-0.100	0.0417	-0.069	0.1820
	KIR2DL4	0.003	0.9467	0.028	0.5866
	KIR3DL1	-0.120	0.0143	-0.092	0.0725
	KIR3DL2	-0.091	0.0632	-0.066	0.1979
	KIR3DL3	0.156	0.0015	0.152	0.0029
	KIR2DS4	-0.057	0.2480	-0.038	0.4560
DC	HLA-DPB1	-0.137	0.0053	-0.094	0.0676
	HLA-DQB1	-0.068	0.1669	-0.011	0.8379
	HLA-DRA	-0.071	0.1492	-0.030	0.5560
	HLA-DPA1	-0.085	0.0831	-0.041	0.4245
Th1 cell	STAT4	-0.232		-0.191
	STAT1	0.087	0.0766	0.120	0.0191
Th2 cell	GATA3	-0.309		-0.297
	STAT6	0.210		0.205
	STAT5A	-0.018	0.7152	-0.007	0.8874
	IL13	-0.068	0.1688	-0.045	0.3857
Th17 cell	STAT3	0.063	0.2023	0.076	0.1417
	IL17A	0.138	0.0048	0.155	0.0024
Treg	FOXP3	-0.031	0.5313	0.022	0.6710
	CCR8	-0.062	0.2108	-0.033	0.5251
	STAT5B	-0.114	0.0204	-0.100	0.0508
T-cell exhaustion	CTLA4	-0.143	0.0035	-0.112	0.0297
	LAG3	-0.109	0.0258	-0.081	0.1163
	GZMB	-0.044	0.3673	-0.003	0.9570

TAM: Tumor-associated macrophage; NK: Natural killer; DC: Dendritic cells; Th: T helper; Treg: Regulatory T cells.

Table 4 Correlation between E74-like ETS transcription factor 3 and related gene markers of immune cells in GEPIA.

Description	Gene markers	Tumor correlation coefficient	P value	Normal	P value
CD8+ T cell	CD8A	-0.170		0.230	0.1700
	CD8B	-0.140	0.0055	0.180	0.2900
T Cell	CD3D	-0.220		0.230	0.1800
	CD3E	-0.160		0.290	0.0820
	CD2	-0.180		0.290	0.0870
B Cell	CD19	-0.210		0.210	0.2200
	CD79A	-0.250		0.380	0.0230
Monocyte	CD86	-0.180		0.220	0.1900
TAM	CCL2	-0.310		-0.530	0.0010
	CD68	0.170		0.650
	IL10	-0.170		0.045	0.7900
M1 macrophage	IRF5	0.048	0.3300	0.650
M2 macrophage	CD163	-0.200		-0.470	0.0041
	VSIG4	-0.160	0.0016	-0.270	0.1200
	MS4A4A	-0.180		-0.480	0.0028
Neutrophils	CCR7	-0.240		0.450	0.0058
NK cell	KIR2DL1	-0.067	0.1800	-0.094	0.5800
	KIR2DL3	-0.048	0.3400	0.098	0.5700
	KIR2DL4	0.170	0.7300	0.550
	KIR3DL1	-0.110	0.0250	-0.002	0.9900
	KIR3DL2	-0.052	0.3000	0.210	0.2100
	KIR3DL3	0.160	0.0011	0.140	0.4300
	KIR2DS4	-0.001	0.9900	0.120	0.4900
DC	HLA-DPB1	-0.110	0.0230	0.170	0.3300
	HLA-DQB1	-0.077	0.1200	0.110	0.5200
	HLA-DRA	-0.075	0.1300	0.240	0.1700
	HLA-DPA1	-0.075	0.1300	0.150	0.3900
Th1 cell	STAT4	-0.220		0.097	0.5800
	STAT1	0.120	0.0160	0.110	0.5100
Th2 cell	GATA3	-0.290		0.420	0.0120
	STAT6	0.320		0.110	0.5400
	STAT5A	0.047	0.3400	-0.300	0.0770
	IL13	-0.070	0.1600	-0.450	0.0065
Th17 cell	STAT3	0.130	0.0068	-0.034	0.8400
	IL17A	0.130	0.0100	0.370	0.0290
Treg	FOXP3	-0.052	0.2900	0.450	0.0060
	CCR8	-0.047	0.3500	0.550
	STAT5B	-0.046	0.3600	-0.390	0.0180
T-cell exhaustion	CTLA4	-0.130	0.0100	0.340	0.0420
	LAG3	-0.130	0.0085	-0.058	0.7300
	GZMB	-0.056	0.2600	0.290	0.0900

TAM: Tumor-associated macrophage; NK: Natural killer; DC: Dendritic cells; Th: T helper; Treg: Regulatory T cells.

Relationship between ELF3 expression and immunomodulators

Immunomodulators, including immunosuppressants and immunostimulants, are substances that regulate the functioning of the immune system. In this study, the correlation between ELF3 expression and immunomodulators was investigated using TISIDB database data. Figure 7A shows a heat map of the relationship between ELF3 expression and immunosuppressants in different tumor types. In STAD, ELF3 is inversely correlated with several immunosuppressants, including IL10, PDCD1 LG2, TGFB1, BTLA, CSF1R, and ADORA2A (Figure 7B). Figure 7C is a heat map of the relationship between ELF3 and immunostimulants in various tumors. In STAD, ELF3 was negatively correlated with the expression of CXCL12, ENTPD1, TNFRSF13C, CD28, KLRK1, and CD48 (Figure 7D).

Figure 7 Correlation between E74-like ETS transcription factor 3 expression and immunomodulators in stomach adenocarcinoma. A: Heatmap of correlations between E74-like ETS transcription factor 3 (ELF3) and immune inhibitors across different cancers from TISIDB; B: Relationships between ELF3 and immune inhibitors in stomach adenocarcinoma, the results show a negative correlation; C: Heatmap of correlations between ELF3 and immune stimulants across different cancers from TISIDB; D: Relationships between ELF3 and immune stimulants in stomach adenocarcinoma, the results show a negative correlation. ELF3: E74-like ETS transcription factor 3; STAD: Stomach adenocarcinoma.

Relationship between ELF3 expression and chemokine

The recruitment and activation of immune cells is driven by the coordinated action of multiple chemokines and their receptors. In order to further estimate the correlation between ELF3 expression and chemokines, the TISIDB database data were used to analyze the correlation. ELF3 is negatively correlated with several chemokines (Figure 8A), including CCL2, CCL11, CCL14, CCL19, CCL21, and CXCL12 (Figure 8B). ELF3 is also negatively correlated with different chemokine receptors (Figure 8C), including CCR2, CCR4, CCR7, CCR10, CX3CR1, and CXCR5 (Figure 8D). The results showed that ELF3 was an immunomodulatory factor of STADs (Supplementary Figure 1).

Figure 8 Correlation between E74-like ETS transcription factor 3 expression and chemokines in stomach adenocarcinoma. A: Heatmap of correlations between E74-like ETS transcription factor 3 (ELF3) and chemokines in different cancers from TISIDB database; B: Correlations between ELF3 expression and chemokines in stomach adenocarcinoma from TISIDB database; C: Heatmap of correlations between ELF3 and receptors in different cancers from TISIDB database; D: Relationships between ELF3 and receptors in stomach adenocarcinoma from TISIDB database. ELF3: E74-like ETS transcription factor 3; STAD: Stomach adenocarcinoma.

DISCUSSION

Today, the clinical prognosis of STAD remains poor, and there is a serious lack of reliable, highly sensitive, and effective specific biomarkers. Therefore, it is crucial to identify important potential tumor biomarkers and explore new therapeutic targets. Several studies have reported that ETS transcription factors may serve as diagnostic and prognostic biomarkers for several cancers[19-21]. Recently, ELK3, a member of the ETS transcription factor family, has been shown to be inversely correlated with the abundance of Tregs, follicular helper T cells, and CD8+ T cells in GC. As an oncogene, ELK3 promotes GC progression and promotes immune evasion in tumor cells[22]. Other studies have identified ELF3 as an oncogene in lung, liver, and breast cancers, and also plays a key role in tumorigenesis, including overexpression of target genes, gene fusion, transition from activator to inhibitor, and even post-translational modifications[7,23], while ELF3 gene mutations have also been confirmed to be associated with GC[24]. The SNAI2-ELF3-AS1 feedback loop regulates the expression of ELF3 at the transcriptional and post-transcriptional levels, which is closely related to GC transfer[25]. These findings suggest that ELF3 may serve as an emerging biomarker that can help evaluate and optimize treatment strategies for patients with STAD.

Limited research on ELF3 hinders a comprehensive understanding of its functional role in STAD, and its underlying mechanisms are difficult to elucidate. In this study, a comprehensive bioinformatics analysis was conducted to explore the expression of ELF3 in STAD and its clinical significance. Our results showed that ELF3 expression was significantly upregulated in STAD tissues, and high expression was associated with poor occlusion rate in STAD patients. In order to further verify the data analysis results, 100 clinical sample data were collected and correlated analysis was conducted, and the results showed that higher ELF3 expression was more correlated with tumor size (P = 0.015), higher N stage (P = 0.023), and higher TNM stage (P = 0.008). In addition, Ki-67 expression (P = 0.001) and E-cadherin expression (P = 0.028) were also significantly correlated with high ELF3 levels, indicating that ELF3 had a pro-infiltration effect in STAD. Multivariate analysis confirmed that high levels of ELF3 expression and vascular invasion were independent prognostic markers in patients with STAD. The Kaplan-Meier curve showed that the occlusion rate was significantly shortened in STAD patients with higher ELF3 expression. These findings from our independent cohort provide strong translational evidence for ELF3 as a practical prognostic indicator.

Mechanistically, our study proposes a unified model that ELF3 drives tumor progression through intrinsic and extrinsic pathways. From an intrinsic perspective, ELF3 expression is associated with key EMT markers, including E-cadherin, N-cadherin, and fibronectin. Previous studies have shown that ELF3 can induce EMT[10]. In addition, low expression of E-cadherin is synergistic in promoting cancer progression[26]. In GC, E-calcium kernels are a well-established tumor suppressor downregulated by mutations or epigenetic factors[11,27-29]. This study aimed to determine the direct regulatory relationship between ELF3 and this EMT phenotype. Our computed chromatin immunoprecipitation followed by sequencing analysis found ELF3 binding peaks in the CDH1 promoter region (E-cadherin). This directly proves that ELF3 acts as a transcriptional repressor of E-cadherin. At the same time, we observed a strong positive correlation between ELF3 and the proliferation marker Ki-67[30-33]. We propose that ELF3 has a dual driving force: It maintains a high proliferative state (indicated by Ki-67) while participating in the EMT program through direct inhibition of CDH1. This synergistic effect results in it exhibiting a highly aggressive phenotype, characterized by rapid growth and increased invasiveness, which explains the poor prognosis observed in our cohort.

From an external perspective, ELF3 appears to reshape the TME to promote immune evasion. The TME consists of a variety of cell types that affect metastasis[34,35]. Using the TISCH database, we confirmed that ELF3 is predominantly expressed in malignant tumor cells rather than immune cells, suggesting that it has a parasecretory mechanism of immune regulation[36,37]. We observed a significant negative correlation between ELF3 expression and infiltration of anti-tumor immune cells, including CD8+ T cells, CD4+ T cells, and DCs[38]. DCs are essential for initiating the immune response, while CD8+ T cells are key effectors of anti-cancer immunity[39,40]. The exclusion of these cells suggests that their phenotype is driven by ELF3[41,42]. To understand this exclusion mechanism, we analyzed the characteristics of chemokines. ELF3 expression is negatively correlated with key chemokines such as CCL2, CCL21, and CXCL12, and is associated with CXCR4 receptors[43]. They promote immune escape by recruiting Tregs and M2 macrophages into the TME and inhibiting anti-tumor immune responses[44]. Most notably, our chromatin immunoprecipitation followed by sequencing analysis showed that ELF3 binds directly to the promoter of CXCL11. CXCL11 is essential for the recruitment of cytotoxic T cells through the CXCR3 receptor. By transcriptional inhibition of CXCL11, ELF3 is likely to form a chemokine-depleted barrier that prevents effector T cells from infiltrating the tumor core.

Despite these important findings, this study has certain limitations. Although we have validated the prognostic value of ELF3 in a cohort of 100 clinical samples, the direct spatial correlation between ELF3 expression and specific immune cell subsets has not been validated in these clinical tissues by multiplex IHC. Our conclusions about immune infiltration rely on comprehensive bioinformatics and single-cell database validation. Future studies need to conduct larger-scale prospective cohort studies to further elucidate the spatial structure of ELF3 in regulating the immune microenvironment. In conclusion, our study confirms that ELF3 is an independent prognostic biomarker in STAD that can harmonize a comprehensive malignant phenotype. By directly inhibiting CDH1, ELF3 drives EMT and intrusion; by inhibiting CXCL11, it inhibits the infiltration of T cells and maintains the immunosuppressive microenvironment. This unified mechanistic insight suggests that targeting ELF3 holds promise to reverse EMT while increasing the sensitivity of “cold” gastric tumors to immunotherapy.

CONCLUSION

ELF3 is significantly overexpressed in STAD tissues and is associated with poor clinicopathological manifestations and poor survival in patients with STAD. High ELF3 expression is associated with reduced levels of infiltration in a variety of immune cells and is closely related to immunomodulators and chemokines in STAD. These findings suggest that ELF3 may serve as a new prognostic biomarker and a potential therapeutic target for STAD.