EC is the seventh most common cancer and the sixth leading cause of death from cancer across the world [1]. Current treatment strategies can vary among stages or cancer types, with endoscopic resection optimal to most early tumors, surgical resection followed by chemotherapy, radiotherapy, or targeted therapy (single or combined) beneficial to locally advanced tumors, but non-surgical treatment, particularly systemic chemotherapy, suitable for metastatic cases [2]. However, the prognosis remains constant in EC patients undergoing antitumor treatment, though diverse and being improved [2]. EC is often diagnosed when it develops to middle or advanced stages and when a 5-year survival rate decreases to lower than 20% [3]. Even so, immunotherapy, particularly immune checkpoint inhibitors (ICIs), has received much attention over the last few years. It has been proven effective in and is recommended for the management of malignant melanoma, non-small cell lung cancer, and clear cell renal cell carcinoma, with significantly improved patient prognosis [4]. For EC treatment, ICIs, alone or combined with chemoradiotherapy, have gradually moved up to the first-line treatment and exerted impressive antitumor effects [5, 6]. However, not all patients can benefit from this treatment, despite some patients who have shown better overall or progression-free survival, which is a concern for immunotherapy application. Therefore, biomarkers for systemic prediction of prognosis and immunotherapy efficacy for EC patients are urgently needed [7].

Tumor occurrence and progression are often determined by malignant behaviors, such as tumor cell proliferation and invasion, which are related to the tumor microenvironment (TME), especially the tumor immune microenvironment (TIME) that contains immune suppressor cells helpful to immune escape [8]. Immune checkpoint molecules, particularly programmed death receptor 1 (PD-1) and programmed cell death-ligand 1 (PD-L1), have been proven to be more frequently present in tumor cells and tumor-infiltrating immune cells to disturb antitumor immune response [9]. Their involvement in cell differentiation in EC cells, tumor staging, immunotherapy efficacy, and patient prognosis have been extensively reported [10-13]. Immune cell infiltration patterns characterized by these molecules can be associated with tumorigenesis, progression, and lymph node metastasis, and subsequently impaired efficacy of immunotherapy and prognosis [14-16]. Further, high TMB is positively correlated with overall survival (OS) after ICIs treatment in various cancer types [17], which may predict the efficacy of ICIs more accurately than PD-L1 [18].

Compared to a single cancer-related gene with limited predictive power, a multigene signature has more significant implications in this regard. In this study, we generated a prognostic risk model comprising seven IRGs based on differentially expressed IRGs in EC, validated its performances in overall survival prediction, and assessed its correlations with prognostic clinicopathological and immune features.

EC is considered most aggressive among gastrointestinal malignancies, which has a 5-year survival rate of 15–25% across the world [27, 28], with median overall survival of only 13 months [29]. EC patients may have cachexia, early satiety, dysphagia, aspiration, apastia, and other symptoms that pronouncedly diminish quality of life. Currently, immunotherapy comprised of immune checkpoint inhibitors, peptide vaccines, and adoptive T cell immunotherapy has received increasing attention [7], though it cannot substitute for conventional treatment like surgery, radiotherapy, and chemotherapy [30]. Its efficacy has been proven for some refractory EC subtypes [31]. For far too long, we have not yet identified an excellent biomarker for predicting immunotherapy response and OS, which emphasizes the need for future studies into exploring such biomarkers for EC. The prediction power of any single tumor marker is insufficient for tumors, whose microenvironment is jointly regulated by multiple genes. Although some studies have reported IRG signatures in EC [32,33], the current study performed extra analyses, including immune checkpoint biomarker expressions and IC₅₀ prediction. Compared to previous reports, our study offers more feasible findings for clinical application, which can be directly used as recommendations for EC treatment. The seven-IRG-based prognostic signature exhibits good accuracy in predicting overall survival (with AUC ranging from 0.673 to 0.816), stages of cancer progression, and characterization of immune cell infiltration pattern. The signature also shows good performance in characterizing expression patterns of immune checkpoint genes and predicting IC₅₀ values. The discrimination power allows physicians to select the optimal treatment strategies to hopefully extend the survival of EC patients.

The immune microenvironment is critical for tumor occurrence and progression. In the present study, we identified 275 DEIs based on gene expression data from 171 tissue samples of EC patients from TCGA. These genes are primarily involved in the activities of cytokines, chemokines, and growth factors, and their recognition and binding to protein targets, closely related to tumor growth, proliferation, or immunity. 15 of 275 prognostic DEIs were included in a Lasso-Cox model for optimal gene signature selection using 2/3 of all patients as a training cohort. A prognostic signature based on seven IRGs (APLN, CACYBP, FABP3, GPER1, JAG2, SFTPA1, and XCR1) was determined, and its efficacy in overall survival prediction was validated using the remanent 1/3 of patients assigned to the test cohort. Among others, the chemokine receptor XCR1 showed the highest specific gravity in the IRGs model (coef = −0.76193). It was reported that XCR1 was exclusively expressed on CD8⁺ DCs and can stimulate CD8⁺T cells to proliferate, thus enhancing the immune system [34]. XCR1 downregulation has been shown to stimulate the immune system to exert the antitumor activity, which is critical to alter the immune cell landscape in the TME that delays tumor progression [35]. It is expected to serve as a novel target of immunotherapy [36]. Calcyclin-binding protein (CACYBP) is universally considered most harmful, with its major function of participating in the connection between actin and tubulin to facilitate cytoskeleton formation [37] and in cell differentiation and proliferation in neuroblastoma NB2a cells via activation of the ERK1/2 pathway [38]. As highlighted in current studies, CACYBP promotes tumor occurrence and progression in various tumors via anti-apoptotic activity in cancer cells and inhibiting the cell cycle [39-41]. Fatty acid binding proteins 3 (FABP3) facilitates fatty acid transport, cell growth, cellular signaling, and gene transcription. Moreover, in non-small cell lung cancer and gastrointestinal stromal tumors, FABP3 overexpression is notably correlated with tumor size and lymph node metastasis of advanced tumors and with remarkably shorter survival of patients [42, 43]. It was therefore revealed that FABP3 is of strong prognostic significance. G protein-coupled estrogen receptor 1 (GPER1) has been reported to be involved in cell cycle regulation, endoplasmic reticulum stress, proliferation, apoptosis, and immune response [44]. GPER1 silencing inhibits gastric cancer cell proliferation, migration, and invasion via inhibiting PI3K/Akt-mediated epithelial-mesenchymal transition [45]. A six-IRGs (AMBP, C6, ITLN1, MADCAM1, PRLR, and TSPAN2) based prognostic model in ESCC also obtained comparable predictive efficacy to our model [46]. The above genes are critical for EC progression, which can be considered to be oncogenes or tumor-suppressor genes. These gene studies may involve the key realm of EC development and management, but more studies are required for validation. The functions of genes mentioned above in tumor cells demonstrate that the signature is expected to predict the prognosis and progression stages of EC patients and hopefully offer opportunities to identify new therapeutic targets of EC to improve treatment. Overall, the signature is a biomarker associated with tumor immunity and growth inhibition.

We also assessed the prediction ability of the prognostic signature and ascertained its excellent accuracy in predicting the overall survival and death risk of EC patients and independent discrimination power from other clinical indicators. Further, it shows significant correlations with these clinical indicators. These findings suggest that the signature shows the potential of predicting how fast EC progresses based on especially clinical stages and lymph node and distant metastasis. High-risk patients need effective treatment in a more timely manner. Therefore, it can be involved in the early screening of high-risk EC patients for improved prognosis. Besides, in analyses of different pathological subtypes of EC, we found that EAC patients exhibited a higher risk score than ESCC patients, and the difference of the survival analysis was also found to be much more significant in the cases of EAC compared to ESCC. This finding indicates that the calculated risk score may be an important indicator in predicting the OS of EC cases, and the seven genes included in the signature can be important roles, probably in regulating the histological evolution of EAC, offering the prospect of identifying new targets for EAC treatment and prognosis prediction. Besides, its ability to predict somatic mutations has been assessed. The signature well predicted mutation probabilities between high- and low-risk EC patients, especially those of TP53, TTN, and MUC16 genes. TP53 mutations are most common in malignant tumors and associated with enhanced invasiveness and worse prognosis of patients [47, 48]. TP53 mutations may stimulate tumor cell proliferation and tumor growth via abnormal p53/TGF-β signaling activity, potentially explaining rapid tumor progression and poor prognosis in high-risk patients. These predicted gene mutations may offer new targets for drug development or a new treatment strategy for patients at increased risk for tumor progression.

The seven-IRG-based signature also shows satisfactory efficacy in predicting ICG expressions, TMB, and the immune cell landscape in the TIME of EC patients, all of which are capable of sensitivity assessment of immunotherapy. Among the 12 ICGs frequently reported, PDCD1 (encoding PD-1) has been proven to facilitate EC progression and distant metastasis [11]. Patients with CD274 (encoding PD-L1) upregulation or high TMB tend to benefit more from immunotherapy therapy [12]. Although TMB has no effect on EC prognosis, it allows us to exclude the prognostic effect of TMB itself and turn our focus to the relationship between TMB and immunotherapy—the signature may somewhat compromise outcome in patients receiving immunotherapy. CTLA4- or IDO1-positive immune cells are negatively correlated with the overall survival of patients [49, 50]. Patients with VISTA-positive immune cells often exhibit prolonged survival [51]. However, those with CD274- and IDO1-double-positive immune cells have shorter overall survival and decreased sensitivity to chemotherapy agents [52]. The potential mechanisms of aberrant ICG expressions for tumor progression are complex and have not yet been fully explored. But PDCD1 and CD274 expressions as effective biomarkers for predicting ICIs’ efficacy have been ascertained by many [10-12,53]. In the present study, CTLA4, CD274, and PDCD1 expressions were upregulated in low-risk patients. Neutrophils are most abundant in immune cells and a critical component of the TME. Neutrophil infiltration into tumors may allow inflammation to persist and fuel tumor progression and metastasis [54]. Mast cells promote tumor growth and proliferation via immunosuppression, angiogenesis, and tissue remodeling [55]. Consistently, our finding shows that activated mast cell and neutrophil infiltration was markedly enhanced in high- vs. low-risk patients, and naive B cell and resting mast cell infiltration was reduced. This indicates that the seven-IRG-based signature can characterize the TIME of high-risk EC patients. Numerous evidence shows that elevated PDCD1, CD274, and CTLA4 expressions are associated with a poor prognosis, which is in contrast to our findings of improved prognosis of low-risk patients who have the same gene expression patterns. This can be explained by the positive correlation of the infiltration of PDCD1-, CD274-, and CTLA4-overexpressed immune cells responsible for antitumor immunity with survival time. Studies have ascertained that PDCD1 and CD274 expressions in tumor cells and tumor-infiltrating immune cells are associated with improved prognosis, which supports our finding [56,57]. The above results indicate that the seven-IRG-based prognostic signature has good efficacy in predicting immune cell infiltration pattern, somatic mutations, TMB, and ICG expression pattern in EC. Taken together, it offers insight into the TIME of individual patients and molecular evidence to optimize ICI strategy for EC patients [58]. However, immune checkpoint expressions are not identical to the exact sensitivity to immunotherapy in patients, so its prediction for ICI efficacy still needs validation by future clinical trials.

In the present study, high-risk patients selected using the signature showed higher predicted IC₅₀ for the chemotherapy agents paclitaxel, cisplatin, and doxorubicin and the targeted therapy agent erlotinib. Rather, low-risk patients had lower predicted IC₅₀ for these agents. These results are consistent with a high frequency of TP53 mutations described above as TP53 has significant associations with the unsatisfactory efficacy of neoadjuvant therapy [59]. Therefore, we believe that this signature can offer helpful feedback to improve efficacy. Thus, the signature is promising in estimating the efficacy of conventional chemotherapy or targeted therapy strategies. Overall, low-risk patients identified by the signature hopefully benefit more from immunotherapy and conventional chemotherapy. As for high-risk patients, new therapeutic strategies or a combination of multiple agents are required to improve prognosis, which, however, calls for massive clinical observations for validation.

The seven-IRG-based prognostic signature can independently predict the prognosis, tumor progression, and immune infiltration pattern in the TIME of EC patients. It shows the potential to monitor the efficacy of immunotherapy, chemotherapy, and targeted therapy for personalized treatment for these patients.