EC is the most common malignant tumor of the digestive tract and has a poor prognosis. Studies have established several novel biomarkers to determine the prognosis of EC patients, such as miRNA signatures7,8, autophagy-related signatures9, m6A RNA methylation regulator-based signatures10, integrated mRNA-lncRNA signatures11, epigenetic signatures12, lymph node metastasis-associated gene signatures13, urinary metabolomic signatures14, and immune-related gene signatures15. Although RBP-related signatures have been analyzed for a variety of cancers16–21, related analyses for EC are rare. Hence, there is a need for a prognostic analysis of RBP-related genes in
EC patients to explore their functional roles and potential clinical significance. Therefore, in this study, we used an integrated analysis of various databases to construct a Cox proportional hazards regression model with 7 prognostic RBPs (TRMT2A, PDHA1, MPRIP, KRI1, IL17A, HSPA1A and HIST1H4J) that could be used to predict prognosis and chemoresistance in EC patients.
Notably, PDHA1 and IL17A are newly predicted RBP genes, and not all 7 prognostic RBP-related genes have been reported to be associated with prognosis in cancer. For TRMT2A, the only study has reported that TRMT2A protein expression is a biomarker of increased risk of recurrence in HER2 + breast cancer patients and may be used to predict the response to adjuvant cytotoxic chemotherapy22. PDHA1 has been reported to be biologically significant in several human tumors. However, for EC, only one study demonstrated that inhibition of PDHA1 gene expression in human ESCC leads to increased malignancies23. However, as shown in our prediction model, TRMT2A was found to be a gene that improves prognosis, while PDHA1 makes the prognosis worse, which needs further validation in EC. IL17A is a member of the IL17 cytokine family and is released by both immune and nonimmune cells (such as tumor and stromal cells) into the tumor microenvironment. Among all the IL17 cytokine family members, IL17A is the most controversial in regulating tumor immunity and has different prognostic values among various cancers. Generally, tumor-infiltrating IL-17A-producing cells (IL17A + cells) are correlated with elevated antitumor immunity24. A study demonstrated that IL17A deficiency reduces tumor latency and promotes metastasis in lung cancer25, and a study showed that IL17A mRNA expression could be used as a predictive biomarker for superior response to adjuvant chemotherapy and can indicate better patient survival in gastric cancer26. In pancreatic cancer, an anti-IL17A antibody can enhance the antitumor response to gemcitabine27, which implies that IL17A may be involved in the development of drug resistance. IL17A polymorphisms were associated with the risk of various cancers, and the IL17A rs4711998 A > G polymorphism was associated with a decreased risk of EC28. Our study showed that IL17A can indicate poor patient survival in EC. HSPA1A was associated with unfavorable survival and poor clinicopathological features in several kinds of tumors29–31. Furthermore, HSPA1A was demonstrated to mediate breast cancer radioresistance32. However, no study has shown the effects of HSPA1A on malignant biological properties, treatment sensitivity and prognosis in EC. Importantly, MPRIP, KRI1 and HIST1H4J have not been reported to be associated with prognosis in cancer and are our newly discovered genes that may be associated with EC prognosis.
In this study, we established a seven-gene biomarker as a novel prognostic model and analyzed its ability to predict prognosis in different cohorts. Although the number of adjacent normal tissues from TCGA was relatively small (n = 11), it did not affect the reliability of the results. The prognostic performance of the model was validated by internal and external validation. Importantly, the RBP signature is also a good independent indicator of survival with adjusted clinical parameters, including age, sex, T classification, N classification, M classification, tumor grade, and stage.
We further analyzed the predictive effect of the RBP signature for chemotherapy and immunotherapy response. Interestingly, our signature can predict the efficacy of chemotherapy, while the efficacy of immunotherapy was not well predicted. Many of the chemotherapy agents used in the treatment of cancer interfere with the production of nucleic acids, RNA and DNA. Thus, chemotherapy may interfere with the binding of RBPs to RNAs. In return, the expression of RBPs may influence chemotherapy, leading to drug sensitivity or resistance. The chemotherapy agents identified (cisplatin, doxorubicin, mitomycin C, sorafenib, and vinblastine) in our study can provide new ideas and serve as a basis for future clinical drug research. However, as shown in our study, there were no significant differences in most of the biomarkers for predicting ICI responses and immune cells in the immune microenvironment. This is probably the main reason for the unpredictability of immunotherapy. Different responses to treatment and different mechanisms of resistance stem from different antitumor mechanisms. This might suggest that different signatures are needed to predict drug sensitivity/resistance and prognosis. Various immune gene signatures have been identified to predict therapeutic effects in various kinds of tumors33–36. Wang et al identified a prognostic immune gene signature in EC; however, this signature did not predict immunotherapy response15. Therefore, further studies are needed to predict the therapeutic effect of immunotherapy in EC.
In conclusion, we established a prognostic signature with 7 prognostic RBPs as biomarkers for EC patients. Our study could also contribute to providing new insight into chemoresistance in EC patients.