Published online Apr 28, 2024. doi: 10.3748/wjg.v30.i16.2195
Revised: March 5, 2024
Accepted: April 10, 2024
Published online: April 28, 2024
Processing time: 91 Days and 7.1 Hours
As a highly invasive malignancy, esophageal cancer (EC) is a global health issue, and was the eighth most prevalent cancer and the sixth leading cause of cancer-related death worldwide in 2020. Due to its highly immunogenic nature, emer-ging immunotherapy approaches, such as immune checkpoint blockade, have demonstrated promising efficacy in treating EC; however, certain limitations and challenges still exist. In addition, tumors may exhibit primary or acquired resistance to immunotherapy in the tumor immune microenvironment (TIME); thus, understanding the TIME is urgent and crucial, especially given the im-portance of an immunosuppressive microenvironment in tumor progression. The aim of this review was to better elucidate the mechanisms of the suppressive TIME, including cell infiltration, immune cell subsets, cytokines and signaling pathways in the tumor microenvironment of EC patients, as well as the downregulated expression of major histocompatibility complex molecules in tumor cells, to obtain a better understanding of the differences in EC patient responses to immunotherapeutic strategies and accurately predict the efficacy of immunotherapies. Therefore, personalized treatments could be developed to maximize the advantages of immunotherapy.
Core Tip: Esophageal cancer (EC) is a significant global health issue, and immunotherapy holds promise for treating this disease. However, resistance to immunotherapy may occur, and is usually associated with the tumor immune microenvironment (TIME). Understanding the TIME, especially the suppressive TIME, is crucial. The aim of this review is to elucidate the underlying mechanisms of the suppressive TIME in EC, including cell infiltration, immune cell subsets, cytokines and signaling pathways, as well as the downregulated expression of major histocompatibility complex molecules in tumor cells. This summary may help predict EC patient responses to immunotherapies and facilitate personalized treatments to optimize immunotherapeutic outcomes.