即使采用手术切除和三联化疗治疗，胰腺癌（PC）的预后也极差。癌症免疫疗法最近已被批准用于通过基因组分析进行肿瘤不可知的治疗，包括在 PC 中。然而，它的疗效有限。除了肿瘤突变负荷低之外，PC免疫治疗的困难之一是其微环境中存在丰富的基质细胞。在基质细胞中，癌症相关成纤维细胞 (CAF) 在免疫治疗耐药性中发挥着重要作用，目前正在开发 CAF 靶向疗法，包括与免疫疗法联合的疗法。与此同时，微生物组和肿瘤源性外泌体 (TDE) 已被证明可以改变 PC 中远端受体细胞的行为。本文讨论了CAF、微生物组和TDE在PC肿瘤免疫中的作用。阐明CAF、微生物组和TDE参与PC肿瘤发生的机制将有助于开发新的免疫治疗策略和识别免疫治疗的伴随生物标志物。肿瘤微环境的空间单细胞分析将有助于识别 PC 免疫的生物标志物。此外，鉴于免疫机制的复杂性，人工智能模型将有利于预测免疫治疗的疗效。

Pancreatic cancer (PC) has an extremely poor prognosis, even with surgical resection and triplet chemotherapy treatment. Cancer immunotherapy has been recently approved for tumor-agnostic treatment with genome analysis, including in PC. However, it has limited efficacy.In addition to the low tumor mutation burden, one of the difficulties of immunotherapy in PC is the presence of abundant stromal cells in its microenvironment. Among stromal cells, cancer-associated fibroblasts (CAFs) play a major role in immunotherapy resistance, and CAF-targeted therapies are currently under development, including those in combination with immunotherapies. Meanwhile, microbiomes and tumor-derived exosomes (TDEs) have been shown to alter the behavior of distant receptor cells in PC. This review discusses the role of CAFs, microbiomes, and TDEs in PC tumor immunity.Elucidating the mechanisms by which CAFs, microbiomes, and TDEs are involved in the tumorigenesis of PC will be helpful for developing novel immunotherapeutic strategies and identifying companion biomarkers for immunotherapy. Spatial single-cell analysis of the tumor microenvironment will be useful for identifying biomarkers of PC immunity. Furthermore, given the complexity of immune mechanisms, artificial intelligence models will be beneficial for predicting the efficacy of immunotherapy.