食管鳞癌三级淋巴结构精准评估模型的建立及其对免疫治疗指导作用的探索

免疫治疗给晚期食管鳞癌患者带来了希望，但目前缺乏生物标记物，仅有少部分患者可以长期生存获益。既往研究发现肿瘤中三级淋巴结构（Tertiary lymphoid structures，TLS）与免疫治疗疗效密切相关，但精准评估TLS存在困难。我们前期研究（1）成功建立了食管癌三级淋巴结的检测平台；（2）发现三级淋巴结构可以预测食管癌免疫治疗的疗效；（3）小剂量表观遗传药物可逆转食管癌免疫治疗耐药，同时诱导食管癌三级淋巴结结构形成。因此，我们推测小剂量表观遗传药物可以通过诱导三级淋巴结形成，达到逆转食管癌免疫治疗的效果。本项目将通过人工智能技术构建TLS可视化预测模型，探索并动态检测小剂量表观遗传药物诱导TLS产生和逆转免疫治疗耐药的作用，为精准预测和逆转食管癌免疫耐药提供理论基础。

Immunotherapy has revolutionized the treatment hallmark of advanced esophageal squamous cell carcinoma (ESCC). Although immune checkpoint inhibitors (ICIs) have achieved significant progress in advanced ESCC, only around 10-30% patients could gain long time survival benefit. Tertiary lymphoid structures (TLS) has been found closely related to ICIs, however, it is hard to precise evalute the TLS multidimensionally and visulaly. In our precious research, we established a platform for detecting the TLS successfully; found that the tertiary lymph structure could predict the efficacy of immunotherapy; revealed that low dose of epigenetic modifiers could reverse the aquired resistance to immunotherapy and induced the formation of tertiary lymphoid structures concurrently. Based on these findings, we hypothesized that low dose epigenetic modifiers could reverse the acquired resistance of ICIs via inducing the formation of TLS. This project will establish a visualization model based on multiomics, radiomics, two-photon fluorescence microscopy and artificial Intelligence technologies and finally explore the mechanism of underlining the formation of TLS and revising the acquired resistance of ICIs. This work will provide novel theoretical basis for precise prediction and reversion of the acquired resistance of ICIs in esophageal cancer.