新辅助化学免疫疗法对局部晚期食管鳞状细胞癌（ESCC）具有良好的疗效。然而，仍然缺乏可靠的生物标志物来稳健地预测治疗反应。收集了局部晚期食管鳞癌患者的福尔马林固定和石蜡包埋的新辅助化学免疫治疗前活检样本。第 1 组由来自前瞻性临床试验 (NCT04506138) 的 66 名局部晚期 ESCC 患者组成，每 3 周接受两个周期的 camrelizumab 联合白蛋白结合型紫杉醇和卡铂治疗。第 2 组包括 48 名接受各种类型的免疫检查点抑制剂以及（白蛋白结合）紫杉醇和铂类化疗作为新辅助治疗的患者。第 3 组由 27 名接受特瑞普利单抗新辅助化疗的 ESCC 患者组成，被用作外部验证数据集。进行了靶向 RNA 测序、程序性死亡配体 1 (PD-L1) 免疫组织化学和多重免疫荧光 (mIF) 成像。靶向 RNA 测序、PD-L1 免疫组织化学和 mIF 的整合揭示了一个显着的免疫抑制微环境，具有较高的中性粒细胞浸润、富集非病理性完全缓解 (non-pCR) 患者的 TGF-β 和细胞周期途径。 NK、活化的 CD4 T 细胞浸润、干扰素-γ、抗原加工和呈递以及其他免疫反应特征与 pCR 显着相关。根据发现的肿瘤微环境特征及其密切相关的基因进行筛选。因此，构建了七基因新辅助化学免疫治疗风险预测特征（NCIRP）模型。除了队列 1 之外，该模型单独或与 PD-L1 组合阳性评分 (CPS) 一起显示出比队列 2 中的 PD-L1 CPS 或其他常规使用的免疫特征（例如 IFN-γ）更高的病理反应预测准确性3. 在癌症基因组图谱计划 ESCC 数据集中或新辅助放化疗队列（队列 4）中的 ESCC 患者中，未观察到与放化疗反应的预后相关性或相关性。NCIRPs 模型是使用未经治疗的内窥镜样本开发和验证的来自最大的 ESCC 新辅助化学免疫治疗数据集代表了一种稳健且具有临床意义的方法，用于为局部晚期 ESCC 患者选择新辅助化学免疫治疗的假定反应者。© 作者（或其雇主）2024。CC BY 允许重复使用-NC。禁止商业再利用。请参阅权利和权限。英国医学杂志出版。

Neoadjuvant chemoimmunotherapy has a promising effect on locally advanced esophageal squamous cell carcinoma (ESCC). However, reliable biomarkers robustly predicting therapeutic response are still lacking.Formalin-fixed and paraffin-embedded pre-neoadjuvant chemoimmunotherapy biopsy samples from locally advanced ESCC patients were collected. Cohort 1 composed of 66 locally advanced ESCC patients from a prospective clinical trial (NCT04506138) received two cycles of camrelizumab in combination with nab-paclitaxel and carboplatin every 3 weeks. Cohort 2 included 48 patients receiving various types of immune checkpoint inhibitors with (nab-)paclitaxel and platinum-based chemotherapy as neoadjuvant therapy. Cohort 3 consisted of 27 ESCC patients receiving neoadjuvant treatment of toripalimab with chemotherapy and was used as the external validation dataset. Targeted RNA sequencing, immunohistochemistry for programmed death ligand 1 (PD-L1), and multiplex immunofluorescence (mIF) imaging were performed.Integration of targeted RNA sequencing, PD-L1 immunohistochemistry, and mIF revealed a significant immune-suppressive microenvironment with higher neutrophil infiltration, enriched TGF-β, and cell cycle pathways in non-pathological complete response (non-pCR) patients. NK, activated CD4+ T cell infiltration, interferon-gamma, antigen processing and presentation, and other immune response signatures were significantly associated with pCR. Based on discovered tumor microenvironmental characteristics and their closely related genes were screened. Consequently, a seven-gene neoadjuvant chemoimmunotherapy risk prediction signature (NCIRPs) model, was constructed. In addition to cohort 1, this model alone or with PD-L1-combined positive score (CPS) demonstrated a higher prediction accuracy of pathological response than PD-L1 CPS or other routinely used immune signatures, such as IFN-γ, in cohorts 2 and 3. Neither prognostic association nor correlation with response to chemoradiotherapy was observed in The Cancer Genome Atlas Program ESCC dataset or in ESCC patients in the neoadjuvant chemoradiotherapy cohort (cohort 4).The NCIRPs model that was developed and validated using treatment-naïve endoscopic samples from the largest ESCC neoadjuvant chemoimmunotherapy dataset represents a robust and clinically meaningful approach to select a putative responder for neoadjuvant chemoimmunotherapy in locally advanced ESCC patients.© Author(s) (or their employer(s)) 2024. Re-use permitted under CC BY-NC. No commercial re-use. See rights and permissions. Published by BMJ.