Department of Medical Oncology, Senior Department of Oncology, Chinese PLA General Hospital, The Fifth Medical Center, Beijing, China.
College of Artificial Intelligence, Nanjing University of Aeronautics and Astronautics, Nanjing, China.
Oncogene. 2024 Sep;43(37):2751-2767. doi: 10.1038/s41388-024-03123-z. Epub 2024 Aug 9.
Esophageal squamous cell carcinoma (ESCC) presents significant clinical and therapeutic challenges due to its aggressive nature and generally poor prognosis. We initiated a Phase II clinical trial (ChiCTR1900027160) to assess the efficacy of a pioneering neoadjuvant chemo-immunotherapy regimen comprising programmed death-1 (PD-1) blockade (Toripalimab), nanoparticle albumin-bound paclitaxel (nab-paclitaxel), and the oral fluoropyrimidine derivative S-1, in patients with locally advanced ESCC. This study uniquely integrates clinical outcomes with advanced spatial proteomic profiling using Imaging Mass Cytometry (IMC) to elucidate the dynamics within the tumor microenvironment (TME), focusing on the mechanistic interplay of resistance and response. Sixty patients participated, receiving the combination therapy prior to surgical resection. Our findings demonstrated a major pathological response (MPR) in 62% of patients and a pathological complete response (pCR) in 29%. The IMC analysis provided a detailed regional assessment, revealing that the spatial arrangement of immune cells, particularly CD8+ T cells and B cells within tertiary lymphoid structures (TLS), and S100A9+ inflammatory macrophages in fibrotic regions are predictive of therapeutic outcomes. Employing machine learning approaches, such as support vector machine (SVM) and random forest (RF) analysis, we identified critical spatial features linked to drug resistance and developed predictive models for drug response, achieving an area under the curve (AUC) of 97%. These insights underscore the vital role of integrating spatial proteomics into clinical trials to dissect TME dynamics thoroughly, paving the way for personalized and precise cancer treatment strategies in ESCC. This holistic approach not only enhances our understanding of the mechanistic basis behind drug resistance but also sets a robust foundation for optimizing therapeutic interventions in ESCC.
食管鳞状细胞癌（ESCC）具有侵袭性和普遍较差的预后，因此在临床和治疗方面具有重大挑战。我们启动了一项 II 期临床试验（ChiCTR1900027160），评估一种新的新辅助化疗免疫治疗方案的疗效，该方案包括程序性死亡受体-1（PD-1）阻断剂（特瑞普利单抗）、白蛋白结合型紫杉醇（nab-紫杉醇）和口服氟嘧啶衍生物 S-1，用于局部晚期 ESCC 患者。该研究使用成像质谱细胞术（IMC）将临床结果与先进的空间蛋白质组学分析独特地结合在一起，以阐明肿瘤微环境（TME）中的动态变化，重点研究耐药性和反应的机制相互作用。60 名患者参与了该研究，在手术切除前接受了联合治疗。我们的研究结果表明，62%的患者有主要病理反应（MPR），29%的患者有病理完全缓解（pCR）。IMC 分析提供了详细的区域评估，显示免疫细胞的空间排列，特别是 CD8+T 细胞和 B 细胞在三级淋巴结构（TLS）内以及纤维化区域中 S100A9+炎症巨噬细胞，与治疗结果相关。通过使用机器学习方法，如支持向量机（SVM）和随机森林（RF）分析，我们确定了与耐药性相关的关键空间特征，并为药物反应开发了预测模型，曲线下面积（AUC）为 97%。这些见解强调了将空间蛋白质组学纳入临床试验以彻底剖析 TME 动态的重要作用，为 ESCC 的个体化和精准癌症治疗策略铺平了道路。这种整体方法不仅增强了我们对耐药性背后的机制基础的理解，而且为优化 ESCC 的治疗干预提供了坚实的基础。
