Department of Medical Oncology and Internal Medicine VI, National Center for Tumor Diseases, University Hospital Heidelberg, Heidelberg, Germany.
German Cancer Consortium (DKTK), Heidelberg, Germany.
Cancer Res. 2018 Sep 1;78(17):5155-5163. doi: 10.1158/0008-5472.CAN-18-1126. Epub 2018 Jul 2.
Solid tumors are rich ecosystems of numerous different cell types whose interactions lead to immune escape and resistance to immunotherapy in virtually all patients with metastatic cancer. Here, we have developed a 3D model of human solid tumor tissue that includes tumor cells, fibroblasts, and myeloid and lymphoid immune cells and can represent over a million cells over clinically relevant timeframes. This model accurately reproduced key features of the tissue architecture of human colorectal cancer and could be informed by individual patient data, yielding tumor explants. Stratification of growth kinetics of these explants corresponded to significantly different overall survival in a cohort of patients with metastatic colorectal cancer. We used the model to simulate the effect of chemotherapy, immunotherapies, and cell migration inhibitors alone and in combination. We classified tumors according to tumor and host characteristics, showing that optimal treatment strategies markedly differed between these classes. This platform can complement other patient-specific models and can be used for high-throughput screening of combinatorial immunotherapies. This patient-informed tumor growth model allows testing of different cancer treatment strategies and immunotherapies on a cell/tissue level in a clinically relevant scenario. .
实体瘤是由众多不同细胞类型组成的丰富生态系统，其相互作用导致几乎所有转移性癌症患者的免疫逃逸和对免疫疗法的耐药性。在这里，我们开发了一种包含肿瘤细胞、成纤维细胞以及髓系和淋巴系免疫细胞的人类实体瘤组织的 3D 模型，该模型可以在临床相关的时间范围内代表超过一百万种细胞。该模型准确再现了人类结直肠癌组织的关键结构特征，并且可以通过个体患者数据进行信息补充，从而生成肿瘤外植体。这些外植体的生长动力学分层与转移性结直肠癌患者队列中的总生存率存在显著差异。我们使用该模型单独和组合模拟了化疗、免疫疗法和细胞迁移抑制剂的效果。我们根据肿瘤和宿主特征对肿瘤进行分类，表明这些类别之间的最佳治疗策略有显著差异。该平台可以补充其他基于患者的模型，并可用于组合免疫疗法的高通量筛选。这种基于患者的肿瘤生长模型允许在临床相关情况下在细胞/组织水平上测试不同的癌症治疗策略和免疫疗法。
