Systematically identifying synergistic combinations of targeted agents and immunotherapies for cancer treatments remains difficult. In this study, we integrated high-throughput and high-content techniques—an implantable microdevice to administer multiple drugs into different sites in tumors at nanodoses and multiplexed imaging of tumor microenvironmental states—to investigate the tumor cell and immunological response signatures to different treatment regimens. Using a mouse model of breast cancer, we identified effective combinations from among numerous agents within days. In vivo studies in three immunocompetent mammary carcinoma models demonstrated that the predicted combinations synergistically increased therapeutic efficacy. We identified at least five promising treatment strategies, of which the panobinostat, venetoclax and anti-CD40 triple therapy was the most effective in inducing complete tumor remission across models. Successful drug combinations increased spatial association of cancer stem cells with dendritic cells during immunogenic cell death, suggesting this as an important mechanism of action in long-term breast cancer control.

系统地识别用于癌症治疗的靶向药物和免疫疗法的协同组合仍然很困难。在这项研究中，我们整合了高通量和高内涵技术——一种可植入的微装置，以纳米剂量将多种药物注射到肿瘤的不同部位，并对肿瘤微环境状态进行多重成像——以研究肿瘤细胞和对不同治疗方案的免疫反应特征。使用乳腺癌小鼠模型，我们在几天内从众多药物中确定了有效的组合。三种免疫活性乳腺癌模型的体内研究表明，预测的组合可协同提高治疗效果。我们确定了至少五种有前景的治疗策略，其中帕比司他、venetoclax 和抗 CD40 三联疗法在跨模型中诱导肿瘤完全缓解方面最有效。成功的药物组合增加了免疫原性细胞死亡过程中癌症干细胞与树突状细胞的空间关联，表明这是长期乳腺癌控制的重要作用机制。