由于血脑屏障和 GBM 的免疫抑制或“冷”肿瘤微环境 (TME)，免疫疗法对胶质母细胞瘤 (GBM) 的疗效有限，该微环境以免疫抑制细胞为主，细胞毒性 T 淋巴细胞 (CTL) 和树突状细胞被耗尽细胞（DC）。在这里，我们报告了一种机器学习精确方法的开发和应用，该方法用于识别细胞命运决定因素（CFD），该方法将 GBM 特异性重编程为具有 DC 样功能的诱导抗原呈递细胞（iDC-APC）。在小鼠 GBM 模型中，iDC-APC 获得了与天然 DC 类似的形态、调控基因表达谱和功能。这些获得的功能包括吞噬作用、内源抗原的直接呈递和外源抗原的交叉呈递。后者赋予 iDC-APC 启动幼稚 CD8 CTL 的能力，这是对抗肿瘤免疫至关重要的标志性 DC 功能。肿瘤内 iDC-APC 仅在免疫功能正常的动物中减少肿瘤生长并提高生存率，这与 TME 中 CD4 T 细胞的广泛浸润和激活的 CD8 CTL 相一致。重新激活的 TME 与肿瘤内可溶性 PD-1 诱饵免疫疗法和基于 DC 的 GBM 疫苗协同作用，导致肿瘤特异性 CD8 CTL 强力杀死高度耐药的 GBM 细胞，并显着延长生存期。最后，我们定义了一种独特的 CFD 组合，专门用于神经胶质瘤干细胞样细胞 (GSC) 和非 GSC GBM 细胞的人 GBM 到 iDC-APC 的转换，证实了计算指导的肿瘤特异性转换免疫疗法的临床实用性GBM 和潜在的其他实体瘤。

Immunotherapy has limited efficacy in glioblastoma (GBM) due to the blood-brain barrier and the immunosuppressed or "cold" tumor microenvironment (TME) of GBM, which is dominated by immune-inhibitory cells and depleted of cytotoxic T lymphocytes (CTL) and dendritic cells (DC). Here, we report the development and application of a machine-learning precision method to identify cell fate determinants (CFD) that specifically reprogram GBM into induced antigen-presenting cells with DC-like functions (iDC-APC). In murine GBM models, iDC-APCs acquired DC-like morphology, regulatory gene expression profile, and functions comparable to natural DCs. Among these acquired functions were phagocytosis, direct presentation of endogenous antigens, and cross presentation of exogenous antigens. The latter endowed the iDC-APCs with the ability to prime naïve CD8+ CTLs, a hallmark DC function critical for antitumor immunity. Intratumor iDC-APCs reduced tumor growth and improved survival only in immunocompetent animals, which coincided with extensive infiltration of CD4+ T cells and activated CD8+ CTLs in the TME. The reactivated TME synergized with an intratumor soluble PD-1 decoy immunotherapy and a DC-based GBM vaccine, resulting in robust killing of highly resistant GBM cells by tumor-specific CD8+ CTLs and significantly extended survival. Lastly, we defined a unique CFD combination specifically for the human GBM to iDC-APC conversion of both glioma stem-like cells (GSC) and non-GSC GBM cells, confirming the clinical utility of a computationally directed, tumor-specific conversion immunotherapy for GBM and potentially other solid tumors.