机器学习引导胶质母细胞瘤细胞转化为树突状细胞样抗原递呈细胞,作为癌症免疫疗法。

IF 8.1 1区 医学 Q1 IMMUNOLOGY
Tianyi Liu, Dan Jin, Son B Le, Dongjiang Chen, Mathew Sebastian, Alberto Riva, Ruixuan Liu, David D Tran
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引用次数: 0

摘要

由于血脑屏障和免疫抑制或 "冷 "肿瘤微环境(TME),免疫疗法对胶质母细胞瘤(GBM)的疗效有限,因为GBM的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(DC)匮乏。在此,我们报告了一种机器学习精确方法的开发和应用情况,该方法可识别细胞命运决定因子(CFD),这些细胞命运决定因子可特异性地将 GBM 重编程为具有类似 DC 功能的诱导抗原递呈细胞(iDC-APC)。在小鼠 GBM 模型中,iDC-APC 获得了类似 DC 的形态、调控基因表达谱以及与天然 DC 类似的功能。这些获得的功能包括吞噬、直接呈现内源性抗原和交叉呈现外源性抗原。后者赋予了 iDC-APCs 为天真 CD8+ CTLs 提供能量的能力,这是一种对抗肿瘤免疫至关重要的 DC 标志性功能。瘤内 iDC-APCs 仅在免疫功能正常的动物中能减少肿瘤生长并提高存活率,这与 CD4+ T 细胞和活化的 CD8+ CTL 在 TME 中的广泛浸润相吻合。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,使肿瘤特异性CD8+ CTL对高度耐药的GBM细胞产生强大的杀伤力,并显著延长了生存期。最后,我们定义了一种独特的CFD组合,专门用于人类GBM向胶质瘤干样细胞(GSC)和非GSC GBM细胞的iDC-APC转换,证实了计算定向、肿瘤特异性转换免疫疗法对GBM和潜在的其他实体瘤的临床实用性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Machine Learning-Directed Conversion of Glioblastoma Cells to Dendritic Cell-Like Antigen-Presenting Cells as Cancer Immunotherapy.

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 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 cells 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 PD1 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 and non-stem-like cell GBM cells, confirming the clinical utility of a computationally directed, tumor-specific conversion immunotherapy for GBM and potentially other solid tumors.

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来源期刊
Cancer immunology research
Cancer immunology research ONCOLOGY-IMMUNOLOGY
CiteScore
15.60
自引率
1.00%
发文量
260
期刊介绍: Cancer Immunology Research publishes exceptional original articles showcasing significant breakthroughs across the spectrum of cancer immunology. From fundamental inquiries into host-tumor interactions to developmental therapeutics, early translational studies, and comprehensive analyses of late-stage clinical trials, the journal provides a comprehensive view of the discipline. In addition to original research, the journal features reviews and opinion pieces of broad significance, fostering cross-disciplinary collaboration within the cancer research community. Serving as a premier resource for immunology knowledge in cancer research, the journal drives deeper insights into the host-tumor relationship, potent cancer treatments, and enhanced clinical outcomes. Key areas of interest include endogenous antitumor immunity, tumor-promoting inflammation, cancer antigens, vaccines, antibodies, cellular therapy, cytokines, immune regulation, immune suppression, immunomodulatory effects of cancer treatment, emerging technologies, and insightful clinical investigations with immunological implications.
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