Shi Lingting, Giglio Ross M, Cai Qingyuan, Vaikunthan Mathini, Hong Justin, Naqvi Abdullah, Milea Marina, Khanshali Hannah, Schoonen Anna, Hou Nicholas, Guo Jonathan, Fraidenburg Melanie, Shen Xumin, Malinowski Seth W, Ligon Keith L, Rabadán Raúl, Azizi Elham, McFaline-Figueroa José L
Irving Institute for Cancer Dynamics, Columbia University, New York, NY, 10027, USA.
Department of Biomedical Engineering, Columbia University, New York, NY, 10027, USA.
bioRxiv. 2026 Jan 9:2026.01.08.698516. doi: 10.64898/2026.01.08.698516.
Immune dysfunction in cancer is enacted by multiple programs, including tumor cell-intrinsic responses to distinct immune subpopulations. A subset of these immune evasion programs can be systematically recapitulated through direct tumor-immune interactions . Here, we present an integrated, high-throughput single-cell CRISPR screening framework focused on the protein kinome for mapping the tumor-intrinsic regulation of T cell-driven immune pressure in glioblastoma (GBM). We combine pooled CRISPR interference and activation (CRISPRi/a) with immune-matched NY-ESO-1 antigen-specific allogeneic GBM-T cell co-culture and massively multiplexed single-cell transcriptomics to systematically quantify how genetic perturbation reshapes baseline tumor state and adaptive responses across graded effector-to-target ratios. We further leverage deep generative models for analyzing pooled CRISPR screens to decipher the effects of genetic perturbations on the mechanisms of tumor resistance. This framework resolves distinct modules of immune evasion and survival, including the regulation of the antigen-presentation machinery, interferon/NF-κB signaling, oxidative stress resilience, and checkpoint/cytokine programs, while identifying perturbations that reroute the continuous tumor transcriptional trajectory induced by T cell engagement. A secondary chemical screen in patient-derived GBM cultures identified putative kinase targets of immune evasion phenotypes (e.g., EPHA2 and PDGFRA), whose inhibition leads to the blockade of evasive programs and enhances T cell-mediated GBM killing. Together, this workflow provides a scalable blueprint for comprehensive charting of the genetic control of tumor-immune interactions.
癌症中的免疫功能障碍是由多种程序引发的,包括肿瘤细胞对不同免疫亚群的内在反应。这些免疫逃逸程序的一部分可以通过直接的肿瘤-免疫相互作用被系统地重现。在这里,我们提出了一个综合的、高通量的单细胞CRISPR筛选框架,该框架聚焦于蛋白激酶组,用于绘制胶质母细胞瘤(GBM)中T细胞驱动的免疫压力的肿瘤内在调控图谱。我们将汇集式CRISPR干扰和激活(CRISPRi/a)与免疫匹配的NY-ESO-1抗原特异性同种异体GBM-T细胞共培养以及大规模多重单细胞转录组学相结合,以系统地量化基因扰动如何在不同效应细胞与靶细胞比例下重塑基线肿瘤状态和适应性反应。我们还利用深度生成模型来分析汇集式CRISPR筛选,以解读基因扰动对肿瘤抗性机制的影响。该框架解析了不同的免疫逃逸和存活模块,包括抗原呈递机制的调控、干扰素/NF-κB信号传导、氧化应激恢复能力以及检查点/细胞因子程序,同时识别出能够改变由T细胞参与诱导的连续肿瘤转录轨迹的扰动。在患者来源的GBM培养物中进行的二次化学筛选确定了免疫逃逸表型的假定激酶靶点(例如,EPHA2和PDGFRA),对其抑制可导致逃逸程序的阻断并增强T细胞介导的GBM杀伤作用。总之,这个工作流程为全面描绘肿瘤-免疫相互作用的基因控制提供了一个可扩展的蓝图。