Malignant Cell Engagement in Immune Circuits of Human Microsatellite-stable and Microsatellite-instable Colorectal Cancer

恶性细胞参与人类微卫星稳定和微卫星不稳定结直肠癌的免疫回路

• 批准号: 10490347
• 负责人: Karin Pelka
• 金额: $ 24.9万
• 依托单位: J. DAVID GLADSTONE INSTITUTES
• 依托单位国家: 美国
• 财政年份: 2021
• 资助国家: 美国
• 起止时间: 2021-04-08 至 2024-08-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/10490347
• 关键词: Acute; Address; Aftercare; Antitumor Response; Automobile Driving; BRAF gene; Beds; Biological Markers; Biological Models; CXCL13 gene; Cancer Etiology; Cancer Patient; Cell Communication; Cell Death; Cell Line; Cells; Cessation of life; Chronic; Clinic; Coculture Techniques; Colorectal Cancer; Communication; Complex; Conflict (Psychology); Data; Development; Environment; Epigenetic Process; Failure; Foundations; Gene Expression; Genes; Genetic Transcription; Human; Immune; Immune Targeting; Immune response; Immune system; Immunologics; Immunotherapeutic agent; Immunotherapy; Impairment; Interferons; Knock-out; Knowledge; Malignant - descriptor; Maps; Measures; Mediating; Microsatellite Repeats; Mission; Modeling; Myelogenous; Myeloid Cells; Neoplasm Transplantation; Organoids; Outcome; Patients; Pattern recognition receptor; Peptides; Phase; Proteomics; Public Health; Research; Resistance; Rest; Solid Neoplasm; Specimen; Stains; Stimulus; Stromal Cells; T cell response; T-Cell Proliferation; T-Lymphocyte; Technology; Testing; Therapeutic; Time; Tumor Immunity; United States; Work; anti-PD-1; antigen-specific T cells; base; cancer cell; career; cell killing; cohort; colon cancer patients; design; epigenetic memory; epigenetic therapy; epigenomics; exposed human population; flexibility; gene induction; genetic signature; in vitro testing; in vivo; inhibitor; insight; metastatic colorectal; mutant; nano-string; neoplastic cell; novel; novel therapeutic intervention; overexpression; patient subsets; pressure; programs; response; single-cell RNA sequencing; spatiotemporal; targeted treatment; therapy resistant; transcriptome; transcriptomics; treatment response; tumor; tumor immunology

Project Summary An important question in cancer immunology is how malignant cells and T cells communicate and impact the efficacy of anti-tumor immunity. To generate hypotheses for how these cells interact, we have applied single cell RNA sequencing to profile the transcriptomes of >700,000 malignant, immune, and stromal cells in 2 cohorts: (1) 65 patients with two types of primary untreated CRC (31 MSS and 34 MSI tumors) which are characterized by vastly different immunotherapy response rates; (2) pre- and post-treatment specimens from 20 BRAF-mutant metastatic CRC patients treated with BRAFi/MEKi/anti-PD1. These data led us to formulate the central hypothesis for this proposal: malignant cells that express interferon-stimulated genes (ISGs) acutely promote anti-tumor immunity, while chronic interferon responses in malignant cells impair anti-tumor immunity and therapeutic responses. The proposed work is anticipated to reveal fundamental insights into human tumor immunology and provide a novel perspective for the design of robust biomarkers and new therapeutic strategies. We will address three major questions. First, is the MSI/responder-associated ISG program in malignant cells part of an intra-tumoral feed-forward loop that is driving anti-tumor immunity? This will be answered by spatially mapping the intratumoral cellular interaction network between ISG+ malignant cells and T cells in untreated primary CRC specimens, and in post-treatment specimens of patients treated with BRAFi/MEKi/anti-PD-1, which will reveal association of this spatial network with tumor regression. Second, what are the drivers of malignant ISGs in human CRC, and can interferons impact immune responses and responses to targeted therapy by epigenetically reprogramming human CRC cells? To address this, we will use interferons and innate immune stimuli to induce ISGs in CRC organoids, map the transcriptional and epigenetic signatures to the signatures found in freshly isolated CRC cells, and nominate ISG-inducing upstream regulators. IFN-stimulated and subsequently rested organoids will be assessed for epigenetic memory and for modulated secondary immune and drug responses. Third, how do pre-existing ISG signatures in malignant cells impact CTL-mediated anti-tumor responses? Using peptide-cognate T cell lines, we will test the in vitro killing of ISG+ and ISG- peptide-loaded CRC organoids. We will furthermore test how ISGs modulate in vivo tumor killing by temporally controlling malignant ISG expression in transplantable tumor models. In summary, we use scRNAseq to predict malignant cell – T cell interactions, and then test these hypotheses with cutting-edge technologies such as spatial profiling, single cell epigenomics, and human organoid T cell co-cultures. The results should elucidate how malignant cells that respond to interferons impact anti-tumor immunity and resistance, generate foundational results and model systems for an R01 proposal, and prepare the candidate for an independent career to study the cellular networks that drive human tumor immunity.

项目摘要 癌症免疫学中的一个重要问题是恶性细胞和T细胞如何沟通和影响肿瘤细胞。 抗肿瘤免疫的功效。为了产生这些细胞如何相互作用的假设，我们应用了单个 细胞RNA测序，以分析2个国家中> 700，000个恶性，免疫和基质细胞的转录组 队列：（1）65名患有两种类型的原发性未经治疗的CRC（31例MSS和34例MSI肿瘤）的患者， 其特征在于免疫治疗反应率差异很大;（2）来自 20例BRAF突变转移性CRC患者接受BRAFi/MEKi/抗PD 1治疗。这些数据使我们制定了 该建议的中心假设：恶性细胞急性表达干扰素刺激基因（ISGs） 促进抗肿瘤免疫，而恶性细胞中的慢性干扰素应答损害抗肿瘤免疫 和治疗反应。这项工作有望揭示人类肿瘤的基本见解 并为设计稳健的生物标志物和新的治疗方法提供了新的视角。 战略布局我们将讨论三个主要问题。首先，MSI/响应者相关的ISG计划 恶性细胞是肿瘤内前馈回路的一部分，它驱动着抗肿瘤免疫？这将是 通过在空间上映射ISG+恶性细胞和 未治疗的原发性CRC标本中的T细胞，以及用 BRAFi/MEKi/抗PD-1，这将揭示这种空间网络与肿瘤消退的关联。第二、 人类CRC中恶性ISG的驱动因素是什么，干扰素是否会影响免疫反应， 通过表观遗传学重编程人类CRC细胞对靶向治疗的反应？为了解决这个问题，我们将 使用干扰素和先天免疫刺激物诱导CRC类器官中的ISG，绘制转录和 表观遗传特征与新鲜分离的CRC细胞中发现的特征相似，并提名ISG诱导 上游监管机构。将评估IFN刺激和随后休息的类器官的表观遗传 记忆和调节的二次免疫和药物反应。第三，如何预先存在的ISG签名 影响CTL介导的抗肿瘤反应？使用肽同源T细胞系，我们将测试 负载ISG+和ISG-肽的CRC类器官的体外杀伤。我们将进一步测试ISG如何 通过暂时控制可移植肿瘤中的恶性ISG表达来调节体内肿瘤杀伤 模型总之，我们使用scRNAseq来预测恶性细胞- T细胞相互作用，然后测试这些相互作用。 假设与尖端技术，如空间分析，单细胞表观基因组学，和人类 类器官T细胞共培养物。结果应该阐明恶性细胞如何对干扰素产生反应， 抗肿瘤免疫和抗性，为R 01提案生成基础结果和模型系统， 并为候选人的独立职业做好准备，以研究驱动人类肿瘤的细胞网络。 免疫力