Determinants of resistance to engineered T-cell therapies targeting CD19 in lymphoma

淋巴瘤中针对 CD19 的工程化 T 细胞疗法耐药性的决定因素

• 批准号: 10740658
• 负责人: Brian Sworder
• 金额: $ 1.54万
• 依托单位: STANFORD UNIVERSITY
• 依托单位国家: 美国
• 财政年份: 2023
• 资助国家: 美国
• 起止时间: 2023-07-01 至 2023-08-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/10740658
• 关键词: Aftercare; Antigen Targeting; Architecture; B-Cell Lymphomas; B-Lymphocytes; Bioinformatics; CD19 gene; Cancer Personalized Profiling by Deep Sequencing; Candidate Disease Gene; Cell Lineage; Cell physiology; Cells; Clinical Trials; DNA Sequence Alteration; Data; Detection; Development; Disease Progression; Doctor of Philosophy; Exhibits; Foundations; Future; Gene Expression; Gene Expression Profiling; Genes; Genomics; Goals; Health; Immune; Immunohistochemistry; Immunophenotyping; Immunotherapy; In Vitro; Inferior; Infusion procedures; Knowledge; Lead; Life; Lymphoma; Lymphoma cell; Measurement; Mediating; Mentorship; Methods; Mission; Modeling; Molecular; Monitor; Mutation; Nature; Non-Hodgkin' s Lymphoma; Organism; Organoids; Outcome; PAX5 gene; Patient-Focused Outcomes; Patients; Phenotype; Plasma; Population; Predictive Factor; Primary Neoplasm; Progressive Disease; Recurrence; Refractory; Relapse; Research Personnel; Resistance; Role; Sampling; Surface; System; T cell therapy; T-Lymphocyte; Techniques; Translating; Treatment Failure; Tumor Biology; Tumor Escape; Tumor Tissue; Tumor-Derived; United States National Institutes of Health; Universities; adverse outcome; biomarker identification; cancer type; career; cell free DNA; chimeric antigen receptor; chimeric antigen receptor T cells; cohort; computerized tools; cytotoxicity; design; disability; engineered T cells; experience; improved; in vitro Model; innovation; medical schools; neoplastic cell; novel; predicting response; prognostic significance; protein expression; relapse prediction; resistance gene; resistance mechanism; resistance mutation; response; targeted sequencing; targeted treatment; therapy development; tissue culture; tool; transcriptome sequencing; treatment response; treatment strategy; tumor; tumor DNA; tumor immunology; tumor microenvironment; tumor-immune system interactions

Project Summary/Abstract The outcomes for patients with large B-cell lymphoma (LBCL) that are relapsed or refractory to frontline therapy remain quite poor. While anti-CD19 chimeric antigen receptor (CAR19) T-cells have emerged as a promising treatment option for this group of patients, over half of these patients still go on to exhibit disease progression. The mechanisms through which resistance to CAR19 T-cell therapy develops, and factors predictive of poor outcomes, have not yet been well characterized. In this proposal we seek to elucidate these mechanisms with the ultimate goal of informing the design of improved immunotherapies that will result in better outcomes for patients with LBCL. Novel methods to profile tumor-derived cell-free DNA from the blood plasma of patients, also referred to as circulating tumor DNA (ctDNA), have unlocked significant opportunities to monitor treatment response and study tumor biology both prior to and after therapy. We recently applied one such method called Cancer Personalized Profiling by Deep Sequencing (CAPP-Seq), a targeted sequencing approach for ctDNA detection and profiling, to a cohort of patients with LBCL undergoing therapy with the CAR19 platform axicabtagene ciloleucel (axi-cel). We found that ctDNA levels prior to and following CAR19 T-cell infusion were predictive of response, and also identified several genes involved in B-cell lineage commitment and determination of the tumor immune microenvironment that were recurrently altered in patients who developed progressive disease. In this proposal we will build on this prior data by validating our findings in an independent cohort of patients undergoing therapy with an alternate CAR19 platform (Aim 1). We will then assess the downstream effects these alterations have on tumor phenotype and the tumor microenvironment. By integrating gene expression data and cutting-edge immunophenotyping and computational tools, we will resolve the components of the intratumoral immune milieu to gain a better understanding of how different immune cell populations contribute to response and resistance (Aim 2). Finally, we will employ a novel organoid tissue culture system to directly assess how alterations in these genes effect the interaction between CAR19 T-cells and tumor cells in the context of an intact immune microenvironment (Aim 3). Ultimately, we hope that these studies will have implications not only in development of improved CAR19 platforms for lymphoma, but also in the improvement of immunotherapies for other cancer types as well. This proposal will be carried out at the Stanford University School of Medicine, under the mentorship of Ash Alizadeh, MD/PhD. Through completion of this proposal, I will gain the relevant experience in bioinformatics and tumor immunology to successfully launch a career as an independent investigator focused on developing and translating new immunotherapies for patients with lymphoma.

项目总结/摘要 复发性或一线治疗难治性大B细胞淋巴瘤（LBCL）患者的结局 治疗仍然很差。虽然抗CD 19嵌合抗原受体（CAR 19）T细胞已经成为一种免疫抑制剂， 尽管这类患者的治疗选择很有希望，但这些患者中仍有一半以上继续表现出疾病， 进展对CAR 19 T细胞疗法产生耐药性的机制，以及 预测不良结局，尚未得到很好的表征。在本建议中，我们试图阐明这些 机制，最终目标是为设计更好的免疫疗法提供信息， LBCL患者的结局。 描述来自患者血浆的肿瘤来源的无细胞DNA的新方法，也称为 作为循环肿瘤DNA（ctDNA），已经开启了监测治疗反应的重要机会， 在治疗前后研究肿瘤生物学。我们最近应用了一种叫做癌症的方法 深度测序个性化分析（CAPP-Seq），ctDNA检测的靶向测序方法 对接受CAR 19平台axicabtagene治疗的LBCL患者队列进行分析 ciloleucel（axi-cel）。我们发现，CAR 19 T细胞输注前后的ctDNA水平可预测 反应，并确定了几个基因参与B细胞谱系的承诺和决定的， 肿瘤免疫微环境在发展为进行性疾病的患者中反复改变。 在这项提案中，我们将建立在这一先前的数据，通过验证我们的研究结果在一个独立的队列， 接受替代CAR 19平台治疗的患者（Aim 1）。然后我们将评估下游 这些改变对肿瘤表型和肿瘤微环境的影响。通过整合基因 表达数据和尖端的免疫表型和计算工具，我们将解决这些问题 为了更好地了解不同的免疫细胞群 有助于反应和抵抗（目标2）。最后，我们将采用一种新的类器官组织培养系统， 直接评估这些基因的改变如何影响CAR 19 T细胞和肿瘤细胞之间的相互作用， 完整的免疫微环境（目标3）。最终，我们希望这些研究能够 不仅在开发用于淋巴瘤的改进的CAR 19平台方面， 免疫疗法也能治疗其他癌症。 这项建议将在斯坦福大学医学院进行，导师是 Ash Alizadeh，MD/PhD.通过完成这一计划，我将获得生物信息学的相关经验 和肿瘤免疫学，成功地启动了职业生涯，作为一个独立的研究人员，专注于发展 并为淋巴瘤患者提供新的免疫疗法。