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.

项目摘要/摘要 复发或对一线无效的大B细胞淋巴瘤(LBCL)患者的预后 治疗仍然相当糟糕。而抗CD19嵌合抗原受体(CAR19)T细胞已经成为一种 对于这一组患者来说，有希望的治疗方案是，超过一半的患者仍然表现出疾病 进步。CAR19 T细胞治疗耐药的发生机制及其影响因素 对糟糕结果的预测，还没有得到很好的描述。在这项提议中，我们试图澄清这些 机制，最终目标是通知改进的免疫疗法的设计，从而产生更好的 LBCL患者的预后。 从患者血浆中分析肿瘤来源的无细胞DNA的新方法，也参考 作为循环中的肿瘤DNA(CtDNA)，释放了监测治疗反应和 在治疗前和治疗后研究肿瘤生物学。我们最近应用了一种名为癌症的方法 一种用于ctDNA检测的靶向测序方法--CAPP-SEQ 以及对一组接受cAR19平台axicabagene治疗的LBCL患者的分析 绒毛(轴细胞)。我们发现，在cAR19 T细胞输注前后ctDNA水平可以预测 并鉴定了几个与B细胞谱系承诺和决定B细胞系的 进展性疾病患者肿瘤免疫微环境反复改变。 在这项提案中，我们将在先前数据的基础上，通过验证我们在独立队列中的发现 接受替代cAR19平台治疗的患者(目标1)。然后我们将对下游进行评估 这些改变对肿瘤表型和肿瘤微环境有影响。通过整合基因 表达数据和尖端的免疫表型和计算工具，我们将解析组件 以更好地了解不同的免疫细胞群如何 有助于应对和抵抗(目标2)。最后，我们将采用一种新的有机组织培养系统来 直接评估这些基因的改变如何影响cAR19 T细胞和肿瘤细胞之间的相互作用 完整免疫微环境的背景(目标3)。最终，我们希望这些研究将有 不仅对改进的淋巴瘤cAR19平台的开发有意义，而且对改进的cAR19平台也有意义 对其他癌症类型的免疫疗法也是如此。 这项提议将在斯坦福大学医学院进行，由 Ash Alizadeh医学博士/博士通过完成这项提案，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，成为一名专注于开发 以及为淋巴瘤患者翻译新的免疫疗法。