Tumor-barcoding coupled with high-throughput sequencing for quantitative radiogenomics of the abscopal response in NSCLC
肿瘤条形码与高通量测序相结合,用于 NSCLC 远隔反应的定量放射基因组学
基本信息
- 批准号:10601182
- 负责人:
- 金额:$ 54.17万
- 依托单位:
- 依托单位国家:美国
- 项目类别:
- 财政年份:2023
- 资助国家:美国
- 起止时间:2023-01-01 至 2027-12-31
- 项目状态:未结题
- 来源:
- 关键词:Abscopal effectAnimalsAttentionBar CodesBiological AssayBiological AvailabilityBiological ModelsCancer ModelCell LineCellsClinicClinical ResearchClustered Regularly Interspaced Short Palindromic RepeatsCollaborationsCombination immunotherapyCombined Modality TherapyCoupledDedicationsDisease modelDoseGeneticGenetically Engineered MouseGenomicsGenotypeGoalsHigh-Throughput Nucleotide SequencingHumanImmuneImmune systemImmunocompetentImmunologicsImmunotherapeutic agentImmunotherapyIn VitroLeftLinkLocal TherapyLungMalignant NeoplasmsMalignant neoplasm of lungMapsMediatingModalityModelingMolecularMolecular TargetNon-Small-Cell Lung CarcinomaOncogenesOncologyOralPathway interactionsPatient-Focused OutcomesPatientsPharmaceutical PreparationsPharmacogeneticsPharmacogenomicsPhase I/II Clinical TrialPreclinical TestingProbabilityProcessRadiationRadiation OncologistRadiation therapyRadioRadiogenomicsResearch Project GrantsResistanceRouteSamplingSchemeStandardizationSystemTechniquesTestingTreatment ProtocolsValidationVeterinariansWorkanti-PD-L1anti-PD-L1 therapyanti-tumor immune responsecancer immunotherapycancer subtypeschemoradiationchemotherapyco-clinical trialcurative treatmentsdeep sequencingimmunogenicimprovedin vivoin vivo Modelinhibitorinnovationneoplastic cellnovelpatient derived xenograft modelpre-clinicalpreclinical studyprogramsradiation responseresearch and developmentresistance mechanismresponsestandard of caresuccesstargeted agenttherapy resistanttooltreatment effecttreatment responsetumortumor growthtumor microenvironmenttumorigenesis
项目摘要
Cancer immunotherapy (IMT) can produce robust and durable anti-tumor immune responses in some cases.
However, many cancers are non-responsive to IMT and combination approaches need to be actively
investigated, particularly in lethal tumors such as IMT-insensitive non-small cell lung cancer (NSCLC). Preclinical
studies in general have been found to be poor predictors of success for IMT agents and chemoradiotherapy
combinations in the clinic, likely due to poorly conceived and executed treatment protocols, dated disease model
systems and lack of an existing framework for cross-validation of preclinical results. There is a need to develop
a rigorous preclinical testing program for existing IMT agents combined with chemoradiation. NSCLC genetically
engineered mouse models (GEMMs) of the major molecular NSCLC subtypes have been created. However,
there are no NSCLC GEMMs that to our knowledge has demonstrated “abscopal” responses reliably to IMT,
which is one unique strength of this current proposal. Also, a major limitation of existing GEMMs is the relatively
small number of different genotypes that can be generated and their lack of quantitative precision. This proposal
leverages a new technique, tumor barcoding with barcode deep-sequencing (Tuba-seq) and in vivo Cre-lox and
CRISPR/Cre-mediated GEMMs to model oncogenesis and radiation-drug response with unprecedented
precision and genomic-comprehensiveness. We are using this R01 mechanism in the present proposal via two
Specific Aims stated below to test the following central hypotheses: (i) we hypothesize that treating with both
anti-PD-L1 and a novel orally bioavailable ATR inhibitor (ATRi), AZD6738, in combination with chemoradiation
will result in an improved and durable anti-tumor immune response in poorly immunogenic NSCLC GEMMs; and,
(ii) Tuba-seq we will allow an unprecedented view of the radio-pharmacogenetic landscape of NSCLC responses
in vivo. SPECIFIC AIM #1 – Establish a radio-pharmacogenetic map of oncogene-driven non-small cell lung
cancer to both chemoradiation and combined chemoradiation/anti-PD-L1 therapy We propose to use novel
CRISPR/Cre-mediated GEMMs of NSCLC to test the optimal combinations of chemoradiation with anti-PD-L1
IMT. We will then examine the mechanism of action of chemoradiation with IMT using multiparametric
immunologic approaches and an innovative technique enabling lineage tracing and direct quantification of
treatment effects on these different genetic backgrounds in vivo. SPECIFIC AIM #2 – Determine tumor cell
genotype effects on combination anti-PD-L1 immunotherapy and ATRi with chemoradiotherapy in oncogene-
driven non-small cell lung cancer. This Aim leverages our novel CRISPR/Cre-mediated GEMMs of NSCLC to
test genotype effects on the combination of anti-PD-L1 and ATRi with chemoradiation. By using all these tools,
we will be able to decode the major aspects of the molecular underpinnings of chemoradiation and combination
IMT resistance in NSCLC, contributing to improved therapies and positively impacting patient outcomes.
在某些情况下,癌症免疫疗法(IMT)可以产生强大且持久的抗肿瘤免疫反应。
然而,许多癌症对 IMT 无反应,需要积极采取联合治疗方法
进行了研究,特别是在致死性肿瘤中,例如 IMT 不敏感的非小细胞肺癌 (NSCLC)。临床前
研究发现,总体而言,IMT 药物和放化疗的成功预测效果不佳
临床上的组合,可能是由于治疗方案构思和执行不当、疾病模型过时
系统和缺乏临床前结果交叉验证的现有框架。有需要发展
针对现有 IMT 药物与放化疗相结合的严格临床前测试计划。非小细胞肺癌基因
主要分子 NSCLC 亚型的工程小鼠模型 (GEMM) 已经创建。然而,
据我们所知,没有 NSCLC GEMM 能够可靠地表现出对 IMT 的“远隔”反应,
这是当前提案的一个独特优势。此外,现有 GEMM 的一个主要限制是相对
可以生成的不同基因型数量较少且缺乏定量精度。这个提议
利用新技术,肿瘤条形码与条形码深度测序 (Tuba-seq) 和体内 Cre-lox 和
CRISPR/Cre 介导的 GEMM 以前所未有的方式模拟肿瘤发生和放射药物反应
精确度和基因组综合性。我们在本提案中通过两个方式使用 R01 机制
下面所述的具体目标是为了检验以下中心假设:(i)我们假设同时治疗
抗 PD-L1 和新型口服生物可利用的 ATR 抑制剂 (ATRi) AZD6738 与放化疗相结合
将在免疫原性差的 NSCLC GEMM 中产生改善且持久的抗肿瘤免疫反应;和,
(ii) Tuba-seq 我们将为 NSCLC 反应的放射药物遗传学景观提供前所未有的视角
体内。具体目标#1 – 建立癌基因驱动的非小细胞肺的放射性药物遗传学图
放化疗和放化疗/抗 PD-L1 联合治疗的癌症 我们建议使用新型
CRISPR/Cre 介导的 NSCLC GEMM 用于测试放化疗与抗 PD-L1 的最佳组合
IMT。然后我们将使用多参数研究 IMT 放化疗的作用机制
免疫学方法和创新技术能够进行谱系追踪和直接定量
体内这些不同遗传背景的治疗效果。具体目标#2 – 确定肿瘤细胞
抗 PD-L1 免疫疗法和 ATRi 联合放化疗对癌基因的基因型影响
驱动非小细胞肺癌。该目标利用我们新型 CRISPR/Cre 介导的 NSCLC GEMM
测试基因型对抗 PD-L1 和 ATRi 联合放化疗的影响。通过使用所有这些工具,
我们将能够解码放化疗和联合化疗的分子基础的主要方面
NSCLC 中的 IMT 耐药有助于改善治疗并对患者预后产生积极影响。
项目成果
期刊论文数量(0)
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会议论文数量(0)
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Christopher Dennis McFarland其他文献
Christopher Dennis McFarland的其他文献
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{{ truncateString('Christopher Dennis McFarland', 18)}}的其他基金
Quantifying the sources and dynamics of tumor growth variability using Tuba-seq
使用 Tuba-seq 量化肿瘤生长变异性的来源和动态
- 批准号:
10394424 - 财政年份:2020
- 资助金额:
$ 54.17万 - 项目类别:
Quantifying the sources and dynamics of tumor growth variability using Tuba-seq
使用 Tuba-seq 量化肿瘤生长变异性的来源和动态
- 批准号:
10523113 - 财政年份:2020
- 资助金额:
$ 54.17万 - 项目类别:
Quantifying the sources and dynamics of tumor growth variability using Tuba-seq
使用 Tuba-seq 量化肿瘤生长变异性的来源和动态
- 批准号:
10304318 - 财政年份:2020
- 资助金额:
$ 54.17万 - 项目类别:
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