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.
癌症免疫治疗(IMT)在某些情况下可以产生强大而持久的抗肿瘤免疫应答。
然而,许多癌症对IMT无反应,需要积极地联合治疗。
研究,特别是在致死性肿瘤,如IMT不敏感的非小细胞肺癌(NSCLC)。临床前
一般研究发现,IMT药物和放化疗的成功预测效果较差
临床联合用药,可能是由于构思和执行不当的治疗方案,过时的疾病模型
系统和缺乏现有的框架交叉验证临床前的结果。需要开发
对现有IMT药物联合放化疗进行严格的临床前试验。NSCLC基因
已经建立了主要分子NSCLC亚型的工程小鼠模型(GEMM)。然而,在这方面,
据我们所知,没有NSCLC GEMM已经证明对IMT的“远位”反应可靠,
这是当前提案的一个独特优势。此外,现有GEMM的一个主要局限性是
可以产生的不同基因型的数量少,并且它们缺乏定量精确度。这项建议
利用一种新的技术,肿瘤条形码与条形码深度测序(Tuba-seq)和体内Cre-lox,
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
精确性和基因组全面性。在本提案中,我们通过两个
具体目的如下所述,以检验以下中心假设:(i)我们假设,
抗PD-L1和新型口服生物可利用ATR抑制剂(ATRi)AZD 6738联合放化疗
将在免疫原性差的NSCLC GEMM中产生改善和持久的抗肿瘤免疫应答;并且,
(ii)Tuba-seq将为NSCLC缓解的放射药物遗传学前景提供前所未有的视角
in vivo.特定目的#1 -建立癌基因驱动的非小细胞肺的放射药理学图谱
我们建议使用新的抗PD-L1治疗方法,
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,我们将研究的作用机制,放化疗与IMT使用多参数
免疫学方法和一种创新的技术,使谱系追踪和直接定量
治疗对这些不同的体内遗传背景的影响。具体目标#2 -确定肿瘤细胞
基因型对抗PD-L1免疫治疗和ATRi联合放化疗在癌基因-
非小细胞肺癌该目标利用我们的新型CRISPR/Cre介导的NSCLC GEMM,
测试基因型对抗PD-L1和ATRi与化疗联合使用的影响。通过使用所有这些工具,
我们将能够解码放化疗和联合治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结局产生积极影响。
项目成果
期刊论文数量(0)
专著数量(0)
科研奖励数量(0)
会议论文数量(0)
专利数量(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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