Quantitative PET Imaging for Oncologic Immune Response Prediction
Quantitative PET Imaging for Oncologic Immune Response Prediction
批准号:
9979791
负责人:
Benjamin M Larimer
金额:
$20.64万
依托单位国家:
美国
项目类别:
财政年份:
2019
资助国家:
美国
项目状态:
已结题
起止时间:
2019-08-01 至 2022-07-31
关键词:
AddressAdverse eventAnatomyAntibodiesApoptosis PromoterBiochemical GeneticsBiological MarkersBiopsyCTLA4 geneCancer ModelCellsClinical ResearchClinical TrialsCombined Modality TherapyConsumptionCytotoxic T-LymphocytesDangerousnessDiagnosticDrug CombinationsEnzymesEvaluationEventExcisionExpression ProfilingFlow CytometryGranzymeHumanImageImmuneImmune checkpoint inhibitorImmune responseImmune systemImmunomodulatorsImmunooncologyImmunotherapyInvadedInvestmentsKnowledgeMalignant NeoplasmsMeasuresMetabolicMethodsMinorityMonitorMusNatureOutcomePD-1 inhibitorsPatientsPeptidesPhenotypePopulationPositron-Emission TomographyProceduresRiskSamplingSiteStagingT-Cell ActivationT-LymphocyteTechniquesTherapeuticTimeTreatment EfficacyTumor MarkersTumor VolumeTumor-infiltrating immune cellsWorkanti-CTLA-4 therapyanti-PD1 therapybasecancer cellcancer imagingcheckpoint therapychemokineclinical investigationcytokineeffective therapyeffector T cellexhaustfluorodeoxyglucosegenetic analysisimaging approachimaging modalityimmune checkpoint blockadeimprovedinsightmRNA Expressionneoplastic cellnew technologynovelpeptide Bpre-clinicalpredicting responsepredictive markerprogrammed cell death ligand 1programmed cell death protein 1responders and non-respondersresponsesingle-cell RNA sequencingskillstraffickingtreatment armtumor
中文摘要
摘要
免疫检查点抑制剂显着改善了多种癌症的总体生存率,
反过来又引发了巨大的科学和财政投资,以进一步扩大这种治疗方法
范式。然而,目前免疫疗法的益处仅在少数患者中得到体现。
使问题进一步复杂化的是,许多免疫疗法都存在严重不良免疫事件的风险,并且
检测治疗效果的方法(例如解剖分期和 18F-FDG PET 成像)很混乱
由于免疫渗透的潜在存在。这些入侵的免疫细胞可能会引起潜在的反应
肿瘤体积增大,18F-FDG 消耗增加,这使得它们与进展无法区分
恶性肿瘤。由于目前诊断能力的缺乏,许多患者唯一的选择是接受
免疫疗法必须确定他们是否对总体生存有反应,这是一个长期且潜在的过程
确定治疗效果的危险方法。另外,随着药品数量的不断增加
以及正在临床试验的组合,在早期阶段监测治疗效果的能力将
可能有助于更快地批准新疗法。目前,尚无批准的生物标志物
确定治疗效果,并在治疗前对肿瘤标志物(例如 PD-L1)进行活检分析
仅导致结果略有改善。因此,预测反应的生物标志物将允许
临床前和临床研究均取得重大进展。
颗粒酶 B,由效应 T 细胞激活后分泌,可作为有效的诱导剂
细胞凋亡是免疫治疗反应的有力预测因子。我开发了一种新颖的选择性 PET
成像肽可检测颗粒酶 B 的分泌形式和活性形式,从而区分
对免疫疗法有积极反应和无反应,其中含有颗粒酶 B 的 T 细胞“耗尽”
可能存在但不主动分泌酶。使用颗粒酶 B 肽进行 PET 成像
在肿瘤体积变化之前对免疫治疗的反应进行高度敏感和特异性的预测
小鼠同基因癌症模型。这种表型不仅限于小鼠,因为人类样本分析了
通过抗体和我的肽显示出响应中的颗粒酶 B 水平显着高于非响应中的颗粒酶 B
有反应的患者。因此,颗粒酶 B PET 成像提供了对早期反应的独特见解,这是
目前可以使用任何其他技术。当前的方法无法准确定义之前的响应
破坏性采样,作为响应被定义为缺乏进展。鉴于这些限制,我建议
使用颗粒酶 B PET 成像根据颗粒酶 B 水平对小鼠进行分层,然后进行生化和
有反应和无反应肿瘤的遗传分析。 PET 成像的非侵入性性质不会
仅在任何解剖变化之前提供反应的准确区分,但也将允许
基于初始 PET 成像结果的二次治疗操作。
英文摘要
Abstract
Immune checkpoint inhibitors have markedly improved overall survival in a number of cancers, which
has in turn sparked tremendous scientific and financial investment into further expansion of this treatment
paradigm. Currently, however, the benefits of immunotherapy have only been realized in a minority of patients.
Further complicating the issue, many immunotherapies carry risks of severe adverse immune events, and
methods to detect therapeutic efficacy such as anatomical staging and 18F-FDG PET imaging are confounded
by the potential presence of immune infiltrate. These invading immune cells can cause potentially responding
tumors to increase in size and in 18F-FDG consumption, which make them indistinguishable from progressing
malignancies. Because of the lack of current diagnostic capabilities, the only option many patients undergoing
immunotherapy have to determine if they are responding is overall survival, which is a long and potentially
dangerous approach to determining therapeutic efficacy. Additionally, given the increasing number of drugs
and combinations being clinically trialed, the ability to monitor therapeutic efficacy at an earlier stage would
potentially help bring new treatments to approval much faster. Currently, there is no approved biomarker for
determining therapeutic efficacy, and biopsy analysis of tumor markers such as PD-L1 prior to treatment have
only resulted in modest improvements of outcome. Thus a biomarker that predicted response would permit
significant advances in both the pre-clinical and clinical investigations.
Granzyme B, which is secreted by T effector cells following activation and acts as a potent inducer of
apoptosis, is a strong predictor of immunotherapy response. I have developed a novel and selective PET
imaging peptide that detects the secreted and active form of granzyme B, permitting differentiation between
active response to immunotherapy and non-response in which “exhausted” T cells that contain granzyme B
may be present but are not actively secreting the enzyme. PET imaging with the granzyme B peptide permits
highly sensitive and specific prediction of response to immunotherapy prior to changes in tumor volume in
murine syngeneic models of cancer. This phenotype is not limited to mice, as human samples analyzed both
by antibody and my peptide show significantly higher levels of granzyme B in responding versus non-
responding patients. Thus, granzyme B PET imaging offers a unique insight into early response that is not
currently possible using any other technique. Current methods cannot accurately define a response prior to
destructive sampling, as a response is defined as lack of progression. Given these limitations, I am proposing
to use granzyme B PET imaging to stratify mice based on granzyme B levels, followed by biochemical and
genetic analysis of responding and non-responding tumors. The non-invasive nature of PET imaging will not
only provide accurate differentiation of response prior to any anatomic changes, but will also allow for
secondary therapeutic manipulations based on initial PET imaging results.
期刊论文(0)
专著(0)
科研奖励(0)
会议论文
Site-Specific Immune Cell Activation Detection for Improving Individualized Cancer Immunotherapy
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批准号:10001195
-
项目类别:
-
资助金额:$222.75万
-
财政年份:2020
-
负责人:Benjamin M Larimer
-
依托单位:
Quantitative PET Imaging for Oncologic Immune Response Prediction
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批准号:10226861
-
项目类别:
-
资助金额:$24.83万
-
财政年份:2019
-
负责人:Benjamin M Larimer
-
依托单位:
Quantitative PET Imaging for Oncologic Immunotherapy Response Prediction
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批准号:9453124
-
项目类别:
-
资助金额:$17.93万
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财政年份:2017
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负责人:Benjamin M Larimer
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依托单位:
海外基金