Using microfluidics to realize patient-specific anti-cancer immunotherapies
利用微流控实现患者特异性抗癌免疫疗法
基本信息
- 批准号:10702214
- 负责人:
- 金额:$ 108.08万
- 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:2023-09-19 至 2028-08-31
- 项目状态:未结题
- 来源:
- 关键词:AddressAffinityAgonistAllelesAmino AcidsAntigen-Presenting CellsBindingBiomechanicsCancerousCell surfaceCellsClone CellsComplexDangerousnessDataDiseaseEncapsulatedEngineeringHourImmune responseImmunologic SurveillanceImmunotherapyIn VitroMalignant NeoplasmsMethodsMicrofluidicsPatientsPeptide ReceptorPeptide VaccinesPeptidesPhysiologicalPlayProteinsQualifyingRecombinantsRoleSensitivity and SpecificitySortingSurfaceT cell responseT-Cell ActivationT-Cell ReceptorT-LymphocyteTCR ActivationTechniquesTechnologyTestingTrainingTransfusionTumor AntigensWorkantigen-specific T cellscancer immunotherapycancer therapycostcytotoxicengineered T cellsfightingimprovedin vivoinventionmicrofluidic technologyneoantigensnew technologynext generation sequencingnovelreceptor bindingscreeningside effecttool
项目摘要
Project Summary
T cells play a central role in the immune response, detecting antigenic peptides cradled within MHC molecules
(pMHCs) displayed on the surface of diseased cells via specific interactions with cell-surface T cell receptors
(TCRs). This recognition triggers downstream T cell activation and cytotoxic killing. In vivo, T cells are
exquisitely sensitive and specific, able to be activated by a single antigenic peptide displayed by a diseased
cell. Immunotherapies attempt to harness this sensitivity and specificity to eliminate cancerous cells by either
transfusing patients with T cells engineered to display TCRs specific for tumor-associated antigens
(neoantigens) or injecting peptide ‘vaccines’ to stimulate expansion of neoantigen-specific T cell clones.
Predicting which neoantigen/TCR combinations will activate a potent T cell response in a patient remains a
formidable challenge. There are a vast number of potential pMHC/TCR complexes: MHC molecules are
encoded by 23,000 HLA alleles, each MHC displays a ~9 amino acid peptide (209 possibilities), and each
patient can express >1020 possible TCRs. While many techniques leverage next-generation sequencing to
screen millions of pMHC/TCR combinations for high-affinity binders, these screens can test only a small
fraction of possible combinations.
Moreover, the strength of pMHC/TCR binding does not predict activation:
many high-affinity peptides do not activate T cells, and many potent agonists bind with only moderate affinities.
T cells generate pN to nN forces on pMHC/TCR complexes as they crawl over antigen-presenting cells, and
emerging evidence has established that these biomechanical forces are essential for sensitive and specific
TCR-pMHC recognition: pMHC/TCR complexes that drive potent activation form ‘catch’ bonds that strengthen
under force, while those that do not form ‘slip’ bonds more likely to break. Thus, developing improved
immunotherapies requires new technologies capable of testing large numbers of candidate pMHC/TCR
interactions for their ability to form catch bonds and activate T cells under physiological forces.
My lab is uniquely qualified to address this critical need. In prior work, we developed a microfluidic platform that
enables recombinant cell-free expression, purification, and quantitative in vitro characterization of >1,500
proteins in hours and at low cost. Here, we will apply this powerful technology to systematically investigate
which pMHC/TCR combinations form ‘catch’ bonds that predict activation (Platform 1) and which neoantigens
are efficiently displayed by 1000s of different MHC sequences encoded by variable HLA alleles (Platform 2).
To further test candidate pMHC/TCR combinations in their cellular context, we will apply a novel droplet-based
technology we invented to co-encapsulate 10s of millions of T cell/APC pairs and sort them based on activation
(Platform 3).
项目摘要
T细胞在免疫反应中起着中心作用,检测MHC分子中的抗原肽。
(PMHC)通过与细胞表面T细胞受体的特异性相互作用显示在疾病细胞表面
(TCR)。这种识别触发下游T细胞激活和细胞毒杀伤。在体内,T细胞
具有极高的敏感性和特异性,能够被病人所展示的单一抗原肽激活。
手机。免疫疗法试图利用这种敏感性和特异性来消除癌细胞,方法是
给患者输注经改造的显示肿瘤相关抗原TCRs的T细胞
(新抗原)或注射多肽“疫苗”,以刺激新抗原特异性T细胞克隆的扩张。
预测哪些新抗原/TCR组合将在患者中激活强大的T细胞反应仍然是一个
这是一项艰巨的挑战。有大量潜在的pMHC/TCR复合体:MHC分子是
由23,000个HLA等位基因编码,每个MHC显示一个~9个氨基酸多肽(209个可能性),每个MHC
患者可以表达1020种可能的TCR。虽然许多技术利用下一代测序来
筛选数以百万计的pMHC/TCR组合用于高亲和力粘合剂,这些筛选只能测试一小部分
可能组合的分数。
此外,pMHC/TCR结合的强度不能预测激活:
许多高亲和力的多肽不能激活T细胞,许多有效的激动剂只与中等亲和力结合。
当T细胞爬过抗原提呈细胞时,它们会在pMHC/TCR复合体上产生PN到NN的作用力,并且
新出现的证据表明,这些生物力学力量对于敏感和特定的
TCR-pMHC识别:驱动有效激活的pMHC/TCR复合体形成增强的Catch键
在力量的作用下,那些没有形成“滑脱”的纽带更有可能破裂。因此,开发改进了
免疫疗法需要能够检测大量候选pMHC/TCR的新技术
相互作用,以形成捕获键并在生理力量下激活T细胞。
我的实验室是唯一有资格满足这一关键需求的实验室。在之前的工作中,我们开发了一种微流控平台
使>;1,500的重组无细胞表达、纯化和体外定量鉴定成为可能
蛋白质在几个小时内,以低成本。在这里,我们将应用这项强大的技术来系统地研究
哪些pMHC/TCR结合形成了预测激活(平台1)和哪些新抗原的‘Catch’键
通过由可变的HLA等位基因(平台2)编码的1000个不同的MHC序列有效地显示。
为了进一步测试候选pMHC/TCR组合在细胞环境中的作用,我们将应用一种新的基于液滴的
我们发明了一种技术,用于共同封装数千万个T细胞/APC对,并根据激活情况对它们进行分类
(平台3)。
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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Polly Morrell Fordyce其他文献
Polly Morrell Fordyce的其他文献
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{{ truncateString('Polly Morrell Fordyce', 18)}}的其他基金
Using Microfluidic Affinity Analysis to Probe Transcriptional Regulation
使用微流控亲和力分析来探测转录调控
- 批准号:
8539046 - 财政年份:2012
- 资助金额:
$ 108.08万 - 项目类别:
Using Microfluidic Affinity Analysis to Probe Transcriptional Regulation
使用微流控亲和力分析来探测转录调控
- 批准号:
8374227 - 财政年份:2012
- 资助金额:
$ 108.08万 - 项目类别:
Using Microfluidic Affinity Analysis to Probe Transcriptional Regulation
使用微流控亲和力分析来探测转录调控
- 批准号:
9196360 - 财政年份:2012
- 资助金额:
$ 108.08万 - 项目类别:
Using Microfluidic Affinity Analysis to Probe Transcriptional Regulation
使用微流控亲和力分析来探测转录调控
- 批准号:
9021659 - 财政年份:2012
- 资助金额:
$ 108.08万 - 项目类别:
Using Microfluidic Affinity Analysis to Probe Transcriptional Regulation
使用微流控亲和力分析来探测转录调控
- 批准号:
9011088 - 财政年份:2012
- 资助金额:
$ 108.08万 - 项目类别:
Quantitative, High-throughput Mechanistic Enzymology
定量、高通量机械酶学
- 批准号:
10013223 - 财政年份:2002
- 资助金额:
$ 108.08万 - 项目类别:
Quantitative, High-throughput Mechanistic Enzymology
定量、高通量机械酶学
- 批准号:
10254238 - 财政年份:2002
- 资助金额:
$ 108.08万 - 项目类别:
Quantitative, High-throughput Mechanistic Enzymology
定量、高通量机械酶学
- 批准号:
10477007 - 财政年份:2002
- 资助金额:
$ 108.08万 - 项目类别:
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