Artificial Intelligence Boosted Evolution and Detection of Genetically Encoded Reporters for In Vivo Imaging

人工智能促进体内成像基因编码报告基因的进化和检测

• 批准号: 10180072
• 负责人: CHRISTIAN T FARRAR
• 金额: $ 68.05万
• 依托单位: MASSACHUSETTS GENERAL HOSPITAL
• 依托单位国家: 美国
• 财政年份: 2021
• 资助国家: 美国
• 起止时间: 2021-04-01 至 2024-12-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/10180072
• 关键词: Algorithms; Amides; Artificial Intelligence; Biological Response Modifier Therapy; Cardiac; Cells; Chemicals; Clinic; Clinical; Clinical assessments; Collaborations; Detection; Development; Diagnosis; Discrimination; Disease; Drug Kinetics; Evolution; Fingerprint; Gene Transfer; Genes; Genetic Programming; Glioblastoma; Goals; Histologic; Image; Infection; Longitudinal Studies; Lysine; Machine Learning; Magnetic Resonance; Magnetic Resonance Imaging; Measurement; Medical Imaging; Metabolic; Methods; Modeling; Monitor; Mus; Oncolytic; Oncolytic viruses; Pathology; Performance; Physiologic pulse; Problem Solving; Protein Engineering; Proteins; Protons; Reporter; Reporter Genes; Resistance; Resolution; Schedule; Sensitivity and Specificity; Signal Transduction; Specificity; Technology; Testing; Therapeutic; Therapeutic Agents; Time; Tissues; Tumor Cell Line; Viral; Virus Diseases; Virus Replication; Water; Work; base; cancer imaging; clinical translation; deep learning; deep neural network; detection method; detection sensitivity; gene therapy; imaging modality; improved; in vivo imaging; neoplastic cell; neural network architecture; novel; oncolytic virotherapy; pre-clinical; radio frequency; rapid technique; response; therapeutic gene; tool; trafficking; transgene expression; tumor; viral gene delivery

PROJECT SUMMARY Magnetic resonance (MR) reporter genes have the potential to monitor transgene expression non-invasively in real time at high resolution. These genes can be applied to interrogate the efficacy of gene therapy, to monitor viral therapeutics and viral gene delivery, to assess cellular differentiation, cell trafficking, and specific metabolic activity, and also assess changes in the microenvironment. Efforts toward the development of MR reporter genes have been made for over a decade, but, despite these efforts, the field is still in its early developmental stage. This reflects the fact that there are numerous complications, caused by the low sensitivity of detection, the need for substrates with their associated undesirable pharmacokinetics, and/or the difficult and, in some cases, delayed interpretation of signal changes. We have previously demonstrated that many of these challenges can be overcome with the use of a lysine rich protein (LRP) reporter gene, that is detectable by chemical exchange saturation transfer (CEST) MRI. However, to mature the CEST reporter gene technology and bring it towards clinical translation, its sensitivity and specificity need to be improved. In particular, the LRP reporter gene specificity is limited by the fact that the lysine amide exchangeable protons of LRP have the same chemical shift as amide protons from endogenous proteins. It is therefore difficult to distinguish the reporter CEST contrast from the background CEST contrast, both of which may be changing with time. The specificity is further limited by the sensitivity of the CEST contrast to intracellular pH where the qualitative CEST contrast cannot distinguish between exchange rate and concentration effects. Finally, a decrease in cytosolic pH, observed in many disease pathologies, reduces the amide proton exchange rate and hence the CEST reporter sensitivity. We therefore propose to develop improved MRI reporter genes and quantitative MRI detection methods that will facilitate the clinical translation of these methods for imaging biological therapeutics, such as oncolytic virotherapy. We hypothesize that CEST reporter genes with improved sensitivity and specificity along with improved quantitative CEST methods will enable viral infection and replication to be monitored longitudinally throughout OV tumor therapy. To test this hypothesis and establish the clinical potential of MRI reporter genes we will capitalize on two transformative technologies developed in our labs; (Aim 1) an artificial intelligence based genetic programming algorithm will be used for optimizing the sensitivity and specificity of the CEST reporter gene and (Aim 2) a CEST magnetic resonance fingerprinting (MRF) method will be used for the rapid quantification of both the reporter protein concentration and chemical exchange rate. (Aim 3) These methods will be validated for imaging oncolytic viral infection and replication in mouse glioblastoma tumor models.

项目总结 磁共振(MR)报告基因有可能无创性地监测转基因的表达 实时、高分辨率。这些基因可以用来询问基因治疗的疗效，监测 病毒疗法和病毒基因传递，以评估细胞分化、细胞转运和特异性 代谢活动，并评估微环境的变化。为发展MR所做的努力 记者基因的研究已经进行了十多年，但尽管有这些努力，这一领域仍处于初级阶段 发展阶段。这反映了这样一个事实，即有许多并发症是由低谷引起的 检测的敏感性，对底物的需求及其相关的不良药代动力学，和/或 对信号变化的解释很困难，在某些情况下还会延迟。 我们以前已经证明，这些挑战中的许多都可以通过使用富含赖氨酸的方法来克服 蛋白(LRP)报告基因，可通过化学交换饱和转移(CEST)MRI检测到。 然而，要使CEST报告基因技术成熟并将其引入临床翻译，其敏感性 特异性有待提高。特别是，LRP报告基因的特异性受到以下事实的限制 LRP的赖氨酰胺可交换质子与酰胺质子具有相同的化学位移 内源性蛋白质。因此，很难将记者CEST的对比与背景区分开来 CEST对比，这两者都可能随着时间的推移而变化。其特异性进一步受限于其敏感性 CEST与细胞内pH的对比，其中定性的CEST对比不能区分 汇率效应和集中度效应。最后，在许多疾病中观察到的胞浆pH值下降。 病理，降低了酰胺质子交换率，从而降低了CEST报告程序的敏感性。 因此，我们建议开发改进的MRI报告基因和定量MRI检测方法 将促进这些成像生物治疗方法的临床翻译，如溶瘤 病毒疗法。我们假设CEST报告基因具有更高的敏感性和特异性，以及 改进的CEST定量方法将使对病毒感染和复制进行纵向监测 在整个卵巢肿瘤治疗中。为了验证这一假设并建立磁共振报告基因的临床潜力 我们将利用我们实验室开发的两项变革性技术；(目标1)人工智能 将基于遗传规划的算法用于优化CEST的灵敏度和特异度 报告基因和(AIM 2)CEST磁共振指纹图谱(MRF)方法将用于快速 定量测定报告蛋白浓度和化学交换率。(目标3)这些方法 将在小鼠胶质母细胞瘤肿瘤模型中验证溶瘤病毒感染和复制的成像。