Leveraging Hyperpolarized MRI for Precision Oncology Approaches in Head and Neck Cancer

利用超极化 MRI 实现头颈癌的精准肿瘤学方法

• 批准号: 10530043
• 负责人: James A Bankson
• 金额: $ 67.51万
• 依托单位: UNIVERSITY OF TX MD ANDERSON CAN CTR
• 依托单位国家: 美国
• 财政年份: 2022
• 资助国家: 美国
• 起止时间: 2022-09-01 至 2027-08-31
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10530043
• 关键词: Address; Affect; Algorithms; Animal Model; Biochemical; Biological Assay; Biology; Biopsy; Cancer Etiology; Carbon; Cessation of life; Characteristics; Chemicals; Cisplatin; Clinical Trials; Coenzymes; DNA; DNA Damage; Data; Data Analyses; Development; Dose; Effectiveness; Evaluation; Exposure to; Failure; Feedback; Genotoxic Stress; Glycolysis; Goals; Grant; Head and Neck Cancer; Head and Neck Squamous Cell Carcinoma; Head and neck structure; Heterogeneity; Human; Human Papillomavirus; Image; In Vitro; Individual; Knowledge; Lactate Dehydrogenase; Link; Magnetic Resonance Imaging; Measurable; Measurement; Measures; Metabolic; Metabolic Pathway; Mission; Modeling; Mus; Mutagens; NADP; Oxidation-Reduction; Patient Recruitments; Patients; Pharmaceutical Preparations; Pre-Clinical Model; Public Health; Publishing; Pyruvate; Radiation therapy; Reaction; Recycling; Regimen; Research; Resistance; Resistance development; Resolution; Selection Criteria; Sensitivity and Specificity; Series; Shunt Device; Solid Neoplasm; Suggestion; Testing; Therapeutic; Time; Toxic effect; Translational Research; Treatment Effectiveness; Treatment Failure; Treatment Protocols; Tumor Burden; Tumor Volume; United States; United States National Institutes of Health; Work; Xenograft procedure; base; cell injury; cell killing; chemotherapeutic agent; chemotherapy; clinical application; clinically relevant; design; effective therapy; first-in-human; imaging biomarker; imaging modality; in vivo; individual patient; innovation; insight; interest; metabolic imaging; metabolic phenotype; metabolomics; minimally invasive; neoplastic cell; non-invasive imaging; novel; oral lesion; patient derived xenograft model; personalized management; precision oncology; preclinical trial; predicting response; predictive modeling; prospective; quantitative imaging; randomized trial; response; standard of care; success; targeted agent; transcriptomics; treatment optimization; treatment response; tumor; tumor growth; tumor metabolism

PROJECT SUMMARY/ABSTRACT Head and neck squamous cell carcinoma (HNSCC) remains a leading cause of cancer deaths worldwide. Genotoxic agents, including radiation therapy (RT) and cisplatin (CDDP), are treatments that damage cellular DNA. RT and CDDP are the current standard of care in multiple solid tumors, including HNSCC. CDDP is the most commonly used chemotherapeutic agent in HNSCC proving superior to novel targeted agents in recent large randomized trials. Despite this, high rates of treatment failure persist in patients who develop resistance following this toxic chemotherapy. Treatment failure is uniformly fatal. However, no robust predictors of acquired cisplatin resistance or tumor response exist. Given this critical unmet need, we have focused our efforts on the assessment of tumor response using minimally invasive quantitative imaging (hyperpolarized magnetic resonance imaging; HP-MRI) while patients are undergoing therapy. We showed that CDDP and other genotoxic agents trigger measurable fluctuations in tumor cell metabolism detectable through HP-MRI with [1-13C]-pyruvate in real time (confirmed by conventional biochemical assays). Genotoxic stress suppresses the apparent rate of pyruvate conversion into lactate (kPL) via lactate dehydrogenase (LDH) in a manner that correlates with anti- tumor effectiveness. We therefore hypothesize that changes in kPL provide unique insight into metabolic changes induced by cisplatin that can be used to optimize response to therapy in HNSCC. In Aim 1, we will characterize baseline HP-MRI parameters such as kPL across the spectrum of HNSCC subtypes and validate the relationship between CDDP and associated shifts in carbon flux. We will also identify metabolomic differences in HNSCC models that affect baseline values of metabolic imaging biomarkers and modulate apparent changes induced by cisplatin. In Aim 2, we will integrate the dose-response data from Aim 1 to develop a predictive model of response to CDDP based on metabolic imaging parameters. We will use a simple algorithm to adjust therapeutic dose based on HP-MRI data in animal models of HNSCC to maximize tumor growth delay, and test whether thresholds suggestive of strong response can be used to select the more effective treatment regimen when multiple regimens are tested in parallel. In Aim 3, we will conduct a first-in- human evaluation of changes in HP-MRI to detect shifts in carbon flux following CDDP in HNSCC patients. We will correlate changes in metabolic imaging parameters with the baseline metabolic phenotype of tumors as determined from metabolomic analysis and direct measurements of tumor LDH. Successful completion of this study will establish HP-MRI as a non-invasive imaging modality able to predict response to treatment, which will be a noteworthy first step towards a precision oncology approach that we have been seeking for nearly half a century. Thus, the proposed research is relevant to the part of the NIH’s mission that pertains to developing and applying fundamental knowledge that will help to reduce the burdens of human illness and addresses directly the recently published “Notice of Special Interest: Precision Imaging of Oral Lesions” (NOT-DE-21-010).

项目概要/摘要 头颈鳞状细胞癌（HNSCC）仍然是全球癌症死亡的主要原因。 基因毒性药物，包括放射治疗 (RT) 和顺铂 (CDDP)，是损害细胞的治疗方法 DNA。RT 和 CDDP 是多种实体瘤的当前标准治疗方法，其中 CDDP 是其中的标准。 近年来，HNSCC 最常用的化疗药物被证明优于新型靶向药物 尽管如此，出现耐药性的患者治疗失败率仍然很高。 这种有毒化疗后的治疗失败通常是致命的。 鉴于这一未满足的关键需求，我们已经集中精力。 使用微创定量成像（超极化磁）评估肿瘤反应 我们在患者接受治疗时显示了 CDDP 和其他遗传毒性。 药物触发肿瘤细胞代谢的可测量波动，可通过 [1-13C]-丙酮酸 HP-MRI 检测到 实时（通过常规生化测定证实）基因毒性应激抑制了表观速率。 丙酮酸通过乳酸脱氢酶 (LDH) 转化为乳酸 (kPL)，其方式与抗- 因此，我们重点关注 kPL 的变化为代谢提供独特的见解。 顺铂引起的变化可用于优化 HNSCC 的治疗反应。 在目标 1 中，我们将表征 HNSCC 谱系中的基线 HP-MRI 参数，例如 kPL 我们还将确定 CDDP 与相关碳通量变化之间的关系。 HNSCC 模型中影响代谢成像生物标志物基线值的代谢组学差异 调节顺铂引起的明显变化 在目标 2 中，我们将整合目标 1 的剂量反应数据。 为了开发基于代谢成像参数的 CDDP 反应预测模型，我们将使用 根据 HNSCC 动物模型中的 HP-MRI 数据调整治疗剂量的简单算法，以最大限度地提高治疗剂量 肿瘤生长延迟，并测试是否可以使用暗示强反应的阈值来选择更多 在目标 3 中，我们将进行先入为主的治疗方案。 我们对 HP-MRI 变化进行人类评估，以检测 HNSCC 患者 CDDP 后碳通量的变化。 将代谢成像参数的变化与肿瘤的基线代谢表型相关联： 通过代谢组学分析和直接测量肿瘤 LDH 确定这一结果成功完成。 研究将 HP-MRI 确立为一种能够预测治疗反应的非侵入性成像方式， 这将是迈向我们一直在寻求的精准肿瘤学方法的值得注意的第一步 因此，拟议的研究与 NIH 的使命中涉及发展的部分相关。 并应用有助于减轻人类疾病负担并直接解决问题的基础知识 最近发布的“特别关注通知：口腔病变的精确成像”(NOT-DE-21-010)。