Role of decorin and diffusion MRI in anti-VEGF efficacy for recurrent glioblastoma

核心蛋白聚糖和扩散 MRI 在复发性胶质母细胞瘤抗 VEGF 疗效中的作用

• 批准号: 10419491
• 负责人: TIMOTHY CLOUGHESY
• 金额: $ 62.3万
• 依托单位: UNIVERSITY OF CALIFORNIA LOS ANGELES
• 依托单位国家: 美国
• 财政年份: 2022
• 资助国家: 美国
• 起止时间: 2022-04-01 至 2027-03-31
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10419491
• 关键词: Address; Angiogenic Factor; Biological Markers; Biopsy; Blood; Cell Line; Characteristics; Chemotherapy and/or radiation; Clinical; Clinical Trials; Combined Modality Therapy; Complex; Controlled Clinical Trials; DNA; Data; Development; Diagnosis; Diffuse; Diffusion; Diffusion Magnetic Resonance Imaging; Disease; Doxycycline; Effectiveness; Epidermal Growth Factor Receptor; Exhibits; Extracellular Matrix; Gene Expression; Genetic; Genetic Transcription; Genotype; Glioblastoma; Glycoproteins; Human; Image; Image Guided Biopsy; Immunohistochemistry; In Situ Hybridization; Link; Magnetic Resonance Imaging; Measurable; Measurement; Measures; Mesenchymal; Modeling; Nature; Operative Surgical Procedures; PTEN gene; Patients; Phase; Phenotype; Placebos; Plasma; Play; Pre-Clinical Model; Prior Therapy; Proteins; Randomized; Recurrence; Reproducibility; Role; Series; System; Testing; Tetracyclines; Therapeutic; Treatment Efficacy; Tumor Tissue; United States; Vascular Endothelial Growth Factors; Water; Xenograft Model; Xenograft procedure; bevacizumab; cancer imaging; cohort; comparative efficacy; contrast enhanced; conventional therapy; cost; decorin; economic impact; effective therapy; exhaust; exhaustion; exome; experience; high risk; humanized monoclonal antibodies; imaging biomarker; improved; inhibiting antibody; neoplastic cell; novel; overexpression; patient derived xenograft model; phase II trial; preclinical trial; predictive marker; predictive tools; protein expression; response; response biomarker; risk stratification; single-cell RNA sequencing; standard of care; theories; transcriptome sequencing; tumor

PROJECT SUMMARY/ABSTRACT Glioblastoma (GBM) is a uniformly fatal disease with very few clinical options. Despite modest advancements in surgical procedures, radiation and chemotherapy, median survival from diagnosis is only around 14 months. Upon recurrence, few effective treatment options exist. Bevacizumab, a humanized monoclonal antibody that inhibits VEGF-A, received accelerated FDA approval in May 2009 for use in recurrent GBM and quickly became the standard of care for recurrent GBM in the United States. Almost all patients receive bevacizumab at some point in their treatment. Because bevacizumab plays such an important role in the management of GBM, the development of imaging biomarkers to improve risk stratification and predict patient benefit is highly desired. Such a biomarker would be clinically useful for identifying patients that will benefit from bevacizumab as well as scientifically useful for cohort enrichment in the next phase of combination therapies or exploratory studies aimed at high-risk patients, where conventional therapies like bevacizumab are likely to fail. Extensive preliminary data (>7 trials in >400 patients) suggests diffusion MRI characteristics are a strong, independent predictor of anti-VEGF therapeutic efficacy in recurrent GBM, with patients exhibiting a significant survival benefit if they present with a high apparent diffusion coefficient (ADC) within contrast enhancing tumor. Data also suggests these diffusion MR signatures may result from an elevated expression of decorin (DCN), a glycoprotein with a variety of functions. We hypothesize that the survival advantage and imaging signatures arise from the multifaceted functions of DCN, which include anti-angiogenic characteristics and softening of the extracellular matrix, which we theorize would result in increased effectiveness of anti-VEGF therapies and an increase in ADC. The current study will explore the causal, mechanistic links between DCN expression, diffusion MRI, and anti-VEGF treatment efficacy. First, Aim 1 will involve a deep exploration into the association between diffusion MR phenotypes and DCN expression in human GBM using image-guided biopsies and examining DCN protein expression using immunohistochemistry and gene expression using in-situ hybridization. The relationship between diffusion MRI, DCN expression, and corresponding genotypes using whole exome analysis, genetic subtypes using bulk RNA sequencing, cellular states using single-cell RNA sequencing, and blood plasma levels of circulating DCN will also be performed. Concurrently, Aim 2 will establish the causal, mechanistic links between DCN expression, diffusion MRI measurements, and anti-VEGF treatment in GBM through ca complex, genetically modified patient-derived orthotopic xenograft (PDX) preclinical trial. To accomplish this, a series of patient-derived cell lines will be edited to silence of overexpress DCN within PDX models using a tetracycline-controlled gene expression system. The direct role of DCN expression in changing diffusion MRI measurements and increasing survival following anti-VEGF therapy by turning on or off DCN expression using doxycycline will be determined.

项目总结/摘要 胶质母细胞瘤（GBM）是一种一致致命的疾病，临床选择很少。尽管外科手术取得了一定的进展， 手术、放疗和化疗，从诊断开始的中位生存期只有14个月左右。复发后，很少 存在有效的治疗选择。贝伐珠单抗是一种抑制VEGF-A的人源化单克隆抗体，接受 2009年5月，FDA加速批准用于复发性GBM，并迅速成为复发性GBM的标准治疗。 GBM在美国几乎所有患者在治疗过程中的某个时间点接受贝伐珠单抗。因为贝伐单抗 在GBM的管理中起着如此重要的作用， 分层和预测患者益处是非常需要的。这种生物标志物在临床上可用于识别 患者将受益于贝伐珠单抗以及科学上有用的队列富集在下一阶段 针对高危患者的联合治疗或探索性研究，其中常规治疗如贝伐珠单抗 很可能会失败。 广泛的初步数据（>7项试验，>400例患者）表明，弥散MRI特征是一个强大的，独立的 复发性GBM中抗VEGF治疗疗效的预测因子，如果患者 在对比增强肿瘤内表现为高表观扩散系数（ADC）。数据还表明，这些扩散 MR特征可能是由核心蛋白聚糖（DCN）表达升高引起的，DCN是一种具有多种功能的糖蛋白。我们 假设生存优势和成像特征来自DCN的多方面功能，包括 抗血管生成特性和细胞外基质的软化，我们理论上会导致增加 抗VEGF治疗的有效性和ADC的增加。 目前的研究将探讨DCN表达、弥散MRI和抗VEGF之间的因果关系和机制联系。 治疗效果首先，目标1将涉及深入探索弥散MR表型与 使用图像引导活检检测人GBM中的DCN表达，并使用 免疫组织化学和基因表达使用原位杂交。磁共振弥散成像与DCN的关系 表达，和使用全外显子组分析的相应基因型，使用批量RNA测序的遗传亚型， 使用单细胞RNA测序的细胞状态，以及循环DCN的血浆水平也将进行。 同时，目标2将建立DCN表达，弥散MRI测量， 和通过ca复合物的抗VEGF治疗GBM，遗传修饰的患者来源的原位异种移植物（PDX） 临床前试验为了实现这一点，将编辑一系列患者来源的细胞系以沉默细胞内的过表达DCN。 使用四环素控制的基因表达系统的PDX模型。DCN表达在改变中的直接作用 通过开启或关闭DCN表达，弥散MRI测量和抗VEGF治疗后的生存率增加 使用强力霉素将被确定。