MDACC-PREDICT

MDACC-预测

基本信息

批准号：
10266195
负责人：
Scott Kopetz
金额：
$ 67.05万
依托单位：
UNIVERSITY OF TX MD ANDERSON CAN CTR
依托单位国家：
美国
项目类别：
财政年份：
2020
资助国家：
美国
起止时间：
2020-09-01 至 2023-08-31
项目状态：
已结题

来源：
https://reporter.nih.gov/project-details/10266195
关键词：
Acetates Affect Algorithms Biological Biological Assay Biological Factors Biological Markers Biological Process Biopsy Cancer Etiology Cancer Model Cancer Patient Cessation of life Cetuximab Characteristics Chronobiology Clinical Colorectal Cancer Community Clinical Oncology Program Coupled DNA Data Data Analyses Development Diet Epidermal Growth Factor Receptor Gene Expression Profile Genomic approach Glutaminase Glutamine Histologic Human Image Imaging Device Individual Knowledge Lead Ligands Location MAP Kinase Gene Malignant Neoplasms Measures Mediating Metabolism Methods Molecular Molecular Genetics Monoclonal Antibodies Monoclonal Antibody Therapy Mus Nature Oncology Outcome Patients Phase I/II Clinical Trial Phenotype Positron-Emission Tomography Protocols documentation RNA Radiochemistry Receptor Inhibition Refractory Regimen Reproducibility Research Resistance Resources Standardization TP53 gene Technology Therapeutic Tracer Universities University of Texas M D Anderson Cancer Center Validation Vision attenuation base circadian clinical imaging co-clinical trial colon cancer patients experience genomic data genomic predictors imaging modality improved inhibitor/antagonist irinotecan mouse model neutralizing monoclonal antibodies novel panitumumab patient derived xenograft model personalized cancer therapy pre-clinical precision oncology preclinical imaging preclinical study predicting response quantitative imaging reconstruction response subcutaneous targeted treatment tool treatment optimization tumor

项目摘要

Project Summary This application proposes a new U24 Oncology Co-Clinical Imaging Resource entitled VU-PREDICT (Vanderbilt University-PET imaging Resource to Enhance Delivery of Individualized Cancer Therapeutics). Precision cancer medicine, which seeks to exploit unique cellular, molecular and genetic characteristics of individual tumors to optimize treatment, remains a critically unmet need. Despite advances in biomarker technologies that yield high-quality cellular and genomic data, critical gaps remain to consistently match patients with cancer and ideal therapies. While `predictive' genomic assays based on RNA and DNA are now commonplace, current methods largely ignore tumor phenotypes differentiable by quantitative imaging. The overarching vision for VU-PREDICT is a suite of quantitative imaging tools that facilitate the discovery of novel, predictive imaging-derived gene expression signatures; such signatures can be deployed by the greater oncology community to improve the personalization of cancer treatment. The linchpin of VU-PREDICT will be positron emission tomography (PET) imaging. The sensitive and quantitative nature of PET, coupled with the ability to produce biologically active PET tracers, renders PET uniquely capable of both detecting tumors and profiling their specific features. Complementary to genomic approaches, PET imaging provides a quantitative, functional measure of tumor phenotype, and when coupled biopsy approaches, can provide a significantly greater breadth of biological characterization. VU-PREDICT centers on a parallel co-clinical trial of patients with advanced colorectal cancer (CRC) and human-in-mouse PDX (patient-derived xenograft) models. CRC is a leading cause of cancer-related deaths worldwide. Epidermal growth factor receptor (EGFR) neutralizing monoclonal antibodies (mAbs; cetuximab, panitumumab) are approved for treatment of advanced wild-type (WT) RAS CRC. However, durable responses to anti-EGFR mAbs occur in only 12–17% of patients. VU-PREDICT will capitalize upon a Phase I/II clinical trial opening at Vanderbilt combining a glutaminase (GLS1) inhibitor (CB-839, Calithera), EGFR mAb therapy (panitumumab) and irinotecan in patients with advanced and refractory WT RAS CRC. It is anticipated that combining CB-839 with EGFR mAb therapy will resensitize refractory CRC patients with Gln- avid tumors to EGFR blockade. VU-PREDICT will allow our development of quantitative PET imaging measures within this trial and in related preclinical studies that may identify patients likely to respond to combined GLS1/EGFR inhibition. We have four Specific Aims: (1) Optimize quantitative preclinical PET imaging protocols for Gln metabolism; Implement quantitative 18F-FSPG PET (2), 11C-Acetate PET (3), and dual-tracer 11C-Acetate/18F-FSPG PET (4) to discover predictive, imaging-derived gene expression signatures.

项目摘要该应用程序提出了一种新的U24肿瘤学共插型成像资源，名为VU Predict （范德比尔特大学宠物成像资源，以增强个性化癌症治疗剂的传递）。精密癌症医学，试图利用独特的细胞，分子和遗传特征单个肿瘤以优化治疗，仍然是一种急需的需求。尽管生物标志物的进步产生高质量的细胞和基因组数据的技术，临界差距保持一致匹配癌症和理想疗法的患者。而基于RNA和DNA的“预测”基因组测定现在是普通的当前方法在很大程度上忽略了通过定量成像可区分的肿瘤表型。这 VU预测的总体视野是一系列定量成像工具，可促进新颖的发现，预测成像衍生的基因表达特征；此类签名可以由更大的签名部署肿瘤学界以改善癌症治疗的个性化。 VU预测的Linchpin将是正电子发射断层扫描（PET）成像。 PET的敏感和定量性质，与能够产生具有生物活性的宠物示踪剂的能力，使宠物独特地能够检测肿瘤和分析他们的特定功能。互补的基因组方法，PET成像提供了定量的，肿瘤表型的功能测量以及耦合活检方法时，可以显着提供生物学特征的更广度。 VU预测的中心以晚期结直肠癌（CRC）患者的平行临床试验为中心和鼠类PDX（患者衍生的Xenographic）模型。 CRC是与癌症有关的主要原因全球死亡。表皮生长因子受体（EGFR）中和单克隆抗体（mAbs; 西妥昔单抗，panitumumab）被批准用于治疗晚期野生型（WT）RAS CRC。然而，对抗EGFR mAb的持久反应仅在12-17％的患者中发生。 VU预测将大写 I/II期临床试验在范德比尔特（Vanderbilt EGFR MAB治疗（Panitumumumab）和Irinotecan患有晚期和难治性WT RAS CRC的患者。这是预计将CB-839与EGFR MAB治疗相结合将使难治性CRC患者具有GLN- 狂热的肿瘤到EGFR封锁。 VU预测将允许我们开发定量宠物成像该试验中的措施以及相关的临床前研究，可能发现可能对患者做出反应的患者 GLS1/EGFR抑制联合。我们有四个特定的目标：（1）优化定量临床前宠物 GLN代谢的成像方案；实施定量的18F-FSPG PET（2），11c-乙酸PET（3）和双追踪器11C-乙酸/18F-FSPG PET（4）发现预测性成像衍生的基因表达特征。