Clinical Correlative Studies of Neuroblastoma

神经母细胞瘤的临床相关研究

• 批准号: 7910335
• 负责人: ROBERT Charles SEEGER
• 金额: $ 39.76万
• 依托单位: CHILDREN'S HOSPITAL OF LOS ANGELES
• 依托单位国家: 美国
• 财政年份: 2009
• 资助国家: 美国
• 起止时间: 2009-08-01 至 2012-07-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/7910335
• 关键词: Accounting; Age; Age-Months; Autologous; Biological Assay; Cells; Children' s Cancer Group; Children' s Oncology Group; Clinical; Correlative Study; DNA; DNA Microarray Chip; Data; Diagnosis; Disease; Disease-Free Survival; Exons; Figs - dietary; Gene Expression; Genes; Genetic Transcription; Genome; Genomics; Germany; Goals; Hematopoietic; Hematopoietic stem cells; Histopathology; Human; Isotretinoin; Loss of Heterozygosity; MYCN gene; Malignant Neoplasms; Molecular; Molecular Profiling; Myeloablative Chemotherapy; Neuroblastoma; Newly Diagnosed; Normal Cell; Oligonucleotide Microarrays; Outcome; Patients; Pediatric Neoplasm; Phase I Clinical Trials; Progression-Free Survivals; Protocols documentation; RNA; Randomized; Research; Research Design; Risk; Risk Factors; Specimen; Staging; Stem cell transplant; Subgroup; Survivors; Test Result; Testing; Therapeutic Studies; Validation; Whole-Body Irradiation; Work; base; chemotherapy; cohort; density; design; effective therapy; follow-up; high risk; improved; therapy development; treatment planning; tumor

DESCRIPTION (provided by applicant): Neuroblastoma is a common childhood tumor, and approximately 40% of patients have aggressive metastatic disease (stage 4) when diagnosed. With improved therapy, survival has increased to 35-40%. Problem: It is not possible at diagnosis to predict which patients will be long-term progression-free survivors (PFS) and which will succumb to disease. Hypothesis: Molecular "signatures" that are derived from microarray analyses of tumor RNA and DNA will define subgroups that have either excellent or poor outcomes. We discovered a 55 gene signature from expression profiles of MYCN gene non-amplified tumors that identifies patients with 79% and 16% PFS. Overall goal: Continue developing therapeutically relevant genomic classifiers for these patients. Specific aims: 1) Determine if RNA expression profiles predict PFS. 2) Determine if DNA signatures based upon loss of heterozygosity and copy number abnormalities predict PFS and if combining DNA and RNA signatures improves accuracy of prediction. Research Design: MYCN amplified and non-amplified tumors will be analyzed as separate groups because they are clinically and biologically distinct. Tumors are available from the Children's Oncology Group and other collaborators with annotation and clinical follow-up. Signatures derived from RNA and DNA microarrays will be used to build validated molecular classifiers that predict the likelihood of PFS. RNA: Initially, expression profiling with Human Exon (HuEx) and standard HG 133 microarrays will be compared to determine if HuEx signatures have similar or better accuracy in predicting PFS. The optimal platform will be used to discover signatures with approximately 337 tumors. Clinically applicable TaqMan(r) Low Density Arrays (TLDA) will be designed for microarray signature genes and tested on the same RNAs to validate their predictive ability. Finally, an independent external set of approximately 210 tumors will be tested with TLDA assays to confirm their validity. DNA: DNA from the same specimens originally used for RNA studies along with paired normal cells will be tested with high density 500K SNP arrays to determine if DNA and DNA + RNA signatures predict PFS. If so, clinically applicable TaqMan(r) DNA assays will be designed from SNP microarray results and tested using the same DNAs. Last, the external validation set of tumors will be tested with TaqMan. DNA assays to confirm their clinical value alone or with TLDA RNA assays. Summary: These are the first and currently only studies aimed at defining subgroups among clinically defined high-risk stage 4 patients. Prediction of long-term PFS using genomic classifiers will facilitate assignment of treatment and development of more effective therapy.

描述（由申请人提供）：神经母细胞瘤是一种常见的儿童肿瘤，大约 40% 的患者在诊断时患有侵袭性转移性疾病（第 4 期）。随着治疗的改进，生存率提高到 35-40%。问题：在诊断时不可能预测哪些患者将成为长期无进展幸存者 (PFS)，哪些患者将死于疾病。假设：源自肿瘤 RNA 和 DNA 微阵列分析的分子“特征”将定义具有良好或不良结果的亚组。我们从 MYCN 基因非扩增肿瘤的表达谱中发现了 55 个基因特征，可识别 PFS 为 79% 和 16% 的患者。总体目标：继续为这些患者开发治疗相关的基因组分类器。具体目标：1) 确定 RNA 表达谱是否可以预测 PFS。 2) 确定基于杂合性丢失和拷贝数异常的 DNA 特征是否可以预测 PFS，以及结合 DNA 和 RNA 特征是否可以提高预测的准确性。研究设计：MYCN 扩增和非扩增肿瘤将作为单独的组进行分析，因为它们在临床和生物学上是不同的。肿瘤可从儿童肿瘤学小组和其他合作者那里获得，并进行注释和临床随访。来自 RNA 和 DNA 微阵列的特征将用于构建经过验证的分子分类器，以预测 PFS 的可能性。 RNA：首先，将比较人类外显子 (HuEx) 和标准 HG 133 微阵列的表达谱，以确定 HuEx 特征在预测 PFS 方面是否具有相似或更好的准确性。最佳平台将用于发现大约 337 个肿瘤的特征。临床适用的 TaqMan(r) 低密度阵列 (TLDA) 将为微阵列特征基因设计，并在相同的 RNA 上进行测试，以验证其预测能力。最后，将使用 TLDA 检测对大约 210 个肿瘤的独立外部组进行测试，以确认其有效性。 DNA：来自最初用于 RNA 研究的相同样本的 DNA 以及配对的正常细胞将使用高密度 500K SNP 阵列进行测试，以确定 DNA 和 DNA + RNA 特征是否可以预测 PFS。如果是这样，临床上适用的 TaqMan(r) DNA 检测将根据 SNP 微阵列结果进行设计，并使用相同的 DNA 进行测试。最后，肿瘤的外部验证集将使用 TaqMan 进行测试。 DNA 检测单独或与 TLDA RNA 检测一起确认其临床价值。摘要：这些是第一项也是目前唯一一项旨在确定临床定义的高危 4 期患者亚组的研究。使用基因组分类器预测长期 PFS 将有助于治疗分配和更有效疗法的开发。