Predictive Markers in Metastatic Renal Cancer

转移性肾癌的预测标志物

• 批准号: 8269570
• 负责人: ERIC J SMALL
• 金额: $ 51.17万
• 依托单位: UNIVERSITY OF CALIFORNIA, SAN FRANCISCO
• 依托单位国家: 美国
• 财政年份: 2008
• 资助国家: 美国
• 起止时间: 2008-07-22 至 2014-05-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/8269570
• 关键词: Address; American Society of Clinical Oncology; Angiogenesis Inhibitors; Angiogenic Factor; Angiopoietin-2; Antibodies; Binding; Biological; Biological Markers; Biology; Cancer and Leukemia Group B; Chromosome abnormality; Clinical; Development; Disease; Enrollment; Epigenetic Process; Family; Fibroblast Growth Factor 2; Future; Genes; Genetic; Genetic Transcription; Genomics; Goals; Health; Immunotherapy; Individual; Interferon-alpha; Interferons; Kidney; Link; Maintenance Therapy; Malignant - descriptor; Malignant Neoplasms; Malignant neoplasm of urinary bladder; Metastatic Renal Cell Cancer; Methods; Methylation; Modality; Modeling; Molecular; Outcome; PGF gene; Paraffin Embedding; Pathologic; Pathway interactions; Patients; Pattern; Phase III Clinical Trials; Phenotype; Phosphotransferases; Plasma; Predictive Value; Progress Review Group; Progression-Free Survivals; Proteomics; Radiation therapy; Reaction Time; Regimen; Renal Cell Carcinoma; Renal carcinoma; Research; Resistance; Resources; Risk; Risk Factors; Sampling; Specimen; Stratification; Testing; Therapeutic; Time; Tissue Microarray; Tissues; Urine; VHL gene; VHL mutation; Vascular Endothelial Growth Factor A; Vascular Endothelial Growth Factors; angiogenesis; arm; base; bevacizumab; candidate marker; chemotherapy; comparative genomic hybridization; design; effective therapy; follow-up; insight; knowledge base; molecular marker; neoplastic cell; outcome forecast; overexpression; predictive modeling; prognostic; protein expression; receptor; response; standard of care; trend; tumor

DESCRIPTION (provided by applicant): Metastatic renal cell carcinoma (RCC) is a dismal disease, with nearly uniform resistance to radiotherapy, chemotherapy and immunotherapy. Recently, the availability of molecularly-targeted therapy against vascular endothelial growth factor (VEGF) has dramatically altered the therapeutic landscape of RCC. One such approach involves the VEGF-binding antibody, bevacizumab. The CALGB has completed an Intergroup Phase III trial of interferon alpha (IFNA) plus bevacizumab versus IFNA alone in 732 patients with metastatic renal cell carcinoma (CALGB 90206), representing one of the largest phase III trials conducted to date in RCC. Baseline paraffin-embedded tissue was collected on 591 of these patients in addition to plasma and urine samples obtained at baseline and after 6 weeks of therapy. This is a unique opportunity for analysis of this tissue to provide insight into the biology of RCC, the mechanisms of response to bevacizumab-based therapy, and to develop a new predictive model for response using extensive biomarker analyses. Our central hypothesis is that genomic alterations and expression changes in genes involved in angiogenesis and other receptor kinase pathways are predictive of outcome in patients with renal cell carcinoma treated with interferon 1 bevacizumab. We will test whether overall survival is associated with: 1) von Hippel Lindau gene mutation and methylation, 2) patterns of genomic alterations by array-CGH, 3) expression of protein targets using a new method of automated quantitative analysis of tissue microarrays (AQUA), and 4) plasma and urine biomarker levels at baseline and 6 weeks into therapy. We will then develop a new predictive multivariate model for risk stratification of patients with metastatic renal cell carcinoma, using clinical, pathologic, and molecular markers. PUBLIC HEALTH RELEVANCE: Identification of molecular alterations associated with outcome after bevacizumab- based therapy will have broad implications for treatment of RCC and other cancers. This agent and the anti-angiogenic approach in general are now widely recognized as an effective treatment modality in a number of tumor types. Insight into the molecular basis for baseline response to bevacizumab will provide a knowledge base upon which to rationally select patients for such therapies in the future. The NCI Progress Review Group for Kidney and Bladder Cancer (2001) identified 13 priorities as research goals. The first two priorities were 1) Understand the biological mechanism underlying the risk factors for kidney and bladder cancer phenotypes, and 2) Identify global genetic, epigenetic, RNA expression, and proteomic alterations in tumors and place them in specific biological pathways that are essential to development, progression, response to therapy, and maintenance of subtypes of bladder and kidney cancers; This proposal directly addresses these two top priorities.

描述（申请人提供）：转移性肾细胞癌（RCC）是一种令人沮丧的疾病，对放疗、化疗和免疫疗法几乎具有一致的抗性。最近，针对血管内皮生长因子（VEGF）的分子靶向治疗的可用性已经极大地改变了RCC的治疗前景。一种这样的方法涉及VEGF结合抗体贝伐单抗。CALGB已经完成了一项在732名转移性肾细胞癌患者中进行的干扰素α（IFNA）加贝伐单抗与IFNA单独治疗的组间III期试验（CALGB 90206），这是迄今为止在RCC中进行的最大的III期试验之一。除了在基线和治疗6周后获得的血浆和尿液样本外，还收集了其中591例患者的基线石蜡包埋组织。这是分析这种组织的独特机会，可以深入了解RCC的生物学，对基于贝伐珠单抗的治疗的反应机制，并使用广泛的生物标志物分析开发新的反应预测模型。我们的中心假设是，基因组的改变和表达的变化，参与血管生成和其他受体激酶途径的肾细胞癌患者干扰素1贝伐单抗治疗的结果是预测。我们将测试总生存率是否与以下因素相关：1）von Hippel Lindau基因突变和甲基化，2）阵列CGH的基因组改变模式，3）使用组织微阵列自动定量分析（AQUA）新方法的蛋白质靶点表达，以及4）基线和治疗6周时的血浆和尿液生物标志物水平。然后，我们将开发一个新的预测性多变量模型，用于转移性肾细胞癌患者的风险分层，使用临床，病理和分子标志物。公共卫生关系：鉴定与基于贝伐单抗的治疗后的结果相关的分子改变将对RCC和其他癌症的治疗具有广泛的意义。这种药物和抗血管生成方法现在被广泛认为是许多肿瘤类型的有效治疗方式。深入了解贝伐单抗基线应答的分子基础将为将来合理选择此类治疗的患者提供知识基础。NCI肾癌和膀胱癌进展审查小组（2001年）确定了13个优先研究目标。前两个优先事项是1）了解肾癌和膀胱癌表型风险因素的生物学机制，以及2）识别肿瘤中的整体遗传，表观遗传，RNA表达和蛋白质组学改变，并将其置于对膀胱癌和肾癌亚型的发展，进展，治疗反应和维持至关重要的特定生物学途径中;这项建议直接涉及这两个最高优先事项。

项目成果

CD70 expression patterns in renal cell carcinoma.

• DOI: 10.1016/j.humpath.2011.10.014
• 发表时间: 2012-09
• 期刊: HUMAN PATHOLOGY
• 影响因子: 3.3
• 作者: Jilaveanu, Lucia B.;Sznol, Joshua;Aziz, Saadia A.;Duchen, Dylan;Kluger, Harriet M.;Camp, Robert L.
• 通讯作者: Camp, Robert L.

The importance of identifying and validating prognostic factors in oncology.

• DOI: 10.1053/j.seminoncol.2010.04.001
• 发表时间: 2010-04
• 期刊: Seminars in oncology
• 影响因子: 4
• 作者: Halabi S;Owzar K
• 通讯作者: Owzar K