Translation of Predictive Cancer Biomarkers into Clinical Practice

将预测性癌症生物标志物转化为临床实践

• 批准号: 7943955
• 负责人: STEPHEN X SKAPEK
• 金额: $ 130.89万
• 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: 2009-09-29 至 2012-08-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/7943955
• 关键词: Accounting; Adult; Age; Alveolar; Alveolar Rhabdomyosarcoma; Anatomic Sites; Archives; Bioinformatics; Biological Assay; Biological Markers; Cancer Therapy Evaluation Program; Cells; Child; Child Care; Childhood; Childhood Leukemia; Childhood Rhabdomyosarcoma; Children' s Oncology Group; Chimeric Proteins; Chromosomes, Human, Pair 2; Classification; Clinical; Clinical Management; Clinical Oncology; Clinical Protocols; Clinical Treatment; Clinical Trials; Clinical Trials Cooperative Group; Data; Diagnosis; Diagnostic; Diagnostic Procedure; Disease; Eligibility Determination; Equilibrium; Formalin; Freezing; Funding; Future; Gene Expression; Gene Expression Profiling; Genes; Genetic; Genetic Crossing Over; Genome; Goals; Histopathology; Individual; Institution; Laboratories; Malignant Childhood Neoplasm; Malignant Neoplasms; Measurement; Methods; Modeling; Molecular; Molecular Biology; Molecular Classification of Tumors; Molecular Genetics; Molecular Profiling; Morbidity - disease rate; North America; Oncologist; Operative Surgical Procedures; Outcome; PAX7 gene; Paraffin Embedding; Pathologist; Patients; Population; Process; Proteins; Protocols documentation; PubMed; Publishing; Relative (related person); Research; Resources; Rhabdomyosarcoma; Risk; Sampling; Sensitivity and Specificity; Skeletal Myoblasts; Specialist; Specimen; Staging; Stratification; Subgroup; System; Technology; Testing; Therapeutic; Tissues; Translating; Translations; Tumor Tissue; Validation; Work; base; cancer diagnosis; cancer therapy; chimeric gene; clinical practice; cost effective; fusion gene; high risk; improved; instrument; meetings; metagenesis; outcome forecast; prognostic; programs; prospective; public health relevance; sarcoma; soft tissue; success; tool; tumor; validation studies

DESCRIPTION (provided by applicant): Diagnostic gene expression profiles were first identified ten years ago to identify subsets of childhood leukemia. Since then, untold thousands of studies (2909 listed in PubMed using 'cancer diagnosis microarrays') have been published purporting to be useful tools for cancer diagnosis and treatment. In reality, few have been incorporated for prospective cancer diagnosis and treatment stratification of patients on NCI funded clinical protocols. The Children's Oncology Group has long conducted trials of childhood cancer treatment that include virtually the entire childhood population of North America for patients under the age of 16. As part of those studies, each patient to be admitted for treatment on a COG protocol in one of the nearly 250 participating institutions undergoes central diagnostic review. In the case of childhood rhabdomyosarcoma, the most common form of sarcoma in the young, this review is used to establish eligibility as well as treatment stratification. Currently, separate protocols are open for those deemed to have low, intermediate, or high risk rhabdomyosarcoma. Unfortunately, the criteria used to identify these strata are cumbersome and imprecise, involving histopathology review, clinical criteria like age, stage, anatomic site, and extent of post-surgical disease. In recent years, identification of a unique chimeric gene (PAX-FKHR/FOXO) found only in the alveolar subgroup has been used to identify this intrinsically poor prognosis group. Unfortunately, the histopathology and genetic findings are often discordant (~30% of histopathologically defined alveolar RMS lacks a translocation). Further, there are clearly additional genetic factors that are involved in accurate and reproducible diagnosis and prognosis that go beyond the current criteria. In this proposal, we seek to create clinically useful diagnostic and prognostic biomarker profiles that can be applied to routinely processed (formalin fixed, paraffin embedded) tumor tissue and thus incorporated into the workup of every patient to be admitted on a COG STS RMS protocol. These biomarker profiles have been created over the past five years as part of an NCI funded effort (Director's Challenge and SPECS) and are recently published. They were derived by whole genome gene expression profiling of hundreds of patients' frozen tumor tissue, but they have not been validated on FFPE specimens. Further, the original technology is not readily applied in a timely, cost- effective manner for clinical use, and an alternate technology platform must be identified and validated. Here we propose in the first year to perform extensive cross validation within a CLIA certified laboratory on COG STS RMS protocol treated patients using a variety of technologies and choose the one that best meets these criteria. In the second year we propose to prospectively test the sensitivity and specificity of the new assay on current protocol patients that have been whole-genome profiled as part of the separately funded SPECS initiative. The validated profiles will then be incorporated into future COG STS RMS protocols for risk-stratified therapy using a central reference lab model widely used by COG for other diagnostic studies. PUBLIC HEALTH RELEVANCE: Genomically identified features of cancer like gene expression levels, when correlated with important clinical parameters like diagnosis and prognosis, can be beneficially employed to create predictive biomarker profiles that can predict prior to therapy the diagnosis and prognosis of an individual patient. This information in turn can be used to stratify patients for optimal therapy. Here we propose to translate robust and reproducible diagnostic and prognostic profiles created with the support of the NCI SPECS program into clinical tools applicable to all tumor specimens, frozen or fixed, and to apply them prospectively to new clinical trials for the treatment of childhood rhabdomyosarcoma being developed by the Soft Tissue Sarcoma committee of Children's Oncology Group.

描述（由申请人提供）：十年前首次确定诊断基因表达谱，以识别儿童白血病的子集。从那时起，数千个研究（使用“癌症诊断微阵列”在PubMed中列出的2909个研究）已发表，声称是用于癌症诊断和治疗的有用工具。实际上，很少有用于根据NCI资助的临床方案对患者的前瞻性癌症诊断和治疗分层的纳入。长期以来，儿童肿瘤学小组已经进行了儿童癌症治疗的试验，其中包括16岁以下患者的北美整个儿童时期。作为这些研究的一部分，每位患者都将在近250家参与的机构之一接受COG方案接受治疗。就儿童横纹肌肉瘤而言，这是年轻人中最常见的肉瘤形式，该综述用于确定资格和治疗分层。当前，为那些被认为具有低，中间或高风险横纹肌肉瘤的人开放。不幸的是，用于识别这些层的标准繁琐且不精确，涉及组织病理学评论，年龄，阶段，解剖部位等临床标准以及后手术后疾病的程度。近年来，仅在肺泡亚组中发现的独特嵌合基因（PAX-FKHR/FOXO）的鉴定已被用于识别这种本质上较差的预后组。不幸的是，组织病理学和遗传发现通常是不一致的（组织病理学定义的肺泡RMS的30％缺乏易位）。此外，显然还有其他遗传因素与准确诊断和预后有关，这些因素超出了当前标准。在此提案中，我们试图创建临床上有用的诊断和预后生物标志物谱，可以应用于常规处理（福尔马林固定的，石蜡嵌入的）肿瘤组织，从而将其纳入每个患者的工作中，以在COG STS RMS方案上接受。这些生物标志物概况是在过去五年中创建的，作为NCI资助的努力（导演的挑战和规格）的一部分，并最近发表。它们是由数百例冷冻肿瘤组织的整个基因组基因表达分析得出的，但尚未在FFPE样品上进行验证。此外，原始技术不容易及时应用，具有成本效益的方式用于临床使用，并且必须确定和验证替代技术平台。在这里，我们建议在第一年对COG STS RMS协议的CLIA认证实验室进行广泛的交叉验证，并使用各种技术对患者进行了治疗，并选择最符合这些标准的技术。在第二年，我们建议将新测定法对当前方案患者的敏感性和特异性进行前瞻性测试，这些敏感性和特异性是全基因组作为单独资助的规格计划的一部分。然后，使用COG广泛用于其他诊断研究的中央参考实验室模型，将将经过验证的概况纳入未来的COG STS RMS协议中，以进行风险分层的治疗。 公共卫生相关性：在基因组上鉴定出基因表达水平（例如基因表达水平），当与重要的临床参数（如诊断和预后）相关时，可以采用有益地使用预测性的生物标志物特征，这些特征可以在治疗之前预测单个患者的诊断和预后。此信息又可以用来对患者进行最佳治疗进行分层。 Here we propose to translate robust and reproducible diagnostic and prognostic profiles created with the support of the NCI SPECS program into clinical tools applicable to all tumor specimens, frozen or fixed, and to apply them prospectively to new clinical trials for the treatment of childhood rhabdomyosarcoma being developed by the Soft Tissue Sarcoma committee of Children's Oncology Group.