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）：诊断基因表达谱在十年前首次确定，以确定儿童白血病的子集。从那时起，数以千计的研究（2909列在PubMed使用“癌症诊断微阵列”）已被发表，声称是癌症诊断和治疗的有用工具。事实上，很少有纳入NCI资助的临床方案的患者的前瞻性癌症诊断和治疗分层。儿童肿瘤学小组长期以来一直在进行儿童癌症治疗的试验，这些试验几乎包括北美16岁以下患者的整个儿童人群。作为这些研究的一部分，在近250个参与机构之一中，每名根据COG协议入院接受治疗的患者都要接受中央诊断审查。在儿童横纹肌肉瘤的情况下，最常见的肉瘤在年轻的形式，本审查是用来建立资格以及治疗分层。目前，单独的协议是开放的那些被认为有低，中，或高风险横纹肌肉瘤。不幸的是，用于识别这些分层的标准是繁琐和不精确的，涉及组织病理学审查，临床标准，如年龄，分期，解剖部位和手术后疾病的程度。近年来，一个独特的嵌合基因（PAX-FKHR/FOXO）的鉴定发现，只在肺泡亚组已被用来确定这个固有的预后不良组。不幸的是，组织病理学和遗传学发现往往是不一致的（约30%的组织病理学定义的肺泡RMS缺乏易位）。此外，有明确的额外的遗传因素，涉及准确和可重复的诊断和预后，超出了目前的标准。在该提案中，我们寻求创建临床上有用的诊断和预后生物标志物谱，其可以应用于常规处理（福尔马林固定，石蜡包埋）的肿瘤组织，从而并入到根据COG STS RMS方案入院的每个患者的检查中。这些生物标志物谱是在过去五年中作为NCI资助的努力（Director's Challenge和SPECS）的一部分创建的，最近发表。它们是通过对数百名患者的冷冻肿瘤组织进行全基因组基因表达谱分析得出的，但尚未在FFPE标本上得到验证。此外，原始技术不容易以及时、成本有效的方式应用于临床使用，并且必须识别和验证替代技术平台。在这里，我们建议在第一年在CLIA认证的实验室内使用各种技术对COG STS RMS协议治疗的患者进行广泛的交叉验证，并选择最符合这些标准的技术。在第二年，我们建议前瞻性地测试新检测方法对当前方案患者的灵敏度和特异性，这些患者已作为单独资助的SPECS计划的一部分进行了全基因组分析。然后，使用COG广泛用于其他诊断研究的中心参考实验室模型，将经验证的特征纳入未来的COG STS RMS方案中，用于风险分层治疗。 公共卫生关系：当与重要的临床参数如诊断和预后相关时，基因组鉴定的癌症样基因表达水平的特征可以有利地用于产生预测性生物标志物谱，其可以在治疗之前预测个体患者的诊断和预后。这些信息又可以用于对患者进行分层，以获得最佳治疗。在这里，我们建议将在NCI SPECS项目的支持下创建的强大且可重复的诊断和预后资料转化为适用于所有冷冻或固定肿瘤标本的临床工具，并将其前瞻性地应用于儿童肿瘤组软组织肉瘤委员会正在开发的治疗儿童横纹肌肉瘤的新临床试验。