Translation of Predictive Cancer Biomarkers into Clinical Practice

描述（由申请人提供）：诊断性基因表达谱在十年前首次被确定，用于确定儿童白血病的亚群。从那时起，无数的研究（2909篇在PubMed上列出的使用“癌症诊断微阵列”的研究）已经发表，声称是癌症诊断和治疗的有用工具。实际上，在NCI资助的临床方案中，很少有纳入前瞻性癌症诊断和治疗分层的患者。儿童肿瘤小组长期以来一直在进行儿童癌症治疗的试验，其中包括北美几乎所有16岁以下的儿童患者。作为这些研究的一部分，在近250个参与机构中的一个接受COG方案治疗的每个患者都要进行中央诊断审查。儿童横纹肌肉瘤是年轻人中最常见的肉瘤，该综述用于确定治疗的适格性和治疗分层。目前，对于那些被认为患有低、中、高风险横纹肌肉瘤的患者，有不同的治疗方案。不幸的是，用于识别这些层的标准是繁琐和不精确的，包括组织病理学检查，临床标准，如年龄，分期，解剖部位和术后疾病的程度。近年来，鉴定一种独特的嵌合基因（PAX-FKHR/FOXO）仅在肺泡亚组中发现，已被用于鉴定这一本质上预后不良的组。不幸的是，组织病理学和遗传学的发现往往不一致（约30%的组织病理学定义的肺泡RMS缺乏易位）。此外，在准确和可重复的诊断和预后方面，显然还有其他超出当前标准的遗传因素。在本提案中，我们寻求创建临床有用的诊断和预后生物标志物谱，可应用于常规处理（福尔马林固定，石蜡包埋）肿瘤组织，从而纳入每一位接受COG STS RMS方案的患者的检查。这些生物标志物概况是在过去五年中作为NCI资助工作（主任挑战和SPECS）的一部分创建的，并于最近发布。它们是通过对数百名患者冷冻肿瘤组织的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，原始技术不能及时、有效地应用于临床，必须确定和验证替代技术平台。在这里，我们建议在第一年在CLIA认证的实验室中对使用多种技术治疗的COG STS RMS方案进行广泛的交叉验证，并选择最符合这些标准的方案。在第二年，我们建议前瞻性地测试新检测的敏感性和特异性，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。经过验证的资料将被纳入未来COG STS RMS方案，使用COG在其他诊断研究中广泛使用的中心参考实验室模型进行风险分层治疗。

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.