Integrated models for metastatic phenotype and outcome prediction in osteosarcoma

描述(申请人提供)：这项申请提出了一项关于骨肉瘤的基因组预后研究，骨肉瘤是一种相对研究较少的癌症，在年轻患者中发病率较高，其分子基础尚不完全清楚。结果是高度可变的，而且缺乏经过充分研究的预测因素，可以进行分层管理决策。一个主要的挑战是相对罕见的疾病，以及缺乏广泛可用的、注释良好的冰冻组织资源。我们最近发表了分析福尔马林固定石蜡包埋(FFPE)骨肉瘤组织的miRNA表达和测序图谱的初步数据，产生了与骨肉瘤临床结果密切相关的可检验假说。特别是，一个强大的预后miRNA图谱已被鉴定，有趣的是，似乎主要聚集在一个染色体位置。在具体目标1中，我们建议在成人队列和儿童队列中验证候选miRNA预后特征，利用基于大型儿童肿瘤组的队列数据。此外，我们还将测试独立于相关临床病理数据(如化疗导致的坏死)的独立性和潜在的协同作用。在目标2中，将测试一种新的方法，旨在通过分别利用来自活检和切除的成对的化疗前和化疗后样本来建立动态miRNA表达模型，以捕捉化疗对肿瘤的影响。这个假设是，他们将提供额外的强大的预后见解，特别是与化疗耐药患者相关的。在目标3中，将研究深层miRNA序列模式，以探索它们与表达谱的关系和潜在的预后意义。在AIM 4中，miRNA测序将扩展到来自活检、化疗耐药切除和转移的连续样本，以识别表明转移表型的进化序列模式，由于丰度低，在诊断时可能不容易通过快照测试检测到这些表型。这些独特的模式可能最终与总体生存结果相关，并与观察到许多复发肿瘤患者仍然可以长期存活有关。 治疗。我们的建议利用了骨肉瘤独特的治疗模式，包括对原发和转移性疾病进行化疗后的连续活检和切除，从而在常规护理中提供连续的患者标本。此外，这些AIMS揭示的模式也将在FFPE标本中进行研究，以便为未来确定的大规模临床应用提供基础。这项多机构和跨学科的提案利用了尖端基因组技术，并汇集了来自达纳/法伯哈佛癌症中心所有机构的骨肉瘤、基因组学、计算生物学和生物统计学方面的专家团队。

DESCRIPTION (provided by applicant): This application proposes a genomic prognostic study in osteosarcoma, a relatively understudied cancer with high incidence in younger patients, the molecular underpinnings of which are incompletely understood. Outcome is highly variable and there is a lack of well-studied prognostic factors that would allow stratified management decisions. A major challenge is the relative disease rarity and the lack of widely available well annotated frozen tissue resources. We recently published preliminary data analyzing miRNA expression and sequencing profiles from formalin fixed paraffin embedded (FFPE) osteosarcoma tissues generating testable hypotheses with strong relevance to osteosarcoma clinical outcome. In particular, a strong prognostic miRNA profile has been identified which, interestingly, appears to be clustered mainly in one chromosomal location. In Specific aim 1, we propose to validate the candidate miRNA prognostic profile in an adult cohort, and a pediatric cohort utilizing data from a large Children's Oncology Group based cohort In addition, we will test for independence from, and potential synergy with, relevant clinicopathologic data such as chemotherapy induced necrosis. In Aim 2 a novel approach will be tested aiming to develop dynamic miRNA expression models capturing the effect of chemotherapy on the tumor, by utilizing paired pre and post chemotherapy specimens from biopsy and resection, respectively. The hypothesis is that they will offer additional powerful prognostic insights specifically relevan to chemoresistant patients. In Aim 3, deep miRNA sequence patterns will be studied in order to explore their relation to expression profiles and potential prognostic significance. In Aim 4 miRNA sequencing will be extended to serial specimens from biopsy, chemoresistant resection and metastasis in order to identify evolving sequence patterns signifying the metastatic phenotype which may not be easily detectable via a "snapshot" test at diagnosis, due to low abundance. These unique patterns may ultimately be relevant to overall survival outcome and to the observation that many patients with recurrent tumors can still survive a long time with further treatment. Our proposal takes advantage of the unique treatment patterns in osteosarcoma, which include serial biopsies and resections following chemotherapy administration in both primary and metastatic disease, resulting in availability of serial patient specimens during routine care. Additionally, patterns revealed in these Aims will also be studied in FFPE specimens in order to provide the basis for definitive large scale clinical application in the futue. This multi institutional and interdisciplinary proposal utilizes cutting edge genomic technologies and brings together a team of experts in osteosarcoma, genomics, and computational biology and biostatistics from all institutions within the Dana/Farber Harvard Cancer Center.