Harnessing p27 for Prognostication of Pediatric Osteosarcoma

描述（申请人提供）：骨肉瘤是儿童和年轻人最常见的恶性肿瘤。尽管使用手术和多药化疗，骨肉瘤患者的生存率在过去三十年中没有改善。个性化医疗有望改善癌症患者的治疗;然而，它依赖于在治疗开始前预测临床风险的准确方法。在骨肉瘤中，诊断时唯一的预后因素是通过常规低灵敏度成像方法检测转移。我们的理由是，分子预后生物标志物的发展将促进个性化医疗，使替代或靶向治疗可用于改善高风险患者的结果，而低风险患者将免于不必要的化疗。大量文献表明，肿瘤抑制因子p27可用于预测各种成人癌症的预后，如乳腺癌、急性髓性白血病、胰腺癌和卵巢癌。我们的实验室已经证明，p27是错误定位在转移性骨肉瘤细胞系，并经常在人类骨肉瘤病例。功能研究进一步表明，胞质p27可以促进骨肉瘤细胞的运动和侵袭。此外，我们已经证明，p27自身抗体升高转移性骨肉瘤患者使用高密度蛋白阵列。基于这些观察，我们假设p27是成人肿瘤的预后生物标志物，可用于诊断儿童骨肉瘤。为了验证这一假设，我们提出了四个具体目标。首先，我们将在两个系列的骨肉瘤病例中，将p27蛋白表达和亚细胞定位与转移和生存信息联系起来。其次，我们将整合p27结果与其他相关的预后生物标志物，以测试我们是否可以增加检测的预后意义。第三，我们将开发一种新的基于Luminex的p27自身抗体检测方法，以验证它是否与使用从儿童肿瘤组收集的治疗前血清样本的骨肉瘤患者的结果相关。最后，我们将对我们实验室中产生的一组p27突变体进行基因组和靶向蛋白质组学分析，以确定新的p27相关生物标志物。这些候选生物标志物将使用我们的SPECS和TARGET联盟生成的数据进行验证。将所有生物标志物结果与现有的预后因素（即转移）进行比较，以测试临床预后。 生物标志物的效用。本研究的长期目标是开发一种生物标志物方法，用于在诊断时对骨肉瘤患者进行诊断，该方法比传统方法更准确。这将促进个性化医疗的发展，从而提高骨肉瘤患者的生存率。完成拟议的研究是实现这一目标的关键一步。此外，由于p27与其他癌症有关，因此这项研究的结果将对癌症生物标志物领域产生更大的影响。

DESCRIPTION (provided by applicant): Osteosarcoma is the most common malignant tumor in children and young adults. Despite the use of surgery and multi-drug chemotherapy, the survival rate of osteosarcoma patients has not improved in the past three decades. Personalized medicine holds the promise of improving the treatment of cancer patients; however, it relies on an accurate way to predict clinical risks before treatment initiation. In osteosarcoma, the only prognostic factor at the time of diagnosis is the detection of metastasis by conventional low-sensitive imaging methods. We reason that the development of a molecular prognostic biomarker will facilitate personalized medicine, so that an alternative or a targeted therapy can be used to improve the outcome of the high-risk patients, while the low-risk patients would be spared from unnecessary chemotherapy. A vast amount of literature has shown that the tumor suppressor p27 can be used to predict prognosis in various adult cancers, such as breast carcinomas, acute myelogenous leukemia, pancreatic cancer and ovarian carcinomas. Our laboratory has demonstrated that p27 is mislocalized in metastatic osteosarcoma cell lines and frequently in human osteosarcoma cases. Functional studies have further shown that cytoplasmic p27 can promote the motility and invasiveness of osteosarcoma cells. In addition, we have demonstrated that the p27 autoantibody is elevated in metastatic osteosarcoma patients using high-density protein arrays. Based on these observations, we hypothesize that p27, which is a prognostic biomarker in adult cancers, can be used to prognosticate pediatric osteosarcoma. To test this hypothesis, we propose four Specific Aims. First, we will correlate the protein expression and subcellular localization of p27 with metastasis and survival information in two series of osteosarcoma cases. Second, we will integrate the p27 results with other related prognostic biomarkers to test if we can increase the prognostic significance of the detection. Third, we will develop a novel Luminex-based assay for the p27 autoantibody to validate if it correlates with the outcomes of osteosarcoma patients using pre-treatment serum samples collected from the Children's Oncology Group. Lastly, we will perform genomic and targeted proteomic analyses of a panel of p27 mutants that have been generated in our laboratory to identify novel p27-related biomarkers. These candidate biomarkers will be validated using the data generated from our SPECS and TARGET consortia. All the biomarker results will be compared with the existing prognostic factor, i.e. metastasis, to test the clinical utility of the biomarkers. The long-term goal of this study is to develop a biomarker approach for the prognostication of osteosarcoma patients at the time of diagnosis that is more accurate than the conventional approaches. It would facilitate the development of personalized medicine and, hence, improve the survival of osteosarcoma patients. Completion of the proposed study is a critical step to achieve this goal. Furthermore, since p27 has been implicated in other cancers, the results obtained from this study will have a larger impact on the field of cancer biomarkers.