Integrated Molecular and Biochemical Profiling of Liposarcoma Subtypes

需要新的实体瘤分析方法来预测远处复发和选择治疗方案。 为个别患者提供最佳治疗。实体瘤辅助治疗的评价方法 依靠大规模随机临床试验来确定疗效。这样的试验是昂贵的，很难 执行并要求许多患者接受不需要或无效的治疗。许多 相信未来的治疗将“靶向”肿瘤中的特定异常。利用这种针对性 治疗需要检测肿瘤组成的特异性靶点的新方法。在这个提议中，先进的计算分析被用于将联合收割机分子谱（微阵列）与NMR结合 确定的代谢物标记物，与来自基因组和途径的生物学功能信息相关联 数据库。总的目标是选择和鉴定脂肪肉瘤的标志物组合， 重要的诊断或预后价值，并确定潜在的新的治疗靶点。这项研究将测试 假设我们可以： (a)更好地选择具有高或低转移风险的患者和肿瘤， (b)通过分析关键信号通路，开发新的脂肪肉瘤靶向治疗药物， 脂肪肉瘤分化和肿瘤发生。 具体目标：通过分析整合的基因表达和代谢产物， NMR生化特征： 1.显示与脂肪肉瘤（LS）组织学亚型相关 2.与正常脂肪组织相比，在LS中差异表达，可用于评估信号传导 作为新的治疗靶点的LS分化和肿瘤发生的中心途径 3.对于低级别LS，可预测肿瘤其他部位或随后出现的高级别LS 患有高级别肿瘤 4.显示与脂肪肉瘤结果相关。 这种综合的分子和生化分析将使客观和准确的发展， 评估LS诊断、进展、转移风险和结果的方法。结果是 该提案最终将能够确定新的目标，提高选择患者的能力， 复发风险最高的患者接受辅助治疗，并提供选择联合治疗的合理方法 沿着实体瘤分子的蛋白质和脂质代谢的理解 遗传学

New methods of solid tumor analysis are needed to enable prediction of distant recurrence and selection of the optimal treatment for individual patients. Current methods for evaluating adjuvant therapy for solid tumors rely on large scale randomized clinical trials to determine efficacy. Such trials are expensive, difficult to perform and require that many patients receive treatment that is either not needed or ineffective. Many believe that future therapy will be "targeted" to specific abnormalities in the tumor. To utilize such targeted therapy novel methods of examining tumor composition for specific targets are needed. In this proposal advanced computational analysis is used to combine molecular profiles (microarrays) with NMR determined metabolite markers, linked with information about biological function from genome and pathway databases. The overall goal is to select and identify combinations of markers in liposarcoma that carry significant diagnostic or prognostic value and to identify potential new therapeutic targets. This study will test the hypothesis that we can: (a) better select patients and tumors that have high or low risk of metastasis and (b) develop new targeted therapeutics for liposarcoma through analysis of signaling pathways critical to liposarcoma differentiation and tumorigenesis. Specific aims: Identify genes and metabolite marker subsets by analysis of integrated gene expression and NMR biochemical profiles that: 1. show associations with liposarcoma (LS) histologic subtype 2. are differentially expressed in LS compared to normal fat tissue and could be used to evaluate signaling pathways central to LS differentiation and tumorigenesis serving as novel therapeutic targets 3. for low grade LS predict the presence of high grade LS elsewhere in the tumor or subsequent presentation with a high grade tumor 4. show association with outcome in liposarcoma. This integrated molecular and biochemical analysis will enable the development of objective and accurate methods for assessing LS diagnosis, progression, risk of metastasis and outcome. The results from this proposal would ultimately enable the identification of new targets, improve the ability to select patients for adjuvant therapy who are at highest risk of relapse and provide a rational approach to selecting combination chemotherapy based on an understanding of protein and lipid metabolism along with solid tumor molecular genetics.