Ovarian Cancer Initiating Cells: Metabolic Characterization

描述(申请人提供)：卵巢上皮癌是最致命的妇科恶性肿瘤。虽然对一线化疗的反应通常会导致完全缓解，但大多数病例会复发，然后出现化疗耐药，导致过早死亡。我们之前报道CD133+细胞表现出肿瘤起始细胞(CICs)的特征，包括经历不对称分裂的能力；自那以后，其他组证实了我们的发现，并通过使用CD133和ALDH细胞表面标志提高了分离卵巢CICs的能力。CICS由肿瘤内的一小部分细胞组成，能够在化疗中存活，重要的是，被认为会导致疾病复发，有时是在几年后，部分原因是它们能够减缓新陈代谢并进入静止状态。因此，如果我们希望延长患有这种疾病的妇女的预期寿命，确定特定的可利用目标来区分这些细胞，从而增加它们的脆弱性是当务之急。对我们的基因表达芯片数据的分析表明，在CD133+和CD133-卵巢癌细胞群体中，含有缺氧诱导因子反应元件的基因表达丰富(FDRq=0.078)。HIF1？作为一个关键的转录因子复合体的一部分，调节代谢途径和过程，以响应氧气水平，低氧水平往往会抑制分化。因此，我们假设，与非CIC肿瘤细胞相比，CICs表现出明显的代谢途径差异，基于这些差异的CICs靶向将改变CICs进行自我更新的能力。我们的长期目标是开发基于新陈代谢差异的新治疗策略，在疾病复发之前根除CIC人群。这项建议的目标1是为超过2,300种已知代谢物和5,200种未知化合物生成CIC细胞与非CIC卵巢癌细胞的代谢谱，然后通过确定所涉及的特定细胞途径和成分来确定CIC细胞与非CIC细胞的不同之处。然后，我们将验证代谢物的差异丰度，并确定是否可以通过靶向使用siRNA技术或相关治疗抑制剂确定的特定途径来改变CICs的比例。在目标2中，我们将确定是否可以通过调节HIF1途径的活性来改变卵巢癌细胞中CIC/非CIC的比例。这些目标的成功实现将极大地提高人们对CICs如何能够在化疗中幸存下来并进入长期缓解状态的理解--通过改变它们的新陈代谢--在复发时以化疗耐药的形式出现。识别导致这种卵巢CIC表型的相关途径和生物学靶点提供了一个前所未有的机会，可以靶向最终导致这种疾病高死亡率的细胞群体。 公共卫生相关性：与公共卫生相关的声明上皮性卵巢癌是一种最常在晚期诊断的疾病。这项建议旨在阐明导致疾病复发的一小部分卵巢癌细胞的全面代谢谱，并基于这些谱确定特定的可利用的治疗靶点，以允许靶向这些细胞并帮助防止肿瘤复发。 原发癌症。这项工作的成功完成将提供一个前所未有的机会，以找到具体的脆弱性，最终根除与卵巢癌相关的高死亡率的最终责任细胞。

DESCRIPTION (provided by applicant): Epithelial ovarian cancer is the most lethal gynecologic malignancy. Although response to first line chemotherapy usually leads to complete remission, most cases relapse and then are chemoresistant, leading to premature death. We previously reported that CD133+ cells exhibit characteristics of cancer initiating cells (CICs) including the ability to undergo asymmetric division; other groups have since confirmed our findings and have improved the ability to isolate ovarian CICs by using both CD133 and ALDH cell surface markers. CICs comprise a small proportion of cells within a tumor, are able to survive chemotherapy and importantly, are thought to cause disease recurrence, sometimes years later, in part due to their ability to slow metabolism and enter quiescence. Therefore, identifying specific exploitable targets that distinguish these cells and thus increase their vulnerability is a top priority if we hope to extend life expectancy of women with this disease. Analysis of our gene expression microarray data showed that expression of genes containing Hypoxia inducible factor (HIF) response elements was enriched in CD133+ versus CD133- ovarian cancer cell populations (FDR q=0.078). HIF1¿ functions as part of a key transcription factor complex regulating metabolic pathways and processes in response to oxygen levels, with low oxygen levels tending to inhibit differentiation. Therefore, we hypothesize that CICs exhibit distinct metabolic pathway differences as compared to non-CIC tumor cells and that targeting of CICs based on these differences will alter the ability of CICs to undergo self-renewal. Our long-term objective is to develop novel therapeutic strategies based on metabolic differences to eradicate CIC populations prior to disease recurrence. Aim 1 of this proposal is to generate metabolic profiles of CIC cells versus non-CIC ovarian cancer cells for over 2,300 known metabolites and 5,200 unnamed compounds and then determine how CICs differ from non-CICs by identifying the specific cellular pathways and components involved. We will then validate the differential abundance of metabolites and determine if the proportion of CICs can be altered by targeting the specific pathways identified using siRNA technology or relevant therapeutic inhibitors. In Aim 2, we will determine if the CIC / non-CIC ratio in ovarian cancer cells can be altered by modulating HIF1 pathway activity. Successful completion of these aims will greatly increase understanding of how CICs are able to survive chemotherapy and enter into prolonged remission - by altering their metabolism - to later emerge in chemoresistant form during relapse. Identifying relevant pathways and biological targets that elicit this ovarian CIC phenotype offers an unprecedented opportunity to target the cell population ultimately responsible for the high mortality of this disease. PUBLIC HEALTH RELEVANCE: Statement of Relevance to Public Health Epithelial ovarian cancer is a disease that is most commonly diagnosed at an advanced stage. This proposal seeks to elucidate comprehensive metabolic profiles of the small subset of ovarian cancer cells that are responsible for disease recurrence, and identify specific exploitable therapeutic targets based on these profiles that will allow targeting of these cells and help prevent recurrence of the primary cancer. Successful completion of this work will offer an unprecedented opportunity to find specific vulnerabilities that will eventually allow for eradication of the cells ultimately responsible for the high mortality associated with ovarian cancer.