Ovarian Cancer Initiating Cells: Metabolic Characterization

描述（申请人提供）：上皮性卵巢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，然后产生化疗耐药性，导致过早死亡。我们之前报道过CD133+细胞表现出癌症起始细胞（CICs）的特征，包括进行不对称分裂的能力；此后，其他研究小组证实了我们的发现，并通过使用CD133和ALDH细胞表面标记物提高了分离卵巢CICs的能力。CICs占肿瘤细胞的一小部分，能够在化疗中存活，重要的是，被认为会导致疾病复发，有时会在数年后复发，部分原因是它们能够减缓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，确定区分这些细胞的特定可利用靶点，从而增加它们的脆弱性是当务之急。基因表达芯片数据分析显示，含缺氧诱导因子（HIF）反应元件的基因在CD133+和CD133-卵巢癌细胞群中表达丰富（FDR q=0.078）。HIF1是调节代谢途径和过程的关键转录因子复合物的一部分，以响应氧水平，低氧水平倾向于抑制分化。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，并且基于这些差异靶向CICs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代谢差异的新型治疗策略，在疾病复发之前根除CIC人群。本提案的目的1是生成CIC细胞与非CIC卵巢癌细胞在2300多种已知代谢物和5200种未命名化合物的代谢谱，然后通过识别特定的细胞途径和相关成分来确定CIC细胞与非CIC细胞的差异。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识别的特定途径来改变CICs的比例。在目的2中，我们将确定是否可以通过调节HIF1通路活性来改变卵巢癌细胞中的CIC /非CIC比率。这些目标的成功完成将极大地增加对CICs如何能够在化疗中存活并通过改变其代谢进入延长缓解期的理解，并在复发期间以耐药形式出现。确定引起这种卵巢CIC表型的相关途径和生物学靶点，为最终导致这种疾病高死亡率的细胞群提供了前所未有的机会。

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.