Nuclear Factor-kappaB in Ovarian Cancer

特异性目的1：鉴定NF-kB调节因子在卵巢癌中的异常表达。原理：在一组癌症样本中，具有异常表达谱的基因是那些在样本子集中具有显著高或低表达的基因。异常值可能表明致癌事件，如易位、扩增或基因组缺失。近年来，提出了一种识别异常基因的方法，该方法依赖于表达数据的缩放变换来突出极端值。我们修改了这种方法，并将其应用于多发性骨髓瘤，试图关注与NF-kB激活相关的异常值。该方法发现了2个癌基因NIK和CD40的极高表达，3个肿瘤抑制基因TRAF3、CYLD和BIRC2/3的极低表达。这些异常发生在有NF-kB活性证据的骨髓瘤病例中，表明这些基因表达的增加或减少是致病的。这种方法以前尚未应用于卵巢癌的基因表达谱，但有可能识别出该疾病发病机制背后的各种遗传异常。对公开可用的卵巢癌数据集的初步分析表明，在IKKb特征基因表达最高的病例中，IGFBP2表达极低。IGFBP2负调控前列腺和乳腺上皮细胞的生长。因此，我们可以假设卵巢癌细胞中IGFBP2的缺失可能会导致NF-kB级联反应的促生长作用。设计：我们将系统地将此方法应用于现有的卵巢癌基因表达谱数据库（http://www.ncbi.nlm.nih.gov/geo/gds和内部生成的数据）。在初始阶段，将分析现有的数据，因此不需要额外的投资，除了人力。一旦识别出异常值，将投入资源对目标进行分类和验证。异常值将与我们当前工作中定义的NF-kB特征表达相关，作为对单个细胞系和患者中NF-kB途径活性的估计。我们将在降低严格程度的情况下进行分析，首先选择异常基因表达的高截止点，以关注最可能具有影响mRNA表达水平的遗传异常的病例。已知NF-kB调节因子的极端异常表达将促使进一步在基因组和蛋白质组学水平上进行研究。我们将通过定量PCR对基因组DNA进行量化，以确定该位点的增益或损失。在材料和试剂可用的情况下，我们将尝试通过细胞系的Western blot或病例组织切片的免疫组织化学方法在蛋白质水平上研究基因产物的表达。该异常的实验验证将在卵巢癌细胞系中通过适当的敲除或过表达该基因来证实。特异性目标2：绘制与NF-kB合作驱动卵巢癌发病机制的交叉通路。原理：NF-kB活性由IkappaB激酶（IKKs）直接调控。这些激酶作用于已知在卵巢癌中重要的信号分子的下游，包括MAP-K、AKT和tgf - β。IKK活动的刺激和每条通路的最终结果可能是特定的。在造血方面，ikk - α活性通常在细胞质中被描述为调节经典NF-kappaB组分活性的异三聚体复合物的一部分，或者作为调节其他NF-kappaB转录因子的同型二聚体。然而，在前列腺癌中，ikk - α在细胞核中发挥着重要作用，去抑制促进转移的基因。在成纤维细胞或巨噬细胞中，IL-1激活可导致经典的ikk - β级联反应或ikk - α信号传导，这取决于IL-1受体相关激酶（IRAK）的状态。在非恶性乳腺上皮细胞中，已知tgf - β可激活细胞凋亡；然而，在乳腺癌中，tgf - β通过ikk - β刺激生长，ikk - β依赖于tgf - β活化的激酶结合蛋白1 （TAB1）。因此，分子环境是决定哪些IKK被激活以及信号最终如何影响癌细胞的关键。在这个目标中，我们将试图定义NF-kB在卵巢癌中被激活的背景，以及合作传播信号的激酶。这些激酶可能会与NF-kB联合靶向，以便为卵巢癌的这一亚群定制治疗。设计：我们的工作得到了Marsha Rivkin科学学者奖的支持，建立了卵巢癌细胞系的一个子集对ikk - β小分子抑制剂的敏感性。我们将使用该抑制剂与靶向人类kinome的RNA干扰（RNAi）联合寻找相互作用途径。我们将进行RNAi基因筛选，以发现在卵巢癌中与ikk - β合作的途径。我们将筛选一个针对500种蛋白激酶的小发夹rna （shRNAs）文库，以确定可能增强或拮抗ikk - β抑制剂毒性作用的遗传途径。卵巢癌细胞系Caov3将用该文库中的逆转录病毒池进行转导，然后用亚最大致死剂量的ikk - β抑制剂进行处理，这样大约50%的细胞在7天后被杀死。由于shRNA文库中的每个载体都具有独特的60碱基对分子条形码序列，因此我们将能够比较用ikk - β抑制剂处理的培养物中存在的shRNA载体的补体与平行未处理的培养物的补体。这将使我们能够识别在ikk - β抑制剂存在下增加或减少细胞死亡的shrna，而忽略那些与ikk - β抑制剂不协同的毒性shrna。每个确定的激酶将在ikk - β敏感和不敏感的细胞系中分别通过shRNA敲低进行验证；如果可用，通过小分子抑制来确认与ikk - β抑制剂的协同作用；通过外显子的重新测序来识别潜在的激活突变特别是在激酶结构域。

SPECIFIC AIM 1: To identify aberrant expression of NF-kB regulators in ovarian cancer. Rationale: In a set of cancer samples, genes with an outlier expression profile are those with a dramatically high or low expression in a subset of samples. Outliers may indicate oncogenic events such as translocations, amplifications, or genomic deletions. Recently, a method to identify outlier genes was described, which relies on a scaling transformation of the expression data to accentuate extreme values. We modified this approach and applied it to multiple myeloma, attempting to focus on outliers associated with NF-kB activation. This approach identified extreme high expression of 2 oncogenes NIK and CD40, and very low expression of 3 tumor supressors TRAF3, CYLD and BIRC2/3 locus. These abnormalities occurred in myeloma cases with evidence of NF-kB activity, suggesting that the gain or loss of expression of these genes was causative. This approach has not been previously applied to the gene expression profiles of ovarian cancer, yet has the potential to identify diverse genetic abnormalities underlying the pathogenesis of the disease. Preliminary analysis of publicly available ovarian cancer datasets indicates that IGFBP2 is extremely under-expressed in the cases with highest IKKb signature gene expression. IGFBP2 negatively regulates cell growth in prostate and breast epithelia. Therefore one could hypothesize that the loss of IGFBP2 in ovarian cancer cells might allow growth-promoting effects of NF-kB cascades to ensue. Design: We will apply this method systematically to existing databases of ovarian cancer gene expression profiles (http://www.ncbi.nlm.nih.gov/geo/gds and internally generated data). In the initial phase, existing data will be analyzed and thus no additional investment, other than manpower, is required. Once outliers are identified, resources will be committed to classify and validate the target. Outliers will be correlated with the NF-kB signature expression as defined in our current work, as an estimate of NF-kB pathway activity in individual cell lines and patients. We will perform the analysis at decreasing levels of stringency, initially choosing a high cutoff for outlier gene expression to focus on cases most likely to have genetic abnormalities affecting mRNA expression levels. Extreme outlier expression of a known NF-kB regulator will prompt further investigation at the genomic and proteomic levels. We will quantify the genomic DNA by quantitative PCR in order to confirm gains or losses of the locus in question. We will attempt to investigate the gene product expression at the protein level by Western blot in the cell lines or with immunohistochemistry in tissue sections from the cases, as material and reagents are available. Experimental validation of the abnormality will be confirmed in ovarian cancer cell lines by either knocking down or overexpressing the gene, as appropriate. SPECIFIC AIM 2: To map out intersecting pathways that cooperate with NF-kB to drive the pathogenesis of ovarian cancer. Rationale: NF-kB activity is regulated directly by IkappaB kinases (IKKs). These kinases act downstream of signaling molecules that are known to be important in ovarian cancer including MAP-K, AKT, and TGF-beta. The stimulus for IKK activity, and the end result of each pathway, may be context specific. In the hematopoetic context, IKK-alpha activity has been most often described in the cytoplasm, as part of a hetero-trimeric complex regulating the activity of classical NF-kappaB components, or as a homo-dimer regulating alternative NF-kappaB transcription factors. In prostate cancer, however, IKK-alpha has a prominent role in the nucleus of the cell, de-repressing metastasis-promoting genes. In fibroblasts or macrophages, IL-1 activation can result in either classical IKK-beta cascades or alternative IKK-alpha signaling depending on the status of the IL-1 receptor associated kinase (IRAK). In non-malignant breast epithelial cells, TGF-beta is known to activate apoptosis; in the context of breast carcinoma, however, TGF-beta stimulates growth via IKK-beta that depends on TGF-beta-activated kinase binding protein 1 (TAB1). Therefore, the molecular context is key to determining which IKK is activated and how the signals will ultimately affect the cancer cell. In this Aim, we will seek to define the context in which NF-kB is activated in ovarian cancer, and the kinases that cooperate to propagate the signal. Such kinases might then be targeted in conjunction with NF-kB in order to tailor therapy for this subset of ovarian cancer. Design: Our work supported by the Marsha Rivkin Scientific Scholar Award established the sensitivity of a subset of ovarian cancer cell lines to a small molecule inhibitor of IKK-beta. We will use this inhibitor in combination with RNA interference (RNAi) targeting the human kinome to search for interacting pathways. We will conduct an RNAi genetic screen to uncover pathways that cooperate with IKK-beta in ovarian cancer. We will screen a library of small hairpin RNAs (shRNAs) targeting 500 protein kinases to identify genetic pathways that might potentiate or antagonize the toxic effect of the IKK-beta inhibitor. The ovarian cancer cell line, Caov3, will be transduced with a pool of retroviruses from this library and then treated with a submaximal lethal dose of IKK-beta inhibitor such that roughly 50% of the cells were killed after 7 days. Since each vector in the shRNA library possesses a unique 60-base pair molecular bar code sequence, we will be able to compare the complement of shRNA vectors present in cultures treated with the IKK-beta inhibitor to that in parallel untreated cultures. This will allow us to identify shRNAs that increase or decrease cell death in the presence of the IKK-beta inhibitor but ignore shRNAs that are toxic in a manner that is not synergistic with IKK-beta inhibition. Each identified kinase will be validated individually by shRNA knockdown in IKK-beta sensitive and insensitive cell lines; by small molecule inhibition, if available, to confirm synergy with the IKK-beta inhibitor; and by re-sequencing of exons to identify potential activating mutations especially in the kinase domain.