LncRNA Pathways as Novel Diagnostic Biomarkers Derived from the Stroma of Epithel

描述（由申请人提供）：侵袭性上皮性卵巢癌（EOC）诊断为晚期（III/IV），其5年生存率仅为~30%。相比之下，在I期发现的EOCs存活率超过90%，并且通常通过手术干预治愈。目前，大多数EOCs在晚期才被诊断出来，因此，卵巢癌是西方社会最致命的妇科恶性肿瘤，尽管在最常见的肿瘤中仅排在第五位。早期检测EOCs将是降低死亡率和提高该疾病存活率的现实方法。然而，目前还没有足够敏感或特异性的生物标志物，可以作为筛查生物标志物，在高危人群中检测早期EOC。该项目旨在鉴定来自EOCs基质的生物标志物，这些标志物可用于检测早期EOCs，从而提高浸润性卵巢癌的生存率。实体瘤可以被认为以类似于身体所有器官的方式发挥作用，因为上皮细胞只是一个细胞群，存在并在基质细胞和细胞外基质的异质混合物中交流。高达70%的卵巢癌是间质癌。肿瘤基质是动态的，与肿瘤共同进化，支持癌变的所有阶段，对维持肿瘤的内稳态至关重要。对于EOC，肿瘤间质的发展尚不清楚，但似乎正常卵巢成纤维细胞和间充质干细胞都有能力发展成癌症相关成纤维细胞（CAFs）。在卵巢CAFs中很少检测到基因组畸变，提示调控元件可能在CAFs的分化中起作用。该项目旨在分析一类调控rna，长链非编码rna （lncRNAs）的表达变化，这些变化发生在CAF发展过程中。lncrna最近被证明在分化过程中发挥作用，类似于CAF前体细胞的CAF发育。此外，现在已知lncrna是癌症中常见的异常通路（例如p53信号）解除管制的主要机制驱动因素。本研究将鉴定与CAF前体相比，在卵巢CAF中表达差异的lncrna，并分析下游lncrna靶基因。将根据这些数据创建用于检测EOC的候选生物标志物清单；生物标志物可以是lncrna，也可以是这些lncrna在转录水平上调控的蛋白编码基因。使用现有的EOC体内异型模型，将通过使用PCR或基于elisa的检测方法检测其在哺乳动物模型血液中的丰度来评估生物标志物。这项研究的下一阶段将是测试在诊断侵袭性EOC之前采集的患者血清样本中表现最好的生物标志物。

DESCRIPTION (provided by applicant): Invasive epithelial ovarian cancer (EOC) diagnosed at an advanced stage (III/IV) is characterized by 5-year survival rates of only ~30%. In contrast, EOCs detected at stage I have survival rates of over 90%, and are often cured by surgical intervention. Currently, most EOCs are diagnosed at the later stages and, as a result, ovarian cancer is the most lethal gynecological malignancy in Western societies, despite being only the 5th most common. Detecting EOCs earlier would be a realistic way to reduce mortality and improve survival rates for this disease. However, no biomarker currently exists that is sensitive or specific enough to be used as a screening biomarker to detect early-stage EOC in at risk populations. This proposed project aims to identify biomarkers that are derived from the stroma of EOCs that could be used in to detect early- stage EOCs and in doing so, improve survival rates for invasive ovarian cancer. A solid tumor can be considered to function in a manner analogous to all organs in the body, in that the epithelial cells are just one cell population existing and communicating within a heterogeneous mix of stromal cells and extracellular matrix. Up to 70% of an ovarian cancer is stroma. The tumor stroma is dynamic, co- evolving with tumor to support all stages of carcinogenesis, and is vital for maintaining homeostasis of the tumor. For EOC, the development of the tumor stroma is poorly understood, but it appears that both normal ovarian fibroblasts and mesenchymal stem cells have the capacity to develop into cancer-associated fibroblasts (CAFs). Genomic aberrations are rarely detected in ovarian CAFs, suggesting regulatory elements may have a role in the differentiation of CAFs. This proposed project aims to profile changes in the expression of a class of regulatory RNAs, long non-coding RNAs (lncRNAs), which occur during CAF development. LncRNAs have recently been shown to have a role in differentiation processes that are analogous to the development of CAFs from CAF precursor cells. Moreover, lncRNAs are now known to be major mechanistic drivers underlying deregulation of pathways commonly aberrated in cancer (e.g. p53 signaling). In this study, lncRNAs differentially expressed in ovarian CAFs compared to CAF precursors will be identified, and downstream lncRNA-target genes profiled. A list of candidate biomarkers for detection of EOC will be created from these data; the biomarkers may either be the lncRNAs or the protein-coding genes regulated at the transcript level by these lncRNAs. Using an existing in vivo heterotypic model of EOC, the biomarkers will be evaluated by testing their abundance in the blood of a mammalian model using PCR or ELISA-based assays. The next stage of this research will be to test the best performing biomarkers in patient sera samples taken preceding a diagnosis of invasive EOC.