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

描述(申请人提供)：侵袭性上皮性卵巢癌(EOC)诊断为晚期(III/IV)，其特征是5年生存率仅为~30%。相比之下，在I期检测到的EOCs存活率超过90%，通常通过手术治疗治愈。目前，大多数卵巢癌是在晚期确诊的，因此，卵巢癌是西方社会最致命的妇科恶性肿瘤，尽管在最常见的癌症中只占第五位。及早检测EOCs将是降低死亡率和提高这种疾病存活率的现实方法。然而，目前还没有足够灵敏或特异的生物标记物作为筛查生物标记物来检测高危人群的早期卵巢早熟。这项拟议的项目旨在确定从卵巢癌间质中提取的生物标记物，这些生物标志物可以用于检测早期卵巢癌，并通过这样做来提高浸润性卵巢癌的生存率。实体肿瘤的功能可以被认为与体内所有器官的功能相似，因为上皮细胞只是一个细胞群体，存在于基质细胞和细胞外基质的异质混合物中并相互联系。高达70%的卵巢癌是间质。肿瘤间质是动态的，与肿瘤共同进化，支持肿瘤发生的各个阶段，对维持肿瘤的动态平衡至关重要。对于上皮性卵巢癌，肿瘤间质的发育尚不清楚，但似乎正常的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的成纤维细胞(CAF)。在卵巢CAF中很少检测到基因组异常，提示调控元件可能在CAF的分化中起作用。这项拟议的项目旨在分析CAF发育过程中发生的一类调控RNA--长非编码RNA(LncRNAs)的表达变化。最近研究表明，lncRNAs在分化过程中具有类似于CAF前体细胞分化成CAF的作用。此外，目前已知，lncRNAs是癌症中常见的异常信号通路(如P53信号)解除调控的主要机制驱动因素。在这项研究中，将鉴定在卵巢CAF中与CAF前体相比差异表达的lncRNA，并对下游的lncRNA靶基因进行分析。根据这些数据将创建用于检测EOC的候选生物标记物的列表；这些生物标记物可能是lncRNAs，也可能是这些lncRNAs在转录水平上调控的蛋白质编码基因。利用现有的EOC体内异型模型，生物标志物将通过使用基于PCR或ELISA法的分析在哺乳动物模型的血液中检测其丰度来评估。这项研究的下一阶段将是测试在诊断侵袭性卵巢癌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.