BIOMEDICAL (BASIC)

我们建议使用最先进的蛋白质组学技术和新的计算策略来鉴定血清蛋白，这些血清蛋白可以在诊断前三年检测到大多数患有浆液性卵巢癌（SOC）的女性。我们研究计划的基本原理来自于我们初步工作中展示的一系列因素，这些因素表明，利用我们掌握的技术和方法，在血浆中发现生物标志物是可行的。这些因素包括有证据表明，在临床诊断前两年或更长时间，SOC中的一些血清蛋白升高，并且我们的蛋白质组学技术能够识别和测量OC发展后血液中的变化。我们的研究策略是基于这样一个假设，即最好的生物标志物可能是那些测量卵巢癌与正常细胞和组织区别的分子改变的直接结果，或者更好的是，可能是卵巢癌女性独有的蛋白质或肽序列。为了鉴定这些蛋白质，我们将能够定量1 ng/ml以下蛋白质的蛋白质组学方法与独特的数据挖掘策略相结合，将我们的SOC数据与其他几个有价值的数据来源相结合，包括：无癌妇女WHI血液的蛋白质组学谱，蛋白质组学和基因组序列以及测量正常和肿瘤卵巢细胞的表达数据。总之，这些数据将使我们能够确定哪些血浆蛋白可能来自肿瘤，并且在无癌妇女中含量较低。

We propose to use state of the art proteomics technologies and novel computational strategies to identify serum proteins that can detect the majority of women with serous ovarian cancer (SOC) three years before diagnosis. The rationale for our research plan follows from a set of factors, demonstrated in our preliminary work, which suggest that for SOC discovering biomarkers in plasma is feasible with the technologies and methodologies at our disposaL. These factors include the evidence that some serum proteins in SOC elevate two or more years before clinical diagnosis, and that our proteomics technologies are capable of identifying and measuring changes in the blood following OC development. Our research strategy is based on a hypothesis that the best performing biomarkers wil likely be those that measure the direct consequence of molecular alterations distinguishing ovarian cancer from normal cells and tissues, or even better, protein or peptide sequences that may be unique to women with OC. To identify these proteins we combine a proteomics approach capable of quantifying proteins below 1 ng/ml with unique data mining strategies that combine our SOC data with several other valuable sources of data, including: proteomic profiles of WHI blood from cancer-free women, and proteomic and genomic sequence and expression data measuring normal and tumor ovary cells. Together these data will permit us to identify which plasma proteins are possibly tumor derived, and low abundant in cancer-free women.