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识别血清蛋白质，这些蛋白质可以在诊断前三年检测到大多数浆液性卵巢癌(SOC)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，对于SOC来说，使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，SOC中的一些血清蛋白质在临床诊断前两年或更长时间内升高，以及我们的蛋白质组学技术能够识别和测量OC发生后血液中的变化。我们的研究策略基于这样一个假设，即表现最好的生物标记物可能是那些衡量区分卵巢癌与正常细胞和组织的分子变化的直接后果的生物标记物，或者更好的，可能是卵巢癌女性独有的蛋白质或肽序列。为了确定这些蛋白质，我们将能够对低于1 ng/ml的蛋白质进行量化的蛋白质组学方法与独特的数据挖掘策略相结合，该策略将我们的SOC数据与其他几个有价值的数据来源相结合，包括：来自非癌症女性的WHI血液的蛋白质组图谱，以及测量正常和肿瘤卵巢细胞的蛋白质组和基因组序列及表达数据。综合这些数据，我们将能够确定哪些血浆蛋白可能来自肿瘤，而非癌症女性的血浆蛋白含量较低。

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.