Prostate Cancer Detection by Serum Proteomic Profiling

描述（由申请人提供）： 我们的假设是，即使癌症仍然包含在前列腺中，血清中低分子量蛋白质和肽片段的模式也会因前列腺癌的存在而改变。我们建议使用基于人工智能的模式识别算法来识别血清蛋白质和肽片段的表达模式，这些蛋白质和肽片段可以区分患有前列腺癌的男性和患有良性前列腺的男性。本研究的目的是开发一种基于血清蛋白质组学的检测方法，该方法将有助于确定血清PSA水平在2.5和10.0 ng/ml之间的男性是否需要前列腺活检。 目标1：确定蛋白质芯片表面和质谱仪仪器，产生血清蛋白质组谱，最好地区分男性前列腺癌与良性前列腺。 目标二：在血清总PSA水平为2.5至10.0 ng/ml的男性中，确定优化血清蛋白质组学算法对活检检测到的前列腺癌的灵敏度、特异性和阳性预测值。 目标3：比较血清总PSA水平为2.5至10.0 ng/ml的男性的血清蛋白质组学分析与PSA密度和游离PSA百分比测量的性能。 目标4：通过分析连续3天从同一患者采集的血清样本，确定血清蛋白质组模式的生物学变异性。

DESCRIPTION (provided by applicant): Our hypothesis is that the patterns of low molecular weight proteins and peptide fragments in serum are altered by the presence of prostate cancer even when the cancer is still contained within the prostate. We propose to use an artificial intelligence-based pattern recognition algorithm to identify expression patterns of serum protein and peptide fragments that discriminate men with prostate cancer from those men with benign prostates. The goal of this study is to develop a serum proteomic based detection method that will help determine the need for prostate biopsy for men with serum PSA levels between 2.5 and 10.0 ng/ml. Aim 1: Determine the protein chip surface and mass spectrometer instrument that generates the serum proteomic profile that best discriminates men with prostate cancer from those with benign prostates. Aim 2: Determine the sensitivity, specificity and positive predictive value for biopsy-detected prostate cancer of the optimized serum proteomic algorithm among men with serum total PSA levels of 2.5 to 10.0 ng/ml. Aim 3: Compare the performance of serum proteomic profiling to PSA density and percent free PSA measurements for men with serum total PSA levels of 2.5 to 10.0 ng/ml. Aim 4: Determine the biological variability of serum proteomic patterns by analyzing serum samples collected from the same patient on 3 consecutive days.