Gleason-based mRNA and Metabolomic Profiling to Predict Prostate Cancer Progress

临床医生和研究人员目前无法在诊断时充分自信地区分患有惰性前列腺癌(CAP)的男性和那些患有侵袭性疾病的男性。目前，对致死上限的最强预测因子是格里森评分。利用基因表达阵列数据，我们先前识别了一个157基因的mRNA签名，该签名区分了高Gleason评分和低Gleason评分。这一特征显著改善了临床异质性Gleason评分为7的男性对致命疾病的预测。该特征可能具有临床实用价值，但在将其应用于患者之前，必须对其进行进一步改进，然后在活组织标本中进行测试，以确定预测的准确性是否足以影响诊断时的治疗决定。这项信使核糖核酸研究还确定了在高级别和低级别疾病中差异丰富的代谢途径，为可能奠定帽状分化和临床进展基础的生物学机制提供了假说。由于不同类型的生物数据可能会增加信使核糖核酸的特征并提供不同的生物信息，因此有必要进一步研究已确定的代谢途径。因此，我们建议建立在我们有希望的表达谱研究结果的基础上，具体目标如下：1)临床使用的致命性疾病的格里森签名的制备和测试-为了确定该mRNA签名是否可以应用于临床，我们将通过测试其在诊断时的活组织标本中的预测准确性来进一步验证它。我们假设，在Gleason评分7分内，如果专门应用于肿瘤的3级或4级病灶，该标志物预测致命疾病的能力可能会提高2)代谢组学将Gleason级别的肿瘤作为致命疾病的预测因子-我们的mRNA研究确定了在高级别和低级别肿瘤中差异丰富的代谢途径(嘧啶、丙酸和β-丙氨酸代谢)。我们的初步数据表明，利用代谢组学数据，这些相同的途径可能会有差异地丰富；我们假设代谢物本身可能与Gleason评分和致命性疾病有关。3)血清Gleason分级的代谢组学作为升级的生物标志物-我们假设血清中的代谢物与Gleason分级相关，可能表明存在活检未发现的较高级别的肿瘤，并可作为监测主动监测患者疾病进展的生物标志物。

Clinicians and researchers are currently unable to distinguish at diagnosis with sufficient confidence men with indolent prostate cancer (CaP) from those who have aggressive disease. At present, the strongest predictor of lethal CaP is Gleason score. Utilizing gene expression array data, we previously identified a 157 gene mRNA signature that distinguished high from low Gleason score. This signature significantly improved prediction of lethal disease among men with clinically heterogeneous Gleason score 7. The signature may have clinical utility, but before applying it to patients it must be further refined and then tested in biopsy specimens to determine if the predictive accuracy is sufficient to influence treatment decisions at the time of diagnosis. This mRNA study also identified metabolic pathways differentially enriched in high and low grade disease, generating hypotheses for biological mechanisms that may underlie CaP differentiation and clinical progression. Since different types of biological data may add to the mRNA signature as well as provide different biological information, it is worthwhile to further investigate the metabolic pathways identified. We therefore propose to build upon our promising expression profiling findings with the following Specific Aims: 1) Preparation and testing of Gleason signature of lethal disease for clinical use -To determine if the mRNA signature can be applied in the clinic, we will further validate it by testing its predictive accuracy in biopsy specimens at the time of diagnosis. We hypothesize that within Gleason score 7, the signature's ability to predict lethal disease may improve if applied specifically to the grade 3 or grade 4 focus of the tumor 2) Metabolomics bf Gleason grade In tumor as predictor of lethal disease - Our mRNA study identified metabolic pathways (pyrimidine, propanoate, and beta-alanine metabolism) differentially enriched in high and low grade tumors. Our preliminary data suggests these same pathways may be differentially enriched using metabolomic data; we hypothesize that metabolites may themselves be associated with Gleason score and lethal disease. 3) Metabolomics of Gleason grade in serum as biomarker for upgrading - We hypothesize that metabolites in serum associated with Gleason grade may indicate the presence of higher-grade tumor not detected at biopsy and could serve as a biomarker for monitoring disease progression of active surveillance patients.