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

基于格里森的 mRNA 和代谢组学分析可预测前列腺癌进展

• 批准号: 9110151
• 负责人: Massimo Loda
• 金额: $ 24.3万
• 依托单位: DANA-FARBER CANCER INST
• 依托单位国家: 美国
• 财政年份: 2002
• 资助国家: 美国
• 起止时间: 2002-09-19 至
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/9110151
• 关键词: Area; Biological; Biological Markers; Biopsy; Biopsy Specimen; Clinic; Clinical; Dana-Farber Cancer Institute; Data; Decision Making; Diagnosis; Disease; Disease Progression; Gene Chips; Gene Expression; Genes; Gleason Grade for Prostate Cancer; Goals; Indolent; Institutes; Link; Malignant Neoplasms; Malignant neoplasm of prostate; Messenger RNA; Metabolic Marker; Metabolic Pathway; Metabolism; Modeling; Molecular Profiling; Monitor; Operative Surgical Procedures; Outcome; Pathway interactions; Patient Monitoring; Patients; Pattern; Preparation; Prostate; Pyrimidine; Radical Prostatectomy; Research Personnel; Sampling; Serum; Specimen; Testing; Time; Tissue Differentiation; Tissue Sample; Tissues; Tumor Tissue; base; beta-Alanine; clinical application; clinical decision-making; genetic signature; improved; men; metabolomics; outcome prediction; tool; tumor

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.

临床医生和研究人员目前无法在诊断时有足够的信心区分患有惰性前列腺癌 (CaP) 的男性和患有侵袭性疾病的男性。目前，致命性 CaP 的最强预测指标是格里森评分。利用基因表达阵列数据，我们之前鉴定了 157 个基因 mRNA 特征，可以区分高格里森评分和低格里森评分。该特征显着改善了临床异质性格里森评分 7 的男性致命疾病的预测。该特征可能具有临床实用性，但在将其应用于患者之前，必须进一步完善，然后在活检标本中进行测试，以确定预测准确性是否足以影响诊断时的治疗决策。这项 mRNA 研究还确定了高级别和低级别疾病中差异丰富的代谢途径，为可能构成 CaP 分化和临床进展的生物学机制提出了假设。由于不同类型的生物数据可能会添加到 mRNA 签名中并提供不同的生物信息，因此值得进一步研究已确定的代谢途径。因此，我们建议在我们有希望的表达谱研究结果的基础上，实现以下具体目标：1）准备和测试用于临床的致命疾病的格里森特征 - 为了确定 mRNA 特征是否可以应用于临床，我们将通过在诊断时在活检标本中测试其预测准确性来进一步验证它。我们假设，在格里森评分 7 内，如果专门应用于肿瘤的 3 级或 4 级病灶，则该特征预测致死性疾病的能力可能会提高。 2) 格里森级的代谢组学在肿瘤中作为致死性疾病的预测因子 - 我们的 mRNA 研究确定了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，使用代谢组数据可能会差异富集这些相同的途径；我们假设代谢物本身可能与格里森评分和致命疾病有关。 3）血清中格里森等级的代谢组学作为升级的生物标志物 - 我们假设血清中与格里森等级相关的代谢物可能表明存在活检时未检测到的较高级别肿瘤，并且可以作为监测主动监测患者疾病进展的生物标志物。