A Proteomics Approach for Identifying Predictive Factors to Androgen Deprivation

描述（由申请人提供）：前列腺癌是美国男性癌症相关发病率和死亡率的主要原因。尽管最初的治疗目的是局部治疗（手术或放疗），但大约三分之一的患者会进展到晚期。这已转化为日益严重的公共卫生负担。目前晚期疾病的临床实践是慢性（终身）雄激素剥夺治疗（ADT）。对ADT反应的疗效是可变的，可能持续几个月到几年，在此期间引入化疗。在医学实践中，对于哪些临床特征或测试可以预测ADT的疗效，缺乏共识，因此存在歧见（“预测因素”-决定哪些患者接受某些类型的治疗效果良好而不接受其他类型治疗的因素）。血清前列腺特异性抗原（PSA）是前列腺癌中最著名的生物标志物，在初始治疗后可用于检测早期进展性疾病，但缺乏作为ADT预测因素的证据。由于ADT在临床中的应用直接影响到患者的管理，因此无法预测ADT的治疗结果是我们知识储备中一个未被满足的关键缺口。例如，对于激素无反应的肿瘤类型患者，ADT很快就会失败，早期开始积极的化疗-激素联合治疗可以提供更长的有意义的临床益处。相反，对ADT有反应的患者可以通过间歇性治疗而不是连续治疗来避免慢性ADT的长期副作用，包括骨质疏松症和性欲减退，这是ADT最常见和最令人痛苦的两种副作用。这个探索性的应用将集中在使用一种新的基于蛋白质组学的方法来识别ADT预测因素的策略上。识别生物标志物和开发预测因子的传统方法依赖于评估癌症特定阶段组织/循环中的单个肽/蛋白质。在最好的情况下，这种策略的成功是有限的，因为多种病理肿瘤途径参与了ADT反应，这降低了任何一种候选蛋白/肽的重要性。我们建议使用双向电泳结合质谱分析作为评估多种基于血清的肿瘤-宿主-治疗相互作用的生物学变量的平台。为了进行这项探索性的蛋白质组学研究，我们将从前列腺癌患者中收集一组独特的、有良好注释的临床研究标本。PI （M Kohli）有进行临床蛋白质组学研究的经验，并且特别适合为癌症蛋白质组学收集高质量的临床标本，用于开发基于蛋白质组学的ADT预测分类器。该应用程序的目的包括在两个主要队列中对蛋白质组进行比较分析，包括；ADT开始前和开始后3 - 4个月的癌症患者（队列1）；和一个单独的癌症患者队列，包括对ADT的短时间反应和对ADT的持续和延长的反应时间（队列2）。与3 - 4个月ADT反应和短期或持续ADT反应相关的一致鉴定和表征的生物标志物将在未来前瞻性设计的预测因子建模临床试验中进行评估。公共卫生相关性：晚期前列腺癌是一个显著且日益加重的公共卫生负担。目前这一阶段的治疗方法是激素治疗。该项目试图集中设计工具来预测激素治疗前列腺癌患者的疗效，因为这种知识有可能提高接受激素治疗的患者群体的癌症和治疗相关发病率。

DESCRIPTION (provided by applicant): Prostate cancer is a leading cause of cancer related morbidity and mortality in US males. Despite initial treatments with curative intent for localized stage (surgery or radiation) approximately one third patients will progress to advanced stages. This has translated into a significant and growing public health burden. Current clinical practice for advanced stage disease is chronic (lifelong) androgen deprivation therapy (ADT). The efficacy of response to ADT is variable and may last from a few months to several years at which time chemotherapy is introduced. A lack of consensus with resultant ambiguity exists in medical practice as to what clinical features or tests predict response to ADT ("Predictive factor"- A factor determining which patients will do well with some types of treatment and not others). The most well known biomarker in prostate cancer, serum prostatic specific antigen (PSA) is useful in detecting early progressive disease after initial treatments but lacks evidence as a predictive factor for ADT. The inability to predict ADT treatment outcomes is an unmet critical gap in our fund of knowledge as its application in the clinic has a direct impact on patient management. For example, in hormonally unresponsive tumor type patients destined to fail ADT quickly, an earlier initiation of aggressive chemo-hormonal combination treatments could provide longer durations of meaningful clinical benefit. Conversely patients harboring a profile responsive to ADT may avoid long-term side effects of chronic ADT including osteoporosis and loss of sexual libido, the two most common and distressing side effects of ADT, by undergoing an intermittent schedule rather than continuous. This exploratory application will focus on an identification strategy for ADT predictive factors using a novel proteomics-based approach. The traditional approach in identifying biomarkers and developing predictive factors has relied on evaluation of a single peptide/protein in tissue/circulation in a cancer-specific stage. At best, this strategy has had limited success since multiple pathological tumor pathways are involved in ADT response which diminish the significance of any one candidate protein/peptide. We propose using two-dimensional electrophoresis coupled with mass spectrometry analysis as a platform for evaluating multiple serum-based biological variables representative of tumor-host-treatment interactions. For conducting this exploratory proteomic research we will collect a unique set of well annotated clinical research specimens obtained from prostate cancer patients. The PI (M Kohli) has previous experience in conducting clinical proteomic research studies, and is specifically attuned to collecting high quality clinical specimens for cancer proteomics for developing proteomic based predictive classifiers of ADT. The application aims include performing comparative analyses of the proteome in two main cohorts including; cancer patients before and three to four month post initiation of ADT (cohort-1); and a separate cohort of cancer patients consisting of a short duration response to ADT and a sustained and prolonged response duration to ADT (cohort -2). Consistently identified and characterized biomarker(s) associated with three to four month ADT response and short or sustained duration of ADT response will be then be evaluated in prospectively designe predictive factor modeling clinical trials in future. PUBLIC HEALTH RELEVANCE: Advanced prostate cancer is a significant and increasing public health burden. Current treatment practice for this stage of the disease is with hormonal therapy. This project attempts to focus on devising tools to predict the efficacy of hormonal treatments in prostate cancer patients, as this knowledge has potential to elevate cancer and treatment related morbidity in patient populations undergoing hormonal treatments.