A Proteomics Approach for Identifying Predictive Factors to Androgen Deprivation

描述(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。尽管最初的治疗意图是局部治疗(手术或放射治疗)，但大约三分之一的患者将进展到晚期。这已经转化为一个重大的、不断增长的公共卫生负担。目前晚期疾病的临床实践是慢性(终生)雄激素剥夺疗法(ADT)。ADT的疗效是可变的，可能持续几个月到几年，在引入化疗的时候。在医疗实践中，对于哪些临床特征或测试可以预测ADT的反应，缺乏共识，因此也存在歧义(“预测因素”--决定哪些患者将在某些类型的治疗中表现良好，而不是其他类型的患者的因素)。作为前列腺癌最著名的生物标志物，血清前列腺特异性抗原(PSA)有助于发现早期进展性疾病，但缺乏证据作为ADT的预测因素。无法预测ADT的治疗结果是我们知识基金中一个尚未填补的关键缺口，因为它在临床上的应用直接影响到患者的管理。例如，在激素反应迟钝的肿瘤型患者中，ADT很快就会失败，更早开始积极的化疗和激素联合治疗可能会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而不是连续地进行治疗，从而避免慢性ADT的长期副作用，包括骨质疏松症和性欲丧失，这是ADT最常见和最令人痛苦的副作用。这一探索性的应用将集中于使用一种新的基于蛋白质组学的方法来识别ADT预测因子的策略。识别生物标记物和开发预测因子的传统方法依赖于在癌症特异性阶段对组织/循环中的单肽/蛋白质进行评估。在最好的情况下，这一策略的成功是有限的，因为ADT反应涉及多个病理肿瘤途径，从而削弱了任何一个候选蛋白质/肽的重要性。我们建议使用二维电泳联用质谱分析作为评估代表肿瘤-宿主-治疗相互作用的多个基于血清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，我们将收集一组独特的、经过良好注释的来自前列腺癌患者的临床研究标本。PI(M Kohli)具有进行临床蛋白质组研究的经验，特别擅长为癌症蛋白质组学收集高质量的临床标本，以开发基于蛋白质组的ADT预测分类器。应用目的包括在两个主要队列中进行蛋白质组的比较分析，其中包括：癌症患者在ADT治疗开始前和三到四个月后(Cohort-1)；以及单独的癌症患者队列，包括对ADT的短期反应和对ADT持续和延长的反应时间(Cohort-2)。一致识别和表征的生物标志物(S)与3-4个月的ADT反应和短期或持续的ADT反应相关，将在未来的前瞻性设计预测因素模拟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重大的且不断增加的公共卫生负担。目前对这一阶段疾病的治疗方法是激素疗法。该项目试图设计工具来预测前列腺癌患者激素治疗的疗效，因为这一知识有可能提高接受激素治疗的患者群体中癌症和治疗相关的发病率。

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.