A Proteomics Approach for Identifying Predictive Factors to Androgen Deprivation

确定雄激素剥夺预测因素的蛋白质组学方法

• 批准号: 7894667
• 负责人: Manish Kohli
• 金额: $ 17.14万
• 依托单位: MAYO CLINIC ROCHESTER
• 依托单位国家: 美国
• 财政年份: 2009
• 资助国家: 美国
• 起止时间: 2009-07-16 至 2011-06-30
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/7894667
• 关键词: A-factor (Streptomyces); Accounting; Adverse effects; Aftercare; Androgen Therapy; Androgens; Antigens; Beds; Behavior; Biological; Biological Markers; Blood Circulation; Cancer Control; Cancer Etiology; Cancer Patient; Cessation of life; Chemotherapy-Oncologic Procedure; Chronic; Clinic; Clinical; Clinical Research; Clinical Treatment; Clinical Trials; Consensus; Coupled; Detection; Development; Diagnosis; Disease; Disease Management; Disease Progression; Distress; Early treatment; Electrophoresis; Evaluation; Failure; Funding; Future; Heterogeneity; Hormonal; Knowledge; Lead; Length; Libido; Life; Malignant Neoplasms; Malignant neoplasm of prostate; Mass Spectrum Analysis; Medical; Modeling; Monitor; Morbidity - disease rate; Operative Surgical Procedures; Osteoporosis; Pathway interactions; Patient Representative; Patients; Pattern; Peptides; Pharmaceutical Preparations; Population; Predictive Factor; Progressive Disease; Prostate; Prostatic; Protein Fingerprints; Proteins; Proteome; Proteomics; Public Health; Radiation; Recurrence; Relapse; Research; Risk; Schedule; Serum; Specimen; Staging; Subgroup; Technology; Testing; Testosterone; Therapeutic; Time; Tissues; Translating; Treatment outcome; Treatment-Related Cancer; Tumor Biology; base; cancer care; cancer proteomics; chemotherapy; clinical care; clinical practice; cohort; comparative; deprivation; experience; factor A; hormone therapy; host neoplasm interaction; male; mortality; novel; palliation; patient population; public health relevance; research study; response; success; tool; treatment effect; tumor; two-dimensional

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.

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治愈局部阶段（手术或放疗），但约三分之一的患者将进展到晚期。这已经转化为一个巨大的和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（终身）雄激素剥夺治疗（ADT）。ADT的疗效是可变的，可能持续几个月到几年，此时引入化疗。在医疗实践中，对于哪些临床特征或测试可预测ADT的反应（“预测因素”-确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治疗中表现良好的因素），缺乏共识，导致模棱两可。作为前列腺癌中最知名的生物标志物，血清前列腺特异性抗原（PSA）可用于检测初始治疗后的早期进展性疾病，但缺乏证据作为ADT的预测因素。无法预测ADT治疗结果是我们知识基金中未满足的关键差距，因为其在临床中的应用对患者管理有直接影响。例如，在注定ADT快速失败的无反应肿瘤类型患者中，早期开始积极的化学-激素联合治疗可以提供更长的持续时间的有意义的临床获益。相反，对ADT有反应的患者可能会避免长期ADT的副作用，包括骨质疏松症和性欲丧失，这是ADT的两种最常见和最令人痛苦的副作用，通过接受间歇性时间表而不是连续性时间表。这种探索性的应用将集中在ADT预测因素的识别策略，使用一种新的蛋白质组学为基础的方法。鉴定生物标志物和开发预测因子的传统方法依赖于在癌症特异性阶段中对组织/循环中的单个肽/蛋白质的评价。最好的情况下，这种策略的成功有限，因为ADT应答中涉及多种病理肿瘤途径，这降低了任何一种候选蛋白/肽的意义。我们建议使用二维电泳结合质谱分析作为平台，用于评估代表肿瘤-宿主-治疗相互作用的多个基于血清的生物变量。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注释良好的临床研究标本，这些标本来自前列腺癌患者。PI（M Kohli）具有开展临床蛋白质组学研究的经验，专门负责收集癌症蛋白质组学的高质量临床标本，以开发基于蛋白质组学的ADT预测分类器。本申请的目的包括对两个主要队列中的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）;以及由ADT短期缓解和ADT持续和延长缓解持续时间组成的单独癌症患者队列（队列2）。随后，将在未来的前瞻性设计预测因素建模临床试验中评价与3 - 4个月ADT缓解和ADT缓解持续时间短或持续相关的一致性鉴定和表征的生物标志物。公共卫生相关性：晚期前列腺癌是一个重大的和日益增加的公共卫生负担。目前对这一阶段的疾病的治疗实践是激素治疗。该项目试图专注于设计工具来预测激素治疗在前列腺癌患者中的疗效，因为这些知识有可能提高接受激素治疗的患者人群中的癌症和治疗相关发病率。