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: 7738853
• 负责人: Manish Kohli
• 金额: $ 22.05万
• 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/7738853
• 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。尽管最初的治疗以局部阶段的治愈为目的（手术或放射），但大约三分之一的患者将进展至晚期。这已转化为巨大且不断增长的公共卫生负担。当前晚期疾病的临床实践是慢性（终身）雄激素剥夺疗法（ADT）。 ADT 的疗效各不相同，可能持续几个月到几年，然后开始化疗。对于哪些临床特征或测试可预测 ADT 的反应（“预测因素”——决定哪些患者对某些类型的治疗效果良好而不是其他类型的治疗效果良好的因素），医疗实践中缺乏共识，因而存在模糊性。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，可用于检测初始治疗后的早期进展性疾病，但缺乏作为 ADT 预测因素的证据。无法预测 ADT 治疗结果是我们知识库中一个未满足的关键缺口，因为它在临床中的应用对患者管理有直接影响。例如，对于激素无反应的肿瘤类型患者，ADT 很快就会失败，尽早开始积极的化疗激素联合治疗可以提供更长持续时间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而不是连续的方案来避免慢性 ADT 的长期副作用，包括骨质疏松和性欲丧失（ADT 的两种最常见和令人痛苦的副作用）。这一探索性应用将重点关注使用基于蛋白质组学的新型方法来识别 ADT 预测因素的策略。识别生物标志物和开发预测因子的传统方法依赖于对癌症特定阶段的组织/循环中的单个肽/蛋白质的评估。充其量，这一策略的成功有限，因为 ADT 反应涉及多种病理肿瘤途径，这降低了任何一种候选蛋白质/肽的重要性。我们建议使用二维电泳与质谱分析相结合作为评估代表肿瘤-宿主-治疗相互作用的多个基于血清的生物变量的平台。为了进行这项探索性蛋白质组学研究，我们将收集从前列腺癌患者身上获得的一组独特的、注释良好的临床研究样本。 PI (M Kohli) 以前具有进行临床蛋白质组学研究的经验，并且专门负责收集癌症蛋白质组学的高质量临床样本，以开发基于蛋白质组学的 ADT 预测分类器。该应用的目的包括对两个主要群体的蛋白质组进行比较分析，包括：开始 ADT 之前和之后三到四个月的癌症患者（队列 1）；另一个癌症患者队列由对 ADT 的短期反应和对 ADT 的持续且延长的反应时间组成（队列 -2）。与三至四个月 ADT 反应以及短期或持续 ADT 反应持续时间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素模型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且不断增加的公共卫生负担。目前该阶段疾病的治疗实践是激素疗法。该项目试图专注于设计工具来预测激素治疗对前列腺癌患者的疗效，因为这些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。