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; 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相关发病率和死亡率的主要原因。尽管对局部阶段（手术或辐射）的治疗意图进行了治疗，但大约三分之一的患者仍会发展为晚期阶段。这已经转化为巨大的公共卫生负担。晚期疾病的当前临床实践是慢性（终身）雄激素剥夺疗法（ADT）。对ADT的反应的功效是可变的，可能会持续几个月到几年，在此期间引入化疗。关于哪些临床特征或测试可以预测对ADT的反应（确定哪些患者对某些类型的治疗而不是其他治疗方法，而不是其他患者），对哪些临床特征或测试预测了哪些临床特征或测试，就缺乏与歧义的共识。血清前列腺特异性抗原（PSA）中最知名的生物标志物在初次治疗后可用于检测早期进行性疾病，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差距，因为其在诊所中的应用对患者管理有直接影响。例如，在荷尔蒙无反应性的肿瘤型患者中，注定会迅速失败的患者，较早的积极化学荷尔蒙组合治疗的开始可能会提供更长的有意义的临床益处。相反，具有响应ADT的患者可以避免长期ADT的长期副作用，包括骨质疏松症和性欲丧失，这是ADT的两个最常见和最令人痛苦的副作用，通过进行间歇性时间表而不是连续的时间表。这种探索性应用将使用基于蛋白质组学的新方法来关注ADT预测因素的识别策略。在癌症特异性阶段，鉴定生物标志物和发展预测因素的传统方法依赖于对组织/循环中单个肽/蛋白质的评估。充其量，这种策略取得了有限的成功，因为多种病理肿瘤途径参与ADT反应，从而降低了任何一种候选蛋白/肽的重要性。我们建议使用二维电泳与质谱分析相结合的平台，以评估代表肿瘤宿主处理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蛋白质组学研究，我们将收集一组从前列腺癌患者获得的独特注释的临床研究标本。 PI（M KOHLI）以前在进行临床蛋白质组学研究方面具有以前的经验，并且专门针对为癌症蛋白质组学收集高质量的临床标本，以开发ADT的基于蛋白质组学的预测分类器。应用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：癌症患者以前开始，在ADT开始后三到四个月（队列-1）；另一组癌症患者包括对ADT持续时间短的持续时间以及对ADT的持续和延长反应持续时间的癌症患者（队列-2）。一致地鉴定并表征了与三到四个月ADT响应相关的生物标志物，并且将在未来的前瞻性设计预测因素建模临床试验中评估ADT响应和ADT响应的短期或持续时间。公共卫生相关性：晚期前列腺癌是一种重大且增加的公共卫生负担。该疾病这一阶段的当前治疗实践是荷尔蒙治疗。该项目试图专注于设计工具来预测荷尔蒙治疗在前列腺癌患者中的疗效，因为该知识有可能提高癌症和治疗相关的发病率，而患者接受激素治疗。