Energy Balance-Related Hormones & Prostate Cancer Incidence & Progression

描述（由申请人提供）：最近的证据证实，正能量平衡，如肥胖估计，强烈影响前列腺癌的发生。然而，能量平衡如何影响和被各种代谢激素和交感神经系统活动（SNS）影响的复杂性增加了能量平衡在这种癌症中的作用的复杂性。此外，能量平衡对前列腺癌发病率和进展的影响可能有所不同。第三个复杂因素是早发性和晚发性前列腺癌可能有不同的病因。根据我们的初步数据和其他研究，我们提出了三种不同的模式，即能量平衡相关变量影响前列腺癌：模式1：与肥胖和缺乏体育活动相关的代谢改变，包括高胰岛素和瘦素，低脂联素水平，增加前列腺癌进展的风险。此外，与肥胖相关的低睾酮水平可能会导致更多的低分化癌症，从而导致更差的预后。模式2：较高的胰岛素样生长因子（IGF-1）水平影响高分化至中度分化前列腺癌的进展，而在IGF-1信号通路中发生分子改变并因此上调IGF-1信号的癌症对循环IGF-1水平相对无反应。模式3：年轻男性具有与SNS活动相关的固有代谢表型，将高能量摄入与体重增加分离，并与慢性前列腺炎/慢性盆腔疼痛综合征前列腺炎相关，前列腺癌的风险增加。我们将在健康专业人员随访研究（HPFS）中讨论能量平衡可能影响前列腺癌风险的这三种模式，该研究是1986年基线时47,000名无癌症男性的队列。我们预计到2010年将有6085例前列腺癌新病例，其中包括668例死亡病例，从1900例前列腺切除术中获得肿瘤块。HPFS中暴露数据的来源是问卷调查，包括饮食、人体测量、活动、药物使用和血浆样本。结果数据将基于(1)病历和病理报告审查，(2)与疾病进展相关的组织阻断标志物。将采用分层分析和多变量分析来控制混杂因素。我们的最终目标是更好地了解体重、相关饮食和其他可改变因素如何影响不同阶段的前列腺癌发生。公共卫生相关性：我们的初步数据和其他数据表明，能量平衡相关变量影响前列腺癌。为了帮助减少文献中关于能量平衡和前列腺癌风险的明显不一致，我们假设了三种不同的模式，即能量平衡变量可能影响前列腺癌风险。这三种模式也有助于解释前列腺癌流行病学的一些明显的年龄模式。我们建议在卫生专业人员随访研究（HPFS）中研究这些模式，该研究是1986年基线时47,000名无癌症男性的队列。我们预计到2010年将有6085例前列腺癌新病例，其中包括668例死亡病例，从1900例前列腺切除术中获得肿瘤块。我们的最终目标是更好地了解体重、相关饮食和其他可改变因素如何在不同阶段影响前列腺癌的发生，重点是预防这些危险因素引起的发病率和死亡率。

DESCRIPTION (provided by applicant): Recent evidence has confirmed that positive energy balance, as estimated by obesity, strongly influences prostate carcinogenesis. However, the complexity of how energy balance influences, and is influenced, by various metabolic hormones and sympathetic nervous system activity (SNS) adds considerable complexity to the role of energy balance for this cancer. Further, the influences of energy balance may differ for prostate cancer incidence and progression. A third complicating factor is that there may be distinct etiologies for early- onset and late-onset prostate cancers. We propose three distinct patterns, suggested by our preliminary data and other studies, whereby energy balance related variables influence prostate cancer: Pattern 1: Metabolic alterations associated with obesity and lack of physical activity, including high insulin and leptin, and low adiponectin levels, increase risk of prostate cancer progression. Further, the low testosterone levels associated with obesity may contribute to more poorly differentiated cancers and thus a worse prognosis. Pattern 2: Higher insulin-like growth factor (IGF-1) levels influence progression of well- to moderately-well differentiated prostate cancers, whereas cancers that have molecular alterations in the IGF-1 signaling pathway and hence upregulated IGF-1 signaling are relatively unresponsive to circulating IGF-1 levels. Pattern 3: Younger men with an inherent metabolic phenotype related to SNS activity that disassociates high energy intake from weight gain and which is associated with chronic prostatitis/chronic pelvic pain syndrome prostatitis are at increased risk of prostate cancer. We will address these three patterns whereby energy balance may influence prostate cancer risk in the Health Professionals Follow-up Study (HPFS), a cohort of the 47,000 men free of cancer at baseline in 1986. We project 6,085 new cases of prostate cancer by 2010, including 668 fatal cases, with tumor blocks from over 1,900 prostatectomy cases. The sources of the exposure data in the HPFS are questionnaire, including diet, anthropometric measures, activity, medication use, and plasma samples. The outcome data will be based on (1) medical record and pathology report review, and (2) tissue block markers that correlate with disease progression. Stratified analysis and multivariate analysis will be used to control for confounding factors. Our ultimate goal is to better understand how body weight, and related dietary and other modifiable factors, influence prostate carginogenesis at various stages. PUBLIC HEALTH RELEVANCE: Our preliminary data and other data suggest that energy balance-related variables influence prostate cancer. To help reduce the apparent inconsistencies in the literature for energy balance and prostate cancer risk, we hypothesize three distinct patterns whereby energy balance variables may influence prostate cancer risk. These three patterns would also help explain some of the apparent age patterns of prostate cancer epidemiology. We propose to study these patterns in the Health Professionals Follow-up Study (HPFS), a cohort of the 47,000 men free of cancer at baseline in 1986. We project 6,085 new cases of prostate cancer by 2010, including 668 fatal cases, with tumor blocks from over 1,900 prostatectomy cases. Our ultimate goal is to better understand how body weight, and related dietary and other modifiable factors, influence prostate carcinogenesis at various stages with a focus on prevention of morbidity and mortality from these risk factors.