Characterizing Prostate Cancer By ex vivo MRS Signatures

通过离体 MRS 特征表征前列腺癌

基本信息

批准号：
9248210
负责人：
Leo L Cheng
金额：
$ 55.64万
依托单位：
MASSACHUSETTS GENERAL HOSPITAL
依托单位国家：
美国
项目类别：
财政年份：
2006
资助国家：
美国
起止时间：
2006-09-27 至 2019-03-31
项目状态：
已结题

来源：
https://reporter.nih.gov/project-details/9248210
关键词：
Address Adjuvant Therapy African American Age Benign Biochemical Biological Biopsy Blood Screening Cancer Detection Cancer Diagnostics Cancer Patient Cancerous Clinic Clinical Clinical Management Diagnosis Diagnostic Errors Dimensions Disease Early Diagnosis Enzymes Evaluation Exploratory/Developmental Grant for Diagnostic Cancer Imaging Fresh Tissue Funding Gland Gleason Grade for Prostate Cancer Growth Histologic Histology Human Incidence Indolent Institution Location Magic Magnetic Resonance Spectroscopy Malignant - descriptor Malignant Neoplasms Malignant neoplasm of prostate Maps Measures Messenger RNA Metabolic Metabolic Marker Operative Surgical Procedures Outcome PSA Velocity Pathologic Pathology Patient Recruitments Patient-Focused Outcomes Patients Process Prospective Studies Prostate Prostate-Specific Antigen Prostatectomy Prostatic Neoplasms Protocols documentation Protons Quality of life Recurrence Resolution Sampling Sampling Errors Sensitivity and Specificity Serum Site Spatial Distribution Structure of base of prostate Survival Rate Techniques Testing Time Tissue Sample Tissues Translations Work androgen deprivation therapy cancer recurrence cancer risk cancer statistics cancer therapy clinically significant follow-up genetic profiling histological specimens human study improved individual patient laser capture microdissection metabolomics neoplastic novel diagnostics pre-clinical prognostic public health relevance response sample collection success treatment response treatment strategy tumor tumor growth

项目摘要

DESCRIPTION (provided by applicant): Serum prostate specific antigen testing improved early detection of prostate tumors, increased diagnosed prostate cancer (PCa) incidence, and shifted newly detected PCa treatment to earlier stages. These successes also generated controversies for effective management of earlier-stage PCa, chiefly: (1) the all-too-common false-negative biopsy finding through tissue sampling errors in asymptomatic patients who harbor small, heterogeneously distributed PCa; and (2) the uncertain malignant potential of most newly detected tumors, with PCa pathologies similar at biopsy but which PCa statistics indicate will trace drastically different disease paths. Greater sensitivity/specificity for PCa diagnostic and prognostic approaches would address both these urgent needs. Our original R01 studies used high resolution magic-angle-spinning proton magnetic resonance spectroscopy (HRMAS 1HMRS), which we developed to permit intact tissue analysis and correlation with pathology, in order to produce proof-of-concept PCa metabolic markers. We then developed PCa metabolomics and demonstrated that PCa metabolomic profiles improve accuracy in PCa detection, diagnosis, and characterization. Profile analyses of histologically-defined benign prostate tissue from PCa patients allowed us to identify PCa pathological stage and predict PCa recurrence by showing the existence of delocalized PCa metabolomic field-effects, or metabolomic fields. These PCa metabolomic fields: 1) yield measures of PCa signatures in histo-benign tissue and thus are likely to reduce histological sampling errors by indicating PCa presence for patients with false-negatives biopsies, and 2) have the capacity to predict PCa malignant potential for patients with positive biopsies. Thus PCa metabolomic fields are likely to contribute most significantly to the PCa clinic by distinguishing aggressive from indolent disease and informing treatment strategies through markers that support active surveillance for indolent tumors or suggest that the patient harbors an aggressive PCa and needs timely institution of adjuvant therapies. These significant outcomes from our original R01 studies comprise the basis for our renewal application, in which we propose: (1) to systematically investigate spatial distributions of PCa metabolites and metabolomic profiles localized at and delocalized beyond their pathological origins in PCa glands to precisely define PCa metabolomic field markers; (2) to use banked PCa tissue samples with known clinical outcomes to test PCa metabolomic profile predictions of PCa growth rate and biochemical recurrence and therapy response, as well as to analyze different pathological components associated with genetic profiles from these same samples via laser capture microdissection and real-time quantitative PCR; and (3) to establish, through longitudinal patient follow-up, the prognostic ability of PCa metabolites, metabolomic profiles, and metabolomic fields as metabolomic criteria that answer the ultimate challenges of the current PCa clinic by predicting PCa risk for biopsy-negative patients and the suitability of entering active surveillance for biopsy-positive patients.

描述（由申请人提供）：血清前列腺特异性抗原测试改善了对前列腺肿瘤的早期检测，诊断的前列腺癌（PCA）发病率增加，并将新近检测到的PCA治疗转移到了早期阶段。这些成功还引起了有效管理早期PCA的争议，主要是：（1）在无症状，无症状，异质分布的PCA的无症状患者中，通过组织采样误差发现了非常普通的假阴性活检；（2）大多数新检测到的肿瘤的不确定恶性潜力，活检时PCA病理相似，但PCA统计数据表明将痕迹痕迹不同。对PCA诊断和预后方法的更高敏感性/特异性将满足这两个紧急需求。我们的原始R01研究使用了高分辨率旋转质子磁共振光谱（HRMAS 1HMR），我们开发出来允许完整的组织分析和与病理相关，以产生概念验证PCA代谢标记。然后，我们开发了PCA代谢组学，并证明PCA代谢组谱提高了PCA检测，诊断和表征的准确性。来自PCA患者的组织学定义的良性前列腺组织的概况分析使我们能够通过显示DeLocalizatization PCA代谢组现场效应或代谢组领域的存在来鉴定PCA病理阶段并预测PCA复发。这些PCA代谢组领域：1）在组织固定组织中PCA特征的产量度量，因此可能通过表明有假阴性活检的患者的PCA存在来减少组织学抽样误差，而2）具有预测积极生动物患者的PCA恶性肿瘤的能力。因此，PCA代谢组学领域可能通过区分侵略性与顽固疾病并通过标志物为治疗策略提供了可对PCA诊所的贡献，这些标志是支持对顽固的肿瘤进行主动监测的，或暗示患者具有积极的PCA并需要及时辅助治疗疗法。我们原始R01研究中的这些重要结果包括我们更新应用的基础，我们提出：（1）系统地研究PCA代谢物的空间分布和在PCA启发中定位于PCA胶质中的病理学原理的空间分布，以精确定义PCA PCA代谢性场均高素质磁场标记；（2）使用带有已知临床结果的库PCA组织样品来测试PCA代谢组学概况的预测PCA生长速率和生化复发和治疗反应的预测，以及分析通过激光捕获的微型分解和实时定量PCR，分析与这些相同样品的遗传谱相关的不同病理成分；（3）通过纵向患者的随访确定PCA代谢产物，代谢组分子特征和代谢组领域的预后能力作为代谢组学标准，这些标准通过预测PCA诊所的最终挑战，通过预测PCA风险风险对生物疾病的患者的风险风险患者和对活跃的患者的适用性进行了适应。

项目成果

期刊论文数量（14）

专著数量（0）

科研奖励数量（0）

会议论文数量（0）

专利数量（0）

Applications of high-resolution magic angle spinning MRS in biomedical studies II-Human diseases.

高分辨率魔角旋转MRS在生物医学研究中的应用II-人类疾病

DOI：
10.1002/nbm.3784
发表时间：
2017-11
期刊：
NMR in biomedicine
影响因子：
2.9
作者：
Dietz C;Ehret F;Palmas F;Vandergrift LA;Jiang Y;Schmitt V;Dufner V;Habbel P;Nowak J;Cheng LL
通讯作者：
Cheng LL

Metabolomic imaging of prostate cancer with magnetic resonance spectroscopy and mass spectrometry.

DOI：
10.1007/s00259-013-2379-x
发表时间：
2013-07
期刊：
EUROPEAN JOURNAL OF NUCLEAR MEDICINE AND MOLECULAR IMAGING
影响因子：
9.1
作者：
Spur, Eva-Margarete;Decelle, Emily A.;Cheng, Leo L.
通讯作者：
Cheng, Leo L.

Metabolomic Prediction of Human Prostate Cancer Aggressiveness: Magnetic Resonance Spectroscopy of Histologically Benign Tissue.

DOI：
10.1038/s41598-018-23177-w
发表时间：
2018-03-26
期刊：
Scientific reports
影响因子：
4.6
作者：
Vandergrift LA;Decelle EA;Kurth J;Wu S;Fuss TL;DeFeo EM;Halpern EF;Taupitz M;McDougal WS;Olumi AF;Wu CL;Cheng LL
通讯作者：
Cheng LL

Magnetic resonance spectroscopy: A promising tool for the diagnostics of human prostate cancer?