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检测改善了前列腺肿瘤的早期检测，增加了诊断的前列腺癌（PCa）发病率，并将新检测到的 PCa 治疗转移到早期阶段。这些成功也引发了对早期 PCa 有效治疗的争议，主要是：（1）通过组织取样错误，在携带小且分布不均的 PCa 的无症状患者中发现非常常见的假阴性活检； (2) 大多数新发现的肿瘤的恶性潜力不确定，活检时 PCa 病理相似，但 PCa 统计数据表明将追踪完全不同的疾病路径。 PCa 诊断和预后方法的更高敏感性/特异性将满足这两个紧迫需求。我们最初的 R01 研究使用高分辨率魔角旋转质子磁共振波谱 (HRMAS 1HMRS)，我们开发该波谱是为了允许完整组织分析并与病理学相关，以便产生概念验证的 PCa 代谢标记物。然后，我们开发了 PCa 代谢组学，并证明 PCa 代谢组学谱可提高 PCa 检测、诊断和表征的准确性。对 PCa 患者的组织学定义的良性前列腺组织进行轮廓分析，使我们能够识别 PCa 病理阶段，并通过显示离域 PCa 代谢组场效应或代谢组场的存在来预测 PCa 复发。这些 PCa 代谢组学领域：1) 产生组织良性组织中 PCa 特征的测量结果，因此可能通过为假阴性活检患者指示 PCa 的存在来减少组织学采样误差，2) 能够预测 PCa 恶性潜能活检呈阳性的患者。因此，PCa 代谢组学领域可能对 PCa 临床做出最显着的贡献，区分侵袭性和惰性疾病，并通过支持主动监测惰性肿瘤的标记物告知治疗策略，或表明患者患有侵袭性 PCa 并需要及时制定辅助治疗。我们最初的 R01 研究的这些重要结果构成了我们更新应用的基础，其中我们建议：（1）系统地研究 PCa 代谢物的空间分布和 PCa 腺体中局部和离域病理起源的代谢组谱，以精确定义 PCa代谢组学领域标记； (2) 使用具有已知临床结果的库存 PCa 组织样本来测试 PCa 生长率、生化复发和治疗反应的 PCa 代谢组学谱预测，以及通过激光捕获显微切割分析与来自这些相同样本的遗传谱相关的不同病理成分和实时定量PCR； (3) 通过纵向患者随访，建立 PCa 代谢物、代谢组学概况和代谢组学领域的预后能力，作为代谢组学标准，通过预测活检阴性患者的 PCa 风险来回答当前 PCa 临床的最终挑战，对活检阳性患者进行主动监测的适宜性。

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?