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

Prostate cancer alters cellular metabolism through events potentially preceding cancer morphological formation. Magnetic resonance spectroscopy (MRS)-based metabolomics of histologically-benign tissues from cancerous prostates can predict disease aggressiveness, offering clinically-translatable prognostic information. This retrospective study of 185 patients (2002-2009) included prostate tissues from prostatectomies (n = 365), benign prostatic hyperplasia (BPH) (n = 15), and biopsy cores from cancer-negative patients (n = 14). Tissues were measured with high resolution magic angle spinning (HRMAS) MRS, followed by quantitative histology using the Prognostic Grade Group (PGG) system. Metabolic profiles, measured solely from 338 of 365 histologically-benign tissues from cancerous prostates and divided into training-testing cohorts, could identify tumor grade and stage, and predict recurrence. Specifically, metabolic profiles: (1) show elevated myo-inositol, an endogenous tumor suppressor and potential mechanistic therapy target, in patients with highly-aggressive cancer, (2) identify a patient sub-group with less aggressive prostate cancer to avoid overtreatment if analysed at biopsy; and (3) subdivide the clinicopathologically indivisible PGG2 group into two distinct Kaplan-Meier recurrence groups, thereby identifying patients more at-risk for recurrence. Such findings, achievable by biopsy or prostatectomy tissue measurement, could inform treatment strategies. Metabolomics information can help transform a morphology-based diagnostic system by invoking cancer biology to improve evaluation of histologically-benign tissues in cancer environments.

High-resolution magic angle spinning 1H MRS in prostate cancer.

Prostate cancer (PCa) is the most frequently diagnosed malignancy in men worldwide, largely as a result of the increased use of the annual serum prostate-specific antigen (PSA) screening test for detection. PSA screening has saved lives, but it has also resulted in the overtreatment of many patients with PCa because of a limited ability to accurately localize and characterize PCa lesions through imaging. High-resolution magic angle spinning (HRMAS) (1)H MRS has proven to be a strong potential clinical tool for PCa diagnosis and prognosis. The HRMAS technique allows valuable metabolic information to be obtained from ex vivo intact tissue samples and also enables the performance of histopathology on the same tissue specimens. Studies have found that the quantification of individual metabolite levels and metabolite ratios, as well as metabolomic profiles, shows strong potential to improve accuracy in PCa detection, diagnosis and monitoring. Ex vivo HRMAS is also a valuable tool for the interpretation of in vivo results, including the localization of tumors, and thus has the potential to improve in vivo diagnostic tests used in the clinic. Here, we primarily review publications of HRMAS (1)H MRS and its use for the study of intact human prostate tissue.

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

Metabolomic imaging of prostate cancer (PCa) aims to improve in vivo imaging capability so that PCa tumors can be localized noninvasively to guide biopsy and evaluated for aggressiveness prior to prostatectomy, as well as to assess and monitor PCa growth in patients with asymptomatic PCa newly diagnosed by biopsy. Metabolomics studies global variations of metabolites with which malignancy conditions can be evaluated by profiling the entire measurable metabolome, instead of focusing only on certain metabolites or isolated metabolic pathways. At present, PCa metabolomics is mainly studied by magnetic resonance spectroscopy (MRS) and mass spectrometry (MS). With MRS imaging, the anatomic image, obtained from magnetic resonance imaging, is mapped with values of disease condition-specific metabolomic profiles calculated from MRS of each location. For example, imaging of removed whole prostates has demonstrated the ability of metabolomic profiles to differentiate cancerous foci from histologically benign regions. Additionally, MS metabolomic imaging of prostate biopsies has uncovered metabolomic expression patterns that could discriminate between PCa and benign tissue. Metabolomic imaging offers the potential to identify cancer lesions to guide prostate biopsy and evaluate PCa aggressiveness noninvasively in vivo, or ex vivo to increase the power of pathology analysis. Potentially, this imaging ability could be applied not only to PCa, but also to different tissues and organs to evaluate other human malignancies and metabolic diseases.