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.

A decade in prostate cancer: from NMR to metabolomics.

Over the past 30 years, continuous progress in the application of nuclear magnetic resonance (NMR) spectroscopy and magnetic resonance spectroscopic imaging (MRSI) to the detection, diagnosis and characterization of human prostate cancer has turned what began as scientific curiosity into a useful clinical option. In vivo MRSI technology has been integrated into the daily care of prostate cancer patients, and innovations in ex vivo methods have helped to establish NMR-based prostate cancer metabolomics. Metabolomic and multimodality imaging could be the future of the prostate cancer clinic--particularly given the rationale that more accurate interrogation of a disease as complex as human prostate cancer is most likely to be achieved through paradigms involving multiple, instead of single and isolated, parameters. The research and clinical results achieved through in vivo MRSI and ex vivo NMR investigations during the first 11 years of the 21st century illustrate areas where these technologies can be best translated into clinical practice.

Characterizing human cancer metabolomics with ex vivo 1H HRMAS MRS.

Publications of proton high resolution magic angle spinning (1H HRMAS) magnetic resonance spectroscopy (MRS) and its role in identification of metabolic markers for human cancer reported between 2005 and 2009 are reviewed according the anatomic sites of cancer: lung, breast, prostate, brain, colorectal, and cervical. Limited and insufficient screening options for the general public have indicated a need for more advanced tests that can identify and locate cancer at an early stage. 1H HRMAS MRS is a valuable tool that can elucidate relevant biological metabolite information that is being used to distinguish cancer from benign tissue, and even classify types of tumors. Researchers are working to translate this ex vivo spectroscopy information into an in vivo system that could be implemented in cancer clinics. For instance, in the case of lung cancer, the goal is to identify the at risk population through a simple blood test, which would be the first level of screening. From these tests, patients identified as at risk will be able to undergo further non-invasive radiological testing for diagnostic purposes. Not only will this ex vivo technology become a valuable diagnostic tool, it will also provide a way to monitor treatments on an individual basis so they can be adjusted accordingly for the best possible outcome.

Metabolomic imaging for human prostate cancer detection.

As current radiological approaches cannot accurately localize prostate cancer in vivo, biopsies are conducted at random within prostates for patients at risk for prostate cancer, leading to high false-negative rates. Metabolomic imaging can map cancer-specific biomolecular profile values onto anatomical structures to direct biopsy. In this preliminary study, we evaluated five whole prostates removed during prostatectomy from biopsy-proven cancer patients on a 7-tesla human whole-body magnetic resonance scanner. Localized, multi-cross-sectional, multivoxel magnetic resonance spectra were used to construct a malignancy index based on prostate cancer metabolomic profiles obtained from previous intact tissue analyses with a 14-tesla spectrometer. This calculated malignancy index is linearly correlated with lesion size and demonstrates a 93 to 97% overall accuracy for detecting the presence of prostate cancer lesions, suggesting the potential clinical utility of this approach.

Assessing prostate cancer growth with mRNA of spermine metabolic enzymes.

Statistical data from prostate cancer (PCa) clinics indicates that a large patient population discovered by annual prostate specific antigen (PSA) screening may have a latent form of the disease. However, current medical tests cannot differentiate slow from fast growing PCa, resulting in many unnecessary radical treatments and morbidities. It is thus necessary to find new screening tests that enable us to differentiate between fast- and slow-growing tumors. Inspired by the reported functions of spermine in carcinogenesis, we analyzed spermine and mRNA expression levels of rate-limiting enzymes in the spermine metabolic pathway for nine cases of PCa with accurately defined PSA velocity (Vpsa). Using MR spectroscopy, histopathology, laser-capture microdissection and real-time PCR techniques, we analyzed relationships between changes in spermine levels, mRNA expression levels of spermine anabolic and catabolic enzymes and human prostate cancer growth rates represented by serum Vpsa. The expression levels of spermine anabolic enzymes: ornithine decarboxylase (ODC1) and S-adenosylmethionine decarboxylase (AMD1) in benign epithelia surrounding cancer glands was logarithmically reduced with the increase of Vpsa (ODC1, p < 0.016; AMD1, p < 0.048), and antizyme (OAZ1) expression in cancer cells was increased with the increase of Vpsa (p < 0.001). Finally, we observed an inverse correlation between ODC1 and OAZ1 (p < 0.019) measured in cancer cells. These correlations may function to evaluate the aggressiveness of human prostate cancer, and assist patients and clinicians to select appropriate treatment strategies based on biological activities of individual tumors.