Screening for Prostate Cancer

Recent advances in metabolomics in oncology

The burden of cancer is growing worldwide and with it a more desperate need for better tools to detect, diagnose and monitor the disease is required. It is well recognized that cancer cells are characterized by distinct metabolic perturbations. The metabolomics approach involves the comprehensive profiling of the full complement of low MW compounds in a biological system. By applying advanced analytical and statistical tools, the 'metabolome' is mined for biomarkers that are associated with the state of cancer. This review presents an introduction to the main analytical platforms used in metabolomics analyses, such as NMR spectroscopy and MS, as well as the statistical tools used to mine these datasets. The discussion focuses on 'state-of-the-art' investigations on the four cancer types that have received the most study by metabolomics, namely breast, prostate, colorectal and liver cancer.

The metabolites citrate, myo-inositol, and spermine are potential age-independent markers of prostate cancer in human expressed prostatic secretions

OBJECTIVES

Due to specific physiological functions, prostatic tissues and fluids have unique metabolic profiles. In this study, proton nuclear magnetic resonance spectroscopy ((1)H-NMRS) is used to assess potential metabolic markers of prostate cancer (PCa) in human expressed prostatic secretions (EPS).

METHODS

Metabolic profiles of EPS from 52 men with PCa and from 26 healthy controls were analyzed using quantitative (1)H-NMRS. The metabolites quantified included citrate, spermine, myo-inositol, lactate, alanine, phosphocholine, glutamine, acetate, and hydroxybutyrate. Logistic regression (LR) was used to model the risk of PCa based on metabolite concentrations while adjusting for age.

RESULTS

The average age of the EPS donors with PCa was 58.0+/-7.0 years and 52.2+/-12.1 for the healthy donors. The median Gleason score for the men with PCa was 7 (range 5-9). The LR models indicated that the absolute concentrations of citrate, myo-inositol, and spermine were highly predictive of PCa and inversely related to the risk of PCa. The areas under the receiver operating characteristic curves (AUROC) for citrate, myo-inositol and spermine were 0.89, 0.87, and 0.79, respectively. At 90% sensitivity, these metabolites had specificities of 74%, 51%, and 34%, respectively. The LR analysis indicated that absolute levels of these three metabolites were independent of age.

CONCLUSIONS

The results indicate that citrate, myo-inositol and spermine are potentially important markers of PCa in human EPS. Further, the absolute concentrations of these metabolites in EPS appear to be independent of age, increasing the potential utility of these markers due to elimination of age as a confounding variable.

Prognostic value of serum markers for prostate cancer

The incidence of prostate cancer has increased dramatically during the last 10-15 years and it is now the commonest cancer in males in developed countries. The increase is mainly caused by the increasing use of opportunistic screening or case-finding based on the use of prostate-specific antigen (PSA) testing in serum. With this approach, prostate cancer is detected 5-10 years before giving rise to symptoms and on average 17 years before causing the death of the patient. While this has led to detection of prostate cancer at a potentially curable stage, it has also led to substantial overdiagnosis, i.e. detection of cancers that would not surface clinically in the absence of screening. A major challenge is thus to identify the cases that need to be treated while avoiding diagnosing patients who will not benefit from being diagnosed and who will only suffer from the stigma of being a cancer patient. It would be useful to have prognostic markers that could predict which patients need to be diagnosed and which do not. Ideally, it should be possible to measure these markers using non-invasive techniques, i.e. by means of serum or urine tests. As it is very useful for both early diagnosis and monitoring of prostate cancer, PSA is considered the most valuable marker available for any tumor. Although the prognostic value of PSA is limited, measurement of the proportion of free PSA has improved the identification of patients with aggressive disease. Furthermore, the rate of increase in serum PSA reflects tumor growth rate and prognosis but, due to substantial physiological variation in serum PSA, reliable estimation of the rate of PSA increase requires follow-up for at least 2 years. Algorithms based on the combined use of free and total PSA and prostate volume in logistic regression and neural networks can improve the diagnostic accuracy for prostate cancer, and assays for minor subfractions of PSA and other new markers may provide additional prognostic information. Markers of neuroendocrine differentiation are useful for the monitoring of androgen-independent disease and various bone markers are useful in patients with metastatic disease.