Urgent need to develop independent biomarkers for functional, diagnostic and prognostic application in oncology research

A novel DNA methylation score accurately predicts death from prostate cancer in men with low to intermediate clinical risk factors

Clinically aggressive disease behavior is difficult to predict in men with low to intermediate clinical risk prostate cancer and methylation biomarkers may be a valuable adjunct for assessing the management of these patients. We set to evaluate the utility of DNA methylation to identify high risk disease in men currently considered as low or intermediate risk. DNA was extracted from formalin-fixed paraffin-embedded transurethral prostate resection tissues collected during the years 1990-96 in a watchful-waiting cohort of men in the UK. The primary end point was death of prostate cancer, assessed by reviewing cancer registry records from 2009. Methylation was quantified by pyrosequencing assays for six genes (HSPB1, CCND2, TIG1, DPYS, PITX2, and MAL) with established biomarker value in prostate cancer. A novel prognostic methylation score was developed by multivariate Cox modelling using the six methylation biomarkers in 385 men with low-and-intermediate clinical risk variables and its prognostic value compared to two previously defined clinically-derived risk scores. Methylation score was the most significant variable in univariate and bivariate analysis in men with low-to-intermediate CAPRA risk score. When combined with CAPRA score the hazard ratio was 2.02; 95% confidence interval, 1.40-2.92. For a methylation score sensitivity of 83% the specificity was 44%, while the maximum achieved sensitivity by CAPRA was 68% at a specificity of 44%. The derived methylation score is a strong predictor of aggressive prostate cancer that could have an important role in directing the management of patients with low-to-intermediate risk disease. The estimated areas under the curve (AUC) at 10 years of follow-up were 0.62 (95% CI: 0.51, 0.70) and 0.74 (95% CI: 0.65, 0.82) for CAPRA, and combined (CAPRA + methylation) risk score (CRS) respectively.

DNA methylation gene-based models indicating independent poor outcome in prostate cancer

BACKGROUND

Prostate cancer has a variable clinical behaviour with frequently unpredictable outcome. DNA methylation plays an important role in determining the biology of cancer but prognostic information is scanty. We assessed the potential of gene-specific DNA methylation changes to predict death from prostate cancer in a cohort of untreated men in the UK.

METHODS

This was a population-based study in which cases were identified from six cancer registries in Great Britain. DNA was extracted from formalin-fixed paraffin wax-embedded transurethral prostate resection tissues collected during 1990-96 from men with clinically-localised cancer who chose not to be treated for at least 6 months following diagnosis. The primary end point was death from prostate cancer. Outcomes were determined through medical records and cancer registry records. Pyrosequencing was used to quantify methylation in 13 candidate genes with established or suggested roles in cancer. Univariate and multivariate Cox models were used to identify possible predictors for prostate cancer-related death.

RESULTS

Of 367 men, 99 died from prostate cancer during a median of 9.5 years follow-up (max = 20). Univariately, 12 genes were significantly associated with prostate cancer mortality, hazard ratios ranged between 1.09 and 1.28 per decile increase in methylation. Stepwise Cox regression modelling suggested that the methylation of genes HSPB1, CCND2 and DPYS contributed objective prognostic information to Gleason score and PSA with respect to cancer-related death during follow-up (p = 0.006).

CONCLUSION

Methylation of 13 genes was analysed in 367 men with localised prostate cancer who were conservatively treated and stratified with respect to death from prostate cancer and those who survived or died of other causes. Of the 13 genes analysed, differential methylation of HSPB1, CCND2 and DPYS provided independent prognostic information. Assessment of gene-methylation may provide independent objective information that can be used to segregate prostate cancers at diagnosis into predicted behavioural groups.

PRKC-ζ Expression Promotes the Aggressive Phenotype of Human Prostate Cancer Cells and Is a Novel Target for Therapeutic Intervention

We show protein kinase C-zeta (PKC-ζ) to be a novel predictive biomarker for survival from prostate cancer (P < 0.001). We also confirm that transcription of the PRKC-ζ gene is crucial to the malignant phenotype of human prostate cancer. Following siRNA silencing of PRKC-ζ in PC3-M prostate cancer cells, stable transfectant cell line si-PRKC-ζ-PC3-M(T1-6) is phenotypically nonmalignant in vitro and in vivo. Genome-wide expression analysis identified 373 genes to be differentially expressed in the knockdown cells and 4 key gene networks to be significantly perturbed during phenotype modulation. Functional interconnection between some of the modulated genes is revealed, although these may be within different regulatory pathways, emphasizing the complexity of their mutual interdependence. Genes with altered expression following PRKC-ζ knockdown include HSPB1, RAD51, and ID1 that we have previously described to be critical in prostatic malignancy. Because expression of PRKC-ζ is functionally involved in promoting the malignant phenotype, we propose PKC-ζ as a novel and biologically relevant target for therapeutic intervention in prostate cancer.

Conditioned media from cell lines: a complementary model to clinical specimens for the discovery of disease-specific biomarkers

In the strictest sense, the cell secretome (conditioned media) refers to the collection of proteins that contain a signal peptide and are processed via the endoplasmic reticulum and Golgi apparatus through the classical secretion pathway. More generally, the secretome also encompasses proteins shed from the cell surface and intracellular proteins released through non-classical secretion pathway or exosomes. These secreted proteins include numerous enzymes, growth factors, cytokines and hormones or other soluble mediators. They are fundamental in the processes of cell growth, differentiation, invasion and angiogenesis by regulating cell-to-cell and cell-to-extracellular matrix interactions. The main aim of this review is to provide a synopsis of findings from the analysis of the secretome taking diabetes, cancer and neurodegenerative diseases as examples. We will also discuss the preparation of conditioned media and on the main proteomic-based methodological approaches that have been developed for the study of secreted/shed proteins.

The identification of chromosomal translocation, t(4;6)(q22;q15), in prostate cancer

Our previous work identified a chromosomal translocation t(4;6) in prostate cancer cell lines and primary tumors. Using probes located on 4q22 and 6q15, the breakpoints identified in LNCaP cells, we performed fluorescence in situ hybridization analysis to detect this translocation in a large series of clinical localized prostate cancer samples treated conservatively. We found that t(4;6)(q22;q15) occurred in 78 of 667 cases (11.7%). The t(4;6)(q22;q15) was not independently associated with patient outcome. However, it occurs more frequently in high clinical T stage, high tumor volume specimens and in those with high baseline PSA (P=0.001, 0.001 and 0.01, respectively). The t(4;6)(q22;q15) occurred more frequently in samples with two or more TMPRSS2:ERG fusion genes caused by internal deletion than in samples without these genomic alterations, but this correlation is not statistically significant (P=0.0628). The potential role of this translocation in the development of human prostate cancer is discussed.