Comprehensive validation of published immunohistochemical prognostic biomarkers of prostate cancer -what has gone wrong? A blueprint for the way forward in biomarker studies

Abstract

Background: Treatment planning of localised prostate cancer remains challenging. Besides conventional parameters, a wealth of prognostic biomarkers has been proposed so far. None of which, however, have successfully been implemented in a routine setting so far. The aim of our study was to systematically verify a set of published prognostic markers for prostate cancer.

Methods: Following an in-depth PubMed search, 28 markers were selected that have been proposed as multivariate prognostic markers for primary prostate cancer. Their prognostic validity was examined in a radical prostatectomy cohort of 238 patients with a median follow-up of 60 months and biochemical progression as endpoint of the analysis. Immunohistochemical evaluation was performed using previously published cut-off values, but allowing for optimisation if necessary. Univariate and multivariate Cox regression were used to determine the prognostic value of biomarkers included in this study.

Results: Despite the application of various cut-offs in the analysis, only four (14%) markers were verified as independently prognostic (AKT1, stromal AR, EZH2, and PSMA) for PSA relapse following radical prostatectomy.

Conclusions: Apparently, many immunohistochemistry-based studies on prognostic markers seem to be over-optimistic. Codes of best practice, such as the REMARK guidelines, may facilitate the performance of conclusive and transparent future studies.

Figure 1

Immunoreactivity of selected prognostic biomarkers. Representative examples of positive immunostaining are shown for each marker, highlighting the typical subcellular localisation (magnification × 200).

Figure 2

Frequencies of immunohistochemically detected expression of selected prognostic markers in primary prostate carcinomas. Markers labelled with an asterisk were recorded as immunoreactive scores and summarised for easier visualisation (IRS 0: negative, IRS 1–3: weakly positive, IRS 4–8 moderately positive, IRS>8: strongly positive). Black bars indicate the cut-off used for dichotomising the variable for Cox regression analysis. Abbreviation: ND: non determined/missing data.

Figure 3

Forest plots for the prognostic markers predicting biochemical PSA relapse in multivariate analysis. Comparison of hazard ratios and 95% confidence intervals for published studies (left) and the Zurich prostate cancer cohort of 238 patients (right). Statistically significant markers are depicted in black, insignificant in red.