Prognostic value of an RNA expression signature derived from cell cycle proliferation genes in patients with prostate cancer: a retrospective study

Abstract

Background: Optimum management of clinically localised prostate cancer presents unique challenges because of the highly variable and often indolent natural history of the disease. To predict disease aggressiveness, clinicians combine clinical variables to create prognostic models, but the models have limited accuracy. We assessed the prognostic value of a predefined cell cycle progression (CCP) score in two cohorts of patients with prostate cancer.

Methods: We measured the expression of 31 genes involved in CCP with quantitative RT-PCR on RNA extracted from formalin-fixed paraffin-embedded tumour samples, and created a predefined score and assessed its usefulness in the prediction of disease outcome. The signature was assessed retrospectively in a cohort of patients from the USA who had undergone radical prostatectomy, and in a cohort of randomly selected men with clinically localised prostate cancer diagnosed by use of a transurethral resection of the prostate (TURP) in the UK who were managed conservatively. The primary endpoint was time to biochemical recurrence for the cohort of patients who had radical prostatectomy, and time to death from prostate cancer for the TURP cohort.

Findings: After prostatectomy, the CCP score was useful for predicting biochemical recurrence in the univariate analysis (hazard ratio for a 1-unit change [doubling] in CCP 1·89; 95% CI 1·54-2·31; p=5·6×10(-9)) and the best multivariate analysis (1·77, 1·40-2·22; p=4·3×10(-6)). In the best predictive model (final multivariate analysis), the CCP score and prostate-specific antigen (PSA) concentration were the most important variables and were more significant than any other clinical variable. In the TURP cohort, the CCP score was the most important variable for prediction of time to death from prostate cancer in both univariate analysis (2·92, 2·38-3·57, p=6·1×10(-22)) and the final multivariate analysis (2·57, 1·93-3·43; p=8·2×10(-11)), and was stronger than all other prognostic factors, although PSA concentration also added useful information. Heterogeneity in the hazard ratio for the CCP score was not noted in any case for any clinical variables.

Interpretation: The results of this study provide strong evidence that the CCP score is a robust prognostic marker, which, after additional validation, could have an essential role in determining the appropriate treatment for patients with prostate cancer.

Funding: Cancer Research UK, Queen Mary University of London, Orchid Appeal, US National Institutes of Health, and Koch Foundation.

Figure 1

Flow chart of patient selection for the radical prostatectomy cohort. The selection of 442 patients for inclusion in this study was based on tissue availability only, not on any clinical parameters.

Figure 2

Analysis of the CCP score in the radical prostatectomy cohort. A) Distribution of the CCP scores (N=366). The median value was 0·16 with an interquartile range of −0·30 to 0·64, as indicated by red tick marks on the x-axis. B) Forest plot graphing the CCP score hazard ratio (HR) in different clinical subgroups. The recurrence rate for each subgroup is also given (recurrences/size), and the size of the each box is proportional to the number of recurrences within that patient subgroup. The thin lines indicate the 95% CI for each HR. The diamond at the bottom is the 95% CI of the HR for the entire cohort. C) Kaplan-Meier plot of recurrence versus time for patients grouped by integer values of CCP score. Each bin corresponds to a 2-fold increase in CCP expression. The green line (149 patients) corresponds CCP score • 0, purple line (161 patients) corresponds to 0 < CCP • 1, pink line (50 patients) corresponds to 1 < CCP • 2, and red line (6 patients) corresponds to CCP score > 2. Also indicated are the 10-year recurrence rates for each group. For these four groups, the 10-year biochemical recurrence rates (%) are: 23.7, 44.5, 61.9 and 83.3, respectively.

Figure 3

Ten-year predicted risk of recurrence for different values of Combined Risk Score for the radical prostatectomy cohort, and below, a histogram showing the distribution of the Combined Risk Score for different subgroups based on Gleason score. The probability of recurrence was estimated from a Cox proportional hazard model using the Combined Risk Score. Gleason scores are shown in categories of <7, white bars; =7, grey bars; >7 black bars.

Figure 4

Flow chart of patient selection for the TURP cohort. The 398 patients were chosen randomly, as specified in the predetermined analysis plan, without regard to clinical or outcome parameters.

Figure 5

Analysis of the CCP score in the TURP cohort. A) Distribution of the CCP scores (N=337). The median value was 0·67 with an interquartile range of 0·16 to 1·35. B) Forest plot graphing the CCP score hazard ratio (HR) in different clinical subgroups. The prostate cancer death rate for each subgroup is also given (death /size), and the size of the each box is proportional to the number of deaths within that patient subgroup. The thin lines indicate the 95% CI for each HR. The diamond at the bottom is the 95% CI of the HR for the entire cohort. C) Kaplan-Meier plot of prostate cancer death versus time for the patients grouped by integer values of CCP score. Each bin corresponds to a 2-fold increase in CCP expression. The green line (59 patients) corresponds CCP score • 0, purple line (150 patients) corresponds to 0 < CCP • 1, pink line (93 patients) corresponds to 1 < CCP • 2, and red line (35 patients) corresponds to CCP score > 2. Also indicated are the 10-year prostate cancer death rates for each group. For these four groups, the 10-year prostate cancer death rates (%) are: 2.1, 13.2, 34.6 and 78.3, respectively.

Figure 6

Ten-year predicted risk of prostate cancer death for different values of the Combined Risk Score for TURP cohort, and below, a histogram showing the distribution of the Combined Risk Score for different subgroups based on Gleason score. The probability of prostate cancer death was estimated from a Cox proportional hazard model using the Combined Risk Score. Gleason scores are shown in categories of <7, white bars; =7, grey bars; >7 black bars.