Enhancing risk stratification models in localized prostate cancer by novel validated tissue biomarkers

Abstract

Background: Localized prostate cancer (PCa) is a largely heterogeneous disease regarding its clinical behavior. Current risk stratification relies on clinicopathological parameters and distinguishing between indolent and aggressive cases remains challenging. To improve risk stratification, we aimed to identify new prognostic markers for PCa.

Methods: We performed an in silico analysis on publicly available PCa transcriptome datasets. The top 20 prognostic genes were assessed in PCa tissue samples of our institutional cohort (n = 92) using the NanoString nCounter technology. The three most promising candidates were further assessed by immunohistochemistry (IHC) in an institutional (n = 121) and an independent validation cohort from the EMPACT consortium (n = 199). Cancer-specific survival (CSS) and progression-free survival (PFS) were used as endpoints.

Results: Our in silico analysis identified 113 prognostic genes. The prognostic values of seven of the top 20 genes were confirmed in our institutional radical prostatectomy (RPE) cohort. Low CENPO, P2RX5, ABCC5 as well as high ASF1B, NCAPH, UBE2C, and ZWINT gene expressions were associated with shorter CSS. IHC analysis confirmed the significant associations between NCAPH and UBE2C staining and worse CSS. In the external validation cohort, higher NCAPH and ZWINT protein expressions were associated with shorter PFS. The combination of the newly identified tissue protein markers improved standard risk stratification models, such as D'Amico, CAPRA, and Cambridge prognostic groups.

Conclusions: We identified and validated high tissue levels of NCAPH, UBE2C, and ZWINT as novel prognostic risk factors in clinically localized PCa patients. The use of these markers can improve routinely used risk estimation models.

Fig. 1

Overview of the performed analyses, patient cohorts and key findings of the present study.

Fig. 2. Forest plot presentation of Cox univariate CSS analyses for the 20 genes with dichotomized GE levels in the institutional GE cohort (cohort I).

HR hazard ratio.

Fig. 3. Gene expression (GE) values of selected risk genes in BPH, RPE and pTURP samples.

GE levels of NCAPH, UBE2C and ZWINT were significantly higher in pTURP compared to BPH samples (A). Cancer-specific survival (CSS) analyses stratified by GE levels in the institutional GE cohort (cohort I) (B). CSS analyses stratified by protein expressions in the institutional IHC cohort (cohort II) (C). Progression-free survival (PFS) analyses of protein expressions in the multicentre validation cohort (cohort III) (D). BPH benign prostate hyperplasia, RPE radical prostatectomy, pTURP palliative transurethral resection of prostate.

Fig. 4. Progression-free survival (PFS) analysis by D’Amico and Cambridge risk scores (left plots), three IHC marker score (middle plots), and the combination of D’Amico or Cambridge with IHC marker scores (right plots) in the multicentre IHC validation cohort (cohort III).

In the D’Amico high-risk and Cambridge prognostic groups (CPG 4 and 5) patients were further stratified by the three maker IHC marker score (at least one marker high). P-values represent PFS differences for all groups (black), and between D’Amico high-risk patients with negative vs. positive marker groups (blue), and between Cambridge risk group 4 (CPG) patients with negative vs. positive marker groups (light blue) and between CPG 5 patients with negative vs. positive marker groups (dark blue). The three IHC marker score evaluation was not feasible in 36 samples due to missing IHC staining of any of the three markers. Neg.: negative marker expression, Pos.: positive expression of any of the three marker.