Differential expression of peroxiredoxins in prostate cancer: consistent upregulation of PRDX3 and PRDX4

Abstract

Background: The peroxiredoxins (PRDXs) are emerging as regulators of antioxidant defense, apoptosis, and therapy resistance in cancer. Because their significance in prostate cancer (PCa) is unclear, we investigated their expression and clinical associations in PCa.

Methods: Transcript expression of PRDX1-6 in PCa was evaluated in cancer gene microarray datasets, whereas protein expression was evaluated by immunoblotting in prostate cell lines, and by immunohistochemistry (IHC) in prostate tissue microarrays (TMAs) containing tumor (n = 80) and control (n = 17) tissues. PRDX3 was also analyzed in TMAs containing PCa tissues from African-American and Caucasian patients (n = 150 per group). PRDX expression was correlated with patients' clinicopathologic characteristics.

Results: Analysis of PRDX expression in cancer microarray datasets revealed consistent upregulation (tumor vs. normal) of PRDX3 and 4. All PRDXs exhibited elevated protein expression in PCa cell lines, compared with non-tumor cells. IHC revealed significant overexpression of PRDX3 and 4 in PCa, associated with age, increased prostate specific antigen (PSA), tumor stage, or Gleason score. High PRDX3 staining was associated with early age and elevated Gleason score at time of radical prostatectomy in African-American but not in Caucasian patients with PCa. PSA recurrence free survival in patients with low PRDX3 tumor expression was significantly longer in Caucasians compared to African-Americans, but no difference was detected for high expression.

Conclusions: PRDXs exhibit differential expression in prostate tumors, with PRDX3 and 4 consistently upregulated. Their role in PCa development, and their potential as biological determinants of PCa health disparities and novel therapeutic targets, deserve further investigation.

Fig. 1. Immunoblotting analysis of PRDX protein expression in a panel of human prostate cell lines

The panel included non-tumor (BRF-55T, PrEc, PrSc), transformed normal (RWPE-1, RWPE-2), androgen-independent (DU-145, PC3), and androgen-responsive (LNCaP, MDA-PCa-2b, BRF-41T, and 22RV1) cell lines. Protein loading was assessed with antibody to β-actin.

Fig. 2. Transcript expression of PRDX1-6 in prostate cancer determined by analysis of cancer gene microarray databases

All the datasets, except SPECS, were from the Oncomine database, and their names appear in the legend box at the right. Fold-changes and corresponding P values testing the difference in PRDX gene expression between PCa and normal prostate tissue (adjacent normal in most datasets) were provided by Oncomine. The P values for the SPECS database were calculated using the LIMMA statistical package [ ref. 25]. *P<0.05; **P<0.01, ***P<0.001.

Fig. 3. Immunohistochemical analysis of PRDX proteins in prostate tumor tissues

Representative examples of immunohistochemical staining of PRDX in prostate tissue microarrays (TMAs) are shown. TMAs were stained for the individual PRDX using specific antibodies, as indicated in Materials and Methods.

Fig. 4. Differential expression of PRDX proteins in prostate tumor tissues

Tissue microarrays were stained for the individual PRDX using specific antibodies, and the individual cores were blindly scored using the following scale: 0=no staining, 1=low staining, 2=moderate staining, 3=strong staining. Scored tissues were divided in two groups: high staining (score 3, light bars), and A) pooled normal prostate tissues (PN, n=17), (B) disease-free normal prostate tissues (N, n=8), and (C) adjacent normal prostate tissues (AN, n=9). *P<0.05; **P<0.01, ***P<0.001. P values were determined with Kruskal-Wallis test.

Fig. 5. Kaplan-Meier curves of PSA recurrence-free survival (PRFS) in relationship to PRDX3 expression in ethnicity prostate cancer tissue microarrays

Low (A) Caucasian (CC) and (B) African-American (AA) patients. PRFS was compared between AA and CC patients expressing low (<high) (C) and high (D) PRDX3 in prostate tumors. P values were calculated using the log-rank test.