Prostate adenocarcinoma is the second most frequent cancer worldwide and is one of the leading causes of male cancer-related deaths. However, it varies greatly in its behaviour, from indolent non-progressive disease to metastatic cancers with high associated mortality. The aim of this study was to identify predictive biomarkers for patients with localised prostate tumours most likely to progress to aggressive disease, to facilitate future tailored clinical treatment and identify novel therapeutic targets. The expression of 602 genes was profiled using oligoarrays, across three prostate cancer cell lines: CA-HPV-10, LNCaP and PC3, qualitatively identifying several potential prognostic biomarkers. Of particular interest was six transmembrane epithelial antigen of the prostate (STEAP) 1 and STEAP 2 which was subsequently analysed further in prostate cancer tissue samples following optimisation of an RNA extraction method from laser captured cells isolated from formalin-fixed paraffin-embedded biopsy samples. Quantitative analysis of STEAP1 and 2 gene expression were statistically significantly associated with the metastatic cell lines DU145 and PC3 as compared to the normal prostate epithelial cell line, PNT2. This expression pattern was also mirrored at the protein level in the cells. Furthermore, STEAP2 up-regulation was observed within a small patient cohort and was associated with those that had locally advanced disease. Subsequent mechanistic studies in the PNT2 cell line demonstrated that an over-expression of STEAP2 resulted in these normal prostate cells gaining an ability to migrate and invade, suggesting that STEAP2 expression may be a crucial molecule in driving the invasive ability of prostate cancer cells.

Six-transmembrane epithelial antigen of the prostate-2 (STEAP2) expression is increased in prostate cancer when compared to normal prostate, suggesting STEAP2 may drive prostate cancer progression. This study aimed to establish the functional role of STEAP2 in prostate tumourigenesis and evaluate if its knockdown resulted in reduced invasive potential of prostate cancer cells. PC3 and LNCaP cells were transfected with STEAP2 siRNA and proliferation, migration, invasion and gene expression analyses were performed. STEAP2 immunohistochemistry was applied to assess the protein expression and localisation according to Gleason score in 164 prostate cancer patients. Invasion significantly decreased in both cell lines following STEAP2 knockdown. PC3 proliferation and migration capacity significantly reduced, while LNCaP cell morphology and growth characteristics were altered. Additionally, STEAP2 downstream targets associated with driving invasion were identified as MMP3, MMP10, MMP13, FGFR4, IL1β, KiSS1 and SERPINE1 in PC3 cells and, MMP7 in LNCaP cells, with CD82 altered in both. In patient tissues, STEAP2 expression was significantly increased in prostate cancer samples and this significantly correlated with Gleason score. These data demonstrate that STEAP2 drives aggressive prostate cancer traits by promoting proliferation, migration and invasion and significantly influencing the transcriptional profile of ten genes underlying the metastatic cascade.

Prostate cancer is the second most common cancer diagnosed in men worldwide; however, few patients are affected by clinically significant disease within their lifetime. Unfortunately, the means to discriminate between patients with indolent disease and those who progress to aggressive prostate cancer is currently unavailable, resulting in over-treatment of patients. We therefore aimed to determine biomarkers of prostate cancer that can be used in the clinic to aid the diagnosis and prognosis. Immunohistochemistry analysis was carried out on prostate cancer specimens with a range of Gleason scores. Samples were stained and analysed for intensity of the Seven Transmembrane Epithelial Antigen of the Prostate (STEAP)-1, -2, -3, -4 and the Divalent Metal Transporter 1 (DMT1) proteins to determine suitable biomarkers for classification of patients likely to develop aggressive prostate cancer. Additionally, these proteins were also analysed to determine whether any would be able to predict future relapse using Kaplan Meier analysis. Data generated demonstrated that the protein expression levels of STEAP2 correlated significantly with Gleason score; furthermore, STEAP4 was a significant predictor of relapse. This data indicates that STEAP2 could be potential prognostic candidate for use in combination with the current prostate cancer detection methods and the presence of STEAP4 could be an indicator of possible relapse.

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