Abstract
Background:
There is an acute need to uncover biomarkers that reflect the molecular pathologies, underpinning prostate cancer progression and poor patient outcome. We have previously demonstrated that in prostate cancer cell lines PDE4D7 is downregulated in advanced cases of the disease. To investigate further the prognostic power of PDE4D7 expression during prostate cancer progression and assess how downregulation of this PDE isoform may affect disease outcome, we have examined PDE4D7 expression in physiologically relevant primary human samples.
Methods:
About 1405 patient samples across 8 publically available qPCR, Affymetrix Exon 1.0 ST arrays and RNA sequencing data sets were screened for PDE4D7 expression. The TMPRSS2-ERG gene rearrangement status of patient samples was determined by transformation of the exon array and RNA seq expression data to robust z-scores followed by the application of a threshold >3 to define a positive TMPRSS2-ERG gene fusion event in a tumour sample.
Results:
We demonstrate that PDE4D7 expression positively correlates with primary tumour development. We also show a positive association with the highly prostate cancer-specific gene rearrangement between TMPRSS2 and the ETS transcription factor family member ERG. In addition, we find that in primary TMPRSS2-ERG-positive tumours PDE4D7 expression is significantly positively correlated with low-grade disease and a reduced likelihood of progression after primary treatment. Conversely, PDE4D7 transcript levels become significantly decreased in castration resistant prostate cancer (CRPC).
Conclusions:
We further characterise and add physiological relevance to PDE4D7 as a novel marker that is associated with the development and progression of prostate tumours. We propose that the assessment of PDE4D7 levels may provide a novel, independent predictor of post-surgical disease progression.
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Main
Prostate cancer is the most commonly occurring non-skin malignancy in men, with an estimated 900 000 new cases diagnosed world-wide in 2013 (Ferlay et al, 2015). However, reactive clinical intervention after routine diagnosis often leads to significant over-treatment of non-aggressive tumours. This has severe negative impacts on both patient quality of life and the medical resources of healthcare institutions (Andriole et al, 2009; Schröder et al, 2009). Therefore, the characterisation of new biomarkers and methods of clinical assessment is of significant importance when assessing the need for different forms of clinical intervention.
Previous studies have shown that signalling pathways mediated by the second messenger cAMP have various roles in the development and progression of prostate cancer (Merkle and Hoffmann, 2011). Cyclic nucleotide phosphodiesterases (PDEs) (Conti and Beavo, 2007; Maurice et al, 2014) provide the sole means of degrading cAMP and cGMP in cells, and are pivotally placed to regulate cAMP signalling by virtue of their intracellular location and post-translational modification (Lugnier, 2006; Houslay, 2010). Each of the 11 PDE genes encode for a series of isoform variants, thereby greatly increasing the diversity of unique regulatory mechanisms, intracellular targeting and kinetic properties, which define functionally independent and unique signalling roles within the cell (Houslay et al, 2007; Houslay, 2010; Francis et al, 2011). This diversity underpins a paradigm of compartmentalised, temporally gated cyclic nucleotide signalling. Due to the complexity of these orchestrated signalling events, any change in PDE isoform expression or regulation can functionally contribute to disease onset (Lee et al, 2012; Michot et al, 2012; Apuhan et al, 2013; Kaname et al, 2014; Yoon et al, 2014). The molecular characterisation of these changes can be expected to provide means for the development of novel therapeutics and diagnostics (Houslay et al, 2005; Houslay, 2010).
Members of the PDE4D subfamily have been implicated as underpinning the molecular pathology of various diseases including prostate cancer (Rahrmann et al, 2009; Henderson et al, 2014), stroke (Gretarsdottir et al, 2003), acrodysostosis (Kaname et al, 2014) and COPD (Yoon et al, 2014). The PDE4D gene encodes a cohort of isoforms that are classified as long, short and super-short. Long isoforms possess two conserved regulatory domains, called UCR1 and UCR2, which allow long isoforms to be phosphorylated and activated by PKA (3′,5′ cAMP-dependent protein kinase) after cAMP elevation in cells (Hoffmann et al, 1998), as well as being functionally regulated through phosphorylation by activated forms of ERK, MK2 and AMPK (MacKenzie et al, 2011; Sheppard et al, 2014).
PDE4D7 is a long isoform member of this subfamily (Li et al, 2010).
Positive TMPRSS2-ERG fusion status was estimated in general by transformation to robust z-scores. Positive TMPRSS2-ERG fusion status was estimated by transformation to robust z-scores, utilising robust statistical measures, namely median and median absolute deviation, to replace mean and s.d., which are sensitive to outliers. Thus, log2-transformed expression values were converted by z-score=(expression−median(expression))/(MAD(expression)), and a threshold of >3 was applied to define samples with positive fusion events. Subsequently, a threshold of >3 was applied to define samples with positive fusion events. For the Erho et al (2013) data set, we applied a supervised clustering algorithm (Partitioning Around Medoids) to assign prostate cancer samples in one of the two clusters (high ERG or low ERG) based on the log2-transformed expression values of ERG. High ERG expression was subsequently assumed as representative for the presence of a positive TMPRSS2-ERG fusion event.
To assess whether any evidence of ERG binding in the genomic region of PDE4D could be observed, we utilised public ChIP-seq data (GSE14092) from the VCaP prostate cancer cell line after liftOver (https://genome.ucsc.edu/cgi-bin/hgLiftOver) to hg19 and found 43 peaks overlap** PDE4D when including 50-kb flanking regions. One of these peaks overlapped the PDE4D7 promoter region, while another was located in close proximity (<200 bases distance), which may hint towards an involvement of ERG binding in regulation of PDE4D7 expression.
Statistical data analysis
For ROC analysis, calculation of AUC under the ROC, ROC P-values and Box-and-Whisker plots the statistical software package MedCalc (MedCalc Software BVBA, Ostend, Belgium) was used. P-values for differences of mean expression were calculated by using Wilcoxon–Mann–Whitney testing unless mentioned otherwise.
Kaplan–Meier Survival curves have been generated by the medical statistical software package MedCalc based on the time to event for those patients who experienced the respective event (e.g., biochemical recurrence (BCR) or clinical recurrence (CR) of disease after surgery) and for those patients who did not suffer from the event at the time of follow-up (censored data). Further, to segregate the analysed patient cohort into two survival groups we determined a cut-off of PDE4D7 expression from a ROC curve analysis. The respective cut-off was objectively determined from the ROC curve at the unique point in the curve, where the sum of sensitivity and specificity reached a maximum.
Results
We have recently provided evidence, suggesting that PDE4D7 may play an important role in regulating cAMP signalling during prostate cancer progression (Henderson et al, 2014). To further explore this finding, we have evaluated the expression of PDE4D7 in a total of eight clinically relevant patient data sets. These data sets comprised a total of 1405 patient samples stratified into 8 sample categories listed in Figure 1A. Three different technology platforms were also leveraged to ensure reproducibility and significance of the gene expression data for PDE4D7, namely: (1) qPCR; (2) Affymetrix Human Exon Array 1.0 ST; (3) RNA seq (see Supplementary Table 1). More details of the data sets used within this study can be found in Supplementary Tables 1 and 2.
PDE4D7 expression correlates with primary localised prostate tumours and is significantly downregulated in CRPC
Our previous investigation in cell lines and xenograft material found that PDE4D7 was differentially expressed between androgen sensitive/responsive and CRPC cells (Henderson et al, 2014). To assess if this finding is physiologically relevant, we thought it prudent to examine PDE4D7 transcript expression in primary patient samples. We selected three prostate cancer exon array data sets (Figure 3. It is significant that in TMPRSS2-ERG-positive tumour samples the expression of PDE4D7 is negatively correlated with increasing pGleason, highlighting the transient nature of PDE4D7 upregulation. This finding bears a striking resemblance to our previous observations in cell lines and xenografts (Henderson et al, 2014).