Whole blood mRNA in prostate cancer reveals a four-gene androgen regulated panel

  1. Hayley C Whitaker1,2,3⇑
  1. 1Uro-Oncology Research Group, Cancer Research UK Cambridge Institute, Robinson Way, Cambridge, UK
  2. 2Biomarker Initiative, Cancer Research UK Cambridge Institute, Robinson Way, Cambridge, UK
  3. 3Molecular Diagnostics and Therapeutics Group, University College London, London, UK
  4. 4Bioinformatics and Statistics Core Facility, Cancer Research UK Cambridge Institute, Robinson Way, Cambridge, UK
  5. 5Astra Zeneca, 2 Riverside, Granta Park, Cambridge, UK
  6. 6Molecular and Computational Diagnostics Group, Cancer Research UK Cambridge Institute, Robinson Way, Cambridge, UK
  7. 7Genomics Core Facility, Cancer Research UK Cambridge Institute, Robinson Way, Cambridge, UK
  8. 8Department of Histopathology, Cambridge University Hospitals NHS Foundation Trust, Cambridge, UK
  9. 9National Institute for Health Research Cambridge Biomedical Research Centre Core Biochemistry Assay Laboratory, Cambridge University Hospitals NHS Foundation Trust, Cambridge, UK
  10. 10Computational Biology Group, Cancer Research UK Cambridge Institute, Robinson Way, Cambridge, UK
  11. 11University College Hospital at Westmoreland Street, London, UK
  12. 12Nuffield Department of Surgical Sciences, John Radcliffe Hospital, Headington, Oxford, UK
  1. Correspondence should be addressed to H Whitaker; Email: Hayley.Whitaker{at}ucl.ac.uk
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    Figure 1

    Identification of differentially expressed genes in circulating mRNA. (A) A schematic overview of the study design giving numbers of patients and genes included at each stage (n). (B) A heat map of clustered results from the HT12 expression arrays for the six identified genes (SOD2, FAM129A, MME, KRT7, PPA1 and DPM3). Multiple probes for these genes that appeared in the top 1000 most DE probes are shown. Red colour indicates high expression, whereas blue colour indicates low expression. (C) Boxplots showing the expression array data for each probe shown in (B), where multiple probes exist for a gene all probes are shown. Limma P-values for differential gene expression are shown. (D) qPCR validation of expression array results. Ct values were calculated for all conditions and the expression of target genes was normalised against the expression of RPLP2 housekeeping gene using the δδCt method. All primer sequences are given in Supplementary Table 5. All P-values were calculated using Mann–Whitney two-tailed t-test. The control group in all figures were patients with raised PSA, negative biopsy. A full colour version of this figure is available at http://dx.doi.org/10.1530/ERC-16-0287.

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    Figure 2

    Expression of FAM129A, KRT7, SOD2 and MME in tissue and serum from metastatic patients. (A) Box and whisker plots were generated from previously published data on metastatic and control cohorts (Taylor et al. 2010). P-values were calculated using Wilcoxon rank-sum test. (B) Immunohistochemistry (IHC) for the four genes on biopsy tissue taken from the patients assayed in Fig. 1. All IHC was performed on the Bondmax Autostainer using the antibodies FAM129A (1:750), KRT7 (2.8 g/L), SOD2 (1:1500) and MME (1:50). Staining is shown in brown colour with nuclei shown in blue colour and was classified into the following categories: none, weak, moderate and high, based on intensity. (C) An ELISA developed on the Meso Scale Discovery platform was used to determine the amount of MME protein in the serum from patients previously tested in the discovery cohort. Plates were coated with goat anti-MME (1.44 μg/mL) and MME protein detected with biotinylated goat anti-MME (1:100) before visualising using streptavidin sulphoTAG (1:1000) and measured using a Sector 6000 plate reader. A full colour version of this figure is available at http://dx.doi.org/10.1530/ERC-16-0287.

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    Figure 3

    Expression of FAM129A, KRT7, SOD2 and MME in different risk cohorts. Patients were defined as low, intermediate or high risk based on the following clinical criteria: low risk – PSA ≤10 ng/mL, Gleason 6, ≥T2; intermediate risk – PSA ≥10 ng/mL but ≤20 ng/mL, Gleason 7, ≥T2 or high risk – PSA ≥20 ***ng/mL, Gleason ≥8, ≥T3. The clinical characteristics of the risk cohort are given in Supplementary Table 3. (A) The circulating mRNA for the four genes was determined in three risk cohorts by qPCR. Ct values were calculated for all conditions, and the expression of target genes was normalised against the expression of RPLP2 housekeeping gene using the δδCt method. Kruskal–Wallis tests for each gene tested the probability of statistically significant differences between the groups: FAM129A – P = 0.34, KRT7 – P = 0.0017, SOD2 – P = 0.79 and MME – P = 0.033. All P-values were calculated using Mann–Whitney two-tailed t-test. (B) Recursive partitioning was performed using Ct values from the qPCR validation to predict cut-offs for each group within the data. Only genes showing significant results are shown. Ct cut-off values and 95% confidence intervals are indicated. High – high risk, inter – intermediate risk, low – low risk. (C) Expression of FAM129A, KRT7, SOD2 and MME was determined in localised prostate using published expression data (Taylor et al. 2010) and P-values determined using a Wilcoxon rank-sum test. (D) Alterations in the protein levels of FAM129A, KRT7, SOD2 and MME in localised disease were determined by IHC using an in-house TMA previously described, where G3, G4 and G5 refer to Gleason grades (Whitaker et al. 2010, 2013). All IHC was performed on the Bondmax Autostainer using conditions described previously. Staining is shown in brown with nuclei shown in blue colour and was classified into the following categories: none, weak, moderate and high, based on intensity. P-values were calculated using Kruskal–Wallis test. A full colour version of this figure is available at http://dx.doi.org/10.1530/ERC-16-0287.

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    Figure 4

    Hormone regulation of FAM129A, KRT7, SOD2 and MME in patient cohorts. (A) The circulating mRNA for the four genes was determined in three hormone cohorts by qPCR: patients yet to receive treatment (hormone naive), patients receiving hormone treatment and continuing to respond (hormonal therapy), and patients who have become hormone refractory (hormone relapsed). Ct values were calculated for all conditions and the expression of target genes was normalised against the expression of RPLP2 housekeeping gene using the δδCt method. Kruskal–Wallis tests for each gene tested the probability of statistically significant differences between the groups: FAM129 – P = 0.0085, KRT7 – P = 0.038, SOD2 – P = 0.014 and MME – P = 0.0079. All P-values shown were calculated using Mann–Whitney two-tailed t-test between two groups. (B) Recursive partitioning was performed using Ct values from the qPCR validation to predict cut-offs for each group within the data. Only genes showing significant results are shown. Ct cut-off values and 95% confidence intervals are indicated. HN – never received hormone treatment (hormone naïve), HT – receiving hormone treatment and responding (hormonal therapy), and HR – receiving hormone treatment and showing biochemical or clinical relapse (hormone relapsed). (C) Alterations in the protein levels of FAM129A, KRT7, SOD2 and MME with hormone status was determined by IHC using a hormone relapsed TMA described in Supplementary Table 7. All IHC was performed on the Bondmax Autostainer using conditions described previously. Staining is shown in brown with nuclei shown in blue and was classified into the following categories: none, weak, moderate and high, based on intensity. P-values across all groups were calculated using Kruskal–Wallis test and pairwise comparisons using a Mann–Whitney two-tailed t-test. A full colour version of this figure is available at http://dx.doi.org/10.1530/ERC-16-0287.

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    Figure 5

    Androgen regulation of the four-gene panel. (A) Androgen regulation of the four genes was determined in the LNCaP cell line by treating with androgens and taking samples for expression analysis over the following 24 h (Massie et al. 2011). Filled circles represent androgen treatment, open circles represent vehicle controls. Data for all good probes are shown for FAM129A. Data for other genes are shown in Supplementary Fig. 6. ACF = autocorrelation (function). A measure greater than zero means that consecutive time points are nearer each other than time points chosen at random. (B) UCSC genome browser view of the FAM129A and MME loci showing AR binding profiles in prostate cancer cells from three independent studies (Wang et al. 2009, Yu et al. 2010, Massie et al. 2011). Coloured blocks indicate AR peaks identified in each of the three chIP studies, red peaks show the AR ChIP-seq profile for two cell lines (Massie et al. 2011). Below gene annotations are ENCODE tracks indicating promoter, enhancer, DNAse hypersensitivity and transcription factor binding profiles. Arrows indicate promoters and direction of transcription. Data for KRT7 and SOD2 are shown in Supplementary Fig. 7. (C) chIP for the AR in the LNCaP cell line following starvation for 48 h in charcoal-stripped media and treatment with 10−8 M R1881 for 1 h (black bars). Data are shown as relative to vehicle-treated cells (grey bars). P-values are calculated using Wilcoxon rank-sum test. A full colour version of this figure is available at http://dx.doi.org/10.1530/ERC-16-0287.

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  1. doi: 10.1530/ERC-16-0287 Endocr Relat Cancer 23 797-812
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