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Am J Pathol. Dec 2009; 175(6): 2264–2276.
PMCID: PMC2789638

Novel Biomarkers for Prostate Cancer Including Noncoding Transcripts

Abstract

Levels of 27 transcripts were investigated as potential novel markers for prostate cancer, including genes encoding plasma membrane proteins (ADAM2, ELOVL5, MARCKSL1, RAMP1, TMEM30A, and TMEM66); secreted proteins (SPON2, TMEM30A, TMEM66, and truncated TMEFF2 (called POP4)); intracellular proteins (CAMK2N1, DHCR24, GLO1, NGFRAP1, PGK1, PSMA7, SBDS, and YWHAQ); and noncoding transcripts (POP1 (100 kb) from mRNA AK000023), POP2 (4 kb from mRNA AL832227), POP3 (50 kb from EST CFI40309), POP5 (intron of NCAM2, accession DO668384), POP6 (intron of FHIT), POP7 (intron of TNFAIP8), POP8 (intron of EFNA5), POP9 (intron of DSTN), POP10 (intron of ADAM2, accession DO668396), POP11 (87kb from EST BG194644), and POP12 (intron of EST BQ226050)). Expression of POP3 was prostate specific, whereas ADAM2, POP1, POP4, POP10, ELOVL5, RAMP1, and SPON2 had limited tissue expression. ELOVL5, MARCKSL1, NGFRAP1, PGK1, POP2, POP5, POP8, PSMA7, RAMP1, and SPON2 were significantly differentially expressed between laser microdissected malignant versus benign clinical samples of prostate tissue. PGK1, POP2, and POP12 correlated to clinical parameters. Levels of CAMK2N1, GLO1, SDBS, and TMEM30A transcripts tended to be increased in primary prostate cancer from patients who later had biochemical failure. Expression of GLO1, DHCR24, NGFRAP1, KLK3, and RAMP1 were significantly decreased in metastatic castration-recurrent disease compared with androgen-dependent primary prostate cancer. These novel potential biomarkers may therefore be useful in the diagnosis/prognosis of prostate cancer.

Prostate-specific antigen (PSA) has been used as a serum biomarker to monitor and screen for prostate cancer since 1986 and 1994, respectively.1 A recommendation for biopsy is set at an arbitrary serum PSA level of 4 ng/ml. At this threshold, PSA displays 93% specificity and a poor sensitivity of 24% for the detection of prostate cancer.2 In addition to carcinoma of the prostate, PSA is expressed in normal prostate tissue, prostatitis, and benign prostatic hyperplasia.3 Furthermore, 27% of men with borderline serum PSA levels (3.1 to 4 ng/ml) have detectable prostate cancer by biopsy.4

Serum PSA levels correlate with the degree of dissemination5,6 and aggressiveness6 of prostate cancer. For example, serum PSA levels > 10 ng/ml are associated with a high pathological stage (odds ratio (OR) 1.7) and high Gleason sum (i.e., 7 to 10; OR 1.9), respectively, compared with PSA levels < 4 ng/ml.6 Following radical prostatectomy or brachytherapy, 7 to 15% of prostate cancers will exhibit biochemical recurrence at 8 years of follow-up as defined by rising PSA levels.7,8 Approximately 1% of prostate cancer patients will develop metastases following first-line therapy concomitant with serum PSA levels ≤ 2 ng/ml.9 Thus, measurement of serum PSA levels is inadequate for monitoring progression for a small subset of patients.

Patients receiving androgen-deprivation therapy for disseminated disease will relapse and their disease will progress to the terminal, castration-recurrent prostate cancer for which there is no effective treatment.10,11,12 Initial response to androgen-deprivation therapy is measured by PSA nadir. PSA nadir is prognostic of the time it takes to reach castration-recurrent prostate cancer and death.13 However, it is unknown whether pretreatment serum PSA levels can predict response to androgen-deprivation therapy.

These limitations of PSA emphasize the need for new biomarkers to accurately detect, monitor, and predict the aggressiveness of prostate cancer. In particular, biomarkers that are prognostic and/or signify the propensity to rapidly develop advanced disease are required. Such biomarkers may stem from gene expression studies using in vivo models of advanced prostate cancer. Here, we characterize the expression of genes and novel non-coding transcripts that were previously identified by Long Serial Analysis of Gene Expression (LongSAGE) (unpublished data) and Subtractive Hybridization14 technologies using samples from the in vivo LNCaP Hollow Fiber model.15 Both technologies can be used to discover unannotated transcripts, and Subtractive Hybridization is particularly well suited for the identification of differentially expressed low abundance transcripts.16

Novel transcripts identified by Subtractive Hybridization are referred to as POP 1 through 12: POP1, transcript 100 kb from mRNA AK000023; POP2, transcript 4 kb from mRNA AL832227; POP3, transcript 50 kb from EST CFI40309; POP4, transcript from the intron of transmembrane protein with epidermal growth factor-like and two follistatin-like domains 2 (TMEFF2); POP5, transcript from the intron of neural cell adhesion molecule 2 (NCAM2; accession DO668384); POP6, transcript from the intron of fragile histidine triad gene (FHIT); POP7, transcript from the intron of tumor necrosis factor, α-induced protein 8 (TNFAIP8); POP8, transcript from the intron of ephrin-A5 (EFNA5); POP9, transcript from the intron of actin depolymerizing factor destrin (DSTN); POP10, transcript from the intron of ADAM2 (accession DO668396); POP11, transcript 87 kb from EST BG194644; and POP12, transcript from the intron of EST BQ226050.14 Genes previously identified by LongSAGE and examined here were the known genes ADAM2, CAMK2N1, ELOVL5, GLO1, MARCKSL1, NGFRAP1, PGK1, PSMA7, RAMP1, SBDS, SPON2, TMEM30A, TMEM66, and YWHAQ. DHCR24 is correlated with a higher incidence of metastases17,18,19 and was included here as a reference gene for comparison. The expression of these transcripts was measured in a variety of cell types and tissues, including clinical samples of androgen-dependent primary prostate cancer and metastasis of castration-recurrent prostate cancer. Here, we examine tissue specificity, androgen regulation, and feasibility of these transcripts in the prognosis of prostate cancer.

Materials and Methods

Cell Culture

Cell lines were maintained in RPMI 1640 media (LNCaP, 22Rv1, and COS1), Dulbecco’s modified Eagle’s medium (PC-3, DU145, and RKO), BRFF-HPC1 medium (MDA PCa 2b), or minimal essential medium (MG63, CV1, HEPG, and MCF7). All media (Stem Cell Technologies, Vancouver, BC, Canada) was supplemented with 100 U/ml penicillin and 100 units/ml streptomycin (Invitrogen, Burlington, ON, Canada) and fetal bovine serum (HyClone, Logan, UT). For androgen treatments, LNCaP cells were serum-starved for 48 hours and then treated for 16 hours in serum-free medium with 10 nmol/L synthetic androgen R1881 (PerkinElmer, Woodbridge, ON, Canada) or vehicle control (ethanol, final concentration 2.85 × 10−4%). Total RNA from cell lines was harvested using TRIzol Reagent (Invitrogen), and RNA from benign human tissue was obtained commercially (BD Clontech, Mountain View, CA).

Prostate Cancer Tissue Samples

Informed consent was obtained from each patient participating in the study according to guidelines set forth by the University of British Columbia/British Columbia Cancer Agency Research Ethics Board. Frozen primary androgen-dependent prostate specimens from patients in Japan who had undergone radical prostatectomies were obtained through coauthor T. Ueda and were embedded in Optimal Cutting Temperature™ (OCT) compound (Tissue-Tek, Torrance, CA). Prostatectomy specimens were accompanied by information, including the age of the patient, prior treatment history, serum PSA levels before surgery, and Tumor-Node-Metastasis (TNM) clinical and pathological stage (Table 1). Any patient who had received presurgical hormone ablation treatment was excluded. Malignant or benign epithelial cells were stringently obtained by laser microdissection using the μCut MMI AG Microscope (MMI Molecular Machines & Industries, Glattbrugg, Switzerland) (Figure 1, A–F). Total RNA was isolated and purified with the RNA Easy Micro kit (Qiagen, Mississauga, ON, Canada). Contaminating genomic DNA was removed from RNA samples by TURBO DNA-free (Ambion, Austin, TX) or DNase I from the RNA Easy Micro Kit. RNA quality and quantity were assessed using the NanoDrop ND-1000 (NanoDrop Technologies, Wilmington, DE) and the Agilent 2100 Bioanalyzer (Agilent Technologies, Mississauga, ON, Canada) with RNA 6000 Nano LabChip kit (Caliper Technologies, Hopkinton, MA). RNA of poor quality (RNA integrity number < 2.8) and insufficient quantity (<531 ng) was not used in this study. SuperScript III First-Strand Synthesis System (Invitrogen) with Oligo(dT) was used to reverse transcribe an input of 2.5 ng of RNA per quantitative (q)PCR.

Figure 1
Laser microdissection of normal and tumor prostate tissue. Selected prostate epithelial cells were cut at ×20 magnification using laser power and collected onto adhesive caps. Images show tissue before cutting (A and D), postcutting (location ...
Table 1
Demographics, PSA, Stage, Gleason grades, and Sum of the Prostate Cancer Patients Used in This Study (Laser Capture-Microdissected Samples)

Clinical samples of primary prostate cancer from men who later did, and did not, develop biochemical failure within 5 years after radical prostatectomy as well as lymph node metastasis from men with castration-recurrent metastatic disease (Prostate Cancer Rapid Autopsy Program) were obtained from the University of Washington through coauthor R. L. Vessella. Total RNA was extracted from tissue with RNA STAT-60 kit (Teltest, Friendswood, TX), and cDNA was synthesized with Oligo dT using Advantage RT for PCR kit (BD Clontech).

Relative Quantitation of Gene Expression

Input RNA was reverse transcribed with SuperScript III First Strand Synthesis kit (Invitrogen). For most RNA samples, a quantity of 0.5 μg was used in the RT reaction, but for limited sample quantities, such as those from the laser microdissected prostate tissue, 0.1 or 0.05 μg of RNA was used. A 10-μl quantitative (q)RT-PCR consisted of 1 μl of template cDNA, 1× TaqMan Universal PCR Master Mix (Applied Biosystems, Foster City, CA), and 0.9 μmol/L each of forward and reverse primers and 0.25 μmol/L of TaqMan probe (FAM-BHQ-1 or TET-BHQ-1; Integrated DNA Technologies, San Diego, CA) that produce specific PCR products ranging in size between 85 and 235 bp (see Table 2 for primer and probe sequences). qRT-PCR reactions were cycled as follows in a 7900HT Sequence Detection System (Applied Biosystems): 50°C for 2 minutes, 95°C for 10 minutes, and 45 cycles of 95°C for 0.25 minutes, followed by 60°C for 1 minute. All qRT-PCRs were performed using technical triplicates. cDNAs (from different conditions/patients) and genes (target and reference) to be directly compared were assayed in the same instrument run. Glyceraldehyde-3-phosphate (GAPDH) was used as a reference gene for all experiments, except the androgen regulation experiment using LNCaP cells in which succinate dehydrogenase complex, subunit A, flavoprotein was used due to its consistent levels of expression despite androgen stimulation. These reference genes were carefully assessed for consistent levels of expression across all conditions. Reactions without template were run for each gene to ensure that DNA had not contaminated the qRT-PCR reactions. Efficiency checks were performed for each primer pair. Relative expression was determined using the Pfaffl method, which takes into consideration the efficiency of the reaction for both the target and reference genes.

Table 2
Primer and Probe Sequences for qRT-PCR of Candidate Transcripts

Western Blot Analyses

LNCaP cells (2 × 106) were cultured in 15-cm plates in RPMI 1640 medium containing 5% fetal bovine serum for 24 hours. Medium was changed to serum-free and phenol red-free RPMI 1640 medium. After at least 24 hours of serum starvation, cells were treated with the indicated concentrations of R1881 or ethanol (vehicle) and were further incubated for 24 or 48 hours. Cells were harvested, and total cell lysates were analyzed by Western blot analysis with the respective antibodies (Santa Cruz Biotechnology, Santa Cruz, CA).

Statistical Analysis

To identify significant changes in gene expression in response to androgen, we used the two-sample Student’s t-test for unequal variance. Nonparametric methods were used with data that were sampled from nonnormal distributions. For gene expression analysis on RNA from laser microdissected prostatic tissue, the Spearman’s correlation test was used to identify associations to patient age or PSA levels, and the Kruskal-Wallis test was used to identify significant differences between mean gene expression in normal (benign) and tumor tissue, TNM stages of cancer, Gleason scores, or biochemical recurrence and terminal castration-recurrent metastases.

Results

Tissue Specificity of Gene Expression

Tissue-specific expression of transcripts in cell lines were measured by qRT-PCR using RNA isolated from five human prostate cancer cells (LNCaP, MDA-PCa-2B, 22Rv1, PC-3, and DU145) and nonprostate human cancer cell lines that included the following: MG63, osteosarcoma cells; RKO, colon carcinoma cells; HEPG, hepatocellular carcinoma cells; MCF7, mammary adenocarcinoma cells; and large T-antigen transformed and normal monkey kidney cells (COS1 and CV1, respectively). Expression of genes ADAM2 and POP11 were relatively specific for LNCaP cells (Figure 2A). ADAM2 and POP10 (intron of ADAM2) showed differences in expression in HEPG cells suggesting tissue-specific expression of splice variants of ADAM2. MARCKSL1, POP1, POP2, POP3, POP4, POP5, POP12, and SPON2 were enriched in human prostate cancer cell lines compared with all other human cancer cell lines tested.

Figure 2
Tissue specificity of gene expression. A: Expression in cell lines. LNCaP, MDAPCa-2B, 22Rv1, PC-3, DU145, MG63, RKO, HEPG, MCF7, COS1, and CV1 cells were maintained in tissue culture under individualized conditions for optimal growth to gauge constitutive ...

To address tissue-specific expression in benign tissues, levels of transcripts in 20 human tissue samples were measured. Gene expression was displayed relative to the levels in benign human prostate tissue. POP3 was the only transcript to exhibit exclusive expression in benign prostate tissue versus other benign human tissues tested (Figure 2B), suggesting it is prostate specific. This was consistent with expression of POP3 predominantly in LNCaP, MDA-PCa-2B, and 22RV1 cells that express androgen receptor and low expression in all other cell lines examined (Figure 2A). Some genes were expressed at a level on par with that of the benign prostate in the adrenal gland (ELOVL5) and testis (ELOVL5 and POP1; Figure 2B). Both adrenal glands and testes produce androgens that are essential for regulating the growth of the prostate.20 POP1 had relatively specific expression in prostate cancer cell lines with similar expression patterns to POP3, whereas ELOVL5 had broad expression across most cell lines (Figure 2A). ADAM2 and POP10 (intron of ADAM2) showed similar expression patterns in prostate, placenta, and testis with the exception of expression of only ADAM2 in thymus tissue (Figure 2B). These data support the tissue-specific expression of splice variants of ADAM2. POP4 (splice variant of TMEFF2) was expressed in the prostate, brain, and prostate cancer cells only expressing the androgen receptor. Both RAMP1 and SPON2 had relatively restricted expression in prostate and uterine tissues (Figure 2B). SPON2 had expression generally specific for prostate cancer cell lines (LNCaP and MDA-PCa-2B), while RAMP1 was also highly expressed in MG63 osteosarcoma cells (Figure 2A). Taken together, these data suggest that ADAM2, ELOVL5, POP1, POP3, POP4, POP10, RAMP1, and SPON2 have relatively restricted expression patterns in the prostate when comparing benign tissues (Figure 2B).

Androgen Regulation of Gene Expression

The androgen signaling axis plays an important role in the growth, survival, and differentiation of the prostate.21,22,23 Treatment for locally advanced and metastatic prostate cancer includes androgen-deprivation therapy. Thus, it is essential to determine whether levels of expression of any of the 27 transcripts were altered by androgen. To do this, levels of expression of these genes were assessed in prostate cancer cells with androgen receptor (LNCaP, MDA-PCa-2B, and 22Rv1) and without a functional androgen receptor (PC-3 and DU145).24,25,26,27,28 Expression of ADAM2, CAMK2N1, DHCR24, MARCKSL1, NGFRAP1, POP1, POP3, POP4, POP5, POP7, POP8, POP10, POP11, SPON2, and TMEM66 transcripts were enriched in prostate cancer cell lines with a functional androgen axis (compare levels in LNCaP, MDA-PCa-2B, and 22Rv1 to PC3 and DU145 cells in Figure 2A). Although MCF7 mammary carcinoma cells express the androgen receptor at low levels,29 activation of the endogenous androgen signaling axis has not been documented.30 With this potential lack of androgen signaling, expression of only ADAM2, MARCKSL1, POP1, POP3, POP4, POP5, POP10, POP11, and SPON2 was not obviously elevated in MCF7 cells (Figure 2A). Of these genes, expression of ADAM2, POP1, POP3, POP10, and SPON2 were generally restricted to the prostate.

Differential expression of these transcripts in response to androgen was also measured in LNCaP cells treated with androgen. KLK3 (PSA) was included as a positive control and was strongly induced by androgen as expected. Expression of 11 other genes (DHCR24, ELOVL5, GLO1, PGK1, POP4, POP6, POP7, POP8, SPON2, TMEM66, and YWHAQ) increased (Figure 3A), whereas significant decreases in expression of 5 genes (ADAM2, CAMK2N1, POP5, POP10, and POP11) were detected (Figure 3B). Consistent changes in levels of POP10 and ADAM2 in response to androgen suggest that these two variant transcripts may share common androgen-response element(s) in the regulatory regions to modulate transcription. Androgen regulation of genes MARCKSL1, NGFRAP1, POP1, POP2, POP3, POP9, POP12, PSMA7, RAMP1, SBDS, and TMEM30A were not detected (data not shown). A few genes were randomly selected for analysis that changes in RNA correlated to protein. PSA (KLK3) was included as a positive control and was robustly induced as expected (Figure 3c). ELOVL5 protein increased in a dose-dependent manner in response to increasing concentrations of androgen with up to eightfold at 10 nmol/L concentration when normalized to levels of β-actin. SPON2 and PGK1 proteins increased 1.7- and 1.8-fold, respectively, which was consistent with the less than twofold increase in mRNA. A weak band for NGFRAP protein could be detected with no apparent increase in response to 10 nmol/L androgen in agreement with mRNA levels. Although levels of MARCKSL1, NGFRAP1, POP1, and POP3 transcripts were elevated in prostate cancer cells with endogenous androgen receptor compared with those cells without a functional receptor, no direct evidence supports that these genes are regulated by androgen. Enhanced expression of ELOVL5, GLO1, PGK1, POP6, and YWHAQ in response to androgen, although lacking enrichment in prostate cancer cells with androgen receptor compared with those without a functional receptor, suggests that these genes may be regulated by secondary downstream effects of androgens such as changes in proliferation, metabolism, and/or differentiation.

Figure 3
Regulation of gene expression by androgen. A: Expression of genes and noncoding transcripts increased (A) or decreased (B) by androgen. RNA was isolated from LNCaP cells that were treated with R1881 and analyzed by qRT-PCR. Fold change was calculated ...

Characterization of Gene Expression in Prostate Cancer

To determine whether levels of any of the transcripts were altered in prostate cancer compared with benign prostate epithelial cells, total RNA was isolated from laser microdissected samples of prostate obtained by radical prostatectomy from prostate cancer patients (Table 1). These studies revealed that levels of expression of ELOVL5, NGFRAP1, PGK1, POP5, POP8, and PSMA7 were significantly reduced, whereas levels of expression of MARCKSL1, POP2, RAMP1, and SPON2 were significantly increased in malignant compared with benign epithelial prostate cells (Kruskal-Wallis test, P ≤ 0.05; Figure 4). POP3 and POP10 were borderline significantly increased (P < 0.1). Borderline significant changes in expression of genes indicate that analysis using a larger sample size may be required to achieve statistical significance.

Figure 4
Candidate biomarkers differentially expressed between benign and malignant prostate epithelial cells. RNA was isolated from laser-microdissected benign epithelial cells from 15 patients and malignant epithelial cells from 13 or 23 patients and analyzed ...

To determine whether the levels of expression of genes in tumor tissue samples correlated to patient age, serum PSA, Gleason grades, or stage of the disease (TNM), only levels of each transcript in the tumor samples were used in statistical analyses. Negative association between the expression of POP2 (P = 0.044, rho = −0.44) and the age of the patient was detected using Spearman’s correlation (Figure 5A). Some pathways that play a role in prostate cancer that are known to be affected by aging include reduced levels of testosterone, changes in the expression of specific G-protein isoforms, and levels of cAMP and melatonin. The mean expression of POP12 was significantly higher in Gleason scores 8 and 9 compared with 6 and 7 (P = 0.039) as assessed with the Kruskal-Wallis test (Figure 5B), suggesting a possible function in regulating differentiation. Expression of PGK1 (P = 0.022) was positively correlated with high serum PSA levels using Spearman’s correlation (Figure 5C). Borderline significance for expression of RAMP1 (P = 0.07) with both serum PSA and TNM stage of prostate cancer was detected (data not shown).

Figure 5
Tissue levels of transcripts correlated with clinical parameters. A: POP2 transcript in prostate cancer tissue is negatively correlated with the age of the patient. Spearman’s correlation test (P < 0.05), n = 13. B: The mean levels ...

Expression Levels in Primary Lesions from 5-Year Disease-Free Patients and Those That Developed Biochemical Recurrence Compared with Metastatic Castration-Recurrent Lesions

To assess whether expression of any of these transcripts could possibly aid in predicting which patients may develop aggressive disease, we compared their levels in clinical samples obtained up to 8 years ago by radical prostatectomy. Half of these samples were from the primary tumor tissue of patients who later developed recurrent disease (RP) measured as biochemical failure (n = 6), and the remaining samples (n = 6) were from the primary tumor tissue of patients who were still disease-free 5 years after primary treatment (nonrecurrent, NP) (range, 5.5 to 8.4 years). CAMK2N1 (P = 0.08), GLO1 (P = 0.06), SBDS (P = 0.08), and TMEM30A (P = 0.06) transcripts were all borderline significantly elevated in the tissue from patients who later had recurrence (Figure 6). The mean levels of KLK3 (PSA) transcript were not significantly different between primary lesions from men with or without biochemical failure (P = 0.87). Comparison of levels of expression of transcripts in androgen-dependent primaries that later recurred (RP) versus castration-recurrent metastases (Met, n = 6) revealed that GLO1 (P = 0.01) expression was significantly decreased in metastases, whereas CAMK2N1 (P = 0.08), NGFRAP1 (P = 0.06), and KLK3 (P = 0.06) expression were borderline significantly decreased. Comparing both primaries that did (RP) and did not (NP) later recur that were androgen-dependent versus castration-recurrent metastases (Met) resulted in significance for DHCR24 (P = 0.04), KLK3 (P = 0.03), NGFRAP1 (P = 0.03), and RAMP1 (P = 0.03), whereas GLO1 remained significant (P = 0.03). CAMK2N1 (P = 0.09) and PSMA7 (P = 0.09) were borderline significant. POP transcripts were not measured because these samples were not DNase-treated and the primers for the POPs cannot span introns.

Figure 6
Candidate biomarkers differentially expressed between androgen-dependent primary prostate cancer from patients who do and do not later have biochemical failure versus levels in castration recurrent metastatic disease. Total RNA isolated from castration-recurrent ...

Discussion

In the Unites States, 86 men die from prostate cancer each day. However, these numbers only represent the 2.5 to 3% of men who die from the disease from the 10% of men over 50 years who will have clinical progression. Autopsy studies indicate that 30% of men over the age of 50 have malignant cells in their prostate.31 The European Study of Screening and the Prostate Cancer Prevention Trial indicate that screening for prostate cancer elevates the incidence rate32 with increases in the ratio of incidence to mortality from 2.5:1 to 17:1. This suggests that a substantial proportion of men with clinically insignificant disease are being overtreated. In other words, their disease will never cause morbidity or mortality. Current treatments for organ-confined malignancy include brachytherapy,33 external beam radiation,34 and radical prostatectomy.35 These forms of therapy can produce significant morbidity such as incontinence and impotence and are not effective for disease that has spread beyond the prostate. Only palliative therapy is available for disseminated disease, which requires reducing levels of androgen and/or using antiandrogens.36,37 Thus, there is an urgent need for selective intervention to spare those men from receiving unnecessary treatment but still provide radical curative treatment to those men who will develop clinically significant disease. Currently, there are no prognostic tools that can distinguish aggressive tumors from latent tumors.

To address this need, the expression of a number of genes and novel noncoding transcripts previously identified to be differentially expressed in an in vivo model of hormonal progression of prostate cancer were studied with the notion that levels of expression may be indicative of aggressive disease. This study revealed the following: 1) GLO1, CAMK2N1, SBDS, and TMEM30A may be associated (P < 0.1) with increased expression in prostate cancer tissue from men that will go on to have biochemical failure; 2) GLO1, RAMP1, PSMA7, DHCR24, and possibly NGFRAP1 and CAMK2N1 were associated with decreased expression in metastatic castration-recurrent tissue compared with androgen-dependent primary lesions; 3) PGK1, POP2, and POP12 levels of expression correlated to clinical parameters; 4) differential expression of ELOV5, RAMP1, SPON2, MARCKSL1, NGFRAP1, PGK1, PMSA7, POP2, POP5, POP8, and possibly POP3 and POP10 between malignant and benign prostate epithelial cells; and 5) evidence for androgen regulation and tissue-specific expression of these transcripts. A summary of results is presented in Table 3.

Table 3
Review of Expression Trends of Candidate Genes

Several of the protein-coding genes investigated in this study are poorly explored in cancer pathobiology with little to nothing known with regard to their expression or function in prostate cancer. For several of these genes, their known general function is consistent with their expression pattern identified here (summarized in Table 4).38,39,40,41,42,43,44,45,46,47,48,49,50,51,52,53,54,55

Table 4
Function and Expression of Potential Novel Biomarkers in Prostate Cancer or Other Diseases

Of particular interest is CAMK2N1, which encodes a protein that interacts and inhibits the activity of Ca2+/calmodulin-dependent protein kinase II (CAMK2). CAMK2 signaling plays a role in cell cycle progression by activating MEK/ERK to enhance phosphorylation of p27Kip1 (Thr187), resulting in degradation and rapid entry into G2-M phase.56 Inhibitors of CAMK2 decrease the activities of CDK4 and CDK2 and enhance levels of p27Kip1 expression to cause cell cycle arrest in G1.57 CAMK2N1 deactivates MEK/ERK to decrease progression of S phase and stabilizes p27 to induce cell cycle arrest, thereby reducing tumor growth.58 In prostate cancer cells, overexpression of CAMK2 decreases apoptosis and caspase activity,59 whereas inhibition of CAMK2 activity reduces both proliferation and Matrigel invasion.60 Thus, reduced expression of CAMK2N1 in castration-recurrent metastatic disease as shown here would lead to increased CAMK2 activity, which is associated with increased proliferation and invasion. CAMK2 activity is under androgen receptor control.59 Here, we show that androgen decreased expression of CAMK2N1, which would theoretically increase CAMK2 activity to potentially contribute to increased proliferation. Contrary to predicted results, expression of CAMK2N1 was elevated in tumors that go on to recur, which would theoretically reduce CAMK2 activity and proliferation. Such discrepancies have been previously reported for other potential markers such as hepsin and PIM-1, which are overrepresented in prostate cancer but surprisingly reduced or absent levels in cancers associated with increased risk of relapse after prostatectomy.61 These observations suggest that various markers may be required for more definitive prognosis of different stages of prostate cancer.

Levels of transcripts for several genes were altered in response to androgen. These findings are useful to begin to appreciate a role for these transcripts in prostate pathobiology and may also have implications for their use as biomarkers. Here, we showed that RAMP1 had an expression profile that was prostate-specific in normal tissues for men. This tissue specificity combined with RAMP1 protein being localized on the plasma membrane indicates potential for RAMP1 to be used for targeting therapeutics or for imaging prostate cancer. No changes in expression of RAMP1 were detected in response to androgen, suggesting that possibly its expression would not be compromised in patients receiving androgen-deprivation therapies. An example of this can be drawn from prostate-specific membrane antigen that is expressed on the plasma membrane and used clinically for detection of recurrent prostate tumors.62,63,64

Noncoding transcripts display a diverse array of functions, including the regulation of expression of other genes. Sense noncoding transcripts can silence gene expression by recruiting chromatin remodeling complexes that methylate and deacetylate histones of specific genomic sequences. Intergenic, noncoding transcripts may promote the expression of the surrounding gene by recruiting chromatin remodeling complexes that demethylate and acetylate histones in the wake of RNA polymerase II. Moreover, steric hindrance of sense transcription via antisense transcription and formation of RNA hybrids between noncoding transcripts and target transcripts may also lead to transcriptional suppression. Double-stranded RNAs may result in RNA interference, RNA masking, RNA hyperediting, and degradation.65 These noncoding POP transcripts are not considered to be micro-RNAs, because their sequences range between 155 and 231 bp in length. POP2 (4 kb from mRNA AL832227) and POP12 (intron of EST BQ226050) are noncoding transcripts of unknown function14 with expression that correlated to clinical parameters, which suggests they may play a role in prostate pathology. POP1 (AK000023) and POP3 (50 kb from EST CFI40309), also noncoding transcripts,14 are of potential interest in prostate biology because of their restricted expression profiles, which may be useful for the identification that disseminated circulating/shed cells or metastatic lesions are of prostatic origin. Thus, further investigation of these noncoding transcripts in prostate biology and pathology is warranted based on their prostate-specific expression, potential to regulate gene expression, and/or correlation to clinical parameters of prostate cancer.

Some of the most exciting biomarkers for prostate cancer are detected at the DNA or RNA levels. These include the following: micro-RNAs66 in both tissue and blood; fusions between the untranslated region of the androgen-regulated gene TMPRSS2 and the ETS gene family67 in tissue; detection of the noncoding transcript PCA3 in urine68,69 and samples of circulating tumor cells from men with metastatic prostate cancer70 by itself or in conjunction with PSA mRNA; and the enhancer of zeste homolog 2 (EZH2), which is associated with aggressive disease and poor survival for prostate cancer patients.71 The combination of gene expression profiles of PCA3, prostein, and transient receptor potential cation channel subfamily M member 8, in concert with EZH2, was reported to provide additional prognostic power in a study of 106 patients with matched prostatectomy samples.72

The present study has identified potentially promising novel biomarkers for the diagnosis/prognosis of prostate cancer and/or for the confirmation of prostatic origin of unknown metastatic cancer and/or disseminated/shed cells. Further development and confirmation of the usefulness of these markers in larger patient cohorts may potentially lead to clinical applications aimed at selective interventions with the goal to spare patients from unnecessary treatment but still provide radical curative treatment to those men who will develop clinically significant disease.

Acknowledgments

Excellent technical assistance was contributed by Iran Travakoli (laser microdissection), Dr. Margaret Sutcliffe (pathology), and Lorena Barclay (tissue sections).

Footnotes

Address reprint requests to Marianne D. Sadar, Ph.D., Genome Sciences Centre, British Columbia Cancer Agency, 675 W. 10th Ave., Vancouver, British Columbia V5Z 1L3, Canada. E-mail: ac.csgcb@radasm.

Supported by National Institutes of Health/National Cancer Institute grant R01 CA105304 and Canadian Institutes for Health Research grant PPP-78770.

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