Prostate cancer is the most common cancer of North American men. Prostate-specific
antigen (PSA), also known as human kallikrein 3 (hK3), according to the approved new
nomenclature of the human kallikrein family (Diamandis et al, 2000a), is used for
early detection and monitoring of prostate cancer (Bilhartz et al, 1991; Oesterling,
1991; Diamandis et al, 2000b). However, nonmalignant prostatic diseases, especially
benign prostatic hyperplasia (BPH) and acute prostatitis, also cause serum PSA elevation,
thus complicating the diagnosis of prostatic cancer by PSA measurements alone (Polascik
et al, 1999). The evaluation of the molecular forms of PSA improves the specificity
of PSA (Mitchell et al, 2001; Stephan et al, 2002). Despite the availability of these
tests, there is an urgent need for new biomarkers for early detection of prostate
cancer. In accordance with the principles of the development of new biomarkers (Sullivan
Pepe et al, 2001), one approach would be to search for genes that are overexpressed
in prostate cancer.
The macrophage inhibitory cytokine-1 (MIC-1) gene is a member of transforming growth
factor-β (TGF-β) superfamily and was originally isolated from macrophages using the
cDNA subtraction method (Bootcov et al, 1997). The macrophage inhibitory cytokine-1
gene is also known as growth/differentiation factor-15 (Bottner et al, 1999) and placental
bone morphogenetic protein (PLAB) (Hromas et al, 1997; Thomas et al, 2001). Recent
reports, using DNA microarray technology, have shown that the MIC-1 gene is more highly
expressed in prostate cancer than in BPH tissues (Buckhaults et al, 2001; Welsh et
al, 2001). Until now, there are no quantitative expression data on relatively large
groups of patients.
The aim of this study was to investigate the expression of MIC-1 in cancerous and
matched noncancerous prostate tissues by quantitative RT–PCR and associate these data
with clinicopathological parameters of prostate cancer patients.
MATERIALS AND METHODS
Study group
Included in this study were 66 patients who had undergone radical retropubic prostatectomy
for prostatic adenocarcinoma at the Charité University Hospital, Berlin, Germany.
Patient ages ranged from 48 to 73 years with a mean of 62.7 and a median of 64 years.
The patients did not receive any hormonal or other therapy before surgery.
Prostate cancer tissues
Fresh prostate tissue samples were obtained from the cancerous and noncancerous parts
of the same prostates. Small pieces of tissue were gross dissected by an experienced
pathologist (GK) immediately after removal of the prostate, snap frozen and stored
in liquid nitrogen until analysis, as described previously (Meyer et al, 1997). Histological
analysis of paraffin-embedded tissue adjacent to these samples was performed by the
same pathologist to verify the diagnoses. Only tumour samples that were fully surrounded
by malignant tissue according to this analysis were used in this study. We also discarded
samples in which benign prostate glands made up more than 10% of the tissue. This
way, we minimised the contamination of the tumour sample with benign glands, which
is not fully avoidable in prostate cancer unless microdissected tissues were processed.
Most of the tumours were located dorsolaterally in the peripheral zone of the prostate.
The tissue that we considered as normal was usually taken from the inner zone of the
contralateral lobe. Histologically, many of these samples displayed a mild glandular
hyperplasia. The criteria of exclusion were prominent inflammatory infiltrates, lack
of epithelia due to stromal hyperplasia and prostatic intraepithelial neoplasia. The
Ethics Committee of the Charite Hospital approved the use of these tissues for research
purposes.
Total RNA extraction and cDNA synthesis
Tumour tissues were minced with a scalpel, on dry ice, and transferred immediately
to 2 ml polypropylene tubes. They were then homogenised and total RNA was extracted
using the RNeasy® total RNA isolation system, following the manufacturer's instructions
(Qiagen, Valencia, CA, USA). The concentration and purity of RNA were determined spectrophotometrically.
Two micrograms of total RNA were reverse-transcribed into first strand cDNA using
the Superscript™ preamplification system (Gibco BRL, Gaithersburg, MD, USA). The final
volume was 20 μl.
Quantitative real-time RT–PCR analysis
Two gene-specific primers were designed (MIC-1/F: 5′ CGC GCA ACG GGG ACG ACT 3′ and
MIC-1/R: 5′ TGA GC ACC ATG GGA TTG TAG C 3′11). Real-time monitoring of PCR reactions
was performed using the LightCycler™ system (RocheApplied Science, Indianapolis, IN,
USA) and the SYBR green I dye, which binds preferentially to double-stranded DNA.
Fluorescence signals, which are proportional to the concentration of the PCR product,
are measured at the end of each cycle and displayed on a computer screen (Buckhaults
et al, 2001). The reaction is characterised by the point during cycling when amplification
of PCR products is first detected, rather than the amount of PCR product accumulated
after a fixed number of cycles. The higher the starting quantity of the template,
the earlier a significant increase in fluorescence is observed (Wittwer et al, 1997;
Bieche et al, 1999). The threshold cycle is defined as the fractional cycle number
at which fluorescence passes a fixed threshold above baseline (Bieche et al, 1998).
Endogenous control
For each sample, the amount of the target and of β actin, as an endogenous control,
was determined using a calibration curve. The amount of the target molecule was then
divided by the amount of the endogenous reference, to obtain a normalised target value
(Bieche et al, 1999).
Calibration curves
Separate calibration (standard) curves for actin and MIC-1 were constructed using
serial dilutions of total cDNA from a healthy human prostate tissue, purchased from
Clontech, Palo Alto, CA, USA. The standard curve samples were included in each run.
Standards for both MIC-1 and actin RNAs were defined to contain an arbitrary starting
concentration, since no primary calibrators exist. Hence, all calculated concentrations
are relative to the concentration of the standard.
PCR amplification
The PCR reaction was carried out on the LightCycler™ system. For each run, a master
mixture was prepared on ice, containing 1 μl of cDNA, 2 μl of LC DNA Master SYBR Green
I mix, 50 ng of primers and 2.4 μl of 25 mM MgCl2. The final volume was adjusted with
H2O to 20 μl. After the reaction mixture was loaded into a glass capillary tube, the
cycling conditions were carried out as follows: initial denaturation at 95°C for 10 min,
followed by 42 cycles of denaturation at 95°C for 1 s, annealing at 58°C for 8 s and
extension at 72°C for 30 s. The temperature transition rate was set at 20°C s−1. Fluorescent
product was measured by a single acquisition mode at 92°C after each cycle.
Melting curve
For distinguishing specific from nonspecific products and primer dimers, a melting
curve was obtained after amplification by holding the temperature at 70°C for 30 s
followed by a gradual increase in temperature to 99°C at a rate of 0.2°C s−1, with
the signal acquisition mode set at step, as described. To verify the melting curve
results, representative samples of the PCR products were run on 1.5% agarose gels,
purified, and cloned into the pCR 2.1-TOPO vector (Invitrogen, Carlsbad, CA, USA)
according to the manufacturer's instructions. The inserts were sequenced from both
directions using vector-specific primers, with an automated DNA sequencer.
Statistical analysis
Statistical analysis was performed with SAS software (SAS Institute, Cary, NC, USA).
The analyses of differences between MIC-1 expression in noncancerous and cancerous
tissues were performed with the nonparametric McNemar test and the Wilcoxon signed
ranks test. The binomial distribution was used to compute the significance level of
the McNemar test. Relations between different variables were assessed by the Mann–Whitney
U-test.
RESULTS
Expression level of MIC-1 in prostatic tissues
We assessed the quantitative expression of MIC-1 mRNA in the 66 matched pairs of cancerous
and noncancerous prostatic tissues. The expression levels of MIC-1 were expressed
in arbitrary units, according to a standard curve that was constructed by using serial
dilutions of a cDNA obtained from normal prostatic tissue. Results were then normalised
by using the ratio of MIC-1/β-actin concentration for each sample.
Fifty eight cases showed higher expression level of MIC-1 gene in cancerous prostatic
tissues in comparison with noncancerous tissues. Lower expression in cancer was observed
in only eight cases. This difference was statistically significant (P<0.001) (Table
1
Table 1
MIC-1 expression in pairs of noncancerous and cancerous prostatic tissues
MIC expression
Number of patients (%)
P-value
a
Higher in cancer vs normal
58 (88)
<0.001
Lower in cancer vs normal
8 (12)
a
Calculated by McNemar test.
and Figure 1
Figure 1
MIC-1 mRNA expression as arbitrary units shown for 66 patients. The black box represents
the level in cancerous tissue and the connected white box the respective level of
the nonmalignant tissue of the same patient. The P-value was calculated by McNemar
test.
). The expression levels of MIC-1 gene in cancerous prostatic tissues were significantly
higher than that in noncancerous prostatic tissues. Results are summarized in Table
2
Table 2
Descriptive statistics for MIC-1 expression (mRNA levels) in noncancerous and cancerous
prostatic tissues
Mean
a
Standard errora
Mediana
Rangea
P-valueb
MIC, noncancer (N=66)
71
27
6.7
0.03–116
MIC, cancer (N=66)
264
106
32
0.21–5581
<0.001
% Increasec
273%
—
375%
a
These values are corrected for actin expression and are unitless ratios.
b
Calculated by the Wilcoxon's signed rank test.
c
Compared to cancer and assuming that the value in noncancerous tissue is 100%.
and Figure 2
Figure 2
MIC-1 mRNA expression in cancerous and noncancerous prostatic tissues. The horizontal
lines indicate the median. The P-value was calculated by the Mann–Whitney U-test.
. Mean and median values of MIC-1 transcripts were significantly higher in the cancerous
tissues by approximately 273–375% (P<0.001).
Association with clinicopathological parameters
The association of MIC-1 mRNA level with clinicopathological parameters in cancerous
tissues is shown in Table 3
Table 3
MIC expression in cancerous prostatic tissues from 66 patients classified by stage
of the disease, Gleason score and tumour grade
Total
Meana
Standard Errora
Mediana
P-valueb
Stage
I/II
32
145
67
10
0.69
III
34
376
195
37
Gleason score
⩽5
21
117
90
9
0.004
>5
40
373
167
54
Unknown
5
Grade
G1/2
39
114
50
22
0.86
G3
27
482
246
40
a
These values are corrected for actin expression and are unitless ratios.
b
Calculated by the Mann–Whitney U-test.
. The expression levels of MIC-1 gene did not show any significant association with
tumour stage (P=0.69) and tumour grade (P=0.86). On the other hand, higher Gleason
score (>5 vs ⩽5) significantly associated with higher MIC-1 gene expression.
DISCUSSION
Prostate-specific antigen, also known as hK3, and its molecular forms are the most
useful tumour markers for the prostate cancer and hK2, another member of the kallikrein
gene family, may help in reducing the number of unnecessary biopsies (Rittenhouse
et al, 1998). Nevertheless, these serum biomarkers cannot accurately predict the presence
of prostate cancer, its aggressiveness or the rate of postoperative PSA failure. New,
improved biomarkers might be necessary especially for Gleason 4/5 tumours (Stamey,
2001).
The MIC-1 gene was originally cloned from macrophages using a subtraction-cloning
strategy (Bootcov et al, 1997). This gene is a member of the TGF-β superfamily. Other
investigators discovered this gene independently and gave it different names, such
as growth/differentiation factor-15 (GDF-15) (Bottner et al, 1999) and prostate differentiation
factor (PLAB) (Hromas et al, 1997; Thomas et al, 2001).
Recently, the MIC-1 gene was found to be highly overexpressed in human prostate (Welsh
et al, 2001) and colorectal cancer (Buckhaults et al, 2001) by microarray technology.
To confirm these results, and investigate the association with clinicopathological
parameters, we assessed the quantitative expression of MIC-1 in a relatively large
number of matched prostate cancerous and noncancerous tissues using LightCycler™ technology.
Our results showed that MIC-1 gene expression was significantly higher in cancerous
prostatic tissue than in noncancerous tissue. Higher Gleason score (>5) cancer expressed
significantly more MIC-1 mRNA (
Table 3). These data suggest that MIC-1 gene expression is increased in cancer tissue,
compared to normal tissue and its expression is increased when the tumour progresses
further. Thus, the level of MIC-1 expression may be a marker of tumour differentiation.
Transforming growth factor-β and its receptor were found to be overexpressed in high-grade
prostatic intraepithelial neoplasia in the rat ventral prostate. It was reported that
high expression of TGF-β and its receptors enhance cancer growth and metastasis and
are associated with poor prognosis (Wong et al, 2000). Preoperative plasma TGF-β levels
are markedly elevated in men with prostate cancer metastasis and are a strong predictor
of biological progression after surgery (Shariat et al, 2001). The macrophage migration
inhibitory factor (MIF) gene was reported to be elevated in prostate cancer tissues
and upregulation of this gene is associated with serum level of MIF (Meyer-Siegler
et al, 2002).
In conclusion, we report upregulation of the MIC-1 gene in prostate cancer and in
advanced and more aggressive prostatic tumours. These data may indicate a possible
role for the MIC-1 protein as a future diagnostic and prognostic biomarker. Furthermore,
the understanding of the biological function of MIC-1 in prostate may help in delineating
its role in prostatic physiology and pathobiology.