Volume 30, Issue 1 , Pages 16-20, January 2012
GREB1 tissue expression is associated with organ-confined prostate cancer☆
Article Outline
- Abstract
- 1. Introduction
- 2. Materials and methods
- 3. Results
- 4. Discussion
- 5. Conclusions
- References
- Copyright
Abstract
Objective
By reason of its heterogeneous behavior, it is difficult to determine the prognosis of many prostate cancer cases. Patients with the same clinicopathologic conditions may present varying clinical findings and rates of progression. We determined the role of new genes as potential molecular markers for prostate cancer prognosis.
Materials and methods
We performed a microarray analysis of two pools of patients with prostate cancer divided according to their clinicopathologic characteristics. After that, we validated these results by testing the genes with most different expressions between the two pools using the quantitative real time polymerase chain reaction method. We analyzed gene expression in 33 patients with localized prostate cancer according to prostate specific antigen (PSA), pathologic stage, Gleason score, and biochemical recurrence. For statistical analysis we used the Mann-Whitney Test.
Results
The microarray analysis revealed that 4,147 genes presented a different expression between the two pools. Among them, 3 genes, TMEFF2, GREB1, and TH1L, were at least 13-times overexpressed, and 1 gene, IGH3, which was at least 5times under-expressed in pool 1 (good prognosis) compared with pool 2 (bad prognosis), were selected for analysis. After the validation tests, GREB1 was significantly more overexpressed among patients with stage T2 compared with T3 (P = 0.020). The expressions of other 3 genes did not present significant differences according to the clinicopathological variables.
Conclusions
Tissue expression of GREB1 is associated with organ-confined prostate cancer and may constitute a gene associated with a favorable prognosis.
Keywords: Prostate , Prostate neoplasms , Biopsy , Prognosis , Gene expression , GREB1
1. Introduction
Prostate cancer (PCa) is still the most frequent noncutaneous tumor in men [1]. However, by reason of its heterogeneous behavior, it is difficult to determine the prognosis of many cases. On one hand, autopsy studies show that almost two-thirds of men above 70 years old present PCa, attesting the indolent behavior of the disease [2], [3]. On the other hand, the prediction of an organ-confined disease by the traditional clinical and pathologic parameters do not guarantee biochemical control, since about 30% of the patients who undergo radical prostatectomy (RP) will present a rise in their prostate specific antigen (PSA) after 10 years of follow-up [4].
Presently, the histologic grade of the biopsy defined by the Gleason score, allied to the PSA and the clinical stage are the most commonly used parameters for foretelling the chances of organ-confined disease and disease progression after treatment [5]. Several groups have brought these parameters together and developed nomograms for the forecasting of the pathologic condition and its clinical evolution [5], [6], [7]. In practice, however, we observe that patients with the same clinicopathologic conditions may present varying clinical findings, rates of progression, and responses to treatment.
Some molecular alterations, which demonstrate prognostic relevance for PCa, include alterations of p53, retinoblastoma, p27, chromogranin A, and e-cadherin, among others [8]. However, considering the profound heterogeneity of neoplastic prostate tissues, individually, the expression of a single gene and/or protein is also not able to adequately foretell the evolution of the disease in any particular patient.
So far we know the functions of only a limited number of genes, and new tools have been developed with a view to the simultaneous function of all of them. In the present study, we determined the role of new genes as potential molecular markers for PCa prognosis, using the microarray and quantitative reverse transcription polymerase chain reaction (qRT-PCR) methods.
2. Materials and methods
2.1. Materials
The first part of the study was based on a microarray analysis (Agilent Technologies 44 k whole human genome, two-color, Wilmington, DE) of 2 pools of patients with PCa who underwent RP between September 1997 and February 2000. These patients were divided according to clinicopathologic characteristics. In pool 1, 5 patients had favorable characteristics (mean PSA 6.8 ng/ml, Gleason score ≤6, stage T1 or T2, and no disease recurrence), and in pool 2, 5 had unfavorable characteristics (mean PSA 17.4 ng/ml, Gleason score >6, pathologic stage T2 or T3, and disease recurrence).
In the second part of the study, we planned to validate the results of the microarray analysis by testing the genes with most different expressions between the two pools of patients. For this purpose, we used the qRT-PCR method in another 33 patients with clinically localized PCa who had undergone RP during the same period. Table 1 describes the characteristics of the 33 patients with PCa used in qRT-PCR analysis. Control group consisted of 9 patients with benign prostatic hyperplasia (BPH). These last patients presented enlarged prostates, had undergone transrectal ultrasound-guided prostate biopsy that excluded PCa, and had indication to undergo surgery.
Table 1. Demographic characteristics of the 33 patients with PCa
| Age (years) | |
 Median (Q1–Q3) | 65(60–70) |
| Minimum–maximum | 49–76 |
| PSA (ng/ml) | |
| Median (Q1–Q3) | 7.9(6.0–12.0) |
| Minimum–maximum | 2.5–37.0 |
| Clinical stage | |
| T1 | 14(42.4%) |
| T2 | 19(57.6%) |
| Gleason score | |
| Median (Q1–Q3) | 7(5.0–8.0) |
| Minimum–maximum | 4–9 |
| Capsule involvement | 17(51.5%) |
| Seminal vesicle involvement | 0 |
| Lymph node involvement | 0 |
| Extra-prostatic involvement | 9(27.3%) |
| Pathological stage | |
| T2A | 10(30.3%) |
| T2B | 6(18.2%) |
| T2C | 7(21.2%) |
| T3A | 10(30.3%) |
| Disease recurrence | |
| Yes | 11(33.3%) |
| No | 22(66.6%) |
All tumor samples were obtained prospectively from surgical specimens and immediately frozen at −80°C. Before RNA extraction, a slide with the fragment was stained with hematoxylin and eosin for verification of tumor presence (representing at least 75% of the sample).
2.2. RNA extraction and cDNA synthesis
Briefly, for extraction of total RNA, frozen specimens were cut using a cryostat at −30°C into 10 fragments of 10 μm. They were then macerated in liquid nitrogen and total RNA was extracted with Trizol according to a pre-established protocol (Invitrogen Life Technologies, Carlsbad, CA). Pureness and concentration of RNA were measured in a spectrophotometer (260/280 nM), and integrity was verified in an Agilent 2100 bioanalyzer (Agilent Technologies). Synthesis of cDNA was performed from at least 5 μg of total RNA with the enzyme M-MLV reverse transcriptase and random primers (Invitrogen Life Technologies). The reactions were incubated at 65°C for 5 minutes followed by 37°C for 1 hour, and finally 95°C for 5 minutes. The cDNA reactions were diluted to 100 μl in nuclease-free water (Invitrogen Life Technologies) and stored at −20°C until further use.
2.3. qRT-PCR and gene expression
The expression of the genes with most different expressions was analyzed from cDNA through the qRT-PCR technology in the Abi7500 platform using the TaqMan protocol (Applied Biosystems, Foster City, CA). TaqMan endogenous control assay (B2M) is listed in Table 2. cDNA (2 μl) from each tumor sample was added to a PCR reaction mix containing 1× TaqMan Universal PCR Master Mix, AmpErase UNG, and 1 μl endogenous control assay or gene expression assay (Applied Biosystems) in a 20 μl reaction volume. The cycling conditions were 50°C for 2 minutes, 95°C for 10 minutes, and 40 cycles of 95°C for 15 seconds and 60°C for 1 minute During the quantitative RT-PCR, multiple samples were run and the results averaged.
Table 2. Assays identifiers (IDs) used for qRT-PCR
| Gene symbol | Gene name | Assays IDs |
|---|---|---|
| IGH3 | Immunoglobulin heavy chain, γ polypeptide | Hs00382386_m1 |
| TH1L | Trihydrophobin human-like 1 | Hs00212624_m1 |
| GREB1 | Gene regulated by estrogen in breast cancer | Hs00536409_m1 |
| TMEFF2 | Transmembrane protein with EGF-like and two follistatin-like domains 2 | Hs00249367_m1 |
| B2M | β-2-microglobulin | Hs00984230_m1 |
Finally, to calculate the relative expression of the target genes, we used the ΔΔCT method, as follows: ΔΔCT = (CT target gene, PCa sample − CT endogenous control, PCa sample) − (CT target gene, BPH sample − CT endogenous control, BPH sample). The fold change in gene expression was calculated as 2−ΔΔCT.
For analysis of clinicopathologic variables, patients were divided according to the serum PSA levels (<10 ng/ml vs. ≥10 ng/ml), pathologic stage (T2 vs. T3) Gleason score (≤6 vs. >6), and disease recurrence status (recurrence vs. no recurrence). For analysis of pathological stage, we used the 2002 TNM staging system [9]. Disease recurrence was defined as a PSA of 0.2 ng/ml or greater during the postoperative period. Prior written and informed consent was obtained from each patient, and the study was approved by the ethics of Hospital das Clínicas from Medical School of University of Sao Paulo.
For descriptive analysis of the relative gene expression level according to clinical-pathologic characteristics, we constructed box-plots, and for comparison between categories, we used the Mann-Whitney test. Statistical analysis was performed using GraphPad Instat, ver. 3.01 (GraphPad Software, Inc, La Jolla, CA), and significance was set as a P ≤ 0.05.
3. Results
Patients' characteristics are described in Table 1. Median age was 65 years and median PSA 7.9 ng/ml. Median Gleason score was 7, and 30% of patients presented extraprostatic disease. After a mean follow up of 50 months, one-third of patients presented biochemical recurrence.
Microarray analysis revealed that 4,147 genes presented a different expression between the 2 pools. Among them, 3 genes, TMEFF2, GREB1, and TH1L, which were at least 13 times overexpressed, and one gene, IGH3, which was at least 5 times underexpressed in pool 1 compared with pool 2 were selected. These 4 genes were then tested for their prognostic value using the qRT-PCR method (see Table 2 for assay identifiers).
According to preoperative serum PSA levels, the 4 genes presented similar expression levels between patients with PSA <10 ng/ml and ≥10 ng/ml (Fig. 1). Analysis of Gleason scores showed similar results. When we analyzed the expression level of the 4 genes among patients with Gleason ≤6 compared with patients with Gleason >6, similar results were found (Fig. 2). Regarding pathologic stage, we found that GREB1 was significantly more overexpressed among patients with stage T2 (mean 6 times) compared with T3 (mean 1.9 times) (P = 0.020). The other three genes showed similar expression patterns between the 2 pathologic stages (Fig. 3). Despite this statistically significant result with respect to pathologic stage, when we analyzed patients with and without biochemical recurrence, the 4 genes showed similar expression levels (Fig. 4).
Fig. 1.
Relative expression of the four genes in the malignant prostatic tissue according to serum PSA value. Fold change in gene expression was calculated using the ΔΔCT method (QRel = 27−ΔΔCT). Results are shown as a box plot with percentile values.
Fig. 2.
Relative expression of the four genes in the malignant prostatic tissue according to Gleason score. Fold change in gene expression was calculated using the ΔΔCT method (QRel = 27−ΔΔCT). Results are shown as a box plot with percentile values.
Fig. 3.
Relative expression of the four genes in the malignant prostatic tissue according to pathologic stage. Fold change in gene expression was calculated using the ΔΔCT method (QRel = 27−ΔΔCT). Results are shown as a box plot with percentile values.
Fig. 4.
Relative expression of the four genes in the malignant prostatic tissue according to biochemical recurrence status. Fold change in gene expression was calculated using the ΔΔCT method (QRel = 27−ΔΔCT). Results are shown as a box plot with percentile values.
4. Discussion
The prediction of prognosis in PCa is still a challenge for urologists and pathologists. In the present study, we demonstrated that GREB1 tissue expressions is significantly related to the presence of an organ-confined PCa. Expressions of this gene is significantly greater among patients with pT2 disease compared with pT3.
Determination of pathologic outcome and prognosis of PCa cases using clinicopathologic markers is limited. These markers evaluate mainly the cellular differentiation and the mass of the tumor, but are incapable of identifying the biological characteristics that determine cancer behavior. In order to overcome these limitations, intrinsic molecular determinants of PCa progression have been intensively studied with a view to discovering additional prognostic indicators [10].
GREB1 is a gene critically involved in the estrogen-induced growth of breast cancer cells. Rae et al. [11] analyzed candidate genes involved in estrogen stimulated breast cancer growth using DNA microarrays and qRT-PCR assays in 3 estrogen receptors positive breast cancer cell lines grown under multiple stimulatory and inhibitory conditions. They demonstrated that GREB1 expression was significantly induced by 17 β-estradiol relative to control in all three cancer cell lines.
Surprisingly, studies based on the qRT-PCR technique have also demonstrated high expression levels of GREB1 in BPH and PCa cell lines. Rae et al. [12] investigated the effects of androgens on GREB1 expression and its role in androgen-dependent PCa growth. They showed through the qRT-PCR method that androgen treatment of PCa cells positive for androgen receptor induced dose-dependent GREB1 expression, which was blocked by anti-androgens. Androgen receptor binding to the GREB1 promoter was confirmed by chromatin immunoprecipitation assays. Furthermore, suppression of GREB1 by RNA interference blocked androgen-stimulated LNCaP cell proliferation. They concluded that GREB1 is expressed in proliferating prostatic tissue and PCa is regulated by androgens, and suppression of GREB1 blocks androgen-induced growth. These results suggest that GREB1 may be critically involved in PCa proliferation. According to this study, we demonstrated that GREB1 tissue expression is significantly greater among patients with pathologic stage pT2 compared with pT3. GREB1 expression was also greater among patients with Gleason score ≤6 but this figure did not reach statistical significance. To our knowledge, our series is the first study in which GREB1 is related to PCa pathologic stage.
The other 3 analyzed genes did not show significant different expressions. TMEFF2 has been described as an androgen regulated gene that can suppress growth of PCa cells. Studies have shown that escape of PCa cells from androgen modulation causes them to decrease their expression of this gene, which may result in their more malignant behavior [13]. Regarding IGH3, increased urinary immunoglobulin levels have been described in patients with PCa. Compared with normal healthy subjects, urinary Ig levels were increased in 33% of patients with androgen-dependent PCa, and in 56% of those with androgen-independent PCa [14]. Finally, TH1L function is not completely described. Liu et al. [15] demonstrated that TH1L specifically binds to A-Raf kinase both in vitro and in vivo with inhibitory effects. A-Raf-Kinase belongs to the MAPK transduction pathway. Of the 3 isoforms, A-Raf, B-Raf, and C-Raf, the first is predominantly distributed in the urogenital tissues. The inhibitory action of TH1L over A-Raf might have important effects on cellular cycle control.
Despite the significantly different expression of GREB1 in relation to pathologic stage, these figures did not influence biochemical recurrence rates, since patients with and without recurrence presented similar levels of this gene. We believe this fact might be explained by the small sample size and the relative short follow-up period. Analyses of larger series with longer follow-up are necessary to confirm these results.
5. Conclusions
GREB1 tissue expression is associated with organ-confined PCa, and may constitute a gene associated with a favorable prognosis. Further analysis of the role of this gene on prostate carcinogenesis may help to elucidate the biological mechanisms of PCa growth and maybe the development of new target therapies to control disease progression.
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☆ This study was supported by FAPESP (Fundação de Amparo à Pesquisa do Estado de Sao Paulo) under the protocol number 2006/56492-5.
PII: S1078-1439(09)00295-6
doi:10.1016/j.urolonc.2009.09.014
© 2012 Elsevier Inc. All rights reserved.
Volume 30, Issue 1 , Pages 16-20, January 2012
