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[Cancer Research 61, 4283-4286, May 15, 2001]
© 2001 American Association for Cancer Research

Tumor Biology

Identification of Differentially Expressed Genes by Serial Analysis of Gene Expression in Human Prostate Cancer1

A. Waghray, M. Schober, F. Feroze, F. Yao, J. Virgin and Y. Q. Chen2

Department of Pathology [A. W., M. S., F. F., F. Y., J. V., Y. Q. C.] and Center for Molecular Medicine and Genetics [Y. Q. C.], Wayne State University, Detroit, Michigan 48201


   ABSTRACT
Top
 ABSTRACT
INTRODUCTION
 MATERIALS AND METHODS
 RESULTS
 DISCUSSIONS
 REFERENCES
 
Prostate cancer is the leading cause of cancer death in American males. To better understand the genetic bases of this disease, we have generated a comprehensive molecular profile of human prostate. The gene expression pattern in normal and prostate cancer tissues was analyzed by serial analysis of gene expression (SAGE). A total of 133,217 transcripts were analyzed, and 35,185 distinct SAGE tags were identified representing 19,287 genes. Comparison of the transcripts in normal and tumor tissue revealed 156 differentially expressed genes (P < 0.05), of which 88 genes were up-regulated and 68 genes were down-regulated in the tumor tissue. Based on SAGE data, we estimate that the transcriptome for human prostate is approximately 37,000. Several differentially expressed genes identified by SAGE were selected for confirmation using immunohistochemistry. Some genes (e.g., E2F4) were overexpressed in tumor epithelial cells and some (e.g., Daxx) were increased in tumor stroma. Further characterization of the role of E2F4 and Daxx as well as other differentially expressed genes may provide useful insights into the mechanism of prostate cancer development.


   INTRODUCTION
Top
 ABSTRACT
 INTRODUCTION
MATERIALS AND METHODS
 RESULTS
 DISCUSSIONS
 REFERENCES
 
The age-adjusted incidence of prostate cancer has been increasing by approximately 3% annually worldwide (1) . Many risk factors for human prostate cancer have been proposed, including genetic predisposition, age, diet, hormones, and environmental factors. However, its etiology is still largely unknown. Nevertheless, all of the above factors modulate gene expression. Therefore, gene expression patterns could be helpful for understanding the molecular mechanism of prostate cancer development. For this reason, efforts are being made to search for epigenetic markers on a large scale. Thus far, the three most widely used methodologies are sequencing of ESTs,3 hybridization of high-density arrays, and SAGE. In the EST method, cDNA libraries are constructed from tissues derived from different stages of prostate tumors, and cDNA clones are sequenced from the 5'- or 3'-end or both (Ref. 2 ; Cancer Genome Anatomy Project, NIH). In the array method, known human genes and ESTs are arrayed on slides and hybridized to cDNA samples obtained from different stages of prostate tumors (3) . In the SAGE method, 10-base tags are obtained from each gene transcript, concatenated, and sequenced (this study). Compared with EST, SAGE is a more efficient method. An average of 50 transcripts can be determined per sequencing, in contrast to a single transcript per sequencing in EST. Although the array technique can give gene expression results on a large set of genes, it depends on the number of genes arrayed. The most severe limitation, perhaps, is its inability to detect novel genes. The SAGE technique allows one to quantitatively detect every gene expressed in cells, provided that enough tags are analyzed.

To better understand molecular changes associated with prostate cancer progression, we have performed a comprehensive analysis of gene expression in normal and prostate tumor tissues by SAGE. Our study provides a list of candidate genes that could be useful for the development of new diagnostic/prognostic markers for human prostate cancer.


   MATERIALS AND METHODS
Top
 ABSTRACT
 INTRODUCTION
 MATERIALS AND METHODS
RESULTS
 DISCUSSIONS
 REFERENCES
 
Prostate Tissue.
Tumor and normal tissues were obtained from radical prostatectomy specimens within 20 min of surgical removal. All patients gave informed consent according to a protocol approved by the Internal Review Board for research involving human subjects at Wayne State University. None of the patients had any treatment for prostate cancer before surgery. After dissection of prostate glands, areas of normal and tumor tissue (1–2 mm3) were identified by gross inspection and frozen in liquid nitrogen. Before freezing, 0.2-mm sections were sectioned from each face of the tissues and used for microscopic estimation of the percentage of tumor, benign glands, and stroma. SAGE analysis was done in matched normal and tumor samples pooled from four patients. The tumor sample contained 80–90% tumor glands (Gleason scores of 7) and 10–20% stroma, with no benign glands identified. The normal sample contained 30–50% benign glands and 50–70% stroma, with no tumor glands identified. Total RNA was isolated using TRIzol reagent (Life Technologies, Inc.).

SAGE.
SAGE analysis was performed as described previously (4) with following modifications: ditags were PCR-amplified using biotinylated primers and digested with NlaIII enzyme (5) . Concatemers were heated for 15 min at 65°C and chilled on ice for 10 min before being separated on an 8% polyacrylamide gel (6) . The concatemers were then cloned into the SphI site of the pZero vector (Invitrogen). Concatenated tags were screened by PCR using M13 forward and M13 reverse primers. PCR products with inserts greater than 500 bp were isolated and sequenced with M13 forward primer on an automated 3700 DNA sequencer (Perkin-Elmer).

SAGE Data Analysis.
SAGE tags were extracted using SAGE software version 4.12 (4) . Tags were matched to the SAGE reliable map (release 10-26-2000).4 Due to the fact that some tags map to multiple genes, and some genes have multiple tags, SAGE data were analyzed in two different ways: (a) by the exclusion method (tags that match to multiple genes were discarded, and only tags that match to a single gene were tabulated, and composite counts were analyzed for their significance); and (b) by the inclusion method (tags that match to multiple genes were counted as 100% toward each gene). All tags were tabulated, and composite counts were analyzed for their statistical significance. Lists of differentially expressed genes (P < 0.05) obtained from the exclusion and inclusion methods were compared, and finally only genes that have a P < 0.05 in both lists were considered statistically significant. The total number of genes identified was estimated by Nm + (Num - 0.1 Num)/3.5, where Nm is the number of genes matched to SAGE tags, Num is the number of SAGE tags that do not match to known genes or ESTs, 10% is the estimated sequencing error per SAGE tag, and 3.5 is the average number of tags/gene in the SAGE reliable map (release 10-26-2000).

Immunohistochemistry.
Paraffin-embedded prostate tissues were deparaffinized and rehydrated by standard procedure. The tissue sections were treated by boiling with 10 mM sodium citrate (pH 6.0) for 20 min, cooled to room temperature for 20 min to retrieve antigen, and treated with 1% hydrogen peroxide at room temperature for 10 min to inactivate endogenous peroxidase. The slides were then washed once with water and once with PBS and processed for immunohistochemical analysis. Sections were blocked in 10% normal serum for 10 min at room temperature and then incubated with primary antibody overnight at 4°C in a humidifier chamber. The section lacking primary antibody treatment served as a control. The sections were incubated for 1 h with biotinylated secondary antibody and then stained using Vectastain Elite ABC (Vector Laboratories, Inc.) avidin-biotin peroxidase complex for 30 min. Positive staining was visualized by a 5-min incubation in a solution containing 3,3'diaminobenzidine-4 substrate.


   RESULTS
Top
 ABSTRACT
 INTRODUCTION
 MATERIALS AND METHODS
 RESULTS
DISCUSSIONS
 REFERENCES
 
Generation of SAGE Data.
A total of 133,217 tags were generated, of which 65,505 were from normal tissue, and 67,712 were from tumor tissues (Table 1)Citation . Sequence analysis identified a total of 35,185 distinct tags representing 19,287 genes [13,371 from normal tissue and 13,904 from tumor tissue (Table 1)Citation ].


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  		Table 1 Summary of SAGE analysis in normal and tumor prostate tissues

 
Comparison of Expression Patterns in Normal and Tumor Tissues.
Comparison of gene expression patterns between normal prostate and tumor revealed that 156 genes were differentially expressed at a statistically significant level (P < 0.05). Ninety-one are known genes, 13 are ESTs, and 52 are novel genes (Table 2)Citation . Eighty-eight genes were up-regulated and 68 genes were down-regulated in tumor tissues. Among the 156 differentially expressed genes, 88 genes were changed >=5-fold in tumor compared to matched normal tissue (Table 3)Citation . Citation


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  		Table 2 Differentially expressed genes in prostate tissues

 

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  		Table 3 List of candidate genes that are differentially expressed in normal versus tumor prostate tissue (>=5-fold)

 

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  		Continued

 
Confirmation of SAGE Data.
Seven genes were selected for confirmation by immunostaining. The selected genes were expressed at different ratios between normal and tumor: (a) integrin {alpha} E (Hs. 851), 1:9 (approximately 9-fold); (b) E2F4 (Hs. 108371), 0:5 (>5-fold); (c) cyclin D1 (Hs. 82932), 13:5 (approximately 3-fold); (d) Daxx (Hs. 180224), 12:26 (approximately 2-fold); (e) cystatin C (Hs. 135084), 15:21 (approximately 1.5-fold); (f) VHL (Hs. 174007), 3:2 (approximately 1-fold); and (g) PSA (Hs. 171995), 120:112 (approximately 1-fold). Tissues from five individual patients were used. E2F4 showed strong epithelial staining in tumor glands but weak to no staining in normal glands (Fig. 1)Citation . Three of five patient tumor samples were positive for E2F4. In contrast, Daxx expression was stromal specific, and its intensity was stronger in areas surrounding tumor glands compared to areas surrounding normal glands (Fig. 1)Citation . Similar results were observed in all five patient samples. Integrin {alpha} E, PSA, and VHL were strongly stained, whereas cystatin C and cyclin D1 were weakly stained in epithelial cells in all five patient samples. All of these five proteins showed similar levels of staining in both normal and tumor epithelium (data not shown).



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  		Fig. 1. Immunocytochemical analysis. Paraffin-embedded prostate tissues were stained with respective antibodies as indicated and visualized by indirect avidin-biotin immunoperoxidase staining. Daxx, staining for Daxx; E2F4, staining for E2F4. Results are representative of five different patient samples.

 
Effect of Environment on Gene Expression.
To determine cellular microenvironment effects on gene expression, we compared SAGE data from the prostate tumor cell line LNCaP treated with or without DHT (in vitro) to that from normal and tumor prostate tissues (in vivo). A total of 856 genes (3.8%) were differentially expressed (P < 0.05) between LNCaP without DHT and normal tissue, 826 genes (3.6%) were differentially expressed between LNCaP without DHT and tumor tissue, 803 genes (3.5%) were differentially expressed between LNCaP with DHT and normal tissue, and 337 genes (1.4%) were differentially expressed between LNCaP with DHT and tumor tissue (Table 4)Citation . It appeared that prostate carcinoma cells in culture with androgen had the closest gene expression profile to prostate tumor cells in vivo. In total, 835 genes (2.5%) were differentially expressed (P < 0.05) between LNCaP and prostate tissues (Table 4)Citation .


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  		Table 4 Comparison of gene expression in vitro and in vivo

 
Human Prostate Transcriptome.
To estimate the total number of genes expressed in human prostate cells, we utilized our data and public SAGE data to calculate the human prostate transcriptome (Table 5)Citation . A total of 527,281 tags were obtained. Monte Carlo simulation indicates that a gene expressed at 1 copy/cell has a 78.2% chance to be detected, and a gene expressed at 4 copies/cell has a 100% chance to be detected in the 527,281 transcripts determined. Our results suggest that approximately 37,000 genes are expressed in human prostate cells (Table 5)Citation .


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  		Table 5 Human prostate transcriptome

 

   DISCUSSIONS
Top
 ABSTRACT
 INTRODUCTION
 MATERIALS AND METHODS
 RESULTS
 DISCUSSIONS
REFERENCES
 
In an effort to better understand the development of prostate cancer at the molecular level, we have generated a comprehensive gene expression profile for human prostate. Approximately 20,000 genes were analyzed, and a large number of genes differentially expressed between normal and tumor tissue were identified. Although several laboratories have used differential display to identify several differentially expressed genes (7, 8, 9) or have sequenced the ESTs to generate expression patterns in prostate (2 , 10) , our study, for the first time, provides a comprehensive gene expression profile in prostate tissue. Profiling of gene expression is useful in many ways. It allows us to identify new molecular markers. For example, among the 88 differentially expressed candidate genes identified in Table 3Citation , 44 are novel, and 8 are ESTs. Cloning and characterization of these genes may shed light on some genetic alterations during prostate cancer development. Gene expression profiling is also a robust hypothesis generator. For example, the roles of the p53 and Rb pathways in prostate cancer development are still unclear. The frequency of p53 and Rb mutation in prostate cancer is low. In the present study, no differences were observed in the expression of p21WAF1, p15, p16, p53, and Rb. However, we have observed a more than 5-fold increase in E2F4 expression in tumor tissue. E2F4 is a transcription factor that is critical for cell proliferation and whose activity is controlled by Rb-related proteins p107/p130 (11 , 12) . Therefore, p53 and Rb pathways may play important roles in prostate cancer through the alteration in E2F4 expression.

Finally, gene expression profiling may provide an alternative tool for human tumor classification that has thus far mainly relied on histology. A better classification could lead to a better diagnosis and/or prognosis. Such profiling has been successfully applied to the classification of human acute leukemias (13) .

To identify potential molecular markers for both epithelium and stroma, we used normal and tumor samples pooled from four patients. The tumor samples contained 80–90% tumor glands and 10–20% stroma. The normal samples contained 30–50% benign glands and 50–70% stroma. Thus, tumor samples had a 2–3x higher proportion of epithelial cells. This could have affected SAGE results. Although genuine differentially expressed genes such as E2F4 and Daxx were identified, integrin {alpha}-E stained epithelial cells in both normal and tumor glands with a similar intensity. Therefore, it is possible that the higher level of integrin {alpha} E found in the tumor sample is due to a higher number of epithelial cells in the tumor than in normal sample. Alternatively, the discrepancy may simply be due to a lack of correlation between the expression of mRNA and protein. Cyclin D1 also appears to lack a correlation between its mRNA and protein levels. Such mRNA-protein expression discordance is common in mammalian cells. We have observed this in a large number of androgen-regulated genes (this study). Cystatin C, VHL, and PSA protein expression seems to correlate with mRNA data.

It is believed that tumor cells in culture are different from cells in vivo. However, there is little quantitative data to confirm it. Previously, a quantitative study has been done in human colon cells by SAGE (14) . Here we have compared the gene expression profile between prostate tumor cells in vivo (tumor tissue) and a cell line in vitro (LNCaP treated with or without DHT). Among the 32,614 genes studied, approximately 2.5% of the genes (P < 0.05) were differentially expressed. This is remarkably low, considering that LNCaP cells have been maintained in culture for decades. Our data suggest that LNCaP cells should be a good model system for many aspects of studies of prostate cancer. However, we have also noticed that in between LNCaP-normal tissue and tumor tissue-normal tissue comparisons, different subsets of genes, with some overlaps, are differentially expressed under these in vivo and in vitro conditions.

Another interest of ours is to estimate the total number of genes expressed in human prostate. Despite the completion of the human genome draft, how many genes exist in Homo sapiens is still a matter of debate (15, 16, 17, 18) . Based on our SAGE data, we estimate that approximately 37,000 genes are expressed in human prostate.


   ACKNOWLEDGMENTS
 
We would like to thank Dr. Ken Kinzler (Johns Hopkins University, Baltimore, MD) for providing SAGE software.

Note Added in Proof

Data from the human genome project were published during the review of this article. Results suggested that there are approximately 40,000 genes in Homo sapiens. For our analysis described in Table 5, it will be more accurate to state that approximately 37,000 different transcripts are expressed in human prostate.


   FOOTNOTES
 
The costs of publication of this article were defrayed in part by the payment of page charges. This article must therefore be hereby marked advertisement in accordance with 18 U.S.C. Section 1734 solely to indicate this fact.

1 This study was supported in part by DAMD17-98-1-8501, R01CA74927, and a fund from Karmanos Cancer Institute. Back

2 To whom requests for reprints should be addressed, at Department of Pathology, Wayne State University, 540 East Canfield, Detroit, MI 48201. Phone: (313) 577-5634; Fax: (313) 577-0057; E-mail: yqchen{at}med.wayne.edu Back

3 The abbreviations used are: EST, expressed sequence tag; SAGE, serial analysis of gene expression; DHT, dihydrotestosterone. Back

4 http://www.ncbi.nlm.nih.gov/SAGE/. Back

Received 1/ 8/01. Accepted .


   REFERENCES
Top
 ABSTRACT
 INTRODUCTION
 MATERIALS AND METHODS
 RESULTS
 DISCUSSIONS
 REFERENCES
 

  1. Boyle P., Maisonneuve P., Napalkov P. Geographical and temporal patterns of incidence and mortality from prostate cancer. Urology, 46: 47-55, 1995.[Medline]
  2. Nelson P., Ng W, Shummer M., True L. D., Liu A. Y., Bumgarner R. E., Ferguson C., Dimak A., Hood L. An expressed-sequence-tag database of the human prostate: sequence analysis of 1168 cDNA clones. Genomics, 47: 12-25, 1998.[Medline]
  3. Cole K. A., Krizman D. B., Emmert-Buck M. R. The genetics of cancer: a 3D model. Nat. Genet., 21 (Suppl.): 38-41, 1999.[Medline]
  4. Velculescu V. E., Zhang L., Vogelstein B., Kinzler K. W. Serial analysis of gene expression. Science (Wash. DC), 270: 484-487, 1995.[Abstract/Free Full Text]
  5. Powell J. Enhanced concatemer cloning: a modification to the SAGE (serial analysis of gene expression) technique. Nucleic Acids Res., 26: 3445-3446, 1998.[Abstract/Free Full Text]
  6. Kenzelmann M., Muhlemann K. Substantially enhanced cloning efficiency of SAGE (serial analysis of gene expression) by adding a heating step to the original protocol. Nucleic Acids Res., 27: 917-918, 1999.[Abstract/Free Full Text]
  7. Blok L. J., Vijay Kumar M., Tindall D. J. Isolation of cDNAs that are differentially expressed between androgen-dependent and androgen-independent prostate carcinoma cells using differential display PCR. Prostate, 26: 213-224, 1995.[Medline]
  8. Wang F., Wang Y., Wong W., Liu Y., Addivinola F. J., Liang P., Chen L. B., Kantoff P. W., Pardee A. B. Two differentially expressed genes in normal prostate tissue and in carcinoma. Cancer Res., 56: 3634-3637, 1996.[Abstract/Free Full Text]
  9. Yang M., Loda M., Sytkowsky J. Identification of genes expressed differentially by LNCaP or PC-3 prostate cancer cell lines. Cancer Res., 58: 3732-3735, 1998.[Abstract/Free Full Text]
  10. Huang G. M., Ng W-L., Farkas J., He L., Liang H. A., Gordon D., Yu J., Hood L. Prostate cancer expression profiling by cDNA sequencing analysis. Genomics, 59: 178-186, 1999.[Medline]
  11. Beijersbergen R. L., Bernards R. Cell cycle regulation by the retinoblastoma family of growth inhibitory proteins. Biochem. Biophys. Acta, 1287: 103-120, 1996.[Medline]
  12. Moberg K., Starz M. A., Lees J. E2F4 switches from p130 to p170 and pRB in response to cell cycle reentry. Mol. Cell. Biol., 16: 1436-1449, 1996.[Abstract]
  13. Golub T. R., Slonim D. K., Tamayo P., Huard C., Gaasenbeek M., Mesirov J. P., Coller H., Loh M. L., Downing J. R., Caligiuri M. A., Bloomfield C. B., Lander E. S. Molecular classification of cancer: class discovery and class prediction by gene expression monitoring. Science (Wash. DC), 286: 531-537, 1999.[Abstract/Free Full Text]
  14. Zhang L., Zhou W., Velculescu V. E., Kern S. E., Hruban R. H., Hamilton S. R., Vogelstein B., Kinzler K. W. Gene expression profiles in normal and cancer cells. Science (Wash. DC), 276: 1268-1272, 1997.[Abstract/Free Full Text]
  15. Cohen J. The genomics gamble. Science (Wash. DC), 275: 767-772, 1997.[Free Full Text]
  16. Velculescu V. E., Madden S. L., Zhang L., Lash A. E., Yu J., Rago C., Lal A., Wang C. J., Beaudry G. A., Ciriello K. M., et al Analysis of human transcriptomes. Nat. Genet., 23: 387-388, 1999.[Medline]
  17. Pennisi E. And the gene number is. Science (Wash. DC), 288: 1146-1147, 2000.[Free Full Text]
  18. Rotman G., Shiloh Y. ATM: from gene to function. Hum. Mol. Genet., 7: 1555-1563, 1998.[Abstract/Free Full Text]



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