| HOME | HELP | FEEDBACK | SUBSCRIPTIONS | ARCHIVE | SEARCH | TABLE OF CONTENTS |
Regular Articles |
Institute for Pathology, University of Basel, Basel, Switzerland
 |
ABSTRACT |
|---|
 Top ABSTRACT INTRODUCTIONMATERIALS AND METHODSRESULTSDISCUSSIONREFERENCES |
|---|
|
INTRODUCTION |
|---|
|
TopABSTRACTINTRODUCTIONMATERIALS AND METHODSRESULTSDISCUSSIONREFERENCES |
|---|
2% of all human cancers worldwide with an incidence of 189.000 and a mortality of 91,000 in the year 2000 (1)
. RCC is characterized by absence of early warning signs leading to a rather high percentage of advanced, already metastatic tumors at first presentation. Additionally, 40% of nonmetastatic tumors will become metastatic during the course of disease (2)
. To date, there is no known cure for metastatic RCC because those tumors are unresponsive to conventional systemic therapies (3
, 4)
. The 5-year survival rate of patients suffering from metastatic RCC is <10% (5)
.
Histopathological tumor stage and grade are well-established prognostic markers for RCC (6)
. However, the clinical behavior of RCC is variable and often unpredictable. Identification of new molecular markers would facilitate outcome predictions and improve therapeutic options. For this reason, many efforts have been made to understand the genetic background of initiation and progression of RCC. Complete or partial loss of 3p is linked to clear cell RCC (cRCC)—the most common subtype of RCC accounting for 75% of all RCCs (7)
—and is the most frequent alteration in this renal tumor subtype (8, 9, 10, 11)
. The short arm of chromosome 3 harbors several potential tumor suppressor genes, including the von Hippel-Lindau gene at 3p25, the RASSF1A gene at 3p21.3, and the nonpapillary renal carcinoma-1 locus at 3p12, which all have been shown to play a role in the biology of cRCC (12, 13, 14, 15)
. In contrast to loss of 3p, which is associated with initiation of cRCC (10
, 11)
, loss of 9p and 14q have been shown to be linked to progression of cRCC (9
, 16
, 17)
. Additional cytogenetic alterations in cRCC are losses of 4q, 6q, 13q, and Xq and gains of 5q, 17p, and 17q (9
, 11)
, suggesting many still unknown genes involved in the initiation and progression of cRCC.
The development of microarray technology platforms allows rapid screening and evaluation of molecular markers and signaling pathways important in human cancer. Using cDNA microarrays, the expression levels of thousands of genes could be assessed in a limited number of samples enabling molecular classification of cancer and the identification of molecular signatures that might facilitate prediction of disease outcome and response to treatment (18, 19, 20) . Tissue microarrays (TMAs) have been designed to analyze simultaneously new cancer-related genes in hundreds of tumors on the DNA, RNA, and protein level (21 , 22) . Consequently, a combination of cDNA microarray and TMA technology is particularly suitable for rapid identification and subsequent validation of potential novel cancer markers and prognostic parameters.
In this study, we used a combination of cDNA microarray analysis and RNA in situ hybridization (RISH) on TMAs made from snap-frozen tissue specimens to identify tumor-relevant genes for cRCC. The B-cell translocation gene 2 (BTG2), coding a negative cell cycle regulator, was further analyzed in fresh frozen primary cRCCs and normal renal cortex biopsies by quantitative reverse transcription-PCR (RT-PCR). Additionally, the regulation of the BTG2 gene was studied in cRCC cell lines.
|
MATERIALS AND METHODS |
|---|
|
TopABSTRACTINTRODUCTIONMATERIALS AND METHODSRESULTSDISCUSSIONREFERENCES |
|---|
Primary Tumors and Normal Renal Tissues.
All primary renal tumors and normal renal tissues used for the TMA construction and the quantitative RT-PCR experiments were taken from our frozen tissue archives. Normal tissue samples stemmed exclusively from the renal cortex parenchyma, which predominantly consists of proximal tubules (23)
. Tumor stage and histological subtype were defined according to the recommendations of the Union International Contre Cancer (24)
and the recent RCC classification (7)
. Histological grading was done according to a three-tiered grading system (25)
. H&E-stained sections were prepared from all tissue samples and were reviewed by one pathologist (H. M) to ensure the integrity of the tissue. Representative tissue areas were marked and used for TMA construction or RNA extraction, respectively.
RNA Extraction.
Total RNA from cRCC cell lines, primary cRCCs, and normal renal cortex biopsies was extracted with TRIzol reagent (Invitrogen) according to the instructions of the manufacturer. DNase treatment of total RNA was done using DNase I system in combination with the RNeasy kit (Qiagen, Hilden, Germany). RNA concentrations were determined with a spectrophotometer.
cDNA Microarray Analysis.
Gene expression patterns of cRCC cell lines Caki-1, Caki-2, 786-O, and 769-P and normal renal tissue (Invitrogen) were analyzed using BD Atlas Human Cancer 1.2 cDNA microarrays (BD Biosciences Clontech, Palo Alto, CA). For each experiment, 5 µg of total RNA were used for single-stranded cDNA synthesis using the Atlas Pure Total RNA Labeling System (BD Biosciences Clontech) and (
-32P) dATP (Amersham Biosciences, Buckinghamshire, United Kingdom) as a label. Unincorporated nucleotides were removed using the QIAquick Nucleotide Removal kit (Qiagen). Prehybridization, hybridization, and washing of the cDNA microarrays were done according to standard protocols. Arrays were exposed to a high-resolution screen (Packard Bioscience Company, Toronto, Ontario, Canada) for 24 h and scanned (Cyclone; Packard Bioscience Company). AtlasImage 1.01a software (BD Biosciences Clontech) was used for digital image analysis. Background-corrected signal density (sDens) values were calculated for each array spot and were normalized according to the AtlasImage sum method. Genes with aberrant expression were identified by calculating ratios between signal densities of each spot on the cell line (test) arrays and the corresponding array spot on the normal renal tissue (reference) array. Only genes showing sDens ratios 
+4 or 
-4 in at least two renal cancer cell lines were considered as significantly differentially expressed.
TMA.
A TMA was constructed from frozen tissue samples of 51 cRCCs, 4 papillary RCCs, 4 chromophobe RCCs, 2 oncocytomas, and 12 tissues from normal renal cortex. There were 32 pT1, 4 pT2, and 15 pT3 cRCCs. Twelve cRCCs were grade 1, 32 grade 2, and 7 grade 3. The TMA was constructed in frozen Tissue-Tek OCT compound (Miles Laboratories, Naperville, IL) as described previously (22)
. We optimized a commercialized microarray device (Beecher Instruments, Sun Prairie, WI) by using a 0.6-mm drill for recipient whole making instead of the conventional hollow needle. Fig. 1A–C
shows the renal TMA generated for this study.
|
-33P) dATP (Amersham Biosciences) using terminal deoxynucleotidyltransferase (Promega, Madison, WI) following the instructions of the manufacturer. Oligonucleotide probes were pooled and unincorporated nucleotides were removed using the QIAquick Nucleotide Removal kit (Qiagen). Air-dried TMA sections were hybridized with 2–4 ng of radiolabeled probe in hybridization mix (50% formamide, 10% dextransulfate, 2x SSC) in a moist chamber at 42°C overnight. After hybridization, slides were washed in 1x SSC at 55°C (4 x 15 min), incubated in distilled H2O, 60 and 90% ethanol (30 s each), and air-dried. Slides were exposed to high-resolution screens for 48 h (Packard Bioscience Company) prior scanning.
ArrayVision software package (Imaging Research Inc., St. Catharines, Ontario, Canada) was used for image analysis. In brief, for each experiment signal density (sDens) values were obtained for all tissue spots on the TMA as well as for the background (measured between tissue spots of a given slide and averaged). The mean background sDens values were nearly identical for all slides. To safely distinguish between true positivity and background signals, only those tissue spots were considered positive for gene expression that showed sDens values 2-fold mean background value.
After image analysis, slides were incubated in Hypercoat LM-1 emulsion (Amersham Biosciences) for 2–4 weeks to evaluate the hybridization specificity by direct autoradiography. After development of the emulsion, slides were counterstained with hematoxylin to facilitate microscopical reevaluation of the TMAs. Spots that lost >40% cells during the experimental process were considered to be not analyzable and were therefore excluded from additional statistical analysis.
Northern Analysis.
PolyA+ RNA was extracted from total RNA of Caki-1, Caki-2, 786-O, and 769-P and normal renal tissue (Invitrogen) using the polyA+ RNA extraction kit from Qiagen. One µg polyA+ RNA of each sample was separated by gelelectrophoresis and blotted to a Hybond-N+ membrane (Amersham Biosciences) following standard protocols (26)
.
Single-stranded DNA probes were generated from 25 ng of BTG2 and G3PDH PCR products using 25 ng sequence-specific reverse primers for BTG2 or G3PDH, respectively, (-32P) dATP (Amersham Bioscience), 0.5 mM dCTP, dGTP, and dTTP, and Klenow enzyme (Promega). QIAquick Nucleotide Removal kit was applied to remove unincorporated nucleotides (Qiagen). Prehybridization, hybridization, and washing of the blot were done according to conventional protocols (26)
. The Northern was exposed to a high-resolution screen (Packard Bioscience Company) before scanning.
Quantitative RT-PCR.
PCR standard curves for BTG2 and the reference G3PDH were generated to allow quantification of the copy numbers of both genes. Serial dilutions of BTG2 and G3PDH in vitro generated transcripts (1012–101 copies) were mixed with rRNA from mice (Roche, Basel, Switzerland) to a final concentration of 0.5 µg/µl.
Two µl of each dilution were reverse transcribed using 50 ng of random hexamers (Invitrogen), 1 mM of each deoxynucleotide triphosphate, 5 mM MgCl2, 1.5 mM Tris-HCl (pH 8.0), 500 mM KCl, 100 units of Moloney murine leukemia virus reverse transcriptase (Invitrogen), and 20 units of RNAsin (Roche) in a total volume of 19.5 µl for 10 min at 25°C and 60 min at 37°C. After heat inactivation of the enzymes, the remaining RNA was treated with 0.5 µl (1 unit) RNase H (Invitrogen) at 37°C for 20 min.
Five µl of a 1:2.5 dilution of each first strand product was amplified using 2 µl of LightCycler-FastStart DNA Master SYBR Green I (Roche), BTG2 (forward: 5'-ctcacctgcaagaaccaagtg-3'; reverse: 5'-agttccccaggttgaggtatgt-3') and G3PDH (forward: 5'-gaaatcccatcaccatcttcc-3'; reverse: 5'-cagagatgatgacccttttgg-3') primer pairs at a final concentration of 1 µM each and MgCl2 at a final concentration of 2 mM for BTG2 and 3 mM for G3PDH. PCR was performed in a total volume of 20 µl for 10 min at 95°C and 40 cycles with 15 s at 95°C, 10 s at 58°C and 7 s at 72°C. PCR efficiencies were calculated from the standard curves (Fig. 3, A and B)
. Melting curve analysis (LightCycler software package) was applied to ensure the specificity of the PCR reaction (Fig. 3C)
.
|
Induction of BTG2 Expression by 12-O-Tetradecanoylphorbolester-13-Acetate (TPA).
Caki-1, Caki-2, 786-O, 769-P, and HeLa (positive control) were plated at 500,000 cells/25 ml culture vessel. Medium renewal was done 24 h after plating. RNA was extracted after 48 h from each cell line to determine the BTG2 and G3PDH mRNA expression level prior to treatment. The remaining cells were treated with various concentrations of TPA (25, 50, 75, or 100 ng/ml culture medium) or DMSO alone (0.1% final concentration). RNA was extracted 70 min after addition of TPA/DMSO. BTG2 and G3PDH mRNA copy numbers were determined by quantitative RT-PCR following the protocol described above.
BTG2 mRNA Expression and Cell Density.
Caki-1, Caki-2, 786-O, and 769-P were plated at 100,000, 200,000, and 500,000 cells/well in 6-well plates. Medium renewal was done 24 h after plating. RNA was extracted after 48 h to determine BTG2 and G3PDH mRNA copy numbers by quantitative RT-PCR as described above.
Statistics.
In RISH experiments, analyzable (>60% representative cells) tissue spots showing sDens values 2-fold mean background sDens value were considered positive for gene expression, whereas the remaining evaluable tissue spots were considered negative for gene expression. Results obtained by RISH were than evaluated in two ways. In a first approach, contingency table (
2) analysis was used to search for differences in the expression frequency of a given gene. For this purpose, the percentage of spots positive for gene expression was compared between normal renal tissue and cRCC and also within the subset of cRCCs. In a second approach, average sDens values were calculated from gene expression positive spots to obtain the mean expression level of a given gene. Those expression levels were than compared between normal renal tissue and cRCC and also within the subset of cRCCs using ANOVA analysis.
Data obtained by quantitative RT-PCR were evaluated by (a) ANOVA analysis to search for differences in the BTG2 mRNA expression between normal renal tissue and primary cRCC and within the subset of cRCCs and (b) Kaplan Meyer analysis to search for associations between the BTG2 mRNA expression and patient survival.
|
RESULTS |
|---|
|
TopABSTRACTINTRODUCTIONMATERIALS AND METHODSRESULTSDISCUSSIONREFERENCES |
|---|
. As an example, BTG2 showed reduced expression in all four cRCC cell lines (Fig. 2, A and B)
.
|
|
.
|
, Fig. 2C
). In a second step, we searched for associations between the expression frequencies of the analyzable 19 genes and tumor stage and grade in the subset of cRCCs. There was an association between expression frequency and tumor stage for BTG2 and CD9. Both genes were detectable in pT1/pT2 (BTG2: 4 of 24, 17%; CD9: 6 of 20, 30%) but not in pT3 tumors (BTG2: 0 of 11; CD9: 0 of 9). There was an association between expression frequency and tumor grade for TIMP3, which was significantly less frequent expressed in grade 3 (1 of 5; 20%) than in grade 2 (17 of 23; 74%) and grade 1 cRCC (7 of 8; 88%; P = 0.03).
We also searched for differences in the expression levels between normal renal tissue and cRCC and also within the subset of cRCCs for all 19 analyzable genes. VIM was significantly stronger expressed in cRCC than in normal renal tissue (P = 0.04). CD74 was significantly higher expressed in pT3 cRCC than in pT1/2 cRCC (P = 0.03).
Northern Blot.
Northern analysis was performed to verify the results of the cDNA microarray experiment in an independent approach. The 2.7-kb mRNA of BTG2 was expressed in normal renal tissue but not in renal cancer cell lines, confirming the results from our cDNA microarray experiment (Fig. 2D)
.
Quantitative RT-PCR.
mRNA expression levels of BTG2 in frozen primary cRCCs and normal renal cortex biopsies were assessed by quantitative RT-PCR using the LightCycler system (Fig. 3A–C)
.
Compared with the mean normalized BTG2 mRNA copy number of normal renal tissue, cRCC showed an average of a 6.7-fold (1.6–44-fold) reduced expression (P < 0.0001; Fig. 3D
) However, there was no significant correlation between BTG2 expression and tumor stage, grade, or other clinical parameters in primary cRCC.
Induction of BTG2 mRNA Expression by TPA.
Because TPA is a potent inductor for BTG2 expression in different cell lines, including HeLa (27
, 28)
, we studied the inducibility of BTG2 expression in cRCC cell lines by TPA. All four cRCC cell lines and the cervix carcinoma cell line HeLa (positive control) were treated with various concentrations of TPA. In contrast to the BTG2 copy numbers, which were comparable with those obtained for primary cRCCs, G3PDH copy numbers were strongly increased in the cRCC cell lines but remained stable throughout the experiment (data not shown). There was a 15-fold increase of the BTG2 expression in HeLa cells. Among the renal cancer cell lines, only Caki-1 showed a slightly elevated (2.3-fold) increase of BTG2 expression after TPA treatment (Fig. 4)
.
|
shows the correlation between cell density and BTG2 expression for all analyzed cell lines.
|
|
DISCUSSION |
|---|
|
TopABSTRACTINTRODUCTIONMATERIALS AND METHODSRESULTSDISCUSSIONREFERENCES |
|---|
TMAs, usually made from formalin-fixed, paraffin-embedded tissue, are an excellent tool for studying protein expression by immunohistochemistry and gene aberrations by fluorescence in situ hybridization (35, 36, 37, 38) . However, these TMAs are not optimally suited for RISH studies. Processing of tissue and tissue fixation using formalin causes degradation and chemically modifies RNA, respectively (39 , 40) . It was shown that TMAs generated from frozen tissue specimens (22) are a better tool for studying mRNA expression patterns of tumor relevant genes.
As the focus of biomedical research is shifting from genomics to proteomics, TMAs from frozen tissue are also likely to prove useful for mass-scale testing of antibodies that are not working on formalin-fixed, paraffin embedded tissue.
The frozen TMA generated in our study, served to demonstrate the utility and feasibility of RISH on TMAs. This method is convenient for further validating RNA expression of most candidate genes identified by cDNA array analysis. A minor fraction of genes was analyzable on the cDNA microarray but showed no detectable mRNA expression on the TMA. There are two explanations for the observed discrepancies: (i) Because the cDNA microarray experiments were performed with RNA extracted from cRCC cell lines, expression of some genes might be cell line specific. (ii) Because the absolute number of mRNA target sequences in a 0.6 mm diameter TMA spot is below the number of cDNA sequences present in a cDNA microarray spot some genes showing weak expression on the cDNA microarray remain undetected by RISH.
On the basis of the data obtained from the cDNA microarray and RISH experiments BTG2 was selected for further analysis. Strong BTG2 expression in normal cells but reduced or absent expression in cRCC cell lines and primary tumors suggest that BTG2 inactivation is important for cRCC development. Several lines of evidence in the literature indicate that this gene has tumor suppressive properties: (i) It was shown that BTG2 is involved in negative cell cycle regulation and differentiation (29 , 41 , 42) . (ii) BTG2 is also involved in DNA damage response and is one of the primary targets of p53 (29 , 43) . (iii) In the normal kidney, BTG2 protein is strongly expressed in the epithelial cells of the proximal tubules from which cRCC arise (25 , 44) . Unfortunately, we were not able to proof the latter finding by RISH because of the insufficient resolution of our detection system. However, since each normal kidney biopsy represented on our TMA exclusively derived from the renal cortex parenchyma we believe that the strong BTG2 mRNA expression stems from proximal tubules, which is the major component of this cortical substructure (23) .
Using quantitative RT-PCR, we confirmed the data obtained from the cDNA microarray, RISH, and Northern experiments. Compared with primary cRCC there was an average 6.7-fold stronger expression of BTG2 mRNA in normal renal tissue. BTG2 mRNA expression level was independent of tumor stage and grade suggesting that the reduction of BTG2 mRNA expression is not associated with tumor progression and might be an early event in renal tumorigenesis.
To address the possible tumor suppressive function of BTG2 in renal tumors, we studied the regulation of BTG2 mRNA expression in renal cancer. Recently, it has been shown that BTG2 is an immediate early response gene, whose transcription can be induced by the phorbolester TPA in human HeLa cells and also in a variety of rodent cell lines of different origin (27 , 28) . These findings prompted us to investigate the inducibility of BTG2 expression by TPA in the cRCC cell lines Caki-1, Caki-2, 786-O, and 769-P. Among all tested cRCC cell lines, merely Caki-1 cells showed a response to TPA. However, compared with HeLa, the increase in BTG2 mRNA expression was very weak (15-fold versus 2.3-fold) suggesting that BTG2 induction is regulated by different mechanism in cervical and renal cancers.
The putative function of BTG2 as a cell cycle regulator was demonstrated recently by the observation that BTG2 expression is low in exponentially growing hepatocarcinoma, breast tumor, and normal prostate cell lines, whereas normal quiescent cells showed high BTG2 expression levels (29 , 30) . Our experiments showed that BTG2 expression was positively associated with increasing cell densities in Caki-2, 786-O, and 769-P but not in Caki-1 cultures. Because Caki-1 derives from a skin metastasis of a cRCC it is tempting to speculate that the ability of BTG2 induction changes during the metastatic process.
BTG2 expression levels in the four cRCC cell lines were comparable with those of the 42 primary tumors. Interestingly, neither TPA nor high cell densities were able to raise BTG2 expression to the level observed in normal renal tissues. This finding corroborates our theory that down-regulation of BTG2 is an important mechanism involved in renal cancer development.
The mechanisms leading to reduced BTG2 expression are yet unknown. Further studies will be necessary to elucidate whether aberrations in the up-stream signaling pathways of BTG2 or methylation of the BTG2 promoter are responsible for impaired expression in cRCC.
Beside BTG2, other genes identified in our study might play an important role in renal tumor biology. For example, reduced expression was also seen for two other genes, CHES1 and LITAF, in cRCC cell lines and primary cRCC. Human CHES1, a member of the family of forkhead/winged transcription factors, is suggested to be involved in DNA damage response because this protein is able to suppress multiple yeast checkpoint mutations (45)
. Reduced expression levels of CHES1 might result in genomic instability, which is one of the hallmarks of cancer. LITAF is involved in the activation of the human TNF- gene (46)
, which encodes for a multifunctional cytokine capable of inducing apoptosis, by binding to TNF receptor (47)
.
CD74, which was down-regulated in cRCC cell lines, was expressed in primary renal tumors with expression levels similar to normal renal tissue. High expression levels were significantly associated with advanced tumor stage in primary cRCC suggesting a potential role of this gene in tumor progression. The possible oncogenic properties of CD74 in RCC would be consistent with findings from other groups because (i) CD74 is localized on chromosome 5q which is frequently gained in cRCC (9) , (ii) strong and frequent CD74 protein expression in primary cRCC was recently described (48 , 49) , and (iii) increased CD74 protein expression is associated with tumor progression in colon and gastric cancers (50 , 51) .
In summary, the combination of cDNA microarray and TMA technologies enabled us to identify three novel renal cancer gene candidates, BTG2, CHES1, and LITAF. Inactivation of BTG2, a cell cycle regulator, suggests a potential mechanism required for renal tumorigenesis. Further studies on the identified genes will contribute to a better understanding of renal cancer biology.
|
ACKNOWLEDGMENTS |
|---|
|
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.
Requests for reprints: Dr. Holger Moch, Institute for Pathology, Schoenbeinstrasse 40, CH-4031 Basel, Switzerland. Phone: 41-61-265-2980; Fax: 41-61-265-3194; E-mail: hmoch{at}uhbs.ch
1 Internet address: http://www.ncbi.nlm.nih.gov. 
Received 6/10/03. Revised 12/22/03. Accepted 12/31/03.
|
REFERENCES |
|---|
|
TopABSTRACTINTRODUCTIONMATERIALS AND METHODSRESULTSDISCUSSIONREFERENCES |
|---|
gene expression: molecular cloning, sequencing, characterization, and chromosomal assignment. Proc. Natl. Acad. Sci. USA, 96: 4518-4523, 1999. and the TNF receptor superfamily: structure-function relationship(s). Microsc. Res. Tech., 50: 184-195, 2000.[CrossRef][Medline]
This article has been cited by other articles:
|
|
 |
|
  Y.-B. Lim, T. J. Park, and I. K. Lim B Cell Translocation Gene 2 Enhances Susceptibility of HeLa Cells to Doxorubicin-induced Oxidative Damage J. Biol. Chem., November 28, 2008; 283(48): 33110 - 33118. [Abstract] [Full Text] [PDF]
|
|
|
|
 |
|
 R. J. Wozniak, S. Keles, J. J. Lugus, K. H. Young, M. E. Boyer, T. M. Tran, K. Choi, and E. H. Bresnick Molecular Hallmarks of Endogenous Chromatin Complexes Containing Master Regulators of Hematopoiesis Mol. Cell. Biol., November 1, 2008; 28(21): 6681 - 6694. [Abstract] [Full Text] [PDF]
|
|
|
|
 |
|
 M. R.H. Estecio, P. S. Yan, A. E.K. Ibrahim, C. S. Tellez, L. Shen, T. H.-M. Huang, and J.-P. J. Issa High-throughput methylation profiling by MCA coupled to CpG island microarray Genome Res., October 1, 2007; 17(10): 1529 - 1536. [Abstract] [Full Text] [PDF]
|
|
|
|
 |
|
 S. Farioli-Vecchioli, M. Tanori, L. Micheli, M. Mancuso, L. Leonardi, A. Saran, M. T. Ciotti, E. Ferretti, A. Gulino, S. Pazzaglia, et al. Inhibition of medulloblastoma tumorigenesis by the antiproliferative and pro-differentiative gene PC3 FASEB J, July 1, 2007; 21(9): 2215 - 2225. [Abstract] [Full Text] [PDF]
|
|
|
|
 |
|
 L. J. Donato, J. H. Suh, and N. Noy Suppression of Mammary Carcinoma Cell Growth by Retinoic Acid: the Cell Cycle Control Gene Btg2 Is a Direct Target for Retinoic Acid Receptor Signaling Cancer Res., January 15, 2007; 67(2): 609 - 615. [Abstract] [Full Text] [PDF]
|
|
|
|
 |
|
 H. Was, T. Cichon, R. Smolarczyk, D. Rudnicka, M. Stopa, C. Chevalier, J. J. Leger, B. Lackowska, A. Grochot, K. Bojkowska, et al. Overexpression of Heme Oxygenase-1 in Murine Melanoma: Increased Proliferation and Viability of Tumor Cells, Decreased Survival of Mice Am. J. Pathol., December 1, 2006; 169(6): 2181 - 2198. [Abstract] [Full Text] [PDF]
|
|
|
|
|
|
V. Busygina, M. C. Kottemann, K. L. Scott, S. E. Plon, and A. E. Bale Multiple Endocrine Neoplasia Type 1 Interacts with Forkhead Transcription Factor CHES1 in DNA Damage Response. Cancer Res., September 1, 2006; 66(17): 8397 - 8403. [Abstract] [Full Text] [PDF]
|
|
|
|
|
|
D. Passeri, A. Marcucci, G. Rizzo, M. Billi, M. Panigada, L. Leonardi, F. Tirone, and F. Grignani Btg2 Enhances Retinoic Acid-Induced Differentiation by Modulating Histone H4 Methylation and Acetylation Mol. Cell. Biol., July 1, 2006; 26(13): 5023 - 5032. [Abstract] [Full Text] [PDF]
|
|
|
|
|
|
F. Lopez-Rios, S. Chuai, R. Flores, S. Shimizu, T. Ohno, K. Wakahara, P. B. Illei, S. Hussain, L. Krug, M. F. Zakowski, et al. Global Gene Expression Profiling of Pleural Mesotheliomas: Overexpression of Aurora Kinases and P16/CDKN2A Deletion as Prognostic Factors and Critical Evaluation of Microarray-Based Prognostic Prediction. Cancer Res., March 15, 2006; 66(6): 2970 - 2979. [Abstract] [Full Text] [PDF]
|
|
|
|
 |
|
 A. D. Boiko, S. Porteous, O. V. Razorenova, V. I. Krivokrysenko, B. R. Williams, and A. V. Gudkov A systematic search for downstream mediators of tumor suppressor function of p53 reveals a major role of BTG2 in suppression of Ras-induced transformation Genes & Dev., January 15, 2006; 20(2): 236 - 252. [Abstract] [Full Text] [PDF]
|
|
|
|
|
|
J. W. Hong, M. S. Ryu, and I. K. Lim Phosphorylation of Serine 147 of tis21/BTG2/pc3 by p-Erk1/2 Induces Pin-1 Binding in Cytoplasm and Cell Death J. Biol. Chem., June 3, 2005; 280(22): 21256 - 21263. [Abstract] [Full Text] [PDF]
|
|
|
|
 |
|
 Y. Li, X. Hong, M. Hussain, S. H. Sarkar, R. Li, and F. H. Sarkar Gene expression profiling revealed novel molecular targets of docetaxel and estramustine combination treatment in prostate cancer cells Mol. Cancer Ther., March 1, 2005; 4(3): 389 - 398. [Abstract] [Full Text] [PDF]
|
|
|
|
|
|
S. Park, Y. J. Lee, H.-J. Lee, T. Seki, K.-H. Hong, J. Park, H. Beppu, I. K. Lim, J.-W. Yoon, E. Li, et al. B-Cell Translocation Gene 2 (Btg2) Regulates Vertebral Patterning by Modulating Bone Morphogenetic Protein/Smad Signaling Mol. Cell. Biol., December 1, 2004; 24(23): 10256 - 10262. [Abstract] [Full Text] [PDF]
|
|
|
|
 |
|
 M.-H. Tan, C. G. Rogers, J. T. Cooper, J. A. Ditlev, T. J. Maatman, X. Yang, K. A. Furge, and B. T. Teh Gene Expression Profiling of Renal Cell Carcinoma Clin. Cancer Res., September 15, 2004; 10(18): 6315S - 6321S. [Abstract] [Full Text] [PDF]
|
|
| ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| HOME | HELP | FEEDBACK | SUBSCRIPTIONS | ARCHIVE | SEARCH | TABLE OF CONTENTS |
| Cancer Research | Clinical Cancer Research |
| Cancer Epidemiology Biomarkers & Prevention | Molecular Cancer Therapeutics |
| Molecular Cancer Research | Cancer Prevention Research |
| Cancer Prevention Journals Portal | Cancer Reviews Online |
| Annual Meeting Education Book | Meeting Abstracts Online |
