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Carcinogenesis Advance Access originally published online on January 10, 2006
Carcinogenesis 2006 27(7):1420-1431; doi:10.1093/carcin/bgi341
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© The Author 2006. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oxfordjournals.org

Efficacy of the farnesyltransferase inhibitor R115777 in a rat mammary tumor model: role of Ha-ras mutations and use of microarray analysis in identifying potential targets

Ruisheng Yao, Yian Wang, Yan Lu, William J. Lemon, David W. End 1, Clinton J. Grubbs 2, Ronald A. Lubet 3 and Ming You *

Department of Surgery and The Alvin J. Siteman Cancer Center, Campus Box 8109, 660 S. Euclid Avenue, Washington University School of Medicine, St Louis, MO 63110, USA, 1 Janssen Research Foundation, Spring House, PA 19477, USA, 2 Chemoprevention Center, University of Alabama at Birmingham, Birmingham, AL 35294, USA and 3 Chemoprevention Branch, National Cancer Institute, Bethesda, MD 20892, USA

* To whom correspondence should be addressed. Email: youm{at}msnotes.wustl.edu


   Abstract
Top
 Abstract
Introduction
 Materials and methods
 Results
 Discussion
 References
 
Rats treated with the alkylating agent methylnitrosourea (MNU) develop multiple, hormonally dependent mammary tumors. Roughly 50% of the tumors have Ha-ras mutation, whereas 50% do not. The MNU-induced rat mammary tumor model was employed to examine the therapeutic efficacy of the farnesyltransferase inhibitor (FTI), R115777, and to examine the use of genomics in identifying susceptible tumors as well as identifying genes whose expression are modulated by FTI treatment. In animals bearing palpable mammary tumors (<7 mm diameter), we performed a surgical biopsy, and 3 days following the biopsy, rats were treated with R115777 (50 mg/kg body wt/day) by gavage. Tumors with Ha-ras mutations underwent profound regression, with nearly 90% showing complete regressions within 4 weeks. In contrast, the non-Ha-ras mutation-bearing tumors yielded a more variable response, although roughly half of the non-Ha-ras mutation tumors underwent significant regression. These results show that although all tumors appear to respond to the FTI inhibitor the tumors with Ha-ras mutations were exquisitely sensitive. We employed a microarray approach to define potential targets and the mechanism of action of R115777 in Ha-ras mutant or wildtype tumors following treatment with FTI. In addition, we determined whether gene expression prior to FTI treatment can be used to differentiate highly sensitive tumors (Ha-ras mutant) and tumors with variable sensitivity (Ha-ras wildtype). Untreated or FTI-treated (4 days at 50 mg/kg body wt) tumors (Ha-ras mutant or wildtype) were examined using oligonucleotide arrays. A significant number of genes were differentially expressed in control rat mammary tumors with or without an activated Ha-ras mutation, suggesting that a microarray analysis might differentiate highly sensitive and variably sensitive tumors. Most of the genes whose expressions were modulated by FTI in tumors were independent of Ha-ras status and were presumably modulated by effects on farnesylation of proteins other than Ha-ras. However, treatment of Ha-ras-mutated mammary tumors with R155777 results in preferential modulation of genes involved in ras-MAP kinase signal transduction pathway and in decreased expression of many genes involved with cell proliferation. In contrast, several classes of genes are altered in rat mammary tumors without a mutated Ha-ras, suggesting that non-ras targets are involved. Ras pathway related genes, p53, WT1 and PCNA, were preferentially modulated in Ha-ras-mutated tumors, whereas modulation of genes in the G-protein pathway, various cytochrome p450s and RB1 are involved in Ha-ras wildtype tumors. Elucidation of gene expression changes in FTI-treated or control rat mammary adenocarcinomas will help in identifying potential pharmacodynamic markers of FTI treatment as well as potential molecular targets of R115777 and other FTIs.

Abbreviations: EST, expressed sequence tags; FTI, farnesyltransferase inhibitor; MNU, methylnitrosourea; RT–PCR, reverse transcription–polymerase chain reaction


   Introduction
Top
 Abstract
 Introduction
Materials and methods
 Results
 Discussion
 References
 
The Ras GTPase gene(s) are involved in signaling a wide range of growth factors and growth factor receptors, including EGFR, Neu, FGF and VEGF (1). Reflecting its central role in determining cell proliferation, Ras is one of the most commonly mutated human oncogenes (2). This family of genes is mutated in a substantial percentage of the two greatest cancer killers in humans (lung and colon) and appears to be mutated in virtually every pancreatic cancer, implying that its mutation may be mandatory for this form of cancer. The Ras genes were identified almost 35 years ago since they were proved to be the primary oncogene in two of the classic oncogenic viruses in mice, specifically Ki-ras in Ki MuSV (Kirsten murine sarcoma virus) and Ha-ras in HSV (Harvey sarcoma virus) (3–5). The Ras oncogene proteins must be prenylated in order to be translocated to the cell membrane and become functional (1). Since their activation is dependent upon this translocation, blocking the prenylation of these proteins has become a major potential focus for pharmacologically intervening in Ras activation. The agent that we have employed is R115777, which is an orally bioavailable imidazole analog that blocks prenylation of Ha-ras, but not Ki-ras and N-ras (6). Inhibition of the growth of tumors that harbor Ki-ras or N-ras mutations indicated that farnesyltransferase inhibitors (FTIs) also target other proteins important in oncogenesis. Like most of the FTIs, it requires significantly higher doses to block the farnesylation of Ki-ras (7). In view of the ability of FTI to inhibit various cancers with Ki-ras mutations, or with no Ras mutations at all, investigators have searched for alternative proteins that are prenylated and might be candidate target genes, for example, Rho B, CNEB E/F and Rheb (1).

The chemically induced models of mammary carcinogenesis were initially developed almost 40 years ago by Huggins et al. (8,9). Female Sprague-Dawley rats develop multiple hormonally responsive mammary cancers, starting within 5 weeks of the time that they are administered the carcinogen. In the methylnitrosourea (MNU) model, ~50% of the resulting tumors have mutations in codon 12 of Ha-ras (10,11). In contrast to this significant contribution of Ras mutations to tumorigenesis in the rat models of mammary cancer, mutations in this family of genes are infrequently observed in human breast cancer. However, increased expression of Ras itself or of MAP kinase (one of its downstream effectors elements) is observed in ~50% of breast cancers (12). Furthermore, upstream effectors of the ras proteins, for example, EGFR and HER2/Neu, are overexpressed in many human mammary tumors. The appeal of this model is that the tumors arise in situ, that roughly 50% of the tumors have mutation and that the mutations are focal. In contrast, transgenic mice overexpressing ras typically have these genes overexpressed in a high percentage of cells in the breast (13). Furthermore, in the case of the transgenic, the fact that the overexpression is the primary oncogenic event almost determines by itself that inhibition of the activating gene will result in profound effects on tumors.

We, therefore, examined the therapeutic effect of the FTI in this model to determine if FTI is effective in this model system, and if therapeutic efficacy is much more striking in tumors with mutation in Ha-ras. On the basis of the results of this experiment, which demonstrate exquisite sensitivity in Ha-ras mutation positive tumors, we employed genomic approaches to (i) define genes whose expression are modulated and may contribute to the mechanism of action of R115777 in Ha-ras mutation positive or negative tumors; (ii) determine whether gene expression differences can be used to differentiate exquisitely sensitive tumors (Ha-ras mutant) and variably sensitive tumors (Ha-ras wildtype) prior to FTI treatment.


   Materials and methods
Top
 Abstract
 Introduction
 Materials and methods
Results
 Discussion
 References
 
Chemicals
Chemicals and other materials were obtained as follows: corn oil was purchased from Sigma Chemical (St Louis, MO). MNU was obtained from NCI Chemical Repository (Bethesda, MD). FTI R115777 was kindly supplied by Johnson and Johnson Pharmaceuticals (Raritan, NJ). Tekclad Mash diet and Sprague-Dawley rats were purchased from Harlan Sprague Dawley (Indianapolis, IN).

Chemotherapeutic studies
Generation of MNU-induced tumors and their use in therapeutic models have been described previously (11,14). Female Sprague-Dawley rats were obtained at 28 days of age and housed in polycarbonate cages (5 rats/cage). At 50 days of age the rats received a single i.v. injection of MNU (50 mg/kg body weight) via the jugular vein. Rats were then examined two times per week for the formation of palpable lesions. Palpable lesions began to arise beginning roughly 5 weeks post MNU. When a tumor reached a volume of ~150–300 mm3, as measured by calipers, animals were anesthetized and mammary tumors were biopsied. The resulting biopsies were placed into liquid nitrogen and the Ki-ras and Ha-ras mutation status of the tumors was examined employing the sequencing procedures outlined below. Tumor volume was calculated on the basis of caliper measurement of individual lesions in two axes and it was presumed that the tumors had a spherical shape. Beginning 5 days following the biopsy, rats were treated with 50 mg/kg body weight/day of R115777 in corn oil. Tumor volume of individual lesions was monitored for an additional 28 days. Tumor growth/regression rates for FTI tumors with or without Ha-ras mutations were compared on the basis of a Wilcoxon Rank analysis.

Analysis of Ras mutations by PCR-direct sequencing
DNA was isolated from rat mammary tumors using the TRIzol (Gibco BRL Carlsbad, CA). Sequences of PCR primers for the exon 1 of the Ki-ras and Ha-ras gene were described previously (11). The 12th codon mutations were analyzed with an ABI PRISM 3700 DNA analyzer (PE Applied Biosystems, Foster City, CA). The primers for Ki-ras gene are as follows: forward: 5'-AGGCCTGCTGAAAATGACTG-3'; backward: 5'-CACCGATGGTTCCCTATTAC-3'. The primers for Ha-ras genes are as follows: forward: 5'-AGTGTGATTCTCATTGGCAG-3'; backward: 5'-TCCTACCTCTTCTTAGACAG-3'.

RNA isolation
Random selected eight rat mammary tumors treated with R115777 or with vehicle control were microdissected to remove surrounding stroma cells before being used for RNA isolation. Generally, two 5 µm frozen sections (with 50–100 µm distance between) were cut using a cryostat microtome. End portions of each collected tissue were paraffin-embedded and H&E stained for identification of areas enriched in glandular cells that were used for RNA analysis. Glandular cell-rich portions of the tissue were snap-frozen in liquid nitrogen and subsequently transferred to a –80°C freezer for storage and subsequent use in RNA isolation. Total RNA was extracted from rat mammary tumors using TRIzol (Gibco BRL Carlbad, CA) according to the manufacturer's instruction. The quality of RNA was confirmed on a formaldehyde agarose gel, and the concentration was determined by reading absorbance at 260/280 nm. We selected individual rat mammary tumors from FTI-treated rats and individual rat mammary tumors from control animals for gene expression profiling employing the Affymetrix gene chip analysis using rat RGU34A array, which includes >8000 genes and expressed sequence tags (ESTs).

cRNA preparation
Total RNA (8 µg) was used as starting material for the cDNA preparation. The first- and second-strand cDNA synthesis was performed using the SuperScript Choice System (Life Technologies Carlsbad, CA) according to the manufacturer's instructions. Labeled cRNA was prepared using the MEGAscript In Vitro Transcription Kit (Ambion Austin, TX). Biotin-labeled CTP and UTP were used in the reaction together with unlabeled NTPs. After the reaction, the unincorporated nucleotides were removed using RNeasy columns (Qiagen Valencia, CA).

Array hybridization and scanning
Approximately 10 µg of cRNA was fragmented at 94°C for 35 min in a fragmentation buffer containing 40 mM Tris–acetate (pH 8.1), 100 mM KOAc and 30 mM MgOAc. Before hybridization, the fragmented cRNA was placed in a 6x SSPE-T hybridization buffer [1 M NaCl, 10 mM Tris (pH 7.6) and 0.005% Triton] and heated to 95°C for 5 min and, subsequently, to 40°C for 5 min before loading onto the Affymetrix probe array cartridge. The probe array was then incubated for 16 h at 40°C at constant rotation (60 r.p.m.). The washing and staining procedure was performed in the Affymetrix Fluidics Station. The probe array was exposed to 10 washes in 6x SSPE-T at 25°C followed by 4 washes in 0.5x SSPE-T at 50°C. The biotinylated cRNA was stained with a streptavidin–phycoerythrin conjugate (10 µg/ml; Molecular Probes, Eugene, OR) in 6x SSPE-T for 30 min at 25°C followed by 10 washes in 6x SSPE-T at 25°C. The probe arrays were scanned at 560 nm using a confocal laser-scanning microscope with an argon ion laser as the excitation source (Hewlett Packard GeneArray Scanner G2500A). The readings from the quantitative scanning were analyzed by the Affymetrix Gene Expression Analysis software.

Color display of gene expression
Colorized versions of gene expression are shown in the tables. Since the oligonucleotide arrays utilize one narrow-band fluorophores, which provides its signal in intensity alone, visualization with color involves a mapping of intensity with hue. In the following data, colors are produced by a linear variation from pure black to white. This scheme involves a natural, straight-line path from one edge of the color wheel through the center and to the opposite edge. Black denotes expression higher than the mean for the tissue, grey denotes near mean expression and white denotes lower than mean expression.

Array normalization, analysis and semiquantitative reverse transcription–polymerase chain reaction (RT–PCR) confirmation
Four independent samples were collected for each group. Array normalization and gene expression estimates were obtained using Affymetrix Microarray Suite 5.0 software (MAS5). The array mean intensities were scaled to 1500. The standard Affymetrix normalization was carried out on probeset expression measures so that all chips have the same mean. A baseline array having the median of the median intensities was chosen. All arrays were then normalized to this ‘baseline’ via the following method. If xbase are the intensities of the baseline array and xi is any array, then let Formula, where Formula is the trimmed mean intensity (in our analysis we have excluded the highest and lowest 2% of probe intensities). Then the intensities for the normalized array would be Formula = ßixi. These estimates formed the basis for statistical testing. Differential expression was determined on the combined basis of statistical testing using t-test and on the basis of ratio with a cut-off of P < 0.05 and fold ≥2 being called positive for differential expression. Genes passing this filter were allocated to four mutually exclusive groups according to their expression pattern. Hierarchical clustering was performed as follows. Genes were selected according to the criteria described in the text. For the selected genes, expression indexes were transformed across samples to an N (0,1) distribution using a standard statistical Z-transform. These values were input to the GeneCluster program of Eisen et al. (15), and genes were clustered using average linkage and correlation dissimilarity. Signal transduction pathways, metabolic pathways and other functional groupings of genes were evaluated for differential regulation using the visualization tool GenMAPP (16) (UCSF, www.GenMAPP.org). Several pathway maps have been developed and additional maps were produced on the basis of Science's Signal Transduction Knowledge Environment (www.stke.org). Genes were identified as important using this tool on the basis of how comprehensively a particular pathway was affected by a given treatment and on the basis of how many of the treatments produced a similar effect on specific genes. Identifying genes in this way helps in reducing false-positive rates associated with analysis of thousands of genes without deleteriously elevating false-negative rates, as often occurs when using purely statistical methods such as Bonferroni correction.

To evaluate the reliability of the array results, 16 genes detected in the microarray assay were selected for further confirmation between Ha-ras wild-type and Ha-ras mutant tumors, and between FTI-treated and non-FTI-treated tumors by semiquantitative RT–PCR as described previously (17).

To find FTI-sensitive gene signatures, k-nearest neighbors (k-NN) algorithm was used with eight FTI-treated tumors with/without Ha-ras mutation. First, neighborhood analysis was used to select gene markers that have expression patterns closely correlated with the Ha-ras status. Then a series of competitive models were built with a wide range of features (1–200 gene markers). The predicting error rate of each of these models was estimated by using ‘leave-one-out’ cross-validation approach. Finally, the best model was chosen on the basis of their predicting error rates. The obtained classifier was then used for predicting FTI sensitivity of the samples. GeneCluster 2.0 was used to perform these analyses.


   Results
Top
 Abstract
 Introduction
 Materials and methods
 Results
Discussion
 References
 
Efficacy of R115777 in treatment of rat mammary tumors
In this experiment, we took animals with small- to moderate-sized mammary tumors and surgically removed a 100–200 mg specimen (Figure 1). Interestingly, minimal bleeding was observed. The skin was closed with wound clips. Three days following this ‘biopsy’ procedure, rats were treated with FTI (50 mg/kg body wt/day for a period of 4 weeks). When one examined the results, it was observed that ~50% of tumors displayed rapid regression, whereas most of the remaining tumors showed relatively indolent growth or partial regression. When we examined the Ha-ras mutation status, we found that 6 out of 7 tumors that were Ha-ras mutation positive underwent complete regression (Figure 1B). Among the Ha-ras mutation negative tumors, 2 out of 8 underwent complete regressions (Figure 1A). However, virtually none of these tumors continued to show rapid progressive tumor growth. These results clearly demonstrate that while the non-mutant Ha-ras-bearing tumors yielded a more variable response, tumors with Ha-ras mutations underwent profound regression within 4 weeks. A comparison of tumor growth/regression rates for tumors in Figure 1A (Ha-ras wildtype) versus those in Figure 1B (Ha-ras mutated) were statistically significant (P < 0.001) on the basis of Wilcoxon rank test.


Figure 1
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  		Fig. 1. Efficacy of R115777 in treatment of rat mammary tumors. (A) Effect of R115777 on Ha-ras wild-type tumors. (B) Effect of R115777 on Ha-ras mutant tumors. Animals with small- to moderate-sized mammary tumors were taken and a 100–200 mg specimen was surgically removed. Three days following the ‘biopsy’ procedure, rats were treated with FTI (50 mg/kg body wt/day for a period of 6 weeks). Approximately 50% of tumors displayed rapid regression: mutant Ha-ras positive underwent almost complete regression, whereas Ha-ras wild-type tumors exhibited a more moderate regression. Symbols reflect caliper measurements from individual tumors.

 
Differential gene expression in control rat mammary tumors with or without a Ha-ras mutation
On the basis of previous studies with a variety of FTIs as well as our own data (see above), we had expected tumors with an Ha-ras mutation to be highly sensitive to the therapeutic effects of R115777. We therefore wished to determine whether an untutored genomic analysis could differentiate highly sensitive (Ha-ras mutant) tumors from variably sensitive (Ha-ras wildtype) tumors prior to FTI treatment. Four Ha-ras mutant tumors, four Ha-ras wildtype tumors and normal mammary epithelia were examined. The differences between tumors and normal epithelia were striking. Furthermore, comparison of Ha-ras mutant tumors with Ha-ras wild-type tumors in non-FTI treatment group revealed 245 genes that differentially expressed on the basis of the Ha-ras mutation status (Figure 2A). A total of 13 out of 16 selected genes were confirmed by semiquantitative RT–PCR; the confirmation rate is ~80% (Figure 3).


Figure 2
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  		Fig. 2. (A) Hierarchical clustering of 245 genes and ESTs found to be differentially expressed during tumorigenesis between the tumors with Ha-ras wild-type and tumors with Ha-ras mutation (P < 0.05 t-test, fold changes >2). (B) Hierarchical clustering of 939 genes and ESTs found to be differentially expressed between the tumors without and with FTI treatment regardless of the genotype of the tumors (P < 0.05 t-test, fold changes >2). The columns represent the various groups examined, whereas the genes and their expression values are displayed in rows. White indicates an expression below the mean value for the gene, grey near the mean and black above the mean. The differential expression of these genes is dependent on the Ha-ras status of the tumors and represents the genes that are directly influenced by the Ha-ras gene status during the tumorigenesis.

 

Figure 3
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  		Fig. 3. Semiquantitative RT–PCR confirmation for selected genes detected by Affymetrix array. Sixteen out of twenty genes were confirmed by RT–PCR; the confirmation rate is ~80%. (A) RT–PCR verification of altered expressed genes between Ha-ras mutation and Ha-ras wild-type tumors. Lanes 1–6: Ha-ras wild-type tumors and lanes 7–12: Ha-ras mutant tumors. (B) Comparison of fold change produced by microarray with relative expression ratio obtained from RT–PCR with high concordance. Asterisk indicates those not detected in Ha-ras wild-type tumors. (C) RT–PCR confirmation for the genes modulated by FTI, especially in the Ha-ras mutant tumors. (D) Comparison of fold change produced by microarray with relative expression ratio obtained from RT–PCR, and there is an excellent concordance.

 
Untutored cluster were created from hierarchical clustering of the gene expression profiles of each sample for the purpose of comparing the wild-type and mutant Ha-ras tumors and normal tissues (Figure 4A). The overall gene expression pattern of tumors with a Ha-ras mutation clustered together and separate from the tumors without a Ha-ras mutation.


Figure 4
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  		Fig. 4. Unsupervised clustering analysis and a FTI/Ha-ras-sensitive gene signature. (A) Unsupervised clustering analysis indicates that control tumors with a Ha-ras mutation clustered together and separately from the tumors with no Ha-ras mutation. (B) There are 82 genes that were found to highly correlate with the Ha-ras status, which may predict FTI sensitivity. The columns represent the various groups examined, whereas the genes and their expression values are displayed in rows. White indicates an expression below the mean value for the gene, grey near the mean and black above the mean.

 
Using k-NN algorithm, we found that 82 genes highly correlate with the Ha-ras status, which may predict FTI sensitivity correctly (Figure 4B). In these 82 genes, several genes are related to important pathways of cancer; for example, Fcgr3 and Tieg are related to regulation of apoptosis; Anpep is related to angiogenesis; Lhx2, Nrg1, Cebpd, Aes, Madh9, Meox2 and Gfi1 are related to regulation of transcription and Mt3 is related to negative regulation of cell growth.

Differential gene expression in rat mammary tumors treated with FTI compared with control tumors
Differentially expressed genes were identified on the basis of consistent fold change and statistical significance was assessed by t-test for equality of expression in FTI-treated tumors and control tumors. Student's t-test statistical analysis of the normalized expression data was used to reveal the genes, ESTs and RIKEN sequences (P < 0.05) with the expression changes ≥2-fold. Figure 2B showed the general effects of FTI on gene expression in rat mammary tumors. More than 900 genes were modulated by FTI treatment regardless of the genotype of the tumors. A list of a limited number of genes whose levels of expression were similarly changed in mutant Ha-ras or Ha-ras wild-type tumors is given in Table I. When examining control or FTI-treated tumors with a Ha-ras mutation, 398 genes were found differentially expressed (Table II). Among them, 158 genes were modulated back to normal levels after FTI treatment, with 117 genes downregulated and 41 genes upregulated (Figure 5A, Clusters a and c). Fifty-one genes were not influenced by FTI even though they were underexpressed during the tumorigenesis (Figure 5A, Cluster d), and 167 genes were modulated by FTI treatment even though expression of these genes was not changed during the progression of tumorigenesis (Figure 5A, Cluster b). Figure 5B shows the gene expressions in normal mammary epithelia and in Ha-ras wild-type tumors with or without FTI treatment. Among the 423 genes, 230 genes were modulated back to normal levels after FTI treatment, with 130 genes downregulated and 99 genes upregulated (Figure 5B, Cluster a and c). FTI treatment had no effect on 28 genes that were found underexpressed during tumorigenesis (Figure 5B, Cluster d), and 164 genes were modulated by FTI treatment even though these genes had not shown differences in expression between normal epithelia and control tumor (Figure 5B, Cluster b). Four selected genes from microarray were confirmed by RT–PCR to have the same expression tendency after FTI treatment (Figure 3C).


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  		Table I. Genes modulated by R115777 treatment regardless of the Ha-ras status of the tumors

 

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  		Table II. Genes that were found differentially expressed during rat mammary tumorigenesis were modulated back to normal levels by FTI treatment (from cluster a and c of Figure 5)

 

Figure 5
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  		Fig. 5. (A) Hierarchical clustering of 398 genes and ESTs found to be differentially expressed between the tumors (Ha-ras activated) with and without FTI treatment (P < 0.05 t-test, fold changes > 2) and compared with the normal epithelium. (B) Hierarchical clustering of 422 genes and ESTs found to be differentially expressed between the tumors (Ha-ras wild-type) with and without FTI treatment (P < 0.05 t-test, fold changes >2) and compared with the normal epithelium. The columns represent the various groups examined, whereas the genes and their expression values are displayed in rows. White indicates an expression below the mean value for the gene, grey near the mean and black above the mean. Expression pattern grouping is to the right of the figure and clustering is to the left. Four subgroups were found in the clustering. Group a: genes are downregulated to normal levels by FTI treatment; Group b: genes are not involved in the tumorigenesis, but modulated by FTI; Group c: genes are upregulated to normal levels by FTI treatment; and Group d: genes are not influenced by FTI.

 
Gene expression profile associated only with FTI-treated rat mammary tumors contained an activated Ha-ras
As shown in Figure 1, the efficacy of FTI treatment against rat mammary tumors is greater in tumors with a mutated Ha-ras when compared with those that did not contain a mutated Ha-ras. We have generated gene expression profiles specific for tumors with a mutated Ha-ras and those that did not contain a mutated Ha-ras (Figure 5A). The expression data are shown in Table II. Major genes preferentially affected by FTI in Ha-ras-mutated tumors are involved in ras pathway, such as RAS guanyl releasing protein 1, ras homolog gene family member V, ral guanine nucleotide dissociation stimulator and p38 MAPK. Several other genes, such as p53, WT1, CDC 37 as well as a number of genes related to cell proliferation, for example, PCNA, c-myc and c-jun, were found to be preferentially modulated by FTI in Ha-ras-mutated tumors.

Gene expression profile associated only with FTI-treated rat mammary tumors did not contain an activated Ha-ras
We also found a series of genes that are preferentially changed in response to FTI treatment only in tumors that did not contain a mutated Ha-ras (Figure 5B). Among the altered genes, many are known from previous studies to be involved in G-protein pathway, such as G11{alpha} subunit, G protein-coupled receptor 51 and G-protein Golf {alpha} subunit. Programmed cell death 8, Rb1, MAD homolog 2 and cAMP responsive-element modulator (CREM) are also involved in the FTI treatment in Ha-ras wild-type tumors. In addition, a variety of genes coding for drug-metabolizing enzymes, including various cytochrome(s) P450 and several GST enzymes, were modulated by FTI only in Ha-ras wild-type tumors (Table II)

Examination of gene expression pathways that were altered by FTI preferentially in Ha-ras positive and wild-type tumors
Various signal transduction pathways, metabolic pathways and other functional groupings of genes that may be involved in rat mammary tumorigenesis and FTI treatment were systematically evaluated for differential regulation using the visualization tool GenMAPP. We imported our data set into the program and converted the expression data into illustrations demonstrating presence and significant expression change for the genes represented on the microarray on the basis of the analysis of FTI treatment in Ha-ras wild-type tumors and Ha-ras mutant tumors. We found that genes in at least two major regulatory pathways were significantly altered during FTI treatment. Figure 6 represents the Wnt signaling pathway and demonstrates the extent of the involvement of the Wnt pathway in our study. FTI treatment downregulated the GSK3ß, c-myc and c-jun in Ha-ras mutant tumors but not in the Ha-ras wild-type tumors. Finally, in Figure 7, the apoptotic pathway is presented. As we can see in the figure, several key apoptotic genes are involved in FTI treatment. Caspase 6, c-jun, c-myc and p53 were downregulated in the Ha-ras mutant tumors, but in Ha-ras wild-type tumors FTI treatment caused downregulation of p53, caspase 7, TNFR1 and Bax. These results indicated that different genes and pathways are involved in FTI treatment depending on the Ha-ras status of the tumors.


Figure 6
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  		Fig. 6. GenMAPP Wnt Pathways integrating our expression data. Yellow indicates a higher level of expression in the prenatal samples. Blue indicates a higher level of expression in the postnatal samples. Grey indicates that the selection criteria were not met but the gene is represented on the array. White boxes indicate that the gene was not present on the chip.

 

Figure 7
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  		Fig. 7. enMAPP Apoptosis Signaling Pathways integrating our expression data. Yellow indicates a higher level of expression in the prenatal samples. Blue indicates a higher level of expression in the postnatal samples. Grey indicates that the selection criteria were not met but the gene is represented on the array. White boxes indicate that the gene was not present on the chip.

 

   Discussion
Top
 Abstract
 Introduction
 Materials and methods
 Results
 Discussion
References
 
As mentioned in the Introduction, Ras is a major focus of the signaling pathway for multiple growth factors including EGF, FGF, VEGF, and so on. Taken together with the fact that many human tumors have mutations in the Ras oncogenes (Ki-Ras, N-Ras and Ha-ras) made inhibition of Ras function a major potential therapeutic target. Since processing of the ras protein is required for its transport to the cell membrane and, apparently, its functioning, it was hypothesized that blocking this function would block the tumorigenic effects of the mutant Ras proteins (1,18). Most of the previously published in vivo tumor studies with the various FTIs have involved the use of transgenic mice routinely overexpressing multiple copies of one of the mutated Ras oncogenes (13,19,20). These studies have shown that a variety of FTIs are profoundly effective in tumors with Ha- or N-Ras mutations but are less effective in tumors with Ki-ras mutations. We have employed R115777, an imidazole-based competitive FTI, in the MNU-induced rat mammary cancer model. MNU treatment of female Sprague-Dawley rats results in virtually a 100% incidence of multiple hormonally responsive mammary tumors beginning at 5 weeks post MNU treatment. Interestingly, about one-half of these tumors have Ha-ras mutation and one-half do not (11).

We employed a modified therapeutic intervention to examine the efficacy of R115777 in this model. After a rat developed a palpable mammary tumor, ~100–200 mg piece of the lesion was removed. These surgical biopsies allow one to characterize the baseline tumor for various biological properties including Ha-ras status. Beginning 3 days following the biopsy, the rats were administered FTI (50 mg/kg body wt/day) and tumor growth was determined by caliper measurements. As can be seen in Figure 1, 6 out of 7 tumors with an Ha-ras mutation underwent complete regression, whereas tumor growth in the non-Ha-ras mutation was significantly variable. Statistical analysis by Wilcoxon ranking demonstrated that the growth/regression rates of FTI-treated tumors with or without an Ha-ras mutation were significantly different (P < 0.001). These results clearly demonstrate that tumors with mutations in the Ha-ras genes are exquisitely sensitive to the therapeutic effects of R115777. However, even the non-Ha-ras mutation tumors showed substantial, albeit more variable, therapeutic effects with this FTI. Although it would appear that the exquisite sensitivity of the Ha-ras mutant tumors is related to Ha-ras itself, the targets in the non-Ha-ras mutant tumors are less obvious. Whether this reflects alterations in farnesylation of non-mutated Ras proteins or of other proteins, for example, CENP E/F, Rheb 1 and PRL (-1, -2, or -3), all of which can be farnesylated, is not known (1). Nevertheless, examination of this question is of great importance since the FTI inhibitors appear to have efficacy in advanced breast cancer in humans where virtually none of the tumors have mutations in Ras.

One of the more striking uses of array analyses to date has been their substantial use in delineating subgroups of tumors of a given organ (e.g. breast, lung, lymphomas) (21–23) that have significantly different gene expression patterns. These different gene expression patterns may be associated with different prognostic indications and may simultaneously show differing responses to standard therapeutic treatments. In the case at hand we knew on the basis of previous in vitro and in vivo studies that tumors with a Ha-ras mutation were likely to be highly susceptible to inhibition by FTI. Therefore, normal mammary epithelia and tumors with or without Ha-ras mutations were employed in an array analysis. In fact, the tumors with a Ha-ras mutation could be clearly separated from the tumors with no Ha-ras mutation. This is quite striking since these tumors are all ER+ and have a similar histopathology and all respond similarly to hormonal agents such as tamoxifen, aromatase inhibitors or dehydropepiandrosterone (13,24,25). Thus, our analysis may be useful to differentiate sensitivity to R115777 but it did not differentiate sensitivity to agents such as tamoxifen, aromatase inhibitors or dehydropepiandrosterone since these agents were strikingly effective on tumors with or without a Ha-ras mutation. In Figures 2 and 4 we performed a tutored analysis examining genes expression patterns in Ha-ras mutant and Ha-ras wildtype tumors. Certain of these genes are listed in Table II. Given that we knew a substantial amount about Ha-ras, some of the genes that showed large differences in expression were unexpected.

In the present study using an Affymetrix microarray that contains ~8000 genes and ESTs, we identified differentially expressed genes in rat mammary tumors and the modulating effects of R115777 on the gene expression. Our goals were to find genes whose expression is highly modulated by FTI treatment, which may contribute to the efficacy of R115777 in tumors with or without mutations in Ha-ras, as well as to identify potential pharmacodynamic markers. We employed a relatively short duration of exposure (4 days), since by 10–14 days we had observed that a substantial number of tumors had significant areas of necrosis (K.Christov, unpublished data). Although there are a great many changes in gene expression that appeared to be relatively specific for tumors with or without an Ha-ras mutation, in fact the greatest number of changes (939 genes) yielded similar changes following FTI treatment in tumors with or without an Ha-ras mutation (Figure 2B). These gene changes are unlikely to be the primary alterations associated with the striking therapeutic efficacy of FTI, particularly for the Ha-ras mutant tumors in this system. However, they may contribute to the efficacy of FTIs in tumors without Ha-ras mutations and may be particularly relevant to human breast cancer, where virtually no Ha-ras mutant tumors are observed. Furthermore, these gene expression alterations might serve as a pharmacodynamic marker for R115777. These gene changes are indicative that R115777 has reached its intended target tissue (breast cancer epithelia) and has achieved alterations in gene expression that reflect an effective dose of the FTI.

When one examines Table II, particularly those genes whose expression is decreased primarily in Ha-ras mutant but not in Ha-ras wildtype tumors, one is struck by a number of genes involved in cell proliferation. These include enzymes directly involved in DNA replication, for example, PCNA, DNA polymerase alpha II subunit, topoisomerase 2 alpha and other genes involved in cell proliferation, such as cdc 37 homolog and the mitogenic regulation SseCKS (322) gene. Striking decrease in expression of these genes is likely to reflect the fact that R115777 is profoundly effective in causing tumor regression in Ha-ras mutant tumors. In fact, we have observed a striking decrease in cell proliferation (>75% decrease at 4 days) assessed by BudR labeling in tumors with Ha-ras mutations following treatment with R115777 (K.Christov and R.Lubet, unpublished data). In contrast, similar treatment of non-Ha-ras mutant tumors had more limited and somewhat variable effects. Presumably, these gene expression changes are a reflection of the decreased proliferation and are not themselves the target molecules since they are not known to be prenylated.

R115777 has profound effects on the modulation of genes whose expression was altered during tumorigenesis, and these genes may or may not be involved in the rat mammary tumorigenesis (Figures 2 and 4). Table II lists some potential genes that are involved in rat mammary tumorigenesis and are also the targets for R115777 treatment. R115777 seem to target different pathways in tumors with or without Ha-ras mutations. In Ha-ras-mutated tumors, R115777 appears to preferentially target the ras signaling pathway including Myc, Jun, p53, WT1, certain growth factor receptors as well as certain of the proliferation genes discussed above. For tumors with wild-type Ha-ras, R115777 preferentially modulated the G-protein signaling pathway as well as a variety of genes involved in drug metabolism. It also modulated Rb1 and various transcription factors, such as Myc/Mad. Since these genes play important roles in tumorigenesis in various organs, modulation of these genes back to normal levels may be involved in the therapeutic effects of R115777. However, as discussed above, there were a wide variety of genes whose expression was modulated similarly in Ha-ras mutated and Ha-ras wild-type tumors. Discussed below are a limited number of genes and gene pathways whose expression is altered by FTI treatment in Ha-ras mutated tumors. RasGRP, a new RasGEF, functions as an upstream Ras activator through rapid conversion of the inactive GDP-bound Ras to the active GTP-bound form on the inner surface of the plasma membrane. Ral is activated downstream to the activation of Ras via the RalGEFs, RalGDS, RGL and Rlf (26) and may act as an integrator of signals from different sources. p38-mediated growth inhibition of cells following transfection has been shown to involve stimulation of p53 (27). Overexpression of Ha-ras resulted in p53 posttranslation modifications at Ser33 and Ser46 (38), which are the same sites that exhibited p38-dependent phosphorylation after UV radiation (27). p53 is mutated, resulting in protein stabilization and overexpression in many cancers, including breast cancer. In addition to its transcriptional function, WT1 binds p53 to stabilize p53 and modulate transcriptional properties of WT1 and p53 (29,30).

In this study, we found that RasGRP1, RalGDS, ras homolog gene family member V, p38, p53, WT1 and Hsp70 were significantly modulated in tumors with Ha-ras mutation after FTI treatment. FTI is known to affect ras-MAP kinase signaling cascade by blocking Ras farnesylation, subcellular localization and activity. Although FTIs were initially developed to inhibit growth of cancers harboring Ras mutations, preclinical data suggests that they also have antiproliferative effects in cell lines with wild-type Ras and it now appears that FTIs may function independently of Ras.

Previous study on pathways identification by microarray analysis in acute myeloid leukemia have shown that cell signaling, cytoskeletal organization, immunity, and apoptosis are affected by R115777 (31). By using the visualization tool GenMAPP, we also found that genes in at least three major regulatory pathways were significantly altered after FTI treatment. Although we do not know at present if there are significant differences in functions of these three pathways in the tumors that do and do not respond, we do know that some of the genes in these pathways are differentially expressed in the tumors that do respond (with Ha-ras mutation) and those that do not (without Ha-ras mutation) (Figures 6 and 7). Figure 6 represents the Wnt signaling pathway. The Wnt pathway is essential for regulating various differentiation events during embryonic development and leading to tumor formation when aberrantly activated. Among other things, it regulates ß-catenin, ensuring the proper activation of cell cycle transcriptional controls. In fact, involvement of this pathway appears to be necessary for the development of most colon cancers. Furthermore, alterations in this pathway appear to be associated with a significant number of mammary tumors based on the fact that the WNT genes were one of those associated with MMTV-induced mammary cancer and that transgenic mice with overexpression of WNT develop breast cancer. The Tcf family influences a wide variety of developmental processes in various tissues, targeting such genes as c-myc, cyclin D and c-jun.

Finally, in Figure 7 the apoptotic pathway is presented. Defective apoptosis represents a major causative factor in the development and progression of cancer. The ability of tumor cells to evade engagement of apoptosis can play a significant role in their resistance to conventional therapeutic regimens. As we can see in the figure, several key apoptotic genes are involved in FTI treatment. Among them, specific genes such as c-jun and c-myc, which might be expected to be antiapoptotic, were downregulated by FTI in Ha-ras-mutated tumors, whereas Bax and TNFR1 were specially downregulated by FTI in tumors without Ha-ras mutation. It may be difficult to discern clearly genes related to apoptosis in this in vivo system since even the exquisitely sensitive Ha-ras mutant-bearing tumors demonstrated no more than 3% apoptotic cells, as defined by the TUNEL assay, following 4 days of treatment with R115777. We have specifically mentioned a limited number of genes whose expression was altered by FTI treatment; however, there are literally hundreds of genes whose expression was altered and which might turn out to be significant in determining the efficacy of this class of agents. Future studies should include the use of an independent animal experiment to determine if gene clusters that identify different phenotypes are reproducible or predictive.

In summation, we have observed the following employing microarray analysis. First, we found that Ha-ras mutant tumors are particularly susceptible to R115777 and that this is paralleled by more striking effects on proliferation-related genes in Ha-ras mutant tumors. Secondly, the greatest number of altered gene expression, following treatment with R115777, is common to both Ha-ras mutant and wild-type tumors. These changes may prove to be both pharmacodynamic markers and give mechanistic insight into mechanisms of action. Thirdly, there appear to be genes that can discriminate Ha-ras mutant and Ha-ras wild-type tumors. Although the rat mammary tumor model may not be immediately relevant to human breast cancer, where few tumors have Ras mutations, it is useful in our understanding of the possible effect of R115777 on ras signaling pathway in human breast cancer. In addition, mammary tumors arise in a heterogenous tumor model (~50% Ha-ras mutant tumors and ~50% non-Ha-ras mutant (tumors). This has allowed us to examine responses in both exquisitely sensitive tumors (Ha-ras mutant) and variably sensitive tumors (Ha-ras wild-type).


   Acknowledgments
 
This work was supported by NIH grants (R01 CA96103; R01 CA1133793; and N01-CN-43308).

Conflict of Interest Statement: None declared.


   References
Top
 Abstract
 Introduction
 Materials and methods
 Results
 Discussion
 References
 

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Received August 18, 2005; revised October 24, 2005; accepted January 3, 2006.


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