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Cancer Epidemiology Biomarkers & Prevention 16, 2150, October 1, 2007. doi: 10.1158/1055-9965.EPI-07-0154
© 2007 American Association for Cancer Research
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Short Communication

Low-Fat, Low-Glycemic Load Diet and Gene Expression in Human Prostate Epithelium: A Feasibility Study of Using cDNA Microarrays to Assess the Response to Dietary Intervention in Target Tissues

Daniel W. Lin1,3, Marian L. Neuhouser1, Jeannette M. Schenk1, Ilsa M. Coleman2, Sarah Hawley1, David Gifford2, Hau Hung2, Beatrice S. Knudsen1, Peter S. Nelson2 and Alan R. Kristal1,4

Divisions of 1 Public Health Sciences and 2 Human Biology, Fred Hutchinson Cancer Research Center, and Departments of 3 Urology and 4 Epidemiology, University of Washington, Seattle, Washington

Requests for reprints: Daniel W. Lin, Department of Urology, University of Washington, Box 356510, 1959 Northeast Pacific Street, Seattle, WA 98195. Phone: 206-667-1342; Fax: 206-667-2917. E-mail: dlin{at}u.washington.edu


   Abstract
Top
 Abstract
Introduction
 Materials and Methods
 Results
 Discussion
 References
 
Purpose: We examined the feasibility of using gene expression changes in human prostate epithelium as a measure of response to a dietary intervention.

Materials and Methods: Eight men with newly diagnosed prostate cancer were randomized to a low-fat/low-glycemic load intervention arm (<20% energy from fat and total daily glycemic load <100) or a "standard American" control arm ({approx}35% energy from fat and total daily glycemic load >200). Prostate tissue was collected before randomization and ~6 weeks later, at the time of radical prostatectomy. Epithelium was acquired by laser capture microdissection, and transcript abundance levels were measured by cDNA microarray hybridization and confirmed by quantitative reverse transcription-PCR.

Results: Men in the intervention arm consumed 39% less total energy (P = 0.004) and the difference in weight change between intervention and control arms was –6.1 kg (P = 0.02). In the intervention arm, 23 (0.46%) of 5,711 cDNAs with measurable expression were significantly altered (P < 0.05; false discovery rate, ≤10%). In the control arm, there were no significant changes in transcript expression, even when using a false discovery rate as high as 50%.

Conclusions: A 6-week, low-fat/low-glycemic load diet was associated with significant gene expression changes in human prostate epithelium. These results show the feasibility of using prostate tissues collected at diagnosis and at surgery to study the effects of dietary manipulation on prostate tissue, which may give insight into the molecular mechanisms underlying the associations of diet and obesity with the development or progression of prostate cancer. (Cancer Epidemiol Biomarkers Prev 2007;16(10):2150–4)


   Introduction
Top
 Abstract
 Introduction
Materials and Methods
 Results
 Discussion
 References
 
There is good evidence that obesity and perhaps, a high fat intake, due to its strong correlation with obesity, increase the risk of high-grade or aggressive prostate cancer, prostate cancer mortality, and the risk of poor outcome following diagnosis and treatment (1-3). However, the molecular mechanisms underlying these associations remains largely unknown. Experimental animal and in vitro studies have shown that dietary patterns and food constituents can affect gene expression, protein synthesis, cell signaling, and other important events related to carcinogenesis (4-6). In humans, however, it is difficult to test hypotheses related to the mechanisms and pathways that underlie diet and cancer associations because appropriate tissues are rarely available. Human studies are generally limited to measuring circulating biomarkers, such as serum steroid hormones, which are influenced by diet and are associated with carcinogenesis.

The objective of this pilot study was to evaluate the feasibility of a randomized clinical trial to test whether short-term modifications in macronutrient intake could modify gene expression in prostate epithelium. We examined the effects of a low-fat/low-glycemic load diet in men with clinically localized prostate cancer who elected prostatectomy as their primary treatment choice. These results will help in the design of studies using gene expression or gene expression signatures as measures of the effect of dietary change on prostate cancer biology.


   Materials and Methods
Top
 Abstract
 Introduction
 Materials and Methods
Results
 Discussion
 References
 
Participants were men with clinically localized prostate cancer, who elected to undergo radical prostatectomy and received no neoadjuvant therapy. Study activities began within 2 weeks of diagnosis.

Eligibility criteria included the ability to implement dietary change, no concurrent disease requiring dietary modification, no current use of hormonal treatments, and body mass index >20 kg/m2 and <35 kg/m2. In addition, men had to have participated in an independent protocol that collected and stored four prostate tissue cores at the time of diagnostic prostate biopsy. Both the dietary intervention and biopsy tissue collection protocols were approved by the Institutional Review Boards of the Veterans Administration, Puget Sound Health Care System and the Fred Hutchinson Cancer Research Center, and all patients signed written informed consents. Study was completed between August 2003 and November 2004.

Randomization and Dietary Intervention
Participants were randomly assigned to one of two groups: group I received instructions to follow a low-fat/low-glycemic load diet (<20% energy from fat and total daily glycemic load <100) and group II was instructed to follow a "standard American" diet (35% energy from fat and total daily glycemic load >200). A detailed description of the intervention is available from the authors upon request. In brief, participants were provided a dietary intervention manual that focused on meal planning. For individuals randomized to the low-fat/low-glycemic load diet, the study nutritionist provided detailed instructions and worked with the participant to plan at least three meals. Participants randomized to the standard American group were asked to continue their usual dietary habits, using lists of prohibited and permitted foods as a guideline for food choices. During the first week, the nutritionist made up to five follow-up telephone calls to review the intervention materials and provide additional meal planning support; calls were made at least once per week thereafter.

Dietary and Anthropometric Assessment
Unscheduled, telephone-administered 24-h dietary recalls were completed each week to assess adherence to the study diet, using the University of Minnesota's Nutrition Data Systems for Research software (version 37, 2006). Interviewers were blinded to the randomization assignment. On the days of randomization and prostatectomy, participants were weighed by study staff on a beam balance scale. Height was measured using a standing stadiometer. Body mass index was calculated as weight (kg) / height (m)2.

Clinical Specimens
At the time of biopsy and after acquiring 12 diagnostic prostate cores, we obtained four additional tissue cores from the peripheral zone. At the time of radical prostatectomy, the prostate was exposed via a midline incision, and we obtained four in situ prostate biopsy cores using an 18-gauge prostate needle biopsy gun (Bard Inc.). All biopsies were collected from the peripheral zone and immediately embedded and frozen as described below. Because our study was limited to the effects of diet on normal epithelium, we attempted to intraoperatively biopsy sites that did not contain malignant epithelium, corresponding to sites from diagnostic biopsy specimens. The in situ samples were collected before removing the prostate because we previously found that surgical manipulation caused artifactual changes in gene expression (7).

Specimen Handling and Laser Capture Microdissection
Biopsy cores were embedded individually in polyethylene glycol freezing media (Tissue-Tek OCT Compound, Sakura Finetek), placed in isopentane that was precooled in liquid nitrogen, and stored at –80°C (8). We used laser capture microdissection to collect 5,000 epithelial cells from histologically benign epithelial glands and extracted RNA using a standardized protocol (9). The RNA was subjected to linear amplification and converted to cDNA for microarray hybridization as previously described (7).

Gene Expression Analysis by Microarray Hybridization
We prepared and hybridized spotted cDNA microarrays as previously described (10), using RNA from a single batch of reference standards for each hybridization. Fluorescent array images were collected for both Cy3 and Cy5 using a GenePix 4000B fluorescent scanner (Axon Instruments), and GenePix Pro 4.1 software was used to grid and extract image intensity data. Spots of poor quality, as determined by visual inspection, were removed from further analysis. To normalize log ratio data, a print tip–specific Lowess curve was fit to the log-intensity versus log-ratio plot, using 20.0% of the data to calculate the fit at each point. This curve was used to center the log-ratio for each spot. Data were filtered to exclude poorly hybridized cDNAs by removing values with average foreground minus background intensity levels less than 300. We used the average of the two duplicate cDNA spots on each microarray chip in subsequent analyses. Data were filtered to include clones returning data for at least 75% of the samples in both preintervention and postintervention groups, which reduced the initial list of 6,751 clones to 5,711 clones and 5,643 clones in the low-fat/low-glycemic load and the standard American diet groups, respectively.

Statistical and Pathway Analyses
We used the significant analysis of microarrays algorithm5 to analyze differences in transcript levels between preintervention and postintervention specimens (11). Paired, two-sample t tests were calculated for each transcript, and genes differentially expressed were identified using false discovery rates (FDR) ranging from 5% to 50%.

Quantitative Reverse Transcription-PCR
We used quantitative reverse transcription-PCR to validate microarray results for selected genes. Primers specific for the genes of interest were designed using the web-based primer design service Primer3 provided by the Whitehead Institute for Biomedical Research.6 We determined acceptable performance characteristics of the PCR primers using normal human prostate cDNA, Biolase Taq polymerase (Bioline Inc.), and the GeneAmp PCR system 9700 (Applied Biosystems) as previously described (8). Total RNA from participant samples were reverse transcribed, and cDNA was purified as previously described. Relative quantification of gene expression by quantitative PCR (40 cycles of 60°C annealing, 72°C extension, and 95°C melting) was done on a 7700 Sequence Detector using SYBR Green Master mix and gene-specific primers following the manufacturer's recommendations.


   Results
Top
 Abstract
 Introduction
 Materials and Methods
 Results
Discussion
 References
 
Participant Demographic and Clinical Characteristics
Median participant age was 64 years (range, 59-69), median body mass index was 29 (range, 23-35), median preoperative serum prostate-specific antigen was 5.2 ng/mL (range, 2.5-16.0), median prostate volume was 50 mL (range, 35-149), and all but one participant was Caucasian.

Intervention Effects on Diet and Weight
The intervention resulted in profoundly different dietary patterns in the two study arms (Table 1 ). Compared with men in the standard American arm, participants in the low-fat/low-glycemic load arm consumed 39% less total energy, 46% less fat, 42% less carbohydrate, and 62% more fiber, and had a 51% lower glycemic load. The intervention effect for weight, defined as the difference in weight change between study arms adjusted for baseline weight, was 6.1 kg (95% confidence interval, 1.6-10.5 kg; P = 0.02).


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  		Table 1. Postintervention dietary characteristics and intervention differences, by study arm

 
Gene Expression Changes Associated with Dietary Intervention
Table 2 gives the distributions of gene expression differences in tissues obtained before and after dietary intervention. Differences in these tables are categorized symmetrically above and below zero in units of log2. In both study arms, the relative difference in expression of ~95% of transcripts ranged between 0.67 and 1.49. In the standard American arm, expression of 20 transcripts decreased by 50% or greater, and 32 transcripts increased by 100% or greater. In the low-fat/low-glycemic load arm, expression of 9 transcripts decreased by 50% or greater, and expression of 43 transcripts increased by 100% of greater. None of the differences in transcript expression in the standard American arm were statistically significant, even using a FDR as high as 50%. In contrast, in the low-fat/low-glycemic load arm, 30 (0.53%) of the cDNAs using a criterion of a 15% FDR and 16 (0.28%) of the cDNAs using a more conservative criterion of a 5% FDR were statistically different.


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  		Table 2. Distribution of preintervention and postintervention differences in transcript expression, and number of significant differences at FDRs of 15%, 10%, and 5%, by treatment arm

 
Figure 1 shows the list of 23 unique genes that showed significantly changed expression in the low-fat/low-glycemic load arm. Several genes are related to cell migration and tissue remodeling, including MMP7 (also called matrilysin), CXCR4, CXCL2, lumican, and SPARC-like 1. Others are involved in intracellular signal transduction, such as the immediate early response genes 2 and 3, the dual specificity phosphatase 1, and the v-ets oncogene homologue. Expression of insulin-like growth factor-II receptor transcripts increased, perhaps due to a positive feedback of the low-glycemic load diet. Genes that were down-regulated include prostate-specific membrane antigen and peroxiredoxin 1, which may play an antioxidant protective role in cells. We confirmed these microarray results by quantitative reverse transcription-PCR and found a correlation of 0.97.


Figure 1
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  		Figure 1. Differential gene expression of predietary versus postdietary intervention (low-fat/low-glycemic load, group I) specimens. Paired two-sample t test results for presurgery versus postsurgery comparison. Twenty-six unique up-regulated genes with FDR ≤ 10% are listed. Average relative expression, change from preintervention to postintervention.

 

   Discussion
Top
 Abstract
 Introduction
 Materials and Methods
 Results
 Discussion
References
 
In this small randomized clinical trial, we showed the feasibility of studying dietary effects on gene expression using the preprostatectomy model. We collected both pretreatment biopsies and posttreatment in situ biopsies, and delivered an effective dietary intervention within the weeks between diagnostic biopsy and surgery. We also showed that tissue from a single prostate biopsy core, weighing ~3 to 5 mg, yielded adequate RNA, albeit after a single round of amplification, for multiple analyses, including cDNA microarrays and quantitative reverse transcription-PCR. Lastly, we found that the intraindividual variability in gene expression in tissues collected at two time points is sufficiently small to allow the detection of intervention effects. Much larger sample sizes are needed to rigorously measure the reliability of transcript expression from prostate tissue collected at different times, but these results are encouraging for future research examining the effects of short-term interventions on prostate tissue.

The low-fat/low-glycemic load diet, and its associated weight loss, was associated with multiple gene expression changes. Many of these changes could conceivably alter the proliferation, metabolism, and redox potential of prostate epithelial cells. For example, insulin-like growth factor-I receptor binds both insulin-like growth factor-I and -II, and the role of insulin-like growth factor-I receptor in tumorigenesis and proliferation is well established (8). We emphasize, however, that much larger samples would be needed to make strong biological inferences based on gene expression arrays.

The principal limitation of this study is its small sample size. We had little power to detect modest changes in transcript expression. We also sampled only ~6,000 genes of the prostate tissue transcriptome, and many additional genes that were not evaluated could be affected to an equal or greater extent. We also have not determined whether the diet-associated changes in transcript levels result in corresponding alterations in the cognate proteins. Lastly, we limited our analyses to the epithelial compartment, as prostate cancer arises from the epithelium, however, there are many interactions between the prostate stroma and epithelium (12-14).

In summary, we conclude that the effect of complex dietary changes on gene expression can be evaluated within the preprostatectomy model. These results provide important information for future studies that aim to examine the role of diet, obesity, and prostate carcinogenesis and/or progression.


   Footnotes
 
Grant support: DK65083 (D.W. Lin), the Pacific Northwest Prostate Cancer Specialized Programs of Research Excellence CA97186 (D.W. Lin and P.S. Nelson), and the Fred Hutchinson Cancer Research Center P30 CA015704.

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.

5 http://www-stat.stanford.edu/~tibs/SAM/ Back

6 http://fokker.wi.mit.edu/cgi-bin/primer3/primer3_www.cgi Back

Received 2/18/07; revised 7/19/07; accepted 8/ 6/07.


   References
Top
 Abstract
 Introduction
 Materials and Methods
 Results
 Discussion
 References
 

  1. Meyer F, Bairati I, Shadmani R, et al. Dietary fat and prostate cancer survival. Cancer Causes Control 1999;10:245–51.[Medline]
  2. Lee MM, Wang RT, Hsing AW, et al. Case-control study of diet and prostate cancer in China. Cancer Causes Control 1998;9:545–52.[CrossRef][Medline]
  3. Ramon JM, Bou R, Romea S, et al. Dietary fat intake and prostate cancer risk: a case-control study in Spain. Cancer Causes Control 2000;11:679–85.[CrossRef][Medline]
  4. Ngo TH, Barnard RJ, Anton T, et al. Effect of isocaloric low-fat diet on prostate cancer xenograft progression to androgen independence. Cancer Res 2004;64:1252–4.[Abstract/Free Full Text]
  5. Ngo TH, Barnard RJ, Cohen P, et al. Effect of isocaloric low-fat diet on human LAPC-4 prostate cancer xenografts in severe combined immunodeficient mice and the insulin-like growth factor axis. Clin Cancer Res 2003;9:2734–43.[Abstract/Free Full Text]
  6. Mukherjee P, Sotnikov AV, Mangian HJ, et al. Energy intake and prostate tumor growth, angiogenesis, and vascular endothelial growth factor expression. J Natl Cancer Inst 1999;91:512–23.[Abstract/Free Full Text]
  7. Lin DW, Coleman IM, Hawley S, et al. Influence of surgical manipulation on prostate gene expression: implications for molecular correlates of treatment effects and disease prognosis. J Clin Oncol 2006;24:3763–70.[Abstract/Free Full Text]
  8. Gennigens C, Menetrier-Caux C, Droz JP. Insulin-like growth factor (IGF) family and prostate cancer. Crit Rev Oncol Hematol 2006;58:124–45.[Medline]
  9. Lin DW, Coleman I, Hawley S, et al. The influence of surgical manipulation on prostate gene expression: implications for molecular correlates of treatment effects and disease prognosis. J Clin Oncol 2006;24:3763–70.[Abstract/Free Full Text]
  10. Moore S, Knudsen B, True LD, et al. Loss of stearoyl-CoA desaturase expression is a frequent event in prostate carcinoma. Int J Cancer 2005;114:563–71.[CrossRef][Medline]
  11. Tusher VG, Tibshirani R, Chu G. Significance analysis of microarrays applied to the ionizing radiation response. Proc Natl Acad Sci U S A 2001;98:5116–21.[Abstract/Free Full Text]
  12. Joesting MS, Perrin S, Elenbaas B, et al. Identification of SFRP1 as a candidate mediator of stromal-to-epithelial signaling in prostate cancer. Cancer Res 2005;65:10423–30.[Abstract/Free Full Text]
  13. Yang F, Tuxhorn JA, Ressler SJ, et al. Stromal expression of connective tissue growth factor promotes angiogenesis and prostate cancer tumorigenesis. Cancer Res 2005;65:8887–95.[Abstract/Free Full Text]
  14. Cunha GR, Hayward SW, Wang YZ, et al. Role of the stromal microenvironment in carcinogenesis of the prostate. Int J Cancer 2003;107:1–10.[CrossRef][Medline]



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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