Associations between apoE genotype and colon and rectal cancer

Martha L. Slattery *, Carol Sweeney, Maureen Murtaugh, Khe Ni Ma, John D. Potter 1, Theodore R. Levin 2, Wade Samowitz 3 and Roger Wolff

Health Research Center, University of Utah, Salt Lake City, UT 84108, USA, 1 Fred Hutchinson Cancer Research Center, Seattle, Washington, DC, USA, 2 Kaiser Permanente Medical Care Research Program, Oakland, CA, USA and 3 Department of Pathology, University of Utah School of Medicine, Salt Lake City, UT, USA

* To whom correspondence should be addressed Email: mslatter{at}hrc.utah.edu


    Abstract
 Top
 Abstract
 Introduction
 Materials and methods
 Results
 Discussion
 References
 
Apolipoprotein E (apoE) plays a major role in the metabolism of bile acids, cholesterol and triglycerides, and has recently been proposed as being involved in the carcinogenic process. Given the potential role of bile acids in colorectal cancer etiology, it is reasonable that colorectal cancer risk might be modified by apoE genotype. We used data collected from a case–control study of colon cancer (n = 1556 cases and 1948 controls) and rectal cancer (n = 777 cases and 988 controls). The absence of an e3 apoE allele significantly increased the risk of colon cancer (OR = 1.37 95% CI 1.00–1.87), particularly among those diagnosed when older than 64 years (OR = 1.88 95% CI 1.17–3.04; P interaction between age and apoE genotype equal to 0.05). A significant three-way interaction was detected for family history of colorectal cancer, age at diagnosis and apoE genotype (P = 0.05), in those diagnosed when older, not having an e3 allele and having a significantly increased risk of colon cancer with family history of colorectal cancer (OR = 3.93 95% CI 1.23–12.6). This was compared with the risk associated with family history of colorectal cancer among those diagnosed when older, with an e3 allele of 1.61 (95% CI 1.17–2.23) or those diagnosed when younger without an e3 allele (OR = 2.40 95% CI 0.56–10.3). Among those diagnosed when older than 64 years, associations of BMI and prudent diet with colon cancer were stronger among individuals without an e3 allele, although the P for interaction was not significant. We did not detect any significant associations between apoE genotype and rectal cancer, survival after diagnosis with colorectal cancer, stage of disease at diagnosis or type of tumor mutation. These findings suggest those apoE genotypes that do not include the e3 allele, the same genotypes that are associated with increased risk of coronary heart disease, may influence development of colon cancer among those who are older at diagnosis.

Abbreviations: apoE, apolipoproteinE; CHD, coronary heart disease; HRT, hormone replacement therapy; KPMCP, Kaiser Permanente Medical Care Program; NSAID, non-steroidal anti-inflammatory drug; RERI, relative excess risk from interaction; SEER, Surveillance Epidemiology and End Results


    Introduction
 Top
 Abstract
 Introduction
 Materials and methods
 Results
 Discussion
 References
 
Apolipoprotein E (apoE) plays a major role in the metabolism of cholesterol and triglycerides by acting as a receptor-binding ligand mediating the clearance of chylomicrons and very-low-density-cholesterol from plasma (13). ApoE has been examined as a risk factor for cardiovascular disease given its role in lipid metabolism (2) although other mechanisms for its contribution to the development of coronary artery disease that are unrelated to lipid metabolism have been examined. These other mechanisms include involvement in platelet aggregation, antioxidant and immune activities (46). ApoE has been proposed as being involved in the carcinogenic process since it has been shown to be a potent inhibitor of proliferation of several cell types; it has been suggested that apoE may be effective in modulating angiogenesis, tumor cell growth and metastasis (7).

Three common isoforms of the apoE gene, epsilon (e) 2, e3 and e4, have been studied because of different receptor binding activity of each isoform. It has been estimated that 2–11% of the variation in serum or plasma cholesterol in healthy white individuals can be attributed to the apoE polymorphism (8, 9). Carriers of the e2 allele have defective receptor-binding ability and lower circulating cholesterol levels and higher triglyceride levels, while carriers of the e4 allele appear to have higher plasma levels of cholesterol. A recent meta-analysis of apoE genotypes and coronary heart disease (CHD) showed that people with the e4 allele had a 42% greater risk of CHD than those with the e3/e3 genotype (2).

ApoE polymorphisms have been studied less frequently with cancer in general and colorectal cancer specifically (10,11). One study has shown that the e4 apoE allele was associated with significant reduction in risk of proximal colon tumors (OR = 0.35 95% CI 0.14–0.86) (11), with similar findings for proximal adenomas (OR = 0.59 95% CI 0.23–1.45) (12). A study conducted in the UK found that those with the e2/e3 genotype had a significant 90% increased risk of colorectal cancer compared with the e3/e3 genotype, although on further analysis this association was found to be limited to men (13). Watson et al. (13) further observed a higher proportion of more advanced tumors with the e2/e3 genotype; they found no association with the e4 genotype. Both these studies were limited to ~200 cases of colorectal cancer/adenomas and did not attempt to evaluate interactions of diet and lifestyle factors that may interact with apoE genotype.

ApoE may influence colorectal cancer development through three possible pathways: cholesterol and bile metabolism, triglyceride and insulin regulation, and inflammation. ApoE is involved in lipid metabolism and may influence absorption of luminal cholesterol and bile acid metabolism (1416). It has been proposed that having an e4 apoE allele might increase the risk of gallstones (17,18). Bile acid production has been hypothesized as important in the etiology of colorectal cancer; people with gallstones have been shown, in some studies, to have higher risk of developing proximal colon tumors (19). Variants of apoE have been associated with lipid and triglyceride levels and influence insulin sensitivity (20,21). Triglycerides and insulin have been hypothesized as being important in colon cancer etiology (22,23). The third pathway through which apoE might importantly regulate colorectal cancer risk is inflammation, given associations with PPAR{gamma} and lower C-reactive protein levels in the presence of an e4 allele (24,25). Both diet and obesity are associated with colon cancer (26,27).

In this study, we examine the association between apoE genotype and colorectal cancer risk. We evaluate associations by tumor site, given previously reported site-specific associations (11,12), and associations by age and gender, given previous gender-specific associations with apoE (13). In addition, we evaluate if people with a family history of colorectal cancer or certain diet and lifestyle factors have a different susceptibility given their apoE genotype. We also explore the interaction between aspirin/NSAIDs use and apoE genotype to evaluate interaction with inflammation pathways, interaction with BMI and physical activity to evaluate possible involvement in an insulin-related pathway, and interaction with dietary pattern to determine involvement in a cholesterol/bile acid pathway.


    Materials and methods
 Top
 Abstract
 Introduction
 Materials and methods
 Results
 Discussion
 References
 
Study population
Participants in the study were from the Kaiser Permanente Medical Care Program of Northern California (KPMCP), the state of Utah, and the Twin City metropolitan area of Minnesota. All eligible cases within these defined geographic areas were identified and recruited for the two studies. The first study included cases and controls from a population-based case–control study of first primary colon cancer (ICD-O 2nd edition codes 18.0, 18.2–18.9) diagnosed between October 1, 1991 and September 30, 1994 conducted in the three geographic areas. Cases from the second study were diagnosed with a first primary tumor in the rectosigmoid junction or rectum and were identified between May 1997 and May 2001 in Utah and KPMCP only. Case eligibility was determined by the Surveillance Epidemiology and End Results (SEER) Cancer Registries in Northern California and in Utah and the Minnesota Surveillance System (colon cancer cases only). In both studies, cases were identified using rapid-reporting systems. For both studies, eligibility included being between 30 and 79 years of age at time of diagnosis, English speaking, mentally competent to complete the interview, no previous history of colorectal cancer (28) and no known (as indicated on the pathology report) familial adenomatous polyposis, ulcerative colitis or Crohn's disease. For the colon cancer study, the median time from diagnosis to interview was 131 days overall (126 days at KPMCP, 154 days in Minnesota and 109 days in Utah). The median time from diagnosis to interview was longer for the rectal cancer study, primarily because of different levels of permission needed prior to contacting patients; at KPMCP the median days from diagnosis to interview was 154 and for Utah was 183. Of cases contacted, 83% participated at KPMCP, 76% in Utah and 67% in Minnesota. For the rectal cancer study, the cooperation rates were 75.4% of cases from KPCMP and 69.7% of cases from Utah (29).

Controls were frequency matched to cases by gender and by 5-year age groups, but not ethnicity. At the KPMCP, controls were randomly selected from the membership lists. In Utah, controls ≥65 years were randomly selected from the lists provided by the Centers for Medicare and Medicaid Services (formerly HCFA) and controls younger than 65 years were randomly selected from driver's license lists. In Minnesota, controls were randomly selected from driver's license lists. Of controls contacted for the colon cancer study, 73% participated at KPMCP, 53% participated from Minnesota and 69% participated from Utah. For the rectal cancer study, cooperation rates among controls were 69.9% for KPMCP and 67.2% for Utah, respectively.

Data collection
Trained and certified interviewers collected diet and lifestyle data (30,31). The referent period for the study was the calendar year ~2 years prior to date of diagnosis (cases) or selection (controls). Information was collected on demographic factors such as age, gender and study center; physical activity as determined by a detailed physical activity questionnaire that obtained information on the activity patterns 10 and 20 years earlier as well as the activity during the referent year (32,33); body size, including usual adult height and weight 2 and 5 years prior to diagnosis; cigarette smoking history; family history of colorectal cancer in first degree relatives; medical and reproductive history including use of hormone replacement therapy (HRT).

Data on regular (at least 3 times a week for 1 month) use of aspirin and non-steroidal anti-inflammatory drugs (NSAIDs) were obtained from the following question: ‘Before the referent date, did you ever take aspirin, excluding Tylenol, regularly?’ Some brand names for aspirin include Anacin, Arthritis Pain Formula, Ascriptin Tablets, Bayer, Buffrin, Empirin, Excedrin and Vanquish. ‘Before the referent data did you ever take other non-steroidal anti-inflammatory drugs or arthritis medicines such as ibuprofen, Motrin, Clinoril, Naprosyn or Feldene?’

Dietary intake data were ascertained using an adaptation of the validated CARDIA diet history questionnaire (34). Eating patterns were developed using factor analysis as described elsewhere using the SAS principal-components program (35). After a varimax rotation, factor scores were saved for each individual. The food patterns arbitrarily labeled as ‘western diet’ and ‘prudent diet’ were used for the analyses presented here. The western dietary eating pattern loaded heavily (factors with loadings >0.30) on processed meats, red meat, fast-food meat, eggs, butter (men only), margarine, potatoes, high fat dairy foods (men only), legumes, refined grains, added sugar (men only), sugar drinks (men only) and sugar desserts, while the prudent dietary eating pattern loaded heavily on fruits, vegetables, whole grains, and fish and chicken.

Genotyping
DNA was extracted from peripheral blood leukocytes. For quality control, known controls representing all polymorphic variants and blanks were included in each 96-well tray. All genotypes were scored by two individuals. DNA was extracted from peripheral blood leukocytes. apoE genotyping was performed according the methods of Zivelin et al. (36) with minor modifications. For quality control, known controls representing all polymorphic variants and blanks were included in each 96-well tray. In brief, 20 ng of genomic DNA was PCR amplified using oligonucleotide primers apoE-F 5'-TCC AAG GAG CTG CAG GCG GCG CA-3' and apoE-R 5'-GCC CCG GCC TGG TAC ACT GCC A-3'. The 23 µl PCR reaction contained 0.2 mM dNTPs, 1.5 mM Mg2+, 1% DMSO and 0.4 U of Taq polymerase (Perkin Elmer, Boston, MA). The PCR reactions were initially denatured at 95°C for 3 min then subjected to 35 two-step cycles consisting of 10 s at 95°C followed by 10 s at 66°C. A final extension of 5 min at 72°C was performed. A 10 µl aliquot of each PCR product was digested with 5 U of AflIII and another 10 µl aliquot was independently digested with 5 U of HaeII. Digests were performed according to the manufacturer's instructions (NEB, Beverly, MA) for 16 h at 37°C. The digested PCR products were size fractionated on 4% agarose gels (GenePure LE, Minneapolis, MN; ISC Bioexpress) and visualized with ethidium bromide. All genotypes were scored by two individuals. Both the apoE*2 and apoE*3 alleles are cut with AflIII yielding products of 50 and 168 bp, while the apoE*4 allele remains uncut at 218 bp. Both the apoE*3 and apoE*4 alleles are cut with HaeII yielding products of 23 and 195 bp, while the apoE*2 allele remains uncut at 218 bp. Where ambiguous phasing of the genotypes was seen, double digests were performed as described in Zivelin et al. (36). Through analysis of these restriction digest patterns, the six common apoE genotypes were assigned.

Tissue ascertainment
Methods for obtaining tumor tissue have been described previously (37). Mutational analysis for microsatellite instability and mutations in codons 12 and 13 of Ki-ras and exons 5–8 of p53 in the 1572 colon cancer cases were determined in previous studies (3840).

Information on age at the time of diagnosis, gender, tumor site and tumor stage were available from the Northern California Tumor Registry, the Sacramento Tumor Registry and the Utah Cancer Registry. These registries are members of the SEER program. Comparable data for cases in Minnesota were obtained from the Minnesota Cancer Surveillance System. We staged the tumors using American Joint Committee on Cancer (AJCC) criteria and determined histological grade by reviewing pathology reports. Since we did not have access to complete medical records, AJCC stage IV tumors were identified using SEER summary stage codes to determine whether or not distant metastases were present. Vital status, date of death, primary cause of death and two contributing causes of death were obtained from local tumor registries using death certificate information. Active follow-up of people diagnosed with cancer is done through the cancer registries on a continuous basis. Vital status as of 2001 was obtained for colon-cancer study participants and as of 2003 for rectal-cancer study participants. For individuals whose vital status or cause of death could not be determined through local tumor registries, National Death Index tapes were used. Months of survival were calculated by subtracting the date of last contact or death from the date of diagnosis. Deaths from any cause as well as deaths attributed to colorectal cancer were assessed based on the availability of data for cause-specific mortality. All aspects of this study were approved by the University of Utah Institutional Review Board.

Statistical analysis
SAS statistical package, version 8.2, was used to conduct the analyses and SAS genetics. Analyses included evaluating the distribution of the alleles and genotypes in the study population and the independent associations of genetic polymorphisms with colorectal cancer risk, and the joint effect of genotypes on colorectal cancer risk. Multiple logistic regression models, adjusting for age, ethnicity and gender, were used to determine associations between genotypes and colorectal cancer risk and reported as odds ratio (OR) and 95% confidence intervals (CI). In these models, potentially confounding factors that were considered included BMI, physical activity, dietary composition, energy intake and aspirin/NSAID use; the final models included age, gender, BMI, physical activity, energy intake, dietary fiber and calcium. The majority of the population studied were non-Hispanic white and adjustment for racial group did not influence the results; stratification by ethnic group was not meaningful given small sample size for participants who were not white (Table I).


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Table I. Characteristics of the study population

 
Several tests for interaction were performed. The relative excess risk from interaction (RERI) and corresponding 95% CI was calculated to provide insight into differences that might be expected on an additive scale of interaction as described by Hosmer and Lemeshow (41). Polytomous regression models were used to evaluate associations with tumor site and with tumor mutations. Tumor site was defined as proximal (cecum through transverse colon), distal (splenic flexure, descending and sigmoid colon) or rectal (rectosigmoid junction and rectum). In these regression models estimating associations with tumor mutations, any p53, Ki-ras or MSI mutation were compared with controls. Associations between survival and apoE genotype were determined using Cox proportional hazards models, adjusting for age, gender and tumor stage at the time of diagnosis.


    Results
 Top
 Abstract
 Introduction
 Materials and methods
 Results
 Discussion
 References
 
Characteristics of the study population are shown in Table I. The majority of cases are non-Hispanic white. Significantly, more colon cancer cases reported a family history of colorectal cancer than rectal cancer cases, while ~40% of both colon and rectal cancer cases reported ever using aspirin or NSAIDs. Colon cancer cases had significantly higher mean levels of BMI and western diet, and lower mean levels of vigorous long-term physical activity and prudent diet. Similar observations for physical activity and western dietary pattern were observed for rectal cancer as for colon cancer.

The e3 allele was the most common allele, with allele frequencies in controls of 8% for the e2 allele, 78% for the e3 allele and 14% for the e4 allele. The allele frequencies were in Hardy–Weinberg equilibrium. To better understand associations between various combinations of apoE alleles, we evaluated various genotypes and tumor site specific associations (Table II). We did not observe differences in risk between proximal and distal tumors (data not shown in table). There were no associations between apoE genotype and MSI, p53, and Ki-ras tumor mutations overall or specific types of p53 and Ki-ras mutations (data not shown in table). apoE genotype did not significantly alter survival after diagnosis with colorectal cancer nor did it influence stage of disease at diagnosis (data not shown in table).


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Table II. Associations between apoE genotype and colon and rectal cancers

 
Compared with subjects having the e3/e3 genotype, those who were heterozygous for e3 and any other allele had very similar colon cancer risk, but individuals with no e3 allele were at an increased risk of colon cancer (Table II). There were no consistent trends in association between apoE genotype and rectal cancer. We did not observe differences in association between apoE and colon or rectal cancer risk by gender (Table III). However, we did observe significant differences in association between apoE genotype and colon cancer by age (RERI P value = 0.05). People diagnosed when older were at significantly increased risk of colon cancer if they did not have an e3 allele (OR = 1.88; 95% CI 1.17–3.04).


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Table III. Gender and age-specific associations between apoE genotype and risk of colon and rectal cancers

 
Since an age-specific association was observed for colon cancer but not rectal cancer, we evaluated potential gene–environment interactions stratified by age for colon cancer. There was no significant interaction between family history of colorectal cancer and apoE genotype overall or for specific age at diagnosis (Table IV). However, there was an overall three-way interaction when age was included in the model (P = 0.05). People diagnosed when younger had a stronger risk of colon cancer if they also had a family history of colorectal cancer regardless of apoE genotype. However, people diagnosed when older had a stronger risk of colon cancer from family history of colorectal cancer if they did not have an e3 allele.


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Table IV. Interaction between apoE genotype and family history of colorectal cancer (CRC) and colon cancer risk

 
apoE genotype did not interact significantly with NSAID use, BMI, physical activity level, western or prudent dietary pattern for either younger or older individuals (Table V). Although interactions were not significant there were clearly different trends in association between those diagnosed when younger and older. Among individuals diagnosed when younger, the strongest risk was observed from being obese, inactive and not using NSAIDs with little variation in colon cancer risk associated with apoE genotype. However, among older individuals, the strongest risk for all exposures was seen among those without an e3 allele, with increasing risk across genotype among those not using NSAIDs, being overweight, sedentary and having a high western dietary pattern and low prudent dietary pattern.


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Table V. Associations between apoE and NSAIDs, BMI, PAL, western and prudent dietary patterns and colon cancer by age

 
Assessment of apoE with NSAID use, BMI, physical activity level, western and prudent dietary pattern and rectal cancer risk did not detect meaningful significant interactions (Table VI). However, unlike risk estimates associated with colon cancer, for rectal cancer there tended to be a non-statistically significant inverse association with most factors for those who did not have an e3 allele.


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Table VI. Interaction between apoE, NSAIDs use, BMI, PAL, western and prudent dietary patterns and rectal cancer

 

    Discussion
 Top
 Abstract
 Introduction
 Materials and methods
 Results
 Discussion
 References
 
Our results suggest that not having an apoE e3 allele increases the risk of colon cancer among those diagnosed at an older age. Among those diagnosed with rectal cancer there was a trend toward reduced risk in the absence of an e3 allele. We also observed a significant interaction between age, apoE3 genotype and family history of colorectal cancer; a family history of colorectal cancer was associated with increased risk among older individuals in the absence of an e3 allele. Assessment of diet and lifestyle factors that could possibly interact with apoE genotype, and potential mechanisms for their influence (lipid or bile metabolism, inflammation or triglyceride and insulin level), did not show any significant interactions, although a clear trend towards a greater risk of colon cancer among those not having an e3 allele was seen.

Previous studies suggest that apoE genotype might alter the risk of colon cancer and/or adenomas, with stronger associations being observed for proximal tumors and adenomas (1113). Although we did not detect any differences in the risk for proximal or distal tumors we did see different trends in association between colon and rectal tumors. A slight increase in risk was observed in the absence of an e3 apoE allele for colon cancer and no effect was observed for rectal cancer. If the mechanism of action is one that relates to bile acid metabolism, it is possible that this mechanism is more specific to colon rather than rectal tumors. Although studies as to the association between gallstones and colon cancer risk are far from conclusive as to the causal association, studies that do detect associations show stronger risk for proximal colon tumors rather than for distal or rectal tumors (42).

Our finding of an association between not having an e3 apoE allele and colon cancer risk was further limited to those diagnosed when older. The majority of individuals without an e3 allele had an e4 allele. The e4 allele has been associated with higher cholesterol and lipid levels (1) and has been reported, in other studies, to reduce the risk of proximal tumors (1113), although we did not observe this in our studies. The genotypes with no e3 alleles, that were associated with increased colon cancer risk in our study, are the same genotypes that are associated with increased risk of coronary heart disease. It is possible that years of exposure to higher cholesterol and lipids may result in the increased colon cancer risk associated with no e3 apoE alleles (8,9).

In the light of the regulatory role of apoE genotypes on lipid metabolism, inflammation and insulin, it is reasonable that dietary factors would be influenced by this gene (1,20,25,43). Although we did not observe significant interaction in diet and lifestyle factors with apoE genotype, associations were generally stronger among those diagnosed with colon cancer when older, with suggestions of possible effect modification. Given the rarity of not having an e3 apoE allele, our ability to detect significant interactions was restricted, imposing a limitation on the study. Assessment of the data indicated that for the most part, any association was limited to those without any e3 allele, making the regrouping of the data to incorporate those with one e3 allele with the ones without any e3 allele, less meaningful. Thus, although no significant interactions were observed, associations with NSAIDs use, diet, BMI and physical activity were considerably stronger among older people without an e3 allele. Other large studies need to evaluate these factors with the apoE genotype.

Of interest is the association between apoE genotype and family history of colorectal cancer and risk of developing colon cancer. A significant three-way interaction (age, apoE genotype and family history of colorectal cancer), was detected for colon cancer risk. The colon cancer risk associated with family history of colorectal cancer in first degree relatives was markedly greater among those without an e3 apoE allele if diagnosed when older, although apoE genotype did not appear to greatly influence risk when diagnosed at a younger age. This observation ties into a consistent pattern in the data that the associations with apoE genotype are restricted to those diagnosed when older. This observation with family history could imply genetic factors, but the association with older age is, perhaps, more consistent with the cumulative effects of shared exposures such as dietary intake.

A strength of the study was its large sample size, although we were still limited in power to assess interactions when restricted to cases of colon cancer diagnosed when older, the subgroup of the population that appeared to be most susceptible to apoE genotype. The data were collected in a rigorous manner, although limitations in individual ability to accurately report exposure data exist. The genotype data were similar to genotype frequencies reported by others (1,13,44) and was in Hardy–Weinberg equilibrium.

In summary, these data suggest that apoE genotype may be associated with colon cancer in older individuals. Furthermore, there are suggestions that the absence of an e3 apoE allele may increase the risk associated with high intake of a western-type diet, not using NSAIDs and BMI among older (>65 years) people. Any increased risk associated with apoE genotype appeared to be limited to colon cancer rather than rectal cancer. apoE genotype did not appear to influence survival after diagnosis, nor was it associated with any specific acquired genetic changes in tumors. Further assessment of apoE genotype with diet composition and gallstones may provide additional insight into the role of apoE in colon cancer development.


    Acknowledgments
 
We would like to acknowledge the contributions of Michael Hoffman and Thao Tran for genotyping and Dr Bette Caan, Sandra Edwards, Karen Curtin, Roger Edwards, Leslie Palmer, Donna Schaffer, Dr Kristin Anderson and Judy Morse for data management and collection. This study was funded by NCI grants CA48998, CA85846, and CA61757 to M.L.S. This research was also supported by the Utah Cancer Registry, which is funded by Contract no. N01-PC-67000 from the National Cancer Institute, with additional support from the State of Utah Department of Health, the Northern California Cancer Registry and the Sacramento Tumor Registry.

Conflict of Interest Statement: The contents of this paper are solely the responsibility of the authors and do not necessarily represent the official view of the National Cancer Institute.


    References
 Top
 Abstract
 Introduction
 Materials and methods
 Results
 Discussion
 References
 

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Received January 25, 2005; revised March 11, 2005; accepted March 25, 2005.





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