| HOME | HELP | FEEDBACK | SUBSCRIPTIONS | ARCHIVE | SEARCH | TABLE OF CONTENTS |
Epidemiology and Prevention |
Health Research Center, Department of Family and Preventive Medicine, University of Utah, Salt Lake City, Utah 84108 [M. L. S., K. C., K-N. M., S. E.]; University of Minnesota, School of Public Health, Minneapolis, Minnesota 55455-0381 [K. A.]; Departments of Genetics [M. L.] and Pathology [W. S. S.], University of Utah, Salt Lake City, Utah 84108; Fred Hutchinson Cancer Research Center, Seattle, Washington 98104 [J. P.]; and Kaiser Permanente Medical Care Program, Oakland, California 94611-5714 [D. S.]
 |
ABSTRACT |
|---|
 Top ABSTRACT INTRODUCTIONSUBJECTS AND METHODSRESULTSDISCUSSIONAPPENDIXREFERENCES |
|---|
A transitions in the second base of codon 12
(2GA). Other than cruciferous vegetables, there were no nutrients or
foods associated specifically with Ki-ras mutations
[odds ratio (OR) for high intake relative to low intake, 0.7; 95%
confidence interval (CI), 0.5–1.0]. However, evaluation of specific
types of Ki-ras mutations revealed that for each of the
most common types of mutation, dietary associations existed. Dietary
factors involved in DNA methylation pathways were associated with
2GA mutations. Comparison of individuals with and without
Ki-ras mutations revealed that individuals with low
levels of dietary folate (OR, 0.7; 95% CI, 0.4–1.3), vitamin
B6 (OR, 0.5; 95% CI, 0.3–1.0), vitamin B12
(OR, 0.6; 95% CI, 0.3–1.1), and high levels of alcohol (OR, 0.7; 95%
CI, 0.4–1.1) were less likely to have a 2GA mutation. Individuals
with high levels of dietary carbohydrate (OR, 2.0; 95% CI, 0.9–4.4)
and a high glycemic index (OR, 1.9; 95% CI, 0.8–4.6) were more likely
to have a GA transition mutation in the second base of codon 13
(5GA). Individuals with high levels of dietary fat (OR, 1.6; 95%
CI, 0.8–3.2), saturated fat (OR, 1.7; 95% CI, 0.8–3.5), and
monounsaturated fat (OR, 1.9; 95% CI, 1.0–3.7) were more likely to
harbor a 2GT mutation. Low levels of cruciferous vegetable intake
and high levels of processed meat intake also were associated with
fewer 5GA, as reflected by the ORs (OR, 0.4; 95% CI, 0.2–1.0 and
OR, 0.4; 95% CI 0.2–0.8, respectively). These data suggest that diet
may be involved in disease pathways represented by specific
Ki-ras mutations. However, given the limited information
currently available on associations between specific genetic mutations
in colon tumors and diet, these findings also should be viewed as
hypothesis generating. |
INTRODUCTION |
|---|
|
TopABSTRACTINTRODUCTIONSUBJECTS AND METHODSRESULTSDISCUSSIONAPPENDIXREFERENCES |
|---|
Mutations in the Ki-ras gene were among the first linked to
the pathogenesis of colon cancer (4)
. Ki-ras
mutations are thought to be early events in colon cancer pathogenesis
because they are observed in both adenomas and carcinomas
(5, 6, 7)
. Most studies estimate that 30–50% of adenomas
and carcinomas have Ki-ras mutations; 
90% of
Ki-ras mutations in colon tumors occur in codons 12 and 13
(7, 8, 9)
.
Data to support specific associations between diet and genetic mutations in tumors are limited. In one case-control study of 108 sporadic colorectal cancers, low levels of calcium and high levels of monounsaturated fat were associated with increased odds of having Ki-ras+ tumors (10) . Another study of adenomas observed that high levels of dietary plus supplemental folate were associated with decreased odds of having Ki-ras+ adenomas; dietary folate without supplements was not associated with Ki-ras+ adenomas (11) . Because previous diet and Ki-ras mutations in colon tumors have included few people, it has not been possible to evaluate dietary associations with specific types of Ki-ras mutations. However, the study by Martinez et al. (11) did evaluate specific types of mutations with dietary factors and did not observe significant differences in dietary associations with specific types of mutations.
In this study, we used data collected as part of a large population-based case-control study of sporadic colon cancer to evaluate associations between dietary intake and Ki-ras mutations. Because we have data available on 1428 colon cancer cases and 2406 controls, we were able to evaluate dietary associations with the overall presence of any Ki-ras mutation in the tumor as well as with specific types and location of mutations. Although we focus on distinct pathways that have been hypothesized as being involved in colon cancer, including bile acids and dietary fat, DNA methylation, carcinogen detoxification, and insulin-related factors (12, 13, 14, 15) , we also explore other dietary associations with Ki-ras. Because little information exists about the role of diet and distinct genetic mutations in tumors, this information also can be viewed as hypothesis generating.
|
SUBJECTS AND METHODS |
|---|
|
TopABSTRACTINTRODUCTIONSUBJECTS AND METHODSRESULTSDISCUSSIONAPPENDIXREFERENCES |
|---|
Controls, in addition to the eligibility criteria for cases, could never have had a previous colorectal tumor. Controls were selected from eligibility lists for the Kaiser Permanente Medical Care Program, driver’s license lists for Minnesota, and random-digit-dialing, driver’s license lists, or Health Care Finance Administration lists for Utah. These methods have been described in detail (16) . Of all controls selected, 63.7% participated.
Dietary Data.
Dietary intake data were ascertained using an adaptation of the
validated CARDIA diet history questionnaire (17
, 18)
.
Participants were asked to determine which foods were eaten (using
brand names of food items such as fast foods, cookies, crackers, and
cereals, when possible), the frequency with which foods were eaten, and
the type of fat used in preparation of foods. Three-dimensional food
models were used to help participants estimate their usual serving
size. Cue cards were used to provide a consistent prompt to help
identify foods within broad categories. For categories within which
many types of food might have been eaten (such as breakfast cereal),
participants were asked to report the three most commonly eaten items.
Detailed information was also obtained on foods eaten as additions to
other foods (such as sugar added to cereal); standard amounts of
additions were assigned per unit of the food item they accompanied.
Nutrients were calculated using the Minnesota Nutrition Coordinating
Center’s nutrient database version 19.
Foods were grouped into categories of red meat; processed meats (including hot dogs, luncheon meat, and sausage); eggs; low-fat dairy products (including milk, yogurt, and cheese); fruit (including fresh, frozen, and canned fruits); vegetables; cruciferous vegetables; whole grains; and refined grains. Food groups were developed by assigning each food item a standard serving size. The number of standard servings consumed from a food group were summed for each individual. A dietary glycemic index was created so that dietary carbohydrates could be weighed by their metabolic effect (19) . A mutagen index was created that accounted for the amount of meat eaten, how it was prepared (i.e., well done, medium rare, and rare), and if it were precooked in a microwave.
Other Data.
Environmental exposure data were collected by trained and certified
interviewers (20)
. The referent period for the study was
the calendar year, 2 years prior to the date of diagnosis (cases) or
selection (controls). Information was collected on demographic factors
such as age, sex, and center; physical activity (16)
; body
size, including usual adult height and weight 2 and 5 years prior to
diagnosis; use of aspirin and/or nonsteroidal anti-inflammatory drugs;
cigarette smoking history; and medical and reproductive history
including use of hormone replacement therapy.
Tissue Ascertainment.
Methods for obtaining tumor tissue and extracting DNA have been
discussed (21)
. Mutations in codons 12 and 13 of the
Ki-ras gene were detected by PCR amplification and
sequencing of exon 1 using DNA obtained from paraffin-embedded tissue
blocks (22)
. Primers were tailed with universal
primer and reverse primer for sequencing. PCR products
were sequenced using prism Big Dye terminators and cycle sequencing
with Taq FS DNA polymerase. DNA sequence was collected and analyzed on
an ABI prism 377 automated DNA sequencer. We considered as mutations
only those bp changes that were verified by sequencing in both
directions (figure in Ref. 23
). Tumor DNA was available
from 1836 cases. Of these, 1428 were interviewed and had valid study
data as well as Ki-ras data. We were able to successfully
PCR amplify and sequence DNA from 95% of tumors we received to
determine Ki-ras mutational status.
Statistical Analyses.
The distribution of specific types of mutations in tumors was
determined. Logistic regression models, using two comparison groups,
were fit to the data. A case-control comparison was conducted to
estimate the relative risk of developing disease with specific genetic
mutations. Evaluation of case-control data enables the evaluation of
risk similar to that presented in the traditional case-control study.
Controls were compared with cases with and without Ki-ras
mutations in their tumors. Logistic regression models also were fit
with the dichotomous dependent variables as either "no disease"
versus "Ki-ras+ disease," or "no disease"
versus "Ki-ras- disease." We also assessed
associations of Ki-ras+ compared with Ki-ras-.
The purpose of the "case-case" comparison was to evaluate
etiological heterogeneity of the risk factors under study. For these
analyses, the logistic regression models were fit with a dichotomous
dependent variable (Ki-ras+ or Ki-ras-). We also
assessed specific types of mutations that were relatively common. We
evaluated lifestyle exposures with mutations in codon 12, mutations in
codon 13, transversions, transitions, and three of the most common
specific types of mutations: GA of the second base of codon 12
(2GA), GT of the second base of codon 12 (2GT), and GA of
the second base of codon 13 (5GA). All nutrients were evaluated
using the density measure, or the amount per 1000 kcal. Categorization
of nutrients was based on the distribution of nutrient values in the
control population. Assessment of linear trend was done using
continuous variables in logistic regression models.
|
RESULTS |
|---|
|
TopABSTRACTINTRODUCTIONSUBJECTS AND METHODSRESULTSDISCUSSIONAPPENDIXREFERENCES |
|---|
. Of these, the majority were in codon
12 (80.7%). The most common type of mutation was a GA transition on
the second base of codon 12, which occurred in 10.5% of all colon
tumors and represented 32.8% of all Ki-ras mutations.
|
. Differences in risk
were similar when comparing controls with individuals in either tumor
group, i.e., those Ki-ras+ and those
Ki-ras-. Few differences in Ki-ras mutational
status were observed for dietary factors in DNA methylation pathways or
insulin-related pathways. Cruciferous vegetables showed a statistically
significant association with Ki-ras+ tumors. People who
reported low levels (<0.37 servings/week) of these vegetables were
less likely to have Ki-ras mutations when compared with
those who ate more than four servings of cruciferous vegetables a week
(OR,3
0.6; 95% CI,
0.4–0.9; P linear trend, 0.01).
|
Assessment of specific types of mutations (Table 3)
support three distinct disease
pathways. The 2GA mutations were associated with dietary factors
involved in the DNA methylation process; high levels of mutagen index
(not shown in the Table
) also were associated with a reduced risk of
having a 2GA mutation (OR, 0.6; 95% CI, 0.3–0.9; P
linear trend = 0.02). Interestingly, high levels of
alcohol and low levels of dietary folate, vitamin
B6, and B12 were associated
with a reduced risk of having this type of Ki-ras mutation.
A 5GA mutation (second base of codon 13) was directly associated
with levels of carbohydrate, refined grain intake, and glycemic index;
low levels of cruciferous vegetable intake and high levels of processed
meat intake were associated with reduced risk of a 5GA mutation (for
cruciferous vegetables: OR, 0.4; 95% CI, 0.2–1.0; P linear
trend = 0.74; for processed meat: OR, 0.4; 95% CI,
0.2–0.8; P linear trend = 0.14). Dietary
fats were directly associated with 2GT mutations. Low levels of
lutein in the diet (data not shown in the Table
) were associated with a
reduced risk of 2GT mutations (OR, 0.7; 95% CI, 0.3–1.4;
P linear trend = 0.02).
|
Low levels of intake of cruciferous vegetables and dietary factors associated with DNA methylation were associated with a reduced risk of having a transition type of Ki-ras mutation (for cruciferous vegetables: OR, 0.6; 95% CI, 0.4–0.9; for all dietary DNA methylation factors: OR, 0.7; 95% CI, 0.4–1.1). High levels of energy (OR, 1.8; 95% CI, 0.1–3.0; P linear trend = 0.60), fat (OR, 1.5; 95% CI, 0.9–2.4; P linear trend = 0.04), monounsaturated fat (OR, 1.3; 95% CI, 0.8–2.0; P linear trend = 0.06), and eggs (OR, 1.5; 95% CI, 1.0–2.4; P linear trend = 0.07) were associated with a greater risk of having a transversion Ki-ras mutation. High levels of carbohydrate were associated with a greater likelihood of not having a transversion Ki-ras mutation (OR, 0.5; 95% CI, 0.3–0.9; P linear trend = 0.10).
|
DISCUSSION |
|---|
|
TopABSTRACTINTRODUCTIONSUBJECTS AND METHODSRESULTSDISCUSSIONAPPENDIXREFERENCES |
|---|
A mutations; carbohydrates, glycemic index,
and refined grains were associated with 5GA mutations; and dietary
fats were associated with 2GT mutations. Low levels of cruciferous
vegetables were associated with fewer Ki-ras mutations.
Cruciferous vegetables are inducers of the phase II metabolizing
enzyme, glutathione S-transferase, which is involved in
multiple biological mechanisms (14)
. Other dietary factors
were inconsistently associated with Ki-ras mutations (see Appendix 1). One study that evaluated dietary factors and Ki-ras mutations observed that a high intake of calcium decreased the risk of having a Ki-ras mutation, whereas a high intake of monounsaturated fat increased the risk of these mutations (10) . In that study, there were 108 colorectal cancer cases, and thus estimates of association were less precise than those presented here. We did not observe an association between dietary calcium that was specific to tumors with Ki-ras mutations. We did observe direct associations with monounsaturated fat for specific types of mutations, as mentioned earlier, although associations with overall Ki-ras mutations were much weaker. High levels of dietary heterocyclic amines influence Ki-ras mutations in rats (24) . In this study, we observed that both the intake of processed meats and dietary mutagen index, which was created to discriminate between people with varying levels of heterocyclic amines in their diets, were associated with specific types of Ki-ras mutations.
Perhaps one of the most intriguing observations from this study is
that, for several dietary factors, particularly those involved in DNA
methylation pathways, the results observed are different from those
reported recently for adenomas (11)
. In the study of
adenomas, only folate supplements were associated with reducing risk of
Ki-ras mutations, whereas dietary folate and alcohol were
not. Other dietary factors involved in the DNA methylation pathway were
not reported in the work by Martinez et al.
(11)
. It was hypothesized in that report that
when the availability of methyl donors was low, a GA transition
would be generated (11)
. In this study, we observed that
dietary factors involved in the DNA methylation pathway were associated
with GA transitions. However, low levels of intake of nutrients
involved in this pathway, including folate, vitamin
B6, and vitamin B12, and
high levels of intake of alcohol were associated with a greater
likelihood of being Ki-ras- rather than having a GA
mutation. In this study population, we observed that folate and
vitamins B6 and B12 were
inversely associated with colon cancer in the total population
(25)
. Because the overall association between these
nutrients and cancer was inverse and these same nutrients were directly
associated with this specific Ki-ras mutation, it is likely
that these dietary factors associated with DNA methylation are involved
in other disease pathways. Our results do suggest that associations
with adenomas and tumors are different, and that dietary factors
associated with DNA methylation act differently at the initiation
versus promotion stage of the carcinogenic process. The
sequence of genetic alterations in adenomas and tumors may have
important significance as we unravel how dietary factors contribute to
the carcinogenic process.
Two other pathways, distinct from the pathway involving DNA
methylation, appear to exist. One of these involves 2GT
Ki-ras mutations and high levels of dietary fat; the other
involves 5GT Ki-ras mutations and high levels of
carbohydrates, glycemic index, and refined grains. Specific chemical or
molecular mechanisms involved can only be speculative. However, this
information may provide insight into how Ki-ras functions.
These observations also may explain differences in dietary associations
observed between epidemiological studies.
It is possible that our findings do not have biological meaning but are the result of bias associated with misclassification. Given that Ki-ras mutations are early events in the carcinogenic process, it is possible that dietary changes have been made so that the referent date of 2 years prior to diagnosis is not reflective of usual adult diet. Likewise, those for whom data are less likely to be available are those with tumors at a more advanced disease stage. We observed both in our collection of tumor tissue (17) and in our collection of dietary data (26) that individuals with more advanced disease are less likely to participate in the study. In our attempts to estimate selection bias associated with exclusion of these individuals from the dietary collection segment of the study, we did not observe specific associations by disease stage (26) . However, we have observed that those with more advanced tumors are more likely to have Ki-ras mutations in codon 12.
There are several strengths to our study. Our study is population based rather than cases derived from select populations of high-risk individuals or hospital-based studies. Given the large sample size, we were able to evaluate specific types of Ki-ras mutations in tumors, which provides more insight into distinct disease pathways. Although not all cases had exposure data, the distribution of Ki-ras mutations was not different for those with and without interview data; there does not appear to be selection bias involving Ki-ras mutation status.
Because there was limited information to guide our analyses, we evaluated dietary factors that had been associated with colon cancer along three pathways that have been hypothesized as being important to colon cancer. Because we evaluated numerous dietary factors, findings could be the result of chance. However, we believe that clustering of similar dietary factors as a group into what could represent distinct disease pathways lends support for the observed associations being real. Repeating these analyses in other large study populations will help to distinguish between these possibilities.
In summary, our results suggest that dietary intake influences distinct Ki-ras mutations that could represent distinct disease pathways, rather than Ki-ras mutations overall. These results, together with previous research, suggest that there may be differences between Ki-ras mutations in adenomas and Ki-ras mutations in colon tumors. In reading these results, however, it should be kept in mind that although some factors, such as dietary folate, were shown to increase the likelihood of specific Ki-ras mutations, these nutrients were associated with a decreased risk of developing colon cancer.
|
APPENDIX |
|---|
|
TopABSTRACTINTRODUCTIONSUBJECTS AND METHODSRESULTSDISCUSSIONAPPENDIXREFERENCES |
|---|
|
|
|
ACKNOWLEDGMENTS |
|---|
|
FOOTNOTES |
|---|
1 This study was funded by CA48998 and CA61757 to
Dr. Slattery. This research was supported by the Utah Cancer Registry,
which is funded by Contract #N01-PC-67000 from the National Cancer
Institute, with additional support from the State of Utah Department of
Health and the University of Utah, the Northern California Cancer
Registry, and the Sacramento Tumor Registry. 
2 To whom requests for reprints should be
addressed, at Health Research Center, Department of Family and
Preventive Medicine, University of Utah, 391 Chipeta Way, Suite G, Salt
Lake City, Utah 84108.
3 The abbreviations used are: OR, odds ratio; CI,
confidence interval.
Received 4/11/00. Accepted 10/10/00.
|
REFERENCES |
|---|
|
TopABSTRACTINTRODUCTIONSUBJECTS AND METHODSRESULTSDISCUSSIONAPPENDIXREFERENCES |
|---|
This article has been cited by other articles:
|
|
 |
|
  H. G Mulholland, L. J Murray, C. R Cardwell, and M. M Cantwell Glycemic index, glycemic load, and risk of digestive tract neoplasms: a systematic review and meta-analysis Am. J. Clinical Nutrition, February 1, 2009; 89(2): 568 - 576. [Abstract] [Full Text] [PDF]
|
|
|
|
 |
|
 Y. Suehiro, C. W. Wong, L. R. Chirieac, Y. Kondo, L. Shen, C. R. Webb, Y. W. Chan, A. S.Y. Chan, T. L. Chan, T.-T. Wu, et al. Epigenetic-Genetic Interactions in the APC/WNT, RAS/RAF, and P53 Pathways in Colorectal Carcinoma Clin. Cancer Res., May 1, 2008; 14(9): 2560 - 2569. [Abstract] [Full Text] [PDF]
|
|
|
|
 |
|
 E. Morales, M. Porta, J. Vioque, T. Lopez, M. A Mendez, J. Pumarega, N. Malats, M. Crous-Bou, J. Ngo, J. Rifa, et al. Food and nutrient intakes and K-ras mutations in exocrine pancreatic cancer J Epidemiol Community Health, July 1, 2007; 61(7): 641 - 649. [Abstract] [Full Text] [PDF]
|
|
|
|
 |
|
 S. de Vogel, M. van Engeland, M. Luchtenborg, A. P. de Bruine, G. M. J. M. Roemen, M. H. F. M. Lentjes, R. A. Goldbohm, P. A. van den Brandt, A. F. P. M. de Goeij, and M. P. Weijenberg Dietary Folate and APC Mutations in Sporadic Colorectal Cancer J. Nutr., December 1, 2006; 136(12): 3015 - 3021. [Abstract] [Full Text] [PDF]
|
|
|
|
|
|
A. O. Chan, A. S. Soliman, Q. Zhang, A. Rashid, A. Bedeir, P. S. Houlihan, N. Mokhtar, N. Al-Masri, U. Ozbek, R. Yaghan, et al. Differing DNA Methylation Patterns and Gene Mutation Frequencies in Colorectal Carcinomas from Middle Eastern Countries Clin. Cancer Res., December 1, 2005; 11(23): 8281 - 8287. [Abstract] [Full Text] [PDF]
|
|
|
|
 |
|
 E. Giovannucci and S. Ogino DNA Methylation, Field Effects, and Colorectal Cancer J Natl Cancer Inst, September 21, 2005; 97(18): 1317 - 1319. [Full Text] [PDF]
|
|
|
|
 |
|
 M. Brink, M. P. Weijenberg, A. F. P. M. de Goeij, L. J. Schouten, F. D. H. Koedijk, G. M. J. M. Roemen, M. H. F. M. Lentjes, A. P. de Bruine, R.A. Goldbohm, and P. A. van den Brandt Fat and K-ras mutations in sporadic colorectal cancer in The Netherlands Cohort Study Carcinogenesis, September 1, 2004; 25(9): 1619 - 1628. [Abstract] [Full Text] [PDF]
|
|
|
|
 |
|
 M. M. Huycke and H. R. Gaskins Commensal Bacteria, Redox Stress, and Colorectal Cancer: Mechanisms and Models Experimental Biology and Medicine, July 1, 2004; 229(7): 586 - 597. [Abstract] [Full Text] [PDF]
|
|
|
|
|
|
M. E. Martinez, S. M Henning, and D. S Alberts Folate and colorectal neoplasia: relation between plasma and dietary markers of folate and adenoma recurrence Am. J. Clinical Nutrition, April 1, 2004; 79(4): 691 - 697. [Abstract] [Full Text] [PDF]
|
|
|
|
 |
|
 M. van Engeland, M. P. Weijenberg, G. M. J. M. Roemen, M. Brink, A. P. de Bruine, R. A. Goldbohm, P. A. van den Brandt, S. B. Baylin, A. F. P. M. de Goeij, and J. G. Herman Effects of Dietary Folate and Alcohol Intake on Promoter Methylation in Sporadic Colorectal Cancer: The Netherlands Cohort Study on Diet and Cancer Cancer Res., June 15, 2003; 63(12): 3133 - 3137. [Abstract] [Full Text] [PDF]
|
|
|
|
|
|
M. Brink, A. F.P.M. de Goeij, M. P. Weijenberg, G. M.J.M. Roemen, M. H.F.M. Lentjes, M. M.M. Pachen, K. M. Smits, A. P. de Bruine, R. A. Goldbohm, and P. A. van den Brandt K-ras oncogene mutations in sporadic colorectal cancer in The Netherlands Cohort Study Carcinogenesis, April 1, 2003; 24(4): 703 - 710. [Abstract] [Full Text] [PDF]
|
|
|
|
|
|
B. Diergaarde, W. L. van Geloof, G. N.P. van Muijen, F. J. Kok, and E. Kampman Dietary factors and the occurrence of truncating APC mutations in sporadic colon carcinomas: a Dutch population-based study Carcinogenesis, February 1, 2003; 24(2): 283 - 290. [Abstract] [Full Text] [PDF]
|
|
|
|
|
|
M L Slattery The science and art of molecular epidemiology J Epidemiol Community Health, October 1, 2002; 56(10): 728 - 729. [Full Text] [PDF]
|
|
|
|
 |
|
 V. Bazan, M. Migliavacca, I. Zanna, C. Tubiolo, N. Grassi, M. A. Latteri, M. La Farina, I. Albanese, G. Dardanoni, S. Salerno, et al. Specific codon 13 K-ras mutations are predictive of clinical outcome in colorectal cancer patients, whereas codon 12 K-ras mutations are associated with mucinous histotype Ann. Onc., September 1, 2002; 13(9): 1438 - 1446. [Abstract] [Full Text] [PDF]
|
|
|
|
 |
|
 L. Prix, P. Uciechowski, B. Bockmann, M. Giesing, and A. J. Schuetz Diagnostic Biochip Array for Fast and Sensitive Detection of K-ras Mutations in Stool Clin. Chem., March 1, 2002; 48(3): 428 - 435. [Abstract] [Full Text] [PDF]
|
|
|
|
 |
|
 M Bardou, S Montembault, V Giraud, A Balian, E Borotto, C Houdayer, F Capron, J-C Chaput, and S Naveau Excessive alcohol consumption favours high risk polyp or colorectal cancer occurrence among patients with adenomas: a case control study Gut, January 1, 2002; 50(1): 38 - 42. [Abstract] [Full Text] [PDF]
|
|
| ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| HOME | HELP | FEEDBACK | SUBSCRIPTIONS | ARCHIVE | SEARCH | TABLE OF CONTENTS |
| Cancer Research | Clinical Cancer Research |
| Cancer Epidemiology Biomarkers & Prevention | Molecular Cancer Therapeutics |
| Molecular Cancer Research | Cancer Prevention Research |
| Cancer Prevention Journals Portal | Cancer Reviews Online |
| Annual Meeting Education Book | Meeting Abstracts Online |
