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Nutrition and Cancer Prevention Jackilen Shannon, PhD, RD Overview Historical perspective ◦ Population data to molecular mechanisms Diet and Breast Cancer ◦ What is the evidence? ◦ Overview of findings from Shanghai ◦ Future research directions Challenges and future directions in Nutrition and Cancer Prevention Research Columbus “discovers” America Yong-He Yan Poor nutrition a cause for esophageal cancer 1492 960-1279 AD Roger Williams ‘probably no single factor is more potent in determining the outbreak of cancer in the predisposed, then excessive feeding’ citing specifically, ‘deficient eating and probably lack of sufficient vegetable food’. (The Natural History of Cancer) 1855 1676 1914-1918 1908 Wiseman - cancer may arise from “ an errour in Diet, a great acrimony in the meats and drinks meeting John Snow tracks with a fault in the first source of Cholera Concoction (digestion)” outbreak – advised abstention from ‘salt, sharp and gross meats’ Great Depression Watson & Crick publish the structure of DNA 1929-1939 1939-1945 1937 World War I World War II Frederick Hoffman (founder of ACS) concluded from a systematic literature review ‘excessive nutrition if not the chief cause is at least a contributory factor of the first importance’ 1953 Population studies: Correlational results 1975 – correlational study of incidence of 27 cancers in 23 countries and dietary intake. Armstrong B, Doll R. Int J Cancer 1975; 15: 617-31 Further Evidence: Case-Control and Cohort Studies Doll and Peto (1981) 35% of cancer deaths may be attributed to dietary factors Doll R, Peto R. The causes of cancer. JNCI 1981; 66:1191-1308 World Cancer Research Fund (1997) Cancer incidence can be reduced by 30%-40% with diet, physical activity and appropriate body size. World Cancer Research Fund,. Food, Nutrition and the Prevention of Cancer: a Global Perspective. Washington DC (USA): American Institute for Cancer Research; 1997: 310-323. Role of Diet in the Cancer Process Metabolism & Excretion of Carcinogens •Block metabolic activation • Increase metabolic detoxification Bioactive dietary constituents B-vitamins, glutathione, flavonoids Alcohol Dietary Carcinogens Aflotoxin, heterocyclic amines N-nitroso compounds Smoking, chewing tobacco, betel Smoking Workplace Genes Procarcinogen Phase I metabolizing enzymes P450’s etc. EXCRETION Bioactive dietary constituents Isothiocyanate, selenium, other phytochemicals Ultimate carciongen Genes Phase II metabolizing enzymes glutahione, glutathione transferase, N-acetyl transferases EXCRETION Role of Diet in the Cancer Process – Initiation Folate Deficiency Heterocyclic Amines Inadequate Methyl groups PhiP DNA adducts Genes Physical Activity Energy Intake DNA Repair Hypomethylation of P53 Somatic alteration of oncogenes, Tumour-suppressor genes and DNA repair genes NORMAL DNA Role of Diet in the Cancer Process – Promotion Physical Activity Phytoestrogens Energy Fat Hormones Obesity Abnormal DNA & cell replication Dietary factors Protein Methionine Cholesterol Growth factors Specific nutrients e.g. carotenoids, retinol Colonic Bacteria Fibre REDIFFERENTIATION APOPTOSIS Volatile fatty acids -3 fatty acids Precancerous lesions & dysplasia Genes Role of Diet in the Cancer Process – Progression •Less work in this area •Some of the same factors that function in initiation DNA Repair Genes DNA Damage Dietary factors Precancerous lesions & dysplasia Immune System Growth factors Cancer Hormones Smoking & other exposures DNA Damage Metastasis DNA Repair Genes Diet in the Cancer Process Dietary Carcinogens, heterocyclic amines, amines, PAHs Procarcinogen B-vitamins, glutathione, flavonoids Folate Deficiency Phase I metabolizing enzymes Ultimate carcinogen Isothiocyanate, selenium, other phytochemicals Phase II metabolizing enzymes Hypomethylation of P53 DNA adducts Obesity Physical Activity Protein Methionine Cholesterol Specific nutrients e.g. carotenoids, retinol Somatic alteration of oncogenes,Tumoursuppressor genes and DNA repair genes Hormones & Growth Factors Abnormal DNA & cell replication Redifferentiation Apoptosis Precancerous lesions & dysplasia Cancer Metastasis -3 fatty acids Specific Dietary Factors Associated with Breast Cancer Risk Fruits and Vegetables. Total Fat Red Meat Phytoestrogens. Fruits and Vegetables and Breast Cancer Risk Procarcinogen B-vitamins, glutathione, flavonoids Isothiocyanate, selenium, other phytochemicals Phase I metabolizing enzymes Ultimate carcinogen Phase II metabolizing enzymes DNA adducts Folate Deficiency Hypomethylation of P53 Somatic alteration Abnormal DNA & cell replication Specific nutrients e.g. carotenoids, retinol Redifferentiation Precancerous lesions & dysplasia Biologic Mechanism – Cancer Metastasis ◦ Unclear – but thought to be primarily due to antioxidants (phytoestrogens (lignans), other biochemical substance) ◦ Phytochemicals have been shown to induce detoxifying (Phase II) enzymes. ◦ May also function later in cancer process – redifferentiation (promotion) Epidemiologic Evidence: ◦ Strong correlational evidence ◦ Case-control studies – Probable ◦ Cohort studies – inconsistent Epidemiologic Evidence Recent cohort studies have cast doubt◦ Pooling project 8 cohort studies No evidence of a protective effect Meta-analysis of 15 Case-control and 10 Cohort studies. Change in Breast Cancer risk with each additional 100g intake. OR (95% CI) 1.1 1.05 1 Smith-Warner SA, Spiegelman D, Yaun SS, et al. Intake of fruits and vegetables and risk of breast cancer: a pooled analysis of cohort studies. JAMA. 2001; 285:769-776. 0.95 0.9 0.85 ◦ EPIC (8 European countries) 285,526 women, 5.4 years followup Vegetables, OR = 0.98 (95% CI, 0.84-1.14) Fruit, OR=1.09 (95% CI, 0.94-1.25) Van Gils C, Peeters PHM et al. Consumption of Vegetables and Fruits and Risk of Breast Cancer. JAMA. 2005;293:183-193 0.8 0.75 0.7 Fruits Vegetables Fruits Vegetables Riboli E, Norat T. Epidemiologic evidence of the protective effect of fruit and vegetables on cancer risk. Am J Clin Nutr 2003;78(suppl):559S–69S. Evidence for the Role of Fat in Breast Carcinogenesis Animal evidence: High Fat – High Meat 1940’s Tannenbaum: ◦ Kcal restricted = ↓mammary tumors ◦ ↑ fat diet = ↑ mammary tumors. Procarcinogen ◦ Indirectly impacts breast cancer risk through altering hormonal pathways 1997 Fay & Freedman – Metaanalyses of animal studies. ◦ Similar findings, still unclear if effect is due to fat, calories, type of fat High Fat etc… ◦ Indirect impacts of fat on – Calories Protein Meat F&V Body size Dietary Carcinogens, heterocyclic amines, amines, PAHs Ultimate carcinogen Lipid peroxidation -6 fatty acids DNA adducts Somatic alteration Obesity Protein Methionine Cholesterol Hormones & Growth Factors Abnormal DNA & cell replication Apoptosis Precancerous lesions & dysplasia Cancer Metastasis -3 fatty acids Dietary Fat and Breast Cancer Risk Epidemiologic Evidence: Since 1996 nearly 500 articles have been published on fat intake and breast cancer risk in humans. ◦ Strongest evidence of an association from correlational studies ◦ Inconsistent evidence from case-control studies ◦ No association found in cohort studies Red Meat and Breast Cancer Biologic Mechanism: ◦ Directly- May contribute procarcinogens – heterocyclic amines- through overcooking N-nitroso compounds (proteins) ◦ Indirectly – Associated with high fat and energy intake. Epidemiologic Evidence: ◦ Strong correlational evidence ◦ Case-control studies – inconsistent ◦ Cohort studies – inconsistent – pooling project found no association Soy and Breast Cancer Risk Soy products are high in phytoestrogens ◦ Competitive binding of the estrogen receptor ◦ Increase production of SHBG and thus reduce free estrogen ◦ Decrease cell proliferation and induce apoptosis Majority of evidence comes for ecologic and in vitro studies. Epidemiologic studies◦ Inconsistent findings, but few large long-term studies. ◦ Two recent case-control studies suggest assoc. with intake in adolescence ◦ Little evidence of an increased risk Why the conflicting findings? What is the important time of intake? ◦ BC and height (growth) What is the correct nutrient/ food to measure? ◦ Oils? Monounsaturated vs. Poly ◦ -3 vs. -6 ◦ All phytoestrogens v. Isoflavones v. Lignan Foods vs. Nutrients ◦ Fruits and Vegetables v. Carotenoids Randomized Trial of Breast Self Examination (BSE) Cell Proliferation Study (CPS) The Nutrition Study (1995-2000) Primary Aim: To determine if Reproductive Health Study increased risk of breast cancer is associated with high consumption of fat and red meat, and low consumption of soy, and fruits and vegetables. What can be learned from the Shanghai analysis? Potential for greater variation in total fat and soy intake. Soy exposure in Western studies Distribution of % Calories from Fat Soy exposure in proposed study China 1989* China 1993* U.S. 1993** high Cancer Incidenc e Rate 0% 4% 8% 12% 16% 20% 24% 28% 32% 36% 40% 44% 48% 52% % kcals from fat low low high Soy Foods Exposure Proposed dose response association between dietary exposures and cancer risk. McMichael A, Potter J. JNCI 1985 What can be learned from the Shanghai analysis? Variation in meat consumption (heme iron) with greater intake of organ meats. Higher consumption of particular types of vegetables (e.g leguminosae, cruciferea) than seen in Western populations. The Shanghai Nutrition Study ◦ Primary Aim: To determine if increased risk of breast cancer is associated with high consumption of fat and red meat, and low consumption of soy, and fruits and vegetables in a population of women in Shanghai, China. Nutrition Study Design Women Recruited into the Breast Self-Examination Study (1989-1991) (n= 266,064) Recruit and Interview Women with Breast Biopsies into The Cell Proliferation Study (1992-1997) Recruit and Interview Women for The Diet Study (1995-2000) Complete FFQ & blood draw Biopsy Select Controls from unaffected cohort Complete FFQ & blood draw (n=367) Benign (n=949+) Malignant (n=378/ 436) Fibroadenoma (n=327) Fibrocysitic (n=551/ 622) Select Controls from unaffected cohort Complete FFQ & blood draw (n=703/ 862) Food Frequency Questionnaire Modified from a validated NCI questionnaire used previously in Shanghai. 24- hour recall portion was added. Reviewed by colleagues in Shanghai Portion size section was dropped Added items regarding dietary change, supplement and herbal remedy use. The Food Frequency Questionnaire Dietary Assessment Interviewers were trained by J. Shannon Pilot dietary data were collected from 100 retrospective cases. Reviewed for face validity Blood specimens Pre-biopsy blood specimens were collected. Processed for assessment of antioxidants, fatty acids & DNA Stored in Shanghai Analyses Daily intake was determined using the reported frequency and average portion sizes reported on the Chinese Health and Nutrition Survey (1993). Individual food intake converted to intake per month. Groupings created based on traditional food groups and botanical groups. Analyses cont. Food group intake converted from continuous variable to categories of intake- based on control group consumption. Why group foods and create categorical variables for intake?? Analyses cont. Association between food groupings and breast cancer risk modeled using conditional logistic regression stratified by year of interview. ◦ ODDS RATIOS (OR) and 95% Confidence Interval All foods models adjusted for age and total energy, botanical models adjusted for age and total fruits and vegetables. Covariates considered for inclusion (maintained in model if change OR >10%) Only duration of breast feeding maintained. Trend OR determined entering category score as a continuous variable and using Wald test of significance. Blood analyses Isoflavones (Daidzein/ Genestein) -- liquid RBC fatty acids analyzed by GCMS @ FHCRC. Membrane Percent of individual Fatty Acids was determined. Levels of fatty acid groups (e.g. total omega-3) were calculated. Ratio groups were calculated – chromatography-coularray method (LC-coularray) and liquid chromatography-mass spectrometry (LC-MS) ◦ Omega-3:omega-6, Saturation index (Palmitic: Palmitoleic and Stearic:Oleic) Associations with Reported Dietary Intake Shannon J, Ray RM, Wu C, Nelson ZC, Gao DL, Li GD, Wei HY, Lampe JW, Horner N, Abouta JS, Patterson R, Fitzgibbons ED, Thomas DB. Food and botanical groupings and risk of breast cancer: Cancer Epidemiol Biomarker & Prev 2005;14:81-90. 2.25 Trend OR (95%CI) 2.00 1.75 1.50 1.25 1.00 0.75 0.50 0.25 Total Meat Milk Seafood Eggs Fruits Soyfood Rice Fried foods Cured foods Desserts Vegetables Trend OR and 95% CI for Each quartile Vs. next lowest quartiles of food groups Conditional Logistic regression adjusted for age, total energy and breastfeeding Summary of Questionnaire Findings A diet high in fruits and vegetables may be protective against breast cancer. ◦ The association does not appear to be due entirely to any single botanical group assessed. Egg intake may be protective against breast cancer but difficult to determine what we are actually measuring. We found no association between soy food intake and breast cancer risk in this population of high soy consumers. Odds ratios (OR) and 95% confidence intervals (CI) of fibrocystic breast conditions and breast cancer in relation to quartiles of plasma daidzein and genistein concentrations. Lampe JW, Nishino Y, Ray RM, Wu C, Li W, Lin MG, Gao DL, Hu Y, Shannon J, Stalsberg H, Porter PL, Frankenfeld CL, Wähälä K, Thomas DB.Plasma isoflavones and fibrocystic breast conditions and breast cancer among women in Shanghai, China. Cancer Epidemiol Biomarkers Prev. 2007 Dec;16(12):2579-86. N of women (%)* Control FBC Cancer FBCs vs. controls † OR 95% CI Cancer vs. controls OR† 95% CI Cancer vs. FBCs OR† 95% CI Daidzein (ng/ml) Q1 Q2 Q3 Q4 (<6.718) (6.718-18.515) (18.515-42.092) (≥ 42.092) 239 (25.0) 239 (25.0) 239 (25.0) 239 (25.0) 956 (100) 115 (41.4) 82 (29.5) 50 (18.0) 31 (11.2) 278 (100) 57 (32.4) 53 (30.1) 43 (24.4) 23 (13.1) 176 (100) p trend 1.00 0.61 0.36-1.02 0.28 0.16-0.50 0.24 0.13-0.45 1.00 0.85 0.48 0.23 < 0.0001 0.47-1.56 0.25-0.91 0.12-0.48 1.00‡ 1.40 0.52-2.48 1.62 0.50-2.59 1.07 0.30-2.62 <0.0001 0.4388 0.31-0.92 0.33-0.97 0.13-0.50 1.00 a 1.23 0.76-2.00 1.71 0.998-2.93 0.73 0.38-1.41 0.0001 0.8152 Genistein (ng/ml) Q1 Q2 Q3 Q4 (<9.418) ( 9.418-31.761) (31.761-76.954) ( ≥ 76.954) p trend 245 (25.0) 246 (25.0) 245 (25.0) 246 (25.0) 982 (100) 128 (44.0) 74 (25.4) 48 (16.5) 41 (14.1) 291 (100) 73 (38.8) 51 (27.1) 44 (23.4) 20 (10.6) 188 (100) 1.00 0.49 0.30-0.80 0.30 0.18-0.51 0.40 0.23-0.70 < 0.0001 1.00 0.54 0.57 0.26 *missing data were excluded in the analysis†adjusted for age and isoflavone analysis method and stratified by year of blood draw‡ futher adjusted for the status of proliferative changes Shannon J, King IB, Lampe JW, Gao DL, Ray RM, Lin M-G, Stalsberg H, Thomas DB. Erythrocyte fatty acids and risk of proliferative and non-proliferative fibrocystic disease in women in Shanghai, China. Am J Clin Nutr. 12/2008; e-pub, ahead of print. Odds Ratio (95% Confidence Interval) 3 2.5 =non-proliferative FCD v. control =proliferative FCD v. control =proliferative FCD v. cancer =cancer v. control 2 1.5 1 0.5 0 Total Omega-3 Fatty Acids Eicosapentaenoic Acid Docosahexaenoic Acid OR and 95% CI for Highest Vs. Lowest Quartiles of RBC Fatty Acid. Conditional logistic regression, adjusting for age, stratified by year of interview. Summary of RBC Fatty Acid Findings Normal 1. ↓ risk with total n-3 PUFA, specifically EPA 2. No association with n-3 or n-6 3. ↓ risk with ↑ total n-3 PUFA, specifically EPA 1 Fibroadenoma Non-Proliferative FCD 2 3 4. ↓ risk with total n-3 PUFA, specifically EPA, DHA, n3:n6 ratio 4 Proliferative FCD with & without Atypia DCIS Invasive Cancer OHSU Cancer Institute – pilot funding OHSU Comprehensive Breast Cancer Clinic OHSU CoInvestigators • John Vetto • Philippe Thuillier • Shannon McWeeney • Rosalie Sears OCTRI / CTRC Resources EPIC Imaging Collaborators • Amy Thurmond • Judith Richmond • Maureen Filipek Aim 1: Determine the effect of purified fish oil supplementation (75% EPA / DHA) on markers of cancer progression in women newly diagnosed with DCIS. Aim2a: Determine the effect of n-3 fatty acids on the targets identified in Aim 1 in breast cancer cells. Treatment/ Intervention: ◦ ~2 week supplementation with 2.0 gram EPA/ DHA (ROPUFA 75) or placebo. Analyses for Primary Endpoints: ◦ Pre- post changes in erythrocyte and NAF fatty acid levels ◦ Pre- post changes in gene expression using genome wide array ◦ Pre- post changes in c-myc phosphorylation and stem cell markers. Table 3.0. Schedule of Events (w-3 FA and DCIS/ADH) STUDY VISITS PreTrial Test/ Procedure Initial Biopsy (request tissue sample) Screening Eligibility (Incl./ Excl. Criteria) Informed Consent Randomization Height, weight, blood pressure Baseline/ Registration Visit Week 1 Week 2 Week 3 Week 4 Weeks 5-8 Surgery1 or PostIntervention Appt X X X X X X X X Research Specimens: Plasma, Serum, Urine, Nipple Aspirate X X Confirm eligibility: Urine HcG test X Diet & Family History Questionnaire X Questionnaire: Adverse Events X Questionnaire: Changes to Diet and Medications X X X X X X X X X X X X X X Questionnaire: Placebo/Supplement Study Supplement Dispensed Study Followup X X * Supplements to be provided only if surgery is delayed due to non-study related concerns 1 Request tissue sample if surgery is completed X* Inclusion criteria: Biopsy confirmed diagnosis of any of the following: ◦ DCIS or ADH or both ◦ DCIS with a component of invasive carcinoma ◦ ADH with a component of invasive carcinoma ◦ DCIS and ADH with a component of invasive carcinoma Age over 21 years (no upper age limit) English or Spanish speaking Female patients Exclusion criteria: Using therapeutic anticoagulation Pure invasive breast cancer on biopsy without a component of DCIS or ADH Pregnancy (as determined by urine hCG test) Male patients Patient reported allergy to fish oil or olive oil Patient reported current use of fish oil greater than 1 gram per day Any condition which, in the opinion of the study clinician, would make participation in the study harmful to the subject Recruit and randomize 40 women Challenges in Diet and Cancer Prevention Research The role of genetic variation. Incomplete knowledge of compounds in foods. Difficulty in capturing “true” dietary intake. A constantly changing food supply. Bridging the disciplines Case-control Population Studies Cohort Correlational Human Trials Randomized Clinical Trials Intervention Studies Laboratory Studies In Vitro Animal Studies What Next? Green Tea Nutrient Supplements Soy