Sunflower vs Canola oil modulation of metabolic traits and tumor development in the South African rat dietary model of Breast Cancer. Dr Annadie Krygsman and Dr Anneke Brand
Background After cervical cancer, breast cancer has highest death rate in SA women Increasing under Black women Rural black South Africans are less obese and have very low incidence of breast cancer: 5-10/100 000, but urban black women: 15.1/100 000 Western Cape rural: 16/100 000 and urban: 26/100 000 Hoffman et al. (2000) S Afri Med J; MRC Kenya Report (2010) Linked to obesity epidemic and transition in macronutrient intake with urbanization Obesity leading to hormone-related cancers body fat causes estrogen in adipose stromal cells Estrogen enhances proliferation of estrogen-sensitive tissues risk of breast cancer Estrogen, via the estrogen receptor, induces expression of IGF-1 and tumor progression Martin et al. (2002) Norman et al. (2006) MRC Technical Report Chronic Diseases of Lifestyle
Dietary fat In SA distinct urban-rural in macronutrient intake Urban animal protein, fat, saturated fat, added sugar Rural plant protein and fibre Steyn et al. 2 (2006) FAO Double burden of malnutrition. Unbalanced omega-6:omega-3 ratio detrimental Healthy is <4:1, current intake >20:1 High omega-6 intake associated with metabolic diseases, incl diabetes and cancer Omega-6 can cause chronic low grade inflammatory status MRC Kenya Report (2010); De Lorgil et al (2014) BMC Med.; Yang et al. (2014) BMC Cancer. Intake of omega-3 might protect against breast and other cancers through reduction of chronic inflammatory state (dependent on dosage excess is toxic and procarcinogenic) Serini et al. (2011) Chem Res Tox, Xia et al. (2014) Cancer Immunol Immunother
Dietary carbohydrates High GI carbohydrates (CHO) linked to cancer via activation of insulin/igf-1 pathway Persistent blood glc elevation leads to IGF-1 plasma levels Downstream activation of mtor (via PI3K/Akt) induced aerobic glycolysis which benefits cancer cell proliferation Klement and Kämmerer (2011) Nutr Metab Restriction of CHO may lower insulin levels, and decrease tumorigenesis In a cell that is borderline between apoptosis and malignancy high levels of insulin and IGF1 in the microenvironment shift towards malignancy Robey and Hay (2006) Oncogene Combination of high omega-6 intake and high GI CHO creates pro-carcinogenic environment
Aims of study Reduction of omega-6 (or supplementation with omega-3 and/or carbohydrate dietary intake can attenuate tumor progression in SA-specific rat dietary model of breast cancer. Characterise metabolic parameters in the SA-representative rural/urban SD rat dietary model Investigate modulation of insulin/igf-1 in response to diets Analyze orthotopic breast cancer development in response to dietary modifications
Diet Designed by using MRC Foodfinder (PROMEC UNIT) Based on MRC Kenya Report 2012 (Steyn and Nel JH, 2012) HF: 29% calories from fat LF: 16% calories from fat SUN: Sunflower oil and hard margarine Plus/minus marine n-3 supplement equal to human intake of 1000 mg/day CAN: Canola oil and spread Macro-Composition of Nutrients and Fatty Acids in each diet. Nutrients HF-SUN LF-SUN HF-CAN LF-CAN HF-SUN-n3 LF-SUN-n3 % Energy-Prot 14 14 14 14 14 14 % Energy-CHO 57 70 57 70 57 70 % Energy-Fat 29 16 29 16 29 16 a ω-6: b ω 3 20:1 20:1 3:1 3:1 6:1 6:1 a Sum of 18:2, 20:4. b Sum of 18:3, 20:5, 22:6 18:2 LA linoleic acid 20:4 AA arachidonic acid 18:3 ALA alpha-linolenic acid 20:5 EPA eicosapentaenoic acid 22:6 DHA docosahexaenoic acid
Orthotopic mammary cancer induction LA-7 cell line: Sprague-Dawley mammary carcinoma from DMBA induced tumor Only orthotopic model of breast cancer in rat Developed from Abbasalipourkabir et al. (2010) AJB 18 million cells per animal in 200 ul Injected into mammary fat pad over 5 minutes under anaesthesia Induction from D2, measurements from D4 to D14
Experimental Design D0 diet start 7d post-weaning Reverse day/night cycle Week 12 ogtt Cancer induction D4 Tumor D8 Tumor D14 Tumor Euthanize
Glucose response and IGF-1 AUCglc mm 1600 1500 1400 1300 1200 Plasma glucose clearance (AUCglc) following 120 min ogtt * * 1100 1000 HF-SUN LF-SUN HF-CAN LF-CAN HF-SUN + n3 LF-SUN + n3 % increase 70 60 50 40 30 20 10 Percentage increase in IGF-1 from D0 baseline * * 0 HF-SUN LF-SUN HF-CAN LF-CAN HF-SUN+n3 LF-SUN+n3 Values with same superscript differ significantly P<0.05
Glucose stimulated insulin response 2500 Glucose stimulated insulin response at 12 weeks of diet 250000 200000 AUCins 150000 100000 50000 * Plasma insulin response following 120 min ogtt * 0 HF-SUN LF-SUN HF-CAN LF-CAN HF-SUN+n3 LF-SUN+n3 2000 GSIS pm 1500 1000 500 0 0 10min 30min 60min 120min HF-SUN LF-SUN HF-CAN LF-CAN HF-SUN+n3 LF-SUN-n3 Values with same superscript differ significantly P<0.05
Tumor progression Tumor volume progression Tumor volume mm2 1400 1200 1000 800 600 400 Low IGF-1 * High IGF-1 Glc intolerant Low IGF-1 Gluc intolerant * D4 D8 D14 200 0 HF-Sun LF-SUN HF-CAN LF-CAN HF-SUN+n3 LF-SUN+n3 Values with same superscript differ significantly P<0.05
Summary High omega-3 + higher CHO = glucose intolerance = tumor progression Only non-marine omega-3 (canola) + higher CHO = IGF-1 High omega-6 + higher CHO = IGF-1 = tumor regression Sunflower oil + marine omega-3 = ~ glucose intolerance = continuous tumor progression Not via insulin/igf-1 Possibly via excessive omega-3 production of oxidative metabolites with procarcinogenic activity (aldehydes), or Chronic high omega-3 intake tumor growth by immunosuppression (induction MDSC and suppression of CD8+ T cell activation) Serini et al. (2011) Chem Res Tox, Xia et al. (2014) Cancer Immunol Immunother Future: Investigations into oxidative status, and other cytokines/hormonal markers
Acknowledgements Emilene Breedt Dr Hester Burger (Promec MRC now CPUT) Natascha Danster (Promec MRC) Prof C Smith Prof MF Essop CANSA NRF
Plasma fatty acid levels PLASMA SFA MUFA PUFA n-3 n-6 n6:n3 HF-SUN 36.7 13.4 49.9 6.6 43.3 6.5:1 LF-SUN 34.9 18.8 46.3 7.6 38.7 5.1:1 HF-CAN 35.3 17.4 47.3 9.8 37.5 3.8:1 LF-CAN 30.2 32.6 37.1 7.7 29.4 3.8:1 HF-SUN+n3 33.5 23.0 43.5 7.2 36.3 5.1:1 LF-SUN+n3 34.2 20.9 44.9 7.4 37.5 5.1:1
TNF-alpha inflammatory response Plasma TNF-alpha levels at 12 weeks of diet TNF-a [pg/ml] 9 8 7 6 5 4 3 2 1 0 a b b BASELINE HF-SUN LF-SUN HF-CAN LF-CAN HF-SUN+n3 LF-SUN+n3
Insulin response AUCins 250000 200000 150000 100000 * Plasma insulin response following 120 min ogtt * 50000 0 HF-SUN LF-SUN HF-CAN LF-CAN HF-SUN+n3 LF-SUN+n3 Fasting insulin at week 12 of diet 2500 2000 Insulin pm 1500 1000 * * 500 0 HF-SUN LF-SUN HF-CAN LF-CAN HF-SUN+n3 LF-SUN+n3