Dietary Fat Intake and Development of Specific Breast Cancer Subtypes

Abstract

We prospectively evaluated fat intake as predictor of developing breast cancer (BC) subtypes defined by estrogen receptor (ER), progesterone receptor (PR), and human epidermal growth factor 2 receptor (HER2), in a large (n = 337327) heterogeneous cohort of women, with 10062 BC case patients after 11.5 years, estimating BC hazard ratios (HRs) by Cox proportional hazard modeling. High total and saturated fat were associated with greater risk of ER⁺PR⁺ disease (HR = 1.20, 95% confidence interval [CI] = 1.00 to 1.45; HR = 1.28, 95% CI = 1.09 to 1.52; highest vs lowest quintiles) but not ER⁻PR⁻ disease. High saturated fat was statistically significantly associated with greater risk of HER2⁻ disease. High saturated fat intake particularly increases risk of receptor-positive disease, suggesting saturated fat involvement in the etiology of this BC subtype.

The hypothesis that high fat intake increases breast cancer (BC) risk dates back to the 1970s (1), but has been persistently controversial. An extensive 2007 review (2) concluded that evidence from prospective epidemiological studies was inconsistent, whereas case–control studies indicate a statistically significant positive association between fat intake and BC. Our recent EPIC study (European Investigation into Cancer and Nutrition) found weak but statistically significant positive associations of saturated fat intake with BC risk (3). The conflicting results of earlier studies are likely because of difficulties in obtaining precise estimates of fat intake and also because of limited heterogeneity of intake within geographically confined populations (4).

BC is now classified into subtypes determined clinically by the expression of receptors for estrogen (ER), progesterone (PR) and human epidermal growth factor 2 (HER2) (5,6); the subtypes differ in prognoses and factors influencing their occurrence (5), which may have confounded associations between fat intake and BC. The association of fat intake with risk of BC subtypes has been little studied and with conflicting results (7–11).

To further investigate the effect of dietary fat on BC, we expanded the follow-up of our EPIC study (3), prospectively evaluating associations of dietary fat with BC subtypes defined by ER, PR, and HER2 status. EPIC is a prospective cohort study conducted in 10 European countries (12) that recruited volunteers after informed consent and completion of dietary and lifestyle questionnaires. The study was approved by the ethical committees of the International Agency for Research on Cancer and participating centers.

This EPIC study was conducted on 337327 women and used multivariable Cox proportional hazard modeling to estimate hazard ratios (HRs) with 95% confidence intervals (CIs) for developing BC in relation to fat intake (as quintiles and continuous variables), with stratification by center and age. Nonalcohol energy, energy from alcohol, smoking, education, age at menarche, full-term pregnancy, hormone therapy use, and body mass index/menopausal status interaction, were covariables.

The proportional hazards assumption for each fat and fat subtype in relation to BC risk was tested using the Grambsch and Therneau method (13). In all cases, the proportional hazards assumption was satisfied. The form of the predictor in the Cox regression is linear and was tested by means of a restricted cubic spline with five knots (14).

To correct the dietary questionnaires for measurement errors, intake data were calibrated against highly standardized 24-hour dietary recall interviews on a random sample (8.0%) of the cohort (15,16) (see Supplementary Methods, available online, for more details). All tests of statistical significance were two-sided, and a P value less than or equal to .05 was considered statistically significant.

After a mean of 11.5 years (359814 person-years) 10062 incident case patients were identified. ER, PR, and HER2 status, obtained from pathology reports, were available for 70.6%, 59.0%, and 22.9% of case patients, respectively.

Women in the highest quintile of saturated fat intake had a statistically significantly greater risk of BC than those in the lowest quintile. Increases in total and monounsaturated fat intake (continuous variables) were also associated with greater BC risk (Supplementary Table 1, available online). The association between fat intake and BC did not vary with menopausal status at baseline or at diagnosis (data not shown).

High total fat intake was positively associated with development of ER⁺PR⁺ disease (HR = 1.20; 95% CI = 1.0 to 1.45, highest vs lowest quintile), but not ER⁻PR⁻ disease, with statistically significant (P = .05) heterogeneity between ER⁺PR⁺ and ER⁻PR⁻ cancers (Table 1).

Table 1.

Multivariable-adjusted hazard ratios with 95% confidence intervals for developing breast cancer subtypes defined by hormone receptor status, according to quintiles of fat intake (n = 5601 case patients)*

Fat type	Case patients/ person-years	HR (95% CI)†	Case patients/ person-years	HR (95% CI)†	Case patients/ person-years	HR (95% CI)†	Case patients/ person-years	HR (95% CI)†
		ER+PR+		ER+PR−		ER−PR−		ER PR unknown
Total fat, g/d
1 (43.2)	644/646061	1.00 (referent)	185/646061	1.00 (referent)	196/646061	1.00 (referent)	632/646061	1.00 (referent)
2 (59.8)	694/646187	1.05 (0.94 to 1.18)	205/646187	1.07 (0.87 to 1.33)	200/646187	0.96 (0.78 to 1.18)	646/646187	1.01 (0.90 to 1.14)
3 (72.6)	689/646722	1.03 (0.91 to 1.17)	208/646722	1.04 (0.83 to 1.32)	196/646722	0.89 (0.71 to 1.12)	666/646722	1.09 (0.96 to 1.24)
4 (87.4)	703/649001	1.03 (0.90 to 1.19)	244/649001	1.19 (0.92 to 1.55)	204/649001	0.84 (0.64 to 1.09)	644/649001	1.12 (0.96 to 1.30)
5 (117.3)	810/644992	1.20 (1.00 to 1.45)	230/644992	1.11 (0.79 to 1.56)	222/644992	0.79 (0.56 to 1.11)	567/644992	1.15 (0.94 to 1.40)
Ptrend‡		.21		.35		.13		.09
Intake as continuous variable§		1.03 (0.99 to 1.07)		1.05 (0.98 to 1.12)		0.96 (0.90 to 1.03)		1.03 (0.99 to 1.07)
Pheterogeneity||			.71		.05
Calibrated data#		1.10 (1.01 to 1.20)		1.18 (1.01 to 1.39)		0.87 (0.74 to 1.02)		1.07 (0.98 to 1.17)
Saturated fat, g/d
1 (15.4)	584/644252	1.00 (referent)	175/644252	1.00 (referent)	166/644252	1.00 (referent)	614/644252	1.00 (referent)
2 (22.2)	683/645600	1.10 (0.98 to 1.24)	179/645600	0.99 (0.80 to 1.23)	193/645600	1.04 (0.84 to 1.30)	616/645600	0.98 (0.87 to 1.10)
3 (27.6)	674/648063	1.07 (0.95 to 1.21)	232/648063	1.26 (1.01 to 1.57)	230/648063	1.17 (0.93 to 1.46)	644/648063	1.01 (0.89 to 1.15)
4 (33.9)	734/648537	1.15 (1.01 to 1.32)	219/648537	1.16 (0.91 to 1.48)	183/648537	0.86 (0.67 to 1.11)	678/648537	1.09 (0.95 to 1.25)
5 (47.5)	865/646512	1.28 (1.09 to 1.52)	267/646512	1.31 (0.97 to 1.77)	246/646512	0.96 (0.70 to 1.31)	603/646512	1.07 (0.90 to 1.27)
Ptrend‡		.009		.05		.39		.19
Intake as continuous variable§		1.03 (1.01 to 1.06)		1.06 (1.01 to 1.11)		0.99 (0.94 to 1.04)		1.02 (0.99 to 1.05)
Pheterogeneity||			.44		.08
Calibrated data#		1.09 (1.03 to 1.16)		1.16 (1.04 to 1.29)		0.96 (0.86 to 1.06)		1.03 (0.97 to 1.09)
Monounsaturated fat, g/d
1 (14.2)	655/645501	1.00 (referent)	181/645500	1.00 (referent)	187/645501	1.00 (referent)	669/645501	1.00 (referent)
2 (20.2)	646/644536	0.94 (0.84 to 1.06)	202/644536	1.07 (0.87 to 1.33)	209/644536	1.04 (0.85 to 1.29)	652/644536	0.98 (0.86 to 1.08)
3 (25.2)	737/645323	1.04 (0.92 to 1.17)	230/645323	1.14 (0.91 to 1.44)	209/645323	0.97 (0.76 to 1.21)	682/645323	1.06 (0.94 to 1.21)
4 (31.6)	783/649092	1.06 (0.92 to 1.22)	244/649092	1.14 (0.88 to 1.48)	207/649092	0.89 (0.69 to 1.16)	668/649092	1.17 (1.01 to 1.35)
5 (46.4)	719/648512	1.09 (0.91 to 1.30)	215/648512	1.16 (0.83 to 1.61)	206/648512	0.95 (0.68 to 1.34)	484/648512	1.06 (0.87 to 1.30)
Ptrend‡		.17		.34		.44		.07
Intake as continuous variable§		1.02 (0.99 to 1.06)		1.04 (0.98 to 1.10)		0.97 (0.92 to 1.03)		1.03 (0.99 to 1.06)
Pheterogeneity||			.77		.06
Calibrated data#		1.08 (1.01 to 1.17)		1.14 (1.00 to 1.30)		0.92 (0.81 to 1.05)		1.07 (1.00 to 1.15)
Polyunsaturated fat, g/d
1 (6.6)	714/655117	1.00 (referent)	230/655117	1.00 (referent)	230/655117	1.00 (referent)	588/655117	1.00 (referent)
2 (9.3)	729/646944	1.01 (0.90 to 1.12)	218/646944	1.00 (0.82 to 1.21)	171/646944	0.80 (0.65 to 0.98)	638/646944	1.01 (0.89 to 1.13)
3 (11.6)	704/643652	0.96 (0.85 to 1.08)	198/643652	0.90 (0.73 to 1.12)	188/643652	0.87 (0.70 to 1.08)	672/643652	1.04 (0.92 to 1.18)
4 (14.6)	669/643236	0.89 (0.78 to 1.01)	223/643236	0.98 (0.78 to 1.22)	225/643236	1.01 (0.80 to 1.27)	642/643236	1.02 (0.89 to 1.16)
5 (21.6)	724/644016	0.98 (0.85 to 1.13)	203/644016	0.90 (0.69 to 1.16)	204/644016	0.91 (0.70 to 1.19)	615/644016	1.03 (0.89 to 1.20)
Ptrend‡		.28		.45		.77		.68
Intake as continuous variable§		0.98 (0.96 to 1.00)		0.97 (0.93 to 1.00)		0.98 (0.94 to 1.02)		1.00 (0.98 to 1.03)
Pheterogeneity||			.79	0.92 (0.83 to 1.01)	.49
Calibrated data#		0.96 (0.91 to 1.01)				0.96 (0.87 to 1.05)		1.02 (0.97 to 1.07)

* CI = confidence interval; ER=estrogen receptor; HR = hazard ratio; PR=progesterone receptor.

† Stratified by center and age and adjusted for nonalcohol energy, educational attainment, smoking status, body mass index/menopausal status interaction, energy from alcohol, full-term pregnancy, and hormone replacement therapy use.

‡ Tests of linear trend were performed by modeling the variable whose value was the number of the quintile to which the subject belonged. All statistical tests were two-sided.

§ Log_{1. 2} transformed (so hazard ratios represent the risk associated with a 20% increase in fat intake).

|| ER⁺PR⁺ vs ER⁺PR⁻, ER⁺PR⁺ vs ER⁻PR⁻. Test for heterogeneity.

# Calibrated data were obtained by linear regression models that compared observed nutrient questionnaire measurements with 24-hour dietary recall.

Women with the highest quintile of saturated fat consumption had a statistically significantly greater risk of ER⁺PR⁺ BC than those in the lowest quintile (HR = 1.28; 95% CI = 1.09 to 1.52), with a statistically significant trend (P = .009). Increasing saturated fat intake (continuous variable) was also associated with greater risk of ER⁺PR⁻ BC. Heterogeneity tests were not statistically significant for saturated fat. No association of any fat type with ER⁻PR⁻ disease was found. Risk estimates for ER⁺, ER⁻, PR⁺, and PR⁻ BC are presented separately in Supplementary Table 2 (available online).

Table 2.

Multivariable-adjusted hazard ratios with 95% confidence intervals for developing breast cancer subtypes defined by HER2 status, according to quintiles of fat intake (n = 2259 case patients)*

	Case patients/ person-years	HR (95% CI)†	Case patients/ person-years	HR (95% CI)†	Case patients/ person-years	HR (95% CI)†
Fat type		HER2 positive		HER2 negative		HER2 unknown
Total fat, g/d
1 (44.5)	116/576095	1.00 (referent)	343/576095	1.00 (referent)	961/576096	1.00 (referent)
2 (61.7)	109/571176	1.01 (0.76 to 1.34)	357/571176	1.11 (0.94 to 1.30)	1049/571176	1.03 (0.94 to 1.12)
3 (74.6)	96/567416	0.93 (0.68 to 1.29)	352/567416	1.15 (0.96 to 1.38)	1173/567416	1.03 (0.94 to 1.14)
4 (89.5)	94/566802	0.94 (0.65 to 1.37)	330/566803	1.13 (0.92 to 1.40)	1214/566803	1.05 (0.94 to 1.17)
5 (119.6)	124/559834	1.34 (0.84 to 2.14)	338/559835	1.28 (0.98 to 1.68)	1359/559835	1.06 (0.92 to 1.22)
Ptrend‡		.59		.14		0.42
Intake as continuous variable§		0.99 (0.91 to 1.09)		1.05 (1.00 to 1.11)		1.02 (0.99 to 1.05)
Pheterogeneity||			.30		.94
Calibrated data#		1.09(0.87 to 1.36)		1.13(1.00 to 1.28)		1.03(0.97 to 1.10)
Saturated fat, g/d
1 (15.7)	111/571950	1.00 (referent)	298/571950	1.00 (referent)	1110/571950	1.00 (referent)
2 (22.9)	105/570260	0.90 (0.68 to 1.19)	370/570260	1.19 (1.01 to 1.39)	1201/570260	1.01 (0.92 to 1.10)
3 (28.3)	115/569843	1.01 (0.75 to 1.37)	359/569843	1.20 (1.01 to 1.43)	1265/569843	1.08 (0.98 to 1.19)
4 (34.8)	101/567160	0.91 (0.64 to 1.28)	359/567160	1.27 (1.04 to 1.54)	1261/567160	1.07 (0.97 to 1.19)
5 (48.6)	107/562112	0.95 (0.62 to 1.46)	334/562112	1.29 (1.01 to 1.64)	919/562112	1.14 (1.01 to 1.30)
Ptrend‡		.86		.04		.03
Intake as continuous variable§		0.98 (0.92 to 1.05)		1.04 (1.00 to 1.09)		1.03 (1.01 to 1.05)
Pheterogeneity||			.14		.53
Calibrated data#		1.00(0.86 to 1.15)		1.11(1.03 to 1.21)		1.05(1.00 to 1.09)
Monounsaturated fat, g/d
1 (14.7)	99/577228	1.00 (referent)	325/577228	1.00 (referent)	1040/577228	1.00 (referent)
2 (21.0)	101/571405	1.02 (0.76 to 1.37)	322/571405	1.02 (0.87 to 1.20)	1101/571405	1.00 (0.92 to 1.09)
3 (26.1)	101/567034	1.01 (0.73 to 1.40)	344/567034	1.11 (0.93 to 1.33)	1239/567034	1.04 (0.94 to 1.14)
4 (32.6)	108/565210	0.99 (0.69 to 1.43)	368/565210	1.15 (0.94 to 1.41)	1179/565210	1.07 (0.96 to 1.19)
5 (47.4)	130/560448	1.11 (0.70 to 1.76)	361/560448	1.07 (0.82 to 1.40)	1197/560448	0.98 (0.85 to 1.13)
Ptrend‡		.80		.28		.54
Intake as continuous variable§		1.02 (0.94 to 1.10)		1.05 (1.01 to 1.09)		1.01 (0.99 to 1.04)
Pheterogeneity||			.52		.42
Calibrated data#		1.15(0.96 to 1.38)		1.13(1.02 to 1.25)		1.01(0.96 to 1.07)
Polyunsaturated fat, g/d
1 (6.6)	133/579794	1.00 (referent)	428/579794	1.00 (referent)	1040/579794	1.00 (referent)
2 (9.5)	112/569599	1.01 (0.77 to 1.32)	392/569599	1.02 (0.88 to 1.18)	1101/569599	0.96(0.88 to 1.05)
3 (11.9)	101/566179	1.02 (0.76 to 1.38)	307/566179	0.90 (0.76 to 1.06)	1239/566179	1.01 (0.92 to 1.11)
4 (15.0)	106/563959	1.22 (0.88 to 1.68)	322/563959	1.04 (0.86 to 1.24)	1179/563959	0.91 (0.83 to 1.04)
5 (22.1)	87/561794	1.12 (0.77 to 1.62)	271/561794	1.00 (0.81 to 1.23)	1197/561794	0.93 (0.84 to 1.04)
Ptrend‡		.33		.98		.13
Intake as continuous variable§		1.01 (0.95 to 1.06)		0.98 (0.95 to 1.01)		0.99 (0.97 to 1.01)
Pheterogeneity||			.45		.73
Calibrated data#		1.01 (0.88 to 1.16)		0.95 (0.88 to 1.02)		0.98 (0.94 to 1.02)

* CI = confidence interval; HER2 = human epidermal growth factor 2 receptor; HR = hazard ratio.

† Stratified by center and age and adjusted for nonalcohol energy, educational attainment, smoking status, body mass index/menopausal status interaction, energy from alcohol, full-term pregnancy, and hormone replacement therapy use.

‡ Tests of linear trend were performed by modeling the variable whose value was the number of the quintile to which the subject belonged.

§ Log_{1. 2} transformed (so hazard ratios represent the risk associated with a 20% increase in fat intake).

|| HER2-positive vs HER2-negative and HER2-positive vs HER2-unknown. Two-sided test for heterogeneity.

# Calibrated data were obtained by linear regression models that compared observed nutrient questionnaire measurements with 24-hour dietary recall.

No association of any fat with HER2⁺ BC was found (Table 2). For saturated fat, all intake quintiles were associated with a statistically significantly greater risk of HER2⁻ BC than reference (HR = 1.29; 95% CI = 1.01 to 1.64, highest vs lowest), with a statistically significant trend (P = .04). Increase in monounsaturated fat intake (continuous variable) was also associated with greater risk of HER2⁻ disease. Furthermore, heterogeneity tests comparing HER2⁺ with HER2⁻ cancer were always non-statistically significant.

The results of this study support our original finding (3) that high saturated fat intake is statistically significantly associated with increased BC risk but indicate that excess dietary fat is more strongly associated with hormone-sensitive than receptor-negative disease. Similar findings have been reported previously (7,9,17), although other studies on postmenopausal women (10,11) found no evidence that the association between dietary fat and BC varied with ER or PR status.

High lifetime exposure to estrogen (early menarche, late menopause, postmenopausal hormone therapy, and postmenopausal adiposity) is more strongly associated with ER⁺PR⁺ than ER⁻PR⁻ BC (5), whereas high endogenous sex hormone levels have also been related to the development of receptor-positive BC (18–22). It is unclear whether high dietary fat increases sex hormone levels, but this is one mechanism by which fat could increase susceptibility to receptor-positive BC (23).

Fat intake and BC HER2 status appear not to have been investigated previously. We found positive associations between high saturated and monounsaturated fat intake and HER⁻ BC but no relation to HER2⁺ disease. HER2⁺ BC is aggressive and seems little influenced by hormone-related risk factors (24). Furthermore, our finding of no association between any type of fat intake and HER2⁺ disease is consistent with the fact that HER2⁺ cancers typically do not express ER or PR and do not respond to tamoxifen (25,26). Evidence suggests that factors influencing hormonal status (eg, parity, age at menarche, age at menopause) only influence the risk of developing HER2⁻ disease (24,26).

Our study strengths are prospective design, large proportion of case patients with receptor information, and wide variation in fat intake. The main source of hormone receptor data was medical records. Although receptor status was usually determined immunohistochemically, methods used varied across laboratories, resulting in some misclassification. Another concern is that women with hormone receptor information may differ from those without this information. However findings for subgroups without ER, PR, or HER2 information were similar to these with this information, suggesting no selection bias related to receptor status information.

All dietary assessment methods involve measurement error. Although the dietary questionnaires used in the various centers were similar, they differed in detail because each was designed to capture local eating habits. To compensate for errors generated by differences in dietary assessment, we corrected (calibrated) dietary data, using data predicted by 24-hour dietary recall.

To conclude, the results of this prospective study on a large heterogeneous population of European women indicate that a high-fat diet increases BC risk and, most conspicuously, that high saturated fat intake increases risk of receptor-positive disease, suggesting saturated fat involvement in the etiology of receptor-positive BC.

Funding

EPIC is supported by the European Commission (DG-SANCO) and the International Agency for Research on Cancer. National cohorts are supported by Danish Cancer Society (Denmark); Ligue Contre le Cancer, Institut Gustave Roussy, Mutuelle Générale de l’Education Nationale, and Institut National de la Santé et de la Recherche Médicale (France); Deutsche Krebshilfe, Deutsches Krebsforschungszentrum and Federal Ministry of Education and Research (Germany); Hellenic Health Foundation (Greece); Italian Association for Research on Cancer, National Research Council, and Associazione Iblea per la Ricerca Epidemiologica (AIRE-ONLUS) Ragusa, Associazione Volontari Italiani Sangu Ragusa, Sicilian Government (Italy); Dutch Ministry of Public Health, Welfare and Sports, Netherlands Cancer Registry, LK Research Funds, Dutch Prevention Funds, Dutch ZON (Zorg Onderzoek Nederland), World Cancer Research Fund, and Statistics Netherlands (the Netherlands); European Research Council (grant No. ERC-2009-AdG 232997) and Nordforsk, and Nordic Center of Excellence Programme on Food, Nutrition and Health (Norway); Health Research Fund, Regional Governments of Andalucía, Asturias, Basque Country, Murcia (No. 6236) and Navarra, the Centro de Investigación Biomédica en Red en Epidemiología y Salud Pública and Instituto de Salud Carlos II (RD06/0020) the Regional Government the Spanish Ministry of Health (FIS) and CIBERESP, San Sebastian (Spain); the Spanish Ministry of Health (ISCIII RETICC RD06/0020/0091) and the Catalan Institute of Oncology; Swedish Cancer Society, Swedish Scientific Council, and Regional Government of Skåne and Västerbotten (Sweden); Cancer Research UK, Medical Research Council, Stroke Association, British Heart Foundation, Department of Health, Food Standards Agency, and Wellcome Trust (UK).

The study sponsors had no role in the design of the study; the collection, analysis, and interpretation of the data; the writing of the manuscript; and the decision to submit the manuscript for publication.