Obesity and metabolic syndrome are risk and prognostic factors for breast cancer (BC) and are associated with chronic inflammation. We investigated the association between distinct BC subtypes and markers of adiposity, dysmetabolisms, and inflammation. We analyzed 1779 patients with primary invasive BC treated at a single institution, for whom anthropometric and clinical-pathological data were archived. BC subtypes were classified by immunohistochemical staining of ER, PR, HER2, and Ki67, and their relations with the study markers were assessed by multinomial logistic regression. Adjusted odds ratios (ORs) and 95 % confidence intervals (CIs) were calculated taking luminal A as reference. All subtypes more aggressive than luminal A were significantly more frequent in younger (<45 years) than older women. Before menopause, luminal B HER2-negative tumors were positively associated with large waist (OR 2.55, 95 % CI 1.53–4.24) and insulin resistance (OR 1.90, 95 % CI 1.05–3.41); luminal B HER2-positive tumors with large waist (OR 2.11, 95 % CI 1.03–4.35) and triple-negative tumors with overweight (OR 3.04, 95 % CI 1.43–6.43) and high C-reactive protein (p trend = 0.026). In postmenopausal women aged <65, luminal B HER2-negative (OR 1.94, 95 % CI 1.16–3.24) and luminal B HER2-positive tumors (OR 2.48, 95 % CI 1.16–5.27) were positively related with metabolic syndrome. Dysmetabolisms and inflammation may be related to different BC subtypes. Before menopause, triple-negative cancers were related to obesity and chronic inflammation, and aggressive luminal subtypes to abdominal adiposity. After menopause, in women aged <65 these latter subtypes were related to metabolic syndrome. Control of adiposity and dysmetabolism can reduce the risk of aggressive BC subtypes, improving the prognosis.
Breast cancer subtype Adiposity Insulin resistance Metabolic syndrome Inflammation
Body mass index
Fluorescence in situ hybridization
Human epidermal growth factor receptor 2
Homeostatic model assessment index
Infiltrating ductal carcinoma
Infiltrating lobular carcinoma
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The authors thank Judith Baggott for help with the English.
Conception and design: R. Agresti, M. Sant, E. Meneghini, F. Berrino. Acquisition of data: H. Amash, A.Turco. Analysis and interpretation of data: E. Meneghini, M. Sant, R. Agresti, P. Minicozzi, F. Berrino, E. Tagliabue. Writing, review and/or revision of the manuscript: M. Sant, R. Agresti, E. Meneghini, P. Minicozzi, F. Berrino, E. Tagliabue. Administrative, technical, or material support: P. Baili, I. Cavallo, F. Funaro. Study supervision: M. Sant, R. Agresti, F. Berrino, E. Tagliabue.
The INT breast cancer registry is subsidized by the project INT 5 × 1000-year 2012 B52I1200057001 “Implementation of breast cancer clinical registry.”
Compliance with ethical standards
Conflict of interest
The authors declare that they have no conflict of interest.
This study has been approved by the Ethical Committee of the National Cancer Institute.
Sørlie T (2004) Molecular portraits of breast cancer: tumor subtypes as distinct disease entities. Eur J Cancer 40(18):2667–2675CrossRefPubMedGoogle Scholar
Goldhirsch A, Wood WC, Coates AS, Gelber RD, Thürlimann B, Senn HJ, Panel members (2011) Strategies for subtypes—dealing with the diversity of breast cancer: highlights of the St. Gallen International Expert Consensus on the Primary Therapy of Early Breast Cancer 2011. Ann Oncol 22:1736–1747. doi:10.1093/annonc/mdr304CrossRefPubMedPubMedCentralGoogle Scholar
Minicozzi P, Bella F, Toss A, Giacomin A, Fusco M, Zarcone M et al (2013) Relative and disease-free survival for breast cancer in relation to subtype: a population-based study. J Cancer Res Clin Oncol 139(9):1569–1577. doi:10.1007/s00432-013-1478-1CrossRefPubMedGoogle Scholar
Ribelles N, Perez-Villa L, Jerez JM, Pajares B, Vicioso L, Jimenez B et al (2013) Pattern of recurrence of early breast cancer is different according to intrinsic subtype and proliferation index. Breast Cancer Res 15(5):R98CrossRefPubMedPubMedCentralGoogle Scholar
Goodwin PJ, Ennis M, Pritchard KI, Trudeau ME, Koo J, Madarnas Y et al (2002) Fasting insulin and outcome in early-stage breast cancer: results of a prospective cohort study. J Clin Oncol 20(1):42–51CrossRefPubMedGoogle Scholar
Suzuki R, Orsini N, Saji S, Key TJ, Wolk A (2009) Body weight and incidence of breast cancer defined by estrogen and progesterone receptor status—a meta-analysis. Int J Cancer 124(3):698–712. doi:10.1002/ijc.23943CrossRefPubMedGoogle Scholar
Ritte R, Lukanova A, Berrino F, Dossus L, Tjønneland A, Olsen A et al (2012) Adiposity, hormone replacement therapy use and breast cancer risk by age and hormone receptor status: a large prospective cohort study. Breast Cancer Res 14(3):R76CrossRefPubMedPubMedCentralGoogle Scholar
Fagherazzi G, Chabbert-Buffet N, Fabre A, Guillas G, Boutron-Ruault MC, Mesrine S et al (2012) Hip circumference is associated with the risk of premenopausal ER−/PR− breast cancer. Int J Obes (Lond) 36(3):431–439. doi:10.1038/ijo.2011.66CrossRefGoogle Scholar
Baili P, Torresani M, Agresti R, Rosito G, Daidone MG, Veneroni S et al (2015) A breast cancer clinical registry in an Italian comprehensive cancer center: an instrument for descriptive, clinical, and experimental research. Tumori 101(4):440–446. doi:10.5301/tj.5000341CrossRefPubMedGoogle Scholar
WHO (2005) ICDO-3: classificazione Internazionale delle Malattie per l’Oncologia-Terza Edizione. Inferenze Scarl, MilanoGoogle Scholar
Hammond ME, Hayes DF, Dowsett M, Allred DC, Hagerty KL, Badve S et al (2010) American Society of Clinical Oncology/College of American Pathologists Guideline Recommendations for Immunohistochemical Testing of Estrogen and Progesterone Receptors in Breast Cancer. J Clin Oncol 28(16):2784–2795. doi:10.1200/JCO.2009.25.6529CrossRefPubMedPubMedCentralGoogle Scholar
Alberti KGMM, Eckel RH, Grundy SM, Zimmet PZ, Cleeman JI, Donato KA et al (2009) Harmonizing the metabolic syndrome: a joint interim statement of the International Diabetes Federation Task Force on Epidemiology and Prevention; National Heart, Lung, and Blood Institute; American Heart Association; World Heart Federation; International Atherosclerosis Society; and International Association for the Study of Obesity. Circulation 120:1640–1645CrossRefPubMedGoogle Scholar
Cotterchio M, Kreiger N, Theis B, Sloan M, Bahl S (2003) Hormonal factors and the risk of breast cancer according to estrogen- and progesterone-receptor subgroup. Cancer Epidemiol Biomark Prev 12:1053–1060Google Scholar
Lahmann PH, Hoffmann K, Allen N, van Gils CH, Khaw KT, Tehard B et al (2004) Body size and breast cancer risk: findings from the European Prospective Investigation into Cancer and Nutrition (EPIC). Int J Cancer 111(5):762–771CrossRefPubMedGoogle Scholar
Muti P, Stanulla M, Micheli A, Krogh V, Freudenheim JL, Yang J et al (2000) Markers of insulin resistance and sex steroid hormone activity in relation to breast cancer risk: a prospective analysis of abdominal adiposity, sebum production, and hirsutism (Italy). Cancer Causes Control 11(8):721–730CrossRefPubMedGoogle Scholar
Chan DS, Bandera EV, Greenwood DC, Norat T (2015) Circulating C-reactive protein and breast cancer risk-systematic literature review and meta-analysis of prospective cohort studies. Cancer Epidemiol Biomark Prev 24(10):1439–1449. doi:10.1158/1055-9965.EPI-15-0324CrossRefGoogle Scholar
Han Y, Mao F, Wu Y, Fu X, Zhu X, Zhou S et al (2011) Prognostic role of C-reactive protein in breast cancer: a systematic review and meta-analysis. Int J Biol Markers 26(4):209–215. doi:10.5301/JBM.2011.8872PubMedGoogle Scholar
Siemes C, Visser LE, Coebergh JW, Splinter TA, Witteman JC, Uitterlinden AG et al (2006) C-reactive protein levels, variation in the C-reactive protein gene, and cancer risk: the Rotterdam Study. J Clin Oncol 24(33):5216–5222CrossRefPubMedGoogle Scholar