Abstract

The incidence of breast cancer in Japanese women has doubled in all age groups over the past two decades. We have recently shown that this marked increase is mostly due to an increase in the estrogen receptor (ER)-positive subtype. It is necessary to establish risk factors capable of predicting the risk of ER-positive breast cancer that will enable the efficient selection of candidates for preventive therapy. We analyzed genetic factors, including 14 single nucleotide polymorphisms (SNPs), environmental risk factors (body mass index, age at menarche, pregnancy, age at first birth, breastfeeding, family history of breast cancer, age at menopause, use of hormone replacement therapy, alcohol intake, and smoking), serum hormones and growth factors (estradiol, testosterone, prolactin, insulin-like growth factor 1 [IGF1] and IGF binding protein 3 [IGFBP3]), and mammographic density in 913 women with breast cancer and 278 disease-free controls. To identify important risk factors, risk prediction models for ER-positive breast cancer in both pre- and postmenopausal women were created by logistic regression analysis. In premenopausal women, one SNP (CYP19A1-rs10046), age, pregnancy, breastfeeding, alcohol intake, serum levels of prolactin, testosterone, and IGFBP3 were considered to be risk predictors. In postmenopausal women, one SNP (TP53-rs1042522), age, body mass index, age at menopause, serum levels of testosterone, and IGF1 were identified as risk predictors. Risk factors may differ between women of different menopausal status, and inclusion of common genetic variants and serum hormone measurements as well as environmental factors might improve risk assessment models. Further validation studies will clarify appropriate risk groups for preventive therapy.

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