MRI reveals increased tumorigenesis following high fat feeding in a mouse model of triple-negative breast cancer

磁共振成像显示,在三阴性乳腺癌小鼠模型中,高脂饮食会增加肿瘤发生率。

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Abstract

High animal fat consumption is associated with an increase in triple-negative breast cancer (TNBC) risk. Based on previous MRI studies demonstrating the feasibility of detecting very early non-palpable mammary cancers in simian virus 40 large T antigen (SV40TAg) mice, we examined the effect of dietary fat fed from weaning to young adulthood in this model of TNBC. Virgin female C3(1)SV40TAg mice (n = 16) were weaned at 3-4 weeks of age and then fed either a low fat diet (LFD) (n = 8, 3.7 kcal/g; 17.2% kcal from vegetable oil) or a high animal fat diet (HAFD) (n = 8, 5.3 kcal/g; 60% kcal from lard). After 8 weeks on the diet (12 weeks of age), fast spin echo MR images of inguinal mammary glands were acquired at 9.4 T. Following in vivo MRI, mice were sacrificed and inguinal mammary glands were excised and formalin fixed for ex vivo MRI. 3D volume-rendered MR images were then correlated with mammary gland histology to assess the glandular parenchyma and tumor burden. Using in vivo MRI, an average of 3.88 ± 1.03 tumors were detected per HAFD-fed mouse compared with an average of 1.25 ± 1.16 per LFD-fed mouse (p < 0.007). Additionally, the average tumor volume was significantly higher following HAFD feeding (0.53 ± 0.45 mm(3) ) compared with LFD feeding (0.20 ± 0.08 mm(3) , p < 0.02). Analysis of ex vivo MR and histology images demonstrated that HAFD mouse mammary glands had denser parenchyma, irregular and enlarged ducts, dilated blood vessels, increased white adipose tissue, and increased tumor invasion. MRI and histological studies of the SV40TAg mice demonstrated that HAFD feeding also resulted in higher cancer incidence and larger mammary tumors. Unlike other imaging methods for assessing environmental effects on mammary cancer growth, MRI allows routine serial measurements and reliable detection of small cancers as well as accurate tumor volume measurements and assessment of the three-dimensional distribution of tumors over time.

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