Diets Differently Regulate Tumorigenesis in Young E0771 Syngeneic Breast Cancer Mouse Model.
Hariprasad ThangavelKezia LizardoDhanya DhanyalayamSonia De AssisJyothi F NagajyothiPublished in: Journal of clinical medicine (2023)
Breast cancer (BC) is the most diagnosed cancer type, accounting for one in eight cancer diagnoses worldwide. Epidemiological studies have shown that obesity is associated with increased risk of BC in post-menopausal women, whereas adiposity reduces the risk of BC in premenopausal women. The mechanistic link between obesity and BC has been examined by combining murine BC models with high-fat diet (HFD) induced obesity. However, the effect of adiposity (not obesity) induced by a short period of HFD consumption on BC pathogenesis is not well understood. In the current study, we examined the effects of different diet compositions on BC pathogenesis using a young E0771 syngeneic BC mouse model fed on either an HFD or regular diet (RD: a low-fat high-carbohydrate diet) for a short period (4 weeks) before implanting mammary tumors in mice. We analyzed the effect of diet composition on the onset of tumor growth, metastasis, and metabolic and immune status in the tumor microenvironment (TME) using various methods including in vivo bioluminescence imaging and immunoblotting analyses. We showed for the first time that a short-term HFD delays the onset of tumorigenesis by altering the immune and metabolic signaling and energy mechanism in the TME. However, RD may increase the risk of tumorigenesis and metastasis by increasing pro-inflammatory factors in the TME in young mice. Our data suggest that diet composition, adipogenesis, and loss of body fat likely regulate the pathogenesis of BC in a manner that differs between young and post-menopausal subjects.
Keyphrases
- high fat diet
- insulin resistance
- weight loss
- high fat diet induced
- polycystic ovary syndrome
- adipose tissue
- metabolic syndrome
- mouse model
- physical activity
- skeletal muscle
- weight gain
- type diabetes
- middle aged
- breast cancer risk
- squamous cell
- postmenopausal women
- papillary thyroid
- machine learning
- high glucose
- artificial intelligence
- electronic health record
- body mass index
- gestational age
- deep learning
- childhood cancer
- endothelial cells
- big data
- case control