Peripubertal high-fat diet promotes c-Myc stabilization in mammary gland epithelium.
Nilakshi KulathungaSusumu KohnoPaing LinnYuuki NishimotoShin-Ichi HorikeMikhail I ZaraiskiiSharad KumarHayato MuranakaChiaki TakahashiPublished in: Cancer science (2020)
Dietary fat consumption during accelerated stages of mammary gland development, such as peripubertal maturation or pregnancy, is known to increase the risk for breast cancer. However, the underlying molecular mechanisms are not fully understood. Here we examined the gene expression profile of mouse mammary epithelial cells (MMECs) on exposure to a high-fat diet (HFD) or control diet (CD). Trp53-/- female mice were fed with the experimental diets for 5 weeks during the peripubertal period (3-8 weeks of age). The treatment showed no significant difference in body weight between the HFD-fed mice and CD-fed mice. However, gene set enrichment analysis predicted a significant enrichment of c-Myc target genes in animals fed HFD. Furthermore, we detected enhanced activity and stabilization of c-Myc protein in MMECs exposed to a HFD. This was accompanied by augmented c-Myc phosphorylation at S62 with a concomitant increase in ERK phosphorylation. Moreover, MMECs derived from HFD-fed Trp53-/- mouse showed increased colony- and sphere-forming potential that was dependent on c-Myc. Further, oleic acid, a major fatty acid constituent of the HFD, and TAK-875, an agonist to G protein-coupled receptor 40 (a receptor for oleic acid), enhanced c-Myc stabilization and MMEC proliferation. Overall, our data indicate that HFD influences MMECs by stabilizing an oncoprotein, pointing to a novel mechanism underlying dietary fat-mediated mammary carcinogenesis.
Keyphrases
- high fat diet
- adipose tissue
- insulin resistance
- high fat diet induced
- body weight
- fatty acid
- genome wide
- signaling pathway
- type diabetes
- weight loss
- genome wide identification
- metabolic syndrome
- copy number
- cell proliferation
- machine learning
- wild type
- transcription factor
- dna methylation
- genome wide analysis
- climate change
- data analysis