Research Paper

Clinical & Experimental Metastasis

, Volume 27, Issue 5, pp 279-293

First online:

Dietary fat-dependent transcriptional architecture and copy number alterations associated with modifiers of mammary cancer metastasis

  • Ryan R. GordonAffiliated withDepartment of Nutrition, University of North Carolina Chapel HillDepartment of Genetics, North Carolina State University Email author 
  • , Michele La MerrillAffiliated withDepartment of Preventive Medicine, Mount Sinai School of Medicine
  • , Kent W. HunterAffiliated withLaboratory of Cancer Biology & Genetics, NIH/NCI
  • , Peter SørensenAffiliated withDepartment of Genetics and Biotechnology, Faculty of Agricultural Sciences, Aarhus University
  • , David W. ThreadgillAffiliated withDepartment of Genetics, University of North Carolina Chapel HillLineberger Comprehensive Cancer Center, University of North Carolina Chapel HillDepartment of Genetics, North Carolina State University
  • , Daniel PompAffiliated withDepartment of Nutrition, University of North Carolina Chapel HillDepartment of Genetics, University of North Carolina Chapel HillDepartment of Cell and Molecular Physiology, University of North Carolina Chapel HillLineberger Comprehensive Cancer Center, University of North Carolina Chapel Hill

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Abstract

Breast cancer is a complex disease resulting from a combination of genetic and environmental factors. Among environmental factors, body composition and intake of specific dietary components like total fat are associated with increased incidence of breast cancer and metastasis. We previously showed that mice fed a high-fat diet have shorter mammary cancer latency, increased tumor growth and more pulmonary metastases than mice fed a standard diet. Subsequent genetic analysis identified several modifiers of metastatic mammary cancer along with widespread interactions between cancer modifiers and dietary fat. To elucidate diet-dependent genetic modifiers of mammary cancer and metastasis risk, global gene expression profiles and copy number alterations from mammary cancers were measured and expression quantitative trait loci (eQTL) identified. Functional candidate genes that colocalized with previously detected metastasis modifiers were identified. Additional analyses, such as eQTL by dietary fat interaction analysis, causality and database evaluations, helped to further refine the candidate loci to produce an enriched list of genes potentially involved in the pathogenesis of metastatic mammary cancer.

Keywords

Breast cancer Causality eQTL High-fat diet Tumors