Dietary fat alters pulmonary metastasis of mammary cancers through cancer autonomous and non-autonomous changes in gene expression

Abstract

Metastasis virulence, a significant contributor to breast cancer prognosis, is influenced by environmental factors like diet. We previously demonstrated in an F2 mouse population generated from a cross between the M16i polygenic obese and MMTV-PyMT mammary cancer models that high fat diet (HFD) decreases mammary cancer latency and increases pulmonary metastases compared to a matched control diet (MCD). Genetic analysis detected eight modifier loci for pulmonary metastasis, and diet significantly interacted with all eight loci. Here, gene expression microarray analysis was performed on mammary cancers from these mice. Despite the substantial dietary impact on metastasis and its interaction with metastasis modifiers, HFD significantly altered the expression of only five genes in mammary tumors; four of which, including serum amyloid A (Saa), are downstream of the tumor suppressor PTEN. Conversely, HFD altered the expression of 211 hepatic genes in a set of tumor free F2 control mice. Independent of diet, pulmonary metastasis virulence correlates with mammary tumor expression of genes involved in endocrine cancers, inflammation, angiogenesis, and invasion. The most significant virulence-associated network harbored genes also found in human adipose or mammary tissue, and contained upregulated Vegfa as a central node. Additionally, expression of Btn1a1, a gene physically located near a putative cis-acting eQTL on chromosome 13 and one of the metastasis modifiers, correlates with metastasis virulence. These data support the existence of diet-dependent and independent cancer modifier networks underlying differential susceptibility to mammary cancer metastasis and suggest that diet influences cancer metastasis virulence through tumor autonomous and non-autonomous mechanisms.

Fig. 1

Top network depicting the influence of high fat diet on mammary tumor gene expression (Ingenuity Pathway Analysis Knowledge Base). One axillary mammary tumor per mouse was used for microarray analyses (n = 64 and 67 microarrays of mammary tumor RNA from mice fed HFD and MCD, respectively). Gene networks depict the direct physical (solid) or indirect (dashed) interactions of molecules and genes’ products, including those genes not identified as significant on the microarrays, thus networks are ranked such that the highest ranked network contains the highest number of significantly expressed genes. Red nodes denote significant upregulation comparing high fat diet-relative to matched control diet-fed mice (Q = 0)

Fig. 2

Top network of metastasis virulence biomarkers (Ingenuity Pathway Analysis Knowledge Base). The gene expression data from individual mammary tumor samples were ordered such that 25% (33 samples) of the total samples came from mice with no surface- or section-metastatic lesions and the longest tumor onset. Gene expression data from these 33 samples served as the reference group when paired with the gene expression data of 33 mammary tumor samples from mice that had the most sectional metastatic lesions detected (AMD66), and when paired with the gene expression data of 33 mammary tumor samples from mice that had the most superficial metastatic lesions detected (MET66). The differential expression of genes common to both the AMD66 and MET66 analyses was further restricted to genes expressed in human adipose or breast to define the set of metastasis virulence biomarkers. Gene networks depict the direct physical (solid) or indirect (dashed) interactions of molecules and genes’ products, including those genes not identified as significant on the microarrays, thus networks are ranked such that the highest ranked network contains the highest number of significantly expressed genes. Red nodes denote significant upregulation in high virulent mammary tumors relative to non-virulent mammary tumors (Q < 0.05). Green nodes denote significant downregulation in high virulent mammary tumors relative to non-virulent mammary tumors (Q < 0.05)

Fig. 3

Btn1a1-gene expression network and quantitative trait locus in metastatic mammary cancer. a Btn1a1, significantly downregulated by metastasis, and binding partner Xdh are regulated in a feedback loop with butyric acid, implicated in high fat diet effects on mammary tumors (Fig. 1) through IL1B, also downregulated by metastasis (P < 0.05). Gene networks depict the direct physical (solid) or indirect (dashed) interactions of molecules and genes’ products, including those genes not identified as significant on the microarrays, thus networks are ranked such that the highest ranked network contains the highest number of significantly expressed genes. Green nodes denote significant downregulation in high virulent mammary tumors relative to non-virulent mammary tumors (Q < 0.05). b Btn1a1 lies within the 95% confidence interval of a QTL (LOD = 3.09) associated with the trait average pulmonary metastatic density only among mice fed high fat diet (11). Variation in mammary tumor Btn1a1 expression (n = 131 mice) was partially explained by a significant expression quantitative trait locus (n = 148 mice) also within the 95% confidence interval of the quantitative trait locus that describes the average pulmonary metastatic density × high fat diet interaction and near the physical location of the Btn1a1 gene