Impact of tumor microenvironment and epithelial phenotypes on metabolism in breast cancer

Abstract

Purpose: Cancer cells have altered metabolism, with increased glucose uptake, glycolysis, and biomass production. This study conducted genomic and metabolomic analyses to elucidate how tumor and stromal genomic characteristics influence tumor metabolism.

Experimental design: Thirty-three breast tumors and six normal breast tissues were analyzed by gene expression microarray and by mass spectrometry for metabolites. Gene expression data and clinical characteristics were evaluated in association with metabolic phenotype. To evaluate the role of stromal interactions in altered metabolism, cocultures were conducted using breast cancer cells and primary cancer-associated fibroblasts (CAF).

Results: Across all metabolites, unsupervised clustering resulted in two main sample clusters. Normal breast tissue and a subset of tumors with less aggressive clinical characteristics had lower levels of nucleic and amino acids and glycolysis byproducts, whereas more aggressive tumors had higher levels of these Warburg-associated metabolites. While tumor-intrinsic subtype did not predict metabolic phenotype, metabolic cluster was significantly associated with expression of a wound response signature. In cocultures, CAFs from basal-like breast cancers increased glucose uptake and basal-like epithelial cells increased glucose oxidation and glycogen synthesis, suggesting interplay of stromal and epithelial phenotypes on metabolism. Cytokine arrays identified hepatocyte growth factor (HGF) as a potential mediator of stromal-epithelial interaction and antibody neutralization of HGF resulted in reduced expression of glucose transporter 1 (GLUT1) and decreased glucose uptake by epithelium.

Conclusions: Both tumor/epithelial and stromal characteristics play important roles in metabolism. Warburg-like metabolism is influenced by changes in stromal-epithelial interactions, including altered expression of HGF/Met pathway and GLUT1 expression.

Figure 1. Unsupervised cluster analysis of 379 metabolites resulted in two main clusters (Clusters 1 and 2)

(A). Cluster 1 (blue lines in dendrogram) included less aggressive tumor types or normal breast samples, while Cluster 2 (red lines in dendrogram) included more aggressive tumors and metastases (B, colored bars). Clusters of metabolites in the heatmap (C) implicated hallmark Warburg phenotypes in aggressive tumors: elevated levels of amino acids, nucleic acids, and decreased steady state levels of sugars/carbohydrates and citric acid cycle metabolites. Pearson correlation of tumor gene expression with a previously published wound response signature shows a role for stromal activation in Cluster 2; that is, metabolic class was strongly correlated with expression of an in vivo wound response signature (25) (D).

Figure 2. Principal Component Analysis reveals a separation of tumor phenotype by key metabolite groups

Four classes of metabolites – (A) amino acids, (B) nucleic acids, (C) tricarboxylic acid (TCA) cyclemetabolites, and (D)carbohydrates/sugars – distinguish normal breast tissue samples, tumors in the less aggressive metabolite cluster (Cluster 1), tumors in the more aggressive metabolite cluster (Cluster 2), and metastatic tumors.

Figure 3. Schematic representing major metabolic pathways in the Warburg effect and their relative levels in distinct groups of breast tumors

Red boxes indicate an increase in metabolite levels in Cluster 2 compared to the less aggressive Cluster 1, while a green box indicates decreasing levels. The dotted red box indicates marginally increased metabolite levels. Glucose processing through glycolysis to pyruvate and lactate provides ATP, while the pentose phosphate shunt (PPS) generates key intermediates in nucleotide biosynthesis. Glucose-derived citrate is exported to the cytosol to contribute to lipid production. Glutamine is converted into glutamate and is transported to the mitochondria where it is de-aminated to generate α-ketoglutarate, an intermediate in the TCA cycle. Aromatic amino acids (Aromatic AAs); oxaloacetate (OAA); Acetyl coenzyme A (Acetyl CoA); Succinyl coenzyme A (Succinyl CoA).

Figure 4. Glucose metabolism is regulated by aggressiveness of both tumor and stroma

Glucose uptake is increased by basal-like CAFs (BCAFs). SUM149 cells had higher levels of glucose uptake than MCF7 cells in coculture regardless of fibroblast type (A). Glucose oxidation was suppressed in luminal cocultures (MCF7 or LCAF), while SUM149 cells cocultured with BCAFs had increased glucose oxidation (B). Finally, analysis of glycogen synthesis (C) revealed an increase in all coculture conditions relative to monocultures, with the strongest fold change among basal-like breast cancer cells (SUM149). All fold change values are expressed relative to the expected levels based on coculture composition and monoculture metabolism, as described in Methods.

Figure 5. HGF-dependent regulation of GLUT1 expression in breast cancer

HGF protein expression is elevated in coculture (cc) models compared to monocultures of RMF, MCF7 and SUM149 cells(A). Cytokine arrays identify HGF as a key factor significantly induced in coculture for both luminal and basal-like breast cancer cells (B), when blocked using an HGF neutralizing antibody (α-HGF), the GLUT1 receptor is inhibited at the RNA level (C). Levels of glucose uptake decrease by 66% (p=0.055) in SUM149 cells when HGF is inhibited using antibody (D).