Mechanisms and Implications of Metabolic Heterogeneity in Cancer

Abstract

Tumors display reprogrammed metabolic activities that promote cancer progression. We currently possess a limited understanding of the processes governing tumor metabolism in vivo and of the most efficient approaches to identify metabolic vulnerabilities susceptible to therapeutic targeting. While much of the literature focuses on stereotyped, cell-autonomous pathways like glycolysis, recent work emphasizes heterogeneity and flexibility of metabolism between tumors and even within distinct regions of solid tumors. Metabolic heterogeneity is important because it influences therapeutic vulnerabilities and may predict clinical outcomes. This Review describes current concepts about metabolic regulation in tumors, focusing on processes intrinsic to cancer cells and on factors imposed upon cancer cells by the tumor microenvironment. We discuss experimental approaches to identify subtype-selective metabolic vulnerabilities in preclinical cancer models. Finally, we describe efforts to characterize metabolism in primary human tumors, which should produce new insights into metabolic heterogeneity in the context of clinically relevant microenvironments.

Figure 1.. Convergent and divergent metabolic properties in cancer.

Convergent metabolic properties (left) arise downstream of diverse regulatory influences. Convergent properties are observed frequently throughout cancer models and include core pathways such as those that allow cells to produce energy, build macromolecules and maintain redox balance. Divergent properties (right), in contrast, appear in distinct molecular subsets of cancer and contribute to metabolic heterogeneity. Convergent and divergent metabolic phenotypes may both give rise to metabolic liabilities, although the generality of these liabilities is predicted to differ according to the class.

Figure 2.. Oncogenic drivers and tissue of origin influence cancer metabolism.

(A) Different oncogenic drivers can produce divergent metabolic features, contributing to metabolic heterogeneity among tumors arising in the same tissue. (B) Cell and tissue of origin also contribute to metabolic heterogeneity. Different tissues display different native metabolic programs, and some aspects of these programs are retained in tumors arising in the tissue. As a result, tumors arising in different tissues may display markedly divergent metabolic phenotypes even if they contain the same oncogenic driver.

Figure 3.. Epigenetics and metabolism in cancer cells.

Epigenetic regulation of gene expression contributes to metabolic heterogeneity because many metabolic enzymes and nutrient transporters are regulated by epigenetic modifications of histones (acetylation, methylation) and DNA (methylation). Conversely, these epigenetic modifications respond to the metabolic state of the cell. The relative abundances of SAM and SAH regulate DNA and histone methyltransferases, while the abundance of acetyl-CoA, the ratio of acetyl-CoA to free CoA and NAD levels can regulate histone acetylation. The TCA cycle intermediate α-KG affects demethylation of histones and DNA by acting as a co-substrate for JHDM histone demethylases and TET-family methylcytosine dioxygenases, respectively. The oncometabolites fumarate, succinate and 2-HG are dicarboxylates that compete with α-KG, interfering with TET/JHDM function. Abbreviations: HK2, hexokinase 2; MCT4, monocarboxylate transporter 4; SAM, S-adenosylmethionine; SAH, S-adenosyl-homocysteine; NAD, nicotinamide adenine dinucleotide; α-KG, alpha-ketoglutarate; 2-HG, 2-hydroxyglutarate; TET, 10–11 translocation enzyme; JHDM, Jumonji C domain-containing histone demethylase.

Figure 4.. Metabolic cross-talk in the tumor microenvironment.

Interactions among cancer cells and other components of the TME contribute to metabolic heterogeneity. Cancer cells and T cells compete for nutrients (e.g., glucose and glutamine), and excessive consumption of these nutrients by cancer cells suppresses T cell activation. Other cells in the TME also engage in metabolic cross-talk with cancer cells. Stromal cells provide nutrients that support cancer cell proliferation. CAFs respond to oxidative stress imposed by cancer cells by activating HIF1α and NFκB, thereby stimulating glycolysis and secreting lactate, which may be taken up by cancer cells. Degradative processes like mitophagy and autophagy in CAFs also provide nutrients to cancer cells. Loss of ECM attachment suppresses NADPH production, resulting in ROS-mediated anoikis; this form of cell death can be overcome through oncogene-stimulated NADPH production by the pentose phosphate pathway. Reducing oxidative stress allows cells to survive in the detached state and promotes formation of distant metastases. Abbreviations, TME, tumor microenvironment; ECM, extracellular matrix; FA, fatty acid; FAO, fatty acid oxidation; CAF, cancer-associated fibroblast; ROS, reactive oxygen species; PEP, phosphoenolpyruvate; GSH, glutathione, reduced; GCLC, Glutamate-Cysteine Ligase.