Amino acids in cancer: Understanding metabolic plasticity and divergence for better therapeutic approaches

Abstract

Metabolic reprogramming is a hallmark of malignant transformation. While initial studies in the field of cancer metabolism focused on central carbon metabolism, the field has expanded to metabolism beyond glucose and glutamine and uncovered the important role of amino acids in tumorigenesis and tumor immunity as energy sources, signaling molecules, and precursors for (epi)genetic modification. As a result of the development and application of new technologies, a multifaceted picture has emerged, showing that context-dependent heterogeneity in amino acid metabolism exists between tumors and even within distinct regions of solid tumors. Understanding the complexity and flexibility of amino acid metabolism in cancer is critical because it can influence therapeutic responses and predict clinical outcomes. This overview discusses the current findings on the heterogeneity in amino acid metabolism in cancer and how understanding the metabolic diversity of amino acids can be translated into more clinically relevant therapeutic interventions.

Keywords: CP: Cancer; CP: Metabolism; amino acids; cancer metabolism; metabolic heterogeneity.

Figure 1.. Factors impacting diversity of amino acid metabolism in cancer

There are several contributing factors to amino acid metabolic diversity. First, different tissues have metabolic needs distinct from other tissues, some of which are maintained in tumors arising from a particular tissue (top left). Therefore, tumors arising in different tissues can exhibit divergent metabolic phenotypes. Additionally, among tumors arising in the same tissue, different oncogenic drivers and/or different gene-expression signatures of tumors can create distinctive metabolic features, influencing metabolic diversity (top right). External factors, such as nutrient availability and stromal cells in the TME, also alter amino acid metabolism. Cancer cells and infiltrating immune cells compete for amino acids (e.g., glutamine, SGOC amino acids, BCAAs) in the TME. Cancer cells require those amino acids, while immune cells need the same amino acids for clonal expansion and activity (bottom, A). In this case, strategies redirecting amino acids from cancer cells to immune cells would support their anti-tumor immunity. Under nutrient poor conditions, cancer cells obtain resources from other cell types (e.g., neurons and cancer-associated fibroblasts) (bottom, B). Cancer cells can also manipulate nutrient composition in the TME to achieve optimal growth and inhibit immune cell function (bottom, C).

Figure 2.. Cancer cells’ adaptation mechanism in asparagine metabolism

(A) Tissue-specific and/or context-dependent transactivation mechanism for ASNS expression. While ATF4 is responsible for ASNS expression in most cancers, some other cancer types where either ATF4 expression is low (CRC) or disease-specific virus modulates gene-expression profile (HBV-driven HCC) induce ASNS in an ATF4-independent manner. (B) Tissue-specific essential gene to survive under asparagine-deprivation conditions. ZBTB1 is required for ATF4-induced ASNS expression in T-ALL, but not in B-ALL or AML. Thus, ZBTB1 suppression can specifically sensitize L-asparaginase-resistant T-ALL, but not other leukemia. (C) Metabolic symbiosis in PDAC. In PDAC with highly glycolytic and high ISR activity, GCN2, a master regulator of ISR, transactivates ATF4, driving ASNS expression and subsequent asparagine production. Asparagine produced inthese cells can be transported into PDAC with high OXPHOS and low ISR activity. When mitochondrial respiration is inhibited, highly glycolytic PDAC cells provide highly oxidative PDAC cells with asparagine, supporting the intracellular aspartate pool for biosynthesis (e.g., nucleotides) as well as maintaining mitochondrial respiration capacity and supporting their survival. ETC, electron transport chain.

Figure 3.. Cancer-type-specific functions of serine

Serine has both catalytic and non-catalytic activities. Cancer cells often increase PHGDH expression to activate serine synthesis. However, PHGDH protein levels can have both pro and anti functions for tumor growth and metastasis, depending on the situations. In the mitochondria, PHGDH forms a complex with ANT2 and mtEFG2, increasing the efficacy of mitochondrial ribosome recycling and subsequent induction of mitochondrial translation (pro-tumor role). In primary TNBC, low PHGDH expression is beneficial for metastasis: the loss of physical interaction between PHGDH and PFK in the glycolysis increases protein glycosylation, thereby potentiating cell dissemination and metastasis.

Figure 4.. Intra- and intertumoral differences in amino acid metabolism (methionine, arginine, BCAAs, and tyrosine)

Alteration of these amino acids (methionine, arginine, BCAAs, and tyrosine), like others, is often observed in cancers, but the degree and direction varies both inter- and intratumorally. Methionine: cancer cells and infiltrating immune cells compete for methionine in the TME, often resulting in T cell exhaustion and an immune-cold environment (see section on methionine and cysteine for more details). Cancer cells also secrete MTA, a metabolic intermediate in the methionine salvage pathway, to the TME and manipulate epigenetic landscape, leading to T cell exhaustion. Arginine: the diversity of arginine metabolism is often associated with expression levels of a urea cycle enzyme, ASS1. In tumors with low ASS shunts, aspartate pools into pyrimidine synthesis, while tumors expressing high levels of ASS1 exhibit enhanced S-nitrosylation of enzymes in the gluconeogenesis pathway, supporting breast cancer cell growth (see section on arginine for more information). BCAAs: cancer cells manipulate BCAA metabolism in the TME through BCKAs. Glioblastoma cells secrete BCKAs to the TME and decrease the phagocytic activity of macrophages. In lung cancer, however, KIV from valine supports M1-like macrophage transition while other two BCKAs exert protumoral effects, similar to glioblastoma (see section on “branched-chain amino acids” for more details). Tyrosine: tyrosine metabolism exhibits intratumor differences depending on cancer stemness status. Within HCC, CD13⁺ cancer stem cells activate the tyrosine catabolic pathway, whereas HCC cells with non-cancer stem cell features suppress the catabolic pathway and activate the dopamine synthesis and secretion pathway, redirecting tyrosine catabolic flux to neurotransmitter production (see section on tyrosine for more information).