By Hung-Hsi Chen
Scientific advancement has allowed for scientists to understand cancer, and to come up with potential therapies that would combat the disease. Cancer stem cells and its metabolism is becoming a popular area of study, with cancer stem cell being one of the major factors contributing to therapy resistance, and cancer metabolism being one of the areas that combat therapy resistance.
Discovered in 1920s by Otto Warburg, glucose metabolism is one of the most well-known and well-studied areas in cancer metabolism, commonly known as the Warburg effect; it still serves as the basis for many imaging techniques like positron emission tomography. The Warburg effect states that glycolysis is the main form of glucose metabolism in cancer, even in the presence of oxygen. Although this pathway is energy inefficient, especially with their higher energy demand, it allows for the generation of ribose and NADPH, which are important for nucleic acid formation and maintaining redox balance, respectively (Tanabe & Sahara, 2020). However, cancer cells still require the production of enough ATP for survival via the electron transport chain (ETC). ATP generation via the ETS produces an excessive amount of reactive oxygen species (ROS), which are harmful for the cells (Snyder et al., 2018). Therefore, it has been observed that mitochondria in cancer cells have upregulated ROS defense mechanisms.
Amino acids and fatty acids metabolism are also crucial in cancer cells. Although glucose has most of the essential biological components, it only contains oxygen, hydrogen and carbon, but lacks nitrogen, which can be supplied by amino acids. It has been previously studied that there is an increased glutamine uptake observed in cancer cells by PI3K, Kras and c-myc (Tanabe & Sahara, 2020). Additionally, tryptophan has a role in promoting immune cell activation. Unfortunately, cancer cells upregulate Indoleamine 2,3-dioxygenase, an enzyme that breaks down tryptophan, to impair immune cell function to surpass immune surveillance (Tanabe & Sahara, 2020). As the cell expands and proliferates, an excessive amount of lipids is required to allow cell growth. Therefore, there is an upregulation in fatty acid synthase to assist in lipid and cholesterol synthesis.
Cancer stem cells show similar properties as normal stem cells, and are responsible for therapy resistance, cancer recurrence, metastasis and producing tumour heterogeneity. With this in mind, the relationship between cancer stem cells and cancer metabolism can be investigated for potential therapeutic interventions.
Glycolysis has been observed to be upregulated in normal stem cells like somatic, embryonic and induced pluripotent stem cells (Tanabe & Sahara, 2020). This is also observed in cancer stem cells in breast, ovarian, prostate and lung cancer, hepatocellular and nasopharyngeal carcinoma and glioma (Tanabe & Sahara, 2020). In mice models, the inhibition of genes contributing to glycolysis, such as GLUTs, pyruvate dehydrogenase kinase 1 and hexokinases, has reduced tumour growth (Tanabe & Sahara, 2020).
Oxidative phosphorylation in the mitochondria has been seen to be switched on in breast, lung, ovarian, pancreatic cancer, glioma and leukemia (Tanabe & Sahara, 2020; Snyder et al., 2018). Furthermore, the mitochondria in cancer stem cells have an increased membrane potential and increased mass, suggesting its use to be a potential biomarker for cancer stem cells in patients.
Difficulty in targeting cancer stem cells in therapy comes with its metabolic heterogeneity. Within the same tumour, they may be multiple cancer stem cell metabolic phenotypes (Snyder et al., 2018). In addition, studies done in vitro and in vivo show different responses in metabolic response, due to the microenvironments that could potentially derive cancer stem cells into different metabolic phenotypes (Tanabe & Sahara, 2020).
Although targeting the metabolism of cancer stem cells seem promising, we are still at an early stage of research. Deprivation of a specific nutrient or having a biased diet for a prolonged period of time may lead to adaptations, leading to further therapeutic resistance. Additionally, with such complicated metabolism system in place, shutting off one pathway may lead to the overexpression of the other. Therefore, the metabolic, transcriptomic and proteomic profiles of the tumour should be studied and tracked during treatment, to determine the efficacy of using metabolic inhibitors in patients.
Tanabe A, Sahara H. The Metabolic Heterogeneity and Flexibility of Cancer Stem Cells. Cancers 2020;12(10):1.
Snyder V, Reed-Newman T, Arnold L, Thomas SM, Anant S. Cancer Stem Cell Metabolism and Potential Therapeutic Targets. Frontiers in oncology; Front Oncol 2018;8:203.