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Review
. 2020 Aug 14;10(8):332.
doi: 10.3390/metabo10080332.

Lipidomic-Based Advances in Diagnosis and Modulation of Immune Response to Cancer

Affiliations
Review

Lipidomic-Based Advances in Diagnosis and Modulation of Immune Response to Cancer

Luis Gil-de-Gómez et al. Metabolites. .

Abstract

While immunotherapies for diverse types of cancer are effective in many cases, relapse is still a lingering problem. Like tumor cells, activated immune cells have an anabolic metabolic profile, relying on glycolysis and the increased uptake and synthesis of fatty acids. In contrast, immature antigen-presenting cells, as well as anergic and exhausted T-cells have a catabolic metabolic profile that uses oxidative phosphorylation to provide energy for cellular processes. One goal for enhancing current immunotherapies is to identify metabolic pathways supporting the immune response to tumor antigens. A robust cell expansion and an active modulation via immune checkpoints and cytokine release are required for effective immunity. Lipids, as one of the main components of the cell membrane, are the key regulators of cell signaling and proliferation. Therefore, lipid metabolism reprogramming may impact proliferation and generate dysfunctional immune cells promoting tumor growth. Based on lipid-driven signatures, the discrimination between responsiveness and tolerance to tumor cells will support the development of accurate biomarkers and the identification of potential therapeutic targets. These findings may improve existing immunotherapies and ultimately prevent immune escape in patients for whom existing treatments have failed.

Keywords: biomarkers; cancer; immunotherapy; lipids; metabolism.

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Conflict of interest statement

The authors declare no conflict of interest.

Figures

Figure 1
Figure 1
A metabolic shift is required by immune cells for them to respond actively to tumor cells. Inactive immune cells rely on oxidative phosphorylation (OxPhos) and fatty acid (FA) oxidation (left), while activated and responsive cells increase glucose uptake/glycolysis, resulting in an increased FA synthesis and lactate production (central panel). Lipogenesis, required for a robust cell proliferation, also characterizes tumor cell metabolism (right). Therefore, an untargeted lipid-based treatment to fuel effector immune cells may produce self-defeating effects inducing tumor cell growth. Many other lipid intermediates regulate inflammation, and exogenous lipids such as gut microbiota-derived short chain fatty acids (SCFAs) may impact the host immune response to tumor cells. Together, these findings indicate (1) the exhaustive regulation required to maintain immunity balance in the presence of tumor cells, and (2) the essential role of a large variety of lipids in this control. New precise lipidomic-based strategies may enhance therapeutic targeting and improve the capacity of existing immunotherapies to control tumor progression.

References

    1. Watson J.D., Crick F.H.C. Molecular Structure of Nucleic Acids: A Structure for Deoxyribose Nucleic Acid. Nature. 1953;171:737–738. doi: 10.1038/171737a0. - DOI - PubMed
    1. Check Hayden E. Technology: The $1,000 genome. Nature. 2014;507:294–295. doi: 10.1038/507294a. - DOI - PubMed
    1. Rattray N.J.W., Deziel N.C., Wallach J.D., Khan S.A., Vasiliou V., Ioannidis J.P.A., Johnson C.H. Beyond genomics: Understanding exposotypes through metabolomics. Hum. Genom. 2018;12:4. doi: 10.1186/s40246-018-0134-x. - DOI - PMC - PubMed
    1. Romero R., Espinoza J., Gotsch F., Kusanovic J., Friel L., Erez O., Mazaki-Tovi S., Than N., Hassan S., Tromp G. The use of high-dimensional biology (genomics, transcriptomics, proteomics, and metabolomics) to understand the preterm parturition syndrome. BJOG Int. J. Obstet. Gynaecol. 2006;113:118–135. doi: 10.1111/j.1471-0528.2006.01150.x. - DOI - PMC - PubMed
    1. Lam S.M., Tian H., Shui G. Lipidomics, en route to accurate quantitation. Biochim. Biophys. Acta (BBA) Mol. Cell Biol. Lipids. 2017;1862:752–761. doi: 10.1016/j.bbalip.2017.02.008. - DOI - PubMed