Authors : Sangeedha G; Madhu mitha T; Bharathi B; DeepaC.Philip

Volume/Issue : Volume 10 - 2025, Issue 3 - March

Google Scholar : https://tinyurl.com/yc52zpn3

Scribd : https://tinyurl.com/2tdmb7fb

DOI : https://doi.org/10.38124/ijisrt/25mar497

Note : A published paper may take 4-5 working days from the publication date to appear in PlumX Metrics, Semantic Scholar, and ResearchGate.

Abstract : Neoplastic Microenvironment is a key factor influencing cancer Proliferation, spread, and therapeutic outcomes by mediating interactions between malignant and immune cells. One of the most significant aspects of these interactions is metabolic competition, wherein cancer cells alter their Cellular metabolic mechanisms—including anaerobic glycolysis, lipid oxidation, and amino acid utilization—to gain a survival advantage over immune cells. This metabolic reprogramming results in the accumulation of immunosuppressive byproducts like lactate, which impair the role of CTLs and NK cells in orchestrating tumor-directed immune responses evasion. The metabolic heterogeneity within the TME adds another layer of complexity, as tumors develop adaptive mechanisms to withstand hypoxia and nutrient deprivation, while immune cells face metabolic stress that leads to dysfunction and exhaustion. Immunotherapies, particularly Immune-modulating drugs targeting PD-1 and CTLA-4 receptors, aim to rejuvenate T-cell responses but often face challenges due to tumor-induced metabolic suppression, featuring mitochondrial dysregulation and surplus ROS production. Addressing these metabolic constraints through targeted interventions offers promising avenues to enhance immune responses and improve cancer treatment outcomes. A deeper understanding of tumor metabolism may lead to innovative therapeutic strategies aimed at disrupting tumor-mediated immune suppression while restoring immune cell functionality.

Keywords : Tumor Microenvironment, Cancer Metabolism, Immune Evasion, Warburg Effect, Metabolic Suppression, Immunotherapy, Immune Checkpoint Inhibitors, Metabolic Reprogramming, Reactive Oxygen Species, Nutrient Competition, Glycolysis, T-Cell Exhaustion.

References :

1. Antonio, M. J., Zhang, C., & Le, A. (2021). Different tumor microenvironments lead to different metabolic phenotypes. Advances in Experimental Medicine and Biology, 1311, https://doi.org/10.1007/978-3-030-65768-0_10
2. Nabi, K., & Le, A. (2021). The intratumoral heterogeneity of cancer metabolism. Advances in Experimental Medicine and Biology, 1311, https://doi.org/10.1007/978-3-030-65768-0_11
3. Hoang, G., Udupa, S., & Le, A. (2019). Application of metabolomics technologies toward cancer prognosis and therapy. International Review of Cell and Molecular Biology, 347, 191–223.
4. Lapa, B., Goncalves, A. C., Jorge, J., Alves, R., Pires, A. S., Abrantes, A. M., et al. (2020). Acute myeloid leukemia sensitivity to metabolic inhibitors: Glycolysis showed to be a better therapeutic target. Medical Oncology, 37(8), 72.
5. Hurley, H. J., Dewald, H., Rothkopf, Z. S., Singh, S., Jenkins, F., Deb, P., et al. (2020). AMPK regulates metabolic reprogramming necessary for interferon production in human plasmacytoid dendritic cells. Journal of Leukocyte Biology.
6. Guerra, L., Bonetti, L., & Brenner, D. (2020). Metabolic modulation of immunity: A new concept in cancer immunotherapy. Cell Reports, 32(1), 107848.
7. Vesely, S., et al. (2013). Parameters derived from the postoperative decline in ultrasensitive PSA improve the prediction of radical prostatectomy outcome. World Journal of Urology, 31(2), 299–304.
8. Klein Geltink, R. I., O’Sullivan, D., Corrado, M., Bremser, A., Buck, M. D., Buescher, J. M., et al. (2017). Mitochondrial priming by CD28. Cell, 171, 385–397.e11. https://doi.org/10.1016/j.cell.2017.08.018
9. Parry, R. V., Chemnitz, J. M., Frauwirth, K. A., Lanfranco, A. R., Braunstein, I., Kobayashi, S. V., et al. (2005). CTLA-4 and PD-1 receptors inhibit T-cell activation by distinct mechanisms. Molecular and Cellular Biology, 25, 9543–9553. https://doi.org/10.1128/MCB.25.21.9543-9553.2005
10. Frauwirth, K. A., Riley, J. L., Harris, M. H., Parry, R. V., Rathmell, J. C., Plas, D. R., et al. (2002). The CD28 signaling pathway regulates glucose metabolism. Immunity, 16, 769–777. https://doi.org/10.1016/s1074-7613(02)00323-0
11. Jacobs, S. R., Herman, C. E., Maciver, N. J., Wofford, J. A., Wieman, H. L., Hammen, J. J., & Rathmell, J. C. (2008). Glucose uptake is limiting in T cell activation and requires CD28-mediated Akt-dependent and independent pathways. Journal of Immunology, 180(7), 4476–4486. https://doi.org/10.4049/jimmunol.180.7.4476
12. Siska, P. J., Beckermann, K. E., Mason, F. M., Andrejeva, G., Greenplate, A. R., Sendor, A. B., et al. (2017). Mitochondrial dysregulation and glycolytic insufficiency functionally impair CD8 T cells infiltrating human renal cell carcinoma. JCI Insight, 2, e93411. https://doi.org/10.1172/jci.insight.93411
13. Zandberg, D. P., Menk, A. V., Velez, M., Normolle, D., DePeaux, K., Liu, A., et al. (2021). Tumor hypoxia is associated with resistance to PD-1 blockade in squamous cell carcinoma of the head and neck. Journal for Immunotherapy of Cancer, 9, e002088. https://doi.org/10.1136/jitc-2020-002088
14. Xu, S., Chaudhary, O., Rodríguez-Morales, P., Sun, X., Chen, D., Zappasodi, R., et al. (2021). Uptake of oxidized lipids by the scavenger receptor CD36 promotes lipid peroxidation and dysfunction in CD8(+) T cells in tumors. Immunity, 54, 1561–1577.e7. https://doi.org/10.1016/j.immuni.2021.05.003
15. Warburg, O. H., & Dickens, F. (1930). The metabolism of tumours. Constable.
16. Papandreou, I., Cairns, R. A., Fontana, L., Lim, A. L., & Denko, N. C. (2006). HIF-1 mediates adaptation to hypoxia by actively downregulating mitochondrial oxygen consumption. Cell Metabolism, 3, 187–197. https://doi.org/10.1016/j.cmet.2006.01.012
17. Fukuda, R., Zhang, H., Kim, J. W., Shimoda, L., Dang, C. V., & Semenza, G. L. (2007). HIF-1 regulates cytochrome oxidase subunits to optimize efficiency of respiration in hypoxic cells. Cell, 129, 111–122. https://doi.org/10.1016/j.cell.2007.01.047
18. Hensley, C. T., Wasti, A. T., & DeBerardinis, R. J. (2013). Glutamine and cancer: Cell biology, physiology, and clinical opportunities. Journal of Clinical Investigation, 123, 3678–3684. https://doi.org/10.1172/JCI69600
19. Buck, M. D., O’Sullivan, D., & Pearce, E. L. (2015). T cell metabolism drives immunity. Journal of Experimental Medicine, 212, 1345–1360. https://doi.org/10.1084/jem.20151159
20. Grover, A., Sanseviero, E., Timosenko, E., & Gabrilovich, D. I. (2021). Myeloid-derived suppressor cells: A propitious road to clinic. Cancer Discovery, 11, 2693–2706. https://doi.org/10.1158/2159-8290.CD-21-0764
21. Munn, D. H., et al. (2002). Potential regulatory function of human dendritic cells expressing indoleamine 2,3-dioxygenase. Science, 297(5588), 1867–1870.
22. June, C. H. (2007). Adoptive T cell therapy for cancer in the clinic. The Journal of Clinical Investigation, 117(6), 1466–1476.
23. Kershaw, M. H., Westwood, J. A., & Darcy, P. K. (2013). Gene-engineered T cells for cancer therapy. Nature Reviews Cancer, 13(8), 525–541.
24. Scharping, N. E., Menk, A. V., Rivadeneira, D. B., Ford, B. R., Rittenhouse, N. L., Peralta, R., et al. (2021). Mitochondrial stress induced by continuous stimulation under hypoxia rapidly drives T cell exhaustion. Nature Immunology, 22, 205–215. https://doi.org/10.1038/s41590-020-00834-9