The DOI matches its Crossref record; 40 of the 40 references it cites were found in a registry or an index.
Enhancing CD8+ T Cell Fatty Acid Catabolism within a Metabolically Challenging Tumor Microenvironment Increases the Efficacy of Melanoma Immunotherapy
Open accessAbstract
Summary How tumor-infiltrating T lymphocytes (TILs) adapt to the metabolic constrains within the tumor microenvironment (TME) and to what degree this affects their ability to combat tumor progression remain poorly understood. Using mouse melanoma models, we report that CD8+ TILs enhance PPAR-α signaling and catabolism of fatty acids (FAs) when simultaneously subjected to hypoglycemia and hypoxia. This metabolic switch partially preserves CD8+ TILs’ effector functions although co-inhibitor expression increases during tumor progression regardless of their antigen specificity. Further promoting FA catabolism improves the CD8+ TIL’s ability to slow tumor progression. PD-1 blockade delays tumor growth without changing TIL metabolism or functions. It synergizes with metabolic reprogramming of T cells to achieve superior antitumor efficacy and even complete cures.
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Cites
PD-1 and PD-L1 Immune Checkpoint Blockade to Treat Breast Cancer
Hartkopf, A. D., Taran, F.-A., Wallwiener, M., Walter, C. B., Krämer, B., Grischke, E.-M., & Brucker, S. Y. (2016) · Breast Care · doi:10.1159/000453569 · Cited by 30,845
Adverse Renal Effects of Immune Checkpoint Inhibitors: A Narrative Review
Wanchoo, R., Karam, S., Uppal, N. N., Barta, V. S., Deray, G., Devoe, C., Launay-Vacher, V., Jhaveri, K. D., & on behalf of Cancer and Kidney International Network Workgroup on Immune Checkpoint Inhibitors (2017) · American Journal of Nephrology · doi:10.1159/000455014 · Cited by 15,256
Combined Nivolumab and Ipilimumab or Monotherapy in Untreated Melanoma
Larkin, J., Chiarion-Sileni, V., Gonzalez, R., Grob, J. J., Cowey, C. L., Lao, C. D., Schadendorf, D., Dummer, R., Smylie, M., Rutkowski, P., et al. (2015) · New England Journal of Medicine · doi:10.1056/nejmoa1504030 · Cited by 8,157
Safety and Tumor Responses with Lambrolizumab (Anti–PD-1) in Melanoma
Hamid, O., Robert, C., Daud, A., Hodi, F. S., Hwu, W.-J., Kefford, R., Wolchok, J. D., Hersey, P., Joseph, R. W., Weber, J. S., et al. (2013) · New England Journal of Medicine · doi:10.1056/nejmoa1305133 · Cited by 3,392
Metabolic Competition in the Tumor Microenvironment Is a Driver of Cancer Progression
Chang, C.-H., Qiu, J., O’Sullivan, D., Buck, M. D., Noguchi, T., Curtis, J. D., Chen, Q., Gindin, M., Gubin, M. M., van der Windt, G. J. W., et al. (2015) · Cell · doi:10.1016/j.cell.2015.08.016 · Cited by 3,331
Fatty acid synthase and the lipogenic phenotype in cancer pathogenesis
Menendez, J. A., & Lupu, R. (2007) · Nature Reviews Cancer · doi:10.1038/nrc2222 · Cited by 2,941 · cited 1×
“Cancer cells increase de novo lipogenesis (Menendez and Lupu, 2007) and recruit adipose progenitor cells.”
BackgroundZou, W., Wolchok, J. D., & Chen, L. (2016) · Science Translational Medicine · doi:10.1126/scitranslmed.aad7118 · Cited by 2,400
CTLA-4 and PD-1 Receptors Inhibit T-Cell Activation by Distinct Mechanisms
Parry, R. V., Chemnitz, J. M., Frauwirth, K. A., Lanfranco, A. R., Braunstein, I., Kobayashi, S. V., Linsley, P. S., Thompson, C. B., & Riley, J. L. (2005) · Molecular and Cellular Biology · doi:10.1128/mcb.25.21.9543-9553.2005 · Cited by 1,931
Transcriptional control of effector and memory CD8+ T cell differentiation
Kaech, S. M., & Cui, W. (2012) · Nature Reviews Immunology · doi:10.1038/nri3307 · Cited by 1,628
Phosphoenolpyruvate Is a Metabolic Checkpoint of Anti-tumor T Cell Responses
Ho, P.-C., Bihuniak, J. D., Macintyre, A. N., Staron, M., Liu, X., Amezquita, R., Tsui, Y.-C., Cui, G., Micevic, G., Perales, J. C., et al. (2015) · Cell · doi:10.1016/j.cell.2015.08.012 · Cited by 1,462
Cited by
Phenotype molding of stromal cells in the lung tumor microenvironment
Lambrechts, D., Wauters, E., Boeckx, B., Aibar, S., Nittner, D., Burton, O., Bassez, A., Decaluwé, H., Pircher, A., Van den Eynde, K., et al. (2018) · Nature Medicine · doi:10.1038/s41591-018-0096-5 · Cited by 1,648
The cancer metabolic reprogramming and immune response
Xia, L., Oyang, L., Lin, J., Tan, S., Han, Y., Wu, N., Yi, P., Tang, L., Pan, Q., Rao, S., et al. (2021) · Molecular Cancer · doi:10.1186/s12943-021-01316-8 · Cited by 1,312
Mitochondrial dynamics in health and disease: mechanisms and potential targets
Chen, W., Zhao, H., & Li, Y. (2023) · Signal Transduction and Targeted Therapy · doi:10.1038/s41392-023-01547-9 · Cited by 1,306
Zeng, D., Li, M., Zhou, R., Zhang, J., Sun, H., Shi, M., Bin, J., Liao, Y., Rao, J., & Liao, W. (2019) · Cancer Immunology Research · doi:10.1158/2326-6066.cir-18-0436 · Cited by 986
“that are considered T-cell suppressive and exclusion (50-52) in TME gene cluster A (Fig.”
BackgroundCD8+ T cells and fatty acids orchestrate tumor ferroptosis and immunity via ACSL4
Liao, P., Wang, W., Wang, W., Kryczek, I., Li, X., Bian, Y., Sell, A., Wei, S., Grove, S., Johnson, J. K., et al. (2022) · Cancer Cell · doi:10.1016/j.ccell.2022.02.003 · Cited by 912
Metadata
- Authors
- Zhang, Y., Kurupati, R., Liu, L., Zhou, X. Y., Zhang, G., Hudaihed, A., Filisio, F., Giles-Davis, W., Xu, X., Karakousis, G. C., Schuchter, L. M., Xu, W., Amaravadi, R., Xiao, M., Sadek, N., Krepler, C., Herlyn, M., Freeman, G. J., Rabinowitz, J. D., & Ertl, H. C. J.
- Venue
- Cancer Cell
- Publisher
- Elsevier BV
- Published
- 2017-09
- Volume
- 32
- Issue
- 3
- Pages
- 377-391.e9
- ISSN
- 1535-6108 (ISSN-L)
- OpenAlex
- W2755181857
- Cited by
- 616
- References
- 40
- FWCI
- 16.37
- Type
- journal article
- Language
- en
- Open access
- bronze
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- Zhang, Y., Kurupati, R., Liu, L., Zhou, X. Y., Zhang, G., Hudaihed, A., Filisio, F., Giles-Davis, W., Xu, X., Karakousis, G. C., Schuchter, L. M., Xu, W., Amaravadi, R., Xiao, M., Sadek, N., Krepler, C., Herlyn, M., Freeman, G. J., Rabinowitz, J. D., & Ertl, H. C. J. (2017). Enhancing CD8+ T Cell Fatty Acid Catabolism within a Metabolically Challenging Tumor Microenvironment Increases the Efficacy of Melanoma Immunotherapy. Cancer Cell. https://doi.org/10.1016/j.ccell.2017.08.004
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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
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