The DOI matches its Crossref record; 78 of the 78 references it cites were found in a registry or an index.
Tumor aerobic glycolysis confers immune evasion through modulating sensitivity to T cell-mediated bystander killing via TNF-α
Open accessAbstract
Metabolic reprogramming toward glycolysis is a hallmark of cancer malignancy. The molecular mechanisms by which the tumor glycolysis pathway promotes immune evasion remain to be elucidated. Here, by performing genome-wide CRISPR screens in murine tumor cells co-cultured with cytotoxic T cells (CTLs), we identified that deficiency of two important glycolysis enzymes, Glut1 (glucose transporter 1) and Gpi1 (glucose-6-phosphate isomerase 1), resulted in enhanced killing of tumor cells by CTLs. Mechanistically, Glut1 inactivation causes metabolic rewiring toward oxidative phosphorylation, which generates an excessive amount of reactive oxygen species (ROS). Accumulated ROS potentiate tumor cell death mediated by tumor necrosis factor alpha (TNF-α) in a caspase-8- and Fadd-dependent manner. Genetic and pharmacological inactivation of Glut1 sensitizes tumors to anti-tumor immunity and synergizes with anti-PD-1 therapy through the TNF-α pathway. The mechanistic interplay between tumor-intrinsic glycolysis and TNF-α-induced killing provides new therapeutic strategies to enhance anti-tumor immunity.
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Cites
Hallmarks of Cancer: The Next Generation
Hanahan, D., & Weinberg, R. A. (2011) · Cell · doi:10.1016/j.cell.2011.02.013 · Cited by 66,590
STAR: ultrafast universal RNA-seq aligner
Dobin, A., Davis, C. A., Schlesinger, F., Drenkow, J., Zaleski, C., Jha, S., Batut, P., Chaisson, M., & Gingeras, T. R. (2013) · Bioinformatics · doi:10.1093/bioinformatics/bts635 · Cited by 51,709
Comprehensive Integration of Single-Cell Data
Stuart, T., Butler, A., Hoffman, P., Hafemeister, C., Papalexi, E., Mauck, W. M., Hao, Y., Stoeckius, M., Smibert, P., & Satija, R. (2019) · Cell · doi:10.1016/j.cell.2019.05.031 · Cited by 15,453
Robust enumeration of cell subsets from tissue expression profiles
Newman, A. M., Liu, C. L., Green, M. R., Gentles, A. J., Feng, W., Xu, Y., Hoang, C. D., Diehn, M., & Alizadeh, A. A. (2015) · Nature Methods · doi:10.1038/nmeth.3337 · Cited by 13,224
Hallmarks of Cancer: New Dimensions
Hanahan, D. (2022) · Cancer Discovery · doi:10.1158/2159-8290.cd-21-1059 · Cited by 9,887
TGFβ attenuates tumour response to PD-L1 blockade by contributing to exclusion of T cells
Mariathasan, S., Turley, S. J., Nickles, D., Castiglioni, A., Yuen, K., Wang, Y., Kadel III, E. E., Koeppen, H., Astarita, J. L., Cubas, R., et al. (2018) · Nature · doi:10.1038/nature25501 · Cited by 5,400
Signatures of T cell dysfunction and exclusion predict cancer immunotherapy response
Jiang, P., Gu, S., Pan, D., Fu, J., Sahu, A., Hu, X., Li, Z., Traugh, N., Bu, X., Li, B., et al. (2018) · Nature Medicine · doi:10.1038/s41591-018-0136-1 · Cited by 5,179
Self-citationxCell: digitally portraying the tissue cellular heterogeneity landscape
Aran, D., Hu, Z., & Butte, A. J. (2017) · Genome Biology · doi:10.1186/s13059-017-1349-1 · Cited by 4,397
Profiling Tumor Infiltrating Immune Cells with CIBERSORT
Chen, B., Khodadoust, M. S., Liu, C. L., Newman, A. M., & Alizadeh, A. A. (2018) · Methods in Molecular Biology · doi:10.1007/978-1-4939-7493-1_12 · Cited by 3,874
Genomic and Transcriptomic Features of Response to Anti-PD-1 Therapy in Metastatic Melanoma
Hugo, W., Zaretsky, J. M., Sun, L., Song, C., Moreno, B. H., Hu-Lieskovan, S., Berent-Maoz, B., Pang, J., Chmielowski, B., Cherry, G., et al. (2016) · Cell · doi:10.1016/j.cell.2016.02.065 · Cited by 3,448
Cited by
The hallmarks of cancer immune evasion
Galassi, C., Chan, T. A., Vitale, I., & Galluzzi, L. (2024) · Cancer Cell · doi:10.1016/j.ccell.2024.09.010 · Cited by 565
Energy metabolism in health and diseases
Liu, H., Wang, S., Wang, J., Guo, X., Song, Y., Fu, K., Gao, Z., Liu, D., He, W., & Yang, L.-L. (2025) · Signal Transduction and Targeted Therapy · doi:10.1038/s41392-025-02141-x · Cited by 399
Zhao, J., Jin, D., Huang, M., Ji, J., Xu, X., Wang, F., Zhou, L., Bao, B., Jiang, F., Xu, W., et al. (2024) · Frontiers in Cell and Developmental Biology · doi:10.3389/fcell.2024.1416472 · Cited by 84
Montico, B., Giurato, G., Guerrieri, R., Colizzi, F., Salvati, A., Nassa, G., Lamberti, J., Memoli, D., Sabatelli, P., Comelli, M., et al. (2025) · Journal of Experimental & Clinical Cancer Research · doi:10.1186/s13046-025-03289-8 · Cited by 10
Feng, K., Cai, X., & Qiao, G. (2025) · Cytojournal · doi:10.25259/cytojournal_190_2024 · Cited by 1
Metadata
- Authors
- Wu, L., Jin, Y., Zhao, X., Tang, K., Zhao, Y., Tong, L., Yu, X., Xiong, K., Luo, C., Zhu, J., Wang, F., Zeng, Z., & Pan, D.
- Venue
- Cell Metabolism
- Publisher
- Elsevier BV
- Published
- 2023-09
- Volume
- 35
- Issue
- 9
- Pages
- 1580-1596.e9
- ISSN
- 1550-4131 (ISSN-L)
- OpenAlex
- W4385302373
- Cited by
- 284
- References
- 78
- FWCI
- 27.57
- Type
- journal article
- Language
- en
- Open access
- bronze
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- Wu, L., Jin, Y., Zhao, X., Tang, K., Zhao, Y., Tong, L., Yu, X., Xiong, K., Luo, C., Zhu, J., Wang, F., Zeng, Z., & Pan, D. (2023). Tumor aerobic glycolysis confers immune evasion through modulating sensitivity to T cell-mediated bystander killing via TNF-α. Cell Metabolism. https://doi.org/10.1016/j.cmet.2023.07.001
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