The DOI matches its Crossref record; 50 of the 50 references it cites were found in a registry or an index.
Mitochondrial Membrane Potential Identifies Cells with Enhanced Stemness for Cellular Therapy
Open accessAbstract
SUMMARY Long-term survival and anti-tumor immunity of adoptively-transferred CD8+ T cells is dependent on their metabolic fitness, but approaches to isolate therapeutic T cells based on metabolic features are not well established. Here we utilized a lipophilic cationic dye tetramethylrhodamine methyl ester (TMRM) to identify and isolate metabolically-robust T cells based on their mitochondrial membrane potential (ΔΨm). Comprehensive metabolomic and gene expression profiling demonstrated global features of improved metabolic fitness in low-ΔΨm-sorted CD8+ T cells. Transfer of these low-ΔΨm T cells was associated with superior long-term in vivo persistence and an enhanced capacity to eradicate established tumors compared with high-ΔΨm cells. Use of ΔΨm-based sorting to enrich for cells with superior metabolic features was observed in CD8+, CD4+ T-cell subsets and long-term hematopoietic stem cells. This metabolism-based approach to cell-selection may be broadly applicable to therapies involving the transfer of HSC or lymphocytes for the treatment of viral-associated illnesses and cancer.
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Targeting Hypoxia-Inducible Factors for the Treatment of Anemia in Chronic Kidney Disease Patients
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Wherry, E. J. (2011) · Nature Immunology · doi:10.1038/ni.2035 · Cited by 4,062 · cited 1×
“In addition to direct detrimental effects of high ROS and DNA damage levels, recent data have demonstrated that chronic infection and cancer can trigger terminal differentiation and T cell exhaustion (Wherry, 2011).”
Chimeric antigen receptor–modified T cells in chronic lymphoid leukemia
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Posttranscriptional Control of T Cell Effector Function by Aerobic Glycolysis
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Self-citationTranscriptional control of effector and memory CD8+ T cell differentiation
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Cited by
Mitochondria are the powerhouses of immunity
Mills, E. L., Kelly, B., & O'Neill, L. A. J. (2017) · Nature Immunology · doi:10.1038/ni.3704 · Cited by 1,161
The Principles of Engineering Immune Cells to Treat Cancer
Lim, W. A., & June, C. H. (2017) · Cell · doi:10.1016/j.cell.2017.01.016 · Cited by 1,080
Clinical implications of T cell exhaustion for cancer immunotherapy
Chow, A., Perica, K., Klebanoff, C. A., & Wolchok, J. D. (2022) · Nature Reviews Clinical Oncology · doi:10.1038/s41571-022-00689-z · Cited by 1,044
Self-citationScharping, N. E., Rivadeneira, D. B., Menk, A. V., Vignali, P. D. A., Ford, B. R., Rittenhouse, N. L., Peralta, R., Wang, Y., Wang, Y., DePeaux, K., et al. (2021) · Nature Immunology · doi:10.1038/s41590-020-00834-9 · Cited by 897
Scharping, N. E., Menk, A. V., Moreci, R. S., Whetstone, R. D., Dadey, R. E., Watkins, S. C., Ferris, R. L., & Delgoffe, G. M. (2016) · Immunity · doi:10.1016/j.immuni.2016.07.009 · Cited by 848
Metadata
- Authors
- Sukumar, M., Liu, J., Mehta, G. U., Patel, S. J., Roychoudhuri, R., Crompton, J. G., Klebanoff, C. A., Ji, Y., Li, P., Yu, Z., Whitehill, G. D., Clever, D., Eil, R. L., Palmer, D. C., Mitra, S., Rao, M., Keyvanfar, K., Schrump, D. S., Wang, E., Marincola, F. M., Gattinoni, L., Leonard, W. J., Muranski, P., Finkel, T., & Restifo, N. P.
- Venue
- Cell Metabolism
- Publisher
- Elsevier BV
- Published
- 2016-01
- Volume
- 23
- Issue
- 1
- Pages
- 63-76
- ISSN
- 1550-4131 (ISSN-L)
- OpenAlex
- W2190766406
- Cited by
- 388
- References
- 50
- FWCI
- 10.31
- Type
- journal article
- Language
- en
- Open access
- bronze
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- Sukumar, M., Liu, J., Mehta, G. U., Patel, S. J., Roychoudhuri, R., Crompton, J. G., Klebanoff, C. A., Ji, Y., Li, P., Yu, Z., Whitehill, G. D., Clever, D., Eil, R. L., Palmer, D. C., Mitra, S., Rao, M., Keyvanfar, K., Schrump, D. S., Wang, E., . . . Restifo, N. P. (2016). Mitochondrial Membrane Potential Identifies Cells with Enhanced Stemness for Cellular Therapy. Cell Metabolism. https://doi.org/10.1016/j.cmet.2015.11.002
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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
