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Mitochondrial Membrane Potential Identifies Cells with Enhanced Stemness for Cellular Therapy

  • Madhusudhanan Sukumar*
  • , Jie Liu
  • , Gautam U. Mehta
  • , Shashank J. Patel
  • , Rahul Roychoudhuri
  • , Joseph G. Crompton
  • , Christopher A. Klebanoff
  • , Yun Ji
  • , Peng Li
  • , Zhiya Yu
  • , Greg D. Whitehill
  • , David Clever
  • , Robert L. Eil
  • , Douglas C. Palmer
  • , Suman Mitra
  • , Mahadev Rao
  • , Keyvan Keyvanfar
  • , David S. Schrump
  • , Ena Wang
  • , Francesco M. Marincola
  • Luca Gattinoni, Warren J. Leonard, Pawel Muranski, Toren Finkel, Nicholas P. Restifo
*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

Abstract

Long-term survival and antitumor 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.

Original languageEnglish
Pages (from-to)63-76
Number of pages14
JournalCell Metabolism
Volume23
Issue number1
DOIs
Publication statusPublished - 12-01-2016

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

  1. SDG 3 - Good Health and Well-being
    SDG 3 Good Health and Well-being

All Science Journal Classification (ASJC) codes

  • Physiology
  • Molecular Biology
  • Cell Biology

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