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MEK inhibition reprograms CD8+ T lymphocytes into memory stem cells with potent antitumor effects

Nature Immunology volume 22, pages 53–66 (2021)Cite this article

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Abstract

Regenerative stem cell–like memory (TSCM) CD8+ T cells persist longer and produce stronger effector functions. We found that MEK1/2 inhibition (MEKi) induces TSCM that have naive phenotype with self-renewability, enhanced multipotency and proliferative capacity. This is achieved by delaying cell division and enhancing mitochondrial biogenesis and fatty acid oxidation, without affecting T cell receptor-mediated activation. DNA methylation profiling revealed that MEKi-induced TSCM cells exhibited plasticity and loci-specific profiles similar to bona fide TSCM isolated from healthy donors, with intermediate characteristics compared to naive and central memory T cells. Ex vivo, antigenic rechallenge of MEKi-treated CD8+ T cells showed stronger recall responses. This strategy generated T cells with higher efficacy for adoptive cell therapy. Moreover, MEKi treatment of tumor-bearing mice also showed strong immune-mediated antitumor effects. In conclusion, we show that MEKi leads to CD8+ T cell reprogramming into TSCM that acts as a reservoir for effector T cells with potent therapeutic characteristics.

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Fig. 1: MEKi supports the expansion of activated effector T cells in the TME leading to reduced tumor growth.
Fig. 2: MEKi-treated CD8+ T cells have enhanced mitochondrial respiration fueled by FAO.
Fig. 3: Metabolomic and lipidomic analysis of MEKi-treated CD8+ T cells.
Fig. 4: MEKi induces stem cell memory characteristics in CD8+ T cells.
Fig. 5: MEKi induces stem cell memory in human CD8+ T cells that is intermediate between that of Tnaive and TCM cells.
Fig. 6: MEKi induces TSCM cells by delaying cell division, proliferation and differentiation.
Fig. 7: MEKi induces FAO-mediated stem cell memory in T cells.
Fig. 8: MEKi-treated CD8+ T cells have higher recall responses leading to stronger TSCM-mediated antitumor effects after ACT.

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Data availability

For healthy adult donors, PBMCs were collected through the St. Jude’s Blood Bank; samples for WGBS were collected under institutional review board protocol no. XPD15-086 as published earlier32. In vitro, in vivo and flow cytometry data are included in this published article and its Extended Data Figures. All other relevant data are available from the corresponding author upon reasonable request. Source data are provided with this paper.

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Acknowledgements

We are grateful to Jeannie and Tony Loop for their generous support to SNK’s laboratory. We acknowledge the Georgia Cancer Center, Augusta University internal support grant to S.N.K. and Flow Cytometry Core Facility at Lombardi Comprehensive Cancer Center. We acknowledge the Metabolomics and Flow Cytometry/Cell Sorting Shared Resource in Georgetown University, which is partially supported by NIH/NCI/CCSG grant P30-CA051008 and NIH S10 grant S10OD016213. We thank S. Bansal for technical assistance with LC–MS data acquisition and S. Li for LC–MS data processing and analysis. This study was supported in part by NIH grant 1 R01 CA237311 01A1 to B.Y. and NIH grants R01-CA184185, R01-CA233512 and P30-CA076292 and The Florida Department of Health grant no. 20B04 to P.C.R. We acknowledge the contribution of P. Finger from the electron microscopy service at the Jackson Laboratory for assistance with electron microscopy.

Author information

Author notes

  1. Rahul Nandre

    Present address: Division of Preclinical Innovation, National Center for Advancing Translational Sciences, NIH, Rockville, MD, USA

  2. Peng Zeng

    Present address: Department of Pharmacology, Case Western Reserve University, Cleveland, OH, USA

  3. Shamim Ahmad

    Present address: Kite Pharma/A GILEAD Company, Emeryville, CA, USA

  4. Paulo C. Rodriguez

    Present address: H. Lee Moffitt Cancer Center & Research Institute, Tampa, FL, USA

Authors and Affiliations

  1. The Loop Immuno-Oncology Laboratory, Lombardi Comprehensive Cancer Center, Georgetown University Medical Center, Washington, DC, USA

    Vivek Verma, Nazli Jafarzadeh, Subhadip Kundu, Zhinuo Jiang, Jose Lopez, Rahul Nandre, Fatmah Alolaqi, Pankaj Gaur, Mikayel Mkrtichyan, Seema Gupta & Samir N. Khleif

  2. Georgia Cancer Center, Augusta University, Augusta, GA, USA

    Vivek Verma, Peng Zeng, Shamim Ahmad, Paulo C. Rodriguez, Seema Gupta & Samir N. Khleif

  3. Department of Immunology, St. Jude Children’s Research Hospital, Memphis, TN, USA

    Shannon Boi & Benjamin Youngblood

  4. Center for Applied Bioinformatics, St. Jude Children’s Research Hospital, Memphis, TN, USA

    Yiping Fan

  5. Bioscience, Early Oncology, AstraZeneca, Cambridge, UK

    Simon T. Barry, Viia E. Valge-Archer & Paul D. Smith

  6. The Jackson Laboratory for Genomic Medicine, Farmington, CT, USA

    Jacques Banchereau

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Contributions

V.V., S.G. and S.N.K. conceived the study and designed the experiments. V.V. performed the experiments with input from N.J., S.K., Z.J., J.L., R.N., P.Z., F.A., S.A., P.G. and M.M. S.T.B., V.E.V.-A. and P.D.S. supplied the materials. B.Y. and S.B. performed the methylation experiment. Y.F. analyzed the whole-genome bisulfite sequencing. J.B. helped with the electron microscopy and, along with B.Y. and S.B., was involved in numerous discussions and reviewed the manuscript. P.C.R. helped with the metabolic assays. V.V., S.G. and S.N.K. analyzed the data and wrote the manuscript. S.N.K. supervised the study.

Corresponding author

Correspondence to Samir N. Khleif.

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Competing interests

S.N.K. and V.V. are inventors on patent applications related to work on the induction of TSCM by MEK1/2 inhibition in T cells and methods for use of these TSCM in various therapeutic applications. S.N.K. reports honoraria from Syndax, IOBiotech, Bioline Therapeutics, Northwest Biotherapeutics, Advaxis, EMD Serono, GSK, UbiVac, McKinsey, AstraZeneca and Lycera. S.N.K. reports stocks or ownership interest in Advaxis, GeorgiaImmune, IOBiotech and Northwest Therapeutics. S.N.K. is a consultant for Syndax, IOBiotech, Bioline, Kahr, PDS Biotechnology, AstraZeneca, CytomX, NewLink Genetics, AratingaBio, CanImGuide and Lycera. S.N.K. is a board member for Advaxis. S.N.K. has research contracts with Syndax, IOBiotech, Bioline Therapeutics, AstraZeneca, MedImmune and Lycera. J.B. is on the Board of Directors of Neovacs and Stamford Pharmaceutical and is a member of the CUE Biopharma and GeorgiaImmune SABs. J.B. reports stock or ownership interest in Neovacs, Stamford Pharmaceuticals and Cue Biopharma. J.B. has a research contract with Sanofi.

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Extended data

Extended Data Fig. 1 MEKi enhances mitochondrial respiration in CD8+ T cells.

Related to Figs. 1 and 2. a, Frequencies of phosphorylated-(p)-MEK1/2 and ERK1/2 CD8+ T cells in the TME as estimated by FACS analysis. Representative data from one of two experiments are shown. Each symbol corresponds to one mouse with the indicated number of mice per group given in parentheses. The error bars indicate the s.e.m. Statistical analysis was performed by unpaired, one-tailed Student’s t-test (*P≤0.05). b, Determination of effect of inhibition of mitochondrial respiration by oligomycin on proliferation (by VCT dilution) of gp100-activated and MEKi-treated CD8+ T cells. Representative results from one of two experiments performed in triplicates are shown. The error bars indicate the s.e.m. Statistical analysis was performed by unpaired, one-tailed Student’s t-test (*P≤0.05; **P≤0.01; ****P≤0.0001).

Extended Data Fig. 2 Expression profiles for markers of proliferation, memory, activation, apoptosis, effector functions and exhaustion on in vitro MEKi-treated pMel-1 CD8+ T cells and effects of MEKi, trametinib on TSCM induction and cellular metabolism.

Related to Figs. 4 and 6. a–d, Scheme of pMel-1 CD8+ T cell activation and analysis (a); FACS analysis of Ki67+ (b); CD95+ and CCR7+ (c); CXCR5+ and IL2Rβ+ (d) in CD62L+CD44– CD8+ T cells after various treatments as shown in figures. Representative results from one of two experiments performed in triplicates are shown. The error bars indicate the s.e.m. Statistical analysis was performed by unpaired, one-tailed Student’s t-test (*P≤0.05; **P≤0.01; ***P≤0.001; ****P≤0.0001; ns: non-significant). e–g, FACS micrographs showing the cell phenotype in the naive compartment (CD62L+CD44–) after 48 h activation under various conditions as shown in picture (e); FACS analysis of expression of IFN-γ, Granzyme B, Perforin, KLRG1 and Eomes on CD62L+CD44– cells in the naive cell compartment (marked by dotted red arrows) (f); Expression levels of mRNA of various effector and exhaustion markers relative to Actb after in vitro activation of pMel-1 CD8+ T cells with gp100 with/without MEKi (g). Experiments were repeated twice with similar results and representative results from one experiment are shown. The error bars indicate the s.e.m. Statistical analysis was performed by unpaired, one-tailed Student’s t-test (**P≤0.01; ***P≤0.001; ****P≤0.0001). h–j, Comparative analysis of induction of TSCM cells (h); Estimation of FA (i) and glucose (j) uptake in CD8+ T cells that were activated in the presence of selumetinib or trametinib. Representative results from one of two experiments performed in triplicates are shown. The error bars indicate the s.e.m. Statistical analysis was performed by unpaired, one-tailed Student’s t-test (****P≤0.0001).

Extended Data Fig. 3 In vitro analysis of effect of MEK1 and MEK2 knock down (MEK1/2KD) using siRNA on generation of naive and TSCM cells.

Related to Fig. 4. a, b, Confirmation of knock down of MEK1 (a) and MEK2 (b) by FACS analysis after siRNA treatment. Data are representative of two experiments performed in triplicates. The error bars indicate the s.e.m. Statistical analysis was performed by unpaired, one-tailed Student’s t-test (***P≤0.001; ****P≤0.0001). c, d, Relative frequencies of CD62L+CD44– cells (c) and mitochondrial potential (TMRM) (d) of CD8+ T cells in which MEK1/2 was knocked down. Data are representative of three experiments performed in triplicate. The error bars indicate the s.e.m. Statistical analysis was performed by unpaired, one-tailed Student’s t-test (**P≤0.01; ****P≤0.0001) e, Memory phenotypes generated after MEK1KD or MEK2KD in pMel-1 CD8+ T cells. Data are representative of two experiments performed in triplicates.

Extended Data Fig. 4 Gating strategy and methylation status of MEKi-treated CD8+ T cells.

Related to Figs. 5 and 7. a, Gating strategy for generation of TSCM cells from human CD8+ T cells. b, A graphical representation of the number of DMRs among the MEKi TSCM (one WGBS sample) versus freshly isolated naive, bonafide TSCM, TCM, and TEM (one WGBS sample for each) from healthy donors (HD). c, Statistical analysis of the methylation status of human TNAIVE, TSCM and TCM cells at Ifng, Prf1 and Tcf7 gene loci, as noted in the figure (related to Fig. 5e–g). Representative data from one of two experiments is shown. The error bars indicate the s.e.m. Statistical analysis was performed by unpaired, one-tailed Student’s t-test (*P≤0.05; **P≤0.01; ****P≤0.0001). d, Estimation of CD62L and CD44 on pMel-1 CD8 cells after activation under various conditions as listed in the figure. Representative results from one of three experiments performed in triplicates are shown. The error bars indicate the s.e.m. Statistical analysis was performed by unpaired, one-tailed Student’s t-test (****P≤0.0001; ns: non-significant).

Extended Data Fig. 5 Frequency of CD8+ T cells in various tissues following ACT, the expression levels of mTORC1 in MEKi-treated CD8+ T cells, and a proposed model for MEKi-mediated TSCM generation.

Related to Fig. 8. a, The frequency of CD8+ T cell engrafted in spleen and tumors of mice that received variously treated pMel-1 CD8+ T cells (48 h post-T cell infusion). FACS analysis of the tumor and spleen samples was performed by gating upon Thy1.1 cell population. A representative of two experiments is shown. Each symbol corresponds to one mouse with the indicated number of mice per group given in parentheses. The error bars indicate the s.e.m. Statistical analysis was performed by unpaired, one-tailed Student’s t-test. Significant differences in engraftment were not observed between MEKi-treated and untreated spleen and tumor samples. b, Loci-specific bisulfite sequencing analysis of the Ifng and Prf1 in TCM CD8+ T cells generated after activation of human CD8+ T cells with anti-CD3/28 with or without MEKi treatment. Horizontal lines represent individual sequenced clones from the pool of FACS-purified CD8+ T cells. Bar graphs represent the frequencies of methylated CpGs in respective sample as shown in the figure. Representative data from one of two experiments are shown. c, Estimation of numbers of adoptively transferred cells in tumors of variously treated mice. The mice were sacrificed at 22 days after ACT and tumors were harvested. Samples were stained and processed for FACS analysis. A representative of two experiments is shown. Each symbol represents one mouse with the indicated number of mice per group given in parentheses. The error bars indicate the s.e.m. Statistical analysis was performed by unpaired, one-tailed Student’s t-test (*P≤0.05). d, Levels of phosphorylated-(p)-mTORC1 and total mTORC1 in MEKi-treated mouse CD8+ T cells during initial cell activation and following antigenic re-challenge as detailed in the figure. Expression of β-actin is shown as a control. Number on the bands show band intensity. Experiments were repeated twice with similar results. e, Proposed model for MEKi-mediated TSCM generation. Inhibition of MEK1/2 during antigen-activation of naive cells: 1) results in a decrease in the levels of ERK1/2 and cyclin D1, delaying cell division and accumulating these cells in early phases of differentiation; 2) results in an increase in PGC1α and its downstream SIRT3, enhancing FAO-mediated metabolic fitness that drives memory generation; and 3) does not affect PI3K-Akt-mediated T cell activation. This crosstalk between MAPK pathway, cellular metabolism and TCR-mediated signaling after MEK-inhibition leads to induction of memory characteristics in naive CD8+ T cells, generating TSCM. These TSCM produce highly activated effector cells following re-stimulation with the cognate antigen resulting in robust recall responses.

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Source Data Fig. 5

A list of the top 3,000 CpG sites across samples.

Source Data Extended Data Fig. 5

Unprocessed blots.

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Verma, V., Jafarzadeh, N., Boi, S. et al. MEK inhibition reprograms CD8+ T lymphocytes into memory stem cells with potent antitumor effects. Nat Immunol 22, 53–66 (2021). https://doi.org/10.1038/s41590-020-00818-9

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