Skip to main content
  • AACR Publications
    • Blood Cancer Discovery
    • Cancer Discovery
    • Cancer Epidemiology, Biomarkers & Prevention
    • Cancer Immunology Research
    • Cancer Prevention Research
    • Cancer Research
    • Clinical Cancer Research
    • Molecular Cancer Research
    • Molecular Cancer Therapeutics

AACR logo

  • Register
  • Log in
  • My Cart
Advertisement

Main menu

  • Home
  • About
    • The Journal
    • AACR Journals
    • Subscriptions
    • Permissions and Reprints
    • Reviewing
  • Articles
    • OnlineFirst
    • Current Issue
    • Past Issues
    • Meeting Abstracts
    • Cancer Immunology Essentials
    • Collections
      • COVID-19 & Cancer Resource Center
      • Toolbox: Coding and Computation
      • Toolbox: Signatures and Cells
      • "Best of" Collection
      • Editors' Picks
  • For Authors
    • Information for Authors
    • Author Services
    • Best of: Author Profiles
    • Submit
  • Alerts
    • Table of Contents
    • Editors' Picks
    • OnlineFirst
    • Citation
    • Author/Keyword
    • RSS Feeds
    • My Alert Summary & Preferences
  • News
    • Cancer Discovery News
  • COVID-19
  • Webinars
  • Search More

    Advanced Search

  • AACR Publications
    • Blood Cancer Discovery
    • Cancer Discovery
    • Cancer Epidemiology, Biomarkers & Prevention
    • Cancer Immunology Research
    • Cancer Prevention Research
    • Cancer Research
    • Clinical Cancer Research
    • Molecular Cancer Research
    • Molecular Cancer Therapeutics

User menu

  • Register
  • Log in
  • My Cart

Search

  • Advanced search
Cancer Immunology Research
Cancer Immunology Research
  • Home
  • About
    • The Journal
    • AACR Journals
    • Subscriptions
    • Permissions and Reprints
    • Reviewing
  • Articles
    • OnlineFirst
    • Current Issue
    • Past Issues
    • Meeting Abstracts
    • Cancer Immunology Essentials
    • Collections
      • COVID-19 & Cancer Resource Center
      • Toolbox: Coding and Computation
      • Toolbox: Signatures and Cells
      • "Best of" Collection
      • Editors' Picks
  • For Authors
    • Information for Authors
    • Author Services
    • Best of: Author Profiles
    • Submit
  • Alerts
    • Table of Contents
    • Editors' Picks
    • OnlineFirst
    • Citation
    • Author/Keyword
    • RSS Feeds
    • My Alert Summary & Preferences
  • News
    • Cancer Discovery News
  • COVID-19
  • Webinars
  • Search More

    Advanced Search

Priority Brief

Checkpoint Blockade Immunotherapy Relies on T-bet but Not Eomes to Induce Effector Function in Tumor-Infiltrating CD8+ T Cells

Melissa M. Berrien-Elliott, Jinyun Yuan, Lauryn E. Swier, Stephanie R. Jackson, Collin L. Chen, Maureen J. Donlin and Ryan M. Teague
Melissa M. Berrien-Elliott
1Department of Molecular Microbiology and Immunology, Saint Louis University School of Medicine, St. Louis, Missouri.
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Jinyun Yuan
1Department of Molecular Microbiology and Immunology, Saint Louis University School of Medicine, St. Louis, Missouri.
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Lauryn E. Swier
1Department of Molecular Microbiology and Immunology, Saint Louis University School of Medicine, St. Louis, Missouri.
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Stephanie R. Jackson
1Department of Molecular Microbiology and Immunology, Saint Louis University School of Medicine, St. Louis, Missouri.
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Collin L. Chen
1Department of Molecular Microbiology and Immunology, Saint Louis University School of Medicine, St. Louis, Missouri.
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Maureen J. Donlin
1Department of Molecular Microbiology and Immunology, Saint Louis University School of Medicine, St. Louis, Missouri.
2Department of Biochemistry and Molecular Biology, Saint Louis University School of Medicine, St. Louis, Missouri.
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Ryan M. Teague
1Department of Molecular Microbiology and Immunology, Saint Louis University School of Medicine, St. Louis, Missouri.
3Saint Louis University Cancer Center, St. Louis, Missouri.
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
  • For correspondence: rteague@slu.edu
DOI: 10.1158/2326-6066.CIR-14-0159 Published February 2015
  • Article
  • Figures & Data
  • Info & Metrics
  • PDF
Loading

Article Figures & Data

Figures

  • Additional Files
  • Figure 1.
    • Download figure
    • Open in new tab
    • Download powerpoint
    Figure 1.

    T-bet is induced by combination checkpoint blockade. Naïve Gag-specific CD8+ T cells (CD90.1+) were transferred into B6 mice bearing an immunogenic FBL tumor (immune), Alb:Gag mice (tolerant), or Alb:Gag mice treated with checkpoint blockade antibodies (blockade). A, 2 days after transfer, T cells were FACS purified and RNA was isolated for gene expression analysis by microarray. Each square represents one biologic triplicate for each experimental condition. B, transferred CD8+ T cells from the indicated environments were FACS purified after 3 days in vivo, and relative gene expression assessed by qRT-PCR normalized to actin. Error bars depict SD. C, T-bet and Eomes intracellular protein expression was determined in Gag-reactive T cells 3 days after transfer into the indicated recipients. Quadrants were set based on T-bet and Eomes expression in naïve T cells from B6 mice (left). Inset numbers within contour plots are the percentage of CD90.1+ CD8+ cells in the quadrant fields. D, pooled data from three independent experiments showing the frequency of T-bet+ CD8+ T cells in recipient spleens 3 days after transfer. E, naïve WT (Embedded Image) or Tbx21−/− (Embedded Image) T cells were transferred into the tolerant or blockade environment and the total number of transferred T cells (CD8+ CD90.1+) in spleens was determined 4 days after infusion. Graph shows pooled data from two separate experiments. F, splenocytes were stimulated overnight and the frequency of CD8+ CD90.1+ T cells producing IFNγ was determined by intracellular flow cytometry; graphs are pooled from three experiments. G, the percentage of CD8+ CD90.1+ T cells expressing CXCR3 is graphed from two pooled experiments. Each circle represents individual recipient mice, horizontal lines depict the mean, and error bars indicate SEM, unless otherwise noted. P values are indicated for the bracketed groups (ns, not statistically significant).

  • Figure 2.
    • Download figure
    • Open in new tab
    • Download powerpoint
    Figure 2.

    T-bet is required for blockade-mediated T-cell effector function. FBL tumor-bearing Alb:Gag mice were infused with of WT, Tbx21−/−, or Eomesf/f Gag-reactive CD8+ T cells and treated on days −1, 1, and 3 with combination checkpoint blockade. A, diagram of experimental setup. B, 6 days after T-cell infusion, the total number of transferred CD90.1+ CD8+ T cells in recipient spleens was assessed. Data are pooled from three independent experiments. C, IFNγ production by transferred T cells was assessed after overnight restimulation with Gag peptide. Expression of CXCR3 on transferred T cells was determined directly ex vivo. Inset numbers represent the percentage of CD90.1+ CD8+ cells within the designated region. D, the frequency of IFNγ-producing CD90.1+ CD8+ T cells from three individual experiments is shown graphically. Circles represent individual recipients and horizontal lines show the mean of each group with P values indicated for the bracketed groups. E, 5 days after T-cell transfer, recipients were infused with a 1:1 ratio of Gag (eFluorlow) and control (eFluorhigh) peptide-pulsed target cells. Target-cell frequency in spleens was assessed 1 day later, with representative histograms shown. Inset numbers are the percentage of total target cells under the indicated region. F, the ratio of eFluorlow to eFluorhigh target cells is graphically displayed from two pooled experiments (n = 6 for each group). Error bars depict the SEM and P values are indicated for the bracketed groups.

  • Figure 3.
    • Download figure
    • Open in new tab
    • Download powerpoint
    Figure 3.

    T-bet is required for TIL effector function and immunotherapy but not for tumor infiltration. FBL tumor-bearing Alb:Gag mice were infused with of WT, Tbx21−/−, or Eomesf/f Gag-reactive CD8+ T cells and treated on days −1, 1, and 3 with combination checkpoint blockade. A, diagram of experimental setup for B–E, and example of tumor foci (inset box) on a representative liver at day 6. B, the frequency of transferred CD90.1+ CD8+ T cells among all TILs was assessed 6 days after T-cell infusion, and data pooled from three separate experiments and displayed graphically. C, IFNγ production by transferred T cells after overnight restimulation with Gag peptide and CXCR3 surface expression directly ex vivo were assessed. D, the ratio of CD90.1+ CD8+ T-cell frequency in TILs versus in spleens from the same recipients in Fig. 2B is shown. E, pooled data from three individual experiments showing the frequency of CD90.1+ CD8+ TILs producing IFNγ. Circles within all graphs represent individual recipient mice and horizontal lines show the mean of each group with P values indicated for the bracketed groups; all error bars represent SEM. F, survival of tumor-bearing Alb:Gag recipients was assessed following treatment with WT T cells only (gray line), checkpoint blockade (anti–CTLA-4/PD-1/LAG-3) only (dashed gray line), or checkpoint blockade and adoptive transfer of WT T cells (black line), Cxcr3−/− T cells (blue) or Tbx21−/− T cells (red). The graph displays pooled data from five independent experiments, showing percentage survival (y-axis) over time in days (x-axis). The n values denote the number of total mice per treatment group and the P value is indicated for the bracketed groups.

  • Figure 4.
    • Download figure
    • Open in new tab
    • Download powerpoint
    Figure 4.

    T-bet regulates expression of T-cell effector genes. FBL tumor-bearing Alb:Gag mice received a cotransfer of WT (CD90.1) and Tbx21−/− (CD90.1/CD90.2) Gag-reactive CD8+ T cells and were treated with combination checkpoint blockade on days −1, 1, and 3. A, 6 days after T-cell infusion, transferred T cells were isolated from the spleen and RNA isolated for analysis by qRT-PCR. Expression of the indicated genes from WT (closed bars) and Tbx21−/− (open bars) T cells is shown relative to the level of the same gene expressed in naïve Gag-reactive CD8+ T cells, which was arbitrarily set at a value of 1 and indicated by the dashed horizontal line. Results are representative of two independent experiments, and error bars represent SD among triplicate samples. B, MFI of T-bet, Eomes, and CCR5 from WT (closed bars), Tbx21−/− (open bars), and Eomesf/f (shaded bars) Gag-reactive CD8+ T cells from spleens and TILs 6 days after infusion into FBL tumor-bearing Alb:Gag mice treated with checkpoint blockade. Graphs display data from two pooled experiments and error bars indicate SEM with P values indicated for the bracketed groups. C, B6 or FBL tumor-bearing Alb:Gag mice were infused with T-bet-ZsGreen Gag-reactive CD8+ T cells and treated with checkpoint blockade antibodies on days −1, 1, and 3. Representative FACS plots display T-bet-ZsGreen expression on splenic CD8+ CD90.1+ cells 6 days after transfer. Inset numbers are the frequency of cells within the above region. D, pooled data from four independent experiments shows the frequency of CD8+ CD90.1+ T-bet-ZsGreen+ cells from indicated recipient mice. E, total CD8+ CD90.1+ T-bet-ZsGreen+ cell numbers pooled from four separate experiments are displayed graphically. Each circle represents an individual mouse and P values are indicated for the bracketed groups.

Additional Files

  • Figures
  • Supplementary Data

    Files in this Data Supplement:

    • Supplemental Figure S1 - Heat map of 53 selected genes differentially expressed in tolerant versus immune CD8+ T cells.
    • Supplemental Figure S2 - CXCR3 is not required for effector function under blockade conditions.
    • Supplemental Methods - Contains qPCR probe and antibody information.
PreviousNext
Back to top
Cancer Immunology Research: 3 (2)
February 2015
Volume 3, Issue 2
  • Table of Contents
  • Table of Contents (PDF)
  • About the Cover

Sign up for alerts

View this article with LENS

Open full page PDF
Article Alerts
Sign In to Email Alerts with your Email Address
Email Article

Thank you for sharing this Cancer Immunology Research article.

NOTE: We request your email address only to inform the recipient that it was you who recommended this article, and that it is not junk mail. We do not retain these email addresses.

Enter multiple addresses on separate lines or separate them with commas.
Checkpoint Blockade Immunotherapy Relies on T-bet but Not Eomes to Induce Effector Function in Tumor-Infiltrating CD8+ T Cells
(Your Name) has forwarded a page to you from Cancer Immunology Research
(Your Name) thought you would be interested in this article in Cancer Immunology Research.
CAPTCHA
This question is for testing whether or not you are a human visitor and to prevent automated spam submissions.
Citation Tools
Checkpoint Blockade Immunotherapy Relies on T-bet but Not Eomes to Induce Effector Function in Tumor-Infiltrating CD8+ T Cells
Melissa M. Berrien-Elliott, Jinyun Yuan, Lauryn E. Swier, Stephanie R. Jackson, Collin L. Chen, Maureen J. Donlin and Ryan M. Teague
Cancer Immunol Res February 1 2015 (3) (2) 116-124; DOI: 10.1158/2326-6066.CIR-14-0159

Citation Manager Formats

  • BibTeX
  • Bookends
  • EasyBib
  • EndNote (tagged)
  • EndNote 8 (xml)
  • Medlars
  • Mendeley
  • Papers
  • RefWorks Tagged
  • Ref Manager
  • RIS
  • Zotero
Share
Checkpoint Blockade Immunotherapy Relies on T-bet but Not Eomes to Induce Effector Function in Tumor-Infiltrating CD8+ T Cells
Melissa M. Berrien-Elliott, Jinyun Yuan, Lauryn E. Swier, Stephanie R. Jackson, Collin L. Chen, Maureen J. Donlin and Ryan M. Teague
Cancer Immunol Res February 1 2015 (3) (2) 116-124; DOI: 10.1158/2326-6066.CIR-14-0159
del.icio.us logo Digg logo Reddit logo Twitter logo CiteULike logo Facebook logo Google logo Mendeley logo
  • Tweet Widget
  • Facebook Like
  • Google Plus One

Jump to section

  • Article
    • Abstract
    • Introduction
    • Materials and Methods
    • Results and Discussion
    • Disclosure of Potential Conflicts of Interest
    • Disclaimer
    • Authors' Contributions
    • Grant Support
    • Footnotes
    • References
  • Figures & Data
  • Info & Metrics
  • PDF
Advertisement

Related Articles

Cited By...

More in this TOC Section

  • Inducing CTLs through DLnano-vaccines to Target Cancer
  • Targeted Inhibitors Increase T-cell Activation
  • Remodeling Translation Primes T-cell Tumor Control
Show more Priority Brief
  • Home
  • Alerts
  • Feedback
  • Privacy Policy
Facebook   Twitter   LinkedIn   YouTube   RSS

Articles

  • Online First
  • Current Issue
  • Past Issues
  • Cancer Immunology Essentials

Info for

  • Authors
  • Subscribers
  • Advertisers
  • Librarians

About Cancer Immunology Research

  • About the Journal
  • Editorial Board
  • Permissions
  • Submit a Manuscript
AACR logo

Copyright © 2021 by the American Association for Cancer Research.

Cancer Immunology Research
eISSN: 2326-6074
ISSN: 2326-6066

Advertisement