T-cell invigoration to tumour burden ratio associated with anti-PD-1 response

Journal name:
Nature
Volume:
545,
Pages:
60–65
Date published:
DOI:
doi:10.1038/nature22079
Received
Accepted
Published online
Corrected online

Abstract

Despite the success of monotherapies based on blockade of programmed cell death 1 (PD-1) in human melanoma, most patients do not experience durable clinical benefit. Pre-existing T-cell infiltration and/or the presence of PD-L1 in tumours may be used as indicators of clinical response; however, blood-based profiling to understand the mechanisms of PD-1 blockade has not been widely explored. Here we use immune profiling of peripheral blood from patients with stage IV melanoma before and after treatment with the PD-1-targeting antibody pembrolizumab and identify pharmacodynamic changes in circulating exhausted-phenotype CD8 T cells (Tex cells). Most of the patients demonstrated an immunological response to pembrolizumab. Clinical failure in many patients was not solely due to an inability to induce immune reinvigoration, but rather resulted from an imbalance between T-cell reinvigoration and tumour burden. The magnitude of reinvigoration of circulating Tex cells determined in relation to pretreatment tumour burden correlated with clinical response. By focused profiling of a mechanistically relevant circulating T-cell subpopulation calibrated to pretreatment disease burden, we identify a clinically accessible potential on-treatment predictor of response to PD-1 blockade.

At a glance

Figures

  1. CD8 T cells responding to anti-PD-1 therapy display an exhausted phenotype.
    Figure 1: CD8 T cells responding to anti-PD-1 therapy display an exhausted phenotype.

    a, Clinical responder (resp, complete response + partial response). NR, non-responder (stable disease + progressive disease). b, Ki67 expression in CD8 T cells at indicated times (n = 29). c, Expression of the indicated markers in Ki67+ (green) and Ki67 (blue) CD8 T cells at 3 weeks (n = 27). d, Ki67 expression in PD-1+ (red) and PD-1 (blue) CD8 T cells at 3 weeks (n = 27). e, Ki67 expression in PD-1+ (red) and PD-1 (blue) CD8 T cells at indicated times (n = 29). f, Fold change of Ki67 expression at peak of immunologic response versus pretreatment. Dotted line denotes fold change of 2.21, which is the mean plus 3 s.d. in healthy donors (see Extended Data Fig. 3d). *P < 0.05, ***P < 0.001, ****P < 0.0001, Wilcoxon matched-pairs test. Error bars, s.d. Flow cytometry data in all panels are representative of 1–4 independent technical replicates of the stain indicated.

  2. Exhausted-phenotype CD8 T cells are preferentially reinvigorated by anti-PD-1 therapy.
    Figure 2: Exhausted-phenotype CD8 T cells are preferentially reinvigorated by anti-PD-1 therapy.

    a, Marker expression in PD-1+CTLA-4+ CD8 T cells at 3 weeks (paired t-test; n = 27). b, Representative plots. c, Ki67 expression in CD8 T cells expressing inhibitory receptors. Bars indicate differences (paired t-test and Wilcoxon matched-pairs test; n = 27). d, Heat map shows effector, memory, and exhausted nodes from SPADE, hierarchically clustered. e, SPADE for median mass intensities (MMI) of granzyme B (left) and perforin (right) at week 3 (n = 4). f, MMI of cytolytic markers in Teff, Tmem, and Tex cells at 3 weeks (gated on PD-1+CD8+). g, MMI of cytolytic markers in Tex cells over time. GzmA, GzmB and GzmK indicate granzymes A, B and K, respectively. h, RNA-seq of total CD8 T cells (n = 3; see Methods). Gene set enrichment analysis of top 50 positive correlates of Ki67, and leading edge of positive (top) or negative (bottom) correlates of Ki67 that were enriched in anti-PD-L1-treated versus control Tex-cell signatures from ref. 19 (bottom). NES, normalized enrichment score. ***P < 0.001, ****P < 0.0001. Error bars, s.d. Flow cytometry data (ac) are representative of 1–4 independent technical replicates of the stain indicated. Mass cytometry data and RNA-seq data (dh) are representative of one technical replicate.

  3. Tumour-infiltrating T-cell clones in responding peripheral blood CD8 T-cell population and blood Ki67+ CD8 T-cell response correlates with tumour burden.
    Figure 3: Tumour-infiltrating T-cell clones in responding peripheral blood CD8 T-cell population and blood Ki67+ CD8 T-cell response correlates with tumour burden.

    ac, TCR sequencing on CD8 T cells (see Methods). a, Frequency of clones in blood and among top 10 clones in tumour (red). Clones only in blood or tumour in grey (P value; Fisher’s exact test). PBMCs, peripheral blood mononuclear cells. b, Frequencies of top 10 blood clones and those shared with top 10 tumour-infiltrating T-cell clones (red arrows). All shared clones were HLA-DR+CD38+ (maroon). c, Proportion of HLA-DR+CD38+ clones among top 100 clones in blood shared versus not shared with top 10 TIL clones. d, Example CT scans of high (top) or low (bottom) tumour burden, and Ki67 expression in blood CD8 T cells. e, Top 39 immune parameters correlated with tumour burden by random forest analysis at week 3 (top). Heat map of top five parameters (bottom). f, Pearson correlation of tumour burden to Ki67 expression pretreatment and maximum post-treatment in indicated cells (n = 25 pretreatment, 23 post-treatment). TCR sequencing data (ac) are representative of one technical replicate. r and P values, Pearson’s correlations.

  4. Tracking CD8 T-cell reinvigoration in context of tumour burden predicts response to anti-PD-1 therapy.
    Figure 4: Tracking CD8 T-cell reinvigoration in context of tumour burden predicts response to anti-PD-1 therapy.

    a, Overall survival of patients with high (n = 11) and low (n = 14) expression of Ki67 (top), or high (n = 9) and low (n = 16) tumour burden (bottom). Cut-points by CART analysis (see Methods). b, c, Plasma cytokines by response and clinical benefit (Mann–Whitney U-test; progression n = 8, clinical benefit n = 9). CR, complete response; PD, progressive disease; SD, stable disease. d, Objective response rate for high and low ratio of Ki67 to tumour burden (left), tumour burden versus Ki67 by LOS (landmark overall survival) (centre), and Kaplan–Meier overall survival stratified by post-treatment Ki67 to tumour burden ratio (right). Objective response by Fischer’s exact test (Ki67 to tumour burden ratio: high, n = 13; low, n = 10). Kaplan–Meier data (Ki67 to tumour burden ratio: high, n = 13; low, n = 12). eg, Independent Keynote 001 trial. e, f, Ki67 in indicated subsets (n = 18; paired t-test (left), Wilcoxon matched-pairs test (right)). g, Objective response rate for high and low Ki67 to tumour burden ratio (left), Ki67 versus tumour burden by LOS (centre) (n = 18), and Kaplan–Meier overall survival for high versus low post-treatment Ki67 expression to tumour burden (right). Objective response by Fischer’s exact test (Ki67 to tumour burden ratio: high, n = 11; low, n = 7). Kaplan–Meier overall survival (Ki67 to tumour burden ratio: high, n = 11; low, n = 7). ***P < 0.001, ****P < 0.0001. Error bars, s.d. Cytokine data (b, c) are representative of two technical replicates. MSKCC flow data (eg) are representative of two technical replicates.

  5. Clinical characteristics, response data, and immune data for cohorts analysed.
    Extended Data Fig. 1: Clinical characteristics, response data, and immune data for cohorts analysed.

    a, Penn pembro Expanded Access Program (left) and MSKCC Keynote-001 trial (right) that were included in analysis. b, Immune and clinical data from analysed patients in Penn cohort stratified by fold change Ki67 greater or less than 2.2 (blue, responder; red, non-responder).

  6. CD4+FOXP3−, CD4+FOXP3+ and CD8 T cells from patients with melanoma have increased Ki67 expression compared to healthy donors.
    Extended Data Fig. 2: CD4+FOXP3, CD4+FOXP3+ and CD8 T cells from patients with melanoma have increased Ki67 expression compared to healthy donors.

    a, Frequency and Ki67 expression in FOXP3+ CD4 T cells in healthy donors and melanoma patients. Student’s t-test. b, Ki67 expression in CD8 T cells between healthy donors and melanoma patients. Mann–Whitney U-test. c, Ki67 expression in PD-1+ and PD-1 CD8 T cells in healthy donors and patients with melanoma. Healthy donors versus patients, Mann–Whitney U-test; PD-1+ versus PD-1 CD8 T cells in patients with melanoma, Wilcoxon matched-pairs test. d, Ki67 expression in FOXP3 CD4 T cells and FOXP3+ CD4 cells over time. Wilcoxon matched-pairs test. e, Scatter plot of Ki67 expression in PD-1+CD4+FOXP3 T cells versus tumour burden by PFS. f, Ki67 expression in PD-1+CD4+FOXP3+ cells versus tumour burden by PFS (pretreatment, n = 29; post-treatment, n = 27 (e, f)). For all panels, **P < 0.01, ****P < 0.0001. Error bars denote s.d. Flow cytometry data in all panels are representative of 1–4 independent technical replicates of the stain indicated.

  7. PD-1 detected after therapy using anti-human IgG4 and proliferating CD8 T cells in healthy donors.
    Extended Data Fig. 3: PD-1 detected after therapy using anti-human IgG4 and proliferating CD8 T cells in healthy donors.

    a, Healthy donor PBMCs were incubated with anti-PD-1 clone EH12 BV421 and/or pembro—alone, together or sequentially followed by anti-human IgG4–phycoerythrin. b, Plots of Eomes, T-bet, CD45RA, and CD27 expression in Ki67+ CD8 T cells from a representative healthy donor. c, Comparison of Eomes versus T-bet and CD45RA versus CD27 phenotypes in patients with melanoma and healthy donors (melanoma, n = 25; healthy donor, n = 10). **P < 0.01, Student’s t-test. d, Mean fold change of Ki67 on PD-1+ CD8 T cells over 3 weeks in healthy donors (n = 7). Error bars denote s.d.; centre line denotes mean; dotted line denotes fold change of 2.21, which is equal to the mean + 3 s.d. Flow cytometry data in all panels are representative of 1–2 independent technical replicates of the stain indicated.

  8. Effect of anti-CTLA-4 therapy on Ki67 expression is restricted to the pretreatment time point.
    Extended Data Fig. 4: Effect of anti-CTLA-4 therapy on Ki67 expression is restricted to the pretreatment time point.

    a, Correlation of the percentage of PD-1+ CD8 T cells expressing Ki67 to months since last dose of anti-CTLA-4 (pretreatment, n = 26; week 3, n = 25). b, Correlation of the percentage of CTLA-4 in CD8 T cells and months since last dose of anti-CTLA-4 (pretreatment, n = 26; week 3, n = 25). c, Correlation of clinical parameters such as PFS, overall survival (OS), tumour burden, and Ki67 to tumour burden ratio with months since last dose of anti-CTLA-4 (pretreatment, n = 23; week 3, n = 22). r and P values, Pearson’s correlations.

  9. CD8 T cells with multiple inhibitory receptors and PD-1+CXCR5+ CD8 T cells are reinvigorated by anti-PD-1 therapy.
    Extended Data Fig. 5: CD8 T cells with multiple inhibitory receptors and PD-1+CXCR5+ CD8 T cells are reinvigorated by anti-PD-1 therapy.

    a, Ki67 expression in CD8 T cells with multiple inhibitory receptors over time. Week 0 versus week 3 (n = 27). Wilcoxon matched-pairs test. b, Percentage of CD8 T cells positive for PD-1 during pembro treatment (n = 27), Wilcoxon matched-pairs test. c, Back-gating of TEMRA and naive CD8 T-cell populations onto CD45RA versus TCF-1 (right). d, TCF-1 expression in PD-1+CXCR5+ CD8 T cells in blood at week 3 (n = 11). Paired t-test. e, Eomes/T-bet (red) and Eomes/TCF-1 (green) expression in PD-1+CXCR5+ (left) and PD-1+CTLA-4+ (right) subsets. f, Ki67 expression in PD-1+CTLA-4+ and PD-1+CXCR5+ CD8 T cells over time (left) and fold change of Ki67 in PD-1+CXCR5+ and PD-1+CTLA-4+ subsets (right) (n = 11). Wilcoxon matched-pairs test. g, IFNγ production by PD-1+CXCR5+ and PD-1+CTLA-4+ subsets over time; paired t-test. For all panels, *P < 0.05, **P < 0.01, ***P < 0.001, ****P < 0.0001. Error bars denote s.d. CXCR5 and TCF-1 stain is representative of one technical replicate. All other flow cytometry data are representative of 1–4 independent technical replicates of the stain indicated.

  10. Conventional differentiation state and clusters of Tex cells can be identified using CyTOF and high-dimensional visualization.
    Extended Data Fig. 6: Conventional differentiation state and clusters of Tex cells can be identified using CyTOF and high-dimensional visualization.

    ac, SPADE analysis applied to blood samples from patients with melanoma and analysed by CyTOF. a, SPADE tree showing MMI of CD27 (left) and CCR7 (right) (representative of 4 patients). b, SPADE tree coloured by median intensities of fold change frequency (left), and Ki67 expression (middle and right) before treatment and at 3 weeks. c, Fold change frequency (left) and MMI of Ki67 (right) of Tex, Tmem, and Teff subsets. d, Frequency of Tex cluster in PD-1+ CD8 T cells over time. e, SPADE tree coloured by MMI of Eomes (left) and CD39 (right) expression at 3 weeks (n = 4). f, MMI of Eomes (left) and CD39 (right) of Tex, Tmem, and Teff subsets. g, Percentage of cells in Tex cluster (left) and Teff cluster (right) in PD-1+ CD8 T cells over time based on CyTOF and SPADE analysis. h, Frequency of Tex versus tumour burden coloured by response. Mass cytometry data in all panels are representative of one technical replicate. MMI shown in this figure represents arcsinh transformed data.

  11. RNA-seq of CD8 T cells reveals molecular pathways correlating with reinvigoration.
    Extended Data Fig. 7: RNA-seq of CD8 T cells reveals molecular pathways correlating with reinvigoration.

    ad, RNA-seq was performed on total purified CD8 T cells from three patients at weeks 0, 3, 9, 12. a, Volcano plot of genes altered at 3 weeks compared to pretreatment. Volcano plot constructed using log2 fold changes and their P values of all genes. b, Pathways identified by gene ontology analysis that were altered at week 3 compared to pretreatment using top 50 differentially expressed genes (all genes with fold change >1.5 and P < 0.05). c, Correlation coefficients to Ki67 were used to generate a correlation network. Nodes coloured by strength of correlation to Ki67 (Pearson r = 1 (red), −1 (blue)); node size indicates degree of connectivity. d, Pathways identified by gene ontology analysis using top 100 correlated genes with Ki67 (positive and negatively correlated genes with correlation coefficients >0.67 and <−0.67). RNA sequencing data in all panels are representative of one technical replicate.

  12. HLA-DR and CD38 expression enriches for responding Ki67+ cells and TCR clones found in top 100 clones in tumour identified in blood.
    Extended Data Fig. 8: HLA-DR and CD38 expression enriches for responding Ki67+ cells and TCR clones found in top 100 clones in tumour identified in blood.

    a, TCR clones present at pretreatment and post-treatment that are also in the top 100 clones in the tumour. Clones that are among the top 10 in the peripheral blood post treatment highlighted in red. Patient 14–784 did not have an available pretreatment sample and was not included. b, Percentage of CD8 T cells that are Ki67+ (red) and HLA-DR+CD38+ (blue) over time. c, Representative plot of Ki67 expression in HLA-DR+CD38+ CD8 T cells and CD8 T cells that were not CD38+HLA-DR+ (that is, CD38HLA-DR, CD38+HLA-DR, and CD38HLA-DR+). d, Representative plot of HLA-DR and CD38 expression on Ki67+ and Ki67 CD8 T cells. e, Representative plot of Eomes versus T-bet and PD-1 versus CTLA-4 in HLA-DR+CD38+ (‘DR+38+’) CD8 T-cell subsets and cells that were not CD38+HLA-DR+. f, Percentage of EomeshiT-betlo, PD-1, CTLA-4 and expression on CD8 T cells (n = 5). TCR sequencing and flow cytometry data in all panels are representative of one technical replicate.

  13. High Ki67 to tumour burden ratio correlates with improved clinical outcomes and model selection identifies BRAF and lactate dehydrogenase as correlates to Ki67.
    Extended Data Fig. 9: High Ki67 to tumour burden ratio correlates with improved clinical outcomes and model selection identifies BRAF and lactate dehydrogenase as correlates to Ki67.

    a, Scatter plot of maximum fold change of Ki67 expression after treatment versus tumour burden stratified by PFS (n = 23). b, Maximum post-treatment Ki67 expression versus tumour burden by response (n = 23). c, Ki67 expression to tumour burden ratio stratified by landmark PFS (PFS starting from 6 weeks into therapy) (left; n = 23). Kaplan–Meier analysis stratified by a Ki67 to tumour burden ratio of 1.94 (right; Ki67 to tumour burden ratio: high, n = 13; low, n = 10); log-rank test. d, Baysean Information Criteria (BIC), used as a criterion for selection of multiple regression models that best predicted Ki67 (low BIC score produces a stronger model). e, Percentage of Ki67 expression in CD8 T cells (left) and tumour burden (right) stratified by BRAF status. All BRAF+ patients had been treated with BRAF-targeted therapy (n = 4, after removal of patients with unmeasurable tumour burden); Mann–Whitney U-test. f, Correlation of percentage Ki67+ versus lactate dehydrogenase (LDH) (left) and tumour burden versus LDH (right); Pearson’s correlation. g, Ki67 to LDH ratio stratified by landmark overall survival (overall survival starting from 6 weeks into therapy) (left; n = 23). Kaplan–Meier analysis stratified by a Ki67 to LDH ratio of 0.065 (right; Ki67 to LDH ratio: high, n = 18; low, n = 5); log-rank test.

  14. T-cell reinvigoration in the context of tumour burden may more accurately reflect the immunobiology of anti-PD-1 patterns of resistance (red) and response (green).
    Extended Data Fig. 10: T-cell reinvigoration in the context of tumour burden may more accurately reflect the immunobiology of anti-PD-1 patterns of resistance (red) and response (green).

Change history

Corrected online 27 April 2017
In Fig. 1c the x-axis label for the bottom bar graph was corrected.

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Author information

  1. These authors contributed equally to this work.

    • Michael A. Postow &
    • Robert J. Orlowski
  2. These authors jointly supervised this work.

    • Tara C. Gangadhar &
    • E. John Wherry

Affiliations

  1. Department of Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, USA

    • Alexander C. Huang,
    • Robert J. Orlowski,
    • Wei Xu,
    • Shannon Harmon,
    • Brandon Wenz,
    • Bradley Wubbenhorst,
    • Kurt D’Andrea,
    • Ramin S. Herati,
    • Suzanne McGettigan,
    • Shawn Kothari,
    • Robert H. Vonderheide,
    • Ravi K. Amaravadi,
    • Lynn M. Schuchter,
    • Katherine L. Nathanson &
    • Tara C. Gangadhar
  2. Institute for Immunology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, USA

    • Alexander C. Huang,
    • Robert J. Orlowski,
    • Bertram Bengsch,
    • Sasikanth Manne,
    • Josephine R. Giles,
    • Felix Quagliarello,
    • Kristen E. Pauken,
    • Ramin S. Herati,
    • Ryan P. Staupe,
    • Sangeeth M. George,
    • Robert H. Vonderheide &
    • E. John Wherry
  3. Abramson Cancer Center, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, USA

    • Alexander C. Huang,
    • Robert J. Orlowski,
    • Rosemarie Mick,
    • Wei Xu,
    • Shannon Harmon,
    • Brandon Wenz,
    • Bradley Wubbenhorst,
    • Kurt D’Andrea,
    • Ramin S. Herati,
    • Suzanne McGettigan,
    • Robert H. Vonderheide,
    • Ravi K. Amaravadi,
    • Giorgos C. Karakousis,
    • Lynn M. Schuchter,
    • Xiaowei Xu,
    • Katherine L. Nathanson,
    • Tara C. Gangadhar &
    • E. John Wherry
  4. Parker Institute for Cancer Immunotherapy at University of Pennsylvania, Philadelphia, Pennsylvania, USA

    • Alexander C. Huang,
    • Robert J. Orlowski,
    • Rosemarie Mick,
    • Bertram Bengsch,
    • Josephine R. Giles,
    • Sangeeth M. George,
    • Robert H. Vonderheide,
    • Katherine L. Nathanson &
    • E. John Wherry
  5. Department of Medicine, Memorial Sloan Kettering Cancer Center, New York, New York, USA

    • Michael A. Postow,
    • Cristina Carrera &
    • Jedd D. Wolchok
  6. Weill Cornell Medical College, New York, New York, USA

    • Michael A. Postow
  7. Department of Biostatistics and Epidemiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, USA

    • Rosemarie Mick
  8. Department of Microbiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, USA

    • Bertram Bengsch,
    • Sasikanth Manne,
    • Josephine R. Giles,
    • Felix Quagliarello,
    • Kristen E. Pauken,
    • Ryan P. Staupe,
    • Sangeeth M. George &
    • E. John Wherry
  9. Immune Monitoring Facility, Ludwig Center for Cancer Immunotherapy, Memorial Sloan Kettering Cancer Center, New York, New York, USA

    • Matthew Adamow &
    • Phillip Wong
  10. Department of Epidemiology and Biostatistics, Memorial Sloan Kettering Cancer Center, New York, New York, USA

    • Deborah Kuk &
    • Katherine S. Panageas
  11. Department of Dermatology, Hospital Clínic de Barcelona, Institut d’Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), University of Barcelona and Centro de Investigación Biomédica en Red de Enfermedades Raras (CIBERER), Barcelona, Spain

    • Cristina Carrera
  12. Parker Institute for Cancer Immunotherapy at Memorial Sloan Kettering Cancer Center, New York, New York, USA

    • Phillip Wong &
    • Jedd D. Wolchok
  13. Department of Pathology, Brigham and Women’s Hospital, Boston, Massachusetts, USA

    • Jason M. Schenkel
  14. Department of Surgery, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, USA

    • Giorgos C. Karakousis
  15. Department of Pathology and Laboratory Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, USA

    • Xiaowei Xu

Contributions

A.C.H. and E.J.W. conceived and designed the overall studies. A.C.H. and T.C.G. designed and implemented the clinical trial at Penn and T.C.G. was principal investigator of this clinical trial. M.A.P., M.A., D.K., C.C., P.W. and J.D.W. designed, executed and performed immune assessment on the MSKCC trial and M.A.P. was principal investigator of this clinical trial. A.C.H. performed immune assessment assays with R.J.O., B.B., J.R.G., F.Q., K.E.P., R.S.H., R.P.S., S.K., J.M.S., and S.M.G. R.M. and K.S.P. performed biostatistical analyses. S.M. and J.R.G. performed computational analyses of immune profiling and RNA-seq. B.We., B.Wu., K.D’A. and K.L.N. performed mutational analysis and neoepitope prediction. W.X., S.H., and S.M. assisted in the Penn clinical trial. R.K.A., G.C.K. and L.M.S. were investigators on the trial. X.X. evaluated pathological biomarkers. A.C.H., R.H.V., T.C.G. and E.J.W. interpreted the data. A.C.H. and E.J.W. wrote the manuscript, and M.A.P., R.M., T.C.G. edited the manuscript. E.J.W. designed, interpreted, and oversaw the study.

Competing financial interests

M.A.P. receives honoraria and/or research support from BMS, Merck, Novartis, Array, Infinity, and RGenix. J.D.W. receives honoraria and/or research support from Merck, BMS, and Genentech. T.C.G. receives honoraria and/or research support from BMS, Novartis, Merck, Incyte, and Roche. R.J.O. has anticipated employment at Merck. E.J.W. receives honoraria and/or research support from BMS, Merck, MedImmune, Surface Oncology, Takeda, and KyMab. E.J.W. has a patent licensing agreement for the PD-1 pathway.

Corresponding authors

Correspondence to:

Reviewer Information Nature thanks A. Alizadeh, V. Boussiotis and T. Tueting for their contribution to the peer review of this work.

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Extended data figures and tables

Extended Data Figures

  1. Extended Data Figure 1: Clinical characteristics, response data, and immune data for cohorts analysed. (381 KB)

    a, Penn pembro Expanded Access Program (left) and MSKCC Keynote-001 trial (right) that were included in analysis. b, Immune and clinical data from analysed patients in Penn cohort stratified by fold change Ki67 greater or less than 2.2 (blue, responder; red, non-responder).

  2. Extended Data Figure 2: CD4+FOXP3, CD4+FOXP3+ and CD8 T cells from patients with melanoma have increased Ki67 expression compared to healthy donors. (255 KB)

    a, Frequency and Ki67 expression in FOXP3+ CD4 T cells in healthy donors and melanoma patients. Student’s t-test. b, Ki67 expression in CD8 T cells between healthy donors and melanoma patients. Mann–Whitney U-test. c, Ki67 expression in PD-1+ and PD-1 CD8 T cells in healthy donors and patients with melanoma. Healthy donors versus patients, Mann–Whitney U-test; PD-1+ versus PD-1 CD8 T cells in patients with melanoma, Wilcoxon matched-pairs test. d, Ki67 expression in FOXP3 CD4 T cells and FOXP3+ CD4 cells over time. Wilcoxon matched-pairs test. e, Scatter plot of Ki67 expression in PD-1+CD4+FOXP3 T cells versus tumour burden by PFS. f, Ki67 expression in PD-1+CD4+FOXP3+ cells versus tumour burden by PFS (pretreatment, n = 29; post-treatment, n = 27 (e, f)). For all panels, **P < 0.01, ****P < 0.0001. Error bars denote s.d. Flow cytometry data in all panels are representative of 1–4 independent technical replicates of the stain indicated.

  3. Extended Data Figure 3: PD-1 detected after therapy using anti-human IgG4 and proliferating CD8 T cells in healthy donors. (275 KB)

    a, Healthy donor PBMCs were incubated with anti-PD-1 clone EH12 BV421 and/or pembro—alone, together or sequentially followed by anti-human IgG4–phycoerythrin. b, Plots of Eomes, T-bet, CD45RA, and CD27 expression in Ki67+ CD8 T cells from a representative healthy donor. c, Comparison of Eomes versus T-bet and CD45RA versus CD27 phenotypes in patients with melanoma and healthy donors (melanoma, n = 25; healthy donor, n = 10). **P < 0.01, Student’s t-test. d, Mean fold change of Ki67 on PD-1+ CD8 T cells over 3 weeks in healthy donors (n = 7). Error bars denote s.d.; centre line denotes mean; dotted line denotes fold change of 2.21, which is equal to the mean + 3 s.d. Flow cytometry data in all panels are representative of 1–2 independent technical replicates of the stain indicated.

  4. Extended Data Figure 4: Effect of anti-CTLA-4 therapy on Ki67 expression is restricted to the pretreatment time point. (144 KB)

    a, Correlation of the percentage of PD-1+ CD8 T cells expressing Ki67 to months since last dose of anti-CTLA-4 (pretreatment, n = 26; week 3, n = 25). b, Correlation of the percentage of CTLA-4 in CD8 T cells and months since last dose of anti-CTLA-4 (pretreatment, n = 26; week 3, n = 25). c, Correlation of clinical parameters such as PFS, overall survival (OS), tumour burden, and Ki67 to tumour burden ratio with months since last dose of anti-CTLA-4 (pretreatment, n = 23; week 3, n = 22). r and P values, Pearson’s correlations.

  5. Extended Data Figure 5: CD8 T cells with multiple inhibitory receptors and PD-1+CXCR5+ CD8 T cells are reinvigorated by anti-PD-1 therapy. (236 KB)

    a, Ki67 expression in CD8 T cells with multiple inhibitory receptors over time. Week 0 versus week 3 (n = 27). Wilcoxon matched-pairs test. b, Percentage of CD8 T cells positive for PD-1 during pembro treatment (n = 27), Wilcoxon matched-pairs test. c, Back-gating of TEMRA and naive CD8 T-cell populations onto CD45RA versus TCF-1 (right). d, TCF-1 expression in PD-1+CXCR5+ CD8 T cells in blood at week 3 (n = 11). Paired t-test. e, Eomes/T-bet (red) and Eomes/TCF-1 (green) expression in PD-1+CXCR5+ (left) and PD-1+CTLA-4+ (right) subsets. f, Ki67 expression in PD-1+CTLA-4+ and PD-1+CXCR5+ CD8 T cells over time (left) and fold change of Ki67 in PD-1+CXCR5+ and PD-1+CTLA-4+ subsets (right) (n = 11). Wilcoxon matched-pairs test. g, IFNγ production by PD-1+CXCR5+ and PD-1+CTLA-4+ subsets over time; paired t-test. For all panels, *P < 0.05, **P < 0.01, ***P < 0.001, ****P < 0.0001. Error bars denote s.d. CXCR5 and TCF-1 stain is representative of one technical replicate. All other flow cytometry data are representative of 1–4 independent technical replicates of the stain indicated.

  6. Extended Data Figure 6: Conventional differentiation state and clusters of Tex cells can be identified using CyTOF and high-dimensional visualization. (343 KB)

    ac, SPADE analysis applied to blood samples from patients with melanoma and analysed by CyTOF. a, SPADE tree showing MMI of CD27 (left) and CCR7 (right) (representative of 4 patients). b, SPADE tree coloured by median intensities of fold change frequency (left), and Ki67 expression (middle and right) before treatment and at 3 weeks. c, Fold change frequency (left) and MMI of Ki67 (right) of Tex, Tmem, and Teff subsets. d, Frequency of Tex cluster in PD-1+ CD8 T cells over time. e, SPADE tree coloured by MMI of Eomes (left) and CD39 (right) expression at 3 weeks (n = 4). f, MMI of Eomes (left) and CD39 (right) of Tex, Tmem, and Teff subsets. g, Percentage of cells in Tex cluster (left) and Teff cluster (right) in PD-1+ CD8 T cells over time based on CyTOF and SPADE analysis. h, Frequency of Tex versus tumour burden coloured by response. Mass cytometry data in all panels are representative of one technical replicate. MMI shown in this figure represents arcsinh transformed data.

  7. Extended Data Figure 7: RNA-seq of CD8 T cells reveals molecular pathways correlating with reinvigoration. (353 KB)

    ad, RNA-seq was performed on total purified CD8 T cells from three patients at weeks 0, 3, 9, 12. a, Volcano plot of genes altered at 3 weeks compared to pretreatment. Volcano plot constructed using log2 fold changes and their P values of all genes. b, Pathways identified by gene ontology analysis that were altered at week 3 compared to pretreatment using top 50 differentially expressed genes (all genes with fold change >1.5 and P < 0.05). c, Correlation coefficients to Ki67 were used to generate a correlation network. Nodes coloured by strength of correlation to Ki67 (Pearson r = 1 (red), −1 (blue)); node size indicates degree of connectivity. d, Pathways identified by gene ontology analysis using top 100 correlated genes with Ki67 (positive and negatively correlated genes with correlation coefficients >0.67 and <−0.67). RNA sequencing data in all panels are representative of one technical replicate.

  8. Extended Data Figure 8: HLA-DR and CD38 expression enriches for responding Ki67+ cells and TCR clones found in top 100 clones in tumour identified in blood. (352 KB)

    a, TCR clones present at pretreatment and post-treatment that are also in the top 100 clones in the tumour. Clones that are among the top 10 in the peripheral blood post treatment highlighted in red. Patient 14–784 did not have an available pretreatment sample and was not included. b, Percentage of CD8 T cells that are Ki67+ (red) and HLA-DR+CD38+ (blue) over time. c, Representative plot of Ki67 expression in HLA-DR+CD38+ CD8 T cells and CD8 T cells that were not CD38+HLA-DR+ (that is, CD38HLA-DR, CD38+HLA-DR, and CD38HLA-DR+). d, Representative plot of HLA-DR and CD38 expression on Ki67+ and Ki67 CD8 T cells. e, Representative plot of Eomes versus T-bet and PD-1 versus CTLA-4 in HLA-DR+CD38+ (‘DR+38+’) CD8 T-cell subsets and cells that were not CD38+HLA-DR+. f, Percentage of EomeshiT-betlo, PD-1, CTLA-4 and expression on CD8 T cells (n = 5). TCR sequencing and flow cytometry data in all panels are representative of one technical replicate.

  9. Extended Data Figure 9: High Ki67 to tumour burden ratio correlates with improved clinical outcomes and model selection identifies BRAF and lactate dehydrogenase as correlates to Ki67. (387 KB)

    a, Scatter plot of maximum fold change of Ki67 expression after treatment versus tumour burden stratified by PFS (n = 23). b, Maximum post-treatment Ki67 expression versus tumour burden by response (n = 23). c, Ki67 expression to tumour burden ratio stratified by landmark PFS (PFS starting from 6 weeks into therapy) (left; n = 23). Kaplan–Meier analysis stratified by a Ki67 to tumour burden ratio of 1.94 (right; Ki67 to tumour burden ratio: high, n = 13; low, n = 10); log-rank test. d, Baysean Information Criteria (BIC), used as a criterion for selection of multiple regression models that best predicted Ki67 (low BIC score produces a stronger model). e, Percentage of Ki67 expression in CD8 T cells (left) and tumour burden (right) stratified by BRAF status. All BRAF+ patients had been treated with BRAF-targeted therapy (n = 4, after removal of patients with unmeasurable tumour burden); Mann–Whitney U-test. f, Correlation of percentage Ki67+ versus lactate dehydrogenase (LDH) (left) and tumour burden versus LDH (right); Pearson’s correlation. g, Ki67 to LDH ratio stratified by landmark overall survival (overall survival starting from 6 weeks into therapy) (left; n = 23). Kaplan–Meier analysis stratified by a Ki67 to LDH ratio of 0.065 (right; Ki67 to LDH ratio: high, n = 18; low, n = 5); log-rank test.

  10. Extended Data Figure 10: T-cell reinvigoration in the context of tumour burden may more accurately reflect the immunobiology of anti-PD-1 patterns of resistance (red) and response (green). (255 KB)

Supplementary information

PDF files

  1. Supplementary Information (270 KB)

    This file contains Supplementary Tables 1-3.

Additional data