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PD-1 blockade induces responses by inhibiting adaptive immune resistance

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Therapies that target the programmed death-1 (PD-1) receptor have shown unprecedented rates of durable clinical responses in patients with various cancer types1,2,3,4,5. One mechanism by which cancer tissues limit the host immune response is via upregulation of PD-1 ligand (PD-L1) and its ligation to PD-1 on antigen-specific CD8+ T cells (termed adaptive immune resistance)6,7. Here we show that pre-existing CD8+ T cells distinctly located at the invasive tumour margin are associated with expression of the PD-1/PD-L1 immune inhibitory axis and may predict response to therapy. We analysed samples from 46 patients with metastatic melanoma obtained before and during anti-PD-1 therapy (pembrolizumab) using quantitative immunohistochemistry, quantitative multiplex immunofluorescence, and next-generation sequencing for T-cell antigen receptors (TCRs). In serially sampled tumours, patients responding to treatment showed proliferation of intratumoral CD8+ T cells that directly correlated with radiographic reduction in tumour size. Pre-treatment samples obtained from responding patients showed higher numbers of CD8-, PD-1- and PD-L1-expressing cells at the invasive tumour margin and inside tumours, with close proximity between PD-1 and PD-L1, and a more clonal TCR repertoire. Using multivariate analysis, we established a predictive model based on CD8 expression at the invasive margin and validated the model in an independent cohort of 15 patients. Our findings indicate that tumour regression after therapeutic PD-1 blockade requires pre-existing CD8+ T cells that are negatively regulated by PD-1/PD-L1-mediated adaptive immune resistance.

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Figure 1: Immunohistochemical analysis of CD8+ T cells in samples obtained before and during pembrolizumab treatment.
Figure 2: Regressing tumours during treatment are associated with proliferating CD8+ T cells that localize to the tumour.
Figure 3: Baseline density, location and proximity of CD8+, PD-1+, PD-L1+ and CD4+ cells, and T-cell repertoire according to treatment outcome.

Change history

  • 27 November 2014

    Extended Data Fig. 3 was revised to include missing labels on panel e.


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This study was funded in part by National Institutes of Health grants K08 AI091663, Kure It Research Grant, UL1TR000124 (to P.C.T.), P01 CA168585, U54 CA119347, R01 CA170689, the Ressler Family Fund, the Dr Robert Vigen Memorial Fund, the Wesley Coyle Memorial Fund, and the Garcia-Corsini Family Fund (to A.R.), P30 CA16042 to D.A.E. A.R. was supported by a Stand Up To Cancer—Cancer Research Institute Cancer Immunology Dream Team Translational Research Grant (SU2C-AACR-DT1012). Stand Up To Cancer is a program of the Entertainment Industry Foundation administered by the American Association for Cancer Research. M.S. was supported as a Howard Hughes Medical Institute Medical Research Fellow. Some of the studies were funded by Merck Sharp and Dome and by Adaptive Biotechnologies. L.R. was supported by the V Foundation-Gil Nickel Family Endowed Fellowship in Melanoma Research and a grant from the Spanish Society of Medical Oncology for Translational Research in Reference Centers. We acknowledge the Translational Pathology Core Laboratory for tissue sectioning and slide scanning, S. Roy, N. Kamsu-Kom, R. Guo, J. Pang, W. Li, A. Villanueva and K. Crawford for biopsy processing and clinical data, S. Hashaghan for assisting with quantitative imaging approaches, E. Penaflor for assisting in IHC assay optimization, execution and digital image generation, and B. Dogdas and S. Mehta who assisted with the proximity assay. We would like to thank S. Ebbinghaus, E. Rubin, S. P. Kang, R. L. Modlin, C. R. Taylor and C. Denny for critically reviewing the manuscript.

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Authors and Affiliations



P.C.T. and A.R. supervised the project and developed the concepts. P.C.T., C.L.H., C.R. and A.R. designed the experiments. P.C.T., C.L.H., M.S., C.R. and A.R. interpreted the data. A.R., P.C.T., C.L.H., C.R., J.H.Y., M.S., I.P.S., E.J.M.T., R.O.E., H.R. and R.H.P. gave conceptual advice and edited the manuscript. P.C.T., J.H.Y., I.P.S., A.N.W. and E.J.M.T. established IHC staining and/or imaging protocols. J.H.Y., I.P.S., E.J.M.T. and R.H.P. provided confirmatory pathology analyses. G.T. worked on IHC samples from the patients from Gustave Roussy. C.L.H., L.R., M.S., G.H., V.C., M.C., C.K. and E.S. provided technical support. P.C.T., T.R.G. and D.A.E. designed and implemented the predictive model and provided statistical support. P.C.T., B.C., A.J.G., C.M., J.A.G., G.C., C.R. and A.R. clinically evaluated patients in the trial.

Corresponding authors

Correspondence to Paul C. Tumeh or Antoni Ribas.

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Competing interests

R.O.E. has full-time employment and equity ownership at Adaptive Biotechnologies Corporation. H.S.R. has consultancy, patents and royalties, and equity ownership at Adaptive Biotechnologies Corporation. P.C.T., D.A.E. and A.R. have filed a patent related to this work.

Extended data figures and tables

Extended Data Figure 1 CD8+-cell infiltrates in tumour biopsies.

a, Segmentation of the invasive margin and tumour parenchyma using S100 and CD8 chromogenic staining. Low magnification (top row) and high magnification (bottom row) are shown. The red dotted line demarcates S100+ tumour (left of red line) from S100 stroma (right of red line). Coordinates of the invasive margin and tumour parenchyma are generated from the S100 stained image (column labelled ‘S100’) and subsequently imported into the CD8 stained image (column labelled ‘CD8’). This is followed by a deconvolution imaging algorithm of the CD8 stained image where first all nuclei (column labelled ‘nuclei+ cells’) are identified and quantified, irrespective of what type of cell. This is followed by identifying CD8+ membrane (column labelled ‘CD8+ cells’) for cell quantification and analysis. b, CD8+ T-cell kinetics within the tumour microenvironment in a serially sampled tumour responding to PD-1 blocking therapy. Example of radiographic, clinical, and CD8 IHC in a serially sampled melanoma tumour of the left chest wall that was obtained from a patient with a delayed response. On day +27, clinical and radiographic examinations indicated progressive disease; at a time when CD8+ T cells expression increased in density at the invasive margin.

Extended Data Figure 2 Proliferation of CD8+ T cells in regressing tumours.

a, Relationship of the change in CD8+-cell density and best percentage change in tumour size in serially sampled tumours that were assessed using quantitative immunohistochemistry and CT scan measurements (n = 18, Spearman r = −0.75, P = 0.0002). b, CD8+-cell density and Ki67+/CD8+-cell density in the response group before treatment (n = 11, empty circles) and during treatment (n = 17, filled circles) and the progression group before treatment (n = 9, empty triangles), and during treatment (n = 15, filled triangles). c. Representative examples of CD8/Ki67 chromogenic double staining from a biopsy of a patient with a tumour response and another with progression. Double-positive CD8 cells (red, labelled Ki67 nucleus; brown, CD8 labelled membrane) are not present at baseline, but are present during tumour regression in the biopsy from a patient with a tumour response. The double-positive cells are not in the biopsy of a patient with progression during treatment (no Ki67 labelling in brown CD8 cells). Magnification, ×40.

Extended Data Figure 3 Granzyme B and pSTAT1 expression before and during treatment in terms of clinical response.

a, Representative examples of granzyme B expression according to clinical response. b, Samples collected during PD-1 blocking therapy were evaluated for granzyme B signal (response n = 13, progression n = 12) using quantitative immunohistochemistry. ****P < 0.0001. c, Representative example of the proximity between CD8+, PD-1+, PD-L1+ and pSTAT1+ cells in the tumour microenvironment in a sample obtained before treatment from the response group. Magnification, ×40. 2 µM serial cut tissue sections were stained for CD8, PD-1, PD-L1 and pSTAT1. d, Localization of CD8+ and pSTAT1+ cells in samples obtained before treatment from a biopsy in a patient with response and two patients with progression on anti-PD-1 therapy (± a CD8 presence). The biopsy from a patient with disease progression had a moderate presence of CD8 cells that did not show pSTAT1 expression in the area. e, Using quantitative IHC analysis, the response group was associated with significantly higher expression of pSTAT1+ at the invasive margin before and during treatment (response n = 16, progression n = 18, P = 0.002 for pre-treatment biopsies; and response n = 13, progression n = 12, P < 0.0001 for post treatment biopsies). Within the response group, pSTAT1 expression was significantly higher during treatment when compared to baseline (P = 0.022).

Extended Data Figure 4 Relationship between CD8 and PD-L1 expression in terms of treatment outcome.

a, Scatterplots of CD8 and PD-L1 density (cells mm−2) using a log(x+1) scale are shown in samples obtained at baseline stratified by treatment outcome. Reference ‘cut-points’ for CD8 and PD-L1 densities were based on the median value for each marker across the entire cohort. Samples present in the CD8highPD-L1high quadrant, in both tumour and invasive margin, were predominantly derived from the response group. Samples present in the CD8lowPD-L1low quadrants were significantly associated with the progression group (response n = 17, progression n = 21, P < 0.001 at both the invasive margin and tumour). b, CD8, PD-1 and PD-L1 expression before treatment in terms of clinical response. Representative examples of the proximity between CD8+, PD-1+, PD-L1+ cells in the tumour microenvironment in pre-treatment samples obtained from a patient with a tumour response and progression. Magnification, ×20. 2 µM serial cut tissue sections were stained for CD8, PD-1 and PD-L1. c, Multiplexed immunofluorescence staining of CD8 and PD-1 to evaluate the relative co-expression of CD8 and PD-1 on individual cells within the tumour microenvironment. CD8+ cells were detected using AlexaFluor 488 staining in the green channel. PD-1+ cells were detected suing AlexaFluor 594 staining in the red channel. High levels of co-expression of the two antigens were observed when the two channels are combined, yielding yellow signal in areas of co-localization.

Extended Data Figure 5 PD-L1 expression and relationship with T-cell infiltration.

a, Multiplexed chromogenic staining of SOX10 (red nucleus) and PD-L1 (brown membrane) to evaluate PD-L1 expression on melanoma cells, lymphocytes and macrophages within the tumour microenvironment. SOX10 is a transcription factor that is melanoma-cell specific. Representative high power fields of double-positive cells (yellow arrows) show melanoma cells expressing PD-L1 and single-positive PD-L1 cells comprising of lymphocytes (high nuclear:cytoplasmic ratio, red arrows) and macrophages (low nuclear:cytoplasmic ratio, green arrows) in three responders from samples obtained during tumour regression. Magnification, ×40. b, Principal component analysis to decompose the variance for the markers (CD8+-, PD-1+-, PD-L1+- and CD4+-cell densities (cells mm−2)) separately in the tumour and in the invasive margin. The first principal component accounted for the majority of the variability in the four markers—69.6% and 57.1% in the tumour centre (***P = 0.001) and the invasive margin (****P < 0.0001), respectively. Principal component scores for the first principal component were compared between response groups with Wilcoxon rank-sum tests.

Extended Data Figure 6 Clonality of the T-cell repertoire and density of T-cell infiltration in terms of clinical response.

a, High-throughput quantitative sequencing of the rearranged TCR β genes using the ImmunoSeq assay (response n = 13, progression n = 12). ***P = 0.005 by Fisher’s exact test. The x-axis represents clonality of the T-cell repertoire (1 − Pielou’s evenness) and the y-axis represents the density of tumour-infiltrating T cells (estimated TCR gene rearrangements per diploid genomes, see Methods for further details). The axes cross at the median value for clonality and T-cell infiltration. T-cell infiltration and T-cell infilitration repertoire clonality were found to be independent in this cohort (R2 = 0.04). Progressors were associated with lower levels of T-cell infiltration and lower T-cell infiltration clonality (that is, a more diverse T-cell infiltration repertoire); all patients with below-median clonality and T-cell infiltration progressed. b, The uniqueness of the CDR3 TCR sequences enable tracking of clonal expansion or contraction in serially sampled tumours. Representative scatterplot of clones from a responding tumour serially sampled before and during anti-PD-1 treatment. (1 dot = 1 unique clone: green, expanded; grey, stable; red, contracted). The x- and y-axes represent the relative abundance of each clone before and during treatment, respectively. Clones that met a 2× change in frequency from baseline must have also met significance using a Fisher exact test of the clone before and during anti-PD-1 treatment and the full set of clone reads, followed by Storey’s Q value for false discovery rate. c, Clonal expansion in terms of clinical response (response n = 6, progression n = 5). **P = 0.006.

Extended Data Table 1 Demographic and clinical characteristics of patients in the study and validation cohorts
Extended Data Table 2 Anatomical location of biopsies performed before and during treatment
Extended Data Table 3 CD8, PD-1, PD-L1 and CD4 expression and clonality before treatment in terms of clinical response to pembrolizumab and previous treatment with ipilimumab
Extended Data Table 4 Predictive model and validation

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Tumeh, P., Harview, C., Yearley, J. et al. PD-1 blockade induces responses by inhibiting adaptive immune resistance. Nature 515, 568–571 (2014).

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