A peripheral immune signature of responsiveness to PD-1 blockade in patients with classical Hodgkin lymphoma (original) (raw)

Data availability

The TCR sequences for this study were processed through the immunoSEQ platform of Adaptive Biotechnologies. The TCR sequences are publicly available (https://doi.org/10.21417/FZC2020NM) through this link: https://adaptivebiotech.com/pub/cader-2020-nm. The raw CyTOF.fcs files are publicly available through login at Cytobank, https://premium.cytobank.org/cytobank/experiments#project-id=2539 and https://premium.cytobank.org/cytobank/experiments/310927. Source data for all main and Extended Data figures are available in the Supplementary Dataset.

Code availability

CyTOF data was processed by VorteX (26 April 2018) and the output was processed by a custom R script. TCR-seq data was processed and analyzed by custom Python and R scripts. The code is available at https://github.com/huxihao/cHL-PBMC.

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Acknowledgements

This work was supported in part by Bloodwise Fellowship 14042 and a Helen Gurley Brown Fellowship (F.Z.C.), a R01 CA161026 (M.A.S.), the Miller Family Fund (M.A.S.), the BMS International Immuno-Oncology Network (M.A.S. and S.J.R.) and a R01 CA234018 (X.S.L.). The authors thank L. Boyne (Dana-Farber Cancer Institute) for providing editorial assistance.

Author information

Author notes

  1. Fathima Zumla Cader
    Present address: AstraZeneca, City House, Cambridge, UK
  2. Xihao Hu
    Present address: GV20 Therapeutics LLC, Cambridge, MA, USA
  3. Kirsty Wienand
    Present address: Department of Hematology and Oncology, Göttingen Comprehensive Cancer Center, Göttingen, Germany
  4. Ron C. J. Schackmann
    Present address: Merus, Utrecht, the Netherlands
  5. Bo Li
    Present address: Lyda Hill Department of Bioinformatics, UT Southwestern Medical Center, Dallas, TX, USA
  6. Wenjiang Ma
    Present address: Clarion Healthcare, Boston, MA, USA
  7. These authors contributed equally: Fathima Zumla Cader, Xihao Hu.
  8. These authors jointly supervised this work: X. Shirley Liu, Margaret A. Shipp.

Authors and Affiliations

  1. Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, MA, USA
    Fathima Zumla Cader, Kirsty Wienand, Jing Ouyang, Elisa Mandato, Lee N. Lawton, Wenjiang Ma, Philippe Armand & Margaret A. Shipp
  2. Department of Data Sciences, Dana-Farber Cancer Institute, Boston, MA, USA
    Xihao Hu, Robert Redd, Bo Li, Donna Neuberg & X. Shirley Liu
  3. Harvard T.H. Chan School of Public Health, Boston, MA, USA
    Xihao Hu, Bo Li & X. Shirley Liu
  4. Department of Cell Biology, Harvard Medical School, Boston, MA, USA
    Walter L. Goh & Ron C. J. Schackmann
  5. Center for Immuno-Oncology, Dana-Farber Cancer Institute, Boston, MA, USA
    Pei-Hsuan Chen & Jason L. Weirather
  6. Department of Pathology, Brigham and Women’s Hospital, Boston, MA, USA
    Scott J. Rodig

Authors

  1. Fathima Zumla Cader
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  2. Xihao Hu
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  3. Walter L. Goh
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  4. Kirsty Wienand
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  7. Robert Redd
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  8. Lee N. Lawton
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  9. Pei-Hsuan Chen
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  10. Jason L. Weirather
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  11. Ron C. J. Schackmann
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  12. Bo Li
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  13. Wenjiang Ma
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  14. Philippe Armand
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  17. X. Shirley Liu
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  18. Margaret A. Shipp
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Contributions

F.Z.C., X.H., X.S.L. and M.A.S. conceived and led the project and analyzed the data. F.Z.C., X.H., W.L.G., J.O., E.M., R.R., P.-H.C., J.L.W., R.C.J.S. and S.J.R. performed experiments and analyzed the data. K.W., L.N.L. B.L., W.M., P.A. and D.N. contributed to the analysis and scientific discussions. F.Z.C., X.H., X.S.L. and M.A.S. wrote the paper.

Corresponding authors

Correspondence toX. Shirley Liu or Margaret A. Shipp.

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Competing interests

After completing the current studies at DFCI, F.Z.C. and X.H. became full-time employees at Astra Zeneca and GV20, respectively. P.A. consults for Merck, Bristol Myers Squibb (BMS), Pfizer, Affimed, Adaptive, Infinity, ADC Therapeutics and Celgene and receives institutional research funding from Merck, BMS, Affimed, Adaptive, Roche, Tensha, Otsuka, Sigma Tau, Genentech and IGM and honoraria from Merck and BMS. S.J.R. has received research funding from BMS, Merck, Affimed and Kite/Gilead. X.S.L. is a cofounder and board member of GV20 Oncotherapy, SAB of 3DMedCare, consultant for Genentech, and stockholder of BMY, TMO, WBA, ABT, ABBV, and JNJ. X.S.L. has received funding from Takeda and Sanofi. M.A.S. has received research funding from BMS, Merck and Bayer and has served on advisory boards for BMS and Celgene. The remaining authors declare no competing financial interests.

Additional information

Peer review information Saheli Sadanand was the primary editor on this article and managed its editorial process and peer review in collaboration with the rest of the editorial team.

Publisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Extended data

Extended Data Fig. 1 Analyses of peripheral TCR repertoire diversity at baseline and following PD-1 blockade.

a, Number of prior therapies in trial patients who were treated with nivolumab ≥ 1 yr after ASCT by best overall response to PD-1 blockade (CR n = 14, PR n = 18, PD n = 12). b, Percentages of CD3 + and CD3- viable cells at baseline in trial patients with relapsed/refractory cHL. Viable singlet cells identified by manual gating of CyTOF data were divided according to CD3 expression (CD3-, grey and CD3 + , orange, n = 38). Individual samples from patients with available CyTOF files who had relapsed/refractory cHL with ≥ 1 year between nivolumab and prior myeloablative ASCT are shown (n = 38) (CR n = 13, PR n = 15, PD n = 10). c, Comparison of baseline CD3 + populations in trial patients with relapsed/refractory cHL (from b) according to their subsequent response to PD-1 blockade. d, Total number of TCR-seq detected clones at baseline in trial patients (from a) according to their subsequent response to PD-1 blockade. e, Percentages of CD4 + (blue) and CD8 + (purple) cells at baseline in trial patients with relapsed/refractory cHL. CD3 + cells identified (from b) and divided according to CD4 + or CD8 + expression by manual gating of CyTOF data. Additional cryopreserved samples from indicated cases (*) were available for CD4 + and CD8 + sorting (n = 18, 2 excluded from this analysis as no CyTOF files available). f, Comparison of baseline CD4 + populations in all trial patients with relapsed/ refractory cHL (from e) according to their subsequent response to PD-1 blockade (CR, PR, PD). g, Comparison of baseline CD4 + populations in trial patients with relapsed/refractory cHL (from e*) with additional PBMC samples sorted for CD4 + and CD8 + T cells (n = 18). h, Total numbers of CD4 + and CD8 + TCR-seq detected clones at baseline in trial patients (from g) according to their subsequent response to PD-1 blockade. Differences between groups in panels a, c, d, f, g and h were assessed with a Wilcoxon rank sum test of the median with two-tailed p values. i, Changes in TCR diversity from C1D1 to C4D1 in the subset of trial patients with known HRS cell expression of MHC class I and MHC class II and CD4 + and CD8 + TCRseq data (n = 9). Definitions of positive (positive or decreased) and negative expression of MHC class I and class II on HRS cells previously described in (Roemer et al 20184). j, Changes in TCR diversity from C1D1 to C4D1 separated by HRS cell expression of MHC class II only, samples from i. Differences in panels i and j were assessed by Wilcoxon rank sum test with one-sided p-values. k, The ratio of maximum expansion of singleton clones (0 or 1 copy at baseline)/ non-singleton clones which have 2 or more copies at baseline in patients with BOR of CR (n = 9), PR (n = 17) or PD (n = 8) to PD-1 blockade. Only patients with all 3 timepoints are included in the analysis. Differences between groups were assessed with a Wilcoxon rank sum test of the median, two-tailed p values. (l and m) The ratio of expanded singleton / non-singleton clones from CD4 + only T cells (l) or CD8 + only T cells (m) from patients with CR, PR or PD to PD-1 blockade (n = 20). Differences in panels l and m were assessed by Wilcoxon rank sum test with one-sided p-values. Graphpad Prism (v8) or R (ggplot function) was used to generate box plots (GraphPad Prism panels b, c, e-g and R panels a, d, h-m). The box corresponds to the first and third quartiles and whiskers define minimum and maximum values. Outliers beyond 1.5x IQR in R- generated plots are plotted individually.

Extended Data Fig. 2

Forced-directed layout of CD3+ populations at baseline in a) healthy donors and patients with newly diagnosed cHL and b) patients with newly diagnosed and relapsed/refractory cHL. Each FDL shows expression of individual proteins ranging from no/low expression in blue to high expression in red. Clusters can be assigned a phenotype on the basis of these FDLs. Shown here are 12 proteins which allow identification of differentiation status (CCR7, CD45RO), polarization (CCR5, CCR4, CD161), activation (PD-1, T-bet, Eomes, Granzyme B), Tregs (FoxP3, CD25) and CXCR5 + cells.

Extended Data Fig. 3 Comparison of CD3+ populations in healthy donors versus patients with newly diagnosed cHL.

To quantify differences between these 2 groups, healthy donors (n = 11) and patients with newly diagnosed cHL (n = 9), we determined the number of cells that each sample contributed to a given cluster and applied a Wilcoxon rank sum test with two-sided p-values. Nominal p-values with Benjamini-Hochberg (BH) corrections for p≤0.05 (CD4 + and CD8 + cells separately). Shown here graphically are box plots (generated in GraphPad Prism) defining the 25th and 75th percentile and median values and whiskers for minimum and maximum values: a, CD4 + clusters; b, CD8 + clusters; and c, CD3 + CD4-CD8- subsets.

Extended Data Fig. 4 Comparison of CD3+ populations in patients with newly diagnosed cHL versus relapsed/refractory cHL (all) at baseline.

To quantify differences between these 2 groups, newly diagnosed cHL (n = 9) and relapsed/refractory cHL (n = 36), we determined the number of cells that each sample contributed to a given cluster and applied a Wilcoxon rank sum test with two-sided p-values. Nominal p-values with Benjamini-Hochberg corrections for p≤0.05 (CD4 + and CD8 + cells separately). Shown here graphically are box plots (generated in GraphPad Prism) defining the 25th and 75th percentile and median values and whiskers for minimum and maximum values: a, CD4 + clusters; b, CD8 + clusters; and c, CD3 + CD4-CD8- subsets. d, PD-1 expression on CD3 + T cell clusters identified by Vortex in patients with newly diagnosed cHL vs. relapsed/refractory disease. Only clusters with z-score normalized PD-1 expression greater than 0 (ie. greater than the mean) in the PD-1 columns in the Fig. 3h heat-maps are shown. The differences in PD-1 expression in T-cell subsets from patients with newly diagnosed and relapsed/refractory cHL were measured by the Wilcoxon rank sum test with two-sided p-values, significance denoted by asterisks.

Extended Data Fig. 5 Comparison of CD3+ populations in patients with relapsed/refractory cHL at baseline split by best overall response to subsequent PD-1 blockade (CR, PR, PD).

To quantify differences between these groups, (CR n = 12, PR n = 15, PD n = 9) we determined the number of cells that each sample contributed to a given cluster and applied a Cuzick trend test (two-sided nominal p-values). Shown here graphically are box plots (generated in GraphPad Prism) defining the 25th and 75th percentile and median values and whiskers for minimum and maximum values: a) CD4 + clusters; b) CD8 + clusters; and c) CD3 + CD4-CD8- subsets.

Extended Data Fig. 6 Comparison of CD3- populations in healthy donors versus patients with newly diagnosed cHL.

To quantify differences between these 2 groups, patients with newly diagnosed cHL (n = 10) and relapsed/refractory cHL (n = 35), we determined the number of cells that each sample contributed to a given cluster and applied a Wilcoxon rank sum test (two-sided nominal p-values) with Benjamini-Hochberg (BH) corrections for p ≤ 0.05 (Classical Monocytes, Neutrophils, B cells and NK cells separately). One patient with newly diagnosed cHL who had sufficient numbers of CD3- sampled events in Extended Data Fig. 6–8 had insufficient numbers of CD3 + sampled events and was excluded from the CD3 + analysis in Extended Data Figs. 3–5). One patient with relapsed/refractory cHL had sufficient numbers of CD3 + sampled events for inclusion in Extended Data Figs. 4, 5 but had insufficient numbers of CD3- sampled events and was excluded from the CD3- analyses in Extended Data Fig. 6–8. Shown here graphically are box plots (generated in GraphPad Prism) defining the 25th and 75th percentile and median values and whiskers for minimum and maximum values: a) Monocyte clusters; b) B cell clusters [(1) CXCR5- CD73- IRF4-, (2) CXCR5 + CD73-IRF4-, (3)CXCR5 + CD73 + IRF4 + ]; c) Neutrophils; d) NK cell clusters and e) CD68 + CD4 + GrB+ cells.

Extended Data Fig. 7 Comparison of CD3- populations in patients with newly diagnosed cHL versus relapsed/refractory cHL (all) at baseline.

To quantify differences between these 2 groups, patients with newly diagnosed cHL (n = 10) and relapsed/refractory cHL (n = 35), we determined the number of cells that each sample contributed to a given cluster and applied a Wilcoxon rank sum test (two-sided nominal p-values) with Benjamini-Hochberg (BH) corrections for p ≤ 0.05 (Classical Monocytes, Neutrophils, B cells and NK cells separately). Shown here graphically are box plots (generated in GraphPad Prism) defining the 25th and 75th percentile and median values and whiskers for minimum and maximum values: a) Monocyte clusters; b) B cell clusters [(2) CXCR5 + CD73-IRF4-, (3) CXCR5 + CD73 + IRF4 + ]; c) Neutrophils; d) NK cell clusters and e) CD68 + CD4 + GrB+ cells.

Extended Data Fig. 8 Comparison of CD3- populations in patients with relapsed/refractory cHL split by best overall response at baseline (CR, PR, PD).

To quantify differences between these groups (CR n = 12, PR n = 15, PD n = 8), we determined the number of cells that each sample contributed to a given cluster and applied Cuzick trend test (two-sided nominal p-values) with Benjamini-Hochberg (BH) corrections for p ≤ 0.05 (B cells and NK cells separately). Shown here graphically are box plots (generated in GraphPad Prism) defining the 25th and 75th percentile and median values and whiskers for minimum and maximum values: a) Monocyte clusters; b) B-cell clusters [(2) CXCR5 + CD73-IRF4-, (3) CXCR5 + CD73 + IRF4 + ]; c) Neutrophils; d) NK-cell clusters and e) CD68 + CD4 + GrB+ cells.

Extended data Fig. 9 CyTOF analyses of CD3- cell populations from viable singlet cells from 7 primary cHLs and 10 reactive lymph nodes/tonsils from31.

a, Force-directed layouts generated from X-shift analysis within VorteX visualization environment by sampling 4500 events from each sample and pooling resulting events together prior to clustering. The X-shift algorithm clusters events according to similarities in expression of CyTOF panel proteins, grouping events with shared lineage, differentiation and polarization within the pool. Every identified unique population is labeled with a specific color based on the Hex color code. b, Expression of CD68, CD4 and Granzyme B across all samples. c, Separate force-directed layouts (FDLs) of reactive lymph node and primary cHL cell suspensions. In each FDL, the events pertaining to the group of interest retain their Hex color code. Events belonging to the other group are represented in grey. d, Comparison of CD3-CD68 + CD4 + GrB+ Cluster 3341 between reactive lymph nodes and primary cHLs. Shown here graphically are box plots (generated in GraphPad Prism) defining the 25th and 75th percentile and median values and whiskers for minimum and maximum values. To quantify differences between these 2 groups, we determined the number of cells that each sample contributed to a given cluster and applied a Wilcoxon rank sum test with two-sided p-values.

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Reporting Summary

Supplementary Table 1

Summary of patient samples included in the study. No sample available (blue), or available specimen had less than the required number of sampled events for the indicated analysis (purple). a, Samples from healthy donors (Sheet 1). b, Samples from patients with newly diagnosed cHL (Sheet 2). c, Samples from patients with relapsed/refractory cHL who commenced anti-PD-1 (nivolumab) <1 yr after ASCT (Sheet 3). d, Samples from patients with relapsed/refractory disease who commenced anti-PD-1 (nivolumab) ≥1 yr after ASCT (Sheet 4). For all patients with R/R cHL we include sample ID, cohort, BOR as determined by IRRC on May 2018 in these patients, number of lines of prior treatment, duration of nivolumab and number of TCR sequences detected. For those patients who commenced anti-PD-1 (nivolumab) ≥1 yr after ASCT, we also indicate availability of samples for CD4+ and CD8+ sorted and where available the associated number of TCR sequences. Two of the evaluated 20 patients had C3D1, sample rather than C4D1, indicated with an asterisk.

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Cader, F.Z., Hu, X., Goh, W.L. et al. A peripheral immune signature of responsiveness to PD-1 blockade in patients with classical Hodgkin lymphoma.Nat Med 26, 1468–1479 (2020). https://doi.org/10.1038/s41591-020-1006-1

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