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Peripheral CD8+ T cell characteristics associated with durable responses to immune checkpoint blockade in patients with metastatic melanoma

Abstract

Immune checkpoint blockade (ICB) of PD-1 and CTLA-4 to treat metastatic melanoma (MM) has variable therapeutic benefit. To explore this in peripheral samples, we characterized CD8+ T cell gene expression across a cohort of patients with MM receiving anti-PD-1 alone (sICB) or in combination with anti-CTLA-4 (cICB). Whereas CD8+ transcriptional responses to sICB and cICB involve a shared gene set, the magnitude of cICB response is over fourfold greater, with preferential induction of mitosis- and interferon-related genes. Early samples from patients with durable clinical benefit demonstrated overexpression of T cell receptor–encoding genes. By mapping T cell receptor clonality, we find that responding patients have more large clones (those occupying >0.5% of repertoire) post-treatment than non-responding patients or controls, and this correlates with effector memory T cell percentage. Single-cell RNA-sequencing of eight post-treatment samples demonstrates that large clones overexpress genes implicated in cytotoxicity and characteristic of effector memory T cells, including CCL4, GNLY and NKG7. The 6-month clinical response to ICB in patients with MM is associated with the large CD8+ T cell clone count 21 d after treatment and agnostic to clonal specificity, suggesting that post-ICB peripheral CD8+ clonality can provide information regarding long-term treatment response and, potentially, facilitate treatment stratification.

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Fig. 1: Transcriptomic response to ICB.
Fig. 2: Identification of transcriptomic correlates of long-term response.
Fig. 3: Number of large clones is of prognostic importance.
Fig. 4: Single-cell sequencing demonstrates that large clones have a distinct cytotoxic expression profile.

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Data availability

All sequencing data will be made freely available to organizations and researchers to conduct research in accordance with the UK Policy Framework for Health and Social Care Research via a data access agreement. Sequence data have been deposited at the European Genome–phenome Archive, which is hosted by the European Bioinformatics Institute and the Centre for Genomic Regulation under accession no. EGAS00001004081. Patient anonymized raw flow cytometry data are freely accessible for download from the group bitbucket account.

Code availability

Scripts used in the analysis and figure synthesis are available from the Fairfax group bitbucket account: https://bitbucket.org/Fairfaxlab/identification-of-peripheral-cd8-t-cell-subsets-associated/src/master/

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Acknowledgements

We are very grateful to all patients who generously contributed samples and participated in the study. We thank all the staff of the Day Treatment Unit, Oxford Cancer Centre, and N. Coupe and R. Matin for assistance in collecting patient samples. We thank R. Morgan for discussion and advice. This study was funded by a Wellcome Intermediate Clinical Fellowship to B.P.F. (no. 201488/Z/16/Z), additionally supporting E.A.M. and I.N. R.A.W. was a National Institute for Health Research (NIHR) Academic Clinical Fellow and was supported by a CRUK predoctoral Fellowship (no. ANR00740). R.C. is supported by a CRUK Clinical Research Training Fellowship. C.A.T. is funded by the Engineering & Physical Sciences Research Council and the Balliol Jowett Society (no. D4T00070). J.C.K. is funded by a Wellcome Trust Investigator Award (no. 204969/Z/16/Z). P.K. is supported by a NIHR Senior Fellowship and Wellcome Trust Award (no. WT109965MA). V.W. was supported by a CRUK CTAAC Clinical Trials Fellowship (no. C2195/A19716), and also by the NIHR Oxford Biomedical Research Centre. The views expressed are those of the authors and not necessarily those of the NHS, the NIHR or the Department of Health.

Author information

Authors and Affiliations

Authors

Contributions

M.R.M. initiated the cohort. B.P.F. conceived and supervised the study. B.P.F. with contributions from C.A.T., I.N., R.A.W., H.F., M.H.A.-M., P.K. and M.R.M., drafted the paper and figures. B.P.F. and I.N. carried out the primary analysis. M.P., V.W., B.P.F., M.R.M. and R.A.W. carried out patient recruitment. S.D., E.A.M., R.A.W., R.C., C.A.T. and B.P.F. collected samples and purified cells. S.D. and E.A.M. extracted RNA. I.N. provided RNA-seq pipelines, quality control and bioinformatic support. C.A.T. carried out flow cytometry and qPCR clones. R.A.W., R.C. and I.N. carried out single-cell sequencing. Z.T. provided the radiological reporting. R.A.W. and B.P.F. collated the clinical data. H.F. and J.C.K. provided statistical support and machine learning. J.C.K. provided scientific and infrastructural support. All authors reviewed and edited the final paper.

Corresponding author

Correspondence to Benjamin P. Fairfax.

Ethics declarations

Competing interests

M.H.M. reports personal fees from Amgen, grants and personal fees from Roche, grants from Astrazeneca, grants and personal fees from GSK, personal fees and other from Novartis, other from Millenium, personal fees, non-financial support and other from Immunocore, personal fees and other from BMS, personal fees and other from Eisai, other from Pfizer, personal fees, non-financial support and other from Merck/MSD, personal fees and other from Rigontec (acquired by MSD), other from Regeneron, personal fees from BiolineRx, personal fees and other from Array Biopharma (now Pfizer), non-financial support and other from Replimune, outside the submitted work. M.P. has received support with conference travel, and fees for advisory work and speaking from Amgen, BMS, L'Oreal, MSD, Novartis and Pierre Fabre. B.P.F. received support with conference travel from BMS.

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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.

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Extended data

Extended Data Fig. 1 Extended transcriptomic response to ICB.

a, Comparison of differential induction of genes by cICB (log fold change y-axis) and sICB (log fold change x-axis) at day 63 (n=46 paired samples, 35 sICB, 11 cICB). b, Pathways preferentially upregulated (NES score >0) or supressed by cICB versus sICB as identified by Gene Set Enrichment analysis depicted in Fig. 1e, f.

Extended Data Fig. 2 Module pathways.

Pathway analysis was performed using Gene Ontology Biological Processes across treatment response associated modules. For 7/9 modules, transcripts within the modules were significantly associated with discrete processes, with limited overlap between modules. These modules (M1:M4, M6:M8) and all associated pathways for them (FDR <0.05) are listed above. GO specific pathway codes are listed on the y-axis.

Extended Data Fig. 3 Module expression.

Graphs demonstrate average gene expression per module for each sample with red boxplots and associated points representing cICB samples (n=20 baseline, n=16 D21, n=5 D63) and green boxplots and associated points representing sICB samples (n=56 baseline, n=41 D21, n=26 D63). Controls are untreated healthy volunteers (n=24). All statistically significant differences (Tukey adjusted P <0.05) are denoted with associated test in the table and refer to both treatments as group, D21= day 21 sample, D63= day 63 sample.

Extended Data Fig. 4 TCR qPCR.

Validation of MiXCR results using quantitative PCR. For n=13 individuals, 2 TCR α and 2 β chains were identified according to whether or not MiXCR reported significant expansion on day 21 versus baseline. Primers were designed to the complementarity determining region 3 (CDR3) sequences for each chain and quantitative PCR performed on pre-treatment day 0 PBMC cDNA and PBMC cDNA from day 21. Ct values were normalized to total expression of CD3E. a, Clones identified as expanding in the MiXCR CD8+ RNA were found to show significantly more expansion (median 3.48 fold, IQR 1.85-12.79) than non expanding (median1.32 fold, IQR 0.97-1.88, Wilcoxon signed-rank Test (two-sided) P=3x108). Lower and upper hinge of box on boxplots represent 25-75th percentiles, central line the median and the whiskers extend to largest and smallest values no greater than 1.5x interquartile range. b, MiXCR fold change per clone from CD8+ cells was highly correlated with that determined from bulk PBMCs using quantitative PCR (Pearson correlation, two-sided T-statistic).

Extended Data Fig. 5 Extended clone size analysis.

a, Day 21 post ICB clonal diversity is similar in patients who have 6-month response versus those with disease progression by this timepoint (two-sided T-test, n=69). b, As per Fig. 3a, but with unique clones defined by the β-chain, left panel two-sided Wilcoxon signed-rank Test (n=25 controls, 49 patients, right panel one-sided Wilcoxon signed-rank Test, n=43 controls, 20 patients). c, Threshold for clone size associating with outcome, x-axis indicates size of clone with test comparing number of clones above that size according to clinical outcome, y-axis: -log10(p-value) from test. The difference between responding patients and progressing patients being maximal at clone size of 0.5% (two-sided Wilcoxon test, n=69). d, Across all samples there is no association between number of clones growing on day 21 (P<0.05) and clinical outcome by treatment type. e, Proportion of repertoire contributed by large clones does not differ according to clinical outcome. f, When all cutaneous patients are grouped a significant association between pre-treatment large clone count and outcome is observed (n=89,Wilcoxon rank-sum, one-sided test). For all boxplots lower and upper hinges of box represent 25-75th percentiles, central line the median and the whiskers extend to largest and smallest values no greater than 1.5x interquartile range.

Extended Data Fig. 6 Temporal stability of clones.

a, Clones from 42 individuals with samples at 3 timepoints were identified at day 0 pre-treatment and classified according to size. The corresponding correlation for the same clones between day 21 and day 63 was assessed (Pearson correlation, two-sided T-statistic all P<2.2x1016), demonstrating large clones show greater stability in proportion of clonal space occupied over time. b, Clones identified pre-treatment were assessed at day 21 and day 63 with bar plot values representing the number that were larger than the lower defining value of the bin (e.g. >0.01% for intermediate) at later timepoints, the values on top of bars represent percentage of day 0 recovery.

Extended Data Fig. 7 Effect of CMV.

For a subset of cutaneous melanoma patients with day 21 data we were able to measure unequivocal CMV serology. a, CMV seropositivity is associated with a depletion of small clones (ratio <1 for clones <0.05% repertoire) and increased numbers of large clones (>2% repertoire) (n=68 left panel, 53 right panel). b, Patients seropositive for CMV demonstrated significantly reduced CD8+ TCR diversity at day 21 (measured on TRB CDR3) (n=53, two-sided T-Test). c, Despite significant differences in diversity from CMV there was no difference in diversity between day 21 samples from progressing and responding patients (n=53, two-sided T-test). d, There is no association between CMV serology and number of large clones at day 21 (n=53, two-sided T-Test) For all boxplots lower and upper hinges of box represent 25-75th percentiles, central line the median and the whiskers extend to largest and smallest values no greater than 1.5x interquartile range.

Extended Data Fig. 8 Comparison of clonotypes to public clones.

a, The complete dataset of clones were screened for public clonotypes for melanoma associated-antigens (MAA), demonstrating that the size of clones matching these clonotypes in untreated melanoma patients is significantly greater than those in controls (Wilcoxon Test, n=106 patients, 68 controls) b, Melanoma patients showed no difference in mean EBV reactive clone size from controls (P>0.05) although the distribution of clones was skewed in non-melanoma patients and median clone size greater in patients (two-way Wilcoxon-Test). c, Treatment led to a small increase in median EBV reactive clonotype clone size across all patients, but d, the significance of this effect was greater for MAA clonotypes e, for samples with data for clone sizes at day 63 as well as day 21 (n=41 individuals) there was no further change in clone size at the later timepoint (two-way Wilcoxon-Test). For all boxplots lower and upper hinges of box represent 25-75th percentiles, central line the median and the whiskers extend to largest and smallest values no greater than 1.5x interquartile range.

Extended Data Fig. 9 Investigating flow correlates of clonal indices.

a, For 42 samples from 19 patients, blinded flow cytometry data to assess CD8+ subsets (Tcm: central memory, Tn: naive, Temra: effector memory re-expressing CD45RA, Tem: effector memory) was integrated with the Shannon diversity index calculated for each sample. This demonstrated a strong positive association between TCM and diversity, whereas TEMRA was significantly anticorrelated with diversity (Pearson correlation, two way T-statistic). b, as per Fig. 3e, except here large clone count was correlated with percentage CD4+ subsets from each of the samples. Unlike for CD8+ cells, there is no association between large clone count and percentage CD4+ subset in the samples analysed (Pearson correlation, two way T-statistic).

Extended Data Fig. 10 Comparing MiXCR and 10X TCR data.

ah, For 8 patients, indicated by number, CD8+ cell samples were subject to 10X chromium single cell 5’ RNA sequencing providing T cell receptor sequencing and standard bulk sequencing (see methods). Clones were identified by their β chain and for each productive β chain identified the relative clonal proportion (frequency) was calculated. Clones were matched via the CDR3 amino acid sequence with β chains from the same samples mapped from bulk CD8+ cell RNA using MiXCR. Where the clone fell below detection limit in MiXCR a value of 0 was attributed. MiXCR clones were identified for 92.1% clones >0.1% population in 10X (6990/7597) and 99.4% clones >0.2% size (5816/5852). x-axis= 10X proportion, y-axis MiXCR proportion, r calculated using Pearson correlation coefficient, all P<2.2x1016. i, Despite the different methods, the number of large clones (>0.5% total clonal population) identified from 10X and MiXCR approaches are correlated.

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Fairfax, B.P., Taylor, C.A., Watson, R.A. et al. Peripheral CD8+ T cell characteristics associated with durable responses to immune checkpoint blockade in patients with metastatic melanoma. Nat Med 26, 193–199 (2020). https://doi.org/10.1038/s41591-019-0734-6

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