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Intra-tumoral T cells in pediatric brain tumors display clonal expansion and effector properties

Nature Cancer (2024)Cite this article

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Abstract

Brain tumors in children are a devastating disease in a high proportion of patients. Owing to inconsistent results in clinical trials in unstratified patients, the role of immunotherapy remains unclear. We performed an in-depth survey of the single-cell transcriptomes and clonal relationship of intra-tumoral T cells from children with brain tumors. Our results demonstrate that a large fraction of T cells in the tumor tissue are clonally expanded with the potential to recognize tumor antigens. Such clonally expanded T cells display enrichment of transcripts linked to effector function, tissue residency, immune checkpoints and signatures of neoantigen-specific T cells and immunotherapy response. We identify neoantigens in pediatric brain tumors and show that neoantigen-specific T cell gene signatures are linked to better survival outcomes. Notably, among the patients in our cohort, we observe substantial heterogeneity in the degree of clonal expansion and magnitude of T cell response. Our findings suggest that characterization of intra-tumoral T cell responses may enable selection of patients for immunotherapy, an approach that requires prospective validation in clinical trials.

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Fig. 1: T cells within pediatric brain tumors show marked clonal expansion.
Fig. 2: Tumor-infiltrating T cells display neoantigen-specific T cell gene signatures that are associated with improved survival.
Fig. 3: Clonally expanded CD8+ T cells display cell states linked to anti-tumor immunity.
Fig. 4: Clonally expanded CD8+ T cells display effector properties.
Fig. 5: PDCD1-expressing intra-tumoral CD8+ T cells are not dysfunctional.
Fig. 6: Heterogeneity in the expression of immunotherapy targets in CD8+ T cells.
Fig. 7: CD4-CTLs are clonally expanded in pediatric brain tumors.
Fig. 8: PD-1+CD4+ T cells display increased expression of cytotoxic molecules and cytokines.

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Data availability

Processed scRNA-seq and TCR-seq data generated from pediatric brain tumors and NSCLC can be accessed in GEO under accession number GSE221776. Previously published scRNA-seq data that were reanalyzed here are available under accession codes GSE163108 (ref. 40) and GSE123813 (ref. 30). Public pediatric brain tumor datasets used for survival analysis, and expression analysis of MHCI, MHCII, KEGG pathway enrichment and CLEC2D can be accessed from the Gabriella Miller Kids First Data Resource Portal (https://portal.kidsfirstdrc.org/login) through the CAVATICA (https://www.cavatica.org) cloud-based platform, and clinical data can be accessed using PedcBioPortal (https://pedcbioportal.kidsfirstdrc.org). Source data for all main and extended data figures are provided as Source Data files. All other data supporting the findings of this study are available from the corresponding author on reasonable request. Source data are provided with this paper.

Code availability

All codes for bioinformatic analysis were deposited in our GitHub repository (https://github.com/vijaybioinfo/PBT_2023).

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Acknowledgements

We thank J. D. Elster and M. Paul (Department of Pediatrics, University of California San Diego and Rady Children’s Hospital) for supporting patient recruitment, and we thank R. Newbury, K. Shayan, J. Mo, N. Ellington, D. Wang and S. Tucker (Department of Pathology, University of California San Diego and Rady Children’s Hospital) for providing fresh brain tumor tissue for research from the material that is surplus beyond clinical testing needs. We thank H. Simon and M. Mondal for support with sequencing. This work was supported by Hyundai Hope On Wheels, Peacock Foundation and Curebound (Pedal The Cause) for research into pediatric brain tumors; the funders had no role in study design, data collection and analysis, decision to publish or preparation of the manuscript. Support is also acknowledged from the Whitaker Fund (C.H.O.), William K. Bowes Jr Foundation (P.V.) and National Institutes of Health K08 CA230164 (A.P.G.).

Author information

Author notes

  1. These authors contributed equally: Aditi Upadhye, Kevin E. Meza Landeros.

  2. These authors jointly supervised this work: Pandurangan Vijayanand, Anusha-Preethi Ganesan.

Authors and Affiliations

  1. La Jolla Institute for Immunology, La Jolla, CA, USA

    Aditi Upadhye, Kevin E. Meza Landeros, Ciro Ramírez-Suástegui, Benjamin J. Schmiedel, Jason A. Greenbaum, Grégory Seumois, Stephen P. Schoenberger, Hilde Cheroutre, Christian H. Ottensmeier, Pandurangan Vijayanand & Anusha-Preethi Ganesan

  2. Center for Genomic Sciences, National Autonomous University of Mexico, Cuernavaca, Mexico

    Kevin E. Meza Landeros

  3. Southampton University Hospitals NHS Trust, Southampton, UK

    Edwin Woo

  4. Department of Respiratory Medicine, Liverpool Heart and Chest Hospital NHS Foundation Trust, Liverpool, UK

    Serena J. Chee

  5. Department of Molecular and Clinical Cancer Medicine, Institute of Systems, Molecular and Integrative Biology, University of Liverpool, Liverpool, UK

    Serena J. Chee, Christian H. Ottensmeier & Pandurangan Vijayanand

  6. Department of Pathology, University of California San Diego, La Jolla, CA, USA

    Denise Malicki

  7. Rady Children’s Hospital, San Diego, CA, USA

    Denise Malicki, Nicole G. Coufal, David Gonda, Michael L. Levy, John Crawford, William D. Roberts & Anusha-Preethi Ganesan

  8. Department of Pediatrics, University of California San Diego, La Jolla, CA, USA

    Nicole G. Coufal, William D. Roberts & Anusha-Preethi Ganesan

  9. Department of Neurological Surgery, University of California San Diego, La Jolla, CA, USA

    David Gonda & Michael L. Levy

  10. Department of Neurosciences, University of California San Diego, La Jolla, CA, USA

    John Crawford

  11. Department of Pediatrics, University of California Irvine, Irvine, CA, USA

    John Crawford

  12. Children’s Hospital Orange County, Irvine, CA, USA

    John Crawford

  13. Clatterbridge Cancer Center NHS Foundation Trust, Liverpool, UK

    Christian H. Ottensmeier

  14. Department of Medicine, University of California San Diego, La Jolla, CA, USA

    Pandurangan Vijayanand

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  1. Aditi Upadhye
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Contributions

A.U. performed the experimental work, along with data generation, analysis and interpretation, and manuscript review. K.E.M.L. performed bioinformatic evaluation and data analysis. C.R.S. performed bioinformatic evaluation, data analysis and manuscript review. B.J.S. conducted experimental work related to NSCLC. E.W. and S.J.C. recruited patients with NSCLC and performed sample collection. A.P.G., D.M., N.G.C., D.G. and M.L.L. recruited patients with pediatric brain tumors and performed sample collection. J.A.G. performed mutanome analysis. G.S. supervised the sequencing work. J.C. and W.D.R. were involved with study development, patient recruitment and manuscript review. S.P.S. performed mutanome analysis and paper review. H.C. interpreted the data and reviewed the manuscript. C.H.O. was involved with study development, patient recruitment and manuscript review. P.V. was involved with study design, data generation and review, and manuscript writing and review. A.P.G. was involved with study design, patient recruitment, data generation and review, and manuscript writing and review. P.V. and A.P.G. conceived, supervised and led the work.

Corresponding authors

Correspondence to Pandurangan Vijayanand or Anusha-Preethi Ganesan.

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The authors declare no competing interests.

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Nature Cancer thanks Vassiliki Boussiotis and the other, anonymous, reviewer(s) for their contribution to the peer review of this work.

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Extended data

Extended Data Fig. 1 Clinical parameters do not correlate with T cell clonal expansion.

Correlation of CD4+ (left panel) or CD8+ (right panel) T cell clonal expansion with clinical and pathological characteristics of PBT patients (CD4+, n = 26; CD8+, n = 32). Patients with <50 CD8+ or CD4+ T cells with TCR data were excluded. Error bars represent mean ± s.e.m.

Source data

Extended Data Fig. 2 Mutanome analysis of pediatric brain tumors.

a, Schema of mutanome analysis and neoantigen profiling in pediatric brain tumors. b, Number of genomic tumor-specific variants in pediatric brain tumors (n = 9) (top); table shows top 10 high-confidence tumor-specific variants detected in two index patients (MBL, medulloblastoma; HGG, high-grade glioma) (bottom). c, Kaplan-Meier survival curve based on T cell gene signature in pediatric high-grade glioma from the Pediatric Brain Tumor Atlas (PBTA); n = 36 per signature group; n.s. denotes P = 0.078 by multivariate Cox regression; HR, hazard ratio; CI, confidence interval.

Source data

Extended Data Fig. 3 CD8+ T cell subsets within pediatric brain tumors.

a, Violin plots show the per-cell distribution of unique genes, unique molecular identifiers (UMI), and percentage of UMI mapped to mitochondrial genome in 26,332 single CD8+ T cells across clusters in PBT (n = 38). Box plots extend from the 25th to 75th percentile and the center line represents the median. Whiskers are bounded by 25th percentile - 1.5*interquartile range or 75th percentile + 1.5*interquartile range. b, UMAP shows Seurat clustering of 26,332 CD8+ T cell transcriptomes in PBT (n = 38). c, Heatmap shows top 50 differentially-expressed genes using MAST across CD8+ T cell clusters. d, GSEA plot shows enrichment of the indicated gene signatures in the indicated CD8+ T cell clusters. e, Gene set enrichment analysis (GSEA) plot showing enrichment of the ICB response signature31 in clonally-expanded versus non-expanded T cells from PBT patients (CD8+, n = 38; CD4+, n = 35). In d and e, FDR-adjusted P value (q) and normalized enrichment score (NES) determined using fgsea package on R. f, Pie charts show TRAV, TRAJ and TRBV gene usage by T cells in MAIT cell clusters (below, key).

Source data

Extended Data Fig. 4 Composition and phenotype of tumor-infiltrating CD8+ T cells.

a, Subset composition of tumor-infiltrating CD8+ T cells (stacked to 100%) across PBT patients (n = 38); numbers above bars represent total number of CD8+ T cells per patient and when <50, numbers are highlighted in red. b, Proportion of CD8+ T cell subsets among total CD8+ T cells in newly diagnosed (n = 34) versus recurrent (n = 4) tumors (above, key); all comparisons are non-significant by nonparametric two-tailed Mann-Whitney test. Error bars represent mean ± s.e.m. c, Analysis of canonical pathways from the Ingenuity Pathway Analysis database (horizontal axis; bars in plot) for which clonally-expanded CD8+ T cells from PBT show enrichment, presented as the frequency of differentially-expressed genes encoding components of each pathway that are upregulated or downregulated (key) in clonally-expanded CD8+ T cells relative to their expression in non-expanded cells (left vertical axis), and adjusted P values (right vertical axis; line; Fisher’s exact test); numbers above bars indicate total genes in each pathway. d, Crater plot displays genes differentially-expressed between clonally-expanded (clone size > 1) versus non-expanded (clone size = 1) CD8+ T cells from PBT (n = 38) (X axis) or pre-ICB tumors from ICB responders30 (n = 6) (Y axis). Top right quadrant displays genes upregulated in clonally-expanded CD8+ T cells that are shared between PBT and tumors from ICB responders. Size of dots represents significance (Benjamini-Hochberg FDR-corrected P-value < 0.05 and log2 fold change > 0.35 or < −0.35 using MAST) and color of dots represents mean expression of displayed genes.

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Extended Data Fig. 5 T cell responses in pediatric brain tumors versus adult brain tumors.

a, UMAP (left) and violin (right) displays TCF7 expression across subsets in tumor-infiltrating CD8+ T cells from PBT (n = 38). Inset (above left) shows proportion of TCF7-expressing cells per subset. b, UMAP (left) and violin (right) displays KLRB1 expression across subsets in tumor-infiltrating CD8+ T cells from PBT (n = 38). Inset (above left) shows proportion of KLRB1-expressing cells per subset. c, Expression of CLEC2D transcripts in adult glioblastoma (GBM, n = 96), pediatric high-grade glioma (pHGG, n = 25) or pediatric low-grade glioma (pLGG, n = 93) from PedcBioPortal datasets. In a-c, box plots extend from the 25th to 75th percentile and the center line represents the median. Whiskers represent minimum and maximum values. d, Single-cell trajectory analysis showing relationship between cells in different CD8+ T cell subsets (line) in pediatric brain tumors, constructed using Monocle 3.

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Extended Data Fig. 6 Tumor-infiltrating PD-1 + CD8+ T cells display clonal expansion and cytokine production.

a, Proportion of clonally-expanded CD8+ T cells in PDCD1-non-expressing versus PDCD1-expressing CD8+ T cells (n = 32) (top); ****P = 1.6×10−5. Proportion of PDCD1-expressing CD8+ T cells in non-expanded versus clonally-expanded CD8+ T cells in PBT (n = 32) (bottom); ****P = 1.8×10−5. P value determined by nonparametric two-tailed Wilcoxon matched-pairs signed rank test in both analyses. Patients with <50 CD8+ T cells with TCR data were excluded. b, Representative flow-cytometric gating strategy for the assessment of CD103, cytotoxic molecule, and cytokine expression in total CD8+ T cells and in PD-1negCD8+ T cells versus PD-1+CD8+ T cells from PBT (also related to Fig. 4b,c). c, Proportion (left plot) of cells expressing IL2 in PDCD1-non-expressing versus PDCD1-expressing CD8+ T cells in PBT (n = 38). Flow-cytometric analysis (right) of the expression and proportion of IL-2+ cells in PD-1negCD8+ T cells versus PD-1+CD8+ T cells from PBT patients (n = 7); n.s. denotes P = 0.16 by non-parametric two-tailed Wilcoxon matched-pairs signed rank test. d, Bar chart shows polyfunctionality based on the production of multiple cytokines in PD-1negCD8+ T cells versus PD-1+CD8+ T cells from PBT (n = 7). e, GSEA plot shows enrichment of cell cycle gene signature in PDCD1-expressing versus PDCD1-non-expressing CD8+ T cells in PBT (n = 38). P value and NES as in Fig. 2a.

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Extended Data Fig. 7 Expression of transcripts encoding HLA molecules and features of LAG3-expressing CD8+ T cells in pediatric brain tumors.

Expression of (a) HLA-A, HLA-B, HLA-C, HLA-DRB1, HLA-DPB1,and HLA-DQB1 transcripts and (b) antigen processing and presentation signature genes across six diagnoses in the PBTA; error bars represent mean ± s.e.m. CPP, choroid plexus papilloma (n = 16); CrPh, craniopharyngioma (n = 36); LGG, low-grade glioma (n = 302); HGG, high-grade glioma (n = 148); MBL, medulloblastoma (n = 119); AE, anaplastic ependymoma (n = 93). c, Volcano plot shows differentially-expressed genes between LAG3-non-expressing versus LAG3-expressing CD8+ T cells from PBT patients with low expression of PDCD1 in CD8+ T cells (n = 10) (Benjamini-Hochberg FDR-corrected P value < 0.05, log2 fold change > 0.35 or < −0.35 using MAST); dot size and color as in Fig. 6b.

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Extended Data Fig. 8 CD4+ T cell subsets within pediatric brain tumors.

a, Violin plots show the per-cell distribution of unique genes, unique molecular identifiers (UMI), and percentage of UMI mapped to mitochondrial genome in 14,994 single CD4+ T cells across clusters in PBT (n = 35). Box plots extend from the 25th to 75th percentile and the center line represents the median. Whiskers are bounded by 25th percentile - 1.5*interquartile range or 75th percentile + 1.5*interquartile range. b, UMAP shows Seurat clustering of 14,994 CD4+ T cell transcriptomes in PBT (n = 35). c, Heatmap shows top 50 differentially-expressed genes using MAST across CD4+ T cell clusters. d, GSEA plot shows enrichment of the indicated gene signatures in the indicated CD4+ T cell clusters. e, GSEA plot shows enrichment of CD4-CTL gene signature in clonally-expanded versus non-expanded non-TREG CD4+ T cells. In d and e, P value and NES determined as in Fig. 2a. f, Proportion of clonally-expanded CD4+ T cells in PDCD1-non-expressing versus PDCD1-expressing non-TREG CD4+ T cells (n = 24); Patients with <50 CD4+ T cells with TCR data or patients with 0 PDCD1+ CD4+ T cells were excluded; **P = 0.0018 by nonparametric two-tailed Wilcoxon matched-pairs signed rank test. g, Flow-cytometric analysis of IL-2 expression and proportion of IL-2+ cells in PD-1negCD4+ T cells versus PD-1+CD4+ T cells from PBT patients (n = 10); n.s. denotes P = 0.37 by non-parametric two-tailed Wilcoxon matched-pairs signed rank test.

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Upadhye, A., Meza Landeros, K.E., Ramírez-Suástegui, C. et al. Intra-tumoral T cells in pediatric brain tumors display clonal expansion and effector properties. Nat Cancer (2024). https://doi.org/10.1038/s43018-023-00706-9

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