Abstract
Therapies that boost the anti-tumor responses of cytotoxic T lymphocytes (CTLs) have shown promise; however, clinical responses to the immunotherapeutic agents currently available vary considerably, and the molecular basis of this is unclear. We performed transcriptomic profiling of tumor-infiltrating CTLs from treatment-naive patients with lung cancer to define the molecular features associated with the robustness of anti-tumor immune responses. We observed considerable heterogeneity in the expression of molecules associated with activation of the T cell antigen receptor (TCR) and of immunological-checkpoint molecules such as 4-1BB, PD-1 and TIM-3. Tumors with a high density of CTLs showed enrichment for transcripts linked to tissue-resident memory cells (TRM cells), such as CD103, and CTLs from CD103hi tumors displayed features of enhanced cytotoxicity. A greater density of TRM cells in tumors was predictive of a better survival outcome in lung cancer, and this effect was independent of that conferred by CTL density. Here we define the 'molecular fingerprint' of tumor-infiltrating CTLs and identify potentially new targets for immunotherapy.
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Acknowledgements
We thank M. Chamberlain, K. Amer, C. Fixmer and B. Johnson for assistance with recruitment of study subjects and processing of samples; A. Easton for help with the assignment of scores to TILs; Z. Fu and J. Greenbaum for help with the processing and analysis of sequencing data; and H. Cheroutre, M. Kronenberg and J. Moore for reviewing the manuscript and providing insight. Supported by the Wessex Clinical Research Network and the National Institute of Health Research, UK (sample collection), Cancer Research UK (O.W., E.V.K., C.H.O.; and C11512/A20256, for CD103 pathology analysis), the William K. Bowes Jr Foundation (P.V. and A.-P.G.) and the Faculty of Medicine of the University of Southampton (P.V., T.S.-E. and C.H.O.).
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A.-P.G., P.S.F., T.S.-E., P.V. and C.H.O. conceived of the work and designed, performed and analyzed experiments; A.-P.G., D.S-C. and D.S. performed micro-scaled RNA-Seq experiments and analysis under the supervision of G.S., P.V. and C.H.O.; A.-P.G. performed data analysis and wrote the manuscript under the supervision of P.V. and C.H.O.; J.C., O.W., E.M.G.-M. and T.M. performed the cell isolations and immunohistochemistry data analysis under the supervision of G.J.T. and C.H.O.; and S.J.C., A.A., E.W. and E.V.K. assisted in patient recruitment, obtaining consent and sample collection.
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Integrated supplementary information
Supplementary Figure 1 RNA-Seq analysis of CD8+ TILs and N-TILs.
(a) Schematic representation of the tumor and cell types used for the study. HNSCC, head and neck squamous cell cancer; NSCLC, non-small cell lung cancer; TIL, tumor-infiltrating lymphocyte; N-TIL, non-tumor-infiltrating lymphocyte. (b) ‘Minus-average’ (MA) plots illustrate differentially expressed genes (red dots) for pairwise comparison of lung CD8+ N-TILs versus NSCLC CD8+ TILs (left), comparison of CD8+ TILs from NSCLC adenocarcinoma versus NSCLC squamous carcinoma (center), comparison of CD8+ TILs from HNSCC HPV-positive versus HPV-negative tumors (right) (DESeq2 analysis, Benjamini-Hochberg adjusted P < 0.05) (Online Methods and Supplementary Table 3). (c) Unsupervised hierarchical clustering of the transcriptomes of all CD8+ N-TILs (grey) and CD8+ TILs from NSCLC adenocarcinoma (red) and squamous carcinoma (pink), HPV-negative (light blue) and HPV-positive (dark blue) HNSCC, based on the expression of genes with the highest variance (n = 1000); each line represents an independent sample. (d) t-SNE plots of CD8+ T cell core transcriptome (symbol) from N-TILs and TILs of indicated cancer subtypes. Color scheme is identical to (c). Data are from one experiment (b-d).
Supplementary Figure 2 Heterogeneity in the expression of molecules that are targets of immunotherapy.
RNA-Seq analysis (row-wise normalized counts; bottom key) of various transcripts (left margin; one per row) in CD8+ TIL from patients with HNSCC (one per column); above, CD8+ TIL density (top row; top left key) and tumor stage (bottom row; far right key) for each patient. Data are from one experiment.
Supplementary Figure 3 Correlation of the abundance of PDCD1 and 4-1BB transcripts with clinical and pathological characteristics of patients with NSCLC.
(a) Correlation of PDCD1 transcript expression (log2 normalized counts) in NSCLC CD8+ TIL and the average number of tumor-infiltrating PD-1+ cells (quantified by immunohistochemistry). Each symbol represents an individual patient (n = 10) (r value and P value as in Fig. 3c,d). (b) Flow-cytometry analysis of the expression of PD-1 versus that of CD8 in live and singlet-gated CD45+CD3+ T cells obtained from matched PBMC, lung N-TILs and NSCLC TILs (above plots) from the same patient. (c) Correlation of age of NSCLC patients with PDCD1 or 4-1BB transcript expression (log2 normalized counts) in CD8+ TILs (left) (r value as in Fig. 3c,d). Bar graphs show PDCD1 or 4-1BB transcript expression in CD8+ TILs from patient groups categorized based on gender (first), tumor histology (second), tumor stage (third), performance status (fourth) and smoking status (fifth) of NSCLC patients; adenocarcinoma (Adeno), squamous carcinoma (Sq). Each symbol represents an individual patient (a,c); small horizontal lines are the mean (± s.e.m.). P value insignificant (Kolmogorov-Smirnov test). Data are from ten experiments (a) or one experiment (c) or representative of six experiments (b).
Supplementary Figure 4 TIL status of patients with NSCLC.
Graph shows the average number of CD8α+ cells per high power field (HPF) in tumor samples from each NSCLC patient (Online Methods).
Supplementary Figure 5 Pathways for which CD8+ TILs from NSCLC TILhi tumors show enrichment, and phenotype of CD8+CD103+ TILs.
(a) Ingenuity pathway analysis of genes downregulated in CD8+ TILs from NSCLC TILhi tumors relative to their expression in TILlo tumors (blue), encoding molecules associated with tissue egress (shape indicates function (key)). (b) Flow-cytometry analysis of the expression of CD69, CD49a, KLRG1, CD62L or CCR7 versus that of CD103 in live and singlet-gated CD45+CD3+CD8+ T cells obtained from NSCLC TILs (left); frequency of CD103+CD8+ or CD103−CD8+ TILs (n = 6) that express the indicated surface marker (right). * P = 0.0025 (CD69), P = 0.0025 (CD49a), P = 0.0016 (KLRG1), P = 0.0021 (CD62L) (paired Student’s two-tailed t-test). (c) Analysis of canonical pathways from the Ingenuity pathway analysis database (horizontal axis; bars in plot) for which CD8+ TILs from NSCLC TILhi tumors show enrichment (presented as in Fig. 2a) relative to their expression in TILlo tumors (P values as in Fig. 2a). Each symbol (b) represents an individual sample; small horizontal lines indicate the mean (± s.e.m.). Data are from one experiment (a,c) or from six experiments (b).
Supplementary Figure 6 CD103 (ITGAE) status of CD8+ TILs.
(a) Correlation of ITGAE transcript expression (log2 normalized counts) in NSCLC CD8+ TIL and the average number of tumor-infiltrating CD103+ cells (quantified by immunohistochemistry). Each symbol represents an individual patient (n = 10) (r value and P value as in Fig. 3c,d). (b) Classification of tumors on the basis of the expression of ITGAE (CD103) transcripts (normalized counts) in CD8+ TILs from each NSCLC patient (Online Methods). Data are from ten experiments (a) or one experiment (b).
Supplementary Figure 7 Density of CD103+ cells is predictive of survival in lung cancer.
a) Correlation of GZMB transcript expression (log2 normalized counts) in NSCLC CD8+ TIL and the average number of tumor-infiltrating GZMB+ cells (quantified by immunohistochemistry, n = 10) (r value and P value as in Fig. 3c,d). (b) Immunohistochemistry microscopy of cytokeratin, CD103, CD8α, PD-1 and GZMB (above images) in CD103lo and CD103hi NSCLC tumors (left margin). Scale bars, 100 μm. (c) Frequency of CD8+TILs expressing the indicated molecules that are either CD103+ or CD103- (n = 9-19). * P = 0.003 for GZMA and P = 0.0029 for GZMB (paired Student’s two-tailed t-test). (d) Frequency of CD103+CD8+ and CD103−CD8+ TILs (n = 9-19) that express the indicated molecules. * P = 0.047 (paired Student’s two-tailed t-test). (e) Expression (gMFI) of granzyme A or perforin in CD8+ TILs from CD103lo tumors (n = 3-5) or CD103hi (n = 7-8) tumors. NS, P value insignificant (Mann-Whitney test). (f) Survival of patients with lung adenocarcinoma from the TCGA dataset, classified on the basis of expression of ITGAE transcripts into CD103hi tumors (upper 10th percentile, n = 49) or CD103lo tumors (lower 10th percentile, n = 49). P = 0.0148 (log-rank test). Each symbol represents an individual patient (a,e) or sample (c,d); small horizontal line indicates the mean (± s.e.m.). Data are from ten experiments (a) or nine to nineteen experiments (c,d) or thirteen experiments (e) or are representative of 10 experiments (b).
Supplementary information
Supplementary Text and Figures
Supplementary Figures 1–7 (PDF 1604 kb)
Supplementary Table 1
Demographic, clinical and histopathological characteristics of cancer patients (XLSX 50 kb)
Supplementary Table 2
Details of libraries run for RNA sequencing (XLSX 71 kb)
Supplementary Table 3
List of differentially expressed genes in CD8+ TILs from NSCLC (XLSX 1333 kb)
Supplementary Table 4
Pathway analysis of differentially expressed genes (DEGs) in CD8+ TILs from NSCLC (XLS 40 kb)
Supplementary Table 5
Analysis of TCR beta chain sequences from RNA-Seq data of CD8+ N-TIL versus NSCLC CD8+ TILs (XLSX 43 kb)
Supplementary Table 6
List of differentially expressed genes in NSCLC CD8+ TILs from TILhi versus TILlo tumors. (XLSX 1449 kb)
Supplementary Table 7
List of differentially expressed genes in NSCLC CD8+ TILs from CD103hi versus CD103lo tumors (XLSX 1511 kb)
Supplementary Table 8
Pathway analysis of differentially expressed genes in CD103hi TILs from NSCLC (XLS 51 kb)
Supplementary Table 9
Disease-specific survival in NSCLC patients based on CD8α and CD103 density in tumor tissue (XLSX 75 kb)
Supplementary Table 10
Gene lists utilized for GSEA analysis (XLSX 23 kb)
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Ganesan, AP., Clarke, J., Wood, O. et al. Tissue-resident memory features are linked to the magnitude of cytotoxic T cell responses in human lung cancer. Nat Immunol 18, 940–950 (2017). https://doi.org/10.1038/ni.3775
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DOI: https://doi.org/10.1038/ni.3775
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