Immune checkpoints are predominantly co-expressed by clonally expanded $ CD4^{+} %$ FoxP3^{+} $ intratumoral T-cells in primary human cancers
Background In addition to anti-PD(L)1, anti-CTLA-4 and anti-LAG-3, novel immune checkpoint proteins (ICP)-targeted antibodies have recently failed to demonstrate significant efficacy in clinical trials. In these trials, patients were enrolled without screening for drug target expression. Although these novel ICP-targeted antibodies were expected to stimulate anti-tumor CD8 + T-cells, the rationale for their target expression in human tumors relied on pre-clinical IHC stainings and transcriptomic data, which are poorly sensitive and specific techniques for assessing membrane protein expression on immune cell subsets. Our aim was to describe ICP expression on intratumoral T-cells from primary solid tumors to better design upcoming neoadjuvant cancer immunotherapy trials. Methods We prospectively performed multiparameter flow cytometry and single-cell RNA sequencing (scRNA-Seq) paired with TCR sequencing on freshly resected human primary tumors of various histological types to precisely determine ICP expression levels within T-cell subsets. Results Within a given tumor type, we found high inter-individual variability for tumor infiltrating CD45 + cells and for T-cells subsets. The proportions of $ CD8^{+} $ T-cells (~ 40%), $ CD4^{+} $ $ FoxP3^{-} $ T-cells (~ 40%) and $ CD4^{+} $ $ FoxP3^{+} $ T-cells (~ 10%) were consistent across patients and indications. Intriguingly, both stimulatory (CD25, CD28, 4-1BB, ICOS, OX40) and inhibitory (PD-1, CTLA-4, PD-L1, CD39 and TIGIT) checkpoint proteins were predominantly co-expressed by intratumoral $ CD4^{+} %$ FoxP3^{+} $ T-cells. ScRNA-Seq paired with TCR sequencing revealed that T-cells with high clonality and high ICP expressions comprised over 80% of $ FoxP3^{+} $ cells among $ CD4^{+} $ T-cells. Unsupervised clustering of flow cytometry and scRNAseq data identified subsets of $ CD8^{+} $ T-cells and of $ CD4^{+} $ $ FoxP3^{-} $ T-cells expressing certain checkpoints, though these expressions were generally lower than in $ CD4^{+} $ $ FoxP3^{+} $ T-cell subsets, both in terms of proportions among total T-cells and ICP expression levels. Conclusions Tumor histology alone does not reveal the complete picture of the tumor immune contexture. In clinical trials, assumptions regarding target expression should rely on more sensitive and specific techniques than conventional IHC or transcriptomics. Flow cytometry and scRNAseq accurately characterize ICP expression within immune cell subsets. Much like in hematology, flow cytometry can better describe the immune contexture of solid tumors, offering the opportunity to guide patient treatment according to drug target expression rather than tumor histological type..
| Medienart: |
E-Artikel |
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| Erscheinungsjahr: |
2023 |
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| Erschienen: |
2023 |
| Enthalten in: |
Zur Gesamtaufnahme - volume:42 |
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| Enthalten in: |
Journal of experimental & clinical cancer research - 42(2023), 1 vom: 06. Dez. |
| Sprache: |
Englisch |
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| Links: |
Volltext [kostenfrei] |
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| Themen: |
Cancer |
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| Anmerkungen: |
© The Author(s) 2023 |
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| doi: |
10.1186/s13046-023-02897-6 |
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| funding: |
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| Förderinstitution / Projekttitel: |
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SPR054003350 |
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| 245 | 1 | 0 | |a Immune checkpoints are predominantly co-expressed by clonally expanded $ CD4^{+} %$ FoxP3^{+} $ intratumoral T-cells in primary human cancers |
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| 520 | |a Background In addition to anti-PD(L)1, anti-CTLA-4 and anti-LAG-3, novel immune checkpoint proteins (ICP)-targeted antibodies have recently failed to demonstrate significant efficacy in clinical trials. In these trials, patients were enrolled without screening for drug target expression. Although these novel ICP-targeted antibodies were expected to stimulate anti-tumor CD8 + T-cells, the rationale for their target expression in human tumors relied on pre-clinical IHC stainings and transcriptomic data, which are poorly sensitive and specific techniques for assessing membrane protein expression on immune cell subsets. Our aim was to describe ICP expression on intratumoral T-cells from primary solid tumors to better design upcoming neoadjuvant cancer immunotherapy trials. Methods We prospectively performed multiparameter flow cytometry and single-cell RNA sequencing (scRNA-Seq) paired with TCR sequencing on freshly resected human primary tumors of various histological types to precisely determine ICP expression levels within T-cell subsets. Results Within a given tumor type, we found high inter-individual variability for tumor infiltrating CD45 + cells and for T-cells subsets. The proportions of $ CD8^{+} $ T-cells (~ 40%), $ CD4^{+} $ $ FoxP3^{-} $ T-cells (~ 40%) and $ CD4^{+} $ $ FoxP3^{+} $ T-cells (~ 10%) were consistent across patients and indications. Intriguingly, both stimulatory (CD25, CD28, 4-1BB, ICOS, OX40) and inhibitory (PD-1, CTLA-4, PD-L1, CD39 and TIGIT) checkpoint proteins were predominantly co-expressed by intratumoral $ CD4^{+} %$ FoxP3^{+} $ T-cells. ScRNA-Seq paired with TCR sequencing revealed that T-cells with high clonality and high ICP expressions comprised over 80% of $ FoxP3^{+} $ cells among $ CD4^{+} $ T-cells. Unsupervised clustering of flow cytometry and scRNAseq data identified subsets of $ CD8^{+} $ T-cells and of $ CD4^{+} $ $ FoxP3^{-} $ T-cells expressing certain checkpoints, though these expressions were generally lower than in $ CD4^{+} $ $ FoxP3^{+} $ T-cell subsets, both in terms of proportions among total T-cells and ICP expression levels. Conclusions Tumor histology alone does not reveal the complete picture of the tumor immune contexture. In clinical trials, assumptions regarding target expression should rely on more sensitive and specific techniques than conventional IHC or transcriptomics. Flow cytometry and scRNAseq accurately characterize ICP expression within immune cell subsets. Much like in hematology, flow cytometry can better describe the immune contexture of solid tumors, offering the opportunity to guide patient treatment according to drug target expression rather than tumor histological type. | ||
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