While immune checkpoint-based immunotherapy (ICI) shows promising clinical results in patients with cancer, only a subset of patients responds favorably. Response to ICI is dictated by complex networks of cellular interactions between malignant and nonmalignant cells. Although insights into the mechanisms that modulate the pivotal antitumoral activity of cytotoxic T cells (Tcy) have recently been gained, much of what has been learned is based on single-cell analyses of dissociated tumor samples, resulting in a lack of critical information about the spatial distribution of relevant cell types. Here, we used multiplexed IHC to spatially characterize the immune landscape of metastatic melanoma from responders and nonresponders to ICI. Such high-dimensional pathology maps showed that Tcy gradually evolve toward an exhausted phenotype as they approach and infiltrate the tumor. Moreover, a key cellular interaction network functionally linked Tcy and PD-L1+ macrophages. Mapping the respective spatial distributions of these two cell populations predicted response to anti-PD-1 immunotherapy with high confidence. These results suggest that baseline measurements of the spatial context should be integrated in the design of predictive biomarkers to identify patients likely to benefit from ICI. SIGNIFICANCE: This study shows that spatial characterization can address the challenge of finding efficient biomarkers, revealing that localization of macrophages and T cells in melanoma predicts patient response to ICI. See related commentary by Smalley and Smalley, p. 3198.

Antoranz, A., Van Herck, Y., Bolognesi, M., Lynch, S., Rahman, A., Gallagher, W., et al. (2022). Mapping the Immune Landscape in Metastatic Melanoma Reveals Localized Cell-Cell Interactions That Predict Immunotherapy Response. CANCER RESEARCH, 82(18), 3275-3290 [10.1158/0008-5472.CAN-22-0363].

Mapping the Immune Landscape in Metastatic Melanoma Reveals Localized Cell-Cell Interactions That Predict Immunotherapy Response

Bolognesi, Maddalena M;Cattoretti, Giorgio;Bosisio, Francesca M
2022

Abstract

While immune checkpoint-based immunotherapy (ICI) shows promising clinical results in patients with cancer, only a subset of patients responds favorably. Response to ICI is dictated by complex networks of cellular interactions between malignant and nonmalignant cells. Although insights into the mechanisms that modulate the pivotal antitumoral activity of cytotoxic T cells (Tcy) have recently been gained, much of what has been learned is based on single-cell analyses of dissociated tumor samples, resulting in a lack of critical information about the spatial distribution of relevant cell types. Here, we used multiplexed IHC to spatially characterize the immune landscape of metastatic melanoma from responders and nonresponders to ICI. Such high-dimensional pathology maps showed that Tcy gradually evolve toward an exhausted phenotype as they approach and infiltrate the tumor. Moreover, a key cellular interaction network functionally linked Tcy and PD-L1+ macrophages. Mapping the respective spatial distributions of these two cell populations predicted response to anti-PD-1 immunotherapy with high confidence. These results suggest that baseline measurements of the spatial context should be integrated in the design of predictive biomarkers to identify patients likely to benefit from ICI. SIGNIFICANCE: This study shows that spatial characterization can address the challenge of finding efficient biomarkers, revealing that localization of macrophages and T cells in melanoma predicts patient response to ICI. See related commentary by Smalley and Smalley, p. 3198.
Articolo in rivista - Articolo scientifico
metastatic melanoma;
English
14-lug-2022
2022
82
18
3275
3290
none
Antoranz, A., Van Herck, Y., Bolognesi, M., Lynch, S., Rahman, A., Gallagher, W., et al. (2022). Mapping the Immune Landscape in Metastatic Melanoma Reveals Localized Cell-Cell Interactions That Predict Immunotherapy Response. CANCER RESEARCH, 82(18), 3275-3290 [10.1158/0008-5472.CAN-22-0363].
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/10281/387989
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