Loading…

Functional heterogeneity of lymphocytic patterns in primary melanoma dissected through single-cell multiplexing

In melanoma, the lymphocytic infiltrate is a prognostic parameter classified morphologically into 'brisk', 'non-brisk' and 'absent' entailing a functional association that has never been proved. Recently, it has been shown that lymphocytic populations can be very hetero...

Full description

Saved in:
Bibliographic Details
Published in:eLife 2020-02, Vol.9
Main Authors: Bosisio, Francesca Maria, Antoranz, Asier, van Herck, Yannick, Bolognesi, Maddalena Maria, Marcelis, Lukas, Chinello, Clizia, Wouters, Jasper, Magni, Fulvio, Alexopoulos, Leonidas, Stas, Marguerite, Boecxstaens, Veerle, Bechter, Oliver, Cattoretti, Giorgio, van den Oord, Joost
Format: Article
Language:English
Subjects:
Citations: Items that this one cites
Items that cite this one
Online Access:Get full text
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary:In melanoma, the lymphocytic infiltrate is a prognostic parameter classified morphologically into 'brisk', 'non-brisk' and 'absent' entailing a functional association that has never been proved. Recently, it has been shown that lymphocytic populations can be very heterogeneous, and that anti-PD-1 immunotherapy supports activated T cells. Here, we characterize the immune landscape in primary melanoma by high-dimensional single-cell multiplex analysis in tissue sections (MILAN technique) followed by image analysis, RT-PCR and shotgun proteomics. We observed that the brisk and non-brisk patterns are heterogeneous functional categories that can be further sub-classified into active, transitional or exhausted. The classification of primary melanomas based on the functional paradigm also shows correlation with spontaneous regression, and an improved prognostic value when compared to that of the brisk classification. Finally, the main inflammatory cell subpopulations that are present in the microenvironment associated with activation and exhaustion and their spatial relationships are described using neighbourhood analysis.
ISSN:2050-084X
2050-084X
DOI:10.7554/eLife.53008