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Different spatial distribution of inflammatory cells in the tumor microenvironment of ABC and GBC subgroups of diffuse large B cell lymphoma

Diffuse Large B-Cell Lymphoma (DLBCL) presents a high clinical and biological heterogeneity, and the tumor microenvironment chracteristics are important in its  progression. The aim of this study was to evaluate tumor T, B cells, macrophages and mast cells distribution in GBC and ABC DLBCL subgroups...

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Detalles Bibliográficos
Autores principales: Guidolin, Diego, Tamma, Roberto, Annese, Tiziana, Tortorella, Cinzia, Ingravallo, Giuseppe, Gaudio, Francesco, Perrone, Tommasina, Musto, Pellegrino, Specchia, Giorgina, Ribatti, Domenico
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer International Publishing 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8505287/
https://www.ncbi.nlm.nih.gov/pubmed/33959827
http://dx.doi.org/10.1007/s10238-021-00716-w
Descripción
Sumario:Diffuse Large B-Cell Lymphoma (DLBCL) presents a high clinical and biological heterogeneity, and the tumor microenvironment chracteristics are important in its  progression. The aim of this study was to evaluate tumor T, B cells, macrophages and mast cells distribution in GBC and ABC DLBCL subgroups through a set of morphometric parameters allowing to provide a quantitative evaluation of the morphological features of the spatial patterns generated by these inflammatory cells.   Histological ABC and GCB samples were immunostained for CD4, CD8, CD68, CD 163, and tryptase in order to determine both percentage and position of positive cells in the tissue characterizing their spatial distribution. The results evidenced that cell patterns generated by CD4-, CD8-, CD68-, CD163- and tryptase-positive cell profiles exhibited a significantly higher uniformity index in ABC than in GCB subgroup. The positive-cell distributions appeared clustered in tissues from GCB, while in tissues from ABC such a feature was lower or absent. The combinations of spatial statistics-derived parameters can lead to better predictions of tumor cell infiltration than any classical morphometric method providing a more accurate description of the functional status of the tumor, useful for patient prognosis.