Spatial distribution of tumour immune in fi ltrate predicts outcomes of patients with high-risk soft tissue sarcomas after neoadjuvant chemotherapy

Background Anthracycline-based neoadjuvant chemotherapy (NAC) may modify tumour immune in fi ltrate. This study characterized immune in fi ltrate spatial distribution after NAC in primary high-risk soft tissue sarcomas (STS) and investigate association with prognosis. Methods The ISG-STS 1001 trial...

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Detalles Bibliográficos
Autores: Pasquali, S, Vallacchi, V, Lalli, L, Collini, P, Barisella, M, Romagosa, C, Bague, S, Coindre, JM, Dei Tos, AP, Palmerini, E, Quagliuolo, V, Martin-Broto, J, Lopez-Pousa, A, Grignani, G, Blay, JY, Beveridge, RD, Casiraghi, E, Brich, S, Renne, SL, Bergamaschi, L, Vergani, B, Sbaraglia, M, Casali, PG, Rivoltini, L, Stacchiotti, S, Gronchi, A
Tipo de recurso: artículo
Estado:Versión publicada
Fecha de publicación:2024
País:España
Institución:Institut d’Investigació Biomèdica Sant Pau (IIB Sant Pau)
Repositorio:r-IIB SANT PAU. Repositorio Institucional de Producción Científica del Instituto de Investigación Biomédica Sant Pau
OAI Identifier:oai:iibsantpau.fundanetsuite.com:p18114
Acceso en línea:https://iibsantpau.fundanetsuite.com/Publicaciones/ProdCientif/PublicacionFrw.aspx?id=18114
http://ddd.uab.cat/record/299788
Access Level:acceso abierto
Palabra clave:Soft tissue sarcomas
Tumour immune microenvironment
Neoadjuvant chemotherapy
Anthracycline
Descripción
Sumario:Background Anthracycline-based neoadjuvant chemotherapy (NAC) may modify tumour immune in fi ltrate. This study characterized immune in fi ltrate spatial distribution after NAC in primary high-risk soft tissue sarcomas (STS) and investigate association with prognosis. Methods The ISG-STS 1001 trial randomized STS patients to anthracycline plus ifosfamide (AI) or a histology-tailored (HT) NAC. Four areas of tumour specimens were sampled: the area showing the highest lymphocyte in fi ltrate (HI) at H & E; the area with lack of post-treatment changes (highest grade, HG); the area with post-treatment changes (lowest grade, LG); and the tumour edge (TE). CD3, CD8, PD-1, CD20, FOXP3, and CD163 were analyzed at immunohistochemistry and digital pathology. A machine learning method was used to generate sarcoma immune index scores (SIS) that predict patient disease-free and overall survival (DFS and OS). Findings Tumour in fi ltrating lymphocytes and PD-1+ cells together with CD163+ cells were more represented in STS histologies with complex compared to simple karyotype, while CD20+ B-cells were detected in both these histology groups. PD-1+ cells exerted a negative prognostic value irrespectively of their spatial distribution. Enrichment in CD20+ B-cells at HI and TE areas was associated with better patient outcomes. We generated a prognostic SIS for each tumour area, having the HI-SIS the best performance. Such prognostic value was driven by treatment with AI. Interpretation The different spatial distribution of immune populations and their different association with prognosis support NAC as a modi fi er of tumour immune in fi ltrate in STS.