2026-04-19T15:52:16Zhttps://recercat.cat/oai/request

oai:recercat.cat:11351/118002025-10-24T10:37:07Zcom_2072_378070com_2072_378040col_2072_378092

Spatial distribution of tumour immune infiltrate predicts outcomes of patients with high-risk soft tissue sarcomas after neoadjuvant chemotherapy Pasquali, Sandro Vallacchi, Viviana Lalli, Luca Collini, Paola Barisella, Marta Romagosa, Cleofé Sarcoma - Tractament Tumors de parts toves - Tractament Limfòcits Avaluació de resultats (Assistència sanitària) DISEASES::Neoplasms::Neoplasms by Site::Soft Tissue Neoplasms Other subheadings::Other subheadings::Other subheadings::/drug therapy ANALYTICAL, DIAGNOSTIC AND THERAPEUTIC TECHNIQUES, AND EQUIPMENT::Therapeutics::Combined Modality Therapy::Neoadjuvant Therapy DISEASES::Neoplasms::Neoplasms by Histologic Type::Neoplasms, Connective and Soft Tissue::Sarcoma ANATOMY::Cells::Blood Cells::Leukocytes::Leukocytes, Mononuclear::Lymphocytes::Lymphocytes, Tumor-Infiltrating ANALYTICAL, DIAGNOSTIC AND THERAPEUTIC TECHNIQUES, AND EQUIPMENT::Diagnosis::Prognosis::Treatment Outcome ENFERMEDADES::neoplasias::neoplasias por localización::neoplasias de los tejidos blandos Otros calificadores::Otros calificadores::Otros calificadores::/farmacoterapia TÉCNICAS Y EQUIPOS ANALÍTICOS, DIAGNÓSTICOS Y TERAPÉUTICOS::terapéutica::tratamiento combinado::tratamiento neoadyuvante ENFERMEDADES::neoplasias::neoplasias por tipo histológico::neoplasias de tejido conjuntivo y de tejidos blandos::sarcoma ANATOMÍA::células::células sanguíneas::leucocitos::leucocitos mononucleares::linfocitos::linfocitos infiltrantes de tumor TÉCNICAS Y EQUIPOS ANALÍTICOS, DIAGNÓSTICOS Y TERAPÉUTICOS::diagnóstico::pronóstico::resultado del tratamiento Anthracycline; Neoadjuvant chemotherapy; Soft tissue sarcomas Antraciclina; Quimioterapia neoadyuvante; Sarcomas de tejidos blandos Antraciclina; Quimioteràpia neoadjuvant; Sarcomes de teixits tous Background: Anthracycline-based neoadjuvant chemotherapy (NAC) may modify tumour immune infiltrate. This study characterized immune infiltrate 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 infiltrate (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 infiltrating 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 modifier of tumour immune infiltrate in STS. Pharmamar; Italian Ministry of Health [RF-2019-12370923; GR-2016-02362609]; 5 × 1000 Funds—2016, Italian Ministry of Health; AIRC Grant [ID#28546]. 2025-10-24T10:37:07Z 2025-10-24T10:37:07Z 2025-10-24T10:37:07Z 2024-07-31T08:20:05Z 2024-07-31T08:20:05Z 2024-07-16 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion http://hdl.handle.net/11351/11800 eBioMedicine;106 https://doi.org/10.1016/j.ebiom.2024.105220 Attribution-NonCommercial 4.0 International http://creativecommons.org/licenses/by-nc/4.0/ info:eu-repo/semantics/openAccess Elsevier Scientia