Radiomics to predict outcomes and abscopal response of patients with cancer treated with immunotherapy combined with radiotherapy using a validated signature of CD8 cells

Roger Sun, Nora Sundahl, Markus Hecht, Florian Putz, Andrea Lancia, Angela Rouyar, Marina Milic, Alexandre Carré, Enzo Battistella, Emilie Alvarez Andres, Stéphane Niyoteka, Edouard Romano, Guillaume Louvel, Jérôme Durand-Labrunie, Sophie Bockel, Rastilav Bahleda, Charlotte Robert, Celine Boutros, Maria Vakalopoulou, Nikos ParagiosBenjamin Frey, Jean Charles Soria, Christophe Massard, Charles Ferté, Rainer Fietkau, Piet Ost, Udo Gaipl, Eric Deutsch

Research output: Contribution to journalArticlepeer-review

Abstract

BACKGROUND: Combining radiotherapy (RT) with immuno-oncology (IO) therapy (IORT) may enhance IO-induced antitumor response. Quantitative imaging biomarkers can be used to provide prognosis, predict tumor response in a non-invasive fashion and improve patient selection for IORT. A biologically inspired CD8 T-cells-associated radiomics signature has been developed on previous cohorts. We evaluated here whether this CD8 radiomic signature is associated with lesion response, whether it may help to assess disease spatial heterogeneity for predicting outcomes of patients treated with IORT. We also evaluated differences between irradiated and non-irradiated lesions. METHODS: Clinical data from patients with advanced solid tumors in six independent clinical studies of IORT were investigated. Immunotherapy consisted of 4 different drugs (antiprogrammed death-ligand 1 or anticytotoxic T-lymphocyte-associated protein 4 in monotherapy). Most patients received stereotactic RT to one lesion. Irradiated and non-irradiated lesions were delineated from baseline and the first evaluation CT scans. Radiomic features were extracted from contrast-enhanced CT images and the CD8 radiomics signature was applied. A responding lesion was defined by a decrease in lesion size of at least 30%. Dispersion metrices of the radiomics signature were estimated to evaluate the impact of tumor heterogeneity in patient's response. RESULTS: A total of 94 patients involving multiple lesions (100 irradiated and 189 non-irradiated lesions) were considered for a statistical interpretation. Lesions with high CD8 radiomics score at baseline were associated with significantly higher tumor response (area under the receiving operating characteristic curve (AUC)=0.63, p=0.0020). Entropy of the radiomics scores distribution on all lesions was shown to be associated with progression-free survival (HR=1.67, p=0.040), out-of-field abscopal response (AUC=0.70, p=0.014) and overall survival (HR=2.08, p=0.023), which remained significant in a multivariate analysis including clinical and biological variables. CONCLUSIONS: These results enhance the predictive value of the biologically inspired CD8 radiomics score and suggests that tumor heterogeneity should be systematically considered in patients treated with IORT. This CD8 radiomics signature may help select patients who are most likely to benefit from IORT.

Original languageEnglish
JournalJournal for ImmunoTherapy of Cancer
Volume8
Issue number2
DOIs
Publication statusPublished - Nov 1 2020

Keywords

  • radioimmunotherapy
  • translational medical research
  • tumor biomarkers
  • tumor microenvironment

ASJC Scopus subject areas

  • Immunology and Allergy
  • Immunology
  • Molecular Medicine
  • Oncology
  • Pharmacology
  • Cancer Research

Fingerprint Dive into the research topics of 'Radiomics to predict outcomes and abscopal response of patients with cancer treated with immunotherapy combined with radiotherapy using a validated signature of CD8 cells'. Together they form a unique fingerprint.

Cite this