Abstract Purpose: Immune checkpoint blockade (ICB) benefits only a subset of sarcoma patients. Biomarkers of response and resistance are needed to help guide patient selection. Patients and Methods: We analyzed peripheral blood and tumor samples from sarcoma patients treated on five ICB-based clinical trials. Baseline peripheral blood mononuclear cells (PBMCs) underwent 11-color flow cytometry to define T cell immunotypes. Baseline tumor tissue underwent RNA sequencing to classify tumors into four tumor microenvironment (TME) subtypes using consensus clustering of 29 functional gene expression signatures. Associations between immune features and clinical outcomes were assessed. A deep-learning model was applied to baseline hematoxylin and eosin (H four were classified as immune-enriched and two responded to ICB. Conclusions: Sarcoma patients with a PRO circulating T cell immunotype had inferior outcomes to ICB, while those with an immune-enriched/non-fibrotic TME had superior outcomes. Automated analysis of H&E slides showed promise in identifying patients with an immune-enriched TME. These findings support utilization of a multimodal approach toward identifying predictors of response to immunotherapy in sarcoma.
Building similarity graph...
Analyzing shared references across papers
Loading...
Rosenbaum et al. (Thu,) studied this question.
www.synapsesocial.com/papers/699010df2ccff479cfe571f6 — DOI: https://doi.org/10.1158/1078-0432.ccr-25-3419
Evan Rosenbaum
Fiona Ehrich
Mohammad Yosofvand
Clinical Cancer Research
Stanford University
Memorial Sloan Kettering Cancer Center
Bristol-Myers Squibb (Switzerland)
Building similarity graph...
Analyzing shared references across papers
Loading...