Sarcoma microenvironment cell states and ecosystems are associated with prognosis and predict response to immunotherapy.

Characterization of the diverse malignant and stromal cell states that make up soft tissue sarcomas and their correlation with patient outcomes has proven difficult using fixed clinical specimens. Here, we employed EcoTyper, a machine-learning framework, to identify the fundamental cell states and cellular ecosystems that make up sarcomas on a large scale using bulk transcriptomes with clinical annotations. We identified and validated 23 sarcoma-specific, transcriptionally defined cell states, many of which were highly prognostic of patient outcomes across independent datasets.

Monitoring Sarcoma Response to Immune Checkpoint Inhibition and Local Cryotherapy with Circulating Tumor DNA Analysis.

Purpose: Immune checkpoint inhibition has led to promising responses in soft tissue sarcomas (STS), but the majority of patients do not respond and biomarkers of response will be crucial. Local ablative therapies may augment systemic responses to immunotherapy. We evaluated circulating tumor DNA (ctDNA) as a biomarker of response in patients treated on a trial combining immunotherapy with local cryotherapy for advanced STS.