What question did this study set out to answer?

This research aims to identify mechanisms behind resistance to checkpoint inhibitors in leiomyosarcoma patients.

May 29, 2026Journal of Clinical Oncology0 citations

Identification of checkpoint inhibitor resistance mechanisms in leiomyosarcoma through enrichment of active chromatin-associated cell-free DNA.

CLCarlos Diego Holanda LopesUniversidade Federal do Rio de Janeiro HWHsin-Ta Wu KDKatharine DilgerCalifornia State University System

Key Points

This research aims to identify mechanisms behind resistance to checkpoint inhibitors in leiomyosarcoma patients.
Analyzed plasma samples at baseline and disease progression (n=52 total: 30 at baseline, 22 at progression).
Utilized cfDNAac capture platform to profile active chromatin-associated cell-free DNA.
Conducted univariate analysis and recursive feature elimination to correlate features with clinical benefit rate and progression-free survival.
1,570 baseline cfDNAac features distinguished patients achieving clinical benefit rate (CBR) from those who did not (n=8 vs 22, p < 0.01).
Immune-related signatures in CBR group were significantly associated with longer progression-free survival (p < 0.05).
Higher baseline tumor fraction (>5%) correlated with reduced CBR (p < 0.05), while recurrent CNV losses on chromosome 15 were linked to improved PFS (HR = 2.48; 95% CI: 0.99-6.22; p = 0.052).

Abstract

11545 Background: Leiomyosarcoma (LMS) is a sarcoma subtype with poor metastatic outcomes and limited treatment options. Checkpoint inhibitors (CPI) combination therapy may benefit LMS patients (pts). We previously showed (Lopes, ASCO 2025) that a liquid biopsy assay enriching for active chromatin–associated cell-free DNA (cfDNAac) identified biomarkers predicting clinical benefit in LMS pts treated with durvalumab plus olaparib or cediranib (NCT03851614). Here, we report longitudinal cfDNAac findings at baseline and progression. Methods: Plasma samples at baseline (n=30) and disease progression (n=22) were analyzed using a cfDNAac capture platform. Univariate analysis and recursive feature elimination identified genomic features associated with clinical benefit rate (CBR; complete response/partial response or stable disease >6 months). Molecular transcriptomic profiles, pathway enrichment, and copy number variation (CNV) were analyzed and correlated with CBR and progression-free survival (PFS). Linear mixed-effects models assessed temporal differences in cfDNAac-derived biomarkers between CBR and non-CBR groups. Results: A total of 1,570 baseline cfDNAac features distinguished pts who achieved CBR from those who did not (n=8 vs 22, p 5%) was also associated with reduced CBR (p < 0.05) and shorter PFS (HR = 3.33; CI: 1.32-8.40 p < 0.01). Recurrent CNV losses on chromosome 15 correlated with improved PFS (HR = 2.48; 95% CI: 0.99-6.22; p = 0.052) and CBR (p = 0.0073). At progression, these CNV reverted in CBR pts but remained stable in non-CBR patients. Conclusions: This active chromatin-associated cell-free DNA profiling enables a non-invasive monitoring of dynamic tumor microenvironment remodeling over time and provides insights into emerging mechanisms of resistance to CPI in LMS pts.

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