Predicting immunotherapy benefit in leiomyosarcoma through active chromatin cfDNA profiling.

Area of Science:

• Oncology
• Genomics
• Immunotherapy

Background:

• Leiomyosarcoma (LMS) is an aggressive soft-tissue sarcoma with unpredictable responses to cancer immunotherapies.
• Epigenomic dysregulation is a hallmark of LMS, influencing treatment outcomes.
• Checkpoint inhibitors (CPIs) offer potential therapeutic benefits, but patient selection remains a challenge.

Purpose of the Study:

• To evaluate a novel circulating cell-free DNA active chromatin (cfDNAac) liquid biopsy platform.
• To identify baseline biomarkers predictive of clinical benefit rate (CBR) in LMS patients treated with CPIs.
• To assess the association of cfDNAac profiles with progression-free survival (PFS).

Main Methods:

• Analysis of cfDNAac profiles from 30 LMS patients receiving durvalumab plus olaparib or cediranib.
• Utilized recursive feature elimination to identify discriminative cfDNAac signatures from 1,570 molecular features.
• Correlated cfDNAac signatures and tumor fraction with clinical benefit and survival outcomes.

Main Results:

• Patients achieving CBR showed enrichment in cell death, interferon-gamma signaling, and immune activation pathways.
• cfDNAac signatures related to B-cell and T-cell activation, and extracellular matrix organization correlated with improved PFS.
• A baseline tumor fraction >5% was negatively associated with CBR and PFS.

Conclusions:

• cfDNAac profiling is a promising non-invasive strategy for predicting clinical benefit from CPI-based therapy in LMS.
• Distinct copy number variation profiles identified in cfDNAac can characterize patients with CBR and predict PFS.
• Prospective validation of cfDNAac profiling in independent cohorts is needed to confirm its clinical utility.