Abstract P030

Cell-Free DNA as Potential Prognosticator and Tracking Tool in Classic Hodgkin Lymphoma: Molecular Profiling and Clinical Correlations.

Introduction: Cell-free DNA (cfDNA) analysis is a promising method to study and follow genomic aberrations in classic Hodgkin lymphoma (cHL) before and during treatment. Although TARC levels correlate with cHL disease activity with high positive predictive value, cfDNA holds the promise to be more sensitive to detect minimal residual disease (MRD). The main goal of this study was to use plasma cfDNA as a non-invasive tool for genomic profiling and compare dynamics during treatment with established biomarkers such as TARC and metabolic tumor volume (MTV).

Methods: We analyzed 42 diagnostic plasma samples of cHL patients and a total of 20 sequential plasma samples from 8 relapsed/refractory (r/r) patients during follow-up that were enriched in our cohort. Copy number variants (CNVs) and estimated tumor fraction (ETF) were determined using low-coverage whole-genome sequencing (lcWGS) data. Single nucleotide variants (SNVs) were called using a custom pipeline on targeted NGS data, as previously described (Veltmaat et al., 2023, JHO). For disease tracking, recurring SNVs detected at baseline were tracked, and expressed as haploid genome equivalents (hGE).

Results: Targeted NGS analysis of cfDNA revealed a median of 9 SNVs per sample, with SOCS1 being the top mutated gene in 60% of cases, followed by KMT2D, TNFAIP3 and IGLL5. Clustering based on EBV status and SOCS1 mutational status resulted in three distinct clusters: EBV+ & SOCS1 mutant (m), EBV− & SOCS1m, and EBV− & SOCS1 wild type (wt). Most r/r cases were observed in the EBV− & SOCS1m cluster (Fig. 1A). This cluster also demonstrated higher TARC levels and higher median VAF of SNVs along with a higher ETF compared to the other clusters (Fig. 1A-D). Median VAF of SNVs were strongly correlated with TARC levels (Fig. 1E). In the sequential samples, ETF and hGE showed dynamics that were similar to TARC and MTV in most patients. Relapses as defined by MTV and TARC showed an increase in either hGE or ETF in 6/8 patients. Two examples are shown in Figure 1F.

Conclusion: In this study, we showed the feasibility of cfDNA analyses for genomic profiling at diagnosis and disease tracking during treatment. A possible increased risk of relapse in patients within the EBV− & SOCS1m cluster was observed. Improvements in sensitivity should elucidate whether cfDNA can be used as a more sensitive biomarker for MRD in cHL, offering additional information as compared to TARC and imaging.