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Molecular clustering on ctDNA improves the prognostic stratification of DLBCL patients compared to ctDNA levels.

Authors: Moia R; Talotta D; Terzi Di Bergamo L; Almasri M; Dondolin R; Salehi M; Cosentino C; +45 Authors

Molecular clustering on ctDNA improves the prognostic stratification of DLBCL patients compared to ctDNA levels.

Abstract

Circulating tumor DNA (ctDNA) levels can help predict outcomes in diffuse large B-cell lymphoma (DLBCL), but its integration with DLBCL molecular clusters remains unexplored. Using the LymphGen tool in 77 DLBCL cases with both ctDNA and tissue biopsy, a 95.8% concordance rate in molecular cluster assignment was observed, showing the reproducibility of molecular clustering on ctDNA. A multicenter, prospective cohort of 166 patients with newly diagnosed DLBCL was analyzed for ctDNA levels and molecular clusters using cancer personalized profiling by deep sequencing. Patients with ctDNA levels of <2.5 log10 haploid genome equivalents (hGE)/mL had a 4-year progression-free survival (PFS) and overall survival (OS) of 71.7% and 85.7%, respectively, compared with 50.3% and 61.0% for those with higher ctDNA levels (P = .0018 and P = .0017). Recursive partitioning showed that patients with ctDNA levels of ≥2.5 log10 hGE/mL were further stratified by clusters ST2/BN2. In this group, ST2/BN2 patients associated with a favorable outcome with a 4-year PFS and OS of 87.5% and 100%, respectively, compared to 38.0% and 47.1% for other clusters (P = .003 and P = .001). Combining ctDNA levels and ST2/BN2 clusters improved outcome prediction. Low-risk patients (n = 51), characterized by ctDNA levels of <2.5 log10 hGE/mL and/or BN2/ST2 cluster, had a 4-year PFS and OS of 75.3% and 87.8%, respectively. High-risk patients (n = 115), with ctDNA levels of ≥2.5 log10 hGE/mL and no BN2/ST2 cluster, had a 4-year PFS and OS of 38.0% and 47.1%, respectively. Adding cluster assignment to ctDNA levels improved the model's C statistics (0.63 vs 0.59 for PFS; 0.68 vs 0.63 for OS). Liquid biopsy thus provides a multilayered approach for outcome prediction in DLBCL.

Country
Italy
Keywords

610, ctdna; dlbcl; molecular clustering

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citations
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
Average
Average
Related to Research communities
Cancer Research