Evidence map›Paper›PMID 40198333›Full record

ArticleAnnals of hematology2025

Molecular profiling of cell-free DNA from classic Hodgkin lymphoma patients identifies potential prognostic clusters and corresponds with disease dynamics.

Nick Veltmaat, Geok-Wee Tan, Yujie Zhong, Sophie Teesink, Martijn Terpstra, Johanna Bult, Marcel Nijland, Joost Kluiver, Arjan Diepstra, Anke van den Berg and 1 more

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Article in Annals of hematology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

2 citing papers in PubMed.

  1. Review
  2. Review
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

11 authors.

Nick VeltmaatDepartment of Hematology, University of Groningen, University Medical Center Groningen, Groningen, The Netherlands.
Geok-Wee TanDepartment of Pathology and Medical Biology, University of Groningen, University Medical Center Groningen, Groningen, The Netherlands.
Yujie ZhongDepartment of Pathology and Medical Biology, University of Groningen, University Medical Center Groningen, Groningen, The Netherlands.
Sophie TeesinkDepartment of Hematology, University of Groningen, University Medical Center Groningen, Groningen, The Netherlands.
Martijn TerpstraDepartment of Pathology and Medical Biology, University of Groningen, University Medical Center Groningen, Groningen, The Netherlands.
Johanna BultDepartment of Hematology, University of Groningen, University Medical Center Groningen, Groningen, The Netherlands.
Marcel NijlandDepartment of Hematology, University of Groningen, University Medical Center Groningen, Groningen, The Netherlands.
Joost KluiverDepartment of Pathology and Medical Biology, University of Groningen, University Medical Center Groningen, Groningen, The Netherlands.
Arjan DiepstraDepartment of Pathology and Medical Biology, University of Groningen, University Medical Center Groningen, Groningen, The Netherlands.
Anke van den BergDepartment of Pathology and Medical Biology, University of Groningen, University Medical Center Groningen, Groningen, The Netherlands.
Wouter J PlattelDepartment of Hematology, University of Groningen, University Medical Center Groningen, Groningen, The Netherlands. w.j.plattel@umcg.nl.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Cell-free DNA (cfDNA) analysis has advantages over tissue analysis for molecular profiling of classic Hodgkin lymphoma (cHL) at diagnosis and offers additional opportunities for sensitive non-invasive disease tracking during treatment. The aim of this study is to correlate cfDNA based molecular profiling with disease characteristics including serum Thymus and Activation Regulated Chemokine (TARC) levels and FDG-PET imaging, which are established markers of disease assessment. cfDNA isolated from plasma samples of 42 cHL patients was analyzed using low coverage whole genome and targeted next-generation sequencing. Patients were clustered in three groups based on Epstein-Barr virus (EBV) and SOCS1 mutational status. Patients in the EBV-negative (EBV-) & SOCS1 mutated (m) cluster had more extensive disease based on significantly higher serum TARC (sTARC) levels, higher metabolic tumor volume and increased risk of treatment failure. Additionally, the median variant allele frequency and mutational load was highest in the EBV- & SOCS1m cluster, which was validated in two external cohorts. The estimated tumor fraction and median variant allele frequency of the single nucleotide variants correlated with sTARC levels. Disease tracking over time demonstrated cfDNA level dynamics that partly resembled sTARC levels and imaging results. In conclusion, we show that cfDNA based clustering on EBV status and SOCS1 mutational status correlates with adverse disease characteristics and increased risk of treatment failure. CfDNA-based disease tracking has the potential to serve as a sensitive tool that can complement existing response assessment methods in cHL patients.

Indexed as

Cell-Free Nucleic AcidsHodgkin DiseaseAdolescentAdultAgedBiomarkers, TumorChemokine CCL17Epstein-Barr Virus InfectionsFemaleHerpesvirus 4, HumanHigh-Throughput Nucleotide SequencingHumansMaleMiddle AgedMutationPrognosisBiomarkers, TumorCCL17 protein, humanCell-Free Nucleic AcidsChemokine CCL17SOCS1 protein, humanSuppressor of Cytokine Signaling 1 ProteinCell-free DNACirculating tumor DNAHodgkin lymphomaLiquid biopsyMinimal residual diseaseTARC

Identifiers

PMID40198333
PMCPMC12031755

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