ArticleHaematologica2022
IGHV-associated methylation signatures more accurately predict clinical outcomes of chronic lymphocytic leukemia patients than IGHV mutation load.
Article in Haematologica, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
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Who cites it
7 citing papers in PubMed, 9 citations in OpenAlex.
- DNA methylation biomarkers-based pan-cancer classifier: predictive modeling for cancer classification.Genome medicine · 2026Article
- The Chronic Lymphocytic Leukemia Epigenome: A Powerful and Stable Framework for Understanding Biological and Clinical Heterogeneity.Hematology/oncology clinics of North America · 2025Review
- Methylation patterns at the adjacent CpG sites within enhancers are a part of cell identity.Epigenetics & chromatin · 2024Article
- Article
- The Role of Methylation in Chronic Lymphocytic Leukemia and Its Prognostic and Therapeutic Impacts in the Disease: A Systematic Review.Advances in hematology · 2024Review
- Long-read sequencing characterizes mitochondrial and plastid genome variants in Arabidopsis msh1 mutants.The Plant journal : for cell and molecular biology · 2022Article
- Evaluation of a Prognostic Epigenetic Classification System in Chronic Lymphocytic Leukemia Patients.Biomarker insights · 2022Article
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Authors and funding
16 authors at 5 institutions in 2 countries.
Funding
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Abstract
Currently, no molecular biomarker indices are used in standard care to make treatment decisions at diagnosis of chronic lymphocytic leukemia (CLL). We used Infinium MethylationEPIC array data from diagnostic blood samples of 114 CLL patients and developed a procedure to stratify patients based on methylation signatures associated with mutation load of the IGHV gene. This procedure allowed us to predict the time to treatment with a hazard ratio (HR) of 8.34 (95% confidence interval [CI]: 4.54-15.30), as opposed to a HR of 4.35 (95% CI: 2.60-7.28) using IGHV mutation status. Detailed evaluation of 17 cases for which the two classification procedures gave discrepant results showed that these cases were incorrectly classified using IGHV status. Moreover, methylation-based classification stratified patients with different overall survival (HR=1.82; 95% CI: 1.07-3.09), which was not possible using IGHV status. Furthermore, we assessed the performance of the developed classification procedure using published HumanMethylation450 array data for 159 patients for whom information on time to treatment, overall survival and relapse was available. Despite 450K array methylation data not containing all the biomarkers used in our classification procedure, methylation signatures again stratified patients with significantly better accuracy than did IGHV mutation load regarding all available clinical outcomes. Thus, stratification using IGHV-associated methylation signatures may provide better prognostic power than IGHV mutation status.
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