IGHV-associated methylation signatures more accurately predict clinical outcomes of chronic lymphocytic leukemia patients than IGHV mutation load
Dianna Hussmann,
Anna Starnawska,
Louise Kristensen,
Iben Daugaard,
Astrid Thomsen,
Tina E. Kjeldsen,
Christine Søholm Hansen,
Jonas Bybjerg-Grauholm,
Karina Dalsgaard Johansen,
Maja Ludvigsen,
Thomas Kristensen,
Thomas Stauffer Larsen,
Michael Boe Møller,
Charlotte Guldborg Nyvold,
Lise Lotte Hansen,
Tomasz K. Wojdacz
Affiliations
Dianna Hussmann
Department of Biomedicine, Aarhus University, Aarhus
Anna Starnawska
Department of Biomedicine, Aarhus University, Aarhus, Denmark; The Lundbeck Foundation Initiative for Integrative Psychiatric Research, iPSYCH, Denmark; Center for Integrative Sequencing, iSEQ, Aarhus University, Aarhus, Denmark; Centre for Genomics and Personalized Medicine, CGPM, Aarhus University, Aarhus
Louise Kristensen
Department of Pathology, Odense University Hospital, Odense
Iben Daugaard
Department of Biomedicine, Aarhus University, Aarhus, Denmark; Department of Pathology, Aarhus University Hospital, Aarhus
Astrid Thomsen
Department of Biomedicine, Aarhus University, Aarhus
Tina E. Kjeldsen
Department of Biomedicine, Aarhus University, Aarhus
Christine Søholm Hansen
The Lundbeck Foundation Initiative for Integrative Psychiatric Research, iPSYCH, Denmark; Department for Congenital Disorders, Statens Serum Institut, Copenhagen
Jonas Bybjerg-Grauholm
The Lundbeck Foundation Initiative for Integrative Psychiatric Research, iPSYCH, Denmark; Department for Congenital Disorders, Statens Serum Institut, Copenhagen
Karina Dalsgaard Johansen
Department of Hematology, Aarhus University Hospital, Aarhus
Maja Ludvigsen
Department of Hematology, Aarhus University Hospital, Aarhus, Denmark; Department of Clinical Medicine, Aarhus University, Aarhus
Thomas Kristensen
Department of Pathology, Odense University Hospital, Odense
Thomas Stauffer Larsen
Department of Haematology, Odense University Hospital, Odense
Michael Boe Møller
Department of Pathology, Odense University Hospital, Odense
Charlotte Guldborg Nyvold
Haematology-Pathology Research Laboratory, Research Unit for Haematology and Research Unit for Pathology, University of Southern Denmark and Odense University Hospital, Odense
Lise Lotte Hansen
Department of Biomedicine, Aarhus University, Aarhus
Tomasz K. Wojdacz
Department of Biomedicine, Aarhus University, Aarhus, Denmark; Aarhus Institute of Advanced Studies, Aarhus University, Aarhus, Denmark; Independent Clinical Epigenetics Laboratory, Pomeranian Medical University, Szczecin
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.
