IGHV-associated methylation signatures more accurately predict clinical outcomes of chronic lymphocytic leukemia patients than IGHV mutation load

Author:

Hussmann Dianna,Starnawska Anna,Kristensen Louise,Daugaard Iben,Thomsen Astrid,Kjeldsen Tina E.,Hansen Christine Søholm,Bybjerg-Grauholm Jonas,Johansen Karina Dalsgaard,Ludvigsen Maja,Kristensen Thomas,Larsen Thomas Stauffer,Møller Michael Boe,Nyvold Charlotte Guldborg,Hansen Lise Lotte,Wojdacz Tomasz K.

Abstract

Currently, no molecular biomarker indexes 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 patient stratification procedure based on methylation signatures associated with mutation load of the IGHV gene. This procedure allowed us to predict the time to treatment (TTT) with HR 8.34 (95% CI, 4.54-15.30), as opposed to HR 4.35 (95% CI, 2.60-7.28) for IGHV mutation status. Detailed evaluation of 17 discrepant cases between the two classification procedures showed that these cases were incorrectly classified using IGHV status. Moreover, methylation-based classification stratified patients with different overall survival (OS) (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 which TTT, OS and relapse were available. Despite that 450K array methylation data did not contain all biomarkers used in our classification procedure, methylation signatures again stratified patients with significantly better accuracy than IGHV mutation load regarding all available clinical outcomes. Thus, stratification using IGHV-associated methylation signatures may provide improved prognostic power than IGHV mutation status.

Publisher

Ferrata Storti Foundation (Haematologica)

Subject

Hematology

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3