增殖史是影响脾边缘区淋巴瘤临床结果的一个新因素

Helen Parker, Amatta Mirandari, Carolina Jaramillo Oquendo, Martí Duran-Ferrer, Benjamin Stevens, Lara Buermann, Harindra E. Amarasinghe, Jaya Thomas, Latha Kadalayil, Louise Carr, Shama Syeda, Methusha Sakthipakan, Marina Parry, Zadie Davis, Neil McIver-Brown, Aliki Xochelli, Sarah Ennis, Lydia Scarfo, Paolo Ghia, Christina Kalpadakis, Gerassimos Pangalis, Davide Rossi, Simon Wagner, Matthew Ahearne, Marc Seifert, Christoph Plass, Dieter Weichenhan, Eva Kimby, Lesley-Ann Sutton, Richard Rosenquist, Francesco Forconi, Kostas Stamatopoulos, Marta Salido, Ana Ferrer, Catherine Thieblemont, Viktor Ljungström, Rose-Marie Amini, David Oscier, Renata Walewska, Matthew J.J. Rose-Zerilli, Jane Gibson, José Ignacio Martín-Subero, Christopher Oakes, Dean Bryant, Jonathan C Strefford
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引用次数: 0

摘要

epiCMIT(表观遗传学决定的累积有丝分裂)有丝分裂钟通过异染色质和含 H3K27me3 染色质的 DNA 甲基化变化追踪 B 细胞有丝分裂的历史。虽然高分与CLL和MCL的不良预后相关,但其在SMZL中的预后意义尚不清楚。利用 DNA 甲基化芯片从 142 个 SMZL 病例中得出 epiCMIT 值,并将其与基因组、转录组和临床数据相关联。作为连续变量的 EpiCMIT 在女性(p=0.02)、IGHV1-2*04 等位基因使用率(p<0001)、中间 IGHV 体细胞高突变负荷(97-99.9%,p=0.04)、突变负荷增加(25 vs. 17 mut/Mb,p=0.001)、驱动基因突变[KLF2(p<0.001)、NOTCH2(p<0.01)、TP53(p=0.01)、KMT2D(p<0.001)]和del(7q)(p=0.01)。epiCMIT 与端粒长度之间的负相关(r=-0.29 p<0.001)支持累积增殖与端粒损耗之间的关联。单变量分析强调 epiCMIT 是较短无治疗生存期(TFS)的可靠预测指标,而多变量分析则证实 epiCMIT 是较短 TFS 的独立标志物。总之,我们的匹配多组学数据集促进了 SMZL 的临床生物学特征描述,并将 epiCMIT 作为一个强有力的预后标志物,可识别高风险患者并预测缩短的无治疗生存期,从而为风险适应型患者管理提供了一种新工具。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Proliferative History Is a Novel Driver of Clinical Outcome in Splenic Marginal Zone Lymphoma
The epiCMIT (epigenetically-determined Cumulative MIToses) mitotic clock traces B-cell mitotic history via DNA methylation changes in heterochromatin and H3K27me3-containing chromatin. While high scores correlated with poor outcomes in CLL and MCL, its prognostic significance in SMZL remains unknown. Derived from 142 SMZL cases using DNA methylation microarrays, epiCMIT values were correlated with genomic, transcriptomic, and clinical data. EpiCMIT as a continuous variable was significantly higher in females (p=0.02), patients with IGHV1-2*04 allele usage (p<0001), intermediate IGHV somatic hypermutation load (97-99.9% identity, p=0.04), elevated mutational burden (25 vs. 17 mut/Mb, p=0.001), driver gene mutations [KLF2 (p<0.001), NOTCH2 (p<0.01), TP53 (p=0.01), KMT2D (p<0.001)], and del(7q) (p=0.01). Negative correlation between epiCMIT and telomere length (r=-0.29 p<0.001) supported the association between cumulated proliferation and telomere attrition. While univariate analysis highlighted epiCMIT as robust predictor of shorter treatment-free survival (TFS), multivariate analysis confirmed epiCMIT as an independent marker for shorter TFS. In summary, our matched multi-omic datasets facilitate the clinico-biological characterization of SMZL and introduces epiCMIT as a strong prognostic marker, identifying high-risk patients and predicting reduced treatment-free survival, hence providing a new tool for risk-adapted patient management.
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