Molecular map of chronic lymphocytic leukemia and its impact on outcome

生物 慢性淋巴细胞白血病 遗传学 白血病 免疫学 计算生物学 癌症研究
作者
Binyamin A. Knisbacher,Ziao Lin,Cynthia K. Hahn,Ferran Nadeu,Martí Duran‐Ferrer,Kristen E. Stevenson,Eugen Tausch,Julio Delgado,Alex Barbera-Mourelle,Amaro Taylor‐Weiner,Pablo Bousquets‐Muñoz,Ander Díaz‐Navarro,Andrew Dunford,Shankara Anand,Helene Kretzmer,Jesús Gutiérrez‐Abril,Sara López-Tamargo,Stacey M. Fernandes,Clare Sun,Mariela Sivina,Laura Z. Rassenti,Christof Schneider,Shuqiang Li,Laxmi Parida,Alexander Meissner,François Aguet,Jan A. Burger,Adrian Wiestner,Thomas J. Kipps,Jennifer R. Brown,Michael Hallek,Chip Stewart,Donna Neuberg,José I. Martín‐Subero,Xosé S. Puente,Stephan Stilgenbauer,Catherine J. Wu,Elı́as Campo,Gad Getz
出处
期刊:Nature Genetics [Springer Nature]
卷期号:54 (11): 1664-1674 被引量:91
标识
DOI:10.1038/s41588-022-01140-w
摘要

Recent advances in cancer characterization have consistently revealed marked heterogeneity, impeding the completion of integrated molecular and clinical maps for each malignancy. Here, we focus on chronic lymphocytic leukemia (CLL), a B cell neoplasm with variable natural history that is conventionally categorized into two subtypes distinguished by extent of somatic mutations in the heavy-chain variable region of immunoglobulin genes (IGHV). To build the ‘CLL map,’ we integrated genomic, transcriptomic and epigenomic data from 1,148 patients. We identified 202 candidate genetic drivers of CLL (109 new) and refined the characterization of IGHV subtypes, which revealed distinct genomic landscapes and leukemogenic trajectories. Discovery of new gene expression subtypes further subcategorized this neoplasm and proved to be independent prognostic factors. Clinical outcomes were associated with a combination of genetic, epigenetic and gene expression features, further advancing our prognostic paradigm. Overall, this work reveals fresh insights into CLL oncogenesis and prognostication. A genomic, transcriptomic and epigenomic analysis of chronic lymphocytic leukemia identifies genetic drivers and molecular subtypes associated with clinical outcomes.

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