Surface IgM expression and function are associated with clinical behavior, genetic abnormalities, and DNA methylation in CLL.

Annalisa D'Avola, Samantha Drennan, Ian Tracy, Isla Henderson, Laura Chiecchio, Marta Larrayoz, Matthew Rose-Zerilli, Jonathan Strefford, Christoph Plass, Peter W Johnson, Andrew J Steele, Graham Packham, Freda K Stevenson, Christopher C Oakes, Francesco Forconi

Journal: Blood 2017;128(6):816-26

PMID: 27301861

Abstract

Chronic lymphocytic leukemia (CLL) with unmutated (U-CLL) or mutated (M-CLL) immunoglobulin gene heavy-chain variable region (IGHV) displays different states of anergy, indicated by reduced surface immunoglobulin M (sIgM) levels and signaling, consequent to chronic (super)antigen exposure. The subsets also differ in the incidence of high-risk genetic aberrations and in DNA methylation profile, preserved from the maturational status of the original cell. We focused on sIgM expression and function, measured as intracellular Ca(2+) mobilization following stimulation, and probed correlations with clinical outcome. The relationship with genetic features and maturation status defined by DNA methylation of an 18-gene panel signature was then investigated. sIgM levels/signaling were higher and less variable in U-CLL than in M-CLL and correlated with disease progression between and within U-CLL and M-CLL. In U-CLL, increased levels/signaling associated with +12, del(17p) or NOTCH1 mutations. In M-CLL, there were fewer genetic lesions, although the methylation maturation status, generally higher than in U-CLL, varied and was increased in cases with lower sIgM levels/signaling. These features revealed heterogeneity in M-CLL and U-CLL with clear clinical correlations. Multivariate analyses with phenotype, genetic lesions, or DNA methylation maturation status identified high sIgM levels as a new potential independent factor for disease progression. Multiple influences on sIgM include the cell of origin, the clonal history of antigen encounter in vivo, and genetic damage. This simple marker compiles these different factors into an indicator worthy of further investigations for prediction of clinical behavior, particularly within the heterogeneous M-CLL subset.

© 2016 by The American Society of Hematology.

Address: Haematology Oncology Group, Cancer Sciences Unit, and Cancer Sciences Unit, Cancer Research UK and National Institute for Health Research (NIHR) Experimental Cancer Medicine Centres, University of Southampton, Southampton, United Kingdom;; Cancer Sciences Unit, Cancer Research UK and National Institute for Health Research (NIHR) Experimental Cancer Medicine Centres, University of Southampton, Southampton, United Kingdom;; Wessex Regional Genetics Laboratory, Salisbury National Health Service (NHS) Foundation Trust, Salisbury, United Kingdom;; Cancer Sciences Unit, Cancer Research UK and National Institute for Health Research (NIHR) Experimental Cancer Medicine Centres, University of Southampton, Southampton, United Kingdom; Cancer Genomics Group, Cancer Sciences Unit, Cancer Research UK and NIHR Experimental Cancer Medicine Centres, University of Southampton, Southampton, United Kingdom;; Division of Epigenomics and Cancer Risk Factors, The German Cancer Research Center, Heidelberg, Germany;; Cancer Sciences Unit, Cancer Research UK and National Institute for Health Research (NIHR) Experimental Cancer Medicine Centres, University of Southampton, Southampton, United Kingdom; Medical Oncology Department, University Hospital Southampton NHS Trust, Southampton, United Kingdom;; Division of Hematology, Department of Internal Medicine, The Ohio State University, Columbus, OH; and.; Haematology Oncology Group, Cancer Sciences Unit, and Cancer Sciences Unit, Cancer Research UK and National Institute for Health Research (NIHR) Experimental Cancer Medicine Centres, University of Southampton, Southampton, United Kingdom; Haematology Department, University Hospital Southampton NHS Trust, Southampton, United Kingdom.

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