Higher-order connections between stereotyped subsets: implications for improved patient classification in CLL.

Publication Date

2020

Journal Title

Blood

Abstract

Chronic lymphocytic leukemia (CLL) is characterized by the existence of subsets of patients with (quasi)identical, stereotyped B cell receptor immunoglobulins (BcR IG). Patients in certain major stereotyped subsets often display remarkably consistent clinicobiological profiles, suggesting that the study of BcR IG stereotypy in CLL has important implications for understanding disease pathophysiology and refining clinical decision-making. Nevertheless, several issues remain open, especially pertaining to the actual frequency of BcR IG stereotypy and major subsets, as well as the existence of higher-order connections between individual subsets. In order to address these issues, we investigated clonotypic IGHV-IGHD-IGHJ gene rearrangements in a series of 29,856 patients with CLL, by far the largest series worldwide. We report that the stereotyped fraction of CLL peaks at 41% of the entire cohort and that all 19 previously identified major subsets retained their relative size and ranking, while 10 new ones emerged; overall, major stereotyped subsets had a cumulative frequency of 13.5%. Higher-level relationships were evident between subsets, particularly for major stereotyped subsets with unmutated IGHV genes (U-CLL), for which close relations with other subsets, termed 'satellites', were identified. Satellite subsets accounted for 3% of the entire cohort. These results confirm our previous notion that major subsets can be robustly identified and are consistent in relative size, hence representing distinct disease variants amenable to compartmentalized research with the potential of overcoming the pronounced heterogeneity of CLL. Furthermore, the existence of satellite subsets reveals a novel aspect of repertoire restriction with implications for refined molecular classification of CLL.

Volume Number

35

Issue Number

4

Pages

587-594

Document Type

Article

Status

Faculty

Facility

School of Medicine

Primary Department

Molecular Medicine

Additional Departments

General Internal Medicine

PMID

32992344

DOI

10.1182/blood.2020007039

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