Abstract

Diagnostic and prognostic evaluation of chronic lymphocytic leukemia (CLL) involves blood cell counts, immunophenotyping, IgVH mutation status, and cytogenetic analyses. We generated B-cell associated gene-signatures (BAGS) based on six naturally occurring B-cell subsets within normal bone marrow. Our hypothesis is that by segregating CLL according to BAGS, we can identify subtypes with prognostic implications in support of pathogenetic value of BAGS. Microarray-based gene-expression samples from eight independent CLL cohorts (1,024 untreated patients) were BAGS-stratified into pre-BI, pre-BII, immature, naïve, memory, or plasma cell subtypes; the majority falling within the memory (24.5–45.8%) or naïve (14.5–32.3%) categories. For a subset of CLL patients (n = 296), time to treatment (TTT) was shorter amongst early differentiation subtypes (pre-BI/pre-BII/immature) compared to late subtypes (memory/plasma cell, HR: 0.53 [0.35–0.78]). Particularly, pre-BII subtype patients had the shortest TTT among all subtypes. Correlates derived for BAGS subtype and IgVH mutation (n = 405) revealed an elevated mutation frequency in late vs. early subtypes (71% vs. 45%, P < .001). Predictions for BAGS subtype resistance towards rituximab and cyclophosphamide varied for rituximab, whereas all subtypes were sensitive to cyclophosphamide. This study supports our hypothesis that BAGS-subtyping may be of tangible prognostic and pathogenetic value for CLL patients.

Highlights

  • Patients with chronic lymphocytic leukemia (CLL) experience a variable disease course

  • We sought to identify differentiation patterns expressed in end-stage CLL cells, using these to classify the disease into subtypes that resemble normal bone marrow (BM) Bcell subsets

  • The six distinct B-cell subsets from normal BM were first evaluated by hierarchical clustering of gene expression using the membrane markers used for subset acquisition and sorting

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Summary

Introduction

Patients with chronic lymphocytic leukemia (CLL) experience a variable disease course. The precise cell-of-origin in CLL remains under debate [10,11] and any direct link to a normal B-cell subset has proven difficult given that no single B-cell population shares the unique CD5+, CD19+, CD20+, and CD23+ immunophenotype characteristic of CLL [6] With this in mind, we sought to identify differentiation patterns expressed in end-stage CLL cells, using these to classify the disease into subtypes that resemble normal bone marrow (BM) Bcell subsets. As the first step in achieving this aim, we recently generated B-cell associated gene signatures (BAGS) for the different developmental stages of normal B-cells in blood, tonsils, thymus, and BM [12] These BAGS signatures serve as a reference material against which tumor derived samples can be challenged. This enables us to classify B-cell malignancies in terms of their cellular phenotype, which may, in turn, generate insights into clonal selection and evolution

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