Flow Cytometry Now Accurate Enough to Detect Minimal Residual Disease

[Guest guest]

Leukemia. 2006 Oct 19; [Epub ahead of print]

Flow cytometric protein expression profiling as a systematic approach

for developing disease-specific assays: identification of a chronic

lymphocytic leukaemia-specific assay for use in rituximab-containing

regimens.

Rawstron AC, de Tute R, Jack AS, Hillmen P.

1Haematological Malignancy Diagnostic Service (HMDS), Leeds Teaching

Hospitals, Leeds, UK.

Depletion of disease below the levels detected by sensitive minimal

residual disease (MRD) assays is associated with prolonged survival

in chronic lymphocytic leukaemia (CLL). Flow cytometric MRD assays

are now sufficiently sensitive and rapid to guide the duration of

therapy in CLL, but generally rely on assessment of CD20 expression,

which cannot be accurately measured during and after therapeutic

approaches containing rituximab.

The aim of this study was to use analytical software developed for

microarray analysis to provide a systematic approach for MRD flow

assay development. Samples from CLL patients (n=49), normal controls

(n=21) and other B-lymphoproliferative disorders (n=12) were assessed

with a panel of 66 antibodies. The DNA-Chip analysis program was used

to identify discriminating antibodies, with hierarchical cluster

analysis to identify complementary combinations.

An iterative process was used: increasing numbers of patients were

assessed with smaller, more targeted antibody panels until a highly

specific combination (CD81/CD22/CD19/CD5) was identified. This

combination was as sensitive and specific as previously reported

assays and potentially applicable to blood and marrow samples from

patients treated with current therapeutic approaches including

rituximab.

This approach to the identification of disease-specific antibody

combinations for MRD analysis is readily applicable to a variety of

haematological disorders.

Leukemia advance online publication, 19 October 2006;

doi:10.1038/sj.leu.2404416.

PMID: 17051247 [PubMed - as supplied by publisher]