Profiles of Surface Mosaics on Chronic Lymphocytic Leukemias Distinguish Stable and Progressive Subtypes

Pauline Yu-Hsiu Huang1, Philippa Kohnke1, Larissa Belov1, Giles Best2, Stephen Peter Mulligan2, Richard Ian Christopherson1

1School of Molecular Bioscience, University of Sydney, Sydney, NSW 2006
2Northern Blood Research Centre, Kolling Institute of Medical Research, Royal North Shore Hospital, St. Leonards, NSW 2065


Purpose. Chronic lymphocytic leukemia (CLL) is a heterogeneous disease, some patients may survive for many years, while 20-30% of patients progress and may die within several years. Currently, there is not a single procedure that enables accurate prognosis and triaging of those patients who need immediate and aggressive treatment. All CLL cells are characterised by the expression of the B-cell antigens CD19, CD20, CD21, CD22 and CD23, with aberrant expression of the T-cell antigen CD5. Methods. We have developed a CD antibody microarray (DotScan) containing 182 immobilised CD antibodies that has been used to obtain extensive surface profiles of CLL cells obtained from 96 patients. Results. Of these 182 antigens, 27 were significantly differentially expressed between stable, stable-progressive and progressive CLL. Some of these antigens are not expressed on normal B-cells and may be targets for therapeutic antibodies against CLL. Unsupervised hierarchical clustering of the surface profiles from 96 patients showed that those with progressive CLL could be distinguished based solely upon this ‘disease signature’. The sensitivity (proportion of actual positives correctly identified) was 67.9%, the specificity (proportion of negatives correctly identified) was 77.5%, and the accuracy was 71.9%. Conclusions. Considerable effort by a number of research groups has resulted in identification of individual markers for progressive CLL, but their collective use is yet to provide a test that identifies CLL patients at risk. Data presented here provide a basis for development of a simple test using an antibody microarray.

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J Pharm Pharm Sci, 16 (2): 231-237, 2013

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