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Analysis of human leukaemias and lymphomas using extensive immunophenotypes from an antibody microarray
Summary A novel antibody microarray has been developed that provides an extensive immunophenotype of leukaemia cells. The assay is a solid phase cell‐capture technique in which 82 antigens are studied simultaneously. This paper presents the analysis of 733 patients with a variety of leukaemias and l...
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Published in: | British journal of haematology 2006-10, Vol.135 (2), p.184-197 |
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Main Authors: | , , , , , , , , , , , , , , , , , , , , , |
Format: | Article |
Language: | English |
Subjects: | |
Citations: | Items that this one cites Items that cite this one |
Online Access: | Get full text |
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Summary: | Summary
A novel antibody microarray has been developed that provides an extensive immunophenotype of leukaemia cells. The assay is a solid phase cell‐capture technique in which 82 antigens are studied simultaneously. This paper presents the analysis of 733 patients with a variety of leukaemias and lymphomas from peripheral blood and bone marrow. Discriminant Function Analysis of the expression profiles from these 733 patients and 63 normal subjects were clustered and showed high levels of consistency with diagnoses obtained using conventional clinical and laboratory criteria. The overall levels of consensus for classification using the microarray compared with established criteria were 93·9% (495/527 patients) for peripheral blood and 97·6% (201/206 patients) for bone marrow aspirates, showing that the extensive phenotype alone was frequently able to classify the disease when the leukaemic clone was the dominant cell population present. Immunophenotypes for neoplastic cells were distinguishable from normal cells when the leukaemic cell count was at least 5 × 109 cells/l in peripheral blood, or 20% of cells obtained from bone marrow aspirates. This technique may be a useful adjunct to flow cytometry and other methods when an extensive phenotype of the leukaemia cell is desired for clinical trials, research and prognostic factor analysis. |
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ISSN: | 0007-1048 1365-2141 |
DOI: | 10.1111/j.1365-2141.2006.06266.x |