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Flow cytometric analysis of acute leukemias. Diagnostic utility and critical analysis of data.

AbstractCONTEXT:
Acute leukemia displays characteristic patterns of surface antigen expression (CD antigens), which facilitate their identification and proper classification and hence play an important role in instituting proper treatment plans. In addition to enzyme cytochemical analysis, multiparameter flow cytometric analysis has become commonplace in most laboratories for that purpose. The essential role and caveats of flow cytometry in that regard, however, have received little scrutiny.
OBJECTIVE:
To evaluate the expression of commonly used immunomarkers and patterns in various acute leukemias to help define the best use and role of multiparameter flow cytometry in the diagnosis and proper classification of acute leukemias.
DESIGN:
We have retrospectively analyzed the immunophenotypic data from 508 de novo adult and pediatric acute leukemia patients, as studied using multiparameter flow cytometry in addition to routine morphologic and enzyme cytochemical analysis. Cytogenetic and/or molecular data were correlated in all 41 cases of acute promyelocytic leukemia (APL) and in 203 other cases of acute leukemia where those data were available. We have also determined the positive and negative predictive values of a combined CD34 and HLA-DR expression pattern for the differentiation of APL from other myeloid leukemias.
RESULTS:
In acute myeloid leukemia (AML) other than APL, expression of CD34 was seen in 62% and expression of HLA-DR in 86% of all cases. Twenty-six (10%) of 259 cases of non-APL AML were negative for both CD34 and HLA-DR as opposed to 33 (80%) of 41 cases of APL. None of the cases of APL were positive for both CD34 and HLA-DR in contrast to 149 (58%) of 259 cases of non-APL AML. Fifty-three cases were found to be examples of minimally differentiated AML (AML M0) based on the lack of expression of cytoplasmic CD3 and cytoplasmic CD79a and expression of one or more myelomonocytic-associated antigens and/or myeloperoxidase. Expression of CD20 was seen in 40 (24%) of 168 cases of precursor B-cell acute lymphoblastic leukemia (pB-ALL) and 52 (29%) lacked CD34 expression. Five of 180 cases of pB-ALL and 2 cases of precursor T-cell ALL (pT-ALL) were negative for terminal deoxynucleotidyl transferase (TdT). Aside from cytoplasmic CD3, CD5 and CD7 were the most sensitive antigens present in all 21 cases of pT-ALL. CD33 was more sensitive but less specific than CD13 for myeloid lineage.
CONCLUSION:
Aside from identification of blasts, flow cytometry was found to be especially useful in the correct identification of AML M0, differentiation of APL from AML M1/M2, and correct identification of TdT-negative ALL and unusual variants, such as transitional B-cell ALL and undifferentiated and biphenotypic acute leukemias.
AuthorsZahid Kaleem, Eric Crawford, M Hanif Pathan, Leah Jasper, Michael A Covinsky, Lawrence R Johnson, Glenda White
JournalArchives of pathology & laboratory medicine (Arch Pathol Lab Med) Vol. 127 Issue 1 Pg. 42-8 (Jan 2003) ISSN: 1543-2165 [Electronic] United States
PMID12521365 (Publication Type: Evaluation Study, Journal Article)
Chemical References
  • Antigens, CD34
  • Antigens, Differentiation, B-Lymphocyte
  • Antigens, Differentiation, Myelomonocytic
  • Antigens, Differentiation, T-Lymphocyte
  • HLA-DR Antigens
  • Peroxidase
  • Proto-Oncogene Proteins c-kit
  • DNA Nucleotidylexotransferase
Topics
  • Acute Disease
  • Adult
  • Antigens, CD34 (immunology, metabolism)
  • Antigens, Differentiation, B-Lymphocyte (immunology, metabolism)
  • Antigens, Differentiation, Myelomonocytic (immunology, metabolism)
  • Antigens, Differentiation, T-Lymphocyte (immunology, metabolism)
  • Cytogenetic Analysis
  • DNA Nucleotidylexotransferase (immunology, metabolism)
  • Flow Cytometry
  • HLA-DR Antigens (immunology, metabolism)
  • Humans
  • Immunophenotyping
  • Killer Cells, Natural (metabolism)
  • Leukemia (classification, diagnosis, metabolism)
  • Megakaryocytes (metabolism)
  • Peroxidase (immunology, metabolism)
  • Proto-Oncogene Proteins c-kit (immunology, metabolism)
  • Retrospective Studies

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