Autor: |
Stasi, R., Taylor, C. G., Venditti, A., Del Poeta, G., Aronica, G., Bastianelli, C., Simone, M. D., Buccisano, F., Cox, M. C., Bruno, A., Piccioni, D., Abruzzese, E., Sargent, J. M., Tribalto, M., Amadori, S. |
Zdroj: |
Annals of Hematology; 19950701, Vol. 71 Issue: 1 p13-27, 15p |
Abstrakt: |
Diagnostic accuracy in acute leukemia (AL) can be improved if traditional morphology and cytochemistry are supplemented with immunophenotypic and genotypic analyses. This multiparameter approach is of crucial importance for the management of patients, as it enables the identification of leukemic syndromes with distinct biological features and response to treatment. Immunophenotyping using monoclonal antibodies has been universally accepted as a useful adjunct to morphological criteria. This technique is particularly valuable in diagnosing and subclassifying acute lymphoblastic leukemia and is also essential in certain types of acute myeloid leukemia (AML), such as AML with minimal differentiation or acute megakaryoblastic leukemia. Cytogenetic findings can be quite helpful in establishing the correct diagnosis and can add information of prognostic significance. A number of specific chromosomal abnormalities have been recognized that are very closely, and sometimes uniquely, associated with morphologically and clinically distinct subsets of leukemia. An even more basic understanding of normal and malignant hematopoietic cells has begun to evolve as molecular biology begins to unravel gene misprogramming by Southern and Northern blot analysis, the polymerase chain reaction, and fluorescence in situ hybridization. With the extensive use of these techniques it has become apparent that a proportion of leukemias exhibit the biologically relevant molecular defect in the absence of a karyotypic equivalent. On the other hand, apparently uniform chromosomal abnormalities such as the t(1;19) (q23;p13), t(9;22) (q33;q11), t(8;14) (q24;q32), or t(15;17) (q21;q21) may differ at the molecular level. Data collected from these modern technologies have introduced a greater complexity, which needs to be taken into consideration to improve both the diagnostic precision and the reproducibility of current classifications. |
Databáze: |
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