Cytogenetics and cell surface marker analysis in chronic myelocytic leukemia. II. Implications for patient management

Chronic myelocytic leukemia (CML) is a model system for the study of many aspects of malignant disease. One aspect that correlates with decreasing therapeutic response is tumor progression. This progression is often accompanied by clonal evolution. In those cases where aggressive therapy does not prevent this evolution, the clinical response to therapy usually proves to be poor and of short duration. Investigators are concentrating their efforts in three primary, but not mutually exclusive, areas with respect to the clinical management of CML. These include: (a) an attempt to distinguish patients at risk for early transformation from those who will have a prolonged chronic phase; (b) the cryopreservation of autologous bone marrow or buffy coat early in chronic phase for subsequent use in the accelerated phase and; (c) endeavors to identify early markers for disease progression allowing intervention before an irreversible blast crisis occurs. This report deals with two types of potential prognostic markers of transformation: chromosomal and cell surface characteristics. The appearance of nonrandom abnormal chromosomal patterns has been correlated with myeloblastic transformation by many investigators. However, there has always been a subset of CML patients who do not undergo clonal evolution. Additionally, the type(s) of transformation in CML may vary depending on the cell lineages involved. Unlike myeloblastic transformants, many of our patients who do not exhibit clonal evolution as a concomitance of disease progression develop a lymphoblastic transformation. Cytofluorometric analysis can distinguish small populations of abnormal cells with lymphoblastic characteristics (HLA DR +). Initial data suggests that patients expressing the HLA DR + in their “normal” peripheral blood cells are at risk of undergoing lymphoblastic transformation. The combined use of clinical, cytogenetic, and cytofluorometric data to predict an impending transformation and to discriminate between myeloblastic and lymphoblastic populations allows clinicians to manage their patients more effectively.