Database-Guided Analysis for Immunophenotypic Diagnosis and Follow-Up of Acute Myeloid Leukemia With Recurrent Genetic Abnormalities

Abstract

Acute myeloid leukemias (AMLs) are hematologic malignancies with varied molecular and immunophenotypic profiles, making them difficult to diagnose and classify. High-dimensional analysis algorithms might increase the utility of multicolor flow cytometry for AML diagnosis and follow-up. The objective of the present study was to assess whether a Compass database-guided analysis can be used to achieve rapid and accurate diagnoses. We conducted this study to determine whether this method could be employed to pilote the genetic and molecular tests and to objectively identify different-from-normal (DfN) patterns to improve measurable residual disease follow-up in AML. Three Compass databases were built using Infinicyt 2.0 software, including normal myeloid-committed hematopoietic precursors (n = 20) and AML blasts harboring the most frequent recurrent genetic abnormalities (n = 50). The diagnostic accuracy of the Compass database-guided analysis was evaluated in a prospective validation study (125 suspected AML patients). This method excluded AML associated with the following genetic abnormalities: t(8;21), t(15;17), inv(16), and KMT2A translocation, with 92% sensitivity [95% confidence interval (CI): 78.6%–98.3%] and a 98.5% negative predictive value (95% CI: 90.6%–99.8%). Our data showed that the Compass database-guided analysis could identify phenotypic differences between AML groups, representing a useful tool for the identification of DfN patterns.

Identification of Leukemia-Associated Immunophenotypes by Databaseguided Flow Cytometry Provides a Highly Sensitive and Reproducible Strategy for the Study of Measurable Residual Disease in Acute Myeloblastic Leukemia

“…Our strategy extends further by allowing the identification of LAIPs even if they are expressed only in a small part of the leukemic population, which are otherwise impossible to detect by conventional methods. Thus, our findings confirm previous observations evidencing that conventional strategies could be significantly improved [ 4 , 20 , 21 , 22 ]. One of the greatest challenges for MFC-MRD assessment is the presence of cell populations expressing the identified LAIPs in healthy or regenerating bone marrow samples [ 8 , 23 ].…”

Identification of leukemia-associated immunophenotypes by database-guided flow cytometry provides a highly sensitive and reproducible strategy for the study of measurable residual disease in acute myeloblastic leukemia

“…Our strategy goes further allowing the identification of LAIPs even if they are expressed only in a small part of the leukemic population, which are otherwise impossible to detect by conventional methods. Thus, our findings confirm previous observations evidencing that conventional strategies could be significantly improved [4, 20-22]…”

“…Our strategy goes further allowing the identification of LAIPs even if they are expressed only in a small part of the leukemic population, which are otherwise impossible to detect by conventional methods. Thus, our findings confirm previous observations evidencing that conventional strategies could be significantly improved [4,[20][21][22] One of the greatest challenges for MFC-MRD assessment is the presence of cell populations expressing the identified LAIPs in healthy or regenerating bone marrow samples [8,23]. Our results confirm these observations even using individual monitoring profiles and database guided analysis for the exclusion of phenotypically normal cells.…”

Combined flow cytometry natural killer immunophenotyping and KIR/HLA-C genotyping reveal remarkable differences in acute myeloid leukemia patients, but suggest an overall impairment of the natural killer response

“…One sample had to be excluded from the analysis due to clotting issues. The sample preparation procedures and the staining strategy were previously described in detail ( 38 , 39 ). The monoclonal antibodies we have used are summarized in Supplementary Table S1 .…”