Using Antigen Expression of Leukemic Cells for a Fast Screening of Acute Promyelocytic Leukemia by Flow Cytometry.
Vitória Ceni-SilvaKatia B B PagnanoGislaine DuarteMarina PellegriniBruno DuarteKonradin MetzeIrene Gyongyver H Lorand MetzePublished in: Diagnostics (Basel, Switzerland) (2021)
(1) Background: Acute promyelocytic leukemia is curable, but bleeding complications still provoke a high early mortality. Therefore, a fast diagnosis is needed for timely starting treatment. We developed a diagnostic algorithm using flow cytometric features for discrimination between acute promyelocytic leukemia (APL) and other types of acute myeloid leukemias (AML). (2) Methods: we analyzed newly diagnosed AMLs where immunophenotyping was performed at diagnosis by an 8-color protocol. The mean fluorescence intensity (MFI) of each antigen used was assessed, and those best separating APL from other types of AML were obtained by a discriminant analysis. Phenotypic characteristics of myeloblasts of normal bone marrow were used as controls. (3) Results: 24 cases of APL and 56 cases of other primary AMLs entered the study. Among non-APL AMLs, 4 had fms-related tyrosine kinase 3 gene internal tandem duplications (FLT3-ITD) mutation, 2 had nucleophosmin (NPM1) and 10 had both mutations. SSC (p < 0.0001), HLA-DR (p < 0.0001), CD13 (p = 0.001), CD64 (p = 0.004) and CD33 (p = 0.002) were differentially expressed, but this was not the case for CD34 (50% of non-APLs had a low expression). In the discriminant analysis, the best differentiation was achieved with SSC and HLA-DR discriminating 91.25% of the patients. (4) Conclusion: MFC could differentiate APL from non-APL AML in the majority of the cases.
Keyphrases
- acute myeloid leukemia
- tyrosine kinase
- liver failure
- bone marrow
- newly diagnosed
- flow cytometry
- respiratory failure
- allogeneic hematopoietic stem cell transplantation
- drug induced
- aortic dissection
- poor prognosis
- epidermal growth factor receptor
- end stage renal disease
- mesenchymal stem cells
- randomized controlled trial
- chronic kidney disease
- hepatitis b virus
- ejection fraction
- machine learning
- coronary artery disease
- intensive care unit
- high intensity
- single molecule
- long non coding rna
- dendritic cells
- cell death
- cardiovascular events
- deep learning
- patient reported
- peritoneal dialysis
- acute respiratory distress syndrome
- replacement therapy
- genome wide identification