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Flow cytometric characterisation of acute leukaemia in adolescent and adult Ethiopians
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Background: Flow cytometric characterisation of acute leukaemia is a key diagnostic approach for clinical management of patients, but is minimally practised in resource-constrained settings like Ethiopia.
Objective: This study aimed to determine the immunophenotypes of acute leukaemia by flow cytometry at Tikur Anbessa Specialised Hospital, Addis Ababa, Ethiopia.
Methods: A cross-sectional study was conducted on adolescent and adult inpatients consecutively admitted from April 2019 to June 2021. Peripheral blood samples were stained for surface and cytoplasmic markers, and analysed by four-colour flow cytometry.
Results: Of 140 cases aged 13 years to 76 years, 74 (53%) were men and 66 (47%) were women, 68 (49%) had acute lymphocytic leukaemia (ALL), 65 (46 %) had acute myelogenous leukaemia (AML), and 7 (5.0%) had acute leukaemia non-otherwise specified. Acute lymphocytic leukaemia was more common among adolescent and male cases; AML was more common among adult and female cases. Among ALL subtypes, B-cell acute lymphocytic leukaemia cases (73.5%) were more common than T-cell acute lymphocytic leukaemia (26.5%). A subset of acute leukaemia, CD19+/CD56+ AML was identified in 3 cases (6% of AML). Of the B-cell ALL cases, 21 (42%) were CD34+/CD10+/CD66c+, 10% were CD34+/CD10+/CD66c–, 32% were CD34-/CD10+, and 6% were CD34+/CD10–. An unexpectedly high number of T-cell ALL cases that lacked surface CD3 were observed to have significantly higher levels of aberrantly expressed myeloid markers.
Conclusion: We observed multiple phenotypes identifying subtypes of acute leukaemia cases, extending our previous studies in Ethiopia.
What this study adds: This study extends previous studies by describing phenotypically defined subsets of ALL and AML which, in addition to diagnosis, may have useful prognostic value for clinicians.
Keywords: flow cytometry; acute leukaemia; Ethiopia; phenotype; cell surface biomarker; cytoplasmic biomarker.
Title: Flow cytometric characterisation of acute leukaemia in adolescent and adult Ethiopians
Description:
Background: Flow cytometric characterisation of acute leukaemia is a key diagnostic approach for clinical management of patients, but is minimally practised in resource-constrained settings like Ethiopia.
Objective: This study aimed to determine the immunophenotypes of acute leukaemia by flow cytometry at Tikur Anbessa Specialised Hospital, Addis Ababa, Ethiopia.
Methods: A cross-sectional study was conducted on adolescent and adult inpatients consecutively admitted from April 2019 to June 2021.
Peripheral blood samples were stained for surface and cytoplasmic markers, and analysed by four-colour flow cytometry.
Results: Of 140 cases aged 13 years to 76 years, 74 (53%) were men and 66 (47%) were women, 68 (49%) had acute lymphocytic leukaemia (ALL), 65 (46 %) had acute myelogenous leukaemia (AML), and 7 (5.
0%) had acute leukaemia non-otherwise specified.
Acute lymphocytic leukaemia was more common among adolescent and male cases; AML was more common among adult and female cases.
Among ALL subtypes, B-cell acute lymphocytic leukaemia cases (73.
5%) were more common than T-cell acute lymphocytic leukaemia (26.
5%).
A subset of acute leukaemia, CD19+/CD56+ AML was identified in 3 cases (6% of AML).
Of the B-cell ALL cases, 21 (42%) were CD34+/CD10+/CD66c+, 10% were CD34+/CD10+/CD66c–, 32% were CD34-/CD10+, and 6% were CD34+/CD10–.
An unexpectedly high number of T-cell ALL cases that lacked surface CD3 were observed to have significantly higher levels of aberrantly expressed myeloid markers.
Conclusion: We observed multiple phenotypes identifying subtypes of acute leukaemia cases, extending our previous studies in Ethiopia.
What this study adds: This study extends previous studies by describing phenotypically defined subsets of ALL and AML which, in addition to diagnosis, may have useful prognostic value for clinicians.
Keywords: flow cytometry; acute leukaemia; Ethiopia; phenotype; cell surface biomarker; cytoplasmic biomarker.
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