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Updated: Jan 28, 2026

Flow Cytometry to Estimate Leukemia Stem Cells in Primary Acute Myeloid Leukemia and in Patient-derived-xenografts, at Diagnosis and Follow Up
Published on: March 26, 2018
Spectrum and Immunophenotypic Profile of Acute Leukemia: A Tertiary Center Flow Cytometry Experience
Nishit Gupta1, Ravikiran Pawar1, Sambhunath Banerjee1
1Department of Laboratory Hematology, Tata Medical Center, Kolkata.
Background:
For diagnosis, sub-categorization and follow up of Acute Leukemia (AL), phenotypic analysis using flow cytometry is mandatory.
Material And Methods:
We retrospectively analyzed immunophenotypic data along with cytogenetics/molecular genetics data (wherever available) from 631 consecutive cases of AL diagnosed at our flow cytometry laboratory from January 2014 to August 2017.
Results:
Of the total 631 cases, 52.9% (n=334) were acute lymphoblastic leukemia (ALL), 43.9% (n=277) acute myeloid leukemia (AML), 2.2% (n=14) mixed phenotypic acute leukemia (MPAL), 0.5% (n=3) acute undifferentiated leukemia (AUL) and 0.5% (n=3) chronic myeloid leukemia in blast crisis (CML-BC). ALL cases comprised of 81.7% (n=273/334) B-cell ALLs (95.2%, n=260/273 common B-ALLs and 4.8%, n=13/273 Pro B-ALLs). CD13 was the commonest cross lineage antigen, expressed in B-ALL (25.6%, n=70/273), followed by CD33 (17.9%, n=49) and combined CD13/CD33 (11.3%, n=31/273) expression. T-ALLs constituted 18.3% (n=61/334) of total ALLs and included 27.9% (n=17/61) cortical T- ALLs. CD13 was commonest (32.7%, n=20/61) aberrantly expressed antigen in T-ALLs, followed by CD117 (19.1%, n=9/47). AML cases included 32.1% (n=89/277) AML with recurrent genetic abnormalities, 9.0% (n=25/277) with FLT3/NPM1c mutation and 58.9% (n=163/277) AML NOS including 14.7% (n=24/163) AML M4/M5, 1.8% (n=3/163) AML M6 and 3.7% (n=6/163) AML M7. In AMLs, CD19 aberrancy was the most common (20.2%, n=56/277) followed by CD56 (15.8%, n=42/265).
Conclusions:
In this study, we document the spectrum, correlate the immunophenotype with genetic data of all leukemias, especially concerning T-ALL where the data from India is scarce.
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