Spectrum and Immunophenotypic Profile of Acute Leukemia: A Tertiary Center Flow Cytometry Experience.

AML AUL B-ALL FLT3/NPM1c MPAL T-ALL

Journal

Mediterranean journal of hematology and infectious diseases
ISSN: 2035-3006
Titre abrégé: Mediterr J Hematol Infect Dis
Pays: Italy
ID NLM: 101530512

Informations de publication

Date de publication:
2019
Historique:
received: 17 09 2018
accepted: 19 01 2019
entrez: 13 3 2019
pubmed: 13 3 2019
medline: 13 3 2019
Statut: epublish

Résumé

For diagnosis, sub-categorization and follow up of Acute Leukemia (AL), phenotypic analysis using flow cytometry is mandatory. 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. 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). 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.

Sections du résumé

BACKGROUND BACKGROUND
For diagnosis, sub-categorization and follow up of Acute Leukemia (AL), phenotypic analysis using flow cytometry is mandatory.
MATERIAL AND METHODS 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 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 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.

Identifiants

pubmed: 30858955
doi: 10.4084/MJHID.2019.017
pii: mjhid-11-1-e2019017
pmc: PMC6402547
doi:

Types de publication

Journal Article

Langues

eng

Pagination

e2019017

Déclaration de conflit d'intérêts

Competing interests: The authors have declared that no competing interests exist.

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Auteurs

Nishit Gupta (N)

Department of Laboratory Hematology, Tata Medical Center, Kolkata.

Ravikiran Pawar (R)

Department of Laboratory Hematology, Tata Medical Center, Kolkata.

Sambhunath Banerjee (S)

Department of Laboratory Hematology, Tata Medical Center, Kolkata.

Subhajit Brahma (S)

Department of Laboratory Hematology, Tata Medical Center, Kolkata.

Asish Rath (A)

Department of Laboratory Hematology, Tata Medical Center, Kolkata.

Sundar Shewale (S)

Department of Laboratory Hematology, Tata Medical Center, Kolkata.

Mayur Parihar (M)

Department of Laboratory Hematology and Cytogenetics, Tata Medical Center, Kolkata.

Manish Singh (M)

Department of Laboratory Hematology and Cytogenetics, Tata Medical Center, Kolkata.

S R Arun (SR)

Department of Laboratory Hematology and Cytogenetics, Tata Medical Center, Kolkata.

Shekhar Krishnan (S)

Department of Pediatric Oncology, Tata Medical Center, Kolkata.

Arpita Bhatacharyya (A)

Department of Pediatric Oncology, Tata Medical Center, Kolkata.

Anirban Das (A)

Department of Pediatric Oncology, Tata Medical Center, Kolkata.

Jeevan Kumar (J)

Department of Clinical Hematology, Tata Medical Center, Kolkata.

Saurabh Bhave (S)

Department of Clinical Hematology, Tata Medical Center, Kolkata.

Vivek Radhakrishnan (V)

Department of Clinical Hematology, Tata Medical Center, Kolkata.

Reena Nair (R)

Department of Clinical Hematology, Tata Medical Center, Kolkata.

Mammen Chandy (M)

Department of Clinical Hematology, Tata Medical Center, Kolkata.

Neeraj Arora (N)

Department of Laboratory Hematology and Molecular Genetics, Tata Medical Center, Kolkata.

Deepak Mishra (D)

Department of Laboratory Hematology and Molecular Genetics, Tata Medical Center, Kolkata.

Classifications MeSH