Immunophenotypic characterization of acute leukemias in Bahia, Brazil

Santos, Mariane Melo dos; Santos, Allan Souza dos; Santos, Herbert Henrique de Melo; Santos, Lorene da Silva; Nascimento, Roberto José Meyer; Torres, Alex José Leite

doi:10.31744/einstein_journal/2023AO0117

ABSTRACT

Objective

To characterize the immunophenotypic profile of acute leukemias in the population of the state of Bahia, Brazil.

Methods

This is a descriptive, retrospective study. From 2014 to 2018, 796 new cases of acute leukemia were evaluated. The data were obtained from analysis of reports and records of tests performed by flow cytometry immunophenotyping. All individuals of all age groups diagnosed as acute lymphoblastic leukemia or acute myeloid leukemia were included in the study. Demographic variables and expression of leukemia antigens were evaluated.

Results

Most cases were diagnosed as acute myeloid leukemia and 42.7% as acute lymphoblastic leukemia. Significant differences were found in expression of markers in acute leukemias when age groups were compared, as well as in demographic characteristics. B-cell acute lymphoblastic leukemia was more prevalent than cases of T-cell origin. Assessing the aberrant markers in acute myeloid leukemias, the non-acute promyelocytic leukemia group presented expression of CD7 and CD56 as the most frequent ones. In B-cell acute lymphoblastic leukemia, the most frequent aberrant markers were CD66c, CD13 and CD33.

Conclusion

Significant differences were found as to several antigens when comparing adults and children, and these findings may contribute to future studies correlating the phenotypic profile to genetic characteristics and therapeutic response, including specific antigen therapies, which may be better targeted.

Leukemia; Immunophenotyping; Acute myeloid leukemia; Precursor B-cell lymphoblastic leukemia-lymphoma; Flow cytometry; Leukemia, myeloid, acute

INTRODUCTION

Acute leukemia can be classified into two main groups: acute myeloid leukemia (AML) or acute lymphoblastic leukemia (ALL). The latter is the most common malignant disease in childhood, but it is rare in older individuals, accounting for approximately 15% of leukemias in adults. The incidence of leukemia in Brazil is 5.15 per 100,000 inhabitants.(¹1. Brasil. Ministério da Saúde. Instituto Nacional de Câncer (INCA). Estimativa 2020. Rio de Janeiro: INCA; s.d. [citado 2022 Mar 29]. Disponível em: https://www.inca.gov.br/estimativa/taxas-ajustadas/leucemias
https://www.inca.gov.br/estimativa/taxas... ) Acute leukemia progresses rapidly and is usually fatal, but treatments have improved significantly in recent years, increasing overall survival and in some cases leading to a cure.(²2. Khwaja A, Bjorkholm M, Gale RE, Levine RL, Jordan CT, Ehninger G, et al. Acute myeloid leukaemia. Nat Rev Dis Primers. 2016;2:16010. Review.

3. Mwirigi A, Dillon R, Raj K. Acute leukaemia. Medicine. 2017;45(5):280-6.-⁴4. Shah A, Andersson TM, Rachet B, Björkholm M, Lambert PC. Survival and cure of acute myeloid leukaemia in England, 1971-2006: a population-based study. Br J Haematol. 2013;162(4):509-16.)

Acute promyelocytic leukemia (APL), or AML with t(15;17) promyelocytic leukemia (PML) retinoic acid receptor α (RARA) is characterized by the predominant presence of abnormal promyelocytes. This subtype often presents disseminated intravascular coagulation and increased fibrinolysis, which results in high rates of early mortality; therefore, to make a quick and accurate diagnosis is essential for maintenance of patient’s life. If diagnosed quickly, APL has a favorable prognosis with good responses to treatment.(⁵5. Swerdlow SH, Campo E, Harris NL, Jaffe ES, Pileri SA, Stein H, et al, editors. WHO classification of tumours of haematopoietic and lymphoid tissues: WHO classification of tumours, revised 4th edition, volume 2. Geneva: WHO; 2017.

6. Thuler LC, Pombo-de-Oliveira MS. Acute promyelocytic leukaemia is highly frequent among acute myeloid leukaemias in Brazil: a hospital-based cancer registry study from 2001 to 2012. Ann Hematol. 2017;96(3):355-62.-⁷7. Rabade N, Raval G, Chaudhary S, Subramanian PG, Kodgule R, Joshi S, et al. Molecular heterogeneity in acute promyelocytic leukemia - a single center experience from India. Mediterr J Hematol Infect Dis. 2018;10(1):e2018002.)

Leukemias have complex genetic characteristics, hindering the initial analysis of different genes involved in the disease. This makes diagnosis difficult, negatively interfering in the initial stages of therapeutic approaches.(⁸8. Hasan M, Beitz B, Rouilly V, Libri V, Urrutia A, Duffy D, Cassard L, Di Santo JP, Mottez E, Quintana-Murci L, Albert ML, Rogge L; Milieu Intérieur Consortium. Semi-automated and standardized cytometric procedures for multi-panel and multi-parametric whole blood immunophenotyping. Clin Immunol. 2015; 157(2):261-76.,⁹9. Peters JM, Ansari MQ. Multiparameter flow cytometry in the diagnosis and management of acute leukemia. Arch Pathol Lab Med. 2011;135(1):44-54. Review.)

Multiparametric flow cytometry immunophenotyping is a standard and essential procedure for diagnosis of acute leukemias. This method identifies cell characteristics, including size, internal complexity and cell antigens; thus, it is possible to establish diagnosis, define leukemia lineage and subclassification, and, in some cases, predict prognosis.(¹⁰10. Chiaretti S, Zini G, Bassan R. Diagnosis and subclassification of acute lymphoblastic leukemia. Mediterr J Hematol Infect Dis. 2014;6(1):e2014073. Review.,¹¹11. Haddad F, Wraikat A, Khasawneh R, Kamal N. Immunophenotypic diagnosis of acute lymphoblastic leukemia using flow cytometry; experience at King Hussein Medical Center. J Royal Med Serv. 2014;21(2):21-6.)

Leukemia-associated phenotypic markers, commonly known as aberrant markers, are useful to discriminate between normal and reactive precursor cells of leukemic cells. This aberrant labeling occurs when myeloid lineage markers are expressed in lymphoid cells, or when markers of lymphoid origin are expressed in myeloid cells. The occurrence of aberrant markers is reported in acute leukemias with varying frequency and its prognostic value is controversial.(¹²12. Bhushan B, Chauhan PS, Saluja S, Verma S, Mishra AK, Siddiqui S, et al. Aberrant phenotypes in childhood and adult acute leukemia and its association with adverse prognostic factors and clinical outcome. Clin Exp Med. 2010;10(1):33-40.,¹³13. van Dongen JJ, Lhermitte L, Böttcher S, Almeida J, van der Velden VH, Flores-Montero J, Rawstron A, Asnafi V, Lécrevisse Q, Lucio P, Mejstrikova E, Szczepański T, Kalina T, de Tute R, Brüggemann M, Sedek L, Cullen M, Langerak AW, Mendonça A, Macintyre E, Martin-Ayuso M, Hrusak O, Vidriales MB, Orfao A; EuroFlow Consortium (EU-FP6, LSHB-CT-2006-018708). EuroFlow antibody panels for standardized n-dimensional flow cytometric immunophenotyping of normal, reactive and malignant leukocytes. Leukemia. 2012;26(9):1908-75.)

The regulatory mechanisms related to this phenomenon have been studied. Some hypotheses were raised emphasizing the possible lineage indecisiveness or poor genetic programming, but the biological function of this aberrant expression has not been fully understood yet.(¹⁴14. Hrusák O, Porwit-MacDonald A. Antigen expression patterns reflecting genotype of acute leukemias. Leukemia. 2002;16(7):1233-58. Review.,¹⁵15. Kalina T, Vaskova M, Mejstrikova E, Madzo J, Trka J, Stary J, et al. Myeloid antigens in childhood lymphoblastic leukemia: clinical data point to regulation of CD66c distinct from other myeloid antigens. BMC Cancer. 2005;5:38.) From a clinical and laboratory point of view, it is crucial to establish associations with chromosomal alterations and prognostic factors, employing more specific molecular tests. In addition, aberrant immunophenotypes are known to be relevant tools to detect minimal residual disease.(¹⁴14. Hrusák O, Porwit-MacDonald A. Antigen expression patterns reflecting genotype of acute leukemias. Leukemia. 2002;16(7):1233-58. Review.,¹⁶16. Emerenciano M, Bossa Y, Zanrosso CW, Alencar DM, Campos MM, Dobbin J, et al. Freqüência de imunofenótipos aberrantes em leucemias agudas. Rev Bras Cancerol. 2004;50(3):183-9.,¹⁷17. Theunissen P, Mejstrikova E, Sedek L, van der Sluijs-Gelling AJ, Gaipa G, Bartels M, Sobral da Costa E, Kotrová M, Novakova M, Sonneveld E, Buracchi C, Bonaccorso P, Oliveira E, Te Marvelde JG, Szczepanski T, Lhermitte L, Hrusak O, Lecrevisse Q, Grigore GE, Froňková E, Trka J, Brüggemann M, Orfao A, van Dongen JJ, van der Velden VH; EuroFlow Consortium. Standardized flow cytometry for highly sensitive MRD measurements in B-cell acute lymphoblastic leukemia. Blood. 2017;129(3):347-57.)

Demographic characteristics, such as age, sex and race, have been used to evaluate the risk of leukemia. Individuals aged 1 to 10 years have a favorable prognosis, while the age groups <1 year and >10 years have an adverse prognosis. The white race presents a favorable factor in relation to the black race. Female individuals have a more favorable prognosis.(¹⁸18. Malard F, Mohty M. Acute lymphoblastic leukaemia. Lancet. 2020;395(10230): 1146-62. Review.)

The literature currently lacks data on immunophenotypic characterization in Brazil. Characterizing the immunophenotypic profile of leukemias evaluated in a diagnostic center in the state of Bahia will enable collecting data that may contribute to better targeting therapies in the future and, consequently, to improve the clinical status and survival of these patients.

OBJECTIVE

To characterize the immunophenotypic profile of acute leukemias in the population of the state of Bahia, Brazil.

METHODS

This is a descriptive, retrospective study with data obtained from January 2014 to December 2018. The variables of sex, age and immunophenotype were obtained from the analysis of reports and records of tests performed using flow cytometry immunophenotyping. The study was approved by the Research Ethics Committee of Instituto de Ciências da Saúde da Universidade Federal da Bahia, under CAAE: 91088418.0.0000.5662; # 2.917.200.

Study population

All individuals of all age groups diagnosed as ALL or AML and seen at the Laboratory of Immunology and Molecular Biology of Instituto de Ciências da Saúde da Universidade Federal da Bahia, in the period between January 2014 to December 2018 were included in the study. Recurrence and reassessment cases were excluded from the study. The Laboratory delivers services to patients by means of the Brazilian Public Health System (SUS - Sistema Único de Saúde). Individuals from all microregions of Bahia were analyzed, except those from the microregion of Porto Seguro, because no patient resided in that region.

Analyzed variables

The panel of antibodies used to define diagnosis of leukemia was comprehensive and also specific for each type of leukemia, as follows:

ALL B: CD19 PECY7, CD20 V450, CD10 APC, CD34 PERCPCY 5.5, CD13 PE, CD33 APC, CD38 APCH7, CD66c PE, CD45 V500, CD79a PE and CD81 FITC.

ALL T: CD3m APCH7, CD3cit V450, CD4 V450, CD8 FITC, CD7 APC, CD2 V450, CD5 PERCPCY 5.5, CD1a APC, CD13 PE, CD33 APC, CD34 PERCPCY 5.5, CD45 V500 and CD117 PECY7.

AML: CD2 FITC, CD7 APC, CD13 PE, CD15 FITC, CD19 PECY7, CD33 APC, CD34 PERCPCY 5.5, CD56 PE, CD64 PE, CD117 PECY7, HLA-DR V450 and MPO FITC.

The analyses were performed on peripheral blood and bone marrow samples. Age and sex variables were also evaluated.

Statistical analysis

Data were compiled in Microsoft Excel 2016 (Windows 10) spreadsheets and transferred to SPSS Statistics version 25.0 to obtain the descriptive epidemiology of frequencies, and the medians and means were calculated. Furthermore, the data were submitted to Pearson’s χ² statistical test to assess categorical variables.

RESULTS

From 2014 to 2018, a total of 796 new cases of acute leukemia in the state of Bahia were evaluated; in that, 456 (57.3%) were diagnosed as AML and 340 (42.7%) as ALL. A total of 80 cases were identified as APL, accounting for 17.6% of AML cases and 10.05% of all cases. The other AML subtypes were grouped and named non-APL AML, accounting for 47.24% (n=376) of total cases. Frequency of 42.7% (n=340) was observed when evaluating the ALL, and 277 cases (81.5%) were of B-lymphocyte origin and 63 (18.5%) of T-lymphocyte origin.

The pediatric population (<16 years) comprised 236 cases (78.3% of lymphoid leukemias). In adolescent and adult population (n=560) the frequency of ALL was 27.6%. The peak incidence of B-cell ALL occurred in children aged between 2 and 5 years. In T-cell ALL, the peak incidence was observed in patients aged between 12 and 18 years, and, in AML, it was in those aged above 60 years. The median age of AML was 43 years, and most patients were female 53.2% (p=0.236). The characteristics of the study population, including age, sex, white blood cell count, mean number of blasts and type of sample analyzed, are summarized in table 1.

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Table 1
Characteristics of the study population

Markers were evaluated and separated into positive, partially positive and negative expression, grouped by type of leukemia. The cutoff point for marker expression to be considered positive or partially positive was 20% and 10%, respectively. Table 2 summarizes the pattern of expression of these antigens in number of cases and frequency.

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Table 2
Pattern of antigen expression in leukemia groups

Chronic myeloid leukemia (CML) can progress to acute leukemia and is called CML blast crisis.(⁵5. Swerdlow SH, Campo E, Harris NL, Jaffe ES, Pileri SA, Stein H, et al, editors. WHO classification of tumours of haematopoietic and lymphoid tissues: WHO classification of tumours, revised 4th edition, volume 2. Geneva: WHO; 2017.) In the study, 13 cases of acute leukemia secondary to chronic myeloid leukemia were evaluated. The previous diagnosis of CML was reported in the medical record. Of these, 7 (53.8%) evolved to AML and 6 (46.2%) to B-cell ALL (p=0.782), and 9 (69.2%) were male and 4 (30.8%) female (p=0.267). The median age was 56 years.

Acute myeloid leukemia

Evaluating the aberrant markers in non-APL AML, CD7 was more frequent (37.4%), followed by CD56 (18.4%). CD19 was expressed in 1.9% of cases and CD2 in 5.9%. Regarding APL, CD7 was found in only 2.5% of cases, whereas CD56 was in 15.6% of cases. CD2 showed a higher frequency, with expression in 34.2% of cases; no expression of CD19 was observed (Table 3).

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Table 3
Rate of positivity of marker expression in non-APL acute myeloid leukemia and acute promyelocytic leukemia

Figure 1 shows the main phenotypic differences between non-APL AML and APL. Based on this analysis, it was possible to determine CD34, HLA-DR, CD13, MPO, CD15, CD64, CD2 and CD7 as the main markers differentiating these two AML groups. The positivity rate was established by adding the cases that had positive and partially positive expression.

Figure 1
Difference in marker expression of antigens in acute myeloid leukemia

Table 3 shows the positivity rate in the non-APL and APL AML groups, separated by sex and age group. In non-APL AML, males showed a significant difference in CD2 expression (p<0.05). Adults had a higher positivity rate in expression of CD13 and MPO (p<0.05). In APL, CD117 was significantly more frequent in adults. When the group of infants (≤2 years) was evaluated separately, in addition to the differences in CD13 and MPO, a significant difference was found in the expression of CD7 and HLA-DR (Figure 2).

Figure 2
Percentage of cases of non-APL acute myeloid leukemia with negative expression of antigens by age group

Acute lymphoblastic leukemia

A total of 340 ALL cases were evaluated; in that, 277 (81.5%) were B-cell ALL and 63 (18.5%) T-cell ALL. As to sex, 50.2% and 77.8% of cases were male in B-cell ALL and T-cell ALL, respectively (p<0.01).

The most frequent aberrant marker in B-cell ALL was CD66c, with a positivity rate of 62.7%. CD13 and CD33 accounted for 33% and 26%, respectively. Table 4 shows the positivity rate in B-cell ALL and T-cell ALL groups, separated by sex and age groups. In B-cell ALL, the frequency of cases with positive expression of CD66c and CD34 was significantly different between adults and children. In T-cell ALL, this difference was seen in the expression of CD2, CD117 and CD5 (Table 4). When evaluating the antigenic expression in the white blood cell count groups, there is a significant difference in the expression of CD2 and CD5 (Figure 3).

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Table 4
Rate of positivity of expression of markers in B-cell ALL and T-cell ALL

Figure 3
Percentage of T-cell ALL cases with negative expression of antigens by white blood cell count range upon diagnosis

Comparing the age groups in B-cell ALL, significant differences were observed in expression of CD10, CD13, CD33, CD66c and CD34 (Figure 4).

Figure 4
Percentage of B-cell ALL cases with negative expression of antigens by age group

DISCUSSION

The present study is the first research carried out in Bahia to characterize the immunophenotypic profile of acute leukemias, as of our knowledge. The data comprise most cases of leukemia diagnosed in the state of Bahia, since they were collected at a diagnostic reference center in the state.

Most cases were AML (57.3%), and less than what was reported by Salem et al.(¹⁹19. Salem DA, Abd El-Aziz SM. Flowcytometric immunophenotypic profile of acute leukemia: mansoura experience. Indian J Hematol Blood Transfus. 2012;28(2):89-96.)(68.9%), who assessed a greater number of adult patients. Acute promyelocytic leukemia accounted to 17.6% of AML cases, a frequency higher than that reported by Ghosh et al.,(²⁰20. Ghosh S, Shinde SC, Kumaran GS, Sapre RS, Dhond SR, Badrinath Y, et al. Haematologic and immunophenotypic profile of acute myeloid leukemia: an experience of Tata Memorial Hospital. Indian J Cancer. 2003;40(2):71-6.) who found 6%, and lower than that described by Salem et al(¹⁹19. Salem DA, Abd El-Aziz SM. Flowcytometric immunophenotypic profile of acute leukemia: mansoura experience. Indian J Hematol Blood Transfus. 2012;28(2):89-96.) (23%). According to the World Health Organization (WHO),(⁵5. Swerdlow SH, Campo E, Harris NL, Jaffe ES, Pileri SA, Stein H, et al, editors. WHO classification of tumours of haematopoietic and lymphoid tissues: WHO classification of tumours, revised 4th edition, volume 2. Geneva: WHO; 2017.)the frequency of APL in AML is 4-5%. In our study, morphological and immunophenotypic criteria were used to assess diagnosis of APL.

The median age (43 years) in the AML group was very different from that reported by WHO (63 years). The incidence of AML is known to increase with age, and this difference could be explained by the fact that developed countries have a higher concentration of elderly population.(²¹21. Shallis RM, Wang R, Davidoff A, Ma X, Zeidan AM. Epidemiology of acute myeloid leukemia: recent progress and enduring challenges. Blood Rev. 2019;36:70-87. Review.,²²22. United States of America. U.S. Department of Health and Human Services. National Institutes of Health. National Cancer Institute. Surveillance, Epidemiology, and End Results Program. SEER Cancer Statistics Review (CSR) 1975-2016. Bethesda: NCI; s.d. [cited 2022 Mar 29]. Available from: https://seer.cancer.gov/archive/csr/1975_2016
https://seer.cancer.gov/archive/csr/1975... ) A Brazilian study conducted by Capra et al.(²³23. Capra M, Vilella L, Pereira WV, Coser VM, Fernandes MS, Schilling MA, et al. Estimated number of cases, regional distribution and survival of patients diagnosed with acute myeloid leukemia between 1996 and 2000 in Rio Grande do Sul, Brazil. Leuk Lymphoma. 2007;48(12):2381-6.)found a very similar median age of 42 years. The frequency of AML was higher in females, 53.2% of cases (p=0.236), in contrast to what is reported in the literature.(²⁴24. Rose-Inman H, Kuehl D. Acute leukemia. Hematol Oncol Clin North Am. 2017;31(6):1011-28. Review.

25. Yamamoto JF, Goodman MT. Patterns of leukemia incidence in the United States by subtype and demographic characteristics, 1997-2002. Cancer Causes Control. 2008;19(4):379-90.-²⁶26. Gupta N, Pawar R, Banerjee S, Brahma S, Rath A, Shewale S, et al. Spectrum and immunophenotypic profile of acute leukemia: a tertiary center flow cytometry experience. Mediterr J Hematol Infect Dis. 2019;11(1):e2019017.)

As to expression of aberrant markers in AML, positive expression was more frequent for CD7 (37.4%), followed by CD56 (18.4%). The present study demonstrated a higher frequency of CD7 than other investigations, ranging from 8.8% to 33%.(¹⁶16. Emerenciano M, Bossa Y, Zanrosso CW, Alencar DM, Campos MM, Dobbin J, et al. Freqüência de imunofenótipos aberrantes em leucemias agudas. Rev Bras Cancerol. 2004;50(3):183-9.,²⁷27. Thalhammer-Scherrer R, Mitterbauer G, Simonitsch I, Jaeger U, Lechner K, Schneider B, et al. The immunophenotype of 325 adult acute leukemias: relationship to morphologic and molecular classification and proposal for a minimal screening program highly predictive for lineage discrimination. Am J Clin Pathol. 2002;117(3):380-9.) CD7 expression in myeloblasts has been associated with failure to achieve complete remission and decreased survival.(²⁸28. Venditti A, Del Poeta G, Buccisano F, Tamburini A, Cox-Froncillo MC, Aronica G, et al. Prognostic relevance of the expression of Tdt and CD7 in 335 cases of acute myeloid leukemia. Leukemia. 1998;12(7):1056-63.,²⁹29. Saxena A, Sheridan DP, Card RT, McPeek AM, Mewdell CC, Skinnider LF. Biologic and clinical significance of CD7 expression in acute myeloid leukemia. Am J Hematol. 1998;58(4):278-84.) It is believed that CD7 is expressed in early stages of hematopoietic ontogeny and has been associated with expression of precursor antigens.(²⁸28. Venditti A, Del Poeta G, Buccisano F, Tamburini A, Cox-Froncillo MC, Aronica G, et al. Prognostic relevance of the expression of Tdt and CD7 in 335 cases of acute myeloid leukemia. Leukemia. 1998;12(7):1056-63.,³⁰30. Cruse JM, Lewis RE, Pierce S, Lam J, Tadros Y. Aberrant expression of CD7, CD56, and CD79a antigens in acute myeloid leukemias. Exp Mol Pathol. 2005;79(1):39-41.) Corroborating this statement, we found the expression of markers linked to cellular immaturity, such as HLA-DR in 91.4%, CD117 in 97.8%, and CD34 in 87.6% of CD7 positive AML cases. Myeloperoxidase (MPO) appears in more mature stages and was demonstrated in only 40% of cases.

As regards to CD56, the literature reports a frequency between 11.6% and 27.6%.(²⁶26. Gupta N, Pawar R, Banerjee S, Brahma S, Rath A, Shewale S, et al. Spectrum and immunophenotypic profile of acute leukemia: a tertiary center flow cytometry experience. Mediterr J Hematol Infect Dis. 2019;11(1):e2019017.,²⁷27. Thalhammer-Scherrer R, Mitterbauer G, Simonitsch I, Jaeger U, Lechner K, Schneider B, et al. The immunophenotype of 325 adult acute leukemias: relationship to morphologic and molecular classification and proposal for a minimal screening program highly predictive for lineage discrimination. Am J Clin Pathol. 2002;117(3):380-9.,³¹31. Abdulateef NA, Ismail MM, Aljedani H. Clinical significance of co-expression of aberrant antigens in acute leukemia: a retrospective cohort study in Makah Al Mukaramah, Saudi Arabia. Asian Pac J Cancer Prev. 2014;15(1):221-7.) In the present study, 18.4% of cases expressed CD56. Raspadori et al.(³²32. Raspadori D, Damiani D, Lenoci M, Rondelli D, Testoni N, Nardi G, et al. CD56 antigenic expression in acute myeloid leukemia identifies patients with poor clinical prognosis. Leukemia. 2001;15(8):1161-4.) emphasized this aberrant expression is related to a reduced probability of achieving complete remission and lower survival rates. Therefore, it is important to regularly assess the presence of CD56 in myeloid blasts and its expression must be considered in the therapeutic strategy.(²⁸28. Venditti A, Del Poeta G, Buccisano F, Tamburini A, Cox-Froncillo MC, Aronica G, et al. Prognostic relevance of the expression of Tdt and CD7 in 335 cases of acute myeloid leukemia. Leukemia. 1998;12(7):1056-63.)

Comparing the phenotypes of non-APL AML and APL, in addition to HLA-DR and CD34, we found significant differences in the expression of markers CD13, MPO, CD15, CD64, CD2 and CD7. Thus, the professional in charge of making immunophenotypic diagnosis must ensure greater importance of these markers when reporting APL. According to the WHO, the main markers differentiating APL from other AML are HLA-DR, CD34, the homogeneous and strong expression of CD33, negative or weakly expressed CD15, and the expression of CD64 that is common in APL. CD2 expression in APL has been associated with FLT3-ITD mutation and may contribute to targeting therapies, such as tyrosine kinase inhibitors. CD56 expression was associated with an unfavorable prognosis.(⁵5. Swerdlow SH, Campo E, Harris NL, Jaffe ES, Pileri SA, Stein H, et al, editors. WHO classification of tumours of haematopoietic and lymphoid tissues: WHO classification of tumours, revised 4th edition, volume 2. Geneva: WHO; 2017.)

In acute leukemias secondary to CML, we observed 46% of cases progressed to B-cell ALL. The WHO reports a percentage of 20-30%. Cases of T-cell ALL and Natural Killer (NK) cells have already been reported.(³³33. Warzynski MJ, White C, Golightly MG, Steingart R, Otto RN, Podgurski AE, et al. Natural killer lymphocyte blast crisis of chronic myelogenous leukemia. Am J Hematol. 1989;32(4):279-86.) Studies reporting the frequency of acute leukemia secondary to CML are scarce. A Mexican study reported 35.3% of cases progressing to B-cell ALL.(³⁴34. López-Karpovitch X, Cárdenas R, Piedras J. Immunophenotypic characteristics of the blast crisis in chronic myeloid leukemia. Rev Invest Clin. 1997;49(1):31-6. Review.)

Acute myeloid leukemia has a complex genetic basis involving several genetic alterations.(³⁵35. Papaemmanuil E, Gerstung M, Bullinger L, Gaidzik VI, Paschka P, Roberts ND, et al. Genomic classification and prognosis in acute myeloid leukemia. N Engl J Med. 2016;374(23):2209-21.) This fact may explain the different phenotypic alterations found among adults and children. CD13 and MPO were more expressed in adults in non-APL AML, and CD117 was more expressed in adults in APL. The group of children aged ≤2 years had a high frequency of cases with negative expression for CD13 and CD33. This fact should be considered when choosing immunotherapy with anti-CD33 antibody, which is one of the most used in AML.(³⁶36. Acheampong DO, Adokoh CK, Asante DB, Asiamah EA, Barnie PA, Bonsu DO, et al. Immunotherapy for acute myeloid leukemia (AML): a potent alternative therapy. Biomed Pharmacother. 2018;97:225-32. Review.)

Among the most common subtypes of leukemia, ALL stands out in the pediatric group.(³⁷37. Kaatsch P. Epidemiology of childhood cancer. Cancer Treat Rev. 2010; 36(4):277-85. Review.) In our study, ALL account for 78.3% of acute leukemia in children. According to Siegel et al.,(³⁸38. Siegel RL, Fedewa SA, Miller KD, Goding-Sauer A, Pinheiro PS, Martinez-Tyson D, et al. Cancer statistics for Hispanics/Latinos, 2015. CA Cancer J Clin. 2015;65(6):457-80.) who carried out a study about the Hispanic and Latin population, ALL accounted for 78% of leukemia cases in children. In adults, the frequency of ALL was 27.6%. B-cell ALL accounted for (81.5%) of ALL cases, corroborating data reported by the WHO (80-85%). In T-cell ALL, 77.8% of cases were males, as described in most literature reports.(³⁹39. Hunger SP, Mullighan CG. Acute lymphoblastic leukemia in children. N Engl J Med. 2015;373(16):1541-52. Review.)

Aberrant markers help to differentiate normal or reactive cells from leukemic cells and are important to evaluate minimal residual disease.(¹⁷17. Theunissen P, Mejstrikova E, Sedek L, van der Sluijs-Gelling AJ, Gaipa G, Bartels M, Sobral da Costa E, Kotrová M, Novakova M, Sonneveld E, Buracchi C, Bonaccorso P, Oliveira E, Te Marvelde JG, Szczepanski T, Lhermitte L, Hrusak O, Lecrevisse Q, Grigore GE, Froňková E, Trka J, Brüggemann M, Orfao A, van Dongen JJ, van der Velden VH; EuroFlow Consortium. Standardized flow cytometry for highly sensitive MRD measurements in B-cell acute lymphoblastic leukemia. Blood. 2017;129(3):347-57.,⁴⁰40. van Dongen JJ, Orfao A; EuroFlow Consortium. EuroFlow: resetting leukemia and lymphoma immunophenotyping. Basis for companion diagnostics and personalized medicine. Leukemia. 2012;26(9):1899-907.) Concerning the expression of aberrant markers in B-cell ALL, the present study found a positivity rate more frequent for CD66c (62.7%) followed by CD13 (33.3%) and CD33 (26.1%). CD66c is the most frequent aberrant marker in B-cell ALL;(⁴¹41. Kiyokawa N, Iijima K, Tomita O, Miharu M, Hasegawa D, Kobayashi K, et al. Significance of CD66c expression in childhood acute lymphoblastic leukemia. Leuk Res. 2014;38(1):42-8.,⁴²42. Guillaume N, Penther D, Vaida I, Gruson B, Harrivel V, Claisse JF, et al. CD66c expression in B-cell acute lymphoblastic leukemia: strength and weakness. Int J Lab Hematol. 2011;33(1):92-6.) therefore, it is the most useful marker to study minimal residual disease. However, it is still not widely used and was added to B-cell ALL panels only a few years ago. For this reason, few studies have reported frequency of positive CD66c in B-cell ALL patients. Kalina et al.(¹⁵15. Kalina T, Vaskova M, Mejstrikova E, Madzo J, Trka J, Stary J, et al. Myeloid antigens in childhood lymphoblastic leukemia: clinical data point to regulation of CD66c distinct from other myeloid antigens. BMC Cancer. 2005;5:38.) demonstrated CD66c expression in 43% of B-cell ALL cases, and Ismail et al.,(⁴³43. Ismail MM, Zaghloul A, Abdulateef NA, Morsi HK. Membranous expression of pan CD66, CD66a, CD66b, and CD66c and their clinical impact in acute leukemia: cross sectional longitudinal cohort study in Saudi Arabia. J Leuk (Los Angel). 2017;5(2):1000230.) in 51.8%. When analyzing CD13 and CD33 expression, the study presenting results more similar to ours was a Brazilian study carried out by Alves,(⁴⁴44. Alves GV. Caracterização hematológica e imunofenotípica em pacientes com leucemia linfoblástica aguda [tese]. Natal: Universidade Federal do Rio Grande do Norte; 2012. 233 p.) with a frequency of 33% and 25%, respectively.

The phenotypic pattern of antigen expression reflects the gene expression of leukemic cells. When comparing the expression of aberrant markers in adults and children, we observed a significant difference for CD66c. This fact may be related to the expression of CD66c being associated with B-cell Philadelphia (Ph) + ALL, which is more frequent in adults.(⁴¹41. Kiyokawa N, Iijima K, Tomita O, Miharu M, Hasegawa D, Kobayashi K, et al. Significance of CD66c expression in childhood acute lymphoblastic leukemia. Leuk Res. 2014;38(1):42-8.) CD13 and CD33 were also more often expressed in adults.

CD34 is a transmembrane protein, widely used as a marker of hematopoietic stem cells. Its biological function is involved in inhibition of differentiation, expansion of hematopoietic stem cells, signaling transduction and adhesion.(⁴⁵45. Furness SG, McNagny K. Beyond mere markers: functions for CD34 family of sialomucins in hematopoiesis. Immunol Res. 2006;34(1):13-32. Review.) Studies showed that in pediatric ALL, the expression of CD34 is a good prognostic factor, while in adults it is related to a worse prognosis.(⁴⁶46. Cascavilla N, Musto P, D’Arena G, Ladogana S, Matera R, Carotenuto M. Adult and childhood acute lymphoblastic leukemia: clinico-biological differences based on CD34 antigen expression. Haematologica. 1997;82(1):31-7.

47. Thomas X, Archimbaud E, Charrin C, Magaud JP, Fiere D. CD34 expression is associated with major adverse prognostic factors in adult acute lymphoblastic leukemia. Leukemia. 1995;9(2):249-53.-⁴⁸48. Jiang Z, Wu D, Lin S, Li P. CD34 and CD38 are prognostic biomarkers for acute B lymphoblastic leukemia. Biomark Res. 2016;4:23. Review.) CD34 expression was significantly higher in adults, and what may be associated with prognostic features of the genetic basis of the disease.

CD10 expression was significantly different between the pediatric and adult groups. The group of children had a higher frequency of negative CD10 in B-cell ALL. This difference can be explained by the fact that pro-B ALL is the most frequent leukemia in children aged <1 year, and it is less common in older children and adults.(⁵5. Swerdlow SH, Campo E, Harris NL, Jaffe ES, Pileri SA, Stein H, et al, editors. WHO classification of tumours of haematopoietic and lymphoid tissues: WHO classification of tumours, revised 4th edition, volume 2. Geneva: WHO; 2017.) Pro-B ALL is characterized by negative CD10, and its most frequent molecular alteration is KMT2A t(4;11) rearrangement; this subtype has an unfavorable prognosis.(⁴⁹49. Emerenciano M, Koifman S, Pombo-de-Oliveira MS. Acute leukemia in early childhood. Braz J Med Biol Res. 2007;40(6):749-60. Review.,⁵⁰50. Meyer C, Burmeister T, Gröger D, Tsaur G, Fechina L, Renneville A, et al. The MLL recombinome of acute leukemias in 2017. Leukemia. 2018;32(2):273-84.) The frequency of negative CD10 in B-cell ALL cases was 8.3%, close to 11.36%, as reported by Haddad et al.(¹¹11. Haddad F, Wraikat A, Khasawneh R, Kamal N. Immunophenotypic diagnosis of acute lymphoblastic leukemia using flow cytometry; experience at King Hussein Medical Center. J Royal Med Serv. 2014;21(2):21-6.)

In T-cell ALL, the most frequent aberrant markers were CD10 (44.3%), CD13 (36.5%), CD33 (25.4%) and CD117 (19%). Sayed et al.,(⁵¹51. Sayed DM, Sayed HA, Raslan HN, Ali AM, Zahran A, Al-Hayek R, et al. Outcome and clinical significance of immunophenotypic markers expressed in different treatment protocols of pediatric patients with T-ALL in developing countries. Clin Lymphoma Myeloma Leuk. 2017;17(7):443-9.) in Egypt, found a frequency of 45.9% for CD10, 4.4% for CD13, 10.1% for CD33 and 5.1% for CD117. In India, Garg et al.(⁵²52. Garg N, Kotru M, Kumar D, Pathak R, Sikka M. Correlation of expression of aberrant immunophenotypic markers in T-ALL with its morphology: a pilot study. J Lab Physicians. 2018;10(4):410-3.) reported a frequency of 35.3% for CD10, 38.46% for CD33 and 42.28% for CD117. Comparing the phenotype of the pediatric and adult groups, significant differences were observed for expression of CD2, CD117 and CD5, possibly because the frequency of early T-cell precursor ALL is higher in adults.(⁵³53. Chopra A, Bakhshi S, Pramanik SK, Pandey RM, Singh S, Gajendra S, et al. Immunophenotypic analysis of T-acute lymphoblastic leukemia. A CD5-based ETP-ALL perspective of non-ETP T-ALL. Eur J Haematol. 2014;92(3):211-8.)

Studies showed the relation between an elevated leukocyte count with unfavorable prognosis, especially in B-cell ALL.(⁵⁴54. Larson RA, Dodge RK, Burns CP, Lee EJ, Stone RM, Schulman P, et al. A five-drug remission induction regimen with intensive consolidation for adults with acute lymphoblastic leukemia: cancer and leukemia group B study 8811. Blood. 1995;85(8):2025-37.,⁵⁵55. Rowe JM. Prognostic factors in adult acute lymphoblastic leukaemia. Br J Haematol. 2010;150(4):389-405. Review.) When evaluating expression of antigens in different white blood count groups in T-cell ALL, a significant difference was observed in expression of CD2 and CD5. A study by Chopra et al.(⁵³53. Chopra A, Bakhshi S, Pramanik SK, Pandey RM, Singh S, Gajendra S, et al. Immunophenotypic analysis of T-acute lymphoblastic leukemia. A CD5-based ETP-ALL perspective of non-ETP T-ALL. Eur J Haematol. 2014;92(3):211-8.) demonstrated the white blood count of early T-cell precursor ALL group is much lower than that of other T-cell ALL subtypes; what may explain the differences found in expression of CD2 and CD5 in white blood count groups in the present study.

CONCLUSION

This work contributed to documenting the immunophenotypic profile of 796 new cases of acute leukemia in the state of Bahia. In contrast to the literature, the incidence of acute myeloid leukemia was slightly higher in women. Significant differences were found in several antigens evaluated when comparing the pediatric and adult groups. CD66c and CD7 were the most frequent aberrant markers in B-cell acute lymphoblastic leukemia and acute myeloid leukemia, respectively, and the frequency was higher as compared to the literature. To determine the positivity of these markers in a standardized fashion, it is necessary to evaluate the influence of the population and the criteria for standardization of analytical processes employed by laboratories. Based on these findings, future studies correlating the phenotypic profile with genetic characteristics and therapeutic response, including antigen-specific therapies, may be better targeted.

ACKNOWLEDGEMENTS

This work had structural and financial support from the Laboratory of Immunology and Molecular Biology of Universidade Federal da Bahia (UFBA).

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» https://www.inca.gov.br/estimativa/taxas-ajustadas/leucemias
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⁴¹
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⁴²
Guillaume N, Penther D, Vaida I, Gruson B, Harrivel V, Claisse JF, et al. CD66c expression in B-cell acute lymphoblastic leukemia: strength and weakness. Int J Lab Hematol. 2011;33(1):92-6.
⁴³
Ismail MM, Zaghloul A, Abdulateef NA, Morsi HK. Membranous expression of pan CD66, CD66a, CD66b, and CD66c and their clinical impact in acute leukemia: cross sectional longitudinal cohort study in Saudi Arabia. J Leuk (Los Angel). 2017;5(2):1000230.
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⁴⁵
Furness SG, McNagny K. Beyond mere markers: functions for CD34 family of sialomucins in hematopoiesis. Immunol Res. 2006;34(1):13-32. Review.
⁴⁶
Cascavilla N, Musto P, D’Arena G, Ladogana S, Matera R, Carotenuto M. Adult and childhood acute lymphoblastic leukemia: clinico-biological differences based on CD34 antigen expression. Haematologica. 1997;82(1):31-7.
⁴⁷
Thomas X, Archimbaud E, Charrin C, Magaud JP, Fiere D. CD34 expression is associated with major adverse prognostic factors in adult acute lymphoblastic leukemia. Leukemia. 1995;9(2):249-53.
⁴⁸
Jiang Z, Wu D, Lin S, Li P. CD34 and CD38 are prognostic biomarkers for acute B lymphoblastic leukemia. Biomark Res. 2016;4:23. Review.
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⁵⁰
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⁵¹
Sayed DM, Sayed HA, Raslan HN, Ali AM, Zahran A, Al-Hayek R, et al. Outcome and clinical significance of immunophenotypic markers expressed in different treatment protocols of pediatric patients with T-ALL in developing countries. Clin Lymphoma Myeloma Leuk. 2017;17(7):443-9.
⁵²
Garg N, Kotru M, Kumar D, Pathak R, Sikka M. Correlation of expression of aberrant immunophenotypic markers in T-ALL with its morphology: a pilot study. J Lab Physicians. 2018;10(4):410-3.
⁵³
Chopra A, Bakhshi S, Pramanik SK, Pandey RM, Singh S, Gajendra S, et al. Immunophenotypic analysis of T-acute lymphoblastic leukemia. A CD5-based ETP-ALL perspective of non-ETP T-ALL. Eur J Haematol. 2014;92(3):211-8.
⁵⁴
Larson RA, Dodge RK, Burns CP, Lee EJ, Stone RM, Schulman P, et al. A five-drug remission induction regimen with intensive consolidation for adults with acute lymphoblastic leukemia: cancer and leukemia group B study 8811. Blood. 1995;85(8):2025-37.
⁵⁵
Rowe JM. Prognostic factors in adult acute lymphoblastic leukaemia. Br J Haematol. 2010;150(4):389-405. Review.

Publication Dates

Publication in this collection
06 Jan 2023
Date of issue
2023

History

Received
29 Mar 2022
Accepted
22 Aug 2022

This is an Open Access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

[1] ¹
Brasil. Ministério da Saúde. Instituto Nacional de Câncer (INCA). Estimativa 2020. Rio de Janeiro: INCA; s.d. [citado 2022 Mar 29]. Disponível em: https://www.inca.gov.br/estimativa/taxas-ajustadas/leucemias
» https://www.inca.gov.br/estimativa/taxas-ajustadas/leucemias

[2] ²
Khwaja A, Bjorkholm M, Gale RE, Levine RL, Jordan CT, Ehninger G, et al. Acute myeloid leukaemia. Nat Rev Dis Primers. 2016;2:16010. Review.

[3] ³
Mwirigi A, Dillon R, Raj K. Acute leukaemia. Medicine. 2017;45(5):280-6.

[4] ⁴
Shah A, Andersson TM, Rachet B, Björkholm M, Lambert PC. Survival and cure of acute myeloid leukaemia in England, 1971-2006: a population-based study. Br J Haematol. 2013;162(4):509-16.

[5] ⁵
Swerdlow SH, Campo E, Harris NL, Jaffe ES, Pileri SA, Stein H, et al, editors. WHO classification of tumours of haematopoietic and lymphoid tissues: WHO classification of tumours, revised 4th edition, volume 2. Geneva: WHO; 2017.

[6] ⁶
Thuler LC, Pombo-de-Oliveira MS. Acute promyelocytic leukaemia is highly frequent among acute myeloid leukaemias in Brazil: a hospital-based cancer registry study from 2001 to 2012. Ann Hematol. 2017;96(3):355-62.

[7] ⁷
Rabade N, Raval G, Chaudhary S, Subramanian PG, Kodgule R, Joshi S, et al. Molecular heterogeneity in acute promyelocytic leukemia - a single center experience from India. Mediterr J Hematol Infect Dis. 2018;10(1):e2018002.

[8] ⁸
Hasan M, Beitz B, Rouilly V, Libri V, Urrutia A, Duffy D, Cassard L, Di Santo JP, Mottez E, Quintana-Murci L, Albert ML, Rogge L; Milieu Intérieur Consortium. Semi-automated and standardized cytometric procedures for multi-panel and multi-parametric whole blood immunophenotyping. Clin Immunol. 2015; 157(2):261-76.

[9] ⁹
Peters JM, Ansari MQ. Multiparameter flow cytometry in the diagnosis and management of acute leukemia. Arch Pathol Lab Med. 2011;135(1):44-54. Review.

[10] ¹⁰
Chiaretti S, Zini G, Bassan R. Diagnosis and subclassification of acute lymphoblastic leukemia. Mediterr J Hematol Infect Dis. 2014;6(1):e2014073. Review.

[11] ¹¹
Haddad F, Wraikat A, Khasawneh R, Kamal N. Immunophenotypic diagnosis of acute lymphoblastic leukemia using flow cytometry; experience at King Hussein Medical Center. J Royal Med Serv. 2014;21(2):21-6.

[12] ¹²
Bhushan B, Chauhan PS, Saluja S, Verma S, Mishra AK, Siddiqui S, et al. Aberrant phenotypes in childhood and adult acute leukemia and its association with adverse prognostic factors and clinical outcome. Clin Exp Med. 2010;10(1):33-40.

[13] ¹³
van Dongen JJ, Lhermitte L, Böttcher S, Almeida J, van der Velden VH, Flores-Montero J, Rawstron A, Asnafi V, Lécrevisse Q, Lucio P, Mejstrikova E, Szczepański T, Kalina T, de Tute R, Brüggemann M, Sedek L, Cullen M, Langerak AW, Mendonça A, Macintyre E, Martin-Ayuso M, Hrusak O, Vidriales MB, Orfao A; EuroFlow Consortium (EU-FP6, LSHB-CT-2006-018708). EuroFlow antibody panels for standardized n-dimensional flow cytometric immunophenotyping of normal, reactive and malignant leukocytes. Leukemia. 2012;26(9):1908-75.

[14] ¹⁴
Hrusák O, Porwit-MacDonald A. Antigen expression patterns reflecting genotype of acute leukemias. Leukemia. 2002;16(7):1233-58. Review.

[15] ¹⁵
Kalina T, Vaskova M, Mejstrikova E, Madzo J, Trka J, Stary J, et al. Myeloid antigens in childhood lymphoblastic leukemia: clinical data point to regulation of CD66c distinct from other myeloid antigens. BMC Cancer. 2005;5:38.

[16] ¹⁶
Emerenciano M, Bossa Y, Zanrosso CW, Alencar DM, Campos MM, Dobbin J, et al. Freqüência de imunofenótipos aberrantes em leucemias agudas. Rev Bras Cancerol. 2004;50(3):183-9.

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Characteristics	ALL B (n=277)	ALL T (n=63)	Non-APL AML (n=376)	APL (n=80)
Age, n (%)
≤2 years	22 (7.9)	0 (0)	15 (4)	0 (0)
3-16 years	137 (49.5)*	26 (41.3)	26 (6.9)	10 (12.5)
>16 years	118 (42.6)	37 (58.7)	335 (89.1)*	70 (87.5)*
Median	11	18	52	33
Sex, n (%)
Female	138 (49.8)	14 (22.2)*	200 (53.2)	42 (52.5)
Male	139 (50.2)	49 (77.8)*	176 (46.8)	38 (47.5)
White blood cell count, n (%)
<10,000	29 (20)	3 (9)	37 (18)	4 (9)
10,000-50,000	55 (38)	14 (42)	72 (35)	23 (49)
50,000-100,000	29 (20)	7 (21)	43 (21)	11 (23)
>100,000	31 (22)	9 (27)	56 (27)	9 (19)
Mean	81,389	83,639	80,218	60,185
Median	39,500	47,600	44,650	44,700
Blasts, (%)
Mean	71	62	50	85
Median	77	70	46	88
Sample, (%)
Bone marrow	69	35	44	60
Peripheral blood	31	65	56	40

	Non-APL AML			n		APL		n	B-cell ALL			n	T-cell ALL

	Positive	Negative	Partial		Positive	Negative	Partial		Positive	Negative	Partial		Positive	Negative		Partial

	cases (%)	cases (%)	cases (%)		cases (%)	cases (%)	cases (%)		cases (%)	cases (%)	cases (%)		cases (%)	cases (%)		cases (%)
CD13	287 (77)	22 (6)	63 (17)	372	74 (93)	0 (0)	6 (7)	80	57 (21)	184 (67)	35 (13)	276	10 (16)		40 (63)	13 (21)	63
CD33	309 (84)	17 (5)	43 (12)	369	78 (99)	0 (0)	1 (1)	79	29 (11)	204 (74)	43 (16)	276	6 (10)		47 (75)	10 (15)	63
CD34	222 (60)	93 (25)	58 (15)	373	0 (0)	66 (83)	14 (17)	80	145 (53)	63 (23)	66 (24)	274	11 (18)		32 (52)	18 (30)	61
CD45	369 (98)	2 (1)	3 (1)	374	80 (100)	0 (0)	0 (0)	80	139 (50)	46 (17)	92 (33)	277	62 (98)		0 (0)	1 (2)	63
MPO	181 (49)	112 (30)	77 (21)	370	80 (100)	0 (0)	0 (0)	80	0 (0)	277 (100)	0 (0)	277	0 (0)		63 (100)	0 (0)	63
CD19	7 (1.9)	349 (93.1)	19 (5.1)	375	0 (0)	80 (100)	0 (0)	80	272 (98.2)	1 (0.4)	4 (1.4)	277	0 (0)		63 (100)	0 (0)	63
CD3cyt	0 (0)	374 (100)	0 (0)	374	0 (0)	79 (100)	0 (0)	79	0 (0)	275 (100)	0 (0)	275	56 (88.9)		0 (0)	7 (11.1)	63
CD3mem	0 (0)	375 (100)	0 (0)	375	0 (0)	80 (100)	0 (0)	80	0 (0)	276 (100)	0 (0)	276	24 (38.1)		18 (28.6)	21 (33.3)	63
CD15	10 (3)	334 (90)	25 (7)	369	0 (0)	78 (97)	2 (3)	80	NR	NR	NR		NR		NR	NR
CD56	13 (7)	151 (82)	21 (11)	185	1 (3)	27 (84)	4 (13)	32	NR	NR	NR		NR		NR	NR
CD64	67 (18)	262 (70)	43 (12)	372	21 (27)	28 (35)	30 (38)	79	NR	NR	NR		NR		NR	NR
HLA-DR	271 (72)	47 (13)	45 (15)	375	0 (0)	72 (92)	7 (8)	79	NR	NR	NR		NR		NR	NR
CD2	9 (2.4)	348 (94.1)	13 (3.5)	370	6 (7.6)	52 (65.8)	21 (26.6)	79	NR	NR	NR		42 (66.7)		11 (17.5)	10 (15.9)	63
CD7	59 (15.8)	234 (62.6)	81 (21.7)	374	1 (1.3)	78 (97.5)	1 (1.3)	80	NR	NR	NR		62 (98.4)		0 (0)	1 (1.6)	63
CD117	309 (82.8)	29 (7.8)	35 (9.3)	373	43 (54.4)	5 (6.3)	31 (39.2)	79	NR	NR	NR		8 (2.7)		51 (81)	4 (6.3)	63
CD10	NR	NR	NR		NR	NR	NR		234 (84.5)	23 (8.3)	20 (7.2)	277	12 (19.7)		34 (55.7)	15 (24.6)	61
CD20	NR	NR	NR		NR	NR	NR		64 (25.8)	93 (37.5)	91 (36.7)	248	NR		NR	NR
CD4	NR	NR	NR		NR	NR	NR		NR	NR	NR		14 (22.6)		29 (46.8)	19 (30.6)	62
CD8	NR	NR	NR		NR	NR	NR		NR	NR	NR		30 (48.4)		19 (30.6)	13 (21)	62
CD5	NR	NR	NR		NR	NR	NR		NR	NR	NR		49 (77.8)		7 (11.1)	7 (11.1)	63
CD1a	NR	NR	NR		NR	NR	NR		NR	NR	NR		8 (13.1)		36 (57.1)	17 (27.8)	61
CD38	NR	NR	NR		NR	NR	NR		123 (74.1)	18 (10.8)	25 (15.1)	166	NR		NR	NR
CD66c	NR	NR	NR		NR	NR	NR		26 (38.8)	25 (37.3)	16 (23.9)	67	NR		NR	NR
CD81	NR	NR	NR		NR	NR	NR		93 (93)	2 (2)	5 (5)	100	NR		NR	NR
CD79a	NR	NR	NR		NR	NR	NR		260 (94.9)	4 (1.5)	10 (3.6)	274	NR		NR	NR

	non-APL AML	APL	non-APL AML		APL		non-APL AML		APL

			Female	Male	Female	Male	≤15 years	>15 years	≤15 years	>15 years

	Cases/total (%)	Cases/total (%)	Cases/total (%)	Cases/total (%)	Cases/total (%)	Cases/total (%)	Cases/total (%)	Cases/total (%)	Cases/total (%)	Cases/total (%)
CD13	350/372 (94.1)	80/80 (100)	186/197 (94.4)	164/175 (93.7)	42/42 (100)	38/38 (100)	30/36 (83.3)	320/336 (95.2)*	9/9 (100)	71/71 (100)
CD33	352/369 (95.4)	79/79 (100)	189/194 (97.4)	163/175 (93.1)	41/41 (100)	38/38 (100)	36/37 (97.3)	316/332 (95.2)	9/9 (100)	70/70 (100)
CD34	280/373 (75.1)	14/80 (17.5)	143/200 (71.5)	137/173 (79.2)	9/42 (21.4)	5/38 (13.2)	29/37 (78.4)	251/336 (74.7)	1/9 (11.1)	13/71 (18.3)
CD2	22/370 (5.9)	27/79 (34.2)	7/198 (3.5)	15/172 (8.7)*	18/42 (42.9)	9/37 (24.3)	4/35 (11.4)	18/335 (5.4)	1/9 (11.1)	26/70 (37.1)
CD7	140/374 (37.4)	2/80 (2.5)	72/198 (36.4)	68/176 (38.6)	2/42 (4.8)	0/38 (0)	16/37 (43.2)	124/337 (36.8)	0/9 (0)	2/71 (2.8)
CD117	344/373 (92.2)	74/79 (93.7)	184/199 (92.5)	160/174 (92)	40/42 (95.2)	34/37 (91.9)	32/37 (86.5)	312/336 (92.9)	6/9 (66.7)	68/70 (97.1)
CD56	34/185 (18.4)	5/32 (15.6)	19/103 (18.4)	15/82 (18.3)	1/17 (5.9)	4/15 (26.7)	4/15 (26.7)	30/170 (17.6)	0/3 (0)	5/29 (17.2)
CD64	110/372 (29.6)	51/79 (64.6)	57/197 (28.9)	53/175 (30.3)	27/41 (65.9)	24/38 (63.2)	14/37 (37.8)	96/335 (28.7)	6/9 (66.7)	45/70 (64.3)
HLA-DR	328/375 (87.5)	7/79 (8.9)	176/199 (88.4)	152/176 (86.4)	5/42 (11.9)	2/37 (5.4)	29/37 (78.4)	299/338 (88.5)	0/9 (0)	7/70 (10)
MPO	258/370 (69.7)	80/80 (100)	144/197 (73.1)	114/173 (65.9)	42/42 (100)	38/38 (100)	19/37 (51.4)	239/333 (71.8)*	9/9 (100)	71/71 (100)

	B-cell ALL	T-cell ALL	B-cell ALL		T-cell ALL		B-cell ALL		T-cell ALL

			Female	Male	Female	Male	≤15 years	>15 years	≤15 years	>15 years

	Cases/total (%)	Cases/total (%)	Cases/total (%)	Cases/total (%)	Cases/total (%)	Cases/total (%)	Cases/total (%)	Cases/total (%)	Cases/total (%)	Cases/total (%)
CD13	92/276 (33)	23/63 (36.5)	43/137 (31.4)	49/139 (35.3)	6/14 (42.9)	17/49 (34.7)	47/152 (30.9)	45/124 (36.3)	8/22 (36.4)	15/41 (36.6)
CD33	72/276 (26)	16/63 (25.4)	34/137 (24.8)	38/139 (27.3)	2/14 (14.3)	14/49 (28.6)	34/152 (22.4)	38/124 (30.6)	6/22 (27.3)	10/41 (24.4)
CD34	211/274 (77)	29/61 (47.5)	100/135 (74.1)	111/139 (79.9)	7/14 (50)	22/47 (46.8)	108/151 (71.5)	103/123 (83.7) *	11/22 (50)	18/39 (46.2)
CD45	231/277 (83.4)	63/63 (100)	117/138 (84.8)	114/139 (82)	14/14 (100)	49/49 (100)	126/153 (82.4)	105/124 (84.7)	22/22 (100)	41/41 (100)
CD10	254/277 (91.7)	27/61 (44.3)	123/138 (89.1)	131/139 (94.2)	8/14 (57.1)	19/47 (40.4)	143/153 (93.5)	111/124 (89.5)	8/22 (36.4)	19/39 (48.7)
CD20	155/248 (62.5)	NR	78/124 (62.9)	77/124 (62.1)	NR	NR	84/134 (62.7)	71/114 (62.3)	NR	NR
CD38	148/166 (89.2)	NR	77/85 (90.6)	71/81 (87.7)	NR	NR	80/86 (93)	68/80 (85)	NR	NR
CD19	276/277 (99.6)	NR	137/138 (99.3)	139/139 (100)	NR	NR	153/153 (100)	123/124 (99.2)	NR	NR
CD66c	42/67 (62.7)	NR	24/34 (70.6)	18/33 (54.5)	NR	NR	19/37 (51.4)	23/30 (76.7) *	NR	NR
CD2	NR	52/63 (82.5)	NR	NR	12/14 (85.7)	40/49 (81.6)	NR	NR	21/22 (95.5)	31/41 (75.6) *
CD7	NR	63/63 (100)	NR	NR	14/14 (100)	49/49 (100)	NR	NR	22/22 (100)	41/41 (100)
CD117	NR	12/63 (19)	NR	NR	1/14 (7.1)	11/49 (22.4)	NR	NR	1/22 (4.5)	11/41 (26.8) *
CD3cyt	NR	63/63 (100)	NR	NR	14/14 (100)	49/49 (100)	NR	NR	22/22 (100)	41/41 (100)
CD3mem	NR	45/63 (71.4)	NR	NR	10/14 (71.4)	35/49 (71.4)	NR	NR	18/22 (81.8)	27/41 (65.9)
CD4	NR	33/62 (53.2)	NR	NR	9/14 (64.3)	24/48 (50)	NR	NR	11/22 (50)	22/40 (55)
CD8	NR	43/62 (69.4)	NR	NR	9/14 (64.3)	34/48 (70.8)	NR	NR	16/22 (72.7)	27/40 (67.5)
CD5	NR	56/63 (88.9)	NR	NR	13/14 (92.9)	43/49 (87.8)	NR	NR	22/22 (100)	34/41 (82.9) *
CD1a	NR	25/61 (41)	NR	NR	7/14 (50)	18/47 (38.3)	NR	NR	10/22 (45.5)	15/39 (38.5)