BACKGROUND: The Human Cell Differentiation Molecules (HCDM) organizes Human Leukocyte Differentiation Antigen (HLDA) workshops to test and name clusters of antibodies that react with a specific antigen. These cluster of differentiation (CD) markers have provided the scientific community with validated antibody clones, consistent naming of targets and reproducible identification of leukocyte subsets. Still, quantitative CD marker expression profiles and benchmarking of reagents at the single-cell level are currently lacking. OBJECTIVE: To develop a flow cytometric procedure for quantitative expression profiling of surface antigens on blood leukocyte subsets that is standardized across multiple research laboratories. METHODS: A high content framework to evaluate the titration and reactivity of Phycoerythrin (PE)-conjugated monoclonal antibodies (mAbs) was created. Two flow cytometry panels were designed: an innate cell tube for granulocytes, dendritic cells, monocytes, NK cells and innate lymphoid cells (12-color) and an adaptive lymphocyte tube for naive and memory B and T cells, including TCRγδ+, regulatory-T and follicular helper T cells (11-color). The potential of these 2 panels was demonstrated via expression profiling of selected CD markers detected by PE-conjugated antibodies and evaluated using 561 nm excitation. RESULTS: Using automated data annotation and dried backbone reagents, we reached a robust workflow amenable to processing hundreds of measurements in each experiment in a 96-well plate format. The immunophenotyping panels enabled discrimination of 27 leukocyte subsets and quantitative detection of the expression of PE-conjugated CD markers of interest that could quantify protein expression above 400 units of antibody binding capacity. Expression profiling of 4 selected CD markers (CD11b, CD31, CD38, CD40) showed high reproducibility across centers, as well as the capacity to benchmark unique clones directed toward the same CD3 antigen. CONCLUSION: We optimized a procedure for quantitative expression profiling of surface antigens on blood leukocyte subsets. The workflow, bioinformatics pipeline and optimized flow panels enable the following: 1) mapping the expression patterns of HLDA-approved mAb clones to CD markers; 2) benchmarking new antibody clones to established CD markers; 3) defining new clusters of differentiation in future HLDA workshops.

• Keywords
• CD marker, cluster of differentiation (CD), expression profiling, flow cytometry, surfaceome,
• MeSH
• Antigens, Surface * metabolism   MeSH
• Killer Cells, Natural metabolism   MeSH
• Antigens, CD metabolism   MeSH
• Leukocytes MeSH
• Humans MeSH
• Antibodies, Monoclonal MeSH
• Immunity, Innate * MeSH
• Workflow MeSH
• Flow Cytometry methods   MeSH
• Reference Standards MeSH
• Reproducibility of Results MeSH
• Check Tag
• Humans MeSH
• Publication type
• Journal Article MeSH
• Research Support, Non-U.S. Gov't MeSH
• Names of Substances
• Antigens, Surface * MeSH
• Antigens, CD MeSH
• Antibodies, Monoclonal MeSH

Acute leukemia is a disease pathologically manifested at both genomic and proteomic levels. Molecular genetic technologies are currently widely used in clinical research. In contrast, sensitive and high-throughput proteomic techniques for performing protein analyses in patient samples are still lacking. Here, we used a technology based on size exclusion chromatography followed by immunoprecipitation of target proteins with an antibody bead array (Size Exclusion Chromatography-Microsphere-based Affinity Proteomics, SEC-MAP) to detect hundreds of proteins from a single sample. In addition, we developed semi-automatic bioinformatics tools to adapt this technology for high-content proteomic screening of pediatric acute leukemia patients.To confirm the utility of SEC-MAP in leukemia immunophenotyping, we tested 31 leukemia diagnostic markers in parallel by SEC-MAP and flow cytometry. We identified 28 antibodies suitable for both techniques. Eighteen of them provided excellent quantitative correlation between SEC-MAP and flow cytometry (p< 0.05). Next, SEC-MAP was applied to examine 57 diagnostic samples from patients with acute leukemia. In this assay, we used 632 different antibodies and detected 501 targets. Of those, 47 targets were differentially expressed between at least two of the three acute leukemia subgroups. The CD markers correlated with immunophenotypic categories as expected. From non-CD markers, we found DBN1, PAX5, or PTK2 overexpressed in B-cell precursor acute lymphoblastic leukemias, LAT, SH2D1A, or STAT5A overexpressed in T-cell acute lymphoblastic leukemias, and HCK, GLUD1, or SYK overexpressed in acute myeloid leukemias. In addition, OPAL1 overexpression corresponded to ETV6-RUNX1 chromosomal translocation.In summary, we demonstrated that SEC-MAP technology is a powerful tool for detecting hundreds of proteins in clinical samples obtained from pediatric acute leukemia patients. It provides information about protein size and reveals differences in protein expression between particular leukemia subgroups. Forty-seven of SEC-MAP identified targets were validated by other conventional method in this study.

• MeSH
• Precursor Cell Lymphoblastic Leukemia-Lymphoma diagnosis   immunology   metabolism   MeSH
• Diagnosis, Differential MeSH
• Child MeSH
• Chromatography, Gel methods   MeSH
• Immunophenotyping methods   MeSH
• Immunoprecipitation MeSH
• Infant MeSH
• Automation, Laboratory MeSH
• Humans MeSH
• Adolescent MeSH
• Cell Line, Tumor MeSH
• Child, Preschool MeSH
• Proteomics methods   MeSH
• Antibodies pharmacology   MeSH
• Gene Expression Regulation, Leukemic MeSH
• Check Tag
• Child MeSH
• Infant MeSH
• Humans MeSH
• Adolescent MeSH
• Child, Preschool MeSH
• Publication type
• Journal Article MeSH
• Research Support, Non-U.S. Gov't MeSH
• Names of Substances
• Antibodies MeSH

BACKGROUND: Both high hyperdiploidy (HeH) and the translocation t(9;22)(q34;q11) are recurrent abnormalities in childhood B-cell acute lymphoblastic leukemia (ALL) and both are used in current classification to define different genetic and prognostic subtypes of the disease. The coexistence of these two primary genetic aberrations within the same clone is very rare in children with ALL. Here we report a new case of a 17-year-old girl with newly diagnosed ALL and uncommon cytogenetic and clinical finding combining high hyperdiploidy and a cryptic BCR/ABL1 fusion and an inherited Charcot-Marie-Tooth neuropathy detected during the induction treatment. RESULTS: High hyperdiploid karyotype 51,XX,+X,+4,+14,+17,+21 without apparent structural aberrations was detected by conventional cytogenetic analysis and multicolor FISH. A cryptic BCR/ABL1 fusion, which was caused by the insertion of part of the ABL1 gene into the 22q11 region, was proved in HeH clone by FISH, RT-PCR and CGH-SNP array. In addition, an abnormal FISH pattern previously described as the deletion of the 3'BCR region in some BCR/ABL1 positive cases was not proved in our patient. CONCLUSION: A novel case of extremely rare childhood ALL, characterized by HeH and a cryptic BCR/ABL1 fusion, is presented and to the best of our knowledge described for the first time. The insertion of ABL1 into the BCR region in malignant cells is supposed. Clearly, further studies are needed to determine the genetic consequences and prognostic implications of these unusual cases.

• Keywords
• BCR/ABL1 fusion, CGH–SNP array, FISH, High-hyperdiploid childhood ALL, Ph-negative childhood ALL,
• Publication type
• Journal Article MeSH
• Case Reports MeSH

Switches from the lymphoid to myeloid lineage during B-cell precursor acute lymphoblastic leukemia (BCP-ALL) treatment are considered rare and thus far have been detected in MLL-rearranged leukemia. Here, we describe a novel BCP-ALL subset, switching BCP-ALL or swALL, which demonstrated monocytosis early during treatment. Despite their monocytic phenotype, 'monocytoids' share immunoreceptor gene rearrangements with leukemic B lymphoblasts. All swALLs demonstrated BCP-ALL with CD2 positivity and no MLL alterations, and the proportion of swALLs cases among BCP-ALLs was unexpectedly high (4%). The upregulation of CEBPα and demethylation of the CEBPA gene were significant in blasts at diagnosis, prior to the time when most of the switching occurs. Intermediate stages between CD14(neg)CD19(pos)CD34(pos) B lymphoblasts and CD14(pos)CD19(neg)CD34(neg) 'monocytoids' were detected, and changes in the expression of PAX5, PU1, M-CSFR, GM-CSFR and other genes accompanied the switch. Alterations in the Ikaros and ERG genes were more frequent in swALL patients; however, both were altered in only a minority of swALLs. Moreover, switching could be recapitulated in vitro and in mouse xenografts. Although children with swALL respond slowly to initial therapy, risk-based ALL therapy appears the treatment of choice for swALL. SwALL shows that transdifferentiating into monocytic lineage is specifically associated with CEBPα changes and CD2 expression.

• MeSH
• CD2 Antigens immunology   MeSH
• Cell Lineage MeSH
• Child MeSH
• Immunophenotyping MeSH
• Cohort Studies MeSH
• Humans MeSH
• Adolescent MeSH
• Monocytes pathology   MeSH
• Multiplex Polymerase Chain Reaction MeSH
• Precursor B-Cell Lymphoblastic Leukemia-Lymphoma immunology   pathology   MeSH
• Child, Preschool MeSH
• Prognosis MeSH
• Neoplasm, Residual MeSH
• Check Tag
• Child MeSH
• Humans MeSH
• Adolescent MeSH
• Male MeSH
• Child, Preschool MeSH
• Female MeSH
• Publication type
• Journal Article MeSH
• Research Support, Non-U.S. Gov't MeSH
• Validation Study MeSH
• Names of Substances
• CD2 Antigens MeSH

BACKGROUND: Mixed phenotype acute leukemia (MPAL) represents a diagnostic and therapeutic dilemma. The European Group for the Immunological Classification of Leukemias (EGIL) scoring system unambiguously defines MPAL expressing aberrant lineage markers. Discussions surrounding it have focused on scoring details, and information is limited regarding its biological, clinical and prognostic significance. The recent World Health Organization classification is simpler and could replace the EGIL scoring system after transformation into unambiguous guidelines. DESIGN AND METHODS: Simple immunophenotypic criteria were used to classify all cases of childhood acute leukemia in order to provide therapy directed against acute lymphoblastic leukemia or acute myeloid leukemia. Prognosis, genotype and immunoglobulin/T-cell receptor gene rearrangement status were analyzed. RESULTS: The incidences of MPAL were 28/582 and 4/107 for children treated with acute lymphoblastic leukemia and acute myeloid leukemia regimens, respectively. In immunophenotypic principal component analysis, MPAL treated as T-cell acute lymphoblastic leukemia clustered between cases of non-mixed T-cell acute lymphoblastic leukemia and acute myeloid leukemia, while other MPAL cases were included in the respective non-mixed B-cell progenitor acute lymphoblastic leukemia or acute myeloid leukemia clusters. Analogously, immunoglobulin/T-cell receptor gene rearrangements followed the expected pattern in patients treated as having acute myeloid leukemia (non-rearranged, 4/4) or as having B-cell progenitor acute lymphoblastic leukemia (rearranged, 20/20), but were missing in 3/5 analyzed cases of MPAL treated as having T-cell acute lymphobastic leukemia. In patients who received acute lymphoblastic leukemia treatment, the 5-year event-free survival of the MPAL cases was worse than that of the non-mixed cases (53+/-10% and 76+/-2% at 5 years, respectively, P=0.0075), with a more pronounced difference among B lineage cases. The small numbers of MPAL cases treated as T-cell acute lymphoblastic leukemia or as acute myeloid leukemia hampered separate statistics. We compared prognosis of all subsets with the prognosis of previously published cohorts. CONCLUSIONS: Simple immunophenotypic criteria are useful for therapy decisions in MPAL. In B lineage leukemia, MPAL confers poorer prognosis. However, our data do not justify a preferential use of current acute myeloid leukemia-based therapy in MPAL.

• MeSH
• Precursor Cell Lymphoblastic Leukemia-Lymphoma diagnosis   immunology   therapy   MeSH
• Leukemia, Myeloid, Acute diagnosis   immunology   therapy   MeSH
• Diagnosis, Differential MeSH
• Child MeSH
• Phenotype * MeSH
• Immunophenotyping * methods   MeSH
• Infant MeSH
• Leukemia diagnosis   immunology   therapy   MeSH
• Humans MeSH
• Adolescent MeSH
• Follow-Up Studies MeSH
• Infant, Newborn MeSH
• Child, Preschool MeSH
• Prognosis MeSH
• Receptors, Antigen, T-Cell immunology   MeSH
• Check Tag
• Child MeSH
• Infant MeSH
• Humans MeSH
• Adolescent MeSH
• Infant, Newborn MeSH
• Child, Preschool MeSH
• Publication type
• Journal Article MeSH
• Multicenter Study MeSH
• Research Support, Non-U.S. Gov't MeSH
• Comparative Study MeSH
• Names of Substances
• Receptors, Antigen, T-Cell MeSH

BACKGROUND: Aberrant expression of myeloid antigens (MyAgs) on acute lymphoblastic leukemia (ALL) cells is a well-documented phenomenon, although its regulating mechanisms are unclear. MyAgs in ALL are interpreted e.g. as hallmarks of early differentiation stage and/or lineage indecisiveness. Granulocytic marker CD66c -- Carcinoembryonic antigen-related cell adhesion molecule 6 (CEACAM6) is aberrantly expressed on ALL with strong correlation to genotype (negative in TEL/AML1 and MLL/AF4, positive in BCR/ABL and hyperdiploid cases). METHODS: In a cohort of 365 consecutively diagnosed Czech B-precursor ALL patients, we analyze distribution of MyAg+ cases and mutual relationship among CD13, CD15, CD33, CD65 and CD66c. The most frequent MyAg (CD66c) is studied further regarding its stability from diagnosis to relapse, prognostic significance and regulation of surface expression. For the latter, flow cytometry, Western blot and quantitative RT-PCR on sorted cells is used. RESULTS: We show CD66c is expressed in 43% patients, which is more frequent than other MyAgs studied. In addition, CD66c expression negatively correlates with CD13 (p < 0.0001), CD33 (p = 0.002) and/or CD65 (p = 0.029). Our data show that different myeloid antigens often differ in biological importance, which may be obscured by combining them into "MyAg positive ALL". We show that unlike other MyAgs, CD66c expression is not shifted from the onset of ALL to relapse (n = 39, time to relapse 0.3-5.3 years). Although opposite has previously been suggested, we show that CEACAM6 transcription is invariably followed by surface expression (by quantitative RT-PCR on sorted cells) and that malignant cells containing CD66c in cytoplasm without surface expression are not found by flow cytometry nor by Western blot in vivo. We report no prognostic significance of CD66c, globally or separately in genotype subsets of B-precursor ALL, nor an association with known risk factors (n = 254). CONCLUSION: In contrast to general notion we show that different MyAgs in lymphoblastic leukemia represent different biological circumstances. We chose the most frequent and tightly genotype-associated MyAg CD66c to show its stabile expression in patients from diagnosis to relapse, which differs from what is known on the other MyAgs. Surface expression of CD66c is regulated at the gene transcription level, in contrast to previous reports.

• MeSH
• Precursor Cell Lymphoblastic Leukemia-Lymphoma metabolism   MeSH
• Sialic Acid Binding Ig-like Lectin 3 MeSH
• Lewis X Antigen biosynthesis   MeSH
• CD13 Antigens biosynthesis   MeSH
• Antigens, Differentiation, Myelomonocytic biosynthesis   MeSH
• Cell Membrane metabolism   MeSH
• Time Factors MeSH
• Antigens, CD biosynthesis   MeSH
• Cytoplasm metabolism   MeSH
• Child MeSH
• Transcription, Genetic MeSH
• Genotype MeSH
• Glycosylation MeSH
• GPI-Linked Proteins MeSH
• Immunophenotyping MeSH
• Cohort Studies MeSH
• Infant MeSH
• Humans MeSH
• Adolescent MeSH
• Cell Adhesion Molecules biosynthesis   MeSH
• Reverse Transcriptase Polymerase Chain Reaction MeSH
• Child, Preschool MeSH
• Disease-Free Survival MeSH
• Prognosis MeSH
• Flow Cytometry MeSH
• Recurrence MeSH
• Gene Expression Regulation, Neoplastic * MeSH
• RNA metabolism   MeSH
• Blotting, Western MeSH
• Check Tag
• Child MeSH
• Infant MeSH
• Humans MeSH
• Adolescent MeSH
• Child, Preschool MeSH
• Publication type
• Journal Article MeSH
• Research Support, Non-U.S. Gov't MeSH
• Geographicals
• Czech Republic MeSH
• Names of Substances
• Sialic Acid Binding Ig-like Lectin 3 MeSH
• Lewis X Antigen MeSH
• CD13 Antigens MeSH
• Antigens, Differentiation, Myelomonocytic MeSH
• Antigens, CD MeSH
• CD33 protein, human MeSH Browser
• CD65s antigen, human MeSH Browser
• CEACAM6 protein, human MeSH Browser
• GPI-Linked Proteins MeSH
• Cell Adhesion Molecules MeSH
• RNA MeSH