High-resolution Antibody Array Analysis of Childhood Acute Leukemia Cells

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.Acute leukemia (AL)¹ is the most common childhood cancer, accounting for a quarter of all pediatric malignancies (1). Accumulated chromosomal translocations and mutations in proto-oncogenes alter proliferation, differentiation, apoptosis and death in developing hematogones, ultimately leading to the development of leukemia (2, 3). The most recent understanding of these cancer-related changes is based on molecular genetic studies that focused primarily on DNA and mRNA alterations. High-throughput molecular genetic technologies, such as mRNA expression profiling and next generation sequencing, are widely used in clinical research. These techniques can provide new classification schemes, define new prognostic subgroups and outline the background of some pathological mechanisms (2, 4, 5, 6, 7) but they cannot easily elucidate the functional consequences at the cellular level. Proteins are the principal carriers of cellular functions. Thus, the analysis of proteins and protein modifications can elucidate the pathological mechanisms of leukemia or clarify the response mechanisms to current and emerging therapies. Currently, flow cytometry is used in clinical laboratories to analyze dozens of proteins that are expressed by leukemic cells (8, 9). These proteins, which are mostly surface CD markers, can reflect lineage commitment, developmental status and even the underlying genetic lesion (10, 11) but they do not carry information about the intracellular processes that control malignant transformation. Moreover, many cancer alterations are manifested only at the functional level, including changes in subcellular localization, post-translational modification (e.g. phosphorylation), protein cleavage, or protein–protein interactions (12). Proteomic techniques that can capture disease-associated changes are needed. Mass spectrometry (MS) is presently the technique of choice for large-scale proteomic analysis. MS can uncover thousands of molecules without an a priori probe selection, e.g. new disease-associated features in B-cell precursor acute lymphoblastic leukemia (BCP-ALL) (13, 14). Despite its tremendous analytical power, MS is complex and not widely accessible. Unlike MS, affinity proteomics is a simple technology suitable for large-scale protein analysis in primary cancer samples in the clinical laboratories. Recently, a technique linking size exclusion chromatography (SEC) to microsphere-based antibody arrays (microsphere-based affinity proteomics (MAP)) has been developed (15, 16). SEC-MAP enables the detection of hundreds of proteins in a single sample and provides essential information about protein size. Because only five to ten million cells are necessary, SEC-MAP can serve as a sensitive, sample-sparing and high-content tool for protein profiling in leukemia samples probing the relative amounts of different proteins, as well as protein size and cleavage (17). Our in-house-assembled MAP array is a set of 1152 populations of fluorescent-labeled microbeads, each carrying an antibody against a single human antigen. Native cellular proteins (and their complexes) are isolated from cellular compartments using detergents, labeled with biotin (biotin-PEO4-NHS) and subjected to SEC to obtain 24 size fractions. The SEC fractions are incubated with MAP microbeads, and antibody-protein binding is detected using phycoerythrin (PE)-labeled streptavidin with flow cytometry. The flow cytometer resolves the color code of each microbead population and reads the amount of bound protein. The data from 24 SEC fractions are combined, and a protein''s binding relative to its size is detected as a “protein entity.” Data are analyzed with in-house R-based software. This approach permits automatic batch processing of raw flow cytometry standard (FCS) files in addition to advanced analyses including quality control steps (the minimal number of microspheres required in a population and the unimodality of the signal in the PE channel is checked) (17). We wanted to find out whether SEC-MAP can be used in the clinical laboratory to bring a biologically important information, e.g. to classify acute leukemias or to find the marker with a prognostic relevance. We assembled MAP arrays to carry antibodies against proteins that are known to be important for leukemia diagnostics (18, 9) and against components of intracellular signaling networks (16). Through extensive testing on leukemia samples, we have identified antibodies that are suitable for immunoprecipitation-based techniques. Furthermore, we have improved the software tools to allow for large-scale data normalization, fast automatic protein entity detection with manual correction, and the discovery of differentially expressed entities in multiple samples. Using innovative software tools, we have identified entities that were differentially expressed between particular AL subgroups. To ensure the specificity we have validated the data collected by SEC-MAP with classical flow cytometry-based immunophenotyping (FACS), Western blot (WB) and quantitative real-time PCR (qRT-PCR). Moreover, we have addressed practical sample processing issues related to patient material handling and logistics. Based on the protein size profile, we were able to discriminate proteolytically degraded samples from those with an uncleaved proteome. Importantly, proteolysis would be missed by conventional protein load controls in Western blots. Thus, the SEC-MAP array was demonstrated to be a useful, reproducible and accurate high-content proteomic tool for the assessment of primary leukemia samples.