Multiparameter flow cytometry in the diagnosis and management of acute leukemia

Exploring the interplay between microRNA expression and DNA mutation analysis in AML patients

MicroRNAs (miRNAs) are key regulators in Acute Myeloid Leukemia AML, affecting gene expression, including that of CD markers and impacting mutations within leukemic cells. Mutations in AML can alter miRNA profiles, which can affect the expression of CD markers and contribute to disease progression by influencing cellular processes such as differentiation, proliferation, and apoptosis. Here, we examined the interplay of cell surface protein expression (CD markers), DNA mutations, and microRNA expression in AML patients. We included 32 recently diagnosed AML patients, and CD marker expression was evaluated using flow cytometry and molecular techniques. This study aims to delve into this relationship within the context of AML, elucidating its potential implications for diagnosis, prognosis, and therapeutic interventions. Mutations were scrutinized in six patients using Whole-Exome Sequencing (WES), while quantitative PCR (qPCR) was employed to investigate the expression levels of nine microRNAs. Subsequently, a comprehensive interaction network was constructed using Cytoscape software, focusing on genes with significant mutations and their corresponding microRNAs. Cell surface protein expression analysis revealed upregulation of CD45, CD99, CD34, HLA-DR, CD38, CD13, CD33, MPO, CD15 and CD117 in AML patients. The molecular analysis results unveiled mutations in specific genes (FLT3, KIT, PTPN11, BCR, DNMT3A, and NRAS) targeted by nine microRNAs. Notably, eight microRNAs exhibited heightened expression levels. Network analysis highlighted interactions between the PTPN11 gene and six scrutinized microRNAs. Understanding the regulatory dynamics between gene mutations and microRNAs in AML patients is pivotal for unraveling the disease's molecular mechanisms and identifying potential therapeutic targets. Further exploration into the functional roles of microRNAs in gene regulation and AML pathogenesis is warranted to validate their potential as therapeutic targets, diagnostic markers, and advanced treatment strategies.

Immunophenotypic clustering in paediatric acute myeloid leukaemia

Acute myeloid leukaemia (AML) is a highly heterogeneous disease, exhibiting diverse subtypes according to the characteristics of tumour cells. The immunophenotype is one of the aspects acquired routinely through flow cytometry in the diagnosis of AML. Here, we characterized the antigen expression in paediatric AML cases across both morphological and molecular genetic subgroups. We discovered a subgroup of patients with unfavourable prognosis that can be immunologically characterized, irrespective of morphological FAB results or genetic aberrations. Cox regression analysis unveiled key antigens influencing the prognosis of AML patients. In terms of underlying genotypes, we observed that the antigenic profiles and outcomes of one specific group, primarily composed of CBFA2T3::GLIS2 and FUS::ERG, were analogous to the reported RAM phenotype. Overall, our data highlight the significance of immunophenotype to tailor treatment for paediatric AML.

Raman classification of selected subtypes of acute lymphoblastic leukemia (ALL)

B-cell precursor acute lymphoblastic leukemia (BCP-ALL) with chromosome translocations like KMT2A gene rearrangement (KMT2A-r) and BCR-ABL1 fusion gene have been recognized as crucial drivers in both BCP-ALL leukemogenesis and treatment management. Standard diagnostic protocols for proliferative diseases of the hematopoietic system, like KMT2A-r-ALL, are genetically based and strongly molecularly oriented. Therefore, an efficient diagnostic procedure requires not only experienced and multidisciplinary laboratory staff but also considerable instrumentation and material costs. In recent years, a Raman spectroscopy method has been increasingly used to detect subtle chemical changes in individual cells resulting from stress or disease. Therefore, the objective of this study was to identify Raman signatures for the molecular subtypes and to develop a classification method based on the unique spectroscopic profile of in vitro models that represent specific aberrations aimed at KMT2A-r (RS4;11, and SEM) and the BCR-ABL1 fusion gene (SUP-B15, BV-173, and SD-1). Data analysis was based on chemometric methods, i.e. principal component analysis (PCA), partial least squares discriminant analysis (PLS-DA), and support vector machine (SVM). The PCA-based multivariate model was used for pattern recognition of each investigated group of cells while PLS-DA and SVM were used to build models for the discrimination of spectra from the studied BCP-ALL molecular subtypes. The results showed that the studied molecular subtypes of ALL have characteristic spectroscopic profiles reflecting their peculiar biochemical state. The content of lipids (1600 cm-1), nucleic acids (789 cm-1), and haemoproteins (754, 1130, and 1315 cm-1), which are crucial in cell metabolism, was indicated as the main source of differentiation between subtypes. Identification of spectroscopic markers of cells with BCR-ABL1 or KMT2A-r may be useful in pharmacological studies to monitor the effectiveness of chemotherapy and further to understand differences in molecular responses between leukemia primary cells and cell lines.

The Role of Erythrocyte Sedimentation Rate (ESR) in Myeloproliferative and Lymphoproliferative Diseases: Comparison between DIESSE CUBE 30 TOUCH and Alifax Test 1

(1) Background: The erythrocyte sedimentation rate (ESR) is widely diffused in hematology laboratories to monitor inflammatory statuses, response to therapies (such as antibiotics), and oncologic diseases. However, ESR is not a specific diagnostic marker but needs to be contextualized and compared with clinical and other laboratory findings. This study aimed to investigate the performance of two automated instruments, namely the DIESSE CUBE 30 TOUCH (DIESSE, Siena, Italy) and the Alifax Test 1 (Alifax Srl, Polverara, Italy), in comparison with the gold standard, the Westergren method, in lymphoproliferative and myeloproliferative patients. (2) Methods: 97 EDTA samples were selected from the hematology department of Roma Tor Vergata Hospital and analyzed. Statistical analysis was applied. (3) A good correlation between CUBE 30 TOUCH and the gold standard was observed in the overall sample (R2 = 0.90), as well as in patients with lymphoproliferative diseases (R2 = 0.90) and myeloproliferative diseases (R2 = 0.90). The correlation between Test 1 and the gold standard was observed in the overall sample (R2 = 0.68), as well as in patients with lymphoproliferative diseases (R2 = 0.79) and myeloproliferative diseases (R2 = 0.53). (4) Conclusions: The CUBE 30 TOUCH appears to be a more trustworthy tool for evaluating ESR in these pathologies.

Exosomal circRNA-001264 promotes AML immunosuppression through induction of M2-like macrophages and PD-L1 overexpression

Exosomes can help to effectively regulate the crosstalk between cancer cells and normal cells in the tumor microenvironment. They also regulate cancer cell proliferation and apoptosis by virtue of their cargo molecules. Transmission electron microscopy (TEM) together with differential ultracentrifugation served for verifying the presence of exosomes. In vivo and in vitro assays served for determining the role of exosomal circ_001264. RNA pull-down and dual-luciferase reporter assays assisted in the classification of the mechanism of exosomal circ_001264-mediated regulation of the crosstalk between Acute myeloid leukemia (AML) cells and M2 macrophages. Furthermore, we adopted a programmed death ligand 1 antibody (aPD-L1) in combination with exosomal circ_001264 siRNA for antitumor treatment in vitro and in vivo mouse models served for validating the in vivo outcomes. Out study illustrated the aberrant overexpression of circ_001264 in AML patients and its correlation with poor patient prognosis. AML cell-derived exosomal circ_001264 regulated the RAF1 expression and activated the p38-STAT3 signaling pathway, thereby inducing the M2 macrophage polarization. Polarized M2 macrophages can induce PD-L1 overexpression by secreting PD-L1. Here, a programmed death ligand (aPD-L1) was adopted for preventing the immunosuppression, which was able to achieve the desired therapeutic effect at the tumor site. Indeed, in the mouse model, leukemia tumor load decreased remarkably in the exosomal circ_001264 siRNA plus aPD-L1 combination group. Taken together, our study contributed to a theoretical basis for AML treatment. The co-administration of exosomal circ_001264 siRNA and aPD-L1 exhibited an obvious anti-cancer effectiveness in AML.

Typing of acute leukemia by intelligent optical time-stretch imaging flow cytometry on a chip

Acute leukemia (AL) is one of the top life-threatening diseases. Accurate typing of AL can significantly improve its prognosis. However, conventional methods for AL typing often require cell staining, which is time-consuming and labor-intensive. Furthermore, their performance is highly limited by the specificity and availability of fluorescent labels, which can hardly meet the requirements of AL typing in clinical settings. Here, we demonstrate AL typing by intelligent optical time-stretch (OTS) imaging flow cytometry on a microfluidic chip. Specifically, we employ OTS microscopy to capture the images of cells in clinical bone marrow samples with a spatial resolution of 780 nm at a high flowing speed of 1 m s^-1 in a label-free manner. Then, to show the clinical utility of our method for which the features of clinical samples are diverse, we design and construct a deep convolutional neural network (CNN) to analyze the cellular images and determine the AL type of each sample. We measure 30 clinical samples composed of 7 acute lymphoblastic leukemia (ALL) samples, 17 acute myelogenous leukemia (AML) samples, and 6 samples from healthy donors, resulting in a total of 227 620 images acquired. Results show that our method can distinguish ALL and AML with an accuracy of 95.03%, which, to the best of our knowledge, is a record in label-free AL typing. In addition to AL typing, we believe that the high throughput, high accuracy, and label-free operation of our method make it a potential solution for cell analysis in scientific research and clinical settings.

Immunophenotypic characterization of acute leukemias in Bahia, Brazil

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.

Quartz Crystal Microbalance-Based Aptasensors for Medical Diagnosis

Aptamers are important materials for the specific determination of different disease-related biomarkers. Several methods have been enhanced to transform selected target molecule-specific aptamer bindings into measurable signals. A number of specific aptamer-based biosensors have been designed for potential applications in clinical diagnostics. Various methods in combination with a wide variety of nano-scale materials have been employed to develop aptamer-based biosensors to further increase sensitivity and detection limit for related target molecules. In this critical review, we highlight the advantages of aptamers as biorecognition elements in biosensors for target biomolecules. In recent years, it has been demonstrated that electrode material plays an important role in obtaining quick, label-free, simple, stable, and sensitive detection in biological analysis using piezoelectric devices. For this reason, we review the recent progress in growth of aptamer-based QCM biosensors for medical diagnoses, including virus, bacteria, cell, protein, and disease biomarker detection.

Monocytosis and Multiple Myeloma: treatment-related acute leukaemia?

Background

Therapy-related acute monocytic leukemias in patients with plasma cell dyscrasias are infrequent.

Case presentation

We here present a case of a 60 year old female who developed an acute monocytic leukemia two years after the diagnosis of multiple myeloma. She was treated with an alkylating agent and bortezomib before undergoing a hematopoietic stem cell transplantation. She suffered of multiple severe infections until her immune system was adequately reconstituted. A year afterwards, she presented signs of deterioration unrelated to the MM, with pancytopenia. The bone marrow aspirate failed to show a prominent blast population. The diagnosis of AML was confirmed after a bone marrow biopsy.

Discussion

The development of acute leukaemia after treatment for multiple myeloma is a well characterized phenomenon. Most frequently, patients develop a myelomonocytic leukemia. Similarly, synchronous acute myeloid leukemias are myelomonocytic or myeloblastic. Rarely synchronous AMLs are monocytic. The development of such suggests a dysfunctional bone marrow microenvironment.

The Application of Single-Cell Technologies in Cardiovascular Research

Cardiovascular diseases (CVDs) are the leading cause of deaths in the world. The intricacies of the cellular composition and tissue microenvironment in heart and vasculature complicate the dissection of molecular mechanisms of CVDs. Over the past decade, the rapid development of single-cell omics technologies generated vast quantities of information at various biological levels, which have shed light on the cellular and molecular dynamics in cardiovascular development, homeostasis and diseases. Here, we summarize the latest single-cell omics techniques, and show how they have facilitated our understanding of cardiovascular biology. We also briefly discuss the clinical value and future outlook of single-cell applications in the field.

Neoteric Algorithm Using Cell Population Data (VCS Parameters) as a Rapid Screening Tool for Haematological Disorders

Hitherto, there has been no comprehensive study on the usefulness of cell population data (CPD) parameters as a screening tool in the discrimination of non-neoplastic and neoplastic haematological disorders. Hence, we aimed to develop an algorithm derived from CPD parameters to enable robust screening of neoplastic from non-neoplastic samples and subsequently to aid in differentiating various neoplastic haematological disorders. In this study, the CPD parameters from 245 subtypes of leukaemia and lymphoma were compared against 1103 non-neoplastic cases, and those CPD parameters that were vigorous discriminants were selected for algorithm development. We devised a novel algorithm: [(SD-V-NE*MN-UMALS-LY*SD-AL2-MO)/MN-C-NE] to distinguish neoplastic from non-neoplastic cases. Following that, the single parameter MN-AL2-NE was used as a discriminant to rule out reactive cases from neoplastic cases. We then assessed CPD parameters that were useful in delineating leukaemia subtypes as follows: AML (SD-MALS-NE and SD-UMALS-NE), APL (MN-V-NE and SD-V-MO), ALL (MN-MALS-NE and MN-LMALS-NE) and CLL (SD-C-MO). Prospective studies were carried out to validate the algorithm and single parameter, MN-AL2-NE. We propose these CPD parameter-based discriminant strategies to be adopted as an initial screening and flagging system in the preliminary evaluation of leukocyte morphology.

A non-invasive tool for early detection of acute leukemia in children using a paper-based optoelectronic nose based on an array of metallic nanoparticles

Volatile organic compounds (VOCs) in blood samples can be used as useful biomarkers to diagnose various human diseases. This study describes the potential of a paper-based sensor array for detecting leukemia using blood VOCs. Blood samples were collected from 59 new leukemia cases and 47 healthy cases as a control group. Each blood sample was divided into two parts; one for a laboratory test and the other was used in our study. Samples were mixed with heparin and then transferred to a sterile container, and a sensor was stacked on its cap. This sensor array contains 16 nanoparticles deposited on a sheet of hydrophobic paper in a 4 × 4 array format. Containers were stored in an oven at 60 °C for 4.5 h. Then, the image of sensors was recorded by a scanner and compared to the image before exposing the blood vapor. The sensor responses were subjected to different multivariate statistical methods to develop models that discriminate between control and leukemia samples. The interaction of nanoparticles with the volatile metabolome of blood caused aggregation and consequently changing in the color of nanoparticles. The color changes resulted in a specific pattern for blood samples with leukemia, which is different from those obtained from healthy specimens. The discrimination analysis was approved by pattern recognition methods such as principal component analysis with 97% accuracy. Among 59 patients, the mean age was 6.02 ± 4.55 years (range 1-16 y). The mean total response was 652.83 ± 117.02. The rock curve showed an accuracy of 96% for classifying patients from the control group. The logistic regression model showed that 93.6% of healthy and 93.2% of patients were classified correctly by using this method. These statistics agree with the classification results obtained by principal component analysis. For every 5000-unit increase in platelet count, the chance of leukemia decreased by 9%. Additionally, the chance of being categorized as a patient decreased by 10% for every 20-unit increase in total response. The electronic nose using VOC's of blood is a non-invasive and inexpensive tool for detecting new cases of leukemia with high sensitivity and specificity. Platelet count is an essential para-clinical parameter determining the total response of the sensors. Follow up studies with a larger sample size are warranted to elucidate its clinical applicability.

Utility of CD36 as a novel addition to the immunophenotypic signature of RAM-phenotype acute myeloid leukemia and study of its clinicopathological characteristics

INTRODUCTION

In 2016, Children Oncology Group (COG) described a new high-risk subtype of acute myeloid leukemia (AML) with a distinct immunophenotypic-signature, RAM-phenotype (RAM-AML). Data on clinical and laboratory features of RAM-AML are still limited to COG report only. Herein, we report the clinicopathological characteristics and detailed immunophenotypic features of RAM-AML patients. In COG report, 38% of RAM-AML belonged to acute megakaryoblastic leukemia (AMKL)-subtype. Hence, we further compared the immunophenotypic features RAM-AML with non-RAM-AMKL diagnosed during the same study period.

METHODS

We included RAM-AML and non-RAM AMKL patients diagnosed between January 2017 and December 2019. We studied their morphological, cytochemical, immunophenotyping, cytogenetic, and molecular characteristics. Mean fluorescent intensity (MFI) and expression-pattern of immunophenotypic markers of RAM-AML were compared with non-RAM AMKLs patients.

RESULTS

We identified 11 RAM-AML (1%) and 21 non-RAM AMKL (1.9%) patients in 1102 pediatric-AML patients. Seven of 11 (63.64%) patients belonged to FAB-M7-subtype. CD56, CD117, and CD33 demonstrated overexpression, whereas CD45 and CD38 showed under-expression in RAM-AML patients. CD36 was consistently negative in RAM-AML, whereas moderate-bright positive in non-RAM AMKLs patients (p < 0.0001). On principle component analysis, addition of CD36 enhanced the visual-separation between RAM-AML and non-RAM AMKL clusters. Cytogenetic and molecular studies did not show any recurrent abnormality; however, RNA-sequencing study revealed CBFA2T3-GLIS2-fusion in three of seven (42.8%) RAM-AML patients.

CONCLUSION

We report the clinicopathological characteristics and the detailed immunophenotypic profile in the world's second series of RAM-AML patients. We further report a novel finding of CD36-negative expression as an additional parameter to the multidimensional immunophenotypic signature of this entity.

Bacterial mock communities as standards for reproducible cytometric microbiome analysis

Flow cytometry has recently established itself as a tool to track short-term dynamics in microbial community assembly and link those dynamics with ecological parameters. However, instrumental configurations of commercial cytometers and variability introduced through differential handling of the cells and instruments frequently cause data set variability at the single-cell level. This is especially pronounced with microorganisms, which are in the lower range of optical resolution. Although alignment beads are valuable to generally minimize instrumental noise and align overall machine settings, an artificial microbial cytometric mock community (mCMC) is mandatory for validating lab workflows and enabling comparison of data between experiments, thus representing a necessary reference standard for the reproducible cytometric characterization of microbial communities, especially in long-term studies. In this study, the mock community consisted of two Gram-positive and two Gram-negative bacterial strains, which can be assembled with respective subsets of cells, including spores, in any selected ratio or concentration. The preparation of the four strains takes a maximum of 5 d, and the stains are storable with either PFA/ethanol fixation at -20 °C or drying at 4 °C for at least 6 months. Starting from this stock, an mCMC can be assembled within 1 h. Fluorescence staining methods are presented and representatively applied with two high-resolution cell sorters and three benchtop flow cytometers. Benchmarked data sets allow the use of bioinformatic evaluation procedures to decode community behavior or convey qualified cell sorting decisions for subsequent high-resolution sequencing or proteomic routines.

Acute undifferentiated leukemia: data on incidence and outcomes from a large population-based database

Acute undifferentiated leukemia (AUL) is rare and defined by the absence of bona fide myeloid and lymphoid markers. Little is known about its incidence, survival and optimal management in the recent time period. Based on a case observed in our clinic, we queried the Surveillance, Epidemiology, and End Results database between 2000 and 2016. A total of 1,888 cases of AUL were diagnosed (1.34 per million person-years). The incidence of AUL has significantly decreased over time. Compared to other acute leukemias, patients with AUL have the highest median age (74 years); in contrast to acute myeloid leukemia (AML, 65) and acute lymphoblastic leukemia (ALL, 12). Excluding patients with preexisting malignancies, 1,444 patients with AUL were analyzed for survival. Only 35% of AUL patients had received chemotherapy. Comparatively, 94% of ALL and 71% of AML cases received chemotherapy. Among AUL patients who received chemotherapy, the median survival was 12 months as opposed to 1 month in the group who did not receive chemotherapy (or unknown status). Among adults, AUL patients had the worst prognosis, with a median overall survival (OS) of 9 months, compared to 27 months in ALL and 13 months in AML. Among children, the median OS was superior for all three groups of leukemias, the OS of AUL patients being better than in AML and very similar to ALL. On multivariate analysis, older age and time period were associated with worse outcome. We describe here the largest series of cases with AUL published to date.

Fluorescence spectral detection of acute lymphoblastic leukemia (ALL) and acute myeloid leukemia (AML): A novel photodiagnosis strategy

Acute lymphoblastic leukemia (ALL) is a cancer of the lymphoid line of blood cell, showing a rapid growth of lymphoblastic immature cells. Acute myeloid leukemia (AML) is a cancer of the myeloid line of blood cells. Early diagnosis is crucial for the effective treatment of these patients. The current standard procedure of diagnosis is extensive blood count analysis, microscopic morphological investigations, bone marrow biopsy and flow-cytometer which are all time- consuming and expensive. Here we demonstrate the advantage a new technique for the diagnosis of ALL and AML based on the fluorescence spectra of blood plasma and RBCs samples from the above patients. Based on the 85 patients analyzed the results reveal that our approach could discriminate the two malignancies unambiguously from the normal with 88 % sensitivity and 80 % specificity. The abnormal decrease in the level of amino acid, tryptophan and coenzyme NADH and abnormal increase in the other amino acid, tyrosine and another coenzyme FAD, (both in comparison to the normal control) act as malignancy indicative biomarkers. Since the contrast parameter between the normal and malignant samples is four- fold, the potential for early detection of leukemia is high. The instrumentation and technique are new and simple; hence may have significant supplementary or complementary value with the existing diagnostic methods.

Clinical and Prognostic Significance of Cell Sensitivity to Chemotherapy Detected in vitro on Treatment Response and Survival of Leukemia Patients

Multidrug resistance (MDR) is a major challenge in leukemia treatment. The objective of this study was to identity predictors of MDR to allow for rapid and economical assessment of the efficacy of planned antitumor therapy for leukemia patients. The study included 113 patients with acute and chronic leukemias. Prior to antitumor therapy, we measured the sensitivity of tumor cells of patients to the panel of chemotherapeutic drugs, together with MDR1 mRNA and P-glycoprotein (P-gp) expression as one of the mechanisms of MDR, and compared these data with the response to therapy. The scales for leukemia patients according to therapy response, drug sensitivity of tumor cells, MDR1 mRNA and P-gp levels, and the presence of unfavorable immunological and cytogenetic markers were introduced for subsequent correlation analysis. We show that the drug resistance of tumor cells of leukemia patients estimated in vitro at diagnosis correlates with a poor response to chemotherapy and is usually combined with aberrant and immature immunological markers, cytogenetic abnormalities, and a high expression of MDR1 mRNA and P-gp. All together, these factors indicate unfavorable prognosis and low survival of leukemia patients. Thus, the sensitivity of tumor cells to chemotherapeutic drugs measured in vitro at diagnosis may have prognostic value for individual types of leukemia.

Immunophenotypic characterisation of morphologically diagnosed cases of Acute Myeloid Leukaemia (AML)

Objective:

To determine immunophenotypic pattern in newly diagnosed cases of acute myeloid leukaemia by flow cytometry and its correlation with morphological findings.

Methods:

This study was conducted at Haematology (Pathology) department, Army Medical College, in collaboration with Immunology Department Armed Forces Institute of Pathology, Rawalpindi from 16 November 2016 to 16 November 2017. One hundred and six patients of both genders and all age groups diagnosed as acute myeloid leukaemia were included in the study. Demographic data was noted. Complete blood counts, bone marrow examination and cytochemical stains were carried out and evaluated microscopically for blast percentage and morphology. Immunophenotyping was performed by flow cytometry using standard panel on peripheral blood or bone marrow samples. The surface and cytoplasmic antigens of interest were analysed and correlated with morphological findings.

Results:

The most commonly expressed antigens were CD13, CD33, CD45 and HLA-DR. Almost all blasts expressed CD45 with no remarkable difference among the subtypes of AML. The mean positivity for CD13 among all AML subtypes was 57% and for CD33 was 67%. Aberrant expression of CD7 and CD19 were expressed in 26.4% and 1.1% of all cases respectively. There was concordance rate of 90% between morphology and FCM in our study.

Conclusion:

Flow cytometric analysis of acute leukaemia done by a combination of patterns and intensity of antigen expression improves diagnostic yield in AML. CD13, CD33 and CD45 are the most frequently expressed antigens in AML. Our findings suggest a 90% concordance between morphology and flow cytometry. It is pertinent to conclude that flow cytometry results interpreted with morphology are complementary.

DNA Aptamers in the Detection of Leukemia Cells by the Thickness Shear Mode Acoustics Method

By using the thickness shear mode acoustics method (TSM) and single-molecule force spectroscopy (SMFS) we studied the interactions between DNA aptamers (sgc8c) specific to the protein tyrosine kinase 7 (PTK7), which is localized in the membranes of leukemia lymphoblastics (MOLT-4), and lymphocyte (Jurkat) cell lines, as well with PTK7-negative U266 myeloid leukemia cells. The TSM method allowed the development of a highly sensitive, label-free biosensor for the detection leukemia cells with a limit of detection of (195±20) cells/mL. SMFS approved the high selectivity of the sgc8c aptamers to the PTK7 receptors at the cell surface and allowed determining the binding probability of the aptamers to the PTK7 receptors at different cell lines.

Integrated automated particle tracking microfluidic enables high-throughput cell deformability cytometry for red cell disorders

Investigating individual red blood cells (RBCs) is critical to understanding hematologic diseases, as pathology often originates at the single-cell level. Many RBC disorders manifest in altered biophysical properties, such as deformability of RBCs. Due to limitations in current biophysical assays, there exists a need for high-throughput analysis of RBC deformability with single-cell resolution. To that end, we present a method that pairs a simple in vitro artificial microvasculature network system with an innovative MATLAB-based automated particle tracking program, allowing for high-throughput, single-cell deformability index (sDI) measurements of entire RBC populations. We apply our technology to quantify the sDI of RBCs from healthy volunteers, Sickle cell disease (SCD) patients, a transfusion-dependent beta thalassemia major patient, and in stored packed RBCs (pRBCs) that undergo storage lesion over 4 weeks. Moreover, our system can also measure cell size for each RBC, thereby enabling 2D analysis of cell deformability vs cell size with single cell resolution akin to flow cytometry. Our results demonstrate the clear existence of distinct biophysical RBC subpopulations with high interpatient variability in SCD as indicated by large magnitude skewness and kurtosis values of distribution, the "shifting" of sDI vs RBC size curves over transfusion cycles in beta thalassemia, and the appearance of low sDI RBC subpopulations within 4 days of pRBC storage. Overall, our system offers an inexpensive, convenient, and high-throughput method to gauge single RBC deformability and size for any RBC population and has the potential to aid in disease monitoring and transfusion guidelines for various RBC disorders.

Multiple myeloma secondary to acute lymphoblastic leukemia: A case report

RATIONALE

Acute lymphoblastic leukemia (ALL) secondary to multiple myeloma (MM) is rare. Here we report a rare case of secondary ALL transformed from MM.

PATIENT CONCERNS

A 64-year-old woman was diagnosed as MM IgG light chain type in 2001. She achieved complete remission after 2 cycles of therapy, and received maintenance therapy with thalidomide. The patient suffered from MM relapse in September 2011. Bone marrow examination showed that the percentage of primary lymphocytes was 59%, indicating ALL-L2 (Pre-B-ALL). The patient reached complete remission after 1 cycle of chemotherapy, and has been maintained for more than 6 years.

DIAGNOSES

Immunophenotyping analysis revealed that the abnormal cell population accounted for approximately 66% which expressed HLA-DR, CD4, CD22, CD33, CD34, and cCD79a. These results indicated acute B lymphoblastic leukemia. Chromosome presented 47, XX, +5, -7, +19. Leukemia fusion gene analysis demonstrated positive EVI1 and negative IgH and TCR gene rearrangement.

INTERVENTIONS

The patient accepted 1 cycle of VDCLP chemotherapy and reached complete remission, followed with consolidation therapies with VDCLP, MA, CAG and other chemotherapy regimens.

OUTCOMES

This patient has maintained CR1 of ALL for more than 6 years.

LESSONS

Even secondary lymphoblastic leukemia has been rarely reported in patients with MM, we still need perform bone marrow examination, flow cytology, and gene tests, especially during maintenance therapy.

Morphologic and immunophenotypic features of a case of acute monoblastic leukemia with unusual positivity for Glycophorin-A

Acute monoblastic leukemia (AMoL) is characterized by cells with highly undifferentiated morphology. Cytochemistry with non-specific esterases is negative in up to 20% of cases. Immunophenotyping by flow cytometry has an essential role in diagnosing such a subtype of leukemia and a multiparametric approach with a wide monoclonal antibody panel is necessary. We describe a case of AMoL with morphology resembling either plasma blasts or very immature erythroblasts. Diagnosis was made by alpha-naphtyl-acetate esterase staining and with immunophenotyping, which was made with a wide monoclonal antibody panel. Blasts were positive for monocytic markers. Most of leukemic cells, however, were positive for Glycophorin-A. The presence of Glycophorin-A, which is considered as a specific marker of the erythroid lineage, has never been reported previously in cases of AMoL. This peculiar immunophenotype might be interpreted as deriving from a common myelo-erythroid precursor undergone leukemic transformation.

Acute myeloid leukaemia

For several decades, few substantial therapeutic advances have been made for patients with acute myeloid leukaemia. However, since 2017 unprecedented growth has been seen in the number of drugs available for the treatment of acute myeloid leukaemia, with several new drugs receiving regulatory approval. In addition to advancing our therapeutic armamentarium, an increased understanding of the biology and genomic architecture of acute myeloid leukaemia has led to refined risk assessment of this disease, with consensus risk stratification guidelines now incorporating a growing number of recurrent molecular aberrations that aid in the selection of risk-adapted management strategies. Despite this promising recent progress, the outcomes of patients with acute myeloid leukaemia remain unsatisfactory, with more than half of patients ultimately dying from their disease. Enrolment of patients into clinical trials that evaluate novel drugs and rational combination therapies is imperative to continuing this progress and further improving the outcomes of patients with acute myeloid leukaemia.

Preliminary investigation on the abnormal mechanism of CD4+FOXP3+CD25high regulatory T cells in pediatric B-cell acute lymphoblastic leukemia

The current study aimed to investigate the changes and regulatory mechanism of cluster of differentiation (CD)4⁺CD25^high forkhead box protein 3 (Foxp3⁺) regulatory T cells (Tregs) in childhood B-cell acute lymphocytic leukemia (B-ALL). A total of 18 children with B-ALL and 15 age-matched healthy children were included. Reverse-transcription quantitative polymerase chain reaction was used to evaluate the mRNA levels of Foxp3, cytotoxic T-lymphocyte associated protein 4 (CTLA4), glucocorticoid-induced tumor necrosis factor receptor (GITR), lymphocyte activation gene 3 (LAG3), interleukin (IL)-2 receptor (R)β/γ, IL-6Rα/β, mothers against decapentaplegic homolog (Smad)3/4 and runt-related transcription factor (RUNX)1/3 in CD4-positive cells. The concentration of cytokines in plasma were measured using a cytometric bead array. Additionally, the proportion of CD4⁺CD25^highFoxp3⁺ Tregs and levels of associated proteins was analyzed using flow cytometry. The results demonstrated that the proportion of CD4⁺CD25^highFoxp3⁺ and expression of Foxp3 in children with B-ALL was significantly higher compared with healthy controls (P<0.05) and that transcription levels of CTLA4, GITR and LAG3 were also significantly elevated (P<0.05). Compared with healthy controls, the expression of IL-2Rα/β and its downstream molecule phosphorylated signal transducer and activator of transcription 5 (pSTAT5) in CD4-positive cells significantly increased (P<0.05); however, no significant difference of IL-2Rγ levels was identified between the two groups. Correlation analysis demonstrated a significant positive correlation between the expression of phosphorylated (p) signal transducer and activator of transcription factor (STAT)5 and CD4⁺CD25^highFoxp3⁺ Tregs in children with B-ALL (r=0.17; P<0.05). The plasma concentration of TGF-β, the expression of its receptor TGF-βRI/II and downstream molecules Smad3/4 were significantly upregulated in children with B-ALL (P<0.05), whereas the expression of RUNX1/3 was lower compared with healthy controls (P<0.05). Furthermore, the expression of Smad3 and RUNX1 was positively correlated with CD4⁺CD25^highFoxp3⁺ Tregs in children with B-ALL (r=0.87 and 0.60, respectively; P<0.05). Additionally, the expression of pSTAT3 in CD4-positive cells decreased significantly in pediatric patients with B-ALL when compared with healthy controls; however, plasma concentrations of IL-6 was significantly higher (P<0.05). Furthermore, a negative correlation was identified between pSTAT3 and CD4⁺CD25^highFoxp3⁺ Tregs in pediatric patients with B-ALL (r=-0.39; P<0.05). However, no significant differences in IL-6Rα/β expression were identified between the two groups. The results demonstrated that the excessive activation of IL-2/pSTAT5 and TGF-β/Smad signaling, and insufficiency of pSTAT3 may be correlated with increased CD4⁺CD25^highFoxp3⁺ Tregs in pediatric B-ALL.

Raman detection and identification of normal and leukemic hematopoietic cells

The analysis of leukocytes of peripheral blood is a crucial step in hematologic exams commonly used for disease diagnosis and, typically, requires molecular labelling. In addition, only a detailed, laborious phenotypic analysis allows identifying the presence and stage of specific pathologies such as leukemia. Most of the biochemical information is lost in the routine blood tests. In the present study, we tackle 2 important issues of label-free biochemical identification and classification of leukocytes using Raman spectroscopy (RS). First, we demonstrate that leukocyte subpopulations of lymphocytes (B, T and NK cells), monocytes and granulocytes can be identified by the unsupervised statistical approach of principal component analysis and classified by linear discriminant analysis with approximately 99% of accuracy. Second, we apply the same procedure to identify and discriminate normal B cells and transformed MN60 lymphocyte leukemic cell lines. In addition, we demonstrate that RS can be efficiently used for monitoring the cell response to low-dose chemotherapy treatment, experimentally eliciting the sensitivity to a dose-dependent cell response, which is of fundamental importance to determine the efficacy of any treatment. These results largely expand established Raman-based research protocols for label-free analysis of white blood cells, leukemic cells and chemotherapy treatment follow-up.

Current status and trends in the diagnostics of AML and MDS

Diagnostics of acute myeloid leukemia (AML) and myelodysplastic syndromes (MDS) have recently been experiencing extensive modifications regarding the incorporation of next-generation sequencing (NGS) strategies into established diagnostic algorithms, classification and risk stratification systems, and minimal residual disease (MRD) detection. Considering the increasing arsenal of targeted therapies (e.g. FLT3 or IDH1/IDH2 inhibitors) for AML, timely and comprehensive molecular mutation screening has arrived in daily practice. Next-generation flow strategies allow for immunophenotypic minimal residual disease (MRD) monitoring with very high sensitivity. At the same time, standard diagnostic tools such as cytomorphology or conventional cytogenetics remain cornerstones for the diagnostic workup of myeloid malignancies. Herein, we summarize the most recent advances and new trends for the diagnostics of AML and MDS, discuss the difficulties, which accompany the integration of these new methods and their results into daily routine, and aim to define the role hemato-oncologists may play in this new diagnostic era.

A Method for the Interpretation of Flow Cytometry Data Using Genetic Algorithms

Background:

Flow cytometry analysis is the method of choice for the differential diagnosis of hematologic disorders. It is typically performed by a trained hematopathologist through visual examination of bidimensional plots, making the analysis time-consuming and sometimes too subjective. Here, a pilot study applying genetic algorithms to flow cytometry data from normal and acute myeloid leukemia subjects is described.

Subjects and Methods:

Initially, Flow Cytometry Standard files from 316 normal and 43 acute myeloid leukemia subjects were transformed into multidimensional FITS image metafiles. Training was performed through introduction of FITS metafiles from 4 normal and 4 acute myeloid leukemia in the artificial intelligence system.

Results:

Two mathematical algorithms termed 018330 and 025886 were generated. When tested against a cohort of 312 normal and 39 acute myeloid leukemia subjects, both algorithms combined showed high discriminatory power with a receiver operating characteristic (ROC) curve of 0.912.

Conclusions:

The present results suggest that machine learning systems hold a great promise in the interpretation of hematological flow cytometry data.

Acute monocytic leukemia diagnosed by flow cytometry includes acute myeloid leukemias with weakly or faintly positive non-specific esterase staining

A diagnosis of acute monocytic leukemia (AML-M5) based on α-naphthyl butyrate esterase (α-NB) staining has some problems, because AML-M5 leukemic cells often show weak or faint positivity on α-NB staining. In these situations, some cases of AML-M5 tend to be misdiagnosed as AML-M0. Therefore, we evaluated the significance of weak or faint α-NB staining in AML-M5 diagnosed by flow cytometry (FCM). Nineteen AML cases in which leukemic cells were negative for naphthol AS-D chloroacetate esterase staining were studied. For FCM, we defined leukemic cells as having a monocytic nature when more than 10% of the leukemic cells were positive for at least one of the following antigens: CD4, CD11c, CD14, and CD64. The monocytic nature determined by FCM was consistent with positive or weak positivity on α-NB staining. Five of 6 cases in which leukemic cells exhibited faint positivity for α-NB staining could be diagnosed as AML-M5 by FCM, while negative α-NB staining was consistent with a diagnosis of AML-M0. These results suggest that AML-M5 should be taken into consideration even when leukemic cells are faintly positive for α-NB staining.

A simple fluorescence biosensing strategy for ultrasensitive detection of the BCR–ABL1 fusion gene based on a DNA machine and multiple primer-like rolling circle amplification

A one-step, rapid fluorescence biosensing method has been developed for ultrasensitive detection of BCR–ABL1 fusion gene based on a DNA machine and multiple primer-like rolling circle amplification.

Immunophenotypic aberrancies in acute lymphoblastic leukemia from 282 Iraqi patients

INTRODUCTION

The identification of aberrancies in leukemia-associated immunophenotype (LAIP) of acute lymphoblastic leukemia (ALL) is quite important in the assessment of minimal residual disease (MRD). This study, the first from Iraq, aimed to assess the frequency and patterns of LAIP among Iraqi patients with ALL, to establish future strategies for evaluating MRD.

METHODS

A total of 282 newly diagnosed Iraqi ALL cases were analyzed with six-parameter flow cytometry using a panel of 29 monoclonal antibodies.

RESULTS

Immunological subtyping revealed that 85.5% of cases were B-ALL and the remainder T-ALL. LAIP was detected in 97.1% of B-ALL, and in 26.8% of T-ALL. The asynchronous maturation-associated antigen patterns in B-ALL were CD10^strong+ /TdT^dim+ , CD38^dim+ /CD34⁺ , CD10^dim+ /CD34⁺ , CD10^strong /CD20^strong+ , CD20^strong+ /CD34^+, and CD45^dim+ /CD20^strong+ in 84.6%, while the cross-lineage myeloid expression was seen in 81.3% and aberrant T-cell antigen expression in 6.2%. For T-ALL, asynchronous maturation-associated antigen patterns included the following: CD1a⁺ /CD5⁺ /sCD3⁺ and CD34⁺ /sCD3⁺ in 12.2%. Myeloid and B-cell antigen expression were each identified in 7.3% of T-ALL. No significant differences in LAIP were found between children and adults.

CONCLUSION

The high rates and the patterns of LAIP particularly in Iraqi B-ALL patients may allow the development of more cost-effective strategies for MRD monitoring.

Role of new Immunophenotypic Markers on Prognostic and Overall Survival of Acute Myeloid Leukemia: a Systematic Review and Meta-Analysis

Despite technological advances, the prognosis and survival of acute myeloid leukemia (AML) adult patients remain low, compared with other hematologic malignancies. Some antigens detected by immunophenotyping may soon play a significant role in the pathophysiologic, prognostic, and overall survival (OS) rate of AML patients. Therefore, we conducted a systematic review and meta-analysis of PubMed, Scopus, Science Direct, Web of Science, and the Cochrane Library (using PRISMA guidelines). We analyzed 11 studies and 13 antigens, detected through the immunophenotyping of 639 patients. From them, twelve exhibited a negative impact with AML prognosis. The meta-analysis demonstrated a high expression of AML markers, which have been associated with a decrease in survival over 10 months (RR 2.55; IC 95%; 1.49-4.37) and over 20 months (RR 2.46; IC 95%; 1.75-3.45). Knowing that the expression of immunophenotypic markers, which are not used on a routine basis, might be able to influence disease behavior, looks promising. However, they have been associated with a poor prognosis as well as a decrease in survival. This may allow for different chemotherapeutical protocols, including future studies for new therapeutic targets.

Mixed-phenotype acute leukemia: suboptimal treatment when the 2008/2016 WHO classification is used

Background

Different criteria have been used to diagnose mixed-phenotype acute leukemia (MPAL), which has impacted the number of individuals diagnosed with this pathology. Better outcomes have been reported when using acute lymphoblastic leukemia (ALL)-type chemotherapy in the treatment of MPAL.

Methods

We compared the outcome of 4 groups of patients with MPAL. Group 1 included patients diagnosed using the 2008/2016 World Health Organization (WHO) classification; group 2 included patients diagnosed using the European Group for the Immunological Characterization of Leukemias (EGIL) criteria; group 3 included patients diagnosed using either the EGIL or the 2008/2016 WHO criteria; and group 4 was comprised of patients diagnosed with MPAL using the EGIL classification only.

Results

We found a significantly worse disease-free survival (groups 1-4) and overall survival (OS) (groups 2 and 3) when comparing MPAL patients to other acute leukemia (AL) patients. A significantly better OS was obtained in patients (groups 2-4) treated with ALL-type chemotherapy compared to acute myeloid leukemia (AML)-type regimens.

Conclusion

In light of these results, and because a trend (P=0.06) was found with regard to a better OS in group 4 when compared to other AL patients, an argument can be made that the 2008/2016 WHO classification is underpowered to diagnose all MPAL cases, potentially resulting in the suboptimal treatment of some individuals with AL.

Development-associated immunophenotypes reveal the heterogeneous and individualized early responses of adult B-acute lymphoblastic leukemia

B cell acute lymphoblastic leukemia (B-ALL) exhibits phenotypes reminiscent of normal stages of B-cell development. As demonstrated by flow cytometry, the immunophenotypes are able to determine the stages of B cell development. Multicolor flow cytometry (MFC) is more accurate at identifying cell populations. In this study, 9-color panels, including CD10, CD19, CD20, CD22, CD34, CD79a, CD179a, and IgM, which are sequentially expressed during B cell development, were designed to detect the leukemia cell subpopulations in adult B-ALL patients. In 23 patients at diagnosis, 192 heterogeneous subpopulations of leukemia cells were detected. Compared with their counterparts at diagnosis and after the 1st course of induction therapy, the responses of the subpopulations were also heterogeneous. In the CD10 population, the residual B cell subpopulations in the BCR/ABL patients were obviously reduced compared to those in the BCR/ABL patients. New subpopulations were detected in 22 of 23 patients and were primarily located in the CD34CD10 populations. Subpopulations of clonal evolution were heterogeneous after induction therapy. Our results suggest that the subpopulations in B-ALL patients should be dynamically monitored by development-associated immunophenotyping before, during, and after induction therapy and to predict the prognosis of the disease.

flowVS: channel-specific variance stabilization in flow cytometry

Background

Comparing phenotypes of heterogeneous cell populations from multiple biological conditions is at the heart of scientific discovery based on flow cytometry (FC). When the biological signal is measured by the average expression of a biomarker, standard statistical methods require that variance be approximately stabilized in populations to be compared. Since the mean and variance of a cell population are often correlated in fluorescence-based FC measurements, a preprocessing step is needed to stabilize the within-population variances.

Results

We present a variance-stabilization algorithm, called flowVS, that removes the mean-variance correlations from cell populations identified in each fluorescence channel. flowVS transforms each channel from all samples of a data set by the inverse hyperbolic sine (asinh) transformation. For each channel, the parameters of the transformation are optimally selected by Bartlett’s likelihood-ratio test so that the populations attain homogeneous variances. The optimum parameters are then used to transform the corresponding channels in every sample. flowVS is therefore an explicit variance-stabilization method that stabilizes within-population variances in each channel by evaluating the homoskedasticity of clusters with a likelihood-ratio test.

With two publicly available datasets, we show that flowVS removes the mean-variance dependence from raw FC data and makes the within-population variance relatively homogeneous. We demonstrate that alternative transformation techniques such as flowTrans, flowScape, logicle, and FCSTrans might not stabilize variance. Besides flow cytometry, flowVS can also be applied to stabilize variance in microarray data. With a publicly available data set we demonstrate that flowVS performs as well as the VSN software, a state-of-the-art approach developed for microarrays.

Conclusions

The homogeneity of variance in cell populations across FC samples is desirable when extracting features uniformly and comparing cell populations with different levels of marker expressions. The newly developed flowVS algorithm solves the variance-stabilization problem in FC and microarrays by optimally transforming data with the help of Bartlett’s likelihood-ratio test. On two publicly available FC datasets, flowVS stabilizes within-population variances more evenly than the available transformation and normalization techniques. flowVS-based variance stabilization can help in performing comparison and alignment of phenotypically identical cell populations across different samples. flowVS and the datasets used in this paper are publicly available in Bioconductor.

Automated Assessment of Disease Progression in Acute Myeloid Leukemia by Probabilistic Analysis of Flow Cytometry Data

OBJECTIVE

Flow cytometry (FC) is a widely acknowledged technology in diagnosis of acute myeloid leukemia (AML) and has been indispensable in determining progression of the disease. Although FC plays a key role as a posttherapy prognosticator and evaluator of therapeutic efficacy, the manual analysis of cytometry data is a barrier to optimization of reproducibility and objectivity. This study investigates the utility of our recently introduced nonparametric Bayesian framework in accurately predicting the direction of change in disease progression in AML patients using FC data.

METHODS

The highly flexible nonparametric Bayesian model based on the infinite mixture of infinite Gaussian mixtures is used for jointly modeling data from multiple FC samples to automatically identify functionally distinct cell populations and their local realizations. Phenotype vectors are obtained by characterizing each sample by the proportions of recovered cell populations, which are, in turn, used to predict the direction of change in disease progression for each patient.

RESULTS

We used 200 diseased and nondiseased immunophenotypic panels for training and tested the system with 36 additional AML cases collected at multiple time points. The proposed framework identified the change in direction of disease progression with accuracies of 90% (nine out of ten) for relapsing cases and 100% (26 out of 26) for the remaining cases.

CONCLUSIONS

We believe that these promising results are an important first step toward the development of automated predictive systems for disease monitoring and continuous response evaluation.

SIGNIFICANCE

Automated measurement and monitoring of therapeutic response is critical not only for objective evaluation of disease status prognosis but also for timely assessment of treatment strategies.

CD3D and PRKCQ work together to discriminate between B-cell and T-cell acute lymphoblastic leukemia

Different therapeutic methods have been developed for the B-cell and T-cell subtypes of acute lymphoblastic leukemia (ALL). The identification of molecular biomarkers that can accurately discriminate between B-cell and T-cell ALLs will facilitate the quick determination of therapeutic plans, as well as reveal the intrinsic mechanisms underlining the two different ALL subtypes. This study computationally screened the high-throughput transcriptome dataset for multiple candidate biomarkers and verified their discrimination abilities in an independent sample set using quantitative real-time polymerase chain reaction (PCR) technology. Both technologies suggest that the two genes CD3D and PKRCQ together provided a good model for classification of B-cell and T-cell ALLs, whereas the individual genes did not show consistent discrimination between the two ALL subtypes. Supplementary material is available at http://healthinformaticslab.org/supp/.

A reliable Raman-spectroscopy-based approach for diagnosis, classification and follow-up of B-cell acute lymphoblastic leukemia

Acute lymphoblastic leukemia type B (B-ALL) is a neoplastic disorder that shows high mortality rates due to immature lymphocyte B-cell proliferation. B-ALL diagnosis requires identification and classification of the leukemia cells. Here, we demonstrate the use of Raman spectroscopy to discriminate normal lymphocytic B-cells from three different B-leukemia transformed cell lines (i.e., RS4;11, REH, MN60 cells) based on their biochemical features. In combination with immunofluorescence and Western blotting, we show that these Raman markers reflect the relative changes in the potential biological markers from cell surface antigens, cytoplasmic proteins, and DNA content and correlate with the lymphoblastic B-cell maturation/differentiation stages. Our study demonstrates the potential of this technique for classification of B-leukemia cells into the different differentiation/maturation stages, as well as for the identification of key biochemical changes under chemotherapeutic treatments. Finally, preliminary results from clinical samples indicate high consistency of, and potential applications for, this Raman spectroscopy approach.

Current Strategies for the Detection of Minimal Residual Disease in Childhood Acute Lymphoblastic Leukemia

Acute lymphoblastic leukemia (ALL) is the most common cancer in children. Current treatment strategies for childhood ALL result in long-term remission for approximately 90% of patients. However, the therapeutic response is worse among those who relapse. Several risk stratification approaches based on clinical and biological aspects have been proposed to intensify treatment in patients with high risk of relapse and reduce toxicity on those with a greater probability of cure.

The detection of residual leukemic cells (minimal residual disease, MRD) is the most important prognostic factor to identify high-risk patients, allowing redefinition of chemotherapy. In the last decades, several standardized research protocols evaluated MRD using immunophenotyping by flow cytometry and/or real-time quantitative polymerase chain reaction at different time points during treatment. Both methods are highly sensitive (10⁻³ a 10⁻⁵), but expensive, complex, and, because of that, require qualified staff and frequently are restricted to reference centers.

The aim of this article was to review technical aspects of immunophenotyping by flow cytometry and real-time quantitative polymerase chain reaction to evaluate MRD in ALL.

Cellometer image cytometry as a complementary tool to flow cytometry for verifying gated cell populations

Traditionally, many cell-based assays that analyze cell populations and functionalities have been performed using flow cytometry. However, flow cytometers remain relatively expensive and require highly trained operators for routine maintenance and data analysis. Recently, an image cytometry system has been developed by Nexcelom Bioscience (Lawrence, MA, USA) for automated cell concentration and viability measurement using bright-field and fluorescent imaging methods. Image cytometry is analogous to flow cytometry in that gating operations can be performed on the cell population based on size and fluorescent intensity. In addition, the image cytometer is capable of capturing bright-field and fluorescent images, allowing for the measurement of cellular size and fluorescence intensity data. In this study, we labeled a population of cells with an enzymatic vitality stain (calcein-AM) and a cell viability dye (propidium iodide) and compared the data generated by flow and image cytometry. We report that measuring vitality and viability using the image cytometer is as effective as flow cytometric assays and allows for visual confirmation of the sample to exclude cellular debris. Image cytometry offers a direct method for performing fluorescent cell-based assays but also may be used as a complementary tool to flow cytometers for aiding the analysis of more complex samples.

Microfluidic cell surface antigen expression analysis using a single antibody type

A single-chip approach to capture and isolate cells based on differences in antigen expression.

ImmuSort, a database on gene plasticity and electronic sorting for immune cells

Gene expression is highly dynamic and plastic. We present a new immunological database, ImmuSort. Unlike other gene expression databases, ImmuSort provides a convenient way to view global differential gene expression data across thousands of experimental conditions in immune cells. It enables electronic sorting, which is a bioinformatics process to retrieve cell states associated with specific experimental conditions that are mainly based on gene expression intensity. A comparison of gene expression profiles reveals other applications, such as the evaluation of immune cell biomarkers and cell subsets, identification of cell specific and/or disease-associated genes or transcripts, comparison of gene expression in different transcript variants and probe set quality evaluation. A plasticity score is introduced to measure gene plasticity. Average rank and marker evaluation scores are used to evaluate biomarkers. The current version includes 31 human and 17 mouse immune cell groups, comprising 10,422 and 3,929 microarrays derived from public databases, respectively. A total of 20,283 human and 20,963 mouse genes are available to query in the database. Examples show the distinct advantages of the database. The database URL is http://202.85.212.211/Account/ImmuSort.html.