“Immuno‐flowFISH” for the Assessment of Cytogenetic Abnormalities in Chronic Lymphocytic Leukemia

Plasma Cell Enrichment and New Genomic Approaches in Multiple Myeloma: A Scoping Review

BACKGROUND

Multiple myeloma (MM) is a genetically heterogeneous disease where specific genetic abnormalities have a significant impact on a patient's prognosis. Diagnostic and prognostic tools like fluorescence in situ hybridization (FISH), PCR, microarrays, and next-generation sequencing (NGS) have transformed MM management. However, the effectiveness of these techniques is often limited by the low concentration of plasma cells in bone marrow samples, which makes enrichment methods necessary. This review aims to clarify how these techniques enhance the detection of genetic abnormalities, reduce false-negative results, and facilitate more precise risk stratification for MM patients.

CONTENT

Following Preferred Reporting Items for Systematic reviews and Meta-Analyses Extension for Scoping Review (PRISMA-ScR) guidelines, the literature on plasma cell separation methods used in genetic studies of MM was systematically identified and mapped. Searches were conducted in the Medline and Embase databases using a structured strategy, supplemented by manual searches on Google Scholar. Of 399 publications evaluated, 69 met the inclusion criteria; 37% utilized FISH and 19% demonstrated an increasing use of NGS. Plasma cell enrichment significantly improved diagnostic accuracy, increasing the detection rates of genetic abnormalities from 61% in non-enriched samples to 95.5% in enriched samples. While FISH remains the gold standard, emerging technologies such as NGS offer superior sensitivity and the ability to identify critical genetic alterations to refine molecular subtypes.

SUMMARY

Clinically significant genetic alterations are detected more frequently with plasma cell enrichment techniques, contributing to improved prognosis and treatment strategies for MM patients.

Imaging Flow Cytometric Identification of Chromosomal Defects in Paediatric Acute Lymphoblastic Leukaemia

Acute lymphoblastic leukaemia is the most common childhood malignancy that remains a leading cause of death in childhood. It may be characterised by multiple known recurrent genetic aberrations that inform prognosis, the most common being hyperdiploidy and t(12;21) ETV6::RUNX1. We aimed to assess the applicability of a new imaging flow cytometry methodology that incorporates cell morphology, immunophenotype, and fluorescence in situ hybridisation (FISH) to identify aneuploidy of chromosomes 4 and 21 and the translocation ETV6::RUNX1. We evaluated this new "immuno-flowFISH" platform on 39 cases of paediatric ALL of B-lineage known to have aneuploidy of chromosomes 4 and 21 and the translocation ETV6::RUNX1. After identifying the leukaemic population based on immunophenotype (i.e., expression of CD34, CD10, and CD19 antigens), we assessed for copy numbers of loci for the centromeres of chromosomes 4 and 21 and the ETV6 and RUNX1 regions using fluorophore-labelled DNA probes in more than 1000 cells per sample. Trisomy 4 and 21, tetrasomy 21, and translocations of ETV6::RUNX1, as well as gains and losses of ETV6 and RUNX1, could all be identified based on FISH spot counts and digital imagery. There was variability in clonal makeup in individual cases, suggesting the presence of sub-clones. Copy number alterations and translocations could be detected even when the cell population comprised less than 1% of cells and included cells with a mature B-cell phenotype, i.e., CD19-positive, lacking CD34 and CD10. In this proof-of-principle study of 39 cases, this sensitive and specific semi-automated high-throughput imaging flow cytometric immuno-flowFISH method has been able to show that alterations in ploidy and ETV6::RUNX1 could be detected in the 39 cases of paediatric ALL. This imaging flow cytometric FISH method has potential applications for diagnosis and monitoring disease and marrow regeneration (i.e., distinguishing residual ALL from regenerating haematogones) following chemotherapy.

Artificial intelligence reveals the predictions of hematological indexes in children with acute leukemia

Childhood leukemia is a prevalent form of pediatric cancer, with acute lymphoblastic leukemia (ALL) and acute myeloid leukemia (AML) being the primary manifestations. Timely treatment has significantly enhanced survival rates for children with acute leukemia. This study aimed to develop an early and comprehensive predictor for hematologic malignancies in children by analyzing nutritional biomarkers, key leukemia indicators, and granulocytes in their blood. Using a machine learning algorithm and ten indices, the blood samples of 826 children with ALL and 255 children with AML were compared to a control group of 200 healthy children. The study revealed notable differences, including higher indicators in boys compared to girls and significant variations in most biochemical indicators between leukemia patients and healthy children. Employing a random forest model resulted in an area under the curve (AUC) of 0.950 for predicting leukemia subtypes and an AUC of 0.909 for forecasting AML. This research introduces an efficient diagnostic tool for early screening of childhood blood cancers and underscores the potential of artificial intelligence in modern healthcare.

Multicolour and lineage-specific interphase chromosome Flow-FISH: method development and clinical validation

Flow cytometry can be applied in the detection of fluorescence in situ hybridisation (FISH) signals to efficiently analyse chromosomal aberrations. However, such interphase chromosome (IC) Flow-FISH protocols are currently limited to detecting a single colour. Furthermore, combining IC Flow-FISH with conventional multicolour flow cytometry is difficult because the DNA-denaturation step in FISH assay also disrupts cellular integrity and protein structures, precluding subsequent antigen-antibody binding and hindering concurrent labeling of surface antigens and FISH signals. We developed a working protocol for concurrent multicolour flow cytometry detection of nuclear IC FISH signals and cell surface markers. The protocol was validated by assaying sex chromosome content of blood cells, which was indicative of chimerism status in patients who had received sex-mismatched allogeneic haematopoietic stem cell transplants (allo-HSCT). The method was also adapted to detect trisomy 12 in chronic lymphocytic leukaemia (CLL) subjects. We first demonstrated the feasibility of this protocol in detecting multiple colours and concurrent nuclear and surface signals with high agreement. In clinical validation experiments, chimerism status was identified in clinical samples (n=56) using the optimised IC Flow-FISH method; the results tightly corresponded to those of conventional slide-based FISH (R2=0.9649 for XX cells and 0.9786 for XY cells). In samples from patients who received sex-mismatched allo-HSCT, individual chimeric statuses in different lineages could be clearly distinguished with high flexibility in gating strategies. Furthermore, in CLL samples with trisomy 12, this method could demonstrate that enriched trisomy 12 FISH signal was present in B cells rather than in T cells. Finally, by performing combined labelling of chromosome 12, X chromosome, and surface markers, we could detect rare residual recipient CLL cells with trisomy 12 after allo-HSCT. This adaptable protocol for multicolour and lineage-specific IC Flow-FISH advances the technique to allow for its potential application in various clinical contexts where conventional FISH assays are currently being utilised.

Imaging flow cytometric detection of del(17p) in bone marrow and circulating plasma cells in multiple myeloma

BACKGROUND

Detection of del(17p) in myeloma is generally performed by fluorescence in situ hybridization (FISH) on a slide with analysis of up to 200 nuclei. The small cell sample analyzed makes this a low precision test. We report the utility of an automated FISH method, called "immuno-flowFISH", to detect plasma cells with adverse prognostic risk del(17p) in bone marrow and blood samples of patients with myeloma.

METHODS

Bone marrow (n = 31) and blood (n = 19) samples from 35 patients with myeloma were analyzed using immuno-flowFISH. Plasma cells were identified by CD38/CD138-immunophenotypic gating and assessed for the 17p locus and centromere of chromosome 17. Cells were acquired on an AMNIS ImageStreamX MkII imaging flow cytometer using INSPIRE software.

RESULTS

Chromosome 17 abnormalities were identified in CD38/CD138-positive cells in bone marrow (6/31) and blood (4/19) samples when the percent plasma cell burden ranged from 0.03% to 100% of cells. Abnormalities could be identified in 14.5%-100% of plasma cells.

CONCLUSIONS

The "immuno-flowFISH" imaging flow cytometric method could detect del(17p) in plasma cells in both bone marrow and blood samples of myeloma patients. This method was also able to detect gains and losses of chromosome 17, which are also of prognostic significance. The lowest levels of 0.009% (bone marrow) and 0.001% (blood) for chromosome 17 abnormalities was below the detection limit of current FISH method. This method offers potential as a new means of identifying these prognostically important chromosomal defects, even when only rare cells are present and for serial disease monitoring.

Comparative analysis of feature-based ML and CNN for binucleated erythroblast quantification in myelodysplastic syndrome patients using imaging flow cytometry data

Myelodysplastic syndrome is primarily characterized by dysplasia in the bone marrow (BM), presenting a challenge in consistent morphology interpretation. Accurate diagnosis through traditional slide-based analysis is difficult, necessitating a standardized objective technique. Over the past two decades, imaging flow cytometry (IFC) has proven effective in combining image-based morphometric analyses with high-parameter phenotyping. We have previously demonstrated the effectiveness of combining IFC with a feature-based machine learning algorithm to accurately identify and quantify rare binucleated erythroblasts (BNEs) in dyserythropoietic BM cells. However, a feature-based workflow poses challenges requiring software-specific expertise. Here we employ a Convolutional Neural Network (CNN) algorithm for BNE identification and differentiation from doublets and cells with irregular nuclear morphology in IFC data. We demonstrate that this simplified AI workflow, coupled with a powerful CNN algorithm, achieves comparable BNE quantification accuracy to manual and feature-based analysis with substantial time savings, eliminating workflow complexity. This streamlined approach holds significant clinical value, enhancing IFC accessibility for routine diagnostic purposes.

IGH cytogenetic abnormalities can be detected in multiple myeloma by imaging flow cytometry

AIMS

Cytogenetic abnormalities involving the IGH gene are seen in up to 55% of patients with multiple myeloma. Current testing is performed manually by fluorescence in situ hybridisation (FISH) on purified plasma cells. We aimed to assess whether an automated imaging flow cytometric method that uses immunophenotypic cell identification, and does not require cell isolation, can identify IGH abnormalities.

METHODS

Aspirated bone marrow from 10 patients with multiple myeloma were studied. Plasma cells were identified by CD38 and CD138 coexpression and assessed with FISH probes for numerical or structural abnormalities of IGH. Thousands of cells were acquired on an imaging flow cytometer and numerical data and digital images were analysed.

RESULTS

Up to 30 000 cells were acquired and IGH chromosomal abnormalities were detected in 5 of the 10 marrow samples. FISH signal patterns seen included fused IGH signals for IGH/FGFR3 and IGH/MYEOV, indicating t(4;14) and t(11;14), respectively. In addition, three IGH signals were identified, indicating trisomy 14 or translocation with an alternate chromosome. The lowest limit of detection of an IGH abnormality was in 0.05% of all cells.

CONCLUSIONS

This automated high-throughput immuno-flowFISH method was able to identify translocations and trisomy involving the IGH gene in plasma cells in multiple myeloma. Thousands of cells were analysed and without prior cell isolation. The inclusion of positive plasma cell identification based on immunophenotype led to a lowest detection level of 0.05% marrow cells. This imaging flow cytometric FISH method offers the prospect of increased precision of detection of critical genetic lesions involving IGH and other chromosomal defects in multiple myeloma.

Imaging flow cytometry-based multiplex FISH for three IGH translocations in multiple myeloma

Three types of chromosomal translocations, t(4;14)(p16;q32), t(14;16)(q32;q23), and t(11;14)(q13;q32), are associated with prognosis and the decision making of therapeutic strategy for multiple myeloma (MM). In this study, we developed a new diagnostic modality of the multiplex FISH in immunophenotyped cells in suspension (Immunophenotyped-Suspension-Multiplex (ISM)-FISH). For the ISM-FISH, we first subject cells in suspension to the immunostaining by anti-CD138 antibody and, then, to the hybridization with four different FISH probes for genes of IGH, FGFR3, MAF, and CCND1 tagged by different fluorescence in suspension. Then, cells are analyzed by the imaging flow cytometry MI-1000 combined with the FISH spot counting tool. By this system of the ISM-FISH, we can simultaneously examine the three chromosomal translocations, i.e, t(4;14), t(14;16), and t(11;14), in CD138-positive tumor cells in more than 2.5 × 104 nucleated cells with the sensitivity at least up to 1%, possibly up to 0.1%. The experiments on bone marrow nucleated cells (BMNCs) from 70 patients with MM or monoclonal gammopathy of undetermined significance demonstrated the promising qualitative diagnostic ability in detecting t(11;14), t(4;14), and t(14;16) of our ISM-FISH, which was more sensitive compared with standard double-color (DC) FISH examining 200 interphase cells with its best sensitivity up to 1.0%. Moreover, the ISM-FISH showed a positive concordance of 96.6% and negative concordance of 98.8% with standard DC-FISH examining 1000 interphase cells. In conclusion, the ISM-FISH is a rapid and reliable diagnostic tool for the simultaneous examination of three critically important IGH translocations, which may promote risk-adapted individualized therapy in MM.

Assessing chromosomal abnormalities in leukemias by imaging flow cytometry

Chromosome analysis assists in the diagnostic classification and prognostication of leukemias. It is typically performed by karyotyping or fluorescent in situ hybridization (FISH) on glass slides. Flow cytometry offers an alternative high throughput automated methodology to analyze chromosomal content. With the advent of imaging flow cytometers, specific chromosomes and regions of interest can be identified and enumerated within specific cell types. The inclusion of immunophenotyping increases the specificity of this technique to ensure only the leukemic cell is analyzed. With many thousands of cells acquired, and neoplastic cells of interest identified by antigen expression, this technology has expanded the role of flow cytometry for cytogenomics in oncology. Applications to date have focused on hematological malignancies to detect aneuploidy (chromosome gains and losses) and structural defects (e.g., deletions; translocations) of diagnostic or prognostic significance at the time of diagnosis. With limits of detection of 1 cytogenetically abnormal cell in 100,000, also makes this new flow cytometry protocol eminently suitable for monitoring low level disease, detecting clonal evolution after therapy and identifying circulating tumor cells. The technique is equally applicable to solid tumors, many of which have chromosomal aberrations, with selection of appropriate immunophenotypic markers and FISH probes.

"Immuno-FlowFISH": Applications for Chronic Lymphocytic Leukemia

Imaging flow cytometry has the capacity to bridge the gap that currently exists between the diagnostic tests that detect important phenotypic and genetic changes in the clinical assessment of leukemia and other hematological malignancies or blood-based disorders. We have developed an "Immuno-flowFISH" method that leverages the quantitative and multi-parametric power of imaging flow cytometry to push the limits of single-cell analysis. Immuno-flowFISH has been fully optimized to detect clinically significant numerical and structural chromosomal abnormalities (i.e., trisomy 12 and del(17p)) within clonal CD19/CD5+ CD3- Chronic Lymphocytic Leukemia (CLL) cells in a single test. This integrated methodology has greater accuracy and precision than standard fluorescence in situ hybridization (FISH). We have detailed this immuno-flowFISH application with a carefully catalogued workflow, technical instructions, and a repertoire of quality control considerations to supplement the analysis of CLL. This next-generation imaging flow cytometry protocol may provide unique advancements and opportunities in the holistic cellular assessment of disease for both research and clinical laboratory settings.

Consequences of chromosome gain: A new view on trisomy syndromes

Chromosome gains are detrimental for the development of the human embryo. As such, autosomal trisomies almost always result in spontaneous abortion, and the rare embryos surviving until live birth suffer from a plethora of pathological defects. There is no treatment currently available to ameliorate the consequences of trisomies, such as Down syndrome (trisomy of chromosome 21). Identifying the source of the phenotypes observed in cells with extra chromosomes is crucial for understanding the underlying molecular causes of trisomy syndromes. Although increased expression of the genes localized on the extra chromosome triggers several pathological phenotypes, an alternative model suggests that global, aneuploidy-associated changes in cellular physiology also contribute to the pathology. Here, we compare the molecular consequences of trisomy syndromes in vivo against engineered cell lines carrying various chromosome gains in vitro. We point out several phenotypes that are shared by variable trisomies and, therefore, might be caused by the presence of an extra chromosome per se, independent of its identity. This alternative view may provide useful insights for understanding Down syndrome pathology and open additional opportunities for diagnostics and treatments.

Detection and Characterization of Circulating Tumor Cells Using Imaging Flow Cytometry—A Perspective Study

Simple Summary

Liquid biopsy is non-invasive approach used to prognose and monitor tumor progression based on the detection and examination of metastasis-related events found in the patients’ blood (such as circulating tumor cells (CTCs), extracellular vesicles, and circulating nucleic acids). Different ultrasensitive techniques are applied to study those events and the biology of tumor dissemination, which in the future might complement standard diagnostics. Here, we suggest that CTCs analysis could be improved by the usage of imaging flow cytometry, combining advantages of both standard flow cytometry (high-scale analysis) and microscopy (high resolution) to investigate detailed features of those cells. From this perspective, we discuss the potential of this technology in the CTC field and present representative images of CTCs from breast and prostate cancer patients analyzed with this method.

Abstract

Tumor dissemination is one of the most-investigated steps of tumor progression, which in recent decades led to the rapid development of liquid biopsy aiming to analyze circulating tumor cells (CTCs), extracellular vesicles (EVs), and circulating nucleic acids in order to precisely diagnose and monitor cancer patients. Flow cytometry was considered as a method to detect CTCs; however, due to the lack of verification of the investigated cells’ identity, this method failed to reach clinical utility. Meanwhile, imaging flow cytometry combining the sensitivity and high throughput of flow cytometry and image-based detailed analysis through a high-resolution microscope might open a new avenue in CTC technologies and provide an open-platform system alternative to CellSearch^®, which is still the only gold standard in this field. Hereby, we shortly review the studies on the usage of flow cytometry in CTC identification and present our own representative images of CTCs envisioned by imaging flow cytometry providing rationale that this novel technology might be a good tool for studying tumor dissemination, and, if combined with a high CTC yield enrichment method, could upgrade CTC-based diagnostics.

Deep imaging flow cytometry

Imaging flow cytometry (IFC) has become a powerful tool for diverse biomedical applications by virtue of its ability to image single cells in a high-throughput manner. However, there remains a challenge posed by the fundamental trade-off between throughput, sensitivity, and spatial resolution. Here we present deep-learning-enhanced imaging flow cytometry (dIFC) that circumvents this trade-off by implementing an image restoration algorithm on a virtual-freezing fluorescence imaging (VIFFI) flow cytometry platform, enabling higher throughput without sacrificing sensitivity and spatial resolution. A key component of dIFC is a high-resolution (HR) image generator that synthesizes "virtual" HR images from the corresponding low-resolution (LR) images acquired with a low-magnification lens (10×/0.4-NA). For IFC, a low-magnification lens is favorable because of reduced image blur of cells flowing at a higher speed, which allows higher throughput. We trained and developed the HR image generator with an architecture containing two generative adversarial networks (GANs). Furthermore, we developed dIFC as a method by combining the trained generator and IFC. We characterized dIFC using Chlamydomonas reinhardtii cell images, fluorescence in situ hybridization (FISH) images of Jurkat cells, and Saccharomyces cerevisiae (budding yeast) cell images, showing high similarities of dIFC images to images obtained with a high-magnification lens (40×/0.95-NA), at a high flow speed of 2 m s-1. We lastly employed dIFC to show enhancements in the accuracy of FISH-spot counting and neck-width measurement of budding yeast cells. These results pave the way for statistical analysis of cells with high-dimensional spatial information.

Imaging flow cytometry reveals a subset of TdT negative T-ALL blasts with very low forward scatter on conventional flow cytometry

BACKGROUND

Studies in T-cell acute lymphoblastic leukemia (T-ALL) have shown that leukemic blast populations may display immunophenotypic heterogeneity. In the clinical setting, evaluation of measurable residual disease during treatment and follow-up is highly dependent on knowledge of the diversity of blast subsets. Here, we set out to evaluate whether variation in expression of the blast marker, TdT, in T-ALL blasts could correspond to differences in morphometric features.

METHODS

We investigated diagnostic bone marrow samples from six individual T-ALL patients run in parallel on imaging flow cytometry (IFC) and conventional flow cytometry (CFC).

RESULTS

Guided by the imagery available in IFC, we identified distinct TdT^neg and TdT^pos subpopulations with apparent differences in internal complexity. As TdT^neg blasts predominantly displayed very low forward scatter (FSC) on CFC, these subsets were initially excluded from routine analysis as debris, elements of small diameter, apoptotic, and/or dead cells. However, IFC-based morphometric analyses demonstrated that cell size and shape of TdT^neg blasts were comparable to the TdT^pos cells and without morphometric apoptotic hallmarks, supporting that the TdT^neg subpopulation corresponded to T-ALL blasts. Fluorescence in situ hybridization analyses substantiated the clinical relevance of TdT^neg FSC^very-low cells by retrieving known diagnostic cytogenetic abnormalities at comparable frequencies in purified TdT^neg FSC^very-low and TdT^pos FSC^int subsets.

CONCLUSION

We highlight this finding as knowledge of phenotypic heterogeneity is of crucial importance in the clinical setting for delineation and quantification of blast subpopulations of potential biological relevance. We argue that the IFC imagery may allow for visual verification and improvement of applied gating strategies.

Multi-probe FISH Analysis of Immunophenotyped Chronic Lymphocytic Leukemia by Imaging Flow Cytometry

Imaging flow cytometry is an automated method that enables cells and fluorescent signals to be visualized and quantified. Here, we describe a new imaging flow cytometry method whereby fluorescence in situ hybridization (FISH) is integrated with cell phenotyping. The method, called "immuno-flowFISH," provides an exciting new dimension for the analysis of genomic changes in cytological samples (e.g., blood, bone marrow). Cells are analyzed in suspension without any requirement for prior cell isolation or separation. Multiple antibodies and FISH probes, each with a unique fluorophore, can be added and many thousands of cells analyzed. Specific cell populations are identified by their antigenic profile and then analyzed for the presence of chromosomal defects. Immuno-flowFISH was applied to the assessment of chronic lymphocytic leukemia (CLL), a mature B-cell neoplasm where chromosomal abnormalities predict prognosis and treatment requirements. This integrated immunophenotyping and multi-probe FISH strategy could detect both structural and numerical chromosomal changes involving chromosomes 12 and 17 in CLL cells. Given that many thousands of cells were analyzed and the leukemic cells were positively identified by their immunophenotype, this multi-probe method adds precision to the cytogenomic analysis of CLL. © 2021 Wiley Periodicals LLC.

Analysis of human chromosomes by imaging flow cytometry

Chromosomal analysis is traditionally performed by karyotyping on metaphase spreads, or by fluorescent in situ hybridization (FISH) on interphase cells or metaphase spreads. Flow cytometry was introduced as a new method to analyze chromosomes number (ploidy) and structure (telomere length) in the 1970s with data interpretation largely based on fluorescence intensity. This technology has had little uptake for human cytogenetic applications primarily due to analytical challenges. The introduction of imaging flow cytometry, with the addition of digital images to standard multi-parametric flow cytometry quantitative tools, has added a new dimension. The ability to visualize the chromosomes and FISH signals overcomes the inherent difficulties when the data is restricted to fluorescence intensity. This field is now moving forward with methods being developed to assess chromosome number and structure in whole cells (normal and malignant) in suspension. A recent advance has been the inclusion of immunophenotyping such that antigen expression can be used to identify specific cells of interest for specific chromosomes and their abnormalities. This capability has been illustrated in blood cancers, such as chronic lymphocytic leukemia and plasma cell myeloma. The high sensitivity and specificity achievable highlights the potential imaging flow cytometry has for cytogenomic applications (i.e., diagnosis and disease monitoring). This review introduces and describes the development, current status, and applications of imaging flow cytometry for chromosomal analysis of human chromosomes.

Interphase fluorescence in situ hybridization analysis of CD19-selected cells: Utility in detecting disease in post-therapy samples of B-cell neoplasms

Context

The detection of low‐level persistent or relapsed B‐cell neoplasms, particularly post‐therapy, can be challenging, often requiring multiple testing modalities.

Objective

Here we investigate the utility of CD19‐based selection of neoplastic B‐cells (CD19S) as an enrichment strategy to improve the detection rate of cytogenetic abnormalities in post‐therapy samples of B‐cell neoplasms, especially those with low‐level disease.

Design

In a cohort largely comprised of post‐therapy B‐ALL and CLL samples, we performed fluorescence in situ hybridization (FISH) analysis on CD19‐selected cells (CD19S FISH) in 128 specimens from 88 patients, and on non‐selected cells (NS FISH) in a subset of cases. The FISH findings were compared with the concurrent flow cytometry (FC) results in all samples and molecular analysis in a subset.

Results

CD19S FISH was able to detect cytogenetic aberrations in 86.0% of post‐therapy samples with evidence of disease as determined by routine or MRD FC, compared to 59.1% of samples by NS FISH. CD19S FISH detected significantly higher percentages of positive cells compared to NS FISH (p < 0.001). Importantly, CD19S FISH enabled the detection of emergent subclones (clonal evolution) associated with poor prognosis.

Conclusions

CD19S FISH can be useful in daily diagnostic practice. Compared to NS FISH, CD19S FISH is quantitatively and qualitatively superior for the detection of cytogenetic aberrations in B‐cell neoplasms, which are important for risk stratification and optimal management of patients with B‐cell neoplasms, especially in the relapsed setting. Although CD19S FISH has a diagnostic sensitivity inferior to that of MRD FC, the sensitivity of this modality is comparable to routine FC for the evaluation of low‐level disease in the post‐therapy setting. Moreover, CD19S samples are invaluable for additional molecular and genetic analyses.

Exploring dyserythropoiesis in patients with myelodysplastic syndrome by imaging flow cytometry and machine-learning assisted morphometrics

BACKGROUND

The hallmark of myelodysplastic syndrome (MDS) remains dysplasia in the bone marrow (BM). However, diagnosing MDS may be challenging and subject to inter-observer variability. Thus, there is an unmet need for novel objective, standardized and reproducible methods for evaluating dysplasia. Imaging flow cytometry (IFC) offers combined analyses of phenotypic and image-based morphometric parameters, for example, cell size and nuclearity. Hence, we hypothesized IFC to be a useful tool in MDS diagnostics.

METHODS

Using a different-from-normal approach, we investigated dyserythropoiesis by quantifying morphometric features in a median of 5953 erythroblasts (range: 489-68,503) from 14 MDS patients, 11 healthy donors, 6 non-MDS controls with increased erythropoiesis, and 6 patients with cytopenia.

RESULTS

First, we morphometrically confirmed normal erythroid maturation, as immunophenotypically defined erythroid precursors could be sequenced by significantly decreasing cell-, nuclear- and cytoplasm area. In MDS samples, we demonstrated cell size enlargement and increased fractions of macronormoblasts in late-stage erythroblasts (both p < .0001). Interestingly, cytopenic controls with high-risk mutational patterns displayed highly aberrant cell size morphometrics. Furthermore, assisted by machine learning algorithms, we reliably identified and enumerated true binucleated erythroblasts at a significantly higher frequency in two out of three erythroblast maturation stages in MDS patients compared to normal BM (both p = .0001).

CONCLUSION

We demonstrate proof-of-concept results of the applicability of automated IFC-based techniques to study and quantify morphometric changes in dyserythropoietic BM cells. We propose that IFC holds great promise as a powerful and objective tool in the complex setting of MDS diagnostics with the potential for minimizing inter-observer variability.