Single-cell sequencing in hematology

Measurable (Minimal) Residual Disease in Myelodysplastic Neoplasms (MDS): Current State and Perspectives

Myelodysplastic Neoplasms (MDS) have been traditionally studied through the assessment of blood counts, cytogenetics, and morphology. In recent years, the introduction of molecular assays has improved our ability to diagnose MDS. The role of Measurable (minimal) Residual Disease (MRD) in MDS is evolving, and molecular and flow cytometry techniques have been used in several studies. In this review, we will highlight the evolving concept of MRD in MDS, outline the various techniques utilized, and provide an overview of the studies reporting MRD and the correlation with outcomes.

Advances in single-cell RNA sequencing and its applications in cancer research

Cancers are a group of heterogeneous diseases characterized by the acquisition of functional capabilities during the transition from a normal to a neoplastic state. Powerful experimental and computational tools can be applied to elucidate the mechanisms of occurrence, progression, metastasis, and drug resistance; however, challenges remain. Bulk RNA sequencing techniques only reflect the average gene expression in a sample, making it difficult to understand tumor heterogeneity and the tumor microenvironment. The emergence and development of single-cell RNA sequencing (scRNA-seq) technologies have provided opportunities to understand subtle changes in tumor biology by identifying distinct cell subpopulations, dissecting the tumor microenvironment, and characterizing cellular genomic mutations. Recently, scRNA-seq technology has been increasingly used in cancer studies to explore tumor heterogeneity and the tumor microenvironment, which has increased the understanding of tumorigenesis and evolution. This review summarizes the basic processes and development of scRNA-seq technologies and their increasing applications in cancer research and clinical practice.

Single-cell analysis of acute lymphoblastic and lineage-ambiguous leukemia: approaches and molecular insights

Despite recent progress in identifying the genetic drivers of acute lymphoblastic leukemia (ALL), prognosis remains poor for those individuals who experience disease recurrence. Moreover, acute leukemias of ambiguous lineage lack a biologically informed framework to guide classification and therapy. These needs have driven the adoption of multiple complementary single-cell sequencing approaches to explore key issues in the biology of these leukemias, including cell of origin, developmental hierarchy and ontogeny, and the molecular heterogeneity driving pathogenesis, progression, and therapeutic responsiveness. There are multiple single-cell techniques for profiling a specific modality, including RNA, DNA, chromatin accessibility and methylation; and an expanding range of approaches for simultaneous analysis of multiple modalities. Single-cell sequencing approaches have also enabled characterization of cell-intrinsic and -extrinsic features of ALL biology. In this review we describe these approaches and highlight the extensive heterogeneity that underpins ALL gene expression, cellular differentiation, and clonal architecture throughout disease pathogenesis and treatment resistance. In addition, we discuss the importance of the dynamic interactions that occur between leukemia cells and the nonleukemia microenvironment. We discuss potential opportunities and limitations of single-cell sequencing for the study of ALL biology and treatment responsiveness.

Single-cell RNA sequencing reveals the role of cell heterogeneity in the sex difference in primary hyperparathyroidism

OBJECTIVE

To explore the difference in parathyroid tissue-derived cells between male and female PHPT patients.

METHODS

Resected parathyroid tissues were collected from PHPT patients of both sexes. Single cells were isolated and sequenced for RNA expression profiles. The cell sequencing data were annotated by cell type, followed by population analysis, functional analysis, pathway analysis, cell communication analysis, differential gene expression analysis, and pseudotime trajectory analysis. The subcluster analyses were also performed in the parathyroid cells.

RESULTS

No substantial difference in the cell population, function, or communication is found between the two sexes. The interferon-a response, oxidative phosphorylation, and reactive oxygen species pathways are up-regulated in females than in male patients, mainly contributed by fibroblast cells, endothelial cells, parathyroid cells, and myeloid cells, which also have significantly more up-regulated pathways and cellular interactions than the other three cell types. The subcluster analysis of parathyroid cells identified five subpopulations: SPARCL1-OC and ISG15-OC are predominant in females, while more S100A13-PCC and PTHLH-OC are found in males. The cellular functions are also elevated in females compared with males. Cells from female patients show a higher expression level of parathyroid hormone (PTH) but a lower expression level of parathyroid hormone-like hormone (PTHLH). The cell pseudotime trajectory and pathway analyses show that the oxyphil cells may be more mature and functionally active than the chief cells in both sexes.

CONCLUSION

These findings suggest that the sex difference in PHPT may be caused by the differentially expressed genes and activated pathways in different cell types in the parathyroid tissue. The heterogeneity of parathyroid cell subpopulations, especially in oxyphil cells, may be associated with the sex differences in PHPT pathogenesis.

Flow Cytometric Identification of Hematopoietic and Leukemic Blast Cells for Tailored Clinical Follow-Up of Acute Myeloid Leukemia

Acute myeloid leukemia (AML) is a myeloid malignancy that is characterized by the accumulation of leukemic blast cells, which originate from hematopoietic stem cells that have undergone leukemic transformation and/or are more mature progenitors that have gained stemness features. Currently, no consensus exists for the flow cytometric identification of normal blast cells and their leukemic counterparts by their antigenic expression profile. Differentiating between the benign cells and the malignant cells is crucial for the further deployment of immunophenotype panels for the clinical follow-up of AML patients. This review provides an overview of immunophenotypic markers that allow the identification of leukemic blast cells in the bone marrow with multiparameter flow cytometry. This technique allows the identification of hematopoietic blast cells at the level of maturing cells by their antigen expression profile. While aberrant antigen expression of a single immunophenotypic marker cell cannot be utilized in order to differentiate leukemic blast cells from normal blast cells, combinations of multiple immunophenotypic markers can enable the distinction of normal and leukemic blast cells. The identification of these markers has provided new perspectives for tailored clinical follow-up, including therapy management, diagnostics, and prognostic purposes. The immunophenotypic marker panels, however, should be developed by carefully considering the variable antigen marker expression profile of individual patients.

ABC portal: a single-cell database and web server for blood cells

ABC portal (http://abc.sklehabc.com) is a database and web portal containing 198 single-cell transcriptomic datasets of development, differentiation and disorder of blood/immune cells. All the datasets were re-annotated with a manually curated and unified single-cell reference, especially for the haematopoietic stem and progenitor cells. ABC portal provides web-based interactive analysis modules, especially a comprehensive cell-cell communication analysis and disease-related gene signature analysis. Importantly, ABC portal allows customized sample selection based on a combination of several metadata for downstream analysis and comparison analysis across datasets. ABC portal also allows users to select multiple cell types for analysis in the modules. Together, ABC portal provides an interactive interface of single-cell data exploration and re-analysis with customized analysis modules for the researchers and clinicians, and will facilitate understanding of haematopoiesis and blood/immune disorders.

Clonal Evolution at First Sight: A Combined Visualization of Diverse Diagnostic Methods Improves Understanding of Leukemic Progression

Patients with myeloid neoplasia are classified by the WHO classification systems. Besides clinical and hematological criteria, cytogenetic and molecular genetic alterations highly impact treatment stratification. In routine diagnostics, a combination of methods is used to decipher different types of genetic variants. Eight patients were comprehensively analyzed using karyotyping, fluorescence in situ hybridization, array-CGH and a custom NGS panel. Clonal evolution was reconstructed manually, integrating all mutational information on single nucleotide variants (SNVs), insertions and deletions (indels), structural variants and copy number variants (CNVs). To allow a correct integration, we differentiate between three scenarios: 1) CNV occurring prior to the SNV/indel, but in the same cells. 2) SNV/indel occurring prior to the CNV, but in the same cells. 3) SNV/indel and CNV existing in parallel, independent of each other. Applying this bioinformatics approach, we reconstructed clonal evolution for all patients. This generalizable approach offers the possibility to integrate various data to analyze identification of driver and passenger mutations as well as possible targets for personalized medicine approaches. Furthermore, this model can be used to identify markers to assess the minimal residual disease.

Computational Reconstruction of Clonal Hierarchies From Bulk Sequencing Data of Acute Myeloid Leukemia Samples

Acute myeloid leukemia is an aggressive cancer of the blood forming system. The malignant cell population is composed of multiple clones that evolve over time. Clonal data reflect the mechanisms governing treatment response and relapse. Single cell sequencing provides most direct insights into the clonal composition of the leukemic cells, however it is still not routinely available in clinical practice. In this work we develop a computational algorithm that allows identifying all clonal hierarchies that are compatible with bulk variant allele frequencies measured in a patient sample. The clonal hierarchies represent descendance relations between the different clones and reveal the order in which mutations have been acquired. The proposed computational approach is tested using single cell sequencing data that allow comparing the outcome of the algorithm with the true structure of the clonal hierarchy. We investigate which problems occur during reconstruction of clonal hierarchies from bulk sequencing data. Our results suggest that in many cases only a small number of possible hierarchies fits the bulk data. This implies that bulk sequencing data can be used to obtain insights in clonal evolution.

The potential of proliferative and apoptotic parameters in clinical flow cytometry of myeloid malignancies

Standardization of the detection and quantification of leukocyte differentiation markers by the EuroFlow Consortium has led to a major step forward in the integration of flow cytometry into classification of leukemia and lymphoma. In our opinion, this now enables introduction of markers for more dynamic parameters, such as proliferative and (anti)apoptotic markers, which have proven their value in the field of histopathology in the diagnostic process of solid tumors and lymphoma. Although use of proliferative and (anti)apoptotic markers as objective parameters in the diagnostic process of myeloid malignancies was studied in the past decades, this did not result in the incorporation of these biomarkers into clinical diagnosis. This review addresses the potential of these markers for implementation in the current, state-of-the-art multiparameter analysis of myeloid malignancies. The reviewed studies clearly recognize the importance of proliferation and apoptotic mechanisms in the pathogenesis of bone marrow (BM) malignancies. The literature is, however, contradictory on the role of these processes in myelodysplastic syndrome (MDS), MDS/myeloproliferative neoplasms, and acute myeloid leukemia. Furthermore, several studies underline the need for the analysis of the proliferative and apoptotic rates in subsets of hematopoietic BM cell lineages and argue that these results can have diagnostic and prognostic value in patients with myeloid malignancies. Recent developments in multiparameter flow cytometry now allow quantification of proliferative and (anti)apoptotic indicators in myeloid cells during their different maturation stages of separate hematopoietic cell lineages. This will lead to a better understanding of the biology and pathogenesis of these malignancies.

Application of Single-Cell Approaches to Study Myeloproliferative Neoplasm Biology

Philadelphia-negative myeloproliferative neoplasms (MPNs) are an excellent tractable disease model of a number of aspects of human cancer biology, including genetic evolution, tissue-associated fibrosis, and cancer stem cells. In this review, we discuss recent insights into MPN biology gained from the application of a number of new single-cell technologies to study human disease, with a specific focus on single-cell genomics, single-cell transcriptomics, and digital pathology.

Illuminating novel biological aspects and potential new therapeutic approaches for chronic myeloproliferative malignancies

This review reflects the presentations and discussion at the 14th post-American Society of Hematology (ASH) International Workshop on Chronic Myeloproliferative Malignancies, which took place on the December 10 and 11, 2019, immediately after the 61st ASH Annual Meeting in Orlando, Florida. Rather than present a resume of the proceedings, we address some of the topical translational science research and clinically relevant topics in detail. We consider how recent studies using single-cell genomics and other molecular methods reveal novel aspects of hematopoiesis which in turn raise the possibility of new therapeutic approaches for patients with myeloproliferative neoplasms (MPNs). We discuss how alternative therapies could benefit patients with chronic myeloid leukemia who develop BCR-ABL1 mutant subclones following ABL1-tyrosine kinase inhibitor therapy. In MPNs, we focus on efforts beyond JAK-STAT and the merits of integrating activin receptor ligand traps, interferon-α, and allografting in the current treatment algorithm for patients with myelofibrosis.

Chemical probes and methods for single-cell detection and quantification of epichaperomes in hematologic malignancies

Detection of protein connectivity dysfunctions in biological samples, i.e., informing on how protein-protein interactions change from a normal to a disease state, is important for both biomedical research and clinical development. The epichaperome is an executor of protein connectivity dysfunction in disease, and thus a surrogate for its detection. This chapter will detail on published methods for epichaperome detection and quantification that combine the advantages of multiparameter flow cytometry with those of the PU-FITC fluorescently labeled epichaperome detection probe. It will offer a comprehensive method description that includes the synthesis and characterization of an epichaperome detection probe and of the negative control probe, the preparation of the biospecimen for epichaperome analysis, the execution of the epichaperome detection and quantification assay and lastly, the data acquisition and analysis. The method provides, at single-cell level, the functional signature of cells, differentiating itself from other single-cell methods that provide a catalog of molecules.

Heterogeneity of Red Blood Cells: Causes and Consequences

Mean values of hematological parameters are currently used in the clinical laboratory settings to characterize red blood cell properties. Those include red blood cell indices, osmotic fragility test, eosin 5-maleimide (EMA) test, and deformability assessment using ektacytometry to name a few. Diagnosis of hereditary red blood cell disorders is complemented by identification of mutations in distinct genes that are recognized "molecular causes of disease." The power of these measurements is clinically well-established. However, the evidence is growing that the available information is not enough to understand the determinants of severity of diseases and heterogeneity in manifestation of pathologies such as hereditary hemolytic anemias. This review focuses on an alternative approach to assess red blood cell properties based on heterogeneity of red blood cells and characterization of fractions of cells with similar properties such as density, hydration, membrane loss, redox state, Ca2+ levels, and morphology. Methodological approaches to detect variance of red blood cell properties will be presented. Causes of red blood cell heterogeneity include cell age, environmental stress as well as shear and metabolic stress, and multiple other factors. Heterogeneity of red blood cell properties is also promoted by pathological conditions that are not limited to the red blood cells disorders, but inflammatory state, metabolic diseases and cancer. Therapeutic interventions such as splenectomy and transfusion as well as drug administration also impact the variance in red blood cell properties. Based on the overview of the studies in this area, the possible applications of heterogeneity in red blood cell properties as prognostic and diagnostic marker commenting on the power and selectivity of such markers are discussed.