Single cell characterization of B-lymphoid differentiation and leukemic cell states during chemotherapy in ETV6-RUNX1-positive pediatric leukemia identifies drug-targetable transcription factor activities

Unlocking the Complexity: Exploration of Acute Lymphoblastic Leukemia at the Single Cell Level

Acute lymphoblastic leukemia (ALL) is the most common cancer in children. ALL originates from precursor lymphocytes that acquire multiple genomic changes over time, including chromosomal rearrangements and point mutations. While a large variety of genomic defects was identified and characterized in ALL over the past 30 years, it was only in recent years that the clonal heterogeneity was recognized. Thanks to the latest advancements in single-cell sequencing techniques, which have evolved from the analysis of a few hundred cells to the analysis of thousands of cells simultaneously, the study of tumor heterogeneity now becomes possible. Different modalities can be explored at the single-cell level: DNA, RNA, epigenetic modifications, and intracellular and cell surface proteins. In this review, we describe these techniques and highlight their advantages and limitations in the study of ALL biology. Moreover, multiomics technologies and the incorporation of the spatial dimension can provide insight into intercellular communication. We describe how the different single-cell sequencing technologies help to unravel the molecular complexity of ALL, shedding light on its development, its heterogeneity, its interaction with the leukemia microenvironment and possible relapse mechanisms.

The uncertainties and certainties of gene transcription in a human tumor cell

Previously we have identified that the expression number and levels of oncogenes and antioncogenes are highly positively or negatively associated with major cellular progress in a cancer cell. However, we have not defined any cellular potentials of a human tumor cell at the level of the overall gene expression. Here, we counted the overall number of expression genes and overall counts of mRNA in depth and revealed that the expression levels of mRNA were directly associated with the expression number of genes in a human tumor cell. Gene expression networks revealed steady states of tricarboxylic acid (TCA) cycle and ATP production, differentiation potentials that might be disturbed and blocked by uncertain gene expressing networks, and potential capabilities to undergo epithelial-mesenchymal transition (EMT), neurogenesis, angiogenesis, inflammatory response, immune evasion, and metastasis in a human tumor cell. Our analysis identifies unpredictable gene expression characteristics in human tumor cells. The results might profoundly influence mechanisms how a human tumor cell generates and undergoes its progresses.

Sequential drug treatment targeting cell cycle and cell fate regulatory programs blocks non-genetic cancer evolution in acute lymphoblastic leukemia

BACKGROUND

Targeted therapies exploiting vulnerabilities of cancer cells hold promise for improving patient outcome and reducing side-effects of chemotherapy. However, efficacy of precision therapies is limited in part because of tumor cell heterogeneity. A better mechanistic understanding of how drug effect is linked to cancer cell state diversity is crucial for identifying effective combination therapies that can prevent disease recurrence.

RESULTS

Here, we characterize the effect of G2/M checkpoint inhibition in acute lymphoblastic leukemia (ALL) and demonstrate that WEE1 targeted therapy impinges on cell fate decision regulatory circuits. We find the highest inhibition of recovery of proliferation in ALL cells with KMT2A-rearrangements. Single-cell RNA-seq and ATAC-seq of RS4;11 cells harboring KMT2A::AFF1, treated with the WEE1 inhibitor AZD1775, reveal diversification of cell states, with a fraction of cells exhibiting strong activation of p53-driven processes linked to apoptosis and senescence, and disruption of a core KMT2A-RUNX1-MYC regulatory network. In this cell state diversification induced by WEE1 inhibition, a subpopulation transitions to a drug tolerant cell state characterized by activation of transcription factors regulating pre-B cell fate, lipid metabolism, and pre-BCR signaling in a reversible manner. Sequential treatment with BCR-signaling inhibitors dasatinib, ibrutinib, or perturbing metabolism by fatostatin or AZD2014 effectively counteracts drug tolerance by inducing cell death and repressing stemness markers.

CONCLUSIONS

Collectively, our findings provide new insights into the tight connectivity of gene regulatory programs associated with cell cycle and cell fate regulation, and a rationale for sequential administration of WEE1 inhibitors with low toxicity inhibitors of pre-BCR signaling or metabolism.

Comparison of high-throughput single-cell RNA-seq methods for ex vivo drug screening

Functional precision medicine (FPM) aims to optimize patient-specific drug selection based on the unique characteristics of their cancer cells. Recent advancements in high throughput ex vivo drug profiling have accelerated interest in FPM. Here, we present a proof-of-concept study for an integrated experimental system that incorporates ex vivo treatment response with a single-cell gene expression output enabling barcoding of several drug conditions in one single-cell sequencing experiment. We demonstrate this through a proof-of-concept investigation focusing on the glucocorticoid-resistant acute lymphoblastic leukemia (ALL) E/R+ Reh cell line. Three different single-cell transcriptome sequencing (scRNA-seq) approaches were evaluated, each exhibiting high cell recovery and accurate tagging of distinct drug conditions. Notably, our comprehensive analysis revealed variations in library complexity, sensitivity (gene detection), and differential gene expression detection across the methods. Despite these differences, we identified a substantial transcriptional response to fludarabine, a highly relevant drug for treating high-risk ALL, which was consistently recapitulated by all three methods. These findings highlight the potential of our integrated approach for studying drug responses at the single-cell level and emphasize the importance of method selection in scRNA-seq studies. Finally, our data encompassing 27 327 cells are freely available to extend to future scRNA-seq methodological comparisons.

SINGLE CELL DISSECTION OF DEVELOPMENTAL ORIGINS AND TRANSCRIPTIONAL HETEROGENEITY IN B-CELL ACUTE LYMPHOBLASTIC LEUKEMIA

Sequencing of bulk tumor populations has improved genetic classification and risk assessment of B-ALL, but does not directly examine intratumor heterogeneity or infer leukemia cellular origins. We profiled 89 B-ALL samples by single-cell RNA-seq (scRNA-seq) and compared them to a reference map of normal human B-cell development established using both functional and molecular assays. Intra-sample heterogeneity was driven by cell cycle, metabolism, differentiation, and inflammation transcriptional programs. By inference of B lineage developmental state composition, nearly all samples possessed a high abundance of pro-B cells, with variation between samples mainly driven by sub-populations. However, ZNF384- r and DUX4- r B-ALL showed composition enrichment of hematopoietic stem cells, BCR::ABL1 and KMT2A -r ALL of Early Lymphoid progenitors, MEF2D -r and TCF3::PBX1 of Pre-B cells. Enrichment of Early Lymphoid progenitors correlated with high-risk clinical features. Understanding variation in transcriptional programs and developmental states of B-ALL by scRNA-seq refines existing clinical and genomic classifications and improves prediction of treatment outcome.

Transcription factor abnormalities in B-ALL leukemogenesis and treatment

The biological regulation of transcription factors (TFs) and repressor proteins is an important mechanism for maintaining cell homeostasis. In B cell acute lymphoblastic leukemia (B-ALL) TF abnormalities occur at high frequency and are often recognized as the major driving factor in carcinogenesis. We provide an in-depth review of molecular mechanisms of six major TF rearrangements in B-ALL, including DUX4-rearranged (DUX4-R), MEF2D-R, ZNF384-R, ETV6-RUNX1 and TCF3-PBX1 fusions, and KMT2A-R. In addition, the therapeutic options and prognoses for patients who harbor these TF abnormalities are discussed. This review aims to provide an up-to-date panoramic view of how TF-based oncogenic fusions might drive carcinogenesis and impact on potential therapeutic exploration of B-ALL treatments.

[Optimized treatment of childhood B-lineage acute lymphoblastic leukemia]

Childhood acute lymphoblastic leukemia (ALL) accounts for about 75% of childhood leukemia cases, and B-lineage acute lymphoblastic leukemia (B-ALL) accounts for more than 80% of childhood ALL cases. Over the past half century, new molecular biological targets discovered by new techniques have been used in precise stratification of disease prognosis, and there has been a gradual increase in the 5-year overall survival rate of childhood ALL. With the increasing attention to long-term quality of life, the treatment of childhood B-ALL has been constantly optimized from induction therapy to the intensity of maintenance therapy, including the treatment of extramedullary leukemia without radiotherapy, which has been tried with successful results. The realization of optimized treatment also benefits from the development of new techniques associated with immunology and molecular biology and the establishment of standardized clinical cohorts and corresponding biobanks. This article summarizes the relevant research on the implementation of precise stratification and the intensity reduction and optimization treatment of B-ALL in recent years, providing reference for clinicians.

ETS transcription factors: Multifaceted players from cancer progression to tumor immunity

The E26 transformation specific (ETS) family comprises 28 transcription factors, the majority of which are involved in tumor initiation and development. Serving as a group of functionally heterogeneous gene regulators, ETS factors possess a structurally conserved DNA-binding domain. As one of the most prominent families of transcription factors that control diverse cellular functions, ETS activation is modulated by multiple intracellular signaling pathways and post-translational modifications. Disturbances in ETS activity often lead to abnormal changes in oncogenicity, including cancer cell survival, growth, proliferation, metastasis, genetic instability, cell metabolism, and tumor immunity. This review systematically addresses the basics and advances in studying ETS factors, from their tumor relevance to clinical translational utility, with a particular focus on elucidating the role of ETS family in tumor immunity, aiming to decipher the vital role and clinical potential of regulation of ETS factors in the cancer field.

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 technologies uncover intra-tumor heterogeneity in childhood cancers

Childhood cancer is the second leading cause of death in children aged 1 to 14. Although survival rates have vastly improved over the past 40 years, cancer resistance and relapse remain a significant challenge. Advances in single-cell technologies enable dissection of tumors to unprecedented resolution. This facilitates unraveling the heterogeneity of childhood cancers to identify cell subtypes that are prone to treatment resistance. The rapid accumulation of single-cell data from different modalities necessitates the development of novel computational approaches for processing, visualizing, and analyzing single-cell data. Here, we review single-cell approaches utilized or under development in the context of childhood cancers. We review computational methods for analyzing single-cell data and discuss best practices for their application. Finally, we review the impact of several studies of childhood tumors analyzed with these approaches and future directions to implement single-cell studies into translational cancer research in pediatric oncology.

Comprehensive multi-omics single-cell data integration reveals greater heterogeneity in the human immune system

Single-cell transcriptomics enables the definition of diverse human immune cell types across multiple tissues and disease contexts. Further deeper biological understanding requires comprehensive integration of multiple single-cell omics (transcriptomic, proteomic, and cell-receptor repertoire). To improve the identification of diverse cell types and the accuracy of cell-type classification in multi-omics single-cell datasets, we developed SuPERR, a novel analysis workflow to increase the resolution and accuracy of clustering and allow for the discovery of previously hidden cell subsets. In addition, SuPERR accurately removes cell doublets and prevents widespread cell-type misclassification by incorporating information from cell-surface proteins and immunoglobulin transcript counts. This approach uniquely improves the identification of heterogeneous cell types and states in the human immune system, including rare subsets of antibody-secreting cells in the bone marrow.

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SuPERR removes heterotypic doublets and cell-type misclassifications in scRNA-seq

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Sequential gating on cell-surface proteins resolves major cell lineages in scRNA-seq

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Defining major cell lineages before clustering reduces cell-type misclassifications

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Antibody counts from single-cell V(D)J matrix accurately identify plasma cells

Single-cell RNA sequencing analysis of human bone-marrow-derived mesenchymal stem cells and functional subpopulation identification

Mesenchymal stem cells (MSCs) are a common kind of multipotent cell in vivo, but their heterogeneity limits their further applications. To identify MSC subpopulations and clarify their relationships, we performed cell mapping of bone-marrow-derived MSCs through single-cell RNA (scRNA) sequencing. In our study, three main subpopulations, namely, the stemness subpopulation, functional subpopulation, and proliferative subpopulation, were identified using marker genes and further bioinformatic analyses. Developmental trajectory analysis showed that the stemness subpopulation was the root and then became either the functional subpopulation or the proliferative subpopulation. The functional subpopulation showed stronger immunoregulatory and osteogenic differentiation abilities but lower proliferation and adipogenic differentiation. MSCs at different passages or isolated from different donors exhibited distinct cell mapping profiles, which accounted for their corresponding different functions. This study provides new insight into the biological features and clinical use of MSCs at the single-cell level, which may contribute to expanding their application in the clinic.

In Utero Development and Immunosurveillance of B Cell Acute Lymphoblastic Leukemia

Acute lymphoblastic leukemia (ALL) is the most frequent type of pediatric cancer with a peak incidence at 2–5 years of age. ALL frequently begins in utero with the emergence of clinically silent, preleukemic cells. Underlying leukemia-predisposing germline and acquired somatic mutations define distinct ALL subtypes that vary dramatically in treatment outcomes. In addition to genetic predisposition, a second hit, which usually occurs postnatally, is required for development of overt leukemia in most ALL subtypes. An untrained, dysregulated immune response, possibly due to an abnormal response to infection, may be an important co-factor triggering the onset of leukemia. Furthermore, the involvement of natural killer (NK) cells and T helper (Th) cells in controlling the preleukemic cells has been discussed. Identifying the cell of origin of the preleukemia-initiating event might give additional insights into potential options for prevention. Modulation of the immune system to achieve prolonged immunosurveillance of the preleukemic clone that eventually dies out in later years might present a future directive. Herein, we review the concepts of prenatal origin as well as potential preventive approaches to pediatric B cell precursor (BCP) ALL.

Elucidating minimal residual disease of paediatric B-cell acute lymphoblastic leukaemia by single-cell analysis

Minimal residual disease that persists after chemotherapy is the most valuable prognostic marker for haematological malignancies and solid cancers. Unfortunately, our understanding of the resistance elicited in minimal residual disease is limited due to the rarity and heterogeneity of the residual cells. Here we generated 161,986 single-cell transcriptomes to analyse the dynamic changes of B-cell acute lymphoblastic leukaemia (B-ALL) at diagnosis, residual and relapse by combining single-cell RNA sequencing and B-cell-receptor sequencing. In contrast to those at diagnosis, the leukaemic cells at relapse tended to shift to poorly differentiated states, whereas the changes in the residual cells were more complicated. Differential analyses highlighted the activation of the hypoxia pathway in residual cells, resistant clones and B-ALL with MLL rearrangement. Both in vitro and in vivo models demonstrated that inhibition of the hypoxia pathway sensitized leukaemic cells to chemotherapy. This single-cell analysis of minimal residual disease opens up an avenue for the identification of potent treatment opportunities for B-ALL.

Single-Cell Sequencing: Biological Insight and Potential Clinical Implications in Pediatric Leukemia

Single-cell sequencing (SCS) provides high-resolution insight into the genomic, epigenomic, and transcriptomic landscape of oncohematological malignancies including pediatric leukemia, the most common type of childhood cancer. Besides broadening our biological understanding of cellular heterogeneity, sub-clonal architecture, and regulatory network of tumor cell populations, SCS can offer clinically relevant, detailed characterization of distinct compartments affected by leukemia and identify therapeutically exploitable vulnerabilities. In this review, we provide an overview of SCS studies focused on the high-resolution genomic and transcriptomic scrutiny of pediatric leukemia. Our aim is to investigate and summarize how different layers of single-cell omics approaches can expectedly support clinical decision making in the future. Although the clinical management of pediatric leukemia underwent a spectacular improvement during the past decades, resistant disease is a major cause of therapy failure. Currently, only a small proportion of childhood leukemia patients benefit from genomics-driven therapy, as 15-20% of them meet the indication criteria of on-label targeted agents, and their overall response rate falls in a relatively wide range (40-85%). The in-depth scrutiny of various cell populations influencing the development, progression, and treatment resistance of different disease subtypes can potentially uncover a wider range of driver mechanisms for innovative therapeutic interventions.

Transcriptomics paving the way for improved diagnostics and precision medicine of acute leukemia

Transcriptional profiling of acute leukemia, specifically by RNA-sequencing or whole transcriptome sequencing (WTS), has provided fundamental insights into its underlying disease biology and allows unbiased detection of oncogenic gene fusions, as well as of gene expression signatures that can be used for improved disease classification. While used as a research tool for many years, RNA-sequencing is becoming increasingly used in clinical diagnostics. Here, we highlight key transcriptomic studies of acute lymphoblastic leukemia (ALL) and acute myeloid leukemia (AML) that have improved our biological understanding of these heterogeneous malignant disorders and have paved the way for translation into clinical diagnostics. Recent single-cell transcriptomic studies of ALL and AML, which provide new insights into the cellular ecosystem of acute leukemia and point to future clinical utility, are also reviewed. Finally, we discuss current challenges that need to be overcome for a more wide-spread adoption of RNA-sequencing in clinical diagnostics and how this technology significantly can aid the identification of genetic alterations in current guidelines and of newly emerging disease entities, some of which are critical to identify because of the availability of targeted therapies, thereby paving the way for improved precision medicine of acute leukemia.

Single-cell RNA sequencing in cancer: Applications, advances, and emerging challenges

Cancer has become one of the greatest threats to human health, and new technologies are urgently needed to further clarify the mechanisms of cancer so that better detection and treatment strategies can be developed. At present, extensive genomic analysis and testing of clinical specimens shape the insights into carcinoma. Nevertheless, carcinoma of humans is a complex ecosystem of cells, including carcinoma cells and immunity-related and stroma-related subsets, with accurate characteristics obscured by extensive genome-related approaches. A growing body of research shows that sequencing of single-cell RNA (scRNA-seq) is emerging to be an effective way for dissecting human tumor tissue at single-cell resolution, presenting one prominent way for explaining carcinoma biology. This review summarizes the research progress of scRNA-seq in the field of tumors, focusing on the application of scRNA-seq in tumor circulating cells, tumor stem cells, tumor drug resistance, the tumor microenvironment, and so on, which provides a new perspective for tumor research.

IGF2BP3 Associates with Proliferative Phenotype and Prognostic Features in B-Cell Acute Lymphoblastic Leukemia

The oncofetal protein insulin-like growth factor 2 mRNA-binding protein 3 (IGF2BP3) belongs to a family of RNA-binding proteins involved in localization, stability, and translational regulation of target RNAs. IGF2BP3 is used as a diagnostic and prognostic marker in several malignancies. Although the prognosis of pediatric B-cell acute lymphoblastic leukemia (B-ALL) has improved, a subgroup of patients exhibits high-risk features and suffer from disease recurrence. We sought to identify additional biomarkers to improve diagnostics, and we assessed expression of IGF2BP3 in a population-based pediatric cohort of B-ALL using a tissue microarray platform. The majority of pediatric B-ALL cases were positive for IGF2BP3 immunohistochemistry and were associated with an increased proliferative phenotype and activated STAT5 signaling pathway. Two large gene expression data sets were probed for the expression of IGF2BP3-the highest levels were seen among the B-cell lymphomas of a germinal center origin and well-established (KMT2A-rearranged and ETV6-RUNX1) and novel subtypes of B-ALL (e.g., NUTM1 and ETV6-RUNX1-like). A high mRNA for IGF2BP3 was associated with a proliferative "metagene" signature and a high expression of CDK6 in B-ALL. A low expression portended inferior survival in a high-risk cohort of pediatric B-ALL. Overall, our results show that IGF2BP3 shows subtype-specificity in expression and provides prognostic utility in high-risk B-ALL.

Identifying Differentially Expressed Genes of Zero Inflated Single Cell RNA Sequencing Data Using Mixed Model Score Tests

Single cell RNA sequencing (scRNA-seq) allows quantitative measurement and comparison of gene expression at the resolution of single cells. Ignoring the batch effects and zero inflation of scRNA-seq data, many proposed differentially expressed (DE) methods might generate bias. We propose a method, single cell mixed model score tests (scMMSTs), to efficiently identify DE genes of scRNA-seq data with batch effects using the generalized linear mixed model (GLMM). scMMSTs treat the batch effect as a random effect. For zero inflation, scMMSTs use a weighting strategy to calculate observational weights for counts independently under zero-inflated and zero-truncated distributions. Counts data with calculated weights were subsequently analyzed using weighted GLMMs. The theoretical null distributions of the score statistics were constructed by mixed Chi-square distributions. Intensive simulations and two real datasets were used to compare edgeR-zinbwave, DESeq2-zinbwave, and scMMSTs. Our study demonstrates that scMMSTs, as supplement to standard methods, are advantageous to define DE genes of zero-inflated scRNA-seq data with batch effects.

Single cell characterization of B-lymphoid differentiation and leukemic cell states during chemotherapy in ETV6-RUNX1-positive pediatric leukemia identifies drug-targetable transcription factor activities

BACKGROUND

Tight regulatory loops orchestrate commitment to B cell fate within bone marrow. Genetic lesions in this gene regulatory network underlie the emergence of the most common childhood cancer, acute lymphoblastic leukemia (ALL). The initial genetic hits, including the common translocation that fuses ETV6 and RUNX1 genes, lead to arrested cell differentiation. Here, we aimed to characterize transcription factor activities along the B-lineage differentiation trajectory as a reference to characterize the aberrant cell states present in leukemic bone marrow, and to identify those transcription factors that maintain cancer-specific cell states for more precise therapeutic intervention.

METHODS

We compared normal B-lineage differentiation and in vivo leukemic cell states using single cell RNA-sequencing (scRNA-seq) and several complementary genomics profiles. Based on statistical tools for scRNA-seq, we benchmarked a workflow to resolve transcription factor activities and gene expression distribution changes in healthy bone marrow lymphoid cell states. We compared these to ALL bone marrow at diagnosis and in vivo during chemotherapy, focusing on leukemias carrying the ETV6-RUNX1 fusion.

RESULTS

We show that lymphoid cell transcription factor activities uncovered from bone marrow scRNA-seq have high correspondence with independent ATAC- and ChIP-seq data. Using this comprehensive reference for regulatory factors coordinating B-lineage differentiation, our analysis of ETV6-RUNX1-positive ALL cases revealed elevated activity of multiple ETS-transcription factors in leukemic cells states, including the leukemia genome-wide association study hit ELK3. The accompanying gene expression changes associated with natural killer cell inactivation and depletion in the leukemic immune microenvironment. Moreover, our results suggest that the abundance of G1 cell cycle state at diagnosis and lack of differentiation-associated regulatory network changes during induction chemotherapy represent features of chemoresistance. To target the leukemic regulatory program and thereby overcome treatment resistance, we show that inhibition of ETS-transcription factors reduced cell viability and resolved pathways contributing to this using scRNA-seq.

CONCLUSIONS

Our data provide a detailed picture of the transcription factor activities characterizing both normal B-lineage differentiation and those acquired in leukemic bone marrow and provide a rational basis for new treatment strategies targeting the immune microenvironment and the active regulatory network in leukemia.