Single-cell mutational profiling enhances the clinical evaluation of AML MRD

Molecular Minimal Residual Disease Detection in Acute Myeloid Leukemia

Initial induction chemotherapy to eradicate the bulk of acute myeloid leukemia (AML) cells results in complete remission (CR) in the majority of patients. However, leukemic cells persisting in the bone marrow below the morphologic threshold remain unaffected and have the potential to proliferate and re-emerge as AML relapse. Detection of minimal/measurable residual disease (MRD) is a promising prognostic marker for AML relapse as it can assess an individual patients' risk profile and evaluate their response to treatment. With the emergence of molecular techniques, such as next generation sequencing (NGS), a more sensitive assessment of molecular MRD markers is available. In recent years, the detection of MRD by molecular assays and its association with AML relapse and survival has been explored and verified in multiple studies. Although most studies show that the presence of MRD leads to a worse clinical outcome, molecular-based methods face several challenges including limited sensitivity/specificity, and a difficult distinction between mutations that are representative of AML rather than clonal hematopoiesis. This review describes the studies that have been performed using molecular-based assays for MRD detection in the context of other MRD detection approaches in AML, and discusses limitations, challenges and opportunities.

Single-Cell RNA-Seq of T Cells in B-ALL Patients Reveals an Exhausted Subset with Remarkable Heterogeneity

Characterization of functional T cell clusters is key to developing strategies for immunotherapy and predicting clinical responses in leukemia. Here, single-cell RNA sequencing is performed with T cells sorted from the peripheral blood of healthy individuals and patients with B cell-acute lymphoblastic leukemia (B-ALL). Unbiased bioinformatics analysis enabled the authors to identify 13 T cell clusters in the patients based on their molecular properties. All 11 major T cell subsets in healthy individuals are found in the patients with B-ALL, with the counterparts in the patients universally showing more activated characteristics. Two exhausted T cell populations, characterized by up-regulation of TIGIT, PDCD1, HLADRA, LAG3, and CTLA4 are specifically discovered in B-ALL patients. Of note, these exhausted T cells possess remarkable heterogeneity, and ten sub-clusters are further identified, which are characterized by different cell cycle phases, naïve states, and GNLY (coding granulysin) expression. Coupled with single-cell T cell receptor repertoire profiling, diverse originations of the exhausted T cells in B-ALL are suggested, and clonally expanded exhausted T cells are likely to originate from CD8+ effector memory/terminal effector cells. Together, these data provide for the first-time valuable insights for understanding exhausted T cell populations in leukemia.

Predicting Time to Relapse in Acute Myeloid Leukemia through Stochastic Modeling of Minimal Residual Disease Based on Clonality Data

Event-free and overall survival remain poor for patients with acute myeloid leukemia. Chemoresistant clones contributing to relapse arise from minimal residual disease (MRD) or newly-acquired mutations. However, the dynamics of clones comprising MRD is poorly understood. We developed a predictive stochastic model, based on a multitype age-dependent Markov branching process, to describe how random events in MRD contribute to the heterogeneity in treatment response. We employed training and validation sets of patients who underwent whole genome sequencing and for whom mutant clone frequencies at diagnosis and relapse were available. The disease evolution and treatment outcome are subject to stochastic fluctuations. Estimates of malignant clone growth rates, obtained by model fitting, are consistent with published data. Using the estimates from the training set, we developed a function linking MRD and time of relapse, with MRD inferred from the model fits to clone frequencies and other data. An independent validation set confirmed our model. In a third data set, we fitted the model to data at diagnosis and remission and predicted the time to relapse. As a conclusion, given bone marrow genome at diagnosis and MRD at or past remission, the model can predict time to relapse, and help guide treatment decisions to mitigate relapse.

Clinico-genomic profiling and clonal dynamic modeling of TP53-aberrant myelodysplastic syndrome and acute myeloid leukemia

TP53-aberrant myelodysplastic syndrome and acute myeloid leukemia have dismal outcomes. Here, we define the clinico-genomic landscape of TP53 disruptions in 40 patients and employ clonal dynamic modeling to map the mutational hierarchy against clinical outcomes. Most TP53 mutations (45.2%) localized to the L3 loop or LSH motif of the DNA-binding domain. TP53 disruptions had high co-occurrence with mutations in epigenetic regulators, spliceosome machinery, and cohesin complex and low co-occurrence with mutations in proliferative signaling genes. Ancestral and descendant TP53 mutations constituted measurable residual disease and fueled relapse. High mutant TP53 gene dosage predicted low durability of remission. The median overall survival (OS) was 280 days. Hypomethylating agent-based therapy served as an effective bridge to transplant, leading to improved median OS compared to patients who did not receive a transplant (14.7 vs. 5.1 months). OS was independent of the genomic location of TP53 disruption, which has implications for rational therapeutic design.

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.

Clinical Perspectives of Single-Cell RNA Sequencing

The ability of single-cell genomics to resolve cellular heterogeneity is highly appreciated in cancer and is being exploited for precision medicine. In the recent decade, we have witnessed the incorporation of cancer genomics into the clinical decision-making process for molecular-targeted therapies. Compared with conventional genomics, which primarily focuses on the specific and sensitive detection of the molecular targets, single-cell genomics addresses intratumoral heterogeneity and the microenvironmental components impacting the treatment response and resistance. As an exploratory tool, single-cell genomics provides an unprecedented opportunity to improve the diagnosis, monitoring, and treatment of cancer. The results obtained upon employing bulk cancer genomics indicate that single-cell genomics is at an early stage with respect to exploration of clinical relevance and requires further innovations to become a widely utilized technology in the clinic.

Genetic heterogeneity and clonal evolution in acute myeloid leukemia

PURPOSE OF REVIEW

Clonal heterogeneity is a significant obstacle to successful treatment of patients with acute myeloid leukemia (AML). Here, we review new advances in the understanding of genetic heterogeneity in AML using single-cell DNA-sequencing technology.

RECENT FINDINGS

New genomics and immunologic discovery tools have provided single-cell resolution maps of the clonal architecture of AML. The use of these technologies reveals the mutational landscape of AML at diagnosis, during treatment, and at relapse has an enormous degree of clonal complexity and diversity that is poised to adapt and evolve under environmental pressures.

SUMMARY

AML is a complex ecosystem of competing and cooperating clones undergoing constant evolution and selection.

The contribution of single-cell analysis of acute leukemia in the therapeutic strategy

After decades during which the treatment of acute myeloblastic leukemia was limited to variations around a skeleton of cytarabine/anthracycline, targeted therapies appeared. These therapies, first based on monoclonal antibodies, also rely on specific inhibitors of various molecular abnormalities. A significant but modest prognosis improvement has been observed thanks to these new treatments that are limited by a high rate of relapse, due to the intrinsic chemo and immune-resistance of leukemia stem cell, together with the acquisition of these resistances by clonal evolution. Relapses are also influenced by the equilibrium between the pro or anti-tumor signals from the bone marrow stromal microenvironment and immune effectors. What should be the place of the targeted therapeutic options in light of the tumor heterogeneity inherent to leukemia and the clonal drift of which this type of tumor is capable? Novel approaches by single cell analysis and next generation sequencing precisely define clonal heterogeneity and evolution, leading to a personalized and time variable adapted treatment. Indeed, the evolution of leukemia, either spontaneous or under therapy selection pressure, is a very complex phenomenon. The model of linear evolution is to be forgotten because single cell analysis of samples at diagnosis and at relapse show that tumor escape to therapy occurs from ancestral as well as terminal clones. The determination by the single cell technique of the trajectories of the different tumor sub-populations allows the identification of clones that accumulate factors of resistance to chemo/immunotherapy ("pan-resistant clones"), making possible to choose the combinatorial agents most likely to eradicate these cells. In addition, the single cell technique identifies the nature of each cell and can analyze, on the same sample, both the tumor cells and their environment. It is thus possible to evaluate the populations of immune effectors (T-lymphocytes, natural killer cells) for the leukemia stress-induced alteration of their functions. Finally, the single cells techniques are an invaluable tool for evaluation of the measurable residual disease since not only able to quantify but also to determine the most appropriate treatment according to the sensitivity profile to immuno-chemotherapy of remaining leukemic cells.

Genomic analysis of cellular hierarchy in acute myeloid leukemia using ultrasensitive LC-FACSeq

Hematopoiesis is hierarchical, and it has been postulated that acute myeloid leukemia (AML) is organized similarly with leukemia stem cells (LSCs) residing at the apex. Limited cells acquired by fluorescence activated cell sorting in tandem with targeted amplicon-based sequencing (LC-FACSeq) enables identification of mutations in small subpopulations of cells, such as LSCs. Leveraging this, we studied clonal compositions of immunophenotypically-defined compartments in AML through genomic and functional analyses at diagnosis, remission and relapse in 88 AML patients. Mutations involving DNA methylation pathways, transcription factors and spliceosomal machinery did not differ across compartments, while signaling pathway mutations were less frequent in putative LSCs. We also provide insights into TP53-mutated AML by demonstrating stepwise acquisition of mutations beginning from the preleukemic hematopoietic stem cell stage. In 10 analyzed cases, acquisition of additional mutations and del(17p) led to genetic and functional heterogeneity within the LSC pool with subclones harboring varying degrees of clonogenic potential. Finally, we use LC-FACSeq to track clonal evolution in serial samples, which can also be a powerful tool to direct targeted therapy against measurable residual disease. Therefore, studying clinically significant small subpopulations of cells can improve our understanding of AML biology and offers advantages over bulk sequencing to monitor the evolution of disease.

Applying high-dimensional single-cell technologies to the analysis of cancer immunotherapy

Advances in molecular biology, microfluidics and bioinformatics have empowered the study of thousands or even millions of individual cells from malignant tumours at the single-cell level of resolution. This high-dimensional, multi-faceted characterization of the genomic, transcriptomic, epigenomic and proteomic features of the tumour and/or the associated immune and stromal cells enables the dissection of tumour heterogeneity, the complex interactions between tumour cells and their microenvironment, and the details of the evolutionary trajectory of each tumour. Single-cell transcriptomics, the ability to track individual T cell clones through paired sequencing of the T cell receptor genes and high-dimensional single-cell spatial analysis are all areas of particular relevance to immuno-oncology. Multidimensional biomarker signatures will increasingly be crucial to guiding clinical decision-making in each patient with cancer. High-dimensional single-cell technologies are likely to provide the resolution and richness of data required to generate such clinically relevant signatures in immuno-oncology. In this Perspective, we describe advances made using transformative single-cell analysis technologies, especially in relation to clinical response and resistance to immunotherapy, and discuss the growing utility of single-cell approaches for answering important research questions.

Decoding Cancer Biology One Cell at a Time

Human tumors are composed of diverse malignant and nonmalignant cells, generating a complex ecosystem that governs tumor biology and response to treatments. Recent technological advances have enabled the characterization of tumors at single-cell resolution, providing a compelling strategy to dissect their intricate biology. Here we describe recent developments in single-cell expression profiling and the studies applying them in clinical settings. We highlight some of the powerful insights gleaned from these studies for tumor classification, stem cell programs, tumor microenvironment, metastasis, and response to targeted and immune therapies. SIGNIFICANCE: Intratumor heterogeneity (ITH) has been a major barrier to our understanding of cancer. Single-cell genomics is leading a revolution in our ability to systematically dissect ITH. In this review, we focus on single-cell expression profiling and lessons learned in key aspects of human tumor biology.

Time to Move to the Single-Cell Level: Applications of Single-Cell Multi-Omics to Hematological Malignancies and Waldenström's Macroglobulinemia-A Particularly Heterogeneous Lymphoma

Single-cell sequencing techniques have become a powerful tool for characterizing intra-tumor heterogeneity, which has been reflected in the increasing number of studies carried out and reported. We have rigorously reviewed and compiled the information about these techniques inasmuch as they are relative to the area of hematology to provide a practical view of their potential applications. Studies show how single-cell multi-omics can overcome the limitations of bulk sequencing and be applied at all stages of tumor development, giving insights into the origin and pathogenesis of the tumors, the clonal architecture and evolution, or the mechanisms of therapy resistance. Information at the single-cell level may help resolve questions related to intra-tumor heterogeneity that have not been previously explained by other techniques. With that in mind, we review the existing knowledge about a heterogeneous lymphoma called Waldenström's macroglobulinemia and discuss how single-cell studies may help elucidate the underlying causes of this heterogeneity.

Single-cell sequencing in translational cancer research and challenges to meet clinical diagnostic needs

The ability to capture alterations in the genome or transcriptome by next-generation sequencing has provided critical insight into molecular changes and programs underlying cancer biology. With the rapid technological development in single-cell sequencing, it has become possible to study individual cells at the transcriptional, genetic, epigenetic, and protein level. Using single-cell analysis, an increased resolution of fundamental processes underlying cancer development is obtained, providing comprehensive insights otherwise lost by sequencing of entire (bulk) samples, in which molecular signatures of individual cells are averaged across the entire cell population. Here, we provide a concise overview on the application of single-cell analysis of different modalities within cancer research by highlighting key articles of their respective fields. We furthermore examine the potential of existing technologies to meet clinical diagnostic needs and discuss current challenges associated with this translation.

Analysis of Intratumoral Heterogeneity in Myelodysplastic Syndromes with Isolated del(5q) Using a Single Cell Approach

Simple Summary

Myelodysplastic syndromes (MDS) are a heterogeneous group of clonal hematopoietic stem cell malignancies characterized by ineffective differentiation of one or more bone marrow cell lineages. Only 50% of patients with de novo MDS will be found to have cytogenetic abnormalities, of which del(5q) is the most common. In 10% of MDS cases, del(5q) is found as a sole abnormality. In this work, a single cell approach was used to analyze intratumoral heterogeneity in four patients with MDS with isolated del(5q). We were able to observe that an ancestral event in one patient can appear as a secondary hit in another one, thus reflecting the high intratumoral heterogeneity in MDS with isolated del(5q) and the importance of patient-specific molecular characterization.

Abstract

Myelodysplastic syndromes (MDS) are a heterogeneous group of hematological diseases. Among them, the most well characterized subtype is MDS with isolated chromosome 5q deletion (MDS del(5q)), which is the only one defined by a cytogenetic abnormality that makes these patients candidates to be treated with lenalidomide. During the last decade, single cell (SC) analysis has emerged as a powerful tool to decipher clonal architecture and to further understand cancer and other diseases at higher resolution level compared to bulk sequencing techniques. In this study, a SC approach was used to analyze intratumoral heterogeneity in four patients with MDS del(5q). Single CD34+CD117+CD45+CD19- bone marrow hematopoietic stem progenitor cells were isolated using the C1 system (Fluidigm) from diagnosis or before receiving any treatment and from available follow-up samples. Selected somatic alterations were further analyzed in SC by high-throughput qPCR (Biomark HD, Fluidigm) using specific TaqMan assays. A median of 175 cells per sample were analyzed. Inferred clonal architectures were relatively simple and either linear or branching. Similar to previous studies based on bulk sequencing to infer clonal architecture, we were able to observe that an ancestral event in one patient can appear as a secondary hit in another one, thus reflecting the high intratumoral heterogeneity in MDS del(5q) and the importance of patient-specific molecular characterization.

A precision medicine approach to management of acute myeloid leukemia in older adults

PURPOSE OF REVIEW

Therapy selection in older adults with acute myeloid leukemia (AML) can be challenging because of a higher incidence of high-risk cytogenetic and molecular features conferring chemoresistance and poor functional status leading to increased treatment-related toxicities. The purpose of this review is to highlight the recent advances in precision medicine in AML that have shown promise to improve outcomes of older adults.

RECENT FINDINGS

The utilization of next generation sequencing to identify and target actionable mutations can influence therapy selection in one-third of patients and can result in higher response rates as well as survival compared with those who do not receive targeted therapy. Oral targeted agents are available for AML with IDH 1, IDH2, or FLT3 mutations. Low-intensity venetoclax-based regimens have shown high rates of responses in AML, particularly among those with NPM1 and IDH2 mutations; responses are often durable and associated with minimal residual disease (MRD) negativity. Multiple studies have demonstrated the prognostic significance of flow cytometric MRD, with potential implications for subsequent therapy.

SUMMARY

Novel approaches for AML risk-stratification, MRD assessment, and a precision medicine approach offer significant promise to improve survival and quality of life of older adults.

Genomic Analysis of Hematopoietic Stem Cell at the Single-Cell Level: Optimization of Cell Fixation and Whole Genome Amplification (WGA) Protocol

Single-cell genomics has become the method of choice for the study of heterogeneous cell populations and represents an elective application in defining the architecture and clonal evolution in hematological neoplasms. Reconstructing the clonal evolution of a neoplastic population therefore represents the main way to understand more deeply the pathogenesis of the neoplasm, but it is also a potential tool to understand the evolution of the tumor population with respect to its response to therapy. Pre-analytical phase for single-cell genomics analysis is crucial to obtain a cell population suitable for single-cell sorting, and whole genome amplification is required to obtain the necessary amount of DNA from a single cell in order to proceed with sequencing. Here, we evaluated the impact of different methods of cellular immunostaining, fixation and whole genome amplification on the efficiency and yield of single-cell sequencing.

Isocitrate Dehydrogenase Mutations in Myelodysplastic Syndromes and in Acute Myeloid Leukemias

Acute myeloid leukemia (AML) is a heterogeneous disease generated by the acquisition of multiple genetic and epigenetic aberrations which impair the proliferation and differentiation of hematopoietic progenitors and precursors. In the last years, there has been a dramatic improvement in the understanding of the molecular alterations driving cellular signaling and biochemical changes determining the survival advantage, stimulation of proliferation, and impairment of cellular differentiation of leukemic cells. These molecular alterations influence clinical outcomes and provide potential targets for drug development. Among these alterations, an important role is played by two mutant enzymes of the citric acid cycle, isocitrate dehydrogenase (IDH), IDH1 and IDH2, occurring in about 20% of AMLs, which leads to the production of an oncogenic metabolite R-2-hydroxy-glutarate (R-2-HG); this causes a DNA hypermethylation and an inhibition of hematopoietic stem cell differentiation. IDH mutations differentially affect prognosis of AML patients following the location of the mutation and other co-occurring genomic abnormalities. Recently, the development of novel therapies based on the specific targeting of mutant IDH may contribute to new effective treatments of these patients. In this review, we will provide a detailed analysis of the biological, clinical, and therapeutic implications of IDH mutations.

Natural HDAC-1/8 inhibitor baicalein exerts therapeutic effect in CBF-AML

BACKGROUND

Although targeting histone deacetylases (HDACs) may be an effective strategy for core binding factor-acute myeloid leukemia (CBF-AML) harboring t(8;21) or inv(16), HDAC inhibitors are reported to be limited by drug-resistant characteristic. Our purpose is to evaluate the anti-leukemia effects of Baicalein on CBF-AML and clarify its underlying mechanism.

METHODS

Enzyme activity assay was used to measure the activity inhibition of HDACs. Rhodamine123 and RT-qPCR were employed to evaluate the distribution of drugs and the change of ATP-binding cassette (ABC) transporter genes. CCK8, Annexin V/PI, and FACS staining certified the effects of Baicalein on cell growth, apoptosis, and differentiation. Duolink and IP assay assessed the interaction between HDAC-1 and ubiquitin, HSP90 and AML1-ETO, and Ac-p53 and CBFβ-MYH11. AML cell lines and primary AML cells-bearing NOD/SCID mice models were used to evaluate the anti-leukemic efficiency and potential mechanism of Baicalein in vivo.

RESULTS

Baicalein showed HDAC-1/8 inhibition to trigger growth suppression and differentiation induction of AML cell lines and primary AML cells. Although the inhibitory action on HDAC-1 was mild, Baicalein could induce the degradation of HDAC-1 via ubiquitin proteasome pathway, thereby upregulating the acetylation of Histone H3 without promoting ABC transporter genes expression. Meanwhile, Baicalein increased the acetylation of HSP90 and lessened its connection to AML1/ETO, consequently leading to degradation of AML1-ETO in t(8;21)q(22;22) AML cells. In inv(16) AML cells, Baicalein possessed the capacity of apoptosis induction accompanied with p53-mediated apoptosis genes expression. Moreover, CBFβ-MYH11-bound p53 acetylation was restored via HDAC-8 inhibition induced by Baicalein contributing the diminishing of survival of CD34+  inv(16) AML cells.

CONCLUSIONS

These findings improved the understanding of the epigenetic regulation of Baicalein, and warrant therapeutic potential of Baicalein for CBF-AML.

The Progression of Acute Myeloid Leukemia from First Diagnosis to Chemoresistant Relapse: A Comparison of Proteomic and Phosphoproteomic Profiles

Acute myeloid leukemia (AML) is an aggressive hematological malignancy. Nearly 50% of the patients who receive the most intensive treatment develop chemoresistant leukemia relapse. Although the leukemogenic events leading to relapse seem to differ between patients (i.e., regrowth from a clone detected at first diagnosis, progression from the original leukemic or preleukemic stem cells), a common characteristic of relapsed AML is increased chemoresistance. The aim of the present study was to investigate at the proteomic level whether leukemic cells from relapsed patients present overlapping molecular mechanisms that contribute to this chemoresistance. We used liquid chromatography–tandem mass spectrometry (LC–MS/MS) to compare the proteomic and phosphoproteomic profiles of AML cells derived from seven patients at the time of first diagnosis and at first relapse. At the time of first relapse, AML cells were characterized by increased levels of proteins important for various mitochondrial functions, such as mitochondrial ribosomal subunit proteins (MRPL21, MRPS37) and proteins for RNA processing (DHX37, RNA helicase; RPP40, ribonuclease P component), DNA repair (ERCC3, DNA repair factor IIH helicase; GTF2F1, general transcription factor), and cyclin-dependent kinase (CDK) activity. The levels of several cytoskeletal proteins (MYH14/MYL6/MYL12A, myosin chains; VCL, vinculin) as well as of proteins involved in vesicular trafficking/secretion and cell adhesion (ITGAX, integrin alpha-X; CD36, platelet glycoprotein 4; SLC2A3, solute carrier family 2) were decreased in relapsed cells. Our study introduces new targetable proteins that might direct therapeutic strategies to decrease chemoresistance in relapsed AML.