Single-cell profiling reveals the trajectories of natural killer cell differentiation in bone marrow and a stress signature induced by acute myeloid leukemia

Chronic IL-15 Stimulation and Impaired mTOR Signaling and Metabolism in Natural Killer Cells During Acute Myeloid Leukemia

Natural Killer (NK) cells are potent anti-leukemic immune effectors. However, they display multiple defects in acute myeloid leukemia (AML) patients leading to reduced anti-tumor potential. Our limited understanding of the mechanisms underlying these defects hampers the development of strategies to restore NK cell potential. Here, we have used a mouse model of AML to gain insight into these mechanisms. We found that leukemia progression resulted in NK cell maturation defects and functional alterations. Next, we assessed NK cell cytokine signaling governing their behavior. We showed that NK cells from leukemic mice exhibit constitutive IL-15/mTOR signaling and type I IFN signaling. However, these cells failed to respond to IL-15 stimulation in vitro as illustrated by reduced activation of the mTOR pathway. Moreover, our data suggest that mTOR-mediated metabolic responses were reduced in NK cells from AML-bearing mice. Noteworthy, the reduction of mTOR-mediated activation of NK cells during AML development partially rescued NK cell metabolic and functional defects. Altogether, our data strongly suggest that NK cells from leukemic mice are metabolically and functionally exhausted as a result of a chronic cytokine activation, at least partially IL-15/mTOR signaling. NK cells from AML patients also displayed reduced IL-2/15Rβ expression and showed cues of reduced metabolic response to IL-15 stimulation in vitro, suggesting that a similar mechanism might occur in AML patients. Our study pinpoints the dysregulation of cytokine stimulation pathways as a new mechanism leading to NK cell defects in AML.

Terminal differentiation of bone marrow NK cells and increased circulation of TIGIT+ NK cells may be related to poor outcome in acute myeloid leukemia

AIM

In order to further understand the feature of natural killer cell (NK) dysfunction in acute myeloid leukemia (AML), The distribution of NK cell subset the expression of the inhibitory receptors immunoglobulin and ITIM domain (TIGIT), killer cell lectin-like receptor (KLRG1), and the expression of maturation marker CD57 in NK cell subsets and their correlation with patient outcomes were analyzed in this study.

METHODS

We collected peripheral blood (PB) and bone marrow (BM) samples from de novo AML (AML-DN) patients, patients who achieved complete remission after chemotherapy (AML-CR), and healthy individuals. An eight-color flow cytometry panel was used to identify different NK subsets and their expression of TIGIT, CD57 and KLRG1.

RESULTS

Decreased percentage of CD56^dim CD16⁺ NK cells was found only in the PB of AML-DN and AML-CR patients but not in the BM. The expression frequency of TIGIT and KLRG1 was elevated on NK cells from the PB of AML-DN patients, while it was recovered in AML-CR patients. Moreover, a higher percentage of CD57⁺ CD56^dim CD16⁺ NK cells, representing a terminally differentiated NK subset with strong cytotoxic capacity but defective replication potential, was detected in the BM of AML-DN patients and predicted sub-optimal survival for patients.

CONCLUSION

The results indicated that the NK cell subsets in the PB of AML patients had an exhaustion phenotype, while the BM NK cells had a terminally differentiated phenotype, which correlated with short survival for AML patients.

Making a Killer: Selecting the Optimal Natural Killer Cells for Improved Immunotherapies

Over the past 20 years natural killer (NK) cell-based immunotherapies have emerged as a safe and effective treatment option for patients with relapsed or refractory leukemia. Unlike T cell-based therapies, NK cells harbor an innate capacity to eliminate malignant cells without prior sensitization and can be adoptively transferred between individuals without the need for extensive HLA matching. A wide variety of therapeutic NK cell sources are currently being investigated clinically, including allogeneic donor-derived NK cells, stem cell-derived NK cells and NK cell lines. However, it is becoming increasingly clear that not all NK cells are endowed with the same antitumor potential. Despite advances in techniques to enhance NK cell cytotoxicity and persistence, the initial identification and utilization of highly functional NK cells remains essential to ensure the future success of adoptive NK cell therapies. Indeed, little consideration has been given to the identification and selection of donors who harbor NK cells with potent antitumor activity. In this regard, there is currently no standard donor selection criteria for adoptive NK cell therapy. Here, we review our current understanding of the factors which govern NK cell functional fate, and propose a paradigm shift away from traditional phenotypic characterization of NK cell subsets towards a functional profile based on molecular and metabolic characteristics. We also discuss previous selection models for NK cell-based immunotherapies and highlight important considerations for the selection of optimal NK cell donors for future adoptive cell therapies.

Haploidentical Stem Cell Transplantation for Acute Myeloid Leukemia: Current Therapies, Challenges and Future Prospective

Haploidentical stem cell transplantation (haplo-SCT), an alternative donor source, offers a curative therapy for patients with acute myeloid leukemia (AML) who are transplant candidates. Advances in transplantation techniques, such as donor selection, conditioning regimen modification, and graft-versus-host disease prophylaxis, have successfully improved the outcomes of AML patients receiving haplo-SCT and extended the haploidentical transplant indictions for AML. Presently, treating de novo AML, secondary AML, therapy-related AML and refractory and relapsed AML with haplo-SCT can achieve comparable outcomes to those of human leukocyte antigen (HLA)-matched sibling donor transplantation (MSDT), unrelated donor transplantation or umbilical cord blood transplantation. For some subgroups of AML subjects, such as patients with positive pretransplantation minimal/measurable residual disease, recent studies suggest that haplo-SCT might be superior to MSDT in decreasing relapse and improving survival. Unfortunately, for patients with AML after haplo-SCT, relapse and infections remain the causes of death that restrict further improvement in clinical outcomes. In this review, we discuss the recent advances and challenges in haplo-SCT for AML treatment, mainly focusing on unmanipulated haplo-SCT protocols. We provide an outlook on future prospects and suggest that relapse prophylaxis, intervention, and treatment, as well as infection prevention and therapy, are areas of active research in AML patients who receive haploidentical allografts.

Expression Regulation and Function of T-Bet in NK Cells

Natural killer (NK) cells are cytotoxic innate lymphocytes that play an important role in immune surveillance. The development, maturation and effector functions of NK cells are orchestrated by the T-box transcription factor T-bet, whose expression is induced by cytokines such as IFN-γ, IL-12, IL-15 and IL-21 through the respective cytokine receptors and downstream JAK/STATs or PI3K-AKT-mTORC1 signaling pathways. In this review, we aim to discuss the expression and regulation of T-bet in NK cells, the role of T-bet in mouse NK cell development, maturation, and function, as well as the role of T-bet in acute, chronic infection, inflammation, autoimmune diseases and tumors.

The Multi-Omic Prognostic Model of Oxidative Stress-Related Genes in Acute Myeloid Leukemia

Background: Acute myeloid leukemia (AML) is one of the most common cancers in the world, and oxidative stress is closely related to leukemia. A lot of effort has been made to improve the prognosis of AML. However, the situation remains serious. Hence, we focused on the study of prognostic genes in AML. Materials and Methods: Prognostic oxidative stress genes were screened out. The gene expression profile of AML patients was downloaded from the The Cancer Genome Atlas (TCGA) database. The oxidative stress-related model was constructed, by which the prognosis of AML patients was predicted using the two GEO GSE23143 datasets and the stability of the GSE71014 authentication model. Results: The prognostic oxidative stress genes were screened out in AML, and the prognostic genes were significantly enriched in a large number of pathways based on Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis. There was a complex interaction between prognostic genes and transcription factors. After constructing the prediction model, the clinical predictive value of the model was discussed in a multi-omic study. We investigated the sensitivity of risk score to common chemotherapeutic agents, the influence of signaling pathways on the prognosis of AML patients, and the correlation of multiple genes with immune score and immune dysfunction. Conclusions: A highly effective prognostic risk model for AML patients was established and validated. The association of prognostic oxidative stress genes with drug sensitivity, signaling pathways, and immune infiltration was explored. The results suggested that oxidative stress genes promised to be potential prognostic biomarkers for AML, which may provide a new basis for disease management.

The Dual Role of Innate Lymphoid and Natural Killer Cells in Cancer. from Phenotype to Single-Cell Transcriptomics, Functions and Clinical Uses

Simple Summary

Innate lymphoid cells (ILCs), a family of innate immune cells including natural killers (NKs), play a multitude of roles in first-line cancer control, in escape from immunity and in cancer progression. In this review, we summarize preclinical and clinical data on ILCs and NK cells concerning their phenotype, function and clinical applications in cellular therapy trials. We also describe how single-cell transcriptome sequencing has been used and forecast how it will be used to better understand ILC and NK involvement in cancer control and progression as well as their therapeutic potential.

Abstract

The role of innate lymphoid cells (ILCs), including natural killer (NK) cells, is pivotal in inflammatory modulation and cancer. Natural killer cell activity and count have been demonstrated to be regulated by the expression of activating and inhibitory receptors together with and as a consequence of different stimuli. The great majority of NK cell populations have an anti-tumor activity due to their cytotoxicity, and for this reason have been used for cellular therapies in cancer patients. On the other hand, the recently classified helper ILCs are fundamentally involved in inflammation and they can be either helpful or harmful in cancer development and progression. Tissue niche seems to play an important role in modulating ILC function and conversion, as observed at the transcriptional level. In the past, these cell populations have been classified by the presence of specific cellular receptor markers; more recently, due to the advent of single-cell RNA sequencing (scRNA-seq), it has been possible to also explore them at the transcriptomic level. In this article we review studies on ILC (and NK cell) classification, function and their involvement in cancer. We also summarize the potential application of NK cells in cancer therapy and give an overview of the most recent studies involving ILCs and NKs at scRNA-seq, focusing on cancer. Finally, we provide a resource for those who wish to start single-cell transcriptomic analysis on the context of these innate lymphoid cell populations.

Inflammaging, an Imbalanced Immune Response That Needs to Be Restored for Cancer Prevention and Treatment in the Elderly

Nowadays, new advances in society and health have brought an increased life expectancy. However, at the same time, aging comes with complications that impact the development of autoimmunity, neurodegenerative diseases and cancer. These complications affect the quality of life and impact the public health system. Specifically, with aging, a low-grade chronic sterile systemic inflammation with self-reactivity in the absence of acute infection occurs termed inflammaging. Inflammaging is related to an imbalanced immune response that can be either naturally acquired with aging or accelerated due to external triggers. Different molecules, metabolites and inflammatory forms of cell death are highly involved in these processes. Importantly, adoptive cellular immunotherapy is a modality of treatment for cancer patients that administers ex vivo expanded immune cells in the patient. The manipulation of these cells confers them enhanced proinflammatory properties. A general consequence of proinflammatory events is the development of autoimmune diseases and cancer. Herein, we review subsets of immune cells with a pertinent role in inflammaging, relevant proteins involved in these inflammatory events and external triggers that enhance and accelerate these processes. Moreover, we mention relevant preclinical studies that demonstrate associations of chronic inflammation with cancer development.

A statistical framework for differential pseudotime analysis with multiple single-cell RNA-seq samples

Pseudotime analysis with single-cell RNA-sequencing (scRNA-seq) data has been widely used to study dynamic gene regulatory programs along continuous biological processes. While many computational methods have been developed to infer the pseudo-temporal trajectories of cells within a biological sample, methods that compare pseudo-temporal patterns with multiple samples (or replicates) across different experimental conditions are lacking. Lamian is a comprehensive and statistically-rigorous computational framework for differential multi-sample pseudotime analysis. It can be used to identify changes in a biological process associated with sample covariates, such as different biological conditions, and also to detect changes in gene expression, cell density, and topology of a pseudotemporal trajectory. Unlike existing methods that ignore sample variability, Lamian draws statistical inference after accounting for cross-sample variability and hence substantially reduces sample-specific false discoveries that are not generalizable to new samples. Using both simulations and real scRNA-seq data, including an analysis of differential immune response programs between COVID-19 patients with different disease severity levels, we demonstrate the advantages of Lamian in decoding cellular gene expression programs in continuous biological processes.

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.