Clonal multi-omics reveals Bcor as a negative regulator of emergency dendritic cell development

Pre-existing stem cell heterogeneity dictates clonal responses to the acquisition of leukemic driver mutations

Cancer cells display wide phenotypic variation even across patients with the same mutations. Differences in the cell of origin provide a potential explanation, but traditional assays lack the resolution to distinguish clonally heterogeneous subsets of stem and progenitor cells. To address this challenge, we developed simultaneous tracking of recombinase activation and clonal kinetics (STRACK), a method to trace clonal dynamics and gene expression before and after the acquisition of cancer mutations. Using mouse models, we studied two leukemic mutations, Dnmt3a-R878H and Npm1c, and found that their effect was highly variable across different stem cell states. Specifically, a subset of differentiation-primed stem cells, which normally becomes outcompeted with time, expands with both mutations. Intriguingly, Npm1c mutations reversed the intrinsic bias of the clone of origin, with differentiation-primed stem cells giving rise to more primitive malignant states. Thus, we highlight the relevance of single-cell lineage tracing to unravel early events in cancer evolution and posit that different cellular histories carry distinct cancer phenotypic potential.

Transformer-based modeling of Clonal Selection and Expression Dynamics reveals resistance mechanisms in breast cancer

Understanding transcriptional heterogeneity in cancer cells and its implication for treatment response is critical to identify how resistance occurs and may be targeted. Such heterogeneity can be captured by in vitro studies through clonal barcoding methods. We present TraCSED (Transformer-based modeling of Clonal Selection and Expression Dynamics), a dynamic deep learning approach for modeling clonal selection. Using single-cell gene expression and the fitness of barcoded clones, TraCSED identifies interpretable gene programs and the time points at which they are associated with clonal selection. When applied to cells treated with either giredestrant, a selective estrogen receptor (ER) antagonist and degrader, or palbociclib, a CDK4/6 inhibitor, pathways dynamically associated with resistance are revealed. For example, ER activity is associated with positive selection around day four under palbociclib treatment and this adaptive response can be suppressed by combining the drugs. Yet, in the combination treatment, one clone still emerged. Clustering based on partial least squares regression found that high baseline expression of both SNHG25 and SNCG genes was the primary marker of positive selection to co-treatment and thus potentially associated with innate resistance - an aspect that traditional differential analysis methods missed. In conclusion, TraCSED enables associating features with phenotypes in a time-dependent manner from scRNA-seq data.

Synthetic DNA barcodes identify singlets in scRNA-seq datasets and evaluate doublet algorithms

Single-cell RNA sequencing (scRNA-seq) datasets contain true single cells, or singlets, in addition to cells that coalesce during the protocol, or doublets. Identifying singlets with high fidelity in scRNA-seq is necessary to avoid false negative and false positive discoveries. Although several methodologies have been proposed, they are typically tested on highly heterogeneous datasets and lack a priori knowledge of true singlets. Here, we leveraged datasets with synthetically introduced DNA barcodes for a hitherto unexplored application: to extract ground-truth singlets. We demonstrated the feasibility of our framework, "singletCode," to evaluate existing doublet detection methods across a range of contexts. We also leveraged our ground-truth singlets to train a proof-of-concept machine learning classifier, which outperformed other doublet detection algorithms. Our integrative framework can identify ground-truth singlets and enable robust doublet detection in non-barcoded datasets.

An emerging maestro of immune regulation: how DOT1L orchestrates the harmonies of the immune system

The immune system comprises a complex yet tightly regulated network of cells and molecules that play a critical role in protecting the body from infection and disease. The activity and development of each immune cell is regulated in a myriad of ways including through the cytokine milieu, the availability of key receptors, via tailored intracellular signalling cascades, dedicated transcription factors and even by directly modulating gene accessibility and expression; the latter is more commonly known as epigenetic regulation. In recent years, epigenetic regulators have begun to emerge as key players involved in modulating the immune system. Among these, the lysine methyltransferase DOT1L has gained significant attention for its involvement in orchestrating immune cell formation and function. In this review we provide an overview of the role of DOT1L across the immune system and the implications of this role on health and disease. We begin by elucidating the general mechanisms of DOT1L-mediated histone methylation and its impact on gene expression within immune cells. Subsequently, we provide a detailed and comprehensive overview of recent studies that identify DOT1L as a crucial regulator of immune cell development, differentiation, and activation. Next, we discuss the potential mechanisms of DOT1L-mediated regulation of immune cell function and shed light on how DOT1L might be contributing to immune cell homeostasis and dysfunction. We then provide food for thought by highlighting some of the current obstacles and technical limitations precluding a more in-depth elucidation of DOT1L's role. Finally, we explore the potential therapeutic implications of targeting DOT1L in the context of immune-related diseases and discuss ongoing research efforts to this end. Overall, this review consolidates the current paradigm regarding DOT1L's role across the immune network and emphasises its critical role in governing the healthy immune system and its potential as a novel therapeutic target for immune-related diseases. A deeper understanding of DOT1L's immunomodulatory functions could pave the way for innovative therapeutic approaches which fine-tune the immune response to enhance or restore human health.

Genome-wide screening identifies Trim33 as an essential regulator of dendritic cell differentiation

The development of dendritic cells (DCs), including antigen-presenting conventional DCs (cDCs) and cytokine-producing plasmacytoid DCs (pDCs), is controlled by the growth factor Flt3 ligand (Flt3L) and its receptor Flt3. We genetically dissected Flt3L-driven DC differentiation using CRISPR-Cas9-based screening. Genome-wide screening identified multiple regulators of DC differentiation including subunits of TSC and GATOR1 complexes, which restricted progenitor growth but enabled DC differentiation by inhibiting mTOR signaling. An orthogonal screen identified the transcriptional repressor Trim33 (TIF-1γ) as a regulator of DC differentiation. Conditional targeting in vivo revealed an essential role of Trim33 in the development of all DCs, but not of monocytes or granulocytes. In particular, deletion of Trim33 caused rapid loss of DC progenitors, pDCs, and the cross-presenting cDC1 subset. Trim33-deficient Flt3+ progenitors up-regulated pro-inflammatory and macrophage-specific genes but failed to induce the DC differentiation program. Collectively, these data elucidate mechanisms that control Flt3L-driven differentiation of the entire DC lineage and identify Trim33 as its essential regulator.

Gene-expression memory-based prediction of cell lineages from scRNA-seq datasets

Assigning single cell transcriptomes to cellular lineage trees by lineage tracing has transformed our understanding of differentiation during development, regeneration, and disease. However, lineage tracing is technically demanding, often restricted in time-resolution, and most scRNA-seq datasets are devoid of lineage information. Here we introduce Gene Expression Memory-based Lineage Inference (GEMLI), a computational tool allowing to robustly identify small to medium-sized cell lineages solely from scRNA-seq datasets. GEMLI allows to study heritable gene expression, to discriminate symmetric and asymmetric cell fate decisions and to reconstruct individual multicellular structures from pooled scRNA-seq datasets. In human breast cancer biopsies, GEMLI reveals previously unknown gene expression changes at the onset of cancer invasiveness. The universal applicability of GEMLI allows studying the role of small cell lineages in a wide range of physiological and pathological contexts, notably in vivo. GEMLI is available as an R package on GitHub ( https://github.com/UPSUTER/GEMLI ).

Microfluidic platform for omics analysis on single cells with diverse morphology and size: A review

BACKGROUND

Microfluidic techniques have emerged as powerful tools in single-cell research, facilitating the exploration of omics information from individual cells. Cell morphology is crucial for gene expression and physiological processes. However, there is currently a lack of integrated analysis of morphology and single-cell omics information. A critical challenge remains: what platform technologies are the best option to decode omics data of cells that are complex in morphology and size?

RESULTS

This review highlights achievements in microfluidic-based single-cell omics and isolation of cells based on morphology, along with other cell sorting methods based on physical characteristics. Various microfluidic platforms for single-cell isolation are systematically presented, showcasing their diversity and adaptability. The discussion focuses on microfluidic devices tailored to the distinct single-cell isolation requirements in plants and animals, emphasizing the significance of considering cell morphology and cell size in optimizing single-cell omics strategies. Simultaneously, it explores the application of microfluidic single-cell sorting technologies to single-cell sequencing, aiming to effectively integrate information about cell shape and size.

SIGNIFICANCE AND NOVELTY

The novelty lies in presenting a comprehensive overview of recent accomplishments in microfluidic-based single-cell omics, emphasizing the integration of different microfluidic platforms and their implications for cell morphology-based isolation. By underscoring the pivotal role of the specialized morphology of different cells in single-cell research, this review provides robust support for delving deeper into the exploration of single-cell omics data.

Clonally heritable gene expression imparts a layer of diversity within cell types

Cell types can be classified according to shared patterns of transcription. Non-genetic variability among individual cells of the same type has been ascribed to stochastic transcriptional bursting and transient cell states. Using high-coverage single-cell RNA profiling, we asked whether long-term, heritable differences in gene expression can impart diversity within cells of the same type. Studying clonal human lymphocytes and mouse brain cells, we uncovered a vast diversity of heritable gene expression patterns among different clones of cells of the same type in vivo. We combined chromatin accessibility and RNA profiling on different lymphocyte clones to reveal thousands of regulatory regions exhibiting interclonal variation, which could be directly linked to interclonal variation in gene expression. Our findings identify a source of cellular diversity, which may have important implications for how cellular populations are shaped by selective processes in development, aging, and disease. A record of this paper's transparent peer review process is included in the supplemental information.

Single-cell lineage tracing with endogenous markers

Resolving lineage relationships between cells in an organism provides key insights into the fate of individual cells and drives a fundamental understanding of the process of development and disease. A recent rapid increase in experimental and computational advances for detecting naturally occurring somatic nuclear and mitochondrial mutation at single-cell resolution has expanded lineage tracing from model organisms to humans. This review discusses the advantages and challenges of experimental and computational techniques for cell lineage tracing using somatic mutation as endogenous DNA barcodes to decipher the relationships between cells during development and tumour evolution. We outlook the advantages of spatial clonal evolution analysis and single-cell lineage tracing using endogenous genetic markers.

Identification of dendritic cell precursor from the CD11c+ cells expressing high levels of MHC class II molecules in the culture of bone marrow with FLT3 ligand

Dendritic cells (DCs) are readily generated from the culture of mouse bone marrow (BM) treated with either granulocyte macrophage-colony stimulating factor (GM-CSF) or FMS-like tyrosine kinase 3 ligand (FLT3L). CD11c+MHCII+ or CD11c+MHCIIhi cells are routinely isolated from those BM cultures and generally used as in vitro-generated DCs for a variety of experiments and therapies. Here, we examined CD11c+ cells in the BM culture with GM-CSF or FLT3L by staining with a monoclonal antibody 2A1 that is known to recognize mature or activated DCs. Most of the cells within the CD11c+MHCIIhi DC gate were 2A1+ in the BM culture with GM-CSF (GM-BM culture). In the BM culture with FLT3L (FL-BM culture), almost of all the CD11c+MHCIIhi cells were within the classical DC2 (cDC2) gate. The analysis of FL-BM culture revealed that a majority of cDC2-gated CD11c+MHCIIhi cells exhibited a 2A1-CD83-CD115+CX3CR1+ phenotype, and the others consisted of 2A1+CD83+CD115-CX3CR1- and 2A1-CD83-CD115-CX3CR1- cells. According to the antigen uptake and presentation, morphologies, and gene expression profiles, 2A1-CD83-CD115-CX3CR1- cells were immature cDC2s and 2A1+CD83+CD115-CX3CR1- cells were mature cDC2s. Unexpectedly, however, 2A1-CD83-CD115+CX3CR1+ cells, the most abundant cDC2-gated MHCIIhi cell subset in FL-BM culture, were non-DCs. Adoptive cell transfer experiments in the FL-BM culture confirmed that the cDC2-gated MHCIIhi non-DCs were precursors to cDC2s, i.e., MHCIIhi pre-cDC2s. MHCIIhi pre-cDC2s also expressed the higher level of DC-specific transcription factor Zbtb46 as similarly as immature cDC2s. Besides, MHCIIhi pre-cDC2s were generated only from pre-cDCs and common DC progenitor (CDP) cells but not from monocytes and common monocyte progenitor (cMoP) cells, verifying that MHCIIhi pre-cDC2s are close lineage to cDCs. All in all, our study identified and characterized a new cDC precursor, exhibiting a CD11c+MHCIIhiCD115+CX3CR1+ phenotype, in FL-BM culture.

Diverse clonal fates emerge upon drug treatment of homogeneous cancer cells

Even among genetically identical cancer cells, resistance to therapy frequently emerges from a small subset of those cells1-7. Molecular differences in rare individual cells in the initial population enable certain cells to become resistant to therapy7-9; however, comparatively little is known about the variability in the resistance outcomes. Here we develop and apply FateMap, a framework that combines DNA barcoding with single-cell RNA sequencing, to reveal the fates of hundreds of thousands of clones exposed to anti-cancer therapies. We show that resistant clones emerging from single-cell-derived cancer cells adopt molecularly, morphologically and functionally distinct resistant types. These resistant types are largely predetermined by molecular differences between cells before drug addition and not by extrinsic factors. Changes in the dose and type of drug can switch the resistant type of an initial cell, resulting in the generation and elimination of certain resistant types. Samples from patients show evidence for the existence of these resistant types in a clinical context. We observed diversity in resistant types across several single-cell-derived cancer cell lines and cell types treated with a variety of drugs. The diversity of resistant types as a result of the variability in intrinsic cell states may be a generic feature of responses to external cues.

Discovery of highly immunogenic spleen-resident FCGR3+CD103+ cDC1s differentiated by IL-33-primed ST2+ basophils

Recombinant interleukin-33 (IL-33) inhibits tumor growth, but the detailed immunological mechanism is still unknown. IL-33-mediated tumor suppression did not occur in Batf3-/- mice, indicating that conventional type 1 dendritic cells (cDC1s) play a key role in IL-33-mediated antitumor immunity. A population of CD103+ cDC1s, which were barely detectable in the spleens of normal mice, increased significantly in the spleens of IL-33-treated mice. The newly emerged splenic CD103+ cDC1s were distinct from conventional splenic cDC1s based on their spleen residency, robust effector T-cell priming ability, and surface expression of FCGR3. DCs and DC precursors did not express Suppressor of Tumorigenicity 2 (ST2). However, recombinant IL-33 induced spleen-resident FCGR3+CD103+ cDC1s, which were found to be differentiated from DC precursors by bystander ST2+ immune cells. Through immune cell fractionation and depletion assays, we found that IL-33-primed ST2+ basophils play a crucial role in the development of FCGR3+CD103+ cDC1s by secreting IL-33-driven extrinsic factors. Recombinant GM-CSF also induced the population of CD103+ cDC1s, but the population neither expressed FCGR3 nor induced any discernable antitumor immunity. The population of FCGR3+CD103+ cDC1s was also generated in vitro culture of Flt3L-mediated bone marrow-derived DCs (FL-BMDCs) when IL-33 was added in a pre-DC stage of culture. FL-BMDCs generated in the presence of IL-33 (FL-33-DCs) offered more potent tumor immunotherapy than control Flt3L-BMDCs (FL-DCs). Human monocyte-derived DCs were also more immunogenic when exposed to IL-33-induced factors. Our findings suggest that recombinant IL-33 or an IL-33-mediated DC vaccine could be an attractive protocol for better tumor immunotherapy.

Clonal selection parallels between normal and cancer tissues

Clonal selection and drift drive both normal tissue and cancer development. However, the biological mechanisms and environmental conditions underpinning these processes remain to be elucidated. Clonal selection models are centered in Darwinian evolutionary theory, where some clones with the fittest features are selected and populate the tissue or tumor. We suggest that different subclasses of stem cells, each of which is responsible for a distinct feature of the selection process, share common features between normal and cancer conditions. While active stem cells populate the tissue, dormant cells account for tissue replenishment/regeneration in both normal and cancerous tissues. We also discuss potential mechanisms that drive clonal drift, their interactions with clonal selection, and their similarities during normal and cancer tissue development.

Mapping of clonal lineages across developmental stages in human neural differentiation

The cell lineages across developmental stages remain to be elucidated. Here, we developed single-cell split barcoding (SISBAR) that allows clonal tracking of single-cell transcriptomes across stages in an in vitro model of human ventral midbrain-hindbrain differentiation. We developed "potential-spective" and "origin-spective" analyses to investigate the cross-stage lineage relationships and mapped a multi-level clonal lineage landscape depicting the whole differentiation process. We uncovered many previously uncharacterized converging and diverging trajectories. Furthermore, we demonstrate that a transcriptome-defined cell type can arise from distinct lineages that leave molecular imprints on their progenies, and the multilineage fates of a progenitor cell-type represent the collective results of distinct rather than similar clonal fates of individual progenitors, each with distinct molecular signatures. Specifically, we uncovered a ventral midbrain progenitor cluster as the common clonal origin of midbrain dopaminergic (mDA) neurons, midbrain glutamatergic neurons, and vascular and leptomeningeal cells and identified a surface marker that can improve graft outcomes.

Single-cell multi-omics and lineage tracing to dissect cell fate decision-making

The concept of cell fate relates to the future identity of a cell, and its daughters, which is obtained via cell differentiation and division. Understanding, predicting, and manipulating cell fate has been a long-sought goal of developmental and regenerative biology. Recent insights obtained from single-cell genomic and integrative lineage-tracing approaches have further aided to identify molecular features predictive of cell fate. In this perspective, we discuss these approaches with a focus on theoretical concepts and future directions of the field to dissect molecular mechanisms underlying cell fate.

Mastering the use of cellular barcoding to explore cancer heterogeneity

Tumours are often composed of a multitude of malignant clones that are genomically unique, and only a few of them may have the ability to escape cancer therapy and grow as symptomatic lesions. As a result, tumours with a large degree of genomic diversity have a higher chance of leading to patient death. However, clonal fate can be driven by non-genomic features. In this context, new technologies are emerging not only to track the spatiotemporal fate of individual cells and their progeny but also to study their molecular features using various omics analysis. In particular, the recent development of cellular barcoding facilitates the labelling of tens to millions of cancer clones and enables the identification of the complex mechanisms associated with clonal fate in different microenvironments and in response to therapy. In this Review, we highlight the recent discoveries made using lentiviral-based cellular barcoding techniques, namely genetic and optical barcoding. We also emphasize the strengths and limitations of each of these technologies and discuss some of the key concepts that must be taken into consideration when one is designing barcoding experiments. Finally, we suggest new directions to further improve the use of these technologies in cancer research.

Cellular barcoding to decipher clonal dynamics in disease

Cellular barcodes are distinct DNA sequences that enable one to track specific cells across time or space. Recent advances in our ability to detect natural or synthetic cellular barcodes, paired with single-cell readouts of cell state, have markedly increased our knowledge of clonal dynamics and genealogies of the cells that compose a variety of tissues and organs. These advances hold promise to redefine our view of human disease. Here, we provide an overview of cellular barcoding approaches, discuss applications to gain new insights into disease mechanisms, and provide an outlook on future applications. We discuss unanticipated insights gained through barcoding in studies of cancer and blood cell production and describe how barcoding can be applied to a growing array of medical fields, particularly with the increasing recognition of clonal contributions in human diseases.

CellDestiny: A RShiny application for the visualization and analysis of single-cell lineage tracing data

Single-cell lineage tracing permits the labeling of individual cells with a heritable marker to follow the fate of each cell's progeny. Over the last twenty years, several single-cell lineage tracing methods have emerged, enabling major discoveries in developmental biology, oncology and gene therapies. Analytical tools are needed to draw meaningful conclusions from lineage tracing measurements, which are characterized by high variability, sparsity and technical noise. However, the single cell lineage tracing field lacks versatile and easy-to-use tools for standardized and reproducible analyses, in particular tools accessible to biologists. Here we present CellDestiny, a RShiny app and associated web application developed for experimentalists without coding skills to perform visualization and analysis of single cell lineage-tracing datasets through a graphical user interface. We demonstrate the functionality of CellDestiny through the analysis of (i) lentiviral barcoding datasets of murine hematopoietic progenitors; (ii) published integration site data from Wiskott-Aldrich Symdrome patients undergoing gene-therapy treatment; and (iii) simultaneous barcoding and transcriptomic analysis of murine hematopoietic progenitor differentiation in vitro. In summary, CellDestiny is an easy-to-use and versatile toolkit that enables biologists to visualize and analyze single-cell lineage tracing data.

Lineage tracing reveals B cell antibody class switching is stochastic, cell-autonomous, and tuneable

To optimize immunity to pathogens, B lymphocytes generate plasma cells with functionally diverse antibody isotypes. By lineage tracing single cells within differentiating B cell clones, we identified the heritability of discrete fate controlling mechanisms to inform a general mathematical model of B cell fate regulation. Founder cells highly influenced clonal plasma-cell fate, whereas class switch recombination (CSR) was variegated within clones. In turn, these CSR patterns resulted from independent all-or-none expression of both activation-induced cytidine deaminase (AID) and IgH germline transcription (GLT), with the latter being randomly re-expressed after each cell division. A stochastic model premised on these molecular transition rules accurately predicted antibody switching outcomes under varied conditions in vitro and during an immune response in vivo. Thus, the generation of functionally diverse antibody types follows rules of autonomous cellular programming that can be adapted and modeled for the rational control of antibody classes for potential therapeutic benefit.

Clonal lineage tracing reveals shared origin of conventional and plasmacytoid dendritic cells

Developmental origins of dendritic cells (DCs) including conventional DCs (cDCs, comprising cDC1 and cDC2 subsets) and plasmacytoid DCs (pDCs) remain unclear. We studied DC development in unmanipulated adult mice using inducible lineage tracing combined with clonal DNA "barcoding" and single-cell transcriptome and phenotype analysis (CITE-seq). Inducible tracing of Cx3cr1+ hematopoietic progenitors in the bone marrow showed that they simultaneously produce all DC subsets including pDCs, cDC1s, and cDC2s. Clonal tracing of hematopoietic stem cells (HSCs) and of Cx3cr1+ progenitors revealed clone sharing between cDC1s and pDCs, but not between the two cDC subsets or between pDCs and B cells. Accordingly, CITE-seq analyses of differentiating HSCs and Cx3cr1+ progenitors identified progressive stages of pDC development including Cx3cr1+ Ly-6D+ pro-pDCs that were distinct from lymphoid progenitors. These results reveal the shared origin of pDCs and cDCs and suggest a revised scheme of DC development whereby pDCs share clonal relationship with cDC1s.

Efficacy and predictive biomarkers of immunotherapy in Epstein-Barr virus-associated gastric cancer

Background

Epstein-Barr virus (EBV)-associated gastric cancer (GC) (EBVaGC) is a distinct molecular subtype of GC with a favorable prognosis. However, the exact effects and potential mechanisms of EBV infection on immune checkpoint blockade (ICB) efficacy in GC remain to be clarified. Additionally, EBV-encoded RNA (EBER) in situ hybridization (ISH), the traditional method to detect EBV, could cause false-positive/false-negative results and not allow for characterizing other molecular biomarkers recommended by standard treatment guidelines for GC. Herein, we sought to investigate the efficacy and potential biomarkers of ICB in EBVaGC identified by next-generation sequencing (NGS).

Design

An NGS-based algorithm for detecting EBV was established and validated using two independent GC cohorts (124 in the training cohort and 76 in the validation cohort). The value of EBV infection for predicting ICB efficacy was evaluated among 95 patients with advanced or metastatic GC receiving ICB. The molecular predictive biomarkers for ICB efficacy were identified to improve the prediction accuracy of ICB efficacy in 22 patients with EBVaGC.

Results

Compared with orthogonal assay (EBER-ISH) results, the NGS-based algorithm achieved high performance with a sensitivity of 95.7% (22/23) and a specificity of 100% (53/53). EBV status was identified as an independent predictive factor for overall survival and progression-free survival in patients with DNA mismatch repair proficient (pMMR) GC following ICB. Moreover, the patients with EBV+/pMMR and EBV−/MMR deficient (dMMR) had comparable and favorable survival following ICB. Twenty-two patients with EBV+/pMMR achieved an objective response rate of 54.5% (12/22) on immunotherapy. Patients with EBVaGC with a high cytotoxic T lymphocyte-associated antigen-4 (CTLA-4) level were less responsive to anti-programmed death-1/ligand 1 (PD-1/L1) monotherapy, and the combination of anti-CTLA-4 plus anti-PD-1/L1 checkpoint blockade benefited patients with EBVaGC more than anti-PD-1/L1 monotherapy with a trend close to significance (p=0.074). There were nearly significant differences in tumor mutational burden (TMB) level and SMARCA4 mutation frequency between the ICB response and non-response group.

Conclusions

We developed an efficient NGS-based EBV detection strategy, and this strategy-identified EBV infection was as effective as dMMR in predicting ICB efficacy in GC. Additionally, we identified CTLA-4, TMB, and SMARCA4 mutation as potential predictive biomarkers of ICB efficacy in EBVaGC, which might better inform ICB treatment for EBVaGC.

Re-building limbs, one cell at a time

New techniques for visualizing and interrogating single cells hold the key to unlocking the underlying mechanisms of salamander limb regeneration.

GM-CSF: Master regulator of the T cell-phagocyte interface during inflammation

The role of granulocyte-macrophage colony-stimulating factor (GM-CSF) was sequentially redefined during the past decades. Originally described as a hematopoietic growth factor for myelopoiesis, GM-CSF was recognized as a central mediator of inflammation bridging the innate and adaptive arms of the immune system. Phagocytes sensing GM-CSF adapt an inflammatory phenotype and facilitate pathogen clearance. However, in the context of chronic tissue inflammation, GM-CSF secreted by tissue-invading lymphocytes has detrimental effects by licensing tissue damage and hyperinflammation. Accordingly, therapeutic intervention at the T cell-phagocyte interface represents an attractive target to ameliorate disease progression and immunopathology. Although GM-CSF is largely dispensable for steady state myelopoiesis, dysregulation, as seen in chronic inflammatory diseases, may however lead to disrupted haematopoiesis and long-term effects on bone marrow output. Here, we will survey the role of GM-CSF during inflammation, discuss the extent to which GM-CSF-secreting T cells, debate their introduction as a separate T cell lineage and explore current and future clinical implications of GM-CSF in human disease settings.

Dendritic cell fate determination revealed by "SISter" assays

Establishing the connection between cell fate and fate-related genes in a single progenitor cell is a challenge. In this issue of Immunity, Tian et al. tackled this challenge by designing SIS-seq and SIS-Skew assays and identified Bcor as a negative regulator for dendritic cell differentiation.