Strategies for monitoring cell-cell interactions

DNA-Directed Activation of Photocatalytic Labeling at Cell-Cell Contact Sites

Cell-cell interactions govern diverse biological activities, necessitating molecular tools for understanding and regulating these interactions. Photoredox chemistry can detect cell-cell interactions by anchoring photocatalysts on cellular membranes to generate reactive species that tag closely contacting cells. However, the activation of photocatalysts lacks precise spatial resolution for selectively labeling intercellular interfaces. Herein, we report a DNA-based approach to selectively activate photocatalytic reactions at cell-cell contacts. Two cell populations are coated with distinct DNA strands, which interact at intercellular contacts, mediating the site-specific turn-on of a Ru(bpy)3-type photocatalyst. We demonstrate high spatial specificity for intercellular chemical labeling in cultured mammalian cells. Furthermore, as a proof of concept, we activate the dynamic DNA catalyst at cell-cell contacts in response to customized DNA triggers. This study lays the foundation for designing versatile chemical tools with high spatial precision and programmable responsiveness, along with the temporal resolution afforded by photoirradiation, to investigate and manipulate cell-cell interactions.

Spatial multi-omics: deciphering technological landscape of integration of multi-omics and its applications

The emergence of spatial multi-omics has helped address the limitations of single-cell sequencing, which often leads to the loss of spatial context among cell populations. Integrated analysis of the genome, transcriptome, proteome, metabolome, and epigenome has enhanced our understanding of cell biology and the molecular basis of human diseases. Moreover, this approach offers profound insights into the interactions between intracellular and intercellular molecular mechanisms involved in the development, physiology, and pathogenesis of human diseases. In this comprehensive review, we examine current advancements in multi-omics technologies, focusing on their evolution and refinement over the past decade, including improvements in throughput and resolution, modality integration, and accuracy. We also discuss the pivotal contributions of spatial multi-omics in revealing spatial heterogeneity, constructing detailed spatial atlases, deciphering spatial crosstalk in tumor immunology, and advancing translational research and cancer therapy through precise spatial mapping.

Therapeutic potential of cis-targeting bispecific antibodies

The growing clinical success of bispecific antibodies (bsAbs) has led to rapid interest in leveraging dual targeting in order to generate novel modes of therapeutic action beyond mono-targeting approaches. While bsAbs that bind targets on two different cells (trans-targeting) are showing promise in the clinic, the co-targeting of two proteins on the same cell surface through cis-targeting bsAbs (cis-bsAbs) is an emerging strategy to elicit new functionalities. This includes the ability to induce proximity, enhance binding to a target, increase target/cell selectivity, and/or co-modulate function on the cell surface with the goal of altering, reversing, or eradicating abnormal cellular activity that contributes to disease. In this review, we focus on the impact of cis-bsAbs in the clinic, their emerging applications, and untangle the intricacies of improving bsAb discovery and development.

Cell-cell communication: new insights and clinical implications

Multicellular organisms are composed of diverse cell types that must coordinate their behaviors through communication. Cell-cell communication (CCC) is essential for growth, development, differentiation, tissue and organ formation, maintenance, and physiological regulation. Cells communicate through direct contact or at a distance using ligand-receptor interactions. So cellular communication encompasses two essential processes: cell signal conduction for generation and intercellular transmission of signals, and cell signal transduction for reception and procession of signals. Deciphering intercellular communication networks is critical for understanding cell differentiation, development, and metabolism. First, we comprehensively review the historical milestones in CCC studies, followed by a detailed description of the mechanisms of signal molecule transmission and the importance of the main signaling pathways they mediate in maintaining biological functions. Then we systematically introduce a series of human diseases caused by abnormalities in cell communication and their progress in clinical applications. Finally, we summarize various methods for monitoring cell interactions, including cell imaging, proximity-based chemical labeling, mechanical force analysis, downstream analysis strategies, and single-cell technologies. These methods aim to illustrate how biological functions depend on these interactions and the complexity of their regulatory signaling pathways to regulate crucial physiological processes, including tissue homeostasis, cell development, and immune responses in diseases. In addition, this review enhances our understanding of the biological processes that occur after cell-cell binding, highlighting its application in discovering new therapeutic targets and biomarkers related to precision medicine. This collective understanding provides a foundation for developing new targeted drugs and personalized treatments.

An In-Situ-Tag-Generation Proximity Labeling Technology for Recording Cellular Interactions

Obtaining information about cellular interactions is fundamental to the elucidation of physiological and pathological processes. Proximity labeling technologies have been widely used to report cellular interactions in situ; however, the reliance on addition of tag molecules typically restricts their application to regions where tags can readily diffuse, while the application in, for example, solid tissues, is susceptible. Here, we propose an "in-situ-tag-generation mechanism" and develop the GalTag technology based on galactose oxidase (GAO) for recording cellular interactions within three-dimensional biological solid regions. GAO mounted on bait cells can in situ generate bio-orthogonal aldehyde tags as interaction reporters on prey cells. Using GalTag, we monitored the dynamics of cellular interactions and assessed the targeting ability of engineered cells. In particular, we recorded, for the first time, the footprints of Bacillus Calmette-Guérin (BCG) invasion into the bladder tissue of living mice, providing a valuable perspective to elucidate the anti-tumor mechanism of BCG.

Multiscale photocatalytic proximity labeling reveals cell surface neighbors on and between cells

Proximity labeling proteomics (PLP) strategies are powerful approaches to yield snapshots of protein neighborhoods. Here, we describe a multiscale PLP method with adjustable resolution that uses a commercially available photocatalyst, Eosin Y, which upon visible light illumination activates different photo-probes with a range of labeling radii. We applied this platform to profile neighborhoods of the oncogenic epidermal growth factor receptor and orthogonally validated more than 20 neighbors using immunoassays and AlphaFold-Multimer prediction. We further profiled the protein neighborhoods of cell-cell synapses induced by bispecific T cell engagers and chimeric antigen receptor T cells. This integrated multiscale PLP platform maps local and distal protein networks on and between cell surfaces, which will aid in the systematic construction of the cell surface interactome, revealing horizontal signaling partners and reveal new immunotherapeutic opportunities.

Advances in 3D tissue models for neural engineering: self-assembled versus engineered tissue models

Neural tissue engineering has emerged as a promising field that aims to create functional neural tissue for therapeutic applications, drug screening, and disease modelling. It is becoming evident in the literature that this goal requires development of three-dimensional (3D) constructs that can mimic the complex microenvironment of native neural tissue, including its biochemical, mechanical, physical, and electrical properties. These 3D models can be broadly classified as self-assembled models, which include spheroids, organoids, and assembloids, and engineered models, such as those based on decellularized or polymeric scaffolds. Self-assembled models offer advantages such as the ability to recapitulate neural development and disease processes in vitro, and the capacity to study the behaviour and interactions of different cell types in a more realistic environment. However, self-assembled constructs have limitations such as lack of standardised protocols, inability to control the cellular microenvironment, difficulty in controlling structural characteristics, reproducibility, scalability, and lengthy developmental timeframes. Integrating biomimetic materials and advanced manufacturing approaches to present cells with relevant biochemical, mechanical, physical, and electrical cues in a controlled tissue architecture requires alternate engineering approaches. Engineered scaffolds, and specifically 3D hydrogel-based constructs, have desirable properties, lower cost, higher reproducibility, long-term stability, and they can be rapidly tailored to mimic the native microenvironment and structure. This review explores 3D models in neural tissue engineering, with a particular focus on analysing the benefits and limitations of self-assembled organoids compared with hydrogel-based engineered 3D models. Moreover, this paper will focus on hydrogel based engineered models and probe their biomaterial components, tuneable properties, and fabrication techniques that allow them to mimic native neural tissue structures and environment. Finally, the current challenges and future research prospects of 3D neural models for both self-assembled and engineered models in neural tissue engineering will be discussed.

Promotion and Detection of Cell-Cell Interactions through a Bioorthogonal Approach

Manipulation of cell-cell interactions via cell surface modification is crucial in tissue engineering and cell-based therapy. To be able to monitor intercellular interactions, it can also provide useful information for understanding how the cells interact and communicate. We report herein a facile bioorthogonal strategy to promote and monitor cell-cell interactions. It involves the use of a maleimide-appended tetrazine-caged boron dipyrromethene (BODIPY)-based fluorescent probe and a maleimide-substituted bicyclo[6.1.0]non-4-yne (BCN) to modify the membrane of macrophage (RAW 264.7) and cancer (HT29, HeLa, and A431) cells, respectively, via maleimide-thiol conjugation. After modification, the two kinds of cells interact strongly through inverse electron-demand Diels-Alder reaction of the surface tetrazine and BCN moieties. The coupling also disrupts the tetrazine quenching unit, restoring the fluorescence emission of the BODIPY core on the cell-cell interface, and promotes phagocytosis. Hence, this approach can promote and facilitate the detection of intercellular interactions, rendering it potentially useful for macrophage-based immunotherapy.

Use of CRISPRoff and synthetic Notch to modulate and relay endogenous gene expression programs in engineered cells

Uncovering the stimulus-response histories that give rise to cell fates and behaviors is an area of great interest in developmental biology, tissue engineering, and regenerative medicine. A comprehensive accounting of cell experiences that lead to the development of organs and tissues can help us to understand developmental anomalies that may underly disease. Perhaps more provocatively, such a record can also reveal clues as to how to drive cell collective decision-making processes, which may yield predictable cell-based therapies or facilitate production of tissue substitutes for transplantation or in vitro screening of prospective therapies to mitigate disease. Toward this end, various methods have been applied to molecularly trace developmental trajectories and record interaction histories of cells. Typical methods involve artificial gene circuits based on recombinases that activate a suite of fluorescent reporters or CRISPR-Cas9 genome writing technologies whose nucleic acid-based record keeping serves to chronicle cell-cell interactions or past exposure to stimuli of interests. Exciting expansions of the synthetic biology toolkit with artificial receptors that permit establishment of defined input-to-output linkages of cell decision-making processes opens the door to not only record cell-cell interactions, but to also potentiate directed manipulation of the outcomes of such interactions via regulation of carefully selected transgenes. Here, we combine CRISPR-based strategies to genetically and epigenetically manipulate cells to express components of the synthetic Notch receptor platform, a widely used artificial cell signaling module. Our approach gives rise to the ability to conditionally record interactions between human cells, where the record of engagement depends on expression of a state-specific marker of a subset of cells in a population. Further, such signal-competent interactions can be used to direct differentiation of human embryonic stem cells toward pre-selected fates based on assigned synNotch outputs. We also implemented CRISPR-based manipulation of native gene expression profiles to bias outcomes of cell engagement histories in a targeted manner. Thus, we present a useful strategy that gives rise to both state-specific recording of cell-cell interactions as well as methods to intentionally influence products of such cell-cell exchanges.

Bioorthogonal Quinone Methide Decaging Enables Live-Cell Quantification of Tumor-Specific Immune Interactions

Effective antitumor immunity hinges on the specific engagement between tumor and cytotoxic immune cells, especially cytotoxic T cells. Although investigating these intercellular interactions is crucial for characterizing immune responses and guiding immunotherapeutic applications, direct and quantitative detection of tumor-T cell interactions within a live-cell context remains challenging. We herein report a photocatalytic live-cell interaction labeling strategy (CAT-Cell) relying on the bioorthogonal decaging of quinone methide moieties for sensitive and selective investigation and quantification of tumor-T cell interactions. By developing quinone methide-derived probes optimized for capturing cell-cell interactions (CCIs), we demonstrated the capacity of CAT-Cell for detecting CCIs directed by various types of receptor-ligand pairs (e.g., CD40-CD40L, TCR-pMHC) and further quantified the strengths of tumor-T cell interactions that are crucial for evaluating the antitumor immune responses. We further applied CAT-Cell for ex vivo quantification of tumor-specific T cell interactions on splenocyte and solid tumor samples from mouse models. Finally, the broad compatibility and utility of CAT-Cell were demonstrated by integrating it with the antigen-specific targeting system as well as for tumor-natural killer cell interaction detection. By leveraging the bioorthogonal photocatalytic decaging chemistry on quinone methide, CAT-Cell provides a sensitive, tunable, universal, and noninvasive toolbox for unraveling and quantifying the crucial but delicate tumor-immune interactions under live-cell settings.

The diversification of methods for studying cell-cell interactions and communication

No cell lives in a vacuum, and the molecular interactions between cells define most phenotypes. Transcriptomics provides rich information to infer cell-cell interactions and communication, thus accelerating the discovery of the roles of cells within their communities. Such research relies heavily on algorithms that infer which cells are interacting and the ligands and receptors involved. Specific pressures on different research niches are driving the evolution of next-generation computational tools, enabling new conceptual opportunities and technological advances. More sophisticated algorithms now account for the heterogeneity and spatial organization of cells, multiple ligand types and intracellular signalling events, and enable the use of larger and more complex datasets, including single-cell and spatial transcriptomics. Similarly, new high-throughput experimental methods are increasing the number and resolution of interactions that can be analysed simultaneously. Here, we explore recent progress in cell-cell interaction research and highlight the diversification of the next generation of tools, which have yielded a rich ecosystem of tools for different applications and are enabling invaluable discoveries.

DNA nanostructures for exploring cell-cell communication

The process of coordinating between the same or multiple types of cells to jointly execute various instructions in a controlled and carefully regulated environment is a very appealing field. In order to provide clearer insight into the role of cell-cell interactions and the cellular communication of this process in their local communities, several interdisciplinary approaches have been employed to enhance the core understanding of this phenomenon. DNA nanostructures have emerged in recent years as one of the most promising tools in exploring cell-cell communication and interactions due to their programmability and addressability. Herein, this review is dedicated to offering a new perspective on using DNA nanostructures to explore the progress of cell-cell communication. After briefly outlining the anchoring strategy of DNA nanostructures on cell membranes and the subsequent dynamic regulation of DNA nanostructures, this paper highlights the significant contribution of DNA nanostructures in monitoring cell-cell communication and regulating its interactions. Finally, we provide a quick overview of the current challenges and potential directions for the application of DNA nanostructures in cellular communication and interactions.

Understanding Macrophage-Tumor Interactions: Insights from Single-Cell Behavior Monitoring in a Sessile Microdroplet System

Interaction between tumor-associated macrophages and tumor cells is crucial for tumor development, metastasis, and the related immune process. However, the macrophages are highly heterogeneous spanning from anti-tumorigenic to pro-tumorigenic, which needs to be understood at the single-cell level. Herein, a sessile microdroplet system designed for monitoring cellular behavior and analyzing intercellular interaction, demonstrated with macrophage-tumor cell pairs is presented. An automatic procedure based on the inkjet printing method is utilized for the precise pairing and co-encapsulation of heterotypic cells within picoliter droplets. The sessile nature of microdroplets ensures controlled fusion and provides stable environments conducive to adherent cell culture. The nitric oxide generation and morphological changes over incubation are explored to reveal the complicated interactions from a single-cell perspective. The immune response of macrophages under distinct cellular microenvironments is recorded. The results demonstrate that the tumor microenvironment displays a modulating role in polarizing macrophages from anti-tumorigenic into pro-tumorigenic phenotype. The approach provides a versatile and compatible platform to investigate intercellular interaction at the single-cell level, showing promising potential for advancing single-cell behavior studies.

A Proximity-Dependent Biosensor System for Visualizing Cell-Cell Interactions Induced by Therapeutic Antibodies

Despite the promise of therapeutic antibodies in engaging the immune system to eliminate malignant cells, many aspects of the complex interplay between immune cells and cancer cells induced by antibody therapy remain incompletely understood. This study aimed to develop a biosensor system that can evaluate direct cell-cell physical contact and interactions between immune effector and target cells induced by therapeutic antibodies in physiologically relevant environments. The system uses two structural complementary luciferase units (SmBit and LgBit) expressed on the respective membranes of effector and target cells. Upon cell-cell contact, the two subunits form active NanoLuc, generating a luminescent signal, allowing for real-time monitoring of cell-cell interactions and quantitatively assessing the pharmacological effects of therapeutic antibodies. We optimized the system to ensure selectivity by adjusting the spacer lengths between two luciferase units to minimize interference from nonspecific intercellular contact. The system was applied to quantitatively monitor cell-cell interactions between NK and target cells induced by rituximab and between T and target cells induced by blinatumomab in a 3D cell culture system. The biosensor system has the potential to characterize antibody pharmacology through a deeper understanding of antibody-mediated cell-cell interactions.

Universal recording of immune cell interactions in vivo

Immune cells rely on transient physical interactions with other immune and non-immune populations to regulate their function1. To study these 'kiss-and-run' interactions directly in vivo, we previously developed LIPSTIC (labelling immune partnerships by SorTagging intercellular contacts)2, an approach that uses enzymatic transfer of a labelled substrate between the molecular partners CD40L and CD40 to label interacting cells. Reliance on this pathway limited the use of LIPSTIC to measuring interactions between CD4+ T helper cells and antigen-presenting cells, however. Here we report the development of a universal version of LIPSTIC (uLIPSTIC), which can record physical interactions both among immune cells and between immune and non-immune populations irrespective of the receptors and ligands involved. We show that uLIPSTIC can be used, among other things, to monitor the priming of CD8+ T cells by dendritic cells, reveal the steady-state cellular partners of regulatory T cells and identify germinal centre-resident T follicular helper cells on the basis of their ability to interact cognately with germinal centre B cells. By coupling uLIPSTIC with single-cell transcriptomics, we build a catalogue of the immune populations that physically interact with intestinal epithelial cells at the steady state and profile the evolution of the interactome of lymphocytic choriomeningitis virus-specific CD8+ T cells in multiple organs following systemic infection. Thus, uLIPSTIC provides a broadly useful technology for measuring and understanding cell-cell interactions across multiple biological systems.

Computational cell-cell interaction technologies drive mechanistic and biomarker discovery in the tumor microenvironment

Complex networks of cell-cell interactions (CCIs) within the tumor microenvironment (TME) play a crucial role in cancer persistence. These communication axes represent prime targets for therapeutic intervention, but our incomplete understanding of the cellular heterogeneity and interacting partners within the TME remains a stubborn barrier to complete drug responses. This review outlines recent advances in the study of CCIs that leverage single-cell RNA sequencing (scRNA-seq) and spatial transcriptomics (ST) technologies that can clarify TME dynamics. We anticipate that these strategies will promote discovery of CCIs critical to the tumor-immune interface and will, by extension, expand the repertoire of druggable tumor biomarkers.

Mapping Cellular Interactions from Spatially Resolved Transcriptomics Data

Cell-cell communication (CCC) is essential to how life forms and functions. However, accurate, high-throughput mapping of how expression of all genes in one cell affects expression of all genes in another cell is made possible only recently, through the introduction of spatially resolved transcriptomics technologies (SRTs), especially those that achieve single cell resolution. However, significant challenges remain to analyze such highly complex data properly. Here, we introduce a Bayesian multi-instance learning framework, spacia, to detect CCCs from data generated by SRTs, by uniquely exploiting their spatial modality. We highlight spacia's power to overcome fundamental limitations of popular analytical tools for inference of CCCs, including losing single-cell resolution, limited to ligand-receptor relationships and prior interaction databases, high false positive rates, and most importantly the lack of consideration of the multiple-sender-to-one-receiver paradigm. We evaluated the fitness of spacia for all three commercialized single cell resolution ST technologies: MERSCOPE/Vizgen, CosMx/Nanostring, and Xenium/10X. Spacia unveiled how endothelial cells, fibroblasts and B cells in the tumor microenvironment contribute to Epithelial-Mesenchymal Transition and lineage plasticity in prostate cancer cells. We deployed spacia in a set of pan-cancer datasets and showed that B cells also participate in PDL1/PD1 signaling in tumors. We demonstrated that a CD8+ T cell/PDL1 effectiveness signature derived from spacia analyses is associated with patient survival and response to immune checkpoint inhibitor treatments in 3,354 patients. We revealed differential spatial interaction patterns between γδ T cells and liver hepatocytes in healthy and cancerous contexts. Overall, spacia represents a notable step in advancing quantitative theories of cellular communications.

SpSrtA-Catalyzed Isopeptide Ligation on Lysine Residues

Sortase-mediated ligation (SML) is widely used for protein bioconjugation. However, the sortase used in this strategy typically recognizes only the N-terminal oligoglycine, which is absent in most natural proteins. To broaden the spectrum of substrates compatible with SML, we focus on a novel sortase, sortase A from Streptococcus pneumoniae (SpSrtA), known for its expanded substrate specificity (N-terminal glycine, alanine, and serine). We present the first evidence showing that the reported SpSrtA mutant (SpSrtA*) can modify lysine residues in itself and other proteins. The modification sites of SpSrtA* were identified through LC-MS/MS analysis. Moreover, we discovered an optimal lysine-containing peptide tag by fusing it onto sfGFP, resulting in a labeling efficiency of 57%. Inspired by this, we applied the method to modify proteins on microorganism surfaces up to 13.5-fold. To enhance labeling efficiency, we fused the SpSrtA* onto a surface protein and achieved a 2.64-fold improvement. We further developed a high-throughput yeast display screening method for the directed evolution of SpSrtA*, achieving a 10-fold improvement in the labeling efficiency of this surface protein. Our study provides a novel strategy for modifying the lysine residues that will be a powerful addition to the protein bioconjugation toolbox.

Deep Learning Image Recognition-Assisted Atomic Force Microscopy for Single-Cell Efficient Mechanics in Co-culture Environments

Atomic force microscopy (AFM)-based force spectroscopy assay has become an important method for characterizing the mechanical properties of single living cells under aqueous conditions, but a disadvantage is its reliance on manual operation and experience as well as the resulting low throughput. Particularly, providing a capacity to accurately identify the type of the cell grown in co-culture environments without the need of fluorescent labeling will further facilitate the applications of AFM in life sciences. Here, we present a study of deep learning image recognition-assisted AFM, which not only enables fluorescence-independent recognition of the identity of single co-cultured cells but also allows efficient downstream AFM force measurements of the identified cells. With the use of the deep learning-based image recognition model, the viability and type of individual cells grown in co-culture environments were identified directly from the optical bright-field images, which were confirmed by the following cell growth and fluorescent labeling results. Based on the image recognition results, the positional relationship between the AFM probe and the targeted cell was automatically determined, allowing the precise movement of the AFM probe to the target cell to perform force measurements. The experimental results show that the presented method was applicable not only to the conventional (microsphere-modified) AFM probe used in AFM indentation assay for measuring the Young's modulus of single co-cultured cells but also to the single-cell probe used in AFM-based single-cell force spectroscopy (SCFS) assay for measuring the adhesion forces of single co-cultured cells. The study illustrates deep learning imaging recognition-assisted AFM as a promising approach for label-free and high-throughput detection of single-cell mechanics under co-culture conditions, which will facilitate unraveling the mechanical cues involved in cell-cell interactions in their native states at the single-cell level and will benefit the field of mechanobiology.

Enabling neighbour labelling: using synthetic biology to explore how cells influence their neighbours

Cell-cell interactions are central to development, but exploring how a change in any given cell relates to changes in the neighbour of that cell can be technically challenging. Here, we review recent developments in synthetic biology and image analysis that are helping overcome this problem. We highlight the opportunities presented by these advances and discuss opportunities and limitations in applying them to developmental model systems.

Proximity extracellular protein-protein interaction analysis of EGFR using AirID-conjugated fragment of antigen binding

Receptor proteins, such as epidermal growth factor receptor (EGFR), interact with other proteins in the extracellular region of the cell membrane to drive intracellular signalling. Therefore, analysis of extracellular protein-protein interactions (exPPIs) is important for understanding the biological function of receptor proteins. Here, we present an approach using a proximity biotinylation enzyme (AirID) fusion fragment of antigen binding (FabID) to analyse the proximity exPPIs of EGFR. AirID was C-terminally fused to the Fab fragment against EGFR (EGFR-FabID), which could then biotinylate the extracellular region of EGFR in several cell lines. Liquid Chromatography-Mass Spectrometry (LC-MS/MS) analysis indicated that many known EGFR interactors were identified as proximity exPPIs, along with many unknown candidate interactors, using EGFR-FabID. Interestingly, these proximity exPPIs were influenced by treatment with EGF ligand and its specific kinase inhibitor, gefitinib. These results indicate that FabID provides accurate proximity exPPI analysis of target receptor proteins on cell membranes with ligand and drug responses.

Secretory GFP reconstitution labeling of neighboring cells interrogates cell-cell interactions in metastatic niches

Cancer cells inevitably interact with neighboring host tissue-resident cells during the process of metastatic colonization, establishing a metastatic niche to fuel their survival, growth, and invasion. However, the underlying mechanisms in the metastatic niche are yet to be fully elucidated owing to the lack of methodologies for comprehensively studying the mechanisms of cell-cell interactions in the niche. Here, we improve a split green fluorescent protein (GFP)-based genetically encoded system to develop secretory glycosylphosphatidylinositol-anchored reconstitution-activated proteins to highlight intercellular connections (sGRAPHIC) for efficient fluorescent labeling of tissue-resident cells that neighbor on and putatively interact with cancer cells in deep tissues. The sGRAPHIC system enables the isolation of metastatic niche-associated tissue-resident cells for their characterization using a single-cell RNA sequencing platform. We use this sGRAPHIC-leveraged transcriptomic platform to uncover gene expression patterns in metastatic niche-associated hepatocytes in a murine model of liver metastasis. Among the marker genes of metastatic niche-associated hepatocytes, we identify Lgals3, encoding galectin-3, as a potential pro-metastatic factor that accelerates metastatic growth and invasion.

Multi-scale photocatalytic proximity labeling reveals cell surface neighbors on and between cells

The cell membrane proteome is the primary biohub for cell communication, yet we are only beginning to understand the dynamic protein neighborhoods that form on the cell surface and between cells. Proximity labeling proteomics (PLP) strategies using chemically reactive probes are powerful approaches to yield snapshots of protein neighborhoods but are currently limited to one single resolution based on the probe labeling radius. Here, we describe a multi-scale PLP method with tunable resolution using a commercially available histological dye, Eosin Y, which upon visible light illumination, activates three different photo-probes with labeling radii ranging from ∼100 to 3000 Å. We applied this platform to profile neighborhoods of the oncogenic epidermal growth factor receptor (EGFR) and orthogonally validated >20 neighbors using immuno-assays and AlphaFold-Multimer prediction that generated plausible binary interaction models. We further profiled the protein neighborhoods of cell-cell synapses induced by bi-specific T-cell engagers (BiTEs) and chimeric antigen receptor (CAR)T cells at longer length scales. This integrated multi-scale PLP platform maps local and distal protein networks on cell surfaces and between cells. We believe this information will aid in the systematic construction of the cell surface interactome and reveal new opportunities for immunotherapeutics.

Monitoring the Cascade of Tumor-specific Immune Response in vivo via Chemoenzymatic Proximity Labeling

Monitoring the highly dynamic and complex immune response remains a great challenge owing to the lack of reliable and specific approaches. Here, we develop a strategy to monitor the cascade of tumor immune response through the cooperation of pore-forming alginate gel with chemoenzymatic proximity-labeling. A macroporous gel containing tumor-associated antigens, adjuvants, and pro-inflammatory cytokines is utilized to recruit endogenous DCs and enhance their maturation in vivo. The mature DCs are then modified with GDP-fucose-fucosyltransferase (GDP-Fuc-Fuct) via the self-catalysis of fucosyltransferase (Fuct). Following the migration of the obtained Fuct-DCs to the draining lymph nodes (dLNs), the molecular recognition mediated interaction of DCs and T cells leads to the successful decoration of T cells with GDP-Fuc-azide through the Fuct catalyzed proximity-labeling. Therefore, the activated tumor-specific T cells in dLNs and tumors can be identified through bioorthogonal labeling, opening up a new avenue for studying the immune mechanism of tumors in situ.

Chemical biology tools for protein labelling: insights into cell-cell communication

Multicellular organisms require carefully orchestrated communication between and within cell types and tissues, and many unicellular organisms also sense their context and environment, sometimes coordinating their responses. This review highlights contributions from chemical biology in discovering and probing mechanisms of cell-cell communication. We focus on chemical tools for labelling proteins in a cellular context and how these can be applied to decipher the target receptor of a signalling molecule, label a receptor of interest in situ to understand its biology, provide a read-out of protein activity or interactions in downstream signalling pathways, or discover protein-protein interactions across cell-cell interfaces.

A Comparison of Cell-Cell Interaction Prediction Tools Based on scRNA-seq Data

Computational prediction of cell-cell interactions (CCIs) is becoming increasingly important for understanding disease development and progression. We present a benchmark study of available CCI prediction tools based on single-cell RNA sequencing (scRNA-seq) data. By comparing prediction outputs with a manually curated gold standard for idiopathic pulmonary fibrosis (IPF), we evaluated prediction performance and processing time of several CCI prediction tools, including CCInx, CellChat, CellPhoneDB, iTALK, NATMI, scMLnet, SingleCellSignalR, and an ensemble of tools. According to our results, CellPhoneDB and NATMI are the best performer CCI prediction tools, among the ones analyzed, when we define a CCI as a source-target-ligand-receptor tetrad. In addition, we recommend specific tools according to different types of research projects and discuss the possible future paths in the field.

Single-cell A/B testing for cell-cell communication

A new method developed by Francisco Quintana's group, systematic perturbation of encapsulated associated cells followed by sequencing (SPEAC-seq), applies a CRISPR screen to co-cultured interacting cells to identify the ligands mediating cell-cell communication. Using this approach, the authors discover the molecular basis of a microglia-astrocyte feedback loop that suppresses neuroinflammatory disease.

Cellular-scale proximity labeling for recording cell spatial organization in mouse tissues

Proximity labeling has emerged as a powerful strategy for interrogating cell-cell interactions. However, the nanometer-scale labeling radius impedes the use of current methods for indirect cell communications and makes recording cell spatial organization in tissue samples difficult. Here, we develop quinone methide-assisted identification of cell spatial organization (QMID), a chemical strategy with the labeling radius matching the cell dimension. The activating enzyme is installed on the surface of bait cells, which produces QM electrophiles that can diffuse across micrometers and label proximal prey cells independent of cell-cell contacts. In cell coculture, QMID reveals gene expression of macrophages that are regulated by spatial proximity to tumor cells. Furthermore, QMID enables labeling and isolation of proximal cells of CD4⁺ and CD8⁺ T cells in the mouse spleen, and subsequent single-cell RNA sequencing uncovers distinctive cell populations and gene expression patterns within the immune niches of specific T cell subtypes. QMID should facilitate dissecting cell spatial organization in various tissues.

Deciphering Cell-Cell Interactions with Integrative Single-Cell Secretion Profiling

Cell-cell interactions are the fundamental behaviors to regulate cellular activities. A comprehensive evaluation of intercellular interactions requires direct profiling of various signaling behaviors simultaneously at the single-cell level, which remains lacking. Herein, an integrative single-cell secretion analysis platform is presented to profile different secreted factors (four proteins, three extracellular vesicles (EV) phenotypes), spatial distances, and migration information (distances and direction) simultaneously from high-throughput paired single cells using an antibody-barcode microchip. Applying the platform to analyze the tumor-stromal and tumor-immune interactions with the human oral squamous cell carcinoma (OSCC) cell lines and primary OSCC cells reveals that the initial distances between cells would determine their migratory distances and direction to approach stable organization. The cell-cell in close proximity enhances protein secretions while attenuating EV secretions. Migration has a more profound correlation with protein secretions than EV secretions, in which absolute migration distance affects protein secretions significantly but not the direction. These findings highlight the significance of spatial organization in regulating cell signaling behaviors and demonstrate that the integrative single-cell secretion profiling platform is well-suited for a comprehensive dissection of intercellular communication and interactions, providing new avenues for understanding cell-cell interaction biology and how different signaling behaviors coordinate within the tumor microenvironment.

Universal recording of cell-cell contacts in vivo for interaction-based transcriptomics

Cellular interactions are essential for tissue organization and functionality. In particular, immune cells rely on direct and usually transient interactions with other immune and non-immune populations to specify and regulate their function. To study these "kiss-and-run" interactions directly in vivo, we previously developed LIPSTIC (Labeling Immune Partnerships by SorTagging Intercellular Contacts), an approach that uses enzymatic transfer of a labeled substrate between the molecular partners CD40L and CD40 to label interacting cells. Reliance on this pathway limited the use of LIPSTIC to measuring interactions between CD4+ helper T cells and antigen presenting cells, however. Here, we report the development of a universal version of LIPSTIC (uLIPSTIC), which can record physical interactions both among immune cells and between immune and non-immune populations irrespective of the receptors and ligands involved. We show that uLIPSTIC can be used, among other things, to monitor the priming of CD8+ T cells by dendritic cells, reveal the cellular partners of regulatory T cells in steady state, and identify germinal center (GC)-resident T follicular helper (Tfh) cells based on their ability to interact cognately with GC B cells. By coupling uLIPSTIC with single-cell transcriptomics, we build a catalog of the immune populations that physically interact with intestinal epithelial cells (IECs) and find evidence of stepwise acquisition of the ability to interact with IECs as CD4+ T cells adapt to residence in the intestinal tissue. Thus, uLIPSTIC provides a broadly useful technology for measuring and understanding cell-cell interactions across multiple biological systems.

The Hippo signaling pathway in gastric cancer

Gastric cancer (GC) is an aggressive malignant disease which still lacks effective early diagnosis markers and targeted therapies, representing the fourth-leading cause of cancer-associated death worldwide. The Hippo signaling pathway plays crucial roles in organ size control and tissue homeostasis under physiological conditions, yet its aberrations have been closely associated with several hallmarks of cancer. The last decade witnessed a burst of investigations dissecting how Hippo dysregulation contributes to tumorigenesis, highlighting the therapeutic potential of targeting this pathway for tumor intervention. In this review, we systemically document studies on the Hippo pathway in the contexts of gastric tumor initiation, progression, metastasis, acquired drug resistance, and the emerging development of Hippo-targeting strategies. By summarizing major open questions in this field, we aim to inspire further in-depth understanding of Hippo signaling in GC development, as well as the translational implications of targeting Hippo for GC treatment.

Enzyme-Instructed Peptide Assembly Favored by Preorganization for Cancer Cell Membrane Engineering

Innovative methods for engineering cancer cell membranes promise to manipulate cell-cell interactions and boost cell-based cancer therapeutics. Here, we illustrate an in situ approach to selectively modify cancer cell membranes by employing an enzyme-instructed peptide self-assembly (EISA) strategy. Using three phosphopeptides (pY1, pY2, and pY3) targeting the membrane-bound epidermal growth factor receptor (EGFR) and differing in just one phosphorylated tyrosine, we reveal that site-specific phosphorylation patterns in pY1, pY2, and pY3 can distinctly command their preorganization levels, self-assembling kinetics, and spatial distributions of the resultant peptide assemblies in cellulo. Overall, pY1 is the most capable of producing preorganized assemblies and shows the fastest dephosphorylation reaction in the presence of alkaline phosphatase (ALP), as well as the highest binding affinity for EGFR after dephosphorylation. Consequently, pY1 exhibits the greatest capacity to construct stable peptide assemblies on cancer cell membranes with the assistance of both ALP and EGFR. We further use peptide-protein and peptide-peptide co-assembly strategies to apply two types of antigens, namely ovalbumin (OVA) protein and dinitrophenyl (DNP) hapten respectively, on cancer cell membranes. This study demonstrates a very useful technique for the in situ construction of membrane-bound peptide assemblies around cancer cells and implies a versatile strategy to artificially enrich cancer cell membrane components for potential cancer immunotherapy.

Types of cell culture inserts affect cell crosstalk between co-cultured macrophages and adipocytes

Cell culture inserts offer an in vivo-like microenvironment to investigate cell-cell interactions between co-cultivated cells. However, it is unclear if types of inserts affect cell crosstalk. Here, we developed an environment-friendly cell culture insert, XL-insert, which can reduce plastic waste with lower cost. We compared XL insert with two types of commercial disposable culture inserts, Koken® insert with atelocollagen membrane (Col-inserts) and Falcon® inserts with plastic membrane (PET-inserts) on cell-cell interactions in co-cultivated THP-1 macrophages and OP9 adipocytes. Scanning electron microscope, immunoassay and imaging analysis showed that among three types of inserts, XL-inserts allowed cytokines from co-cultivated macrophages and adipocytes to diffuse freely and offered preferable in vivo-like microenvironment for cell-cell interactions. PET-inserts showed limitations for intercellular communication due to some pores being blocked by somas on the membrane that caused much lower permeability for cytokines passing through. Col-inserts blocked large sized cytokines but allowed small sized molecules to permeate resulting in improved lipid accumulation and adiponectin secretion in OP9 adipocytes. Taken together, our data demonstrated that membrane type and pore size on the membrane affect the cross-talk between co-cultivated cells very differently. Some previous co-culture studies might have different results if the inserts were changed.

Synthetic Notch receptors and their applications to study cell-cell contacts in vivo

Physical cell-cell interaction is a fundamental mechanism that controls the development and physiology of multicellular organisms. However, methods to study cell contact within complex tissues are limited. In a recent issue of Science, Zhang et al. developed synthetic Notch (synNotch)-based tools that can monitor and trace cell-cell contacts in mammals.

Targeted activation in localized protein environments via deep red photoredox catalysis

State-of-the-art photoactivation strategies in chemical biology provide spatiotemporal control and visualization of biological processes. However, using high-energy light (λ < 500 nm) for substrate or photocatalyst sensitization can lead to background activation of photoactive small-molecule probes and reduce its efficacy in complex biological environments. Here we describe the development of targeted aryl azide activation via deep red-light (λ = 660 nm) photoredox catalysis and its use in photocatalysed proximity labelling. We demonstrate that aryl azides are converted to triplet nitrenes via a redox-centric mechanism and show that its spatially localized formation requires both red light and a photocatalyst-targeting modality. This technology was applied in different colon cancer cell systems for targeted protein environment labelling of epithelial cell adhesion molecule (EpCAM). We identified a small subset of proteins with previously known and unknown association to EpCAM, including CDH3, a clinically relevant protein that shares high tumour-selective expression with EpCAM.

Image-based crosstalk analysis of cell-cell interactions during sprouting angiogenesis using blood-vessel-on-a-chip

BACKGROUND

Sprouting angiogenesis is an important mechanism for morphogenetic phenomena, including organ development, wound healing, and tissue regeneration. In regenerative medicine, therapeutic angiogenesis is a clinical solution for recovery from ischemic diseases. Mesenchymal stem cells (MSCs) have been clinically used given their pro-angiogenic effects. MSCs are reported to promote angiogenesis by differentiating into pericytes or other vascular cells or through cell-cell communication using multiple protein-protein interactions. However, how MSCs physically contact and move around ECs to keep the sprouting angiogenesis active remains unknown.

METHODS

We proposed a novel framework of EC-MSC crosstalk analysis using human umbilical vein endothelial cells (HUVECs) and MSCs obtained from mice subcutaneous adipose tissue on a 3D in vitro model, microvessel-on-a-chip, which allows cell-to-tissue level study. The microvessels were fabricated and cultured for 10 days in a collagen matrix where MSCs were embedded.

RESULTS

Immunofluorescence imaging using a confocal laser microscope showed that MSCs smoothed the surface of the microvessel and elongated the angiogenic sprouts by binding to the microvessel's specific microstructures. Additionally, three-dimensional modeling of HUVEC-MSC intersections revealed that MSCs were selectively located around protrusions or roots of angiogenic sprouts, whose surface curvature was excessively low or high, respectively.

CONCLUSIONS

The combination of our microvessel-on-a-chip system for 3D co-culture and image-based crosstalk analysis demonstrated that MSCs are selectively localized to concave-convex surfaces on scaffold structures and that they are responsible for the activation and stabilization of capillary vessels.

Proteomic mapping of intercellular synaptic environments via flavin-dependent photoredox catalysis

Receptor-ligand interactions play essential signaling roles within intercellular contact regions. This is particularly important within the context of the immune synapse where protein communication at the surface of physically interacting T cells and antigen-presenting cells regulate downstream immune signaling responses. To identify protein microenvironments within immunological synapses, we combined a flavin-dependent photocatalytic labeling strategy with quantitative mass spectrometry-based proteomics. Using α-PD-L1 or α-PD-1 single-domain antibody (VHH)-based photocatalyst targeting modalities, we profiled protein microenvironments within the intercellular region of an immune synapse-forming co-culture system. In addition to enrichment of both PD-L1 and PD-1 with either targeting modality, we also observed enrichment of both known immune synapse residing receptor-ligand pairs and surface proteins, as well as previously unknown synapse residing proteins.

Use of intercellular proximity labeling to quantify and decipher cell-cell interactions directed by diversified molecular pairs

FucoID is an intercellular proximity labeling technique for studying cell-cell interactions (CCIs) via fucosyltransferase (FT)-meditated fucosyl-biotinylation, which has been applied to probe antigen-specific dendritic cell (DC)-T cell interactions. In this system, bait cells of interest with cell surface-anchored FT are used to capture the interacting prey cells by transferring a biotin-modified substrate to prey cells. Here, we leveraged FucoID to study CCIs directed by different molecular pairs, e.g., programmed cell death protein-1(PD-1)/programmed cell death protein-ligand-1 (PD-L1), and identify unknown or little studied CCIs, e.g., the interaction of DCs and B cells. To expand the application of FucoID to complex systems, we also synthesized site-specific antibody-based FT conjugate, which substantially improves the ability of FucoID to probe molecular signatures of specific CCI when cells of interest (bait cells) cannot be purified, e.g., in clinical samples. Collectively, these studies demonstrate the general applicability of FucoID to study unknown CCIs in complex systems at a molecular resolution.

Engineering Biomimetic Trogocytosis with Farnesylated Chemically Self-Assembled Nanorings

Inspired by the natural intercellular material-transfer process of trans-endocytosis or trogocytosis, we proposed that targeted farnesylated chemically self-assembled nanorings (f-CSANs) could serve as a biomimetic trogocytosis vehicle for engineering directional cargo transfer between cells, thus allowing cell-cell interactions to be monitored and facilitating cell-cell communications. The membranes of sender cells were stably modified by hydrophobic insertion with the targeted f-CSANs, which were efficiently transferred to receiver cells expressing the appropriate receptors by endocytosis. CSAN-assisted cell-cell cargo transfer (C4T) was demonstrated to be receptor specific and dependent on direct cell-cell interactions, the rate of receptor internalization, and the level of receptor expression. In addition, C4T was shown to facilitate cell-to-cell delivery of an apoptosis inducing drug, as wells as antisense oligonucleotides. Taken together, the C4T approach is a potentially versatile biomimetic trogocytosis platform that can be deployed as a macro-chemical biological tool for monitoring cell-cell interactions and engineering cell-cell communications.

Recent Advances in DNA-Based Cell Surface Engineering for Biological Applications

Due to its excellent programmability and biocompatibility, DNA molecule has unique advantages in cell surface engineering. Recent progresses provide a reliable and feasible way to engineer cell surfaces with diverse DNA molecules and DNA nanostructures. The abundant form of DNA nanostructures has greatly expanded the toolbox of DNA-based cell surface engineering and gave rise to a variety of novel and fascinating applications. In this review, we summarize recent advances in DNA-based cell surface engineering and its biological applications. We first introduce some widely used methods of immobilizing DNA molecules on cell surfaces and their application features. Then we discuss the approaches of employing DNA nanostructures and dynamic DNA nanotechnology as elements for creating functional cell surfaces. Finally, we review the extensive biological applications of DNA-based cell surface engineering and discuss the challenges and prospects of DNA-based cell surface engineering.

Spatiotemporal multiplexed immunofluorescence imaging of living cells and tissues with bioorthogonal cycling of fluorescent probes

Cells in complex organisms undergo frequent functional changes, but few methods allow comprehensive longitudinal profiling of living cells. Here we introduce scission-accelerated fluorophore exchange (SAFE), a method for multiplexed temporospatial imaging of living cells with immunofluorescence. SAFE uses a rapid bioorthogonal click chemistry to remove immunofluorescent signals from the surface of labeled cells, cycling the nanomolar-concentration reagents in seconds and enabling multiple rounds of staining of the same samples. It is non-toxic and functional in both dispersed cells and intact living tissues. We demonstrate multiparameter (n ≥ 14), non-disruptive imaging of murine peripheral blood mononuclear and bone marrow cells to profile cellular differentiation. We also show longitudinal multiplexed imaging of bone marrow progenitor cells as they develop into neutrophils over 6 days and real-time multiplexed cycling of living mouse hepatic tissues. We anticipate that SAFE will find broad utility for investigating physiologic dynamics in living systems.

A single-cell human islet interactome atlas identifies disrupted autocrine and paracrine communications in type 2 diabetes

A sensible control of hormone secretion from pancreatic islets requires concerted inter-cellular communications, but a comprehensive picture of the whole islet interactome is presently missing. Single-cell transcriptomics allows to overcome this and we used here a single-cell dataset from type 2 diabetic (T2D) and non-diabetic (ND) donors to leverage islet interaction networks. The single-cell dataset contains 3046 cells classified in 7 cell types. The interactions across cell types in T2D and ND were obtained and resulting networks analysed to identify high-centrality genes and altered interactions in T2D. The T2D interactome displayed a higher number of interactions (10 787) than ND (9707); 1289 interactions involved beta cells (1147 in ND). High-centrality genes included EGFR, FGFR1 and FGFR2, important for cell survival and proliferation. In conclusion, this analysis represents the first in silico model of the human islet interactome, enabling the identification of signatures potentially relevant for T2D pathophysiology.

Visualization of intercellular cargo transfer using upconverting nanoparticles

Cell-cell communication is important for cellular differentiation, organ function, and immune responses. In intercellular communication, the extracellular vesicles (EVs) play a significant role in delivering the cargo molecules such as genes, proteins, and enzymes, to regulate and control the ability of the recipient cells. In this study, the observation of intercellular cargo transfer via dual-colour imaging using upconverting nanoparticles (UCNPs) has been demonstrated. Using this technique, the intercellular transport via contact-dependent and contact-independent signaling in live HeLa cells was clearly visualized with real-time, long-term single-vesicle tracking. Furthermore, it was demonstrated that the endocytosed UCNPs can be transmitted with the encapsulation of EVs labelled with fluorescent proteins.

Detection of cell-cell interactions via photocatalytic cell tagging

The growing appreciation of immune cell-cell interactions within disease environments has led to extensive efforts to develop immunotherapies. However, characterizing complex cell-cell interfaces in high resolution remains challenging. Thus, technologies leveraging therapeutic-based modalities to profile intercellular environments offer opportunities to study cell-cell interactions with molecular-level insight. We introduce photocatalytic cell tagging (PhoTag) for interrogating cell-cell interactions using single-domain antibodies (VHHs) conjugated to photoactivatable flavin-based cofactors. Following irradiation with visible light, the flavin photocatalyst generates phenoxy radical tags for targeted labeling. Using this technology, we demonstrate selective synaptic labeling across the PD-1/PD-L1 axis in antigen-presenting cell-T cell systems. In combination with multiomics single-cell sequencing, we monitored interactions between peripheral blood mononuclear cells and Raji PD-L1 B cells, revealing differences in transient interactions with specific T cell subtypes. The utility of PhoTag in capturing cell-cell interactions will enable detailed profiling of intercellular communication across different biological systems.

Listening in on Multicellular Communication in Human Tissue Immunology

Immune responses in human tissues rely on the concerted action of different cell types. Inter-cellular communication shapes both the function of the multicellular interaction networks and the fate of the individual cells that comprise them. With the advent of new methods to profile and experimentally perturb primary human tissues, we are now in a position to systematically identify and mechanistically dissect these cell-cell interactions and their modulators. Here, we introduce the concept of multicellular hubs, functional modules of immune responses in tissues. We outline a roadmap to discover multicellular hubs in human tissues and discuss how emerging technologies may further accelerate progress in this field.

Non-destructive monitoring of 3D cell cultures: new technologies and applications

3D cell cultures are becoming the new standard for cell-based in vitro research, due to their higher transferrability toward in vivo biology. The lack of established techniques for the non-destructive quantification of relevant variables, however, constitutes a major barrier to the adoption of these technologies, as it increases the resources needed for the experimentation and reduces its accuracy. In this review, we aim at addressing this limitation by providing an overview of different non-destructive approaches for the evaluation of biological features commonly quantified in a number of studies and applications. In this regard, we will cover cell viability, gene expression, population distribution, cell morphology and interactions between the cells and the environment. This analysis is expected to promote the use of the showcased technologies, together with the further development of these and other monitoring methods for 3D cell cultures. Overall, an extensive technology shift is required, in order for monolayer cultures to be superseded, but the potential benefit derived from an increased accuracy of in vitro studies, justifies the effort and the investment.

Antigen-Specific T Cell Detection via Photocatalytic Proximity Cell Labeling (PhoXCELL)

Quantitative detection and characterization of antigen-specific T cells are crucial to our understanding of immune responses as well as the development of new immunotherapies. Herein, we report a spatiotemporally resolved method for the detection and quantification of cell-cell interactions via Photocatalytic proXimity CELl Labeling (PhoXCELL). The biocompatible photosensitizer dibromofluorescein (DBF) was leveraged and optimized as a nongenetic alternative of enzymatic approaches for efficient generation of singlet oxygen upon photoirradiation (520 nm) on the cell surface, which allowed the subsequent labeling of nearby oxidized proteins with primary aliphatic amine-based probes. We demonstrated that DBF-functionalized dendritic cells (DCs) could spatiotemporally label interacting T cells in immune synapses via rapid photoirradiation with quantitatively discriminated interaction strength, which revealed distinct gene signatures for T cells that strongly interact with antigen-pulsed DCs. Furthermore, we employed PhoXCELL to simultaneously detect tumor antigen-specific CD8⁺ as well as CD4⁺ T cells from tumor-infiltrating lymphocytes and draining lymph nodes in murine tumor models, enabling PhoXCELL as a powerful platform to identify antigen-specific T cells in T cell receptor (TCR)-relevant personal immunotherapy.