Single-cell Perspective Research Articles

The heterogeneity of erythroid cells: insight at the single-cell transcriptome level.

Erythroid cells, the most prevalent cell type in blood, are one of the earliest products and permeate through the entire process of hematopoietic development in the human body, the oxygen-transporting function of which is crucial for maintaining overall health and life support. Previous investigations into erythrocyte differentiation and development have primarily focused on population-level analyses, lacking the single-cell perspective essential for comprehending the intricate pathways of erythroid maturation, differentiation, and the encompassing cellular heterogeneity. The continuous optimization of single-cell transcriptome sequencing technology, or single-cell RNA sequencing (scRNA-seq), provides a powerful tool for life sciences research, which has a particular superiority in the identification of unprecedented cell subgroups, the analyzing of cellular heterogeneity, and the transcriptomic characteristics of individual cells. Over the past decade, remarkable strides have been taken in the realm of single-cell RNA sequencing technology, profoundly enhancing our understanding of erythroid cells. In this review, we systematically summarize the recent developments in single-cell transcriptome sequencing technology and emphasize their substantial impact on the study of erythroid cells, highlighting their contributions, including the exploration of functional heterogeneity within erythroid populations, the identification of novel erythrocyte subgroups, the tracking of different erythroid lineages, and the unveiling of mechanisms governing erythroid fate decisions. These findings not only invigorate erythroid cell research but also offer new perspectives on the management of diseases related to erythroid cells.

Stochastic Gene Expression in Proliferating Cells: Differing Noise Intensity in Single-Cell and Population Perspectives.

Random fluctuations (noise) in gene expression can be studied from two complementary perspectives: following expression in a single cell over time or comparing expression between cells in a proliferating population at a given time. Here, we systematically investigated scenarios where both perspectives lead to different levels of noise in a given gene product. We first consider a stable protein, whose concentration is diluted by cellular growth, and the protein inhibits growth at high concentrations, establishing a positive feedback loop. For a stochastic model with molecular bursting of gene products, we analytically predict and contrast the steady-state distributions of protein concentration in both frameworks. Although positive feedback amplifies the noise in expression, this amplification is much higher in the population framework compared to following a single cell over time. We also study other processes that lead to different noise levels even in the absence of such dilution-based feedback. When considering randomness in the partitioning of molecules between daughters during mitosis, we find that in the single-cell perspective, the noise in protein concentration is independent of noise in the cell cycle duration. In contrast, partitioning noise is amplified in the population perspective by increasing randomness in cell-cycle time. Overall, our results show that the commonly used single-cell framework that does not account for proliferating cells can, in some cases, underestimate the noise in gene product levels. These results have important implications for studying the inter-cellular variation of different stress-related expression programs across cell types that are known to inhibit cellular growth.

Unveiling novel cell clusters and biomarkers in glioblastoma and its peritumoral microenvironment at the single-cell perspective

BackgroundGlioblastoma (GBM) is a highly heterogeneous, recurrent and aggressively invasive primary malignant brain tumor. The heterogeneity of GBM results in poor targeted therapy. Therefore, the aim of this study is to depict the cellular landscape of GBM and its peritumor from a single-cell perspective. Discovering new cell subtypes and biomarkers, and providing a theoretical basis for precision therapy.MethodsWe collected 8 tissue samples from 4 GBM patients to perform 10 × single-cell transcriptome sequencing. Quality control and filtering of data by Seurat package for clustering. Inferring copy number variations to identify malignant cells via the infercnv package. Functional enrichment analysis was performed by GSVA and clusterProfiler packages. STRING database and Cytoscape software were used to construct protein interaction networks. Inferring transcription factors by pySCENIC. Building cell differentiation trajectories via the monocle package. To infer intercellular communication networks by CellPhoneDB software.ResultsWe observed that the tumor microenvironment (TME) varies among different locations and different GBM patients. We identified a proliferative cluster of oligodendrocytes with high expression of mitochondrial genes. We also identified two clusters of myeloid cells, one primarily located in the peritumor exhibiting an M1 phenotype with elevated TNFAIP8L3 expression, and another in the tumor and peritumor showing a proliferative tendency towards an M2 phenotype with increased DTL expression. We identified XIST, KCNH7, SYT1 and DIAPH3 as potential factors associated with the proliferation of malignant cells in GBM.ConclusionsThese biomarkers and cell clusters we discovered may serve as targets for treatment. Targeted drugs developed against these biomarkers and cell clusters may enhance treatment efficacy, optimize immune therapy strategies, and improve the response rates of GBM patients to immunotherapy. Our findings provide a theoretical basis for the development of individualized treatment and precision medicine for GBM, which may be used to improve the survival of GBM patients.

Single-cell nascent RNA sequencing unveils coordinated global transcription

Transcription is the primary regulatory step in gene expression. Divergent transcription initiation from promoters and enhancers produces stable RNAs from genes and unstable RNAs from enhancers1,2. Nascent RNA capture and sequencing assays simultaneously measure gene and enhancer activity in cell populations3. However, fundamental questions about the temporal regulation of transcription and enhancer–gene coordination remain unanswered, primarily because of the absence of a single-cell perspective on active transcription. In this study, we present scGRO–seq—a new single-cell nascent RNA sequencing assay that uses click chemistry—and unveil coordinated transcription throughout the genome. We demonstrate the episodic nature of transcription and the co-transcription of functionally related genes. scGRO–seq can estimate burst size and frequency by directly quantifying transcribing RNA polymerases in individual cells and can leverage replication-dependent non-polyadenylated histone gene transcription to elucidate cell cycle dynamics. The single-nucleotide spatial and temporal resolution of scGRO–seq enables the identification of networks of enhancers and genes. Our results suggest that the bursting of transcription at super-enhancers precedes bursting from associated genes. By imparting insights into the dynamic nature of global transcription and the origin and propagation of transcription signals, we demonstrate the ability of scGRO–seq to investigate the mechanisms of transcription regulation and the role of enhancers in gene expression.

Label-free metabolic optical biomarkers track stem cell fate transition in real time.

Tracking stem cell fate transition is crucial for understanding their development and optimizing biomanufacturing. Destructive single-cell methods provide a pseudotemporal landscape of stem cell differentiation but cannot monitor stem cell fate in real time. We established a metabolic optical metric using label-free fluorescence lifetime imaging microscopy (FLIM), feature extraction and machine learning-assisted analysis, for real-time cell fate tracking. From a library of 205 metabolic optical biomarker (MOB) features, we identified 56 associated with hematopoietic stem cell (HSC) differentiation. These features collectively describe HSC fate transition and detect its bifurcate lineage choice. We further derived a MOB score measuring the "metabolic stemness" of single cells and distinguishing their division patterns. This score reveals a distinct role of asymmetric division in rescuing stem cells with compromised metabolic stemness and a unique mechanism of PI3K inhibition in promoting ex vivo HSC maintenance. MOB profiling is a powerful tool for tracking stem cell fate transition and improving their biomanufacturing from a single-cell perspective.

Nature of epigenetic aging from a single-cell perspective.

Age-related changes in DNA methylation (DNAm) form the basis of the most robust predictors of age-epigenetic clocks-but a clear mechanistic understanding of exactly which aspects of aging are quantified by these clocks is lacking. Here, to clarify the nature of epigenetic aging, we juxtapose the dynamics of tissue and single-cell DNAm in mice. We compare these changes during early development with those observed during adult aging in mice, and corroborate our analyses with a single-cell RNA sequencing analysis within the same multiomics dataset. We show that epigenetic aging involves co-regulated changes as well as a major stochastic component, and this is consistent with transcriptional patterns. We further support the finding of stochastic epigenetic aging by direct tissue and single-cell DNAm analyses and modeling of aging DNAm trajectories with a stochastic process akin to radiocarbon decay. Finally, we describe a single-cell algorithm for the identification of co-regulated and stochastic CpG clusters showing consistent transcriptomic coordination patterns. Together, our analyses increase our understanding of the basis of epigenetic clocks and highlight potential opportunities for targeting aging and evaluating longevity interventions.

Bioconcentration of Inorganic and Methyl Mercury by Algae Revealed Using Dual-Mass Single-Cell ICP-MS with Double Isotope Tracers.

Algae are an entry point for mercury (Hg) into the food web. Bioconcentration of Hg by algae is crucial for its biogeochemical cycling and environmental risk. Herein, considering the cell heterogeneity, we investigated the bioconcentration of coexisting isotope-labeled inorganic (199IHg) and methyl Hg (201MeHg) by six typical freshwater and marine algae using dual-mass single-cell inductively coupled plasma mass spectrometry (scICP-MS). First, a universal pretreatment procedure for the scICP-MS analysis of algae was developed. Using the proposed method, the intra- and interspecies heterogeneities and the kinetics of Hg bioconcentration by algae were revealed at the single-cell level. The heterogeneity in the cellular Hg contents is largely related to cell size. The bioconcentration process reached a dynamic equilibrium involving influx/adsorption and efflux/desorption within hours. Algal density is a key factor affecting the distribution of Hg between algae and ambient water. Cellular Hg contents were negatively correlated with algal density, whereas the volume concentration factors almost remained constant. Accordingly, we developed a model based on single-cell analysis that well describes the density-driven effects of Hg bioconcentration by algae. From a novel single-cell perspective, the findings improve our understanding of algal bioconcentration governed by various biological and environmental factors.

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.

One-Shot Single-Cell Proteome and Metabolome Analysis Strategy for the Same Single Cell.

Characterizing the profiles of proteome and metabolome at the single-cell level is of great significance in single-cell multiomic studies. Herein, we proposed a novel strategy called one-shot single-cell proteome and metabolome analysis (scPMA) to acquire the proteome and metabolome information in a single-cell individual in one injection of LC-MS/MS analysis. Based on the scPMA strategy, a total workflow was developed to achieve the single-cell capture, nanoliter-scale sample pretreatment, one-shot LC injection and separation of the enzyme-digested peptides and metabolites, and dual-zone MS/MS detection for proteome and metabolome profiling. Benefiting from the scPMA strategy, we realized dual-omic analysis of single tumor cells, including A549, HeLa, and HepG2 cells with 816, 578, and 293 protein groups and 72, 91, and 148 metabolites quantified on average. A single-cell perspective experiment for investigating the doxorubicin-induced antitumor effects in both the proteome and metabolome aspects was also performed.

SPDB: a comprehensive resource and knowledgebase for proteomic data at the single-cell resolution.

The single-cell proteomics enables the direct quantification of protein abundance at the single-cell resolution, providing valuable insights into cellular phenotypes beyond what can be inferred from transcriptome analysis alone. However, insufficient large-scale integrated databases hinder researchers from accessing and exploring single-cell proteomics, impeding the advancement of this field. To fill this deficiency, we present a comprehensive database, namely Single-cell Proteomic DataBase (SPDB, https://scproteomicsdb.com/), for general single-cell proteomic data, including antibody-based or mass spectrometry-based single-cell proteomics. Equipped with standardized data process and a user-friendly web interface, SPDB provides unified data formats for convenient interaction with downstream analysis, and offers not only dataset-level but also protein-level data search and exploration capabilities. To enable detailed exhibition of single-cell proteomic data, SPDB also provides a module for visualizing data from the perspectives of cell metadata or protein features. The current version of SPDB encompasses 133 antibody-based single-cell proteomic datasets involving more than 300 million cells and over 800 marker/surface proteins, and 10 mass spectrometry-based single-cell proteomic datasets involving more than 4000 cells and over 7000 proteins. Overall, SPDB is envisioned to be explored as a useful resource that will facilitate the wider research communities by providing detailed insights into proteomics from the single-cell perspective.

SIK2-positive tumor epithelial cells in breast cancer maybe potential anti-cancer messengers: A systematic analysis from a single-cell perspective.

Breast cancer is the most common malignancy in the world and one of the leading causes of cancer death, which is a heterogeneous disease involving genetic and environmental factors. Breast cancer stem cells (BCSCs) are the main players in the aggressiveness of different tumors, at the same time, these cells are the main challenge for cancer treatment. There are multiple treatment options for breast cancer (BC) patients and the lack of understanding of prognostic and predictive biomarkers for breast cancer is a potential research direction for us to develop better treatments in the future. In this paper, we conducted a correlation analysis between SIK2 and clinical traits by searching numerous BRCA datasets in the GEO database. The model was constructed and validated by incorporating tumor samples from the TCGA-BRCA cohort. Surprisingly, we found differential expression of SIK2 gene in individual tumor samples from the UCSC database. Subsequently, we found significantly high expression of SIK2 in epithelial cells by comparing the differential expression of SIK2 in different cell subpopulations and performed subsequent immune infiltration and pathway correlation analysis. Differential genes in SIK2+ epithelial cells, which may be potential therapeutic targets for breast cancer. In conclusion, our results suggest that SIK2 may be a potential prognostic and predictive biomarker that could serve as an oncogenic messenger for breast cancer. This discovery of SIK2 may provide more valuable references for potential therapeutic tools for breast cancer.

Deciphering pathological behavior of pediatric medullary thyroid cancer from single-cell perspective.

Pediatric medullary thyroid cancer (MTC) is one of the rare pediatric endocrine neoplasms. Derived from C cells of thyroid glands, MTC is more aggressive and more prompt to metastasis than other types of pediatric thyroid cancer. The mechanism remains unclear. We performed single-cell transcriptome sequencing on the samples of the primary tumor and metastases lymph nodes from one patient diagnosed with MTC, and it is the first single-cell transcriptome sequencing data of pediatric MTC. In addition, whole exome sequencing was performed and peripheral blood was regarded as a normal reference. All cells that passed quality control were merged and analyzed in R to discover the association between tumor cells and their microenvironment as well as tumor pathogenesis. We first described the landscape of the single-cell atlas of MTC and studied the interaction between the tumor cell and its microenvironment. C cells, identified as tumor cells, and T cells, as the dominant participant in the tumor microenvironment, were particularly discussed in their development and interactions. In addition, the WES signature of tumor cells and their microenvironment were also described. Actively immune interactions were found, indicating B cells, T cells and myeloid cells were all actively participating in immune reaction in MTC. T cells, as the major components of the tumor microenvironment, proliferated in MTC and could be divided into clusters that expressed proliferation, immune effectiveness, and naive markers separately.

The diversity and dynamics of tumor-associated macrophages in recurrent glioblastoma.

Despite tremendous efforts to exploit effective therapeutic strategies, most glioblastoma (GBM) inevitably relapse and become resistant to therapies, including radiotherapy and immunotherapy. The tumor microenvironment (TME) of recurrent GBM (rGBM) is highly immunosuppressive, dominated by tumor-associated macrophages (TAMs). TAMs consist of tissue-resident microglia and monocyte-derived macrophages (MDMs), which are essential for favoring tumor growth, invasion, angiogenesis, immune suppression, and therapeutic resistance; however, restricted by the absence of potent methods, the heterogeneity and plasticity of TAMs in rGBM remain incompletely investigated. Recent application of single-cell technologies, such as single-cell RNA-sequencing has enabled us to decipher the unforeseen diversity and dynamics of TAMs and to identify new subsets of TAMs which regulate anti-tumor immunity. Here, we first review hallmarks of the TME, progress and challenges of immunotherapy, and the biology of TAMs in the context of rGBM, including their origins, categories, and functions. Next, from a single-cell perspective, we highlight recent findings regarding the distinctions between tissue-resident microglia and MDMs, the identification and characterization of specific TAM subsets, and the dynamic alterations of TAMs during tumor progression and treatment. Last, we briefly discuss the potential of TAM-targeted strategies for combination immunotherapy in rGBM. We anticipate the comprehensive understanding of the diversity and dynamics of TAMs in rGBM will shed light on further improvement of immunotherapeutic efficacy in rGBM.

Upregulated FADD is associated with poor prognosis, immune exhaustion, tumor malignancy, and immunotherapy resistance in patients with lung adenocarcinoma.

FAS-associated death structural domain (FADD) proteins are important proteins that regulate apoptosis and are also involved in many nonapoptotic pathways in tumors. However, how dysregulated FADD affects the development of lung adenocarcinoma (LUAD) remains unknown. Transcriptome profiles and corresponding clinical information of LUAD patients were convened from different databases, and the results were validated by qRT-PCR and cell counting kit-8 using LUAD cell lines. Potential associations between FADD and tumor malignancy, the immune microenvironment, genomic stability, and treatment sensitivity in LUAD patients were revealed by systematic bioinformatics analysis. FADD was significantly overexpressed in LUAD, and patients with higher expression levels of FADD had a worse prognosis and more advanced tumor stage. Functional analysis revealed that elevated expression of FADD was associated with cell cycle dysregulation, angiogenesis, and metabolic disturbances. In addition, overexpression of FADD was associated with a higher infiltration of suppressive immune cells. From a single-cell perspective, cells with lower FADD expression are more active in immune-related pathways. FADD was associated with more genomic mutations, especially TP53. Patients with high FADD expression are more likely to benefit from conventional chemotherapy, while those with low FADD expression are more suitable for immunotherapy. Upregulated FADD is associated with worse prognosis, immune exhaustion, and tumor malignancy in LUAD patients. In addition, FADD can be an efficient indicator for assessing sensitivity to chemotherapy and immunotherapy. Therefore, FADD has the potential to serve as a new target for precision medicine and targeted therapy for LUAD.

ScRNA-seq and spatial transcriptomics: exploring the occurrence and treatment of coronary-related diseases starting from development.

Single-cell RNA sequencing (scRNA-seq) is a new technology that can be used to explore molecular changes in complex cell clusters at the single-cell level. Single-cell spatial transcriptomic technology complements the cell-space location information lost during single-cell sequencing. Coronary artery disease is an important cardiovascular disease with high mortality rates. Many studies have explored the physiological development and pathological changes in coronary arteries from the perspective of single cells using single-cell spatial transcriptomic technology. This article reviews the molecular mechanisms underlying coronary artery development and diseases as revealed by scRNA-seq combined with spatial transcriptomic technology. Based on these mechanisms, we discuss the possible new treatments for coronary diseases.

Single-cell RNA sequencing reveals the heterogeneity and microenvironment in one adenoid cystic carcinoma sample

Adenoid cystic carcinoma (ACC) is one of the most common malignancy of the major salivary glands with a high recurrence rate and poor prognosis. Determining tumor heterogeneity and factors in the microenvironment may provide novel therapeutic targets for ACC. We performed single-cell RNA sequencing of one ACC sample and normal salivary gland tissues from a patient to analyze tumor heterogeneity, immunosuppressive landscape, and intercellular communication networks. The heterogeneity of epithelial cells in ACC tissues was significantly higher compared with that in normal tissues, whereas immune cells were almost absent. We found four malignant cell clusters in ACC and explored their characteristics and function. In tumor tissues, CD8 + cytotoxic T cells and CD4 + T helper cells were significantly decreased, whereas IgA + plasma cells were absent. There were two clusters of macrophages, one representing IL1B macrophages and the other consisted of a cluster of macrophages associated with the epithelial mesenchymal transition (EMT). Both were significantly different from the normal tissue composition. In addition, the communication between epithelial cells and other cells in the tumor tissue was enhanced. MIF-CD74 and APP-CD74 were significantly upregulated. We comprehensively described the heterogeneity of ACC and the tumor microenvironment (TME) from a single cell perspective including cell characteristics, immune cell infiltration, and cell communication. CLINICAL RELEVANCE: This study provided further insights into ACC and may lead to new treatment strategies.

Immune heterogeneity in cardiovascular diseases from a single-cell perspective.

A variety of immune cell subsets occupy different niches in the cardiovascular system, causing changes in the structure and function of the heart and vascular system, and driving the progress of cardiovascular diseases (CVDs). The immune cells infiltrating the injury site are highly diverse and integrate into a broad dynamic immune network that controls the dynamic changes of CVDs. Due to technical limitations, the effects and molecular mechanisms of these dynamic immune networks on CVDs have not been fully revealed. With recent advances in single-cell technologies such as single-cell RNA sequencing, systematic interrogation of the immune cell subsets is feasible and will provide insights into the way we understand the integrative behavior of immune populations. We no longer lightly ignore the role of individual cells, especially certain highly heterogeneous or rare subpopulations. We summarize the phenotypic diversity of immune cell subsets and their significance in three CVDs of atherosclerosis, myocardial ischemia and heart failure. We believe that such a review could enhance our understanding of how immune heterogeneity drives the progression of CVDs, help to elucidate the regulatory roles of immune cell subsets in disease, and thus guide the development of new immunotherapies.

Integrated single-nucleus and spatial transcriptomics captures transitional states in soybean nodule maturation.

Legumes form symbiosis with rhizobium leading to the development of nitrogen-fixing nodules. By integrating single-nucleus and spatial transcriptomics, we established a cell atlas of soybean nodules and roots. In central infected zones of nodules, we found that uninfected cells specialize into functionally distinct subgroups during nodule development, and revealed a transitional subtype of infected cells with enriched nodulation-related genes. Overall, our results provide a single-cell perspective for understanding rhizobium-legume symbiosis.

Simultaneous Assessment of Kinship, Division Number, and Phenotype via Flow Cytometry for Hematopoietic Stem and Progenitor Cells.

Few techniques can assess phenotype and fate for the same cell simultaneously. Most of the current protocols used to characterize phenotype, although able to generate large datasets, necessitate the destruction of the cell of interest, making it impossible to assess its functional fate. Heterogeneous biological differentiating systems like hematopoiesis are therefore difficult to describe. Building on cell division tracking dyes, we further developed a protocol to simultaneously determine kinship, division number, and differentiation status for many single hematopoietic progenitors. This protocol allows the assessment of the ex vivo differentiation potential of murine and human hematopoietic progenitors, isolated from various biological sources. Moreover, as it is based on flow cytometry and a limited number of reagents, it can quickly generate a large amount of data, at the single-cell level, in a relatively inexpensive manner. We also provide the analytical pipeline for single-cell analysis, combined with a robust statistical framework. As this protocol allows the linking of cell division and differentiation at the single-cell level, it can be used to quantitatively assess symmetric and asymmetric fate commitment, the balance between self-renewal and differentiation, and the number of divisions for a given commitment fate. Altogether, this protocol can be used in experimental designs aiming to unravel the biological differences between hematopoietic progenitors, from a single-cell perspective.

Epstein-Barr virus DNA seropositivity links distinct tumoral heterogeneity and immune landscape in nasopharyngeal carcinoma.

Epstein-Barr virus (EBV) DNA seronegative (Sero-) and seropositive (Sero+) nasopharyngeal carcinoma (NPC) are distinctly different disease subtypes. Patients with higher baseline EBV DNA titers seem to benefit less from anti-PD1 immunotherapy, but underlying mechanisms remain unclear. Tumor microenvironment (TME) characteristics could be the important factor affecting the efficacy of immunotherapy. Here, we illuminated the distinct multicellular ecosystems of EBV DNA Sero- and Sero+ NPCs from cellular compositional and functional perspectives at single-cell resolution. We performed single-cell RNA sequencing analyses of 28,423 cells from ten NPC samples and one non-tumor nasopharyngeal tissue. The markers, function, and dynamics of related cells were analyzed. We found that tumor cells from EBV DNA Sero+ samples exhibit low-differentiation potential, stronger stemness signature, and upregulated signaling pathways associated with cancer hallmarks than that of EBV DNA Sero- samples. Transcriptional heterogeneity and dynamics in T cells were associated with EBV DNA seropositivity status, indicating different immunoinhibitory mechanisms employed by malignant cells depending on EBV DNA seropositivity status. The low expression of classical immune checkpoints, early-triggered cytotoxic T-lymphocyte response, global activation of IFN-mediated signatures, and enhanced cell-cell interplays cooperatively tend to form a specific immune context in EBV DNA Sero+ NPC. Collectively, we illuminated the distinct multicellular ecosystems of EBV DNA Sero- and Sero+ NPCs from single-cell perspective. Our study provides insights into the altered tumor microenvironment of NPC associated with EBV DNA seropositivity, which will help direct the development of rational immunotherapy strategies.