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Microarray analysis of human epithelial cell responses to bacterial interaction.

Host-pathogen interactions are inherently complex and dynamic. The recent use of human microarrays has been invaluable to monitor the effects of various bacterial and viral pathogens upon host cell gene expression programs. This methodology has allowed the host response transcriptome of several cell lines to be studied on a global scale. To this point, the great majority of reports have focused on the response of immune cells, including macrophages and dendritic cells. These studies revealed that the immune response to microbial pathogens is tailored to different microbial challenges. Conversely, the paradigm for epithelial cells has--until recently--held that the epithelium mostly served as a relatively passive physical barrier to infection. It is now generally accepted that the epithelial barrier contributes more actively to signaling events in the immune response. In light of this shift, this review will compare transcriptional profiling data from studies that involved host-pathogen interactions occurring with epithelial cells. Experiments that defined both a common core response, as well as pathogen-specific host responses will be discussed. This review will also summarize the contributions that transcriptional profiling analysis has made to our understanding of bacterial physio-pathogensis of infection. This will include a discussion of how host transcriptional responses can be used to infer the function of virulence determinants from bacterial pathogens interacting with epithelial mucosa. In particular, we will expand upon the lessons that have been learned from gastro-intestinal and oral pathogens, as well as from members of the commensal flora.

Animals↗

A murine model of sepsis induces age- and sex-specific chromatin remodeling in myeloid-derived suppressor cells.

INTRODUCTION: Sepsis survivors frequently develop long-term immune dysfunction, but the epigenetic mechanisms underlying persistent myeloid suppression remain unclear. Myeloid-derived suppressor cells (MDSCs), whose function is shaped by host age and sex, are key contributors to post-sepsis immune dysregulation. METHODS: Here, we present a high-resolution epigenetic map targeting gene promoters of MDSCs after sepsis and daily chronic stress using MAPit-FENGC, a single-molecule assay that simultaneously profiles DNA methylation and chromatin accessibility. In a clinically relevant murine model, including young and older adult male and female mice, splenic MDSCs were isolated for MAPit-FENGC and single-cell RNA sequencing. RESULTS: Unsupervised clustering identified nine promoter classes reflecting chromatin dynamics: age- and sex-dependent sepsis-induced opening (Classes 1-4), persistent closure with varying levels of DNA methylation (Classes 5-7), and constitutive openness post-sepsis (Classes 8, 9). Transcriptomic profiling corroborated these promoter states, linking accessibility with gene expression. CONCLUSIONS: These findings define promoter-level epigenetic classes across a targeted locus panel in splenic CD11b+Gr1+ cells within this murine sepsis model and generate mechanistic hypotheses regarding age- and sex-associated chromatin states.

Animals↗

GenOT: generative optimal transport enables spatiotemporal interpolation and generation in cross-platform spatial transcriptomics.

Spatial transcriptomics technologies have revolutionized the analysis of spatial gene expression, yet integrating spatial information and generating data across heterogeneous samples remain challenging. We present GenOT, a generative framework combining multi-scale graph self-supervised contrastive learning with optimal transport barycenter theory for efficient cross-slice and cross-platform spatiotemporal interpolation. The core innovation of GenOT lies in introducing an optimal transport barycenter-based interpolation algorithm, which mathematically models spatial distribution differences across heterogeneous samples to reconstruct spatiotemporal gene expression dynamics. Extensive evaluations demonstrate that GenOT consistently outperforms existing approaches in spatial domain identification, cross-platform interpolation, and developmental trajectory reconstruction.

Spatial Transcriptomics↗

Cracking the egg: molecular dynamics and evolutionary aspects of the transition from the fully grown oocyte to embryo.

Fully grown oocytes (FGOs) contain all the necessary transcripts to activate molecular pathways underlying the oocyte-to-embryo transition (OET). To elucidate this critical period of development, an extensive survey of the FGO transcriptome was performed by analyzing 19,000 expressed sequence tags of the Mus musculus FGO cDNA library. Expression of 5400 genes and transposable elements is reported. For a majority of genes expressed in mouse FGOs, homologs transcribed in eggs of Xenopus laevis or Ciona intestinalis were found, pinpointing evolutionary conservation of most regulatory cascades underlying the OET in chordates. A large proportion of identified genes belongs to several gene families with oocyte-restricted expression, a likely result of lineage-specific genomic duplications. Gene loss by mutation and expression in female germline of retrotransposed genes specific to M. musculus is documented. These findings indicate rapid diversification of genes involved in female reproduction. Comparison of the FGO and two-cell embryo transcriptomes demarcated the processes important for oogenesis from those involved in OET and identified novel motifs in maternal mRNAs associated with transcript stability. Discovery of oocyte-specific eukaryotic translation initiation factor 4E distinguishes a novel system of translational regulation. These results implicate conserved pathways underlying transition from oogenesis to initiation of development and illustrate how genes acquire and lose reproductive functions during evolution, a potential mechanism for reproductive isolation.

Amino Acid Sequence↗

Stepping out of the dark: how metabolomics shed light on fungal biology.

Metabolomics, a critical tool for analyzing small-molecule metabolites, integrates with genomics, transcriptomics, and proteomics to provide a systems-level understanding of fungal biology. By mapping metabolic networks, it elucidates regulatory mechanisms driving physiological and ecological adaptations. In fungal pathogenesis, metabolomics reveals host-pathogen dynamics, identifying virulence factors like gliotoxin in Aspergillus fumigatus and metabolic shifts, such as glyoxylate cycle upregulation in Candida albicans. Ecologically, it highlights fungal responses to abiotic stressors, including osmolyte production like trehalose, enhancing survival in extreme environments. These insights highlight metabolomics' role in decoding fungal persistence and niche colonization. In drug discovery, it aids target identification by profiling biosynthetic pathways, supporting novel antifungal and nanostructured therapy development. Combined with multi-omics, metabolomics advances insights into fungal pathogenesis, ecological interactions, and therapeutic innovation, offering translational potential for addressing antifungal resistance and improving treatment outcomes for fungal infections. Its progress shed light on complex fungal molecular profiles, advancing discovery and innovation in fungal biology.

Metabolomics↗

Aging-associated changes in cardiac gene expression: large scale transcriptome analysis.

Aging and aging-related diseases are associated with altered patterns of gene expression, involving quantitative and qualitative changes in the abundance of specific transcripts. A complete and simultaneous analysis of gene expression should therefore lead to important insights into the transcriptional mechanisms underlying the aging process. Recently, we have employed high-throughput gene expression profiling to study transcriptional activity in heart. Two technologies, serial analysis of gene expression (SAGE) and gene expression arrays, allow rapid, large-scale expression profiling, which provides information about the dynamics of total gene expression with age and which can be employed to identify candidate genes that may serve as diagnostic and prognostic markers in age-associated cardiac diseases. The accompanying gene predictions from high-throughput gene expression profiling provide a starting point for understanding the function, the complexity of interactions, and the role of genes in promoting cellular/organismal phenotypes during senescence and disease. In this review we describe the current state of transcriptome profiling by SAGE and microarrays and discuss how results generated with these approaches in heart can be applied to the study of aging and the treatment of cardiovascular diseases.

Aging↗

Expression profiling of the host response to bacterial infection: the transition from basal to induced defence responses in RPM1-mediated resistance.

Changes in transcription in leaves of Arabidopsis thaliana were characterised following challenge with strains of Pseudomonas syringae pv. tomato DC3000 allowing differentiation of basal resistance (hrpA mutants), gene-specific resistance (RPM1-specified interactions) and susceptibility (wild-type pathogen). In planta avirulence gene induction, changes in host [Ca2+]cyt and leaf collapse were used to delineate the transition from infection to induced resistance. The plant responds rapidly, dynamically and discriminately to infection by phytopathogenic bacteria. Within the first 2 h host transcriptional changes are common to all challenges indicating that Type III effector function does not contribute to early events in host transcriptome re-programming. The timing of induction for specific transcripts was reproducible, hierarchical and modulated at least in part through EDS1 function. R gene-specific transcripts were not observed until 3 h after inoculation. Intriguingly, the R gene-specific response proteins are expected to localise to diverse cellular addresses indicative of a global impact on cellular homeostasis. The altered transcriptional response rapidly manifests into initial symptoms of leaf collapse within 2 h, although establishment of the full macroscopic HR occurs significantly later.

Arabidopsis↗

Functional genomics of cell elongation in developing cotton fibers.

Cotton fibers are single-celled seed trichomes of major economic importance. Factors that regulate the rate and duration of cell expansion control fiber morphology and important agronomic traits. For genetic characterization of rapid cell elongation in cotton fibers, approximately 14,000 unique genes were assembled from 46,603 expressed sequence tags (ESTs) from developmentally staged fiber cDNAs of a cultivated diploid species ( Gossypium arboreum L.). Conservatively, the fiber transcriptome represents 35-40% of the genes in the cotton genome. In silico expression analysis revealed that rapidly elongating fiber cells exhibit significant metabolic activity, with the bulk of gene transcripts, represented by three major functional groups - cell wall structure and biogenesis, the cytoskeleton and energy/carbohydrate metabolism. Oligonucleotide microarrays revealed dynamic changes in gene expression between primary and secondary cell wall biogenesis showing that fiber genes in the dbEST are highly stage-specific for cell expansion - a conclusion supported by the absence of known secondary cell wall-specific genes from our fiber dbEST. During the developmental switch from primary to secondary cell wall syntheses, 2553 "expansion-associated" fiber genes are significantly down regulated. Genes (81) significantly up-regulated during secondary cell wall synthesis are involved in cell wall biogenesis and energy/carbohydrate metabolism, which is consistent with the stage of cellulose synthesis during secondary cell wall modification in developing fibers. This work provides the first in-depth view of the genetic complexity of the transcriptome of an expanding cell, and lays the groundwork for studying fundamental biological processes in plant biology with applications in agricultural biotechnology.

Cell Growth Processes↗

Spatial habitat radiomics predicts tertiary lymphoid structure status and identifies an IDO1+ migratory dendritic cell axis in breast cancer.

BACKGROUND: Tertiary lymphoid structures (TLS) are spatially organized immune niches associated with therapeutic response and favorable outcomes in breast cancer (BC). However, TLS assessment currently relies on invasive tissue-based analyses, and the biological mechanisms underlying imaging-based TLS prediction remain poorly understood. METHODS: We developed and validated a spatial heterogeneity-based radiomic TLS signature (shTLS) using dynamic contrast-enhanced MRI to non-invasively predict TLS status across multicenter BC cohorts. Spatial habitat radiomics were used to capture intratumoral and peritumoral immune-related heterogeneity. Integrated multi-omics analyses, including transcriptomics, pathomics, genomics, single-cell RNA sequencing, immunohistochemistry, and multiplex immunofluorescence, were performed to biologically interpret shTLS-defined subgroups. Functional drug-sensitivity assays were conducted to assess therapeutic implications. RESULTS: The shTLS model achieved robust predictive performance across independent cohorts and molecular subtypes. High shTLS scores were associated with immune-inflamed tumors characterized by spatially clustered activated T cells and dendritic cells (DCs). In contrast, shTLS-low tumors exhibited an immunosuppressive spatial niche with peripheral accumulation of CD4+ PD-1+ T cells and plasma cells, increased immune-tumor separation, and enhanced inflammatory and immunoregulatory signaling. An indoleamine 2,3-dioxygenase 1 (IDO1)-associated immunoregulatory program was observed in the shTLS-low tumors, which appeared to be preferentially expressed by LAMP3+CCR7+ migratory DCs. Pharmacologic inhibition of IDO1 enhanced chemotherapy and CDK4/6 inhibitor sensitivity in vitro. CONCLUSION: This study establishes spatial radiomics as a non-invasive approach to decode TLS-associated immune ecosystems and supports the presence of an IDO1-associated immunosuppressive phenotype, providing biological insight and translational rationale for patient stratification and future combination strategies.

Humans↗

Whole-cell simulation: a grand challenge of the 21st century.

Study of the cell will never be complete unless its dynamic behavior is understood. The complex behavior of the cell cannot be determined or predicted unless a computer model of the cell is constructed and computer simulation is undertaken. Rapid accumulation of biological data from genome, proteome, transcriptome and metabolome projects can bring us to the point where it is no longer purely speculative to discuss how to construct virtual cells in silico. This article describes attempts to construct whole cell models. The E-CELL project has completed a couple of virtual cell models, and computer simulations have revealed some biological surprises.

Anemia, Hemolytic, Congenital↗

HMGA2 links morphological evolution and microenvironment dynamics to systemic therapy response in clear cell renal cell carcinoma.

BACKGROUND: Clear cell renal cell carcinoma (ccRCC) exhibits significant heterogeneity due to morphological changes and tumor microenvironment dynamics, influencing systemic therapy responses. While the role of high-mobility group AT-hook 2 (HMGA2) in tumor progression has been implicated in other cancers, its significance in ccRCC remains unclear. This study investigates the role of HMGA2 in these processes and its clinical impact. METHODS: Spatial transcriptomics (ST) was performed on primary ccRCC samples to investigate expression trajectories associated with HMGA2 expression and morphological evolution. In metastatic ccRCC cohorts treated with systemic therapy, immunohistochemistry and bulk RNA sequencing data were analyzed to evaluate molecular and clinical features in relation to HMGA2. Single-cell RNA sequencing (scRNA-seq) data were used to explore immune cell populations and their interactions. Based on these findings, multiplex immunohistochemistry (mIHC) assessed spatial distribution, cell-cell interactions, and pathological responses of key immune populations. RESULTS: HMGA2 expression was associated with aggressive morphological patterns, such as solid sheets and rhabdoid/sarcomatoid. ST revealed a progressive increase in HMGA2 expression along the morphological trajectory, marked by a shift from clear to eosinophilic cytoplasm, with eccentric nuclei and prominent nucleoli, and loss of vascular architecture. HMGA2-high tumors exhibited aggressive phenotypes driven by cell cycle, epithelial-mesenchymal transition, and inflammatory signaling pathways. Clinically, patients with high HMGA2 had worse progression-free survival but responded better to immune checkpoint inhibitor combination (Combo-ICI) therapy than to tyrosine kinase inhibitor monotherapy. To assess the immune landscape, scRNA-seq data revealed that HMGA2-high tumors were enriched with progenitor exhausted CD8+ T cells (Tpex), along with increased frequencies of conventional dendritic cell type 1 (cDC1) and inflammatory cDC type 2, which were found to interact with Tpex via ICAM-1. mIHC confirmed that Tpex were enriched among Combo-ICI responders in HMGA2-high tumors, with higher densities and closer proximity to ICAM-1+ cDC1. CONCLUSIONS: These findings suggest that dynamic HMGA2 expression contributes to morphological evolution and modulates immune responses through enhanced Tpex-cDCs engagement, serving as a potential marker for systemic therapy response in ccRCC. However, additional experimental studies are required to validate these mechanisms.

Humans↗

The role of initial trauma in the host's response to injury and hemorrhage: insights from a correlation of mathematical simulations and hepatic transcriptomic analysis.

Trauma and hemorrhagic shock (HS) elicit severe physiological disturbances that predispose the victims to subsequent organ dysfunction and death. The general lack of effective therapeutic options for these patients is mainly due to the complex interplay of interacting inflammatory and physiological elements working at multiple levels. Systems biology has emerged as a new paradigm that allows the study of large portions of physiological networks simultaneously. Seeking a better understanding of the interplay among known inflammatory pathways, we constructed a mathematical model encompassing the dynamics of the acute inflammatory response that incorporates the intertwined effects of inflammation and global tissue damage. The model was calibrated using data from C57Bl/6 mice subjected to endotoxemia, sham operation (i.e., surgical trauma induced by cannulation [ST]) or ST + HS+ resuscitation (ST-HS-R). An in silico simulation, made at whole-organism level, suggested that similar pathways of different magnitudes were operant as the degree of total body damage increased. We sought to validate this hypothesis by subjecting mice to HS and comparing the models predictions to circulating markers of inflammation and tissue injury as well as the global transcriptomic response of the liver. C57Bl/6 mice were subjected to ST or ST-HS (without resuscitation). Liver gene expression was assessed using an Affymetrix DNA microarray (GeneChip Mouse Expression Set 430A, Affymetrix, Santa Clara, CA), which contains 22,621 probe sets and effectively interrogates 12,341 mouse genes. The microarray data sets were subjected to hierarchical clustering and pathway analysis. In agreement with model predictions, circulating levels of inflammation/tissue injury markers and the microarray analysis both demonstrated that ST alone accounts for a substantial proportion of the observed phenotypic and genetic/molecular changes versus untreated animals. The addition of HS further increased the magnitude of gene expression, but relatively few additional genes were recruited. Mathematical simulations and DNA microarrays, both systems biology tools, may provide valuable insight into the complex global physiological interactions that occur in response to trauma and hemorrhagic shock.

Animals↗

Transcriptome sequencing provides novel insights into larval development and sexual dimorphism in the firefly Aquatica leii (Coleoptera: Lampyridae).

Fireflies are regarded as one of the most charismatic beetles due to their bioluminescence and ecological importance as bioindicators of freshwater quality. However, molecular mechanisms of larval development and sexual dimorphism in aquatic species remain poorly understood. Here, we performed multi-stage transcriptomic analysis of the aquatic firefly Aquatica leii across larval instars from L2 to L6, together with adult females and males, with three biological replicates per stage. Using time-series expression clustering, differential expression analysis, and weighted gene co-expression network analysis (WGCNA), we characterized the transcriptional dynamics of continuous larval development and the onset of sex-biased gene expression. We identified a critical transcriptional transition occurred at L5-L6, marked by downregulation of early morphogenetic genes and upregulation of juvenile hormone metabolism, oxidoreductase activity, and muscle contraction genes, indicating a shift from growth to metamorphic preparation. WGCNA identified a module strongly correlated with L6 (R = 0.97) enriched for the same functions, confirming a coordinated late-larval program. Notably, genes exhibiting sex-biased expression in adults were already expressed during late larval stages (L5 and L6), and 123 genes progressively upregulated from L2 to L6 showed enrichment in chitin biosynthesis, heart contraction, and ion transport; among these, six genes maintained high expression in adults with clear male-biased (Alei052192, Alei006658, and Alei087054) or female-biased (Alei003725, Alei096818, and Alei074026) patterns. These findings establish that transcriptional foundations for sexual dimorphism and adult tissue formation are laid during late larval stages, providing the first multi-stage transcriptomic resource for aquatic firefly conservation and breeding.

Animals↗

Single-cell multi-omics dissects transcript isoform and immune repertoire dynamics in human immunosenescence.

Immunosenescence, a major hallmark of systemic aging, refers to the progressive functional decline of the immune system. This decline not only compromises host defense and immunological memory but also fuels chronic inflammation and tissue degeneration (collectively known as inflammaging). While single-cell RNA sequencing (scRNA-seq) has revealed transcriptomic alterations associated with immune aging, analyses restricted to transcript abundance fail to capture deeper regulatory layers, such as transcript isoform diversity and the remodeling of immune receptor repertoires. To address this limitation, we present a human peripheral immune single-cell multi-omics atlas that integrates gene expression, transcript isoform diversity, and immune receptor repertoires. By combining single-cell full-length transcriptome sequencing (scCycloneSEQ), short-read scRNA-seq, and single-cell immune receptor sequencing (scTCR/BCR-seq), we systematically profiled peripheral blood mononuclear cells (PBMCs) from healthy donors aged 30-40 and 60-70 years. Our analyses uncovered extensive age-related remodeling of immune cell composition, functional states, and TCR/BCR diversity. Notably, we found that CD4+ effector memory T cells exhibited widespread differential isoform usage (DIU), 3'UTR length variation, and a marked reshaping of cytotoxic T lymphocyte (CTL) clonotypes-all of which were closely associated with aging-related inflammation and cellular senescence. This multi-omics atlas delineates key molecular features of immunosenescence and provides a high-resolution resource for deciphering the regulatory architecture underlying immune aging.

TCR/BCR↗

Platform influence on DNA microarray data in postmortem brain research.

In addition to the substantial biological diversity among humans, our limited ability to reliably measure expression changes of small magnitude significantly reduces our capacity to obtain convergent sets of transcriptome data in postmortem brain. In particular, differences in the structure and sensitivity/reproducibility of microarray platforms, and in the variety of tools used to analyze microarray data, strongly influence experimental outcome. In order to better understand the sensitivity, dynamic range, and reproducibility of three common DNA microarray platforms, we compared two human postmortem samples on cDNA microarrays with dual-fluorescence, oligonucleotide GeneChips (Affymetrix), and single-color gel matrix deposited CodeLink oligonucleotide arrays. All three microarray platforms reported a good dynamic range and high correlation in replicate experiments, but they failed to consistently identify the same genes as differentially expressed between the same samples. Given their reproducibility and proven accuracy, different microarray platforms appear to be measuring different things by nature of their design and function. This needs to be taken into account when comparing data across studies.

Brain↗

An RNA polymerase III tissue and tumor atlas uncovers context-specific activities linked to 3D epigenome regulatory mechanisms.

RNA polymerase III (Pol III) produces a plethora of small noncoding RNA species involved in diverse cellular processes, from transcription regulation and splicing to RNA stability, translation, and proteostasis. Though Pol III activity is broadly coupled with cellular demands for protein synthesis and growth, a more precise understanding of gene-level dynamics and context-specific expression patterns remains missing, in part due to challenges related to sequencing and mapping Pol III-derived small ncRNAs. Here, we establish a predictive multi-tissue map of human Pol III activity across 19 tissues and 23 primary cancer subtypes by comprehensively profiling the chromatin accessibility of canonical Pol III-transcribed gene classes. Our framework relies on the unique relationship between gene accessibility and Pol III transcription, inferring activity through uniform binary classification of ATAC-seq enrichment at Pol III-transcribed genes. By characterizing multi-context gene uniformity, we provide a definition of the core Pol III transcriptome, broadly active across specialized tissues, and catalog genes with varied levels of context specificity. Our genomic Pol III atlas uncovers variable levels of activity across tissues, including sharp contraction of the Pol III transcriptome in heart and brain tissues and frequent expansion across diverse cancers. We show that both tissue- and tumor-specific genes are significantly enriched within lamina-associated domains (LADs), and that aberrant expression of nuclear lamin proteins is sufficient to induce Pol III-emergent patterns at tumor-specific genes. Together, these findings link Pol III dynamics to subnuclear compartmentalization and provide a resource for better understanding Pol III expansion and small RNA biogenesis in cancer.

Journal Article↗

PUS7-dependent Ψ reshapes specific synaptic gene exons to facilitate fear extinction memory formation.

RNA modifications serve as dynamic regulators of neural plasticity through their ability to fine-tune transcript stability and splicing. Pseudouridine (Ψ), an evolutionarily conserved RNA modification catalyzed by pseudouridine synthases, plays established roles in neurodevelopment, yet its functional significance in activity-dependent behavioral adaptation remains poorly defined. Here, we investigate Ψ-mediated epitranscriptomic regulation within the infralimbic prefrontal cortex (ILPFC), a brain region requiring precise synaptic remodeling for the clinically relevant form of fear extinction memory. Combining transcriptome-wide pseudouridylation profiling with behavioral analysis in mice, we identified selective Ψ enrichment at exons of synaptic regulatory genes within ILPFC during fear extinction learning. Fear extinction in the ILPFC drives concomitant exonic Ψ deposition and upregulation of synaptogenic transcripts, processes that involve pseudouridine synthase PUS7. Crucially, PUS7 knockdown in the ILPFC selectively impaired fear extinction memory formation without altering baseline fear expression, establishing a causal link between Ψ-dependent RNA processing and activity-dependent synaptic structural remodeling in this microcircuit. Our findings demonstrate that PUS7-mediated Ψ modification spatiotemporally regulates activity-dependent RNA dynamics in the ILPFC, providing the evidence that epitranscriptomic mechanisms precisely coordinate synaptic gene expression within behaviorally defined brain sub-region. This work bridges molecular RNA biology with systems neuroscience, revealing a novel mechanism for activity-dependent regulation of fear extinction in ILPFC.

Animals↗

Dissecting spatial heterogeneity and the immune-evasion mechanism of CTCs by single-cell RNA-seq in hepatocellular carcinoma.

Little is known about the transcriptomic plasticity and adaptive mechanisms of circulating tumor cells (CTCs) during hematogeneous dissemination. Here we interrogate the transcriptome of 113 single CTCs from 4 different vascular sites, including hepatic vein (HV), peripheral artery (PA), peripheral vein (PV) and portal vein (PoV) using single-cell full-length RNA sequencing in hepatocellular carcinoma (HCC) patients. We reveal that the transcriptional dynamics of CTCs were associated with stress response, cell cycle and immune-evasion signaling during hematogeneous transportation. Besides, we identify chemokine CCL5 as an important mediator for CTC immune evasion. Mechanistically, overexpression of CCL5 in CTCs is transcriptionally regulated by p38-MAX signaling, which recruites regulatory T cells (Tregs) to facilitate immune escape and metastatic seeding of CTCs. Collectively, our results reveal a previously unappreciated spatial heterogeneity and an immune-escape mechanism of CTC, which may aid in designing new anti-metastasis therapeutic strategies in HCC.

Aged↗