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Results for “Cell-type specific activation”

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PubMed2026

Cell-type specific activation of the cGAS-STING pathway in tumor immunotherapy: mechanisms and therapeutic implications.

BACKGROUND: The cyclic GMP–AMP synthase–stimulator of interferon genes (cGAS–STING) pathway acts as a pivotal innate immune sensor that detects cytosolic DNA and links genomic instability to antitumor immune activation. Therapeutic activation of this pathway has garnered substantial interest as a strategy to enhance cancer immunotherapy by promoting dendritic cell maturation, augmenting antigen presentation, and facilitating cytotoxic lymphocyte infiltration. However, the functional outcomes of cGAS–STING signaling are highly context dependent and influenced by both cell type and tumor microenvironmental (TME) conditions. MAIN BODY: Recent advances in single-cell and spatial transcriptomic profiling have revealed profound heterogeneity in cGAS–STING activation across distinct cellular and regional compartments within tumors. Acute and spatially restricted activation of the pathway can elicit potent antitumor immune responses, whereas chronic or dysregulated signaling may promote immune tolerance and tumor progression. Moreover, metabolic stress, epigenetic silencing, and microenvironmental immunosuppressive factors such as TGF-β and IL-10 can further modulate STING activity, leading to resistance to immunotherapy. Current translational efforts focus on next-generation STING agonists, nanoparticle-based delivery systems, and rational combination strategies with immune checkpoint blockade and metabolic modulators to overcome tumor-intrinsic resistance and minimize systemic toxicity. CONCLUSIONS: Understanding the cell-type-specific and spatial dynamics of cGAS–STING signaling is crucial for the rational design of precision immunotherapies. Future research should emphasize context-dependent modulation of STING activity to maximize therapeutic benefit while limiting adverse effects. Integrating multi-omics technologies and spatially guided drug delivery may ultimately enable personalized modulation of the cGAS–STING axis, transforming it into a clinically effective and safe strategy for cancer immunotherapy.

Humans↗

PubMed2026

An Integrated Proteomics and Genomics Approach to Identify Essential Protein Kinases During Human Trophoblast Development.

In the developing human placenta, three subtypes of trophoblast cells, cytotrophoblasts (CTBs), extravillous trophoblasts (EVTs), and syncytiotrophoblasts (STBs), mediate critical functions essential for a successful pregnancy. CTBs constitute the stem/progenitor compartment and differentiate into STBs and EVTs within the floating and anchoring villi, respectively. STBs establish the maternal-fetal exchange interface and secrete human chorionic gonadotropin (hCG), a hormone vital for the maintenance of early pregnancy. EVTs anchor the maternal endometrium and invade the uterine tissue to remodel maternal cells, supporting implantation and progression of pregnancy. In this study, we used human trophoblast stem cells (hTSCs) as a model system and performed quantitative, label-free liquid chromatography-tandem mass spectrometry (LC-MS/MS) to profile the proteome and phosphoproteome in TSC stem state (analogous to undifferentiated CTBs) and following their differentiation to STBs and EVTs. Through a multiomics approach, we integrated our proteomics data with global gene expression profiles to correlate cell-type specific gene and protein expression during human trophoblast development. We also identified global phosphoproteome and analyzed kinases that are specifically active in hTSC stem state, as well as in differentiated STBs and EVTs. We experimentally validated specific kinases, such as BUB1B, PAK6, PKYMT1, and TNIK, that are essential for maintaining the hTSC stem-state. Additionally, atypical protein kinase C isoforms PKCζ are essential for STB development, whereas PTK2B, SRC, TRIO, and LYN are important for EVT development. Our findings highlight key kinases uniquely required for specific stages of trophoblast development during human placentation and suggest that pharmacological inhibition of these kinases could negatively impact the placentation process during pregnancy.

Humans↗

PubMed2025

Drought recovery in plants triggers a cell-state-specific immune activation.

All organisms experience stress as an inevitable part of life, from single-celled microorganisms to complex multicellular beings. The ability to recover from stress is a fundamental trait that determines the overall resilience of an organism, yet stress recovery is understudied. To investigate how plants recover from drought, we examine a fine-scale time series of RNA sequencing starting 15 min after rehydration following moderate drought. We reveal that drought recovery is a rapid process involving the activation of thousands of recovery-specific genes. To capture these rapid recovery responses in different Arabidopsis thaliana (A. thaliana) leaf cell types, we perform a single-nucleus transcriptome analysis at the onset of drought recovery, identifying a cell type-specific transcriptional state developing independently across cell types. To further validate the cell-type specific transcriptional changes observed during drought recovery, we employ spatial transcriptomics using multiplexed error-robust fluorescence in situ hybridization (MERFISH), revealing anatomical localization of recovery-induced gene expression programs across Arabidopsis leaf tissues. Furthermore, we reveal a recovery-induced activation of the immune system that occurs autonomously, and which enhances pathogen resistance in vivo in A. thaliana, wild tomato (Solanum pennellii) and domesticated tomato (Solanum lycopersicum cv. M82). Since rehydration promotes microbial proliferation and thereby increases the risk of infection, the activation of drought recovery-induced immunity may be crucial for plant survival in natural environments. These findings indicate that drought recovery coincides with a preventive defense response, unraveling the complex regulatory mechanisms that facilitate stress recovery in different plant cell types.

Arabidopsis↗

PubMed2025

Profiling hippocampal neuronal populations reveals unique gene expression mosaics reflective of connectivity-based degeneration in the Ts65Dn mouse model of Down syndrome and Alzheimer's disease.

INTRODUCTION: Individuals with Down syndrome (DS) exhibit neurological deficits throughout life including the development of in Alzheimer's disease (AD) pathology and cognitive impairment. At the cellular level, dysregulation in neuronal gene expression is observed in postmortem human brain and mouse models of DS/AD. To date, RNA-sequencing (RNA-seq) analysis of hippocampal neuronal gene expression including the characterization of discrete circuit-based connectivity in DS remains a major knowledge gap. We postulate that spatially characterized hippocampal neurons display unique gene expression patterns due, in part, to dysfunction of the integrity of intrinsic circuitry. METHODS: We combined laser capture microdissection to microisolate individual neuron populations with single population RNA-seq analysis to determine gene expression analysis of CA1 and CA3 pyramidal neurons and dentate gyrus granule cells located in the hippocampus, a region critical for learning, memory, and synaptic activity. RESULTS: The hippocampus exhibits age-dependent neurodegeneration beginning at ~6 months of age in the Ts65Dn mouse model of DS/AD. Each population of excitatory hippocampal neurons exhibited unique gene expression alterations in Ts65Dn mice. Bioinformatic inquiry revealed unique vulnerabilities and differences with mechanistic implications coinciding with onset of degeneration in this model of DS/AD. CONCLUSIONS: These cell-type specific vulnerabilities may underlie degenerative endophenotypes suggesting precision medicine targeting of individual populations of neurons for rational therapeutic development.

Alzheimer’s disease↗

PubMed2026

Cardiovascular Organoids With Adjustable Endothelial Composition via SOX17-Engineered hPSCs.

Organoids are considered a novel modeling platform for studying human biology and advancing health research. With the ability to demonstrate complex 3D structure and multicellular interactions, organoids have advanced studies in all major organs as a reliable model. In this study, we generated an advanced cardiovascular organoid by using a genome-edited human pluripotent stem cell line with inducible SOX17 expression, enabling controlled endothelial specification, adjustable cell-type composition, and human heart-like morphology. Our organoids recapitulated the cardiotoxic phenotypes of FDA-approved chemotherapeutic doxorubicin, manifesting as decreased cell viability and diminished contractile activity. Cryoinjury-induced myocardial infarction in our organoids led to reduced beating, viability, and α-actinin expression, along with increased fibroblast formation, which were mitigated by Captopril. Lastly, isoproterenol treatment increased peak Ca2+ transient amplitude and shortened APD50 in our organoids, consistent with previously reported β-adrenergic responses. In summary, we established a protocol for generating in vitro 3D cardiovascular organoids with controllable cellular composition and heart-like structures, providing a robust and easy-to-produce platform for future studies of human heart disease.

Humans↗

PubMed2026

Metabolic atlas of early human cortex reveals glycolytic remodeling and pentose phosphate pathway control of cell fate transitions.

Cortical development involves rapid progenitor expansion and cell diversification supported by tightly regulated metabolic programs, yet these programs remain largely uncharacterized in human development. Here, we generated a metabolic atlas of the early human cortex using primary tissue and stem cell-derived cortical organoids. We observed dynamic changes in core metabolic functions, including an unexpected increase in glycolysis and pentose phosphate pathway (PPP) activity during late neurogenesis. Manipulation of glucose availability in cortical organoids altered cell-type composition, increasing outer radial glia (oRG) and inhibitory neuron populations. Pharmacological and genetic inhibition of PPP enzymes recapitulated these cell fate changes. Ribose was sufficient to rescue radial glia (RG) gene expression changes, revert organoid cell-type composition, and restore levels of ATP and hypotaurine. These data identify a critical role for the PPP in modulating RG cell fate specification and generate a resource for future exploration of additional metabolic pathways in human cortical development.

cell fate↗

PubMed2026

A contextual activity score (CAS) for inferring ADAR-associated transcriptional activity across RNA-seq, single-cell, and spatial transcriptomics.

BACKGROUND AND OBJECTIVE: Adenosine-to-inosine RNA editing, catalyzed by Adenosine Deaminases Acting on RNA (ADARs), is a widespread modification involved in neural function, immune regulation, and cancer. The Alu Editing Index (AEI) is the standard metric to estimate ADAR activity but requires raw sequencing reads and is poorly suited for single-cell and spatial transcriptomic data. This study aimed to develop an alternative framework for inferring ADAR-associated transcriptional activity from gene expression data across diverse transcriptomic technologies. METHODS: We developed the Contextual Activity Score (CAS), a framework based on transcriptional signatures from ADAR perturbation experiments. Context-specific signatures were generated for human neurons, mouse neurons, and cancer models to infer ADAR1 and ADAR2 activity. CAS was computed from normalized gene expression matrices using regulon-based enrichment analysis. Performance was evaluated by comparing with the Alu Editing Index across bulk RNA sequencing datasets, simulated sequencing depths, and library preparation protocols. RESULTS: CAS showed strong concordance with the Alu Editing Index across multiple datasets, while remaining robust to reduced sequencing depth and different library protocols. Unlike the Alu Editing Index, CAS can be applied to single-cell and spatial transcriptomic data and enables the independent assessment of ADAR2 activity. In cancer and neuronal contexts, CAS captured biologically meaningful variations in ADAR-associated transcriptional activity at sample, cell-type, and spatial levels. CONCLUSION: CAS provides a scalable approach applicable across multiple RNA-seq protocols for estimating ADAR-associated transcriptional activity using gene expression data. This method, implemented in an open-source R package for broad adoption, expands the ability to study ADAR-associated transcriptional activity across transcriptomic modalities where direct editing quantification is challenging, such as single-cell and spatial transcriptomics.

Adenosine Deaminase↗

PubMed2026

Multi-omics and spatial transcriptomics reveal that S100A10 drives CD8+ T-cell exhaustion and immune evasion in hepatocellular carcinoma through cPLA2-5-LOX-mediated arachidonic acid metabolism and ferroptosis.

Immune evasion in hepatocellular carcinoma (HCC) represents a major biological barrier limiting the efficacy of immunotherapy, yet its molecular basis remains incompletely understood. Increasing evidence indicates that tumor metabolic reprogramming and ferroptosis-related signaling play critical roles in shaping an immunosuppressive tumor microenvironment (TME); however, the specific regulatory factors involved remain unclear. This study aims to systematically elucidate the functional role of S100 calcium-binding protein A10 (S100A10) in immune evasion in HCC, with a particular focus on the molecular mechanisms by which S100A10 regulates CD8+ T-cell exhaustion through arachidonic acid (AA) metabolism and ferroptosis, as well as its potential therapeutic implications. To this end, data from The Cancer Genome Atlas Liver Hepatocellular Carcinoma (TCGA-LIHC) cohort are integrated to analyze the expression patterns of S100A10, its prognostic value, and its association with the immune microenvironment. S100A10 overexpression and knockout models are established in HCCLM3 and MHCC97L cell lines, and S100A10-mediated metabolic pathway reprogramming is characterized using transcriptomic profiling, untargeted metabolomics, and ferroptosis-related functional assays. In parallel, single-cell RNA sequencing (scRNA-seq) and spatial transcriptomics are employed to delineate the cell-type specificity and spatial distribution of S100A10. Furthermore, human CD8+ T-cell co-culture systems and orthotopic mouse HCC models are used to evaluate the impact of S100A10 on immune function and responsiveness to anti-programmed cell death protein 1 (anti-PD-1) therapy. The results demonstrate that S100A10 is significantly upregulated in HCC and is closely associated with poor prognosis and an immunosuppressive state. Mechanistically, S100A10 activates cytosolic phospholipase A2-arachidonate 5-lipoxygenase (cPLA2-5-LOX)-mediated AA oxidative metabolism, leading to the accumulation of lipid peroxidation products and ferroptosis-associated signals, thereby driving CD8+ T-cell exhaustion and promoting immune evasion. Significantly, inhibition of S100A10 reshapes the tumor immune microenvironment (TIME) and enhances the therapeutic efficacy of anti-PD-1 treatment. Collectively, these findings identify S100A10 as a critical regulator of metabolic-immune coupling in HCC and provide a theoretical basis for combinatorial strategies targeting metabolism and immunotherapy.

Arachidonic acid metabolism↗

PubMed2026

A single-cell atlas of multiple myeloma defines malignant archetypes and proliferative states.

Multiple myeloma (MM) is a plasma-cell malignancy with extensive genomic and transcriptional heterogeneity, limiting disease classification and precision therapy. Here we generated a clinically annotated, population-scale, single-cell atlas of MM from 341 individuals spanning the disease and treatment continuum. We identified five recurrent malignant transcriptional archetypes and an orthogonal proliferative program associated with genomic features, therapeutic resistance and clinical outcomes. Validation in the independent CoMMpass cohort demonstrated robustness, prognostic relevance and portability across platforms. We developed a single-cell, target-discovery pipeline prioritizing malignant enrichment, cell-type specificity and tissue restriction, identifying FCRL2 as a plasma-restricted or B cell-lineage-restricted surface target expressed by malignant plasma cells. FCRL2-targeted chimeric antigen receptor T cells demonstrated antigen-specific activity in vitro and survival benefit in vivo. Together, these data provide a clinically actionable blueprint for patient stratification and precision target nomination in plasma-cell malignancies.

Multiple Myeloma↗

PubMed2026

Dysregulated adult hippocampal neurogenesis in major depressive disorder.

Major depressive disorder (MDD) is associated with reduced hippocampal volume, altered connectivity and negative memory bias, suggesting disrupted hippocampal plasticity. Dysregulated adult hippocampal neurogenesis is a potential contributor, but its relevance in humans and role in MDD remain unclear. Here we investigated the molecular basis of hippocampal dysfunction in nonmedicated individuals with MDD by integrating analyses of neurogenic trajectories, cell-type- and subfield-specific gene expression, chromatin accessibility and protein expression. We identify a neurogenic lineage in the adult human hippocampal subgranular zone and provide evidence for a stalled neurogenic process in MDD, associated with transcriptional regulation, stress-related reprogramming and interferon signaling across developmental stages. Excitatory and inhibitory neurons show dysregulation of transcription factor networks affecting cell states. Cellular stress, excitatory-inhibitory imbalance, impaired synaptic plasticity, reduced metabolic capacity and immune activation, underlie impaired neurogenesis and reduced hippocampus circuit plasticity. Findings indicate genetic and epigenetic regulation of gene expression in MDD, and overlapping pathogenetic mechanisms with autoimmune, neurodevelopmental and neurodegenerative diseases. This work provides a new understanding of the pathogenesis of hippocampus-dependent cognitive symptoms in MDD and suggests potential therapeutic targets.

Journal Article↗

PubMed2025

Detection of cell-type-specific differentially methylated regions in epigenome-wide association studies.

MOTIVATION: DNA methylation at cytosine-phosphate-guanine (CpG) sites is one of the most important epigenetic markers. Therefore, epidemiologists are interested in investigating DNA methylation in large cohorts through epigenome-wide association studies (EWAS). However, the observed EWAS data are bulk data with signals aggregated from distinct cell types. Deconvolution of cell-type-specific signals from EWAS data is challenging because phenotypes can affect both cell-type proportions and cell-type-specific methylation levels. Recently, there has been active research on detecting cell-type-specific risk CpG sites for EWAS data. However, existing methods all assume that the methylation levels of different CpG sites are independent and perform association detection for each CpG site separately. Although these methods significantly improve the detection at the aggregated-level-identifying a CpG site as a risk CpG site as long as it is associated with the phenotype in any cell type, they have low power in detecting cell-type-specific associations for EWAS with typical sample sizes. RESULTS: Here, we develop a new method, Fine-scale inference for Differentially Methylated Regions (FineDMR), to borrow strengths of nearby CpG sites to improve the cell-type-specific association detection. Via a Bayesian hierarchical model built upon Gaussian process functional regression, FineDMR takes advantage of the spatial dependencies between CpG sites. FineDMR can provide cell-type-specific association detection as well as output subject-specific and cell-type-specific methylation profiles for each subject. Simulation studies and real data analysis show that FineDMR substantially improves the power in detecting cell-type-specific associations for EWAS data. AVAILABILITY AND IMPLEMENTATION: FineDMR is freely available at https://github.com/JiaRuofan/Detection-of-Cell-type-specific-DMRs-in-EWAS.

DNA Methylation↗

PubMed2026

ARCADIA reveals spatially dependent transcriptional programs through integration of scRNA-seq and spatial proteomics.

MOTIVATION: Cellular states are strongly influenced by spatial context, but single-cell RNA sequencing (scRNA-seq) loses information about local tissue organization, while spatial proteomic assays capture limited marker panels that constrain transcriptomic inference. Integrating these modalities can elucidate how spatial niches shape transcriptional programs, yet existing approaches depend on either feature-level correspondence such as gene-protein linkage or cell-level barcode pairing, which is often unavailable. RESULTS: We present ARCADIA (ARchetype-based Clustering and Alignment with Dual Integrative Autoencoders), a generative framework for cross-modal integration that operates without cell barcode pairing and does not assume direct feature-to-feature correspondence. ARCADIA identifies modality-specific archetypes, that is, convex combinations of cells representing extreme phenotypic states, and aligns these anchors across modalities by minimizing the discrepancy between their cell-type composition profiles. The aligned archetypes define a shared coordinate system that anchors dual variational autoencoders (VAEs) trained with cross-modal geometric regularization, preserving archetype structure and spatial neighborhood information while enabling bidirectional translation between modalities. On semi-synthetic CITE-seq data, ARCADIA outperforms existing weak-linkage methods. Applied to independent human tonsil scRNA-seq and CODEX data, ARCADIA reconstructs known tissue architecture and reveals spatially dependent transcriptional programs linking B-cell maturation and T-cell activation or exhaustion to microenvironmental niches. AVAILABILITY AND IMPLEMENTATION: Source code is accessible at https://github.com/azizilab/ARCADIA_public. Reproducibility scripts and data are available at https://github.com/azizilab/arcadia_reproducibility.

Proteomics↗

PubMed2026

DeepGeSeq: deep learning library for genomic sequence modeling and analysis.

MOTIVATION: Deep learning methods have demonstrated significant potential in genomics, enabling broad applications such as sequence activity prediction, regulatory rule identification, and variant effect quantification. However, their widespread adoption is often hindered by the steep computational learning curve required for model construction, training, and downstream biological interpretation. Here, we introduce DeepGeSeq, a user-friendly Deep-learning library tailored for Genomic Sequence modeling and analysis. RESULTS: By integrating state-of-the-art architectural modules, DeepGeSeq streamlines the entire deep learning workflow, requiring minimal user input via a simple configuration file and an intuitive agentic skill. We comprehensively validate the efficacy of DeepGeSeq through diverse case studies, encompassing pipeline verification using synthetic datasets, the reproduction and application of established models, and model fine-tuning coupled with biological interpretation on user-defined data. Furthermore, we demonstrate DeepGeSeq's versatility in domain-specific applications, including single-cell ATAC-seq modeling for cell-type clustering, and MPRA data modeling coupled with in silico saturation mutagenesis to dissect cis-regulatory elements. Ultimately, DeepGeSeq bridges the gap between computational complexity and biological discovery, providing an accessible resource that facilitates the development and broad application of deep learning methods in genomics research. AVAILABILITY AND IMPLEMENTATION: https://github.com/JiaqiLi1024/DeepGeSeq.

Deep Learning↗

PubMed2026

Beyond Bulk: Cell-Type-Resolved Epigenomics as the Path Forward in Alzheimer's Disease Research.

Alzheimer's disease (AD) is a complex neurodegenerative disorder in which most risk variants are noncoding and are enriched at gene regulatory regions, implicating epigenetic mechanisms as central mediators of disease pathogenesis. For most of the history of AD epigenetics research, bulk tissue analysis has dominated, obscuring the fundamentally distinct epigenomic landscapes of individual brain cell types and masking cell-type-specific contributions to disease. Advances in single-cell and single-nucleus sequencing, fluorescence-activated nuclei sorting and multiplexed epigenomic platforms have transformed this landscape, enabling cell-type-resolved profiling of chromatin accessibility, DNA methylation, histone modifications and transcription across the major neuronal, glial and neurovascular populations of the human brain. Here, we review these advances, structured around the argument that cell-type resolution is not a methodological refinement but a conceptual necessity. We describe the distinct epigenomic programs disrupted in neurons, microglia, astrocytes, oligodendrocytes and neurovascular cells in AD, highlighting how each cell type responds to pathology. We discuss the discovery of epigenomic erosion, the progressive loss of cell-type-specific epigenomic identity across virtually all brain cell populations as AD advances, as a unifying disease mechanism linking chromatin dysregulation to cognitive decline. Finally, we identify critical gaps in current knowledge, including the near-complete absence of cell-type-resolved histone modification and DNA methylation data for most brain cell types, the underrepresentation of rare populations in standard preparations and the untapped potential of metabolic acylation marks as indicators of the epigenome-metabolism interface in neurodegeneration.

Humans↗

PubMed2026

Cell type-dependent induction of type I interferon and PARP1 activation in astrocytes and neurons during chikungunya virus infection.

Chikungunya virus, a mosquito-borne alphavirus, causes fever, rash, arthritis, and neurological disorders. Its non-structural protein 3 harbors a macrodomain, a key neurovirulence factor that removes adenosine diphosphate ribose from ADP-ribosylated substrates. Notably, chikungunya virus infection results in distinct ADP-ribosylation patterns and non-structural protein 3 macrodomain-mediated replication dynamics in astrocytes and neurons. Understanding the connection between ADP-ribosylation and the activation of innate immunity, particularly interferon release, is key to elucidating how the cellular immunological state influences ADP-ribosylation, an understudied post-translational modification during viral infection. Here, murine astrocytic (C8-D1A) and neuronal (NSC-34) cells were infected with chikungunya virus to profile transcript and protein expression of innate immune mediators and type I IFNs. The role of PARP1 in global ADP-ribosylation patterns was assessed using PARP-specific inhibitors and genetic depletion approaches. Our investigations revealed that neuronal chikungunya virus infection induces ADP-ribosylation through PARP1 activation, driven by caspase-3-mediated apoptosis, without transcriptionally activating PARPs. In contrast, astrocytic infections showed minimal ADP-ribosylation despite transcriptional activation of interferon-stimulated PARPs. Neurons exhibited limited innate immune response gene transcriptional activity, whereas astrocytes demonstrated strong upregulation of genes essential for pattern recognition receptor activation, thus enhancing double-stranded RNA sensing and increasing type I interferon production during infection. We posit that PARP1 activation and type I IFN response differentially regulate ADP-ribosylation in chikungunya virus-infected neural cells in a cell type-dependent manner.IMPORTANCEChikungunya virus is an emergent mosquito-borne alphavirus increasingly associated with neurological infection and subsequent long-term disabilities. Its continued global spread and recurrent outbreaks underscore its significant pandemic potential and the urgent need for effective countermeasures. Chikungunya virus showcases distinct, cell-type dependent replication dynamics within astrocytes and neurons, two major permissive cerebral cell types. However, understanding of the immunological basis of such cell type-specific infection dynamics remains limited, yet is necessary to elucidate virus pathogenesis within the brain and thus identification of downstream drug targets. Our study characterized two distinctly activated innate immunological pathways in chikungunya virus-infected astrocytes versus neurons, thus significantly contributing to molecular understanding cell type-specific chikungunya virus neurovirulence on a molecular level.

Animals↗

PubMed2026

IL1RAP Is Associated With an Inflammation-Immunity-Related State in Skin Cutaneous Melanoma: Integrative Evidence From Pan-Cancer Data and Melanoma Immunotherapy Cohorts.

BACKGROUND: The crosstalk between inflammation and immunity plays a central role in tumor progression, immune evasion, and therapeutic response. Interleukin-1 receptor accessory protein (IL1RAP) is a key adaptor in inflammatory signaling, yet its immunological relevance and clinical implications in skin cutaneous melanoma (SKCM) remain largely unexplored. METHODS: We performed an integrative analysis combining pan-cancer and melanoma-focused datasets. Bulk transcriptomic, single-cell, spatial transcriptomic, genomic alteration, pharmacogenomic, and clinical survival data were obtained from TCGA, GTEx, GEO, ENA, and other public resources. IL1RAP expression was evaluated across cancer types in relation to diagnostic performance, immune subtypes, survival outcomes, functional pathway activity, immune-genomic states, somatic alterations, and drug-response metrics. Melanoma-focused analyses examined immune infiltration, methylation-derived tumor-infiltrating lymphocyte (MeTIL) scores, and exploratory survival associations in five treatment cohorts; the survival groups were defined using cohort-specific optimal cutoffs rather than median splits. RESULTS: IL1RAP expression differed between tumor and normal tissues in multiple cancers, although the direction and magnitude varied by cancer type. Pan-cancer survival associations were likewise context dependent. Single-cell and spatial transcriptomic resources indicated cell-type and spatial heterogeneity of IL1RAP expression within tumor microenvironments. Pathway, immune-genomic, and pharmacogenomic analyses identified exploratory associations with functional states, genomic features, and drug-response metrics. In SKCM, IL1RAP expression was associated with several immune-infiltration estimates and higher MeTIL scores. Across five melanoma immunotherapy cohorts, the direction and magnitude of the overall survival associations varied substantially. CONCLUSIONS: This retrospective integrative analysis suggests that IL1RAP may mark an inflammation-immunity-related state in SKCM. The heterogeneous associations across cancers and melanoma treatment cohorts support further validation but do not establish IL1RAP as a causal regulator, a treatment-response predictor, or a therapeutic target.

IL1RAP↗

PubMed2025

Multi-omics analysis reveals distinct spatial compartmentalization of lung repair niches in pediatric ARDS.

BACKGROUND: Pediatric acute respiratory distress syndrome (PARDS), often triggered by viral infections, is a life-threatening condition. Despite its severity, children demonstrate significantly better survival rates and superior lung repair compared to adults. However, the mechanisms underlying this age-specific advantage remain incompletely understood. PATIENTS AND METHODS: We conducted a pilot multi-omics study of influenza-associated PARDS integrating single-cell RNA sequencing (scRNA-seq) of pediatric lung tissue and bronchoalveolar lavage fluid (BALF), spatial transcriptomics, and plasma proteomics. Analyses were harmonized with the Human Lung Cell Atlas (HLCA) reference, reanalysis of public pediatric PARDS airway scRNA-seq, and contextual comparisons to adult lethal COVID-19 lung. RESULTS: Tissue scRNA-seq and spatial data indicated outcome-linked divergence in PARDS. Survivor showed spatially restricted repair with preserved alveolar type II (AT2) cells, AT2-to-alveolar type I (AT1) differentiation signatures, and higher KRT17, whereas fatal case and adults exhibited diffuse immune activation with pro-fibrotic and pro-apoptotic signaling. In BALF, KRT17-positive airway stress–repair epithelial cells (hillock-like) increased from the acute to recovery phase, and plasma proteomics showed higher circulating KRT17 in survivors. HLCA-based label transfer strengthened cell-type definitions and enabled pediatric–adult comparisons suggesting biological and developmental differences; the adult lethal COVID-19 atlas provided a benchmark with attenuated epithelial repair and prominent collagen CTHRC1-pathologic fibroblasts. Fibroblast programs were regionally compartmentalized, with injury-enriched CTHRC1+ states versus alveolar fibroblasts in preserved areas, and showed stronger injury–homeostasis anti-correlation in fatalities. Myeloid remodeling included BALF transitions from FCN1-high inflammatory states toward FABP4-positive resident-like states, consistent with public pediatric datasets showing reduced inflammatory and interferon-stimulated gene (ISG) modules and severity-linked increases in aged neutrophils. CONCLUSIONS: This pilot multi-omics case series outlines putative pediatric lung repair niches in influenza-associated PARDS. KRT17-positive transitional epithelium, preserved AT2 differentiation, and restoration of resident-like macrophages may align with recovery, whereas diffuse immune activation and CTHRC1-enriched fibroblast programs may accompany worse outcomes. HLCA-guided annotations and adult benchmarks indicate possible age-related differences, warranting validation in larger multi-center cohorts.

Humans↗

PubMed2026

Systematic characterization of neurotransmitter receptor dysregulation identifies a neural-related prognostic signature associated with biochemical recurrence in prostate cancer.

BACKGROUND: The nervous system is increasingly recognized to play a critical role in tumor initiation and progression. Central to this complex relationship are the interactions between neurotransmitters secreted by neurons and their receptors (neurotransmitter receptors, NTRs) expressed on cancer cells, which activate multiple intracellular signaling pathways. However, the spectrum of NTR dysregulation and its association with biochemical recurrence (BCR) in prostate cancer (PCa) has not been explored. Therefore, the aim of this study was to fill this gap. METHODS: We systematically characterized the expression profiles of 130 NTR genes by integrating bulk and single-cell transcriptomic data. Consistently dysregulated NTR (cdNTR) genes were identified and used to construct a PCa signature (PCaSig) using elastic-net regression. The robustness of PCaSig was evaluated across three independent cohorts. In addition, the associations of PCaSig with clinicopathological characteristics, genomic alterations, tumor immune-related characteristics, and biological pathways were comprehensively investigated. RESULTS: Thirteen cdNTR genes with strong cell-type specificity, particularly in luminal epithelial cells, were identified. PCaSig robustly stratified patients into distinct BCR risk groups across multiple independent cohorts and remained an independent predictor after adjustment for clinicopathological factors. High PCaSig scores were associated with aggressive clinicopathological features, elevated tumor mutation burden (TMB), suppression of neurotransmitter-related signaling, and activation of cell-cycle and immune-related pathways. Notably, PCaSig refined prognostic stratification regardless of TMB status and was associated with distinct immune-related characteristics, including immune checkpoint expression and immune cell infiltration. Incorporation of PCaSig into a clinical nomogram significantly improved prognostic accuracy and clinical net benefit. CONCLUSIONS: These findings establish NTR dysregulation as a previously underappreciated dimension of PCa and support PCaSig as a clinically relevant tool for personalized management.

Neurotransmitter receptor (NTR)↗