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PubMed2026

Endocrine-disrupting chemical-induced gene networks confer coronary heart disease risk revealed by causal inference and single-cell analyses.

BACKGROUND: Endocrine-disrupting chemicals (EDCs) are linked to coronary heart disease (CHD), but underlying mechanisms remain unclear. We aimed to identify EDC-related genes and evaluate their causal roles in CHD. METHODS: We curated EDC-related genes from a compound-gene interaction database and integrated them with CHD genome-wide association study (GWAS) summary statistics and tissue-specific expression quantitative trait loci (eQTL) data. Two-sample Mendelian randomization (MR) and Bayesian colocalization were applied to infer causality. Functional enrichment, single-cell RNA sequencing of human coronary arteries, and EDC-gene networks were further analyzed. RESULTS: After FDR correction, 39 genes were significantly associated with CHD risk via MR. Four genes-ZNF827, FCHO1, IPO9 (protective), and RPL13 (risk-increasing)-showed strong colocalization (PPH4 > 0.9). Pathway and single-cell analyses of coronary artery tissue indicated that vascular and immune pathways mediate these effects. An interaction network highlighted associations between specific EDCs and candidate genes implicated in CHD susceptibility. CONCLUSION: This integrative genomic study provides evidence that EDCs influence CHD susceptibility through distinct gene networks, revealing potential mechanisms and molecular targets for prevention and therapy.

Humans↗
PubMed2025

Growth Hormone Alleviates Atherosclerosis Through Regulating the Activity of PI3K/AKT Pathway: Insights From Single-Cell Sequence and Mechanism Exploration.

PURPOSE: This research sought to investigate the impact and underlying mechanisms of growth hormone (GH) on atherosclerosis (AS) based on the analysis of single-cell RNA sequencing (scRNA-seq) data. METHODS: We analyzed the impact of GH on arterial vascular smooth muscle cells (VSMCs) by utilizing scRNA-seq data obtained from both atherosclerotic and healthy vascular tissues in mice. AS was induced in C57BL/6 and ApoE-/- mice through hypophysectomy performed via the parapharyngeal approach, followed by a high-fat diet (HFD), resulting in the C57-Hx and ApoE-/--Hx models. AS was evaluated by measuring arterial lipid deposition, plaque progression, collagen loss, vascular inflammation, and oxidative stress. Serum metabolite alterations were assessed using liquid chromatography-mass spectrometry (LC-MS). RNA sequencing was employed to examine the underlying mechanisms of GH in the context of AS treatment, with findings further confirmed through western blot analysis. In vitro experiments involved treating VSMCs with oxidized low-density lipoprotein (ox-LDL) to simulate atherosclerotic injury. The formation of foam cells was evaluated by measuring lipid accumulation, inflammatory responses, apoptosis, and the expression levels of foam cell-related markers. Finally, the PI3K/AKT inhibitor LY294002 confirmed that GH alleviates AS via the PI3K/AKT signaling pathway. RESULTS: scRNA-seq data analysis showed that growth hormone signaling was reduced in VSMCs of atherosclerotic arteries. HFD led to elevated levels of serum total cholesterol (TC), triglycerides (TGs), and low-density lipoprotein cholesterol (LDL-C), accompanied by increased lipid deposition, inflammatory responses, and oxidative stress. In contrast, high-density lipoprotein cholesterol (HDL-C) and insulin-like growth factor 1 (IGF-1) levels were lower in C57-Hx mice. GH treatment improved HFD-induced AS in ApoE-/--Hx mice. LC-MS analysis revealed that GH altered lipid metabolism in serum samples from C57-sham, C57-Hx, ApoE-/--Hx, and ApoE-/--Hx-GH(3) mice. GH maintained lipid balance by increasing 1-palmitoyl-2-oleoyl-sn-glycerol-3-phosphocholine (POPC), PE-NMe2(18:1(9z)/18:1(9z)) (DMPE), and 4-chloro-2-nitrobenzylalcohol levels and decreasing 1-heptadecanoyl-sn-glycerol-3-phosphocholine. RNA sequencing showed significant gene expression differences in the aortas of C57-sham and C57-Hx mice. Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis revealed that GH inhibited the progression of AS by modulating the phosphatidylinositol 3-kinase/protein kinase B (PI3K/AKT) signaling pathway, a finding that was validated through western blotting. Further in vitro studies demonstrated that GH exerted protective effects on VSMCs against ox-LDL-induced damage through activation of the PI3K/AKT pathway, as evidenced by experiments using the specific PI3K inhibitor LY294002. CONCLUSION: GH alleviates the development of AS through the activation of the PI3K/AKT pathway. The findings of this research emphasize the therapeutic potential of GH in inhibiting AS and highlight the importance of the PI3K/AKT pathway as a promising target for clinical intervention.

PI3K/AKT signaling pathway↗
PubMed2026

Perturbation of genes linked to common schizophrenia risk variants identifies cilia programs.

Schizophrenia (SCZ) is a common psychiatric disorder characterized by psychosis, emotional withdrawal, and cognitive deficits. Most SCZ risk variants reside in non-coding regions of the genome and are thought to influence disease risk by modulating gene regulation. However, the target genes, biological pathways, and cell types through which these variants exert their effects remain poorly understood. To address this gap, we employed in vivo CRISPR droplet sequencing (CROP-seq) in the postnatal mouse neocortex. We perturbed 12 SCZ risk genes previously linked to functionally validated risk variants, followed by single-cell RNA sequencing. We identified 3,031 differentially expressed genes (DEGs) that recapitulate transcriptional alterations observed in postmortem SCZ brains. Integrative analysis using DEG clustering, factor analysis, and gene regulatory network inference uncovered convergent gene programs with distinct biological functions and cell type specificity. Notably, ciliary transcriptional programs consistently emerged across analytical frameworks. The primary cilium is a neurocircuit modulating signaling organelle in neurons and glia that remains understudied in SCZ. Perturbation of key contributors to the ciliary transcriptional programs led to significant alterations in ciliary structure, suggesting that SCZ genetic risk factors may influence how brain cells sense and transduce extracellular signals through synapse-independent mechanisms. Together, this study provides the first in vivo characterization of the functional consequence of common variant architecture in SCZ and implicates ciliary dysfunction as a convergent downstream mechanism.

Journal Article↗
PubMed2026

Multi-omics identification and functional validation of signal regulatory protein gamma as a prognostic biomarker and immune regulator in head and neck squamous cell carcinoma.

BACKGROUND: Head and neck squamous cell carcinoma (HNSCC) comprises biologically diverse tumors, and durable responses to immune-checkpoint blockade are achieved by only a subset of patients. There remains a need for markers that connect clinical outcome with malignant-cell phenotypes and tissue-level immune organization. METHODS: We integrated The Cancer Genome Atlas HNSCC cohort (TCGA-HNSC), five Gene Expression Omnibus (GEO) validation cohorts, single-cell RNA sequencing, Visium spatial transcriptomics, cellular indexing of transcriptomes and epitopes by sequencing (CITE-seq)-informed protein-potential inference, pharmacogenomic screening, genetic-risk analysis and experimental validation. A reconstructed 296-pipeline survival modelling framework was used to prioritize prognostic hub genes across validation-cohort-specific analyses. RESULTS: SIRPG was repeatedly ranked among the top ten selected genes in all five validation cohorts. At single-cell resolution, SIRPG-high tumor cells showed stronger malignant-cell features, immune-inhibitory and metabolic programs, Scissor-positive risk association, CLCA2/P53-related perturbation signals and inferred SIRPG-CD47/signal regulatory protein (SIRP) communication. Spatial analyses placed this axis within an immune-checkpoint-coupled niche, supported by Maxspin/multiview intercellular spatial modelling (MISTy) spatial coupling, communication analysis by optimal transport (COMMOT)-inferred CD47-SIRPG communication and scProTrans-inferred CD47/SIRPG protein-potential overlap. Functionally, SIRPG knockdown reduced HNSCC cell viability and increased apoptosis, whereas re-expression of short hairpin RNA (shRNA)-resistant SIRPG restored the CLCA2-BAX/BCL2 protein response. CONCLUSION: Together, these findings identify SIRPG as an immune-related prognostic hub and context-dependent tumor-cell regulator associated with apoptosis, immune communication and spatial microenvironmental organization in HNSCC.

Humans↗
PubMed2026

Integrative evidence-knowledge marker selection enhances LLM-based cell type annotation in single-cell RNA-seq analysis.

BACKGROUND: Cell type annotation is essential for gaining biological insight from single-cell RNA sequencing data, yet manual labeling remains time-consuming and difficult to reproduce. Various computational approaches have been developed to automate this process, and recent studies suggest that large language models can infer cell types with promising accuracy in single-cell analysis. However, most workflows still rely on cluster-specific markers derived from gene expression alone or manual curation. As a result, marker selection can be sensitive to statistical criteria and dataset-dependent bias, which may lead to the selection of less informative genes or missing important markers, while providing limited biological context. RESULTS: To address this limitation, we introduce CELLIA, an LLM-based workflow for automated and robust cell type annotation. CELLIA employs an integrative evidence-knowledge marker selection strategy that combines statistical differential expression criteria with curated tissue-specific marker resources to identify informative marker genes. In benchmarking analyses of 102 cell types, this approach improved agreement with manual annotations. In addition, CELLIA achieved higher agreement in subtype-level analyses of closely related immune populations and was further evaluated in a non-immune stromal subtype setting, covering 25 cell types in total. CONCLUSION: By integrating evidence-knowledge from gene expression with curated biological prior knowledge, CELLIA provides a more stable marker selection and improves the reliability of LLM-cell type annotation.

Cell type annotation↗
PubMed2026

The extracellular matrix in cancer-associated fibrosis: molecular mechanisms and clinical relevance.

The ECM is a dynamic component of the tumor microenvironment with a critical role in cancer progression, invasion, metastasis, immune exclusion, and response to therapy. Recent advances in proteomic analyses investigating the insoluble ECM fractions (termed "matrisome analysis"), along with single-cell RNA sequencing and spatial transcriptomics, have revealed cancer-specific patterns of ECM remodeling. These studies have identified a panel of recurrently upregulated ECM proteins, including annexin A1, fibrillin-1, fibronectin, periostin, and tenascin-C, actively contributing to tumor growth, invasion, angiogenesis, and immune exclusion. The expression of the cancer-associated ECM is largely driven by cancer-associated fibroblasts (CAFs), whose molecular diversity has been dissected through single-cell profiling and consolidated in emerging CAF atlases across cancers. By investigating the matrisome composition and CAF heterogeneity, these studies have unraveled the pivotal role of the stroma in shaping tumor biology. Based on these discoveries, ECM proteins and CAFs are now being explored as biomarkers and therapeutic targets. Future integration of multi-omics datasets with clinical outcomes will help to translate these insights into novel biomarkers for patient stratification and stroma-directed therapeutic interventions.

Humans↗
PubMed2026

Integrated multi-omics analyses identify an RAS-SLC11A2-associated molecular framework linking iron metabolism with PCOS-related cardiometabolic risk.

INTRODUCTION: PCOS is a common endocrine disorder with elevated cardiometabolic risk, yet the role of the renin-angiotensin system (RAS)-iron metabolism axis in this comorbidity remains unclear. We explored its underlying mechanisms and evaluated the therapeutic potential of gentiopicroside. METHODS: Integrated multi-omics analyses combining transcriptomics, single-cell RNA sequencing, Mendelian randomization, machine learning, molecular docking, and in vitro functional assays were performed to identify shared molecular pathways and therapeutic targets across PCOS, hypertension, NAFLD, and T2DM. RESULTS: SLC11A2 was consistently dysregulated in PCOS transcriptomic datasets, and associated with iron metabolism, inflammatory response and oxidative stress pathways. Genetic analyses validated RAS-related regulation in hypertension susceptibility and revealed shared genetic architecture between PCOS and cardiometabolic traits. Network and single-cell analyses characterized SLC11A2-associated molecular patterns in disease-relevant cell types; machine learning identified disease-classifying molecular signatures. Gentiopicroside alleviated inflammatory and oxidative stress phenotypes, including reduced IL-6 expression and reactive oxygen species accumulation. CONCLUSION: This study defines an RAS-SLC11A2 molecular framework linking iron metabolism dysregulation to PCOS-related cardiometabolic risk, elucidating the mechanisms connecting ovarian dysfunction, inflammation, oxidative stress and hypertension, and supports gentiopicroside as a promising therapeutic candidate.

Humans↗
PubMed2026

Integrated single-cell and spatial transcriptomic analyses reveal malignant epithelial glycolytic heterogeneity and spatial niche remodeling during colorectal cancer progression.

Colorectal cancer (CRC) progression is shaped by metabolic reprogramming and complex interactions within the tumor microenvironment. However, the cellular heterogeneity, spatial organization, and clinical relevance of glycolytic activity in CRC remain incompletely understood. In this study, we integrated single-cell RNA sequencing, bulk transcriptomics, and spatial transcriptomics data to systematically characterize glycolytic heterogeneity in CRC. Glycolytic activity was quantified using five independent scoring methods, consistently showing that epithelial cells exhibited the highest glycolytic activity across the two single-cell cohorts. Stratification of CopyKAT-verified aneuploid malignant epithelial cells into high-glycolysis (HG) and low-glycolysis (LG) subgroups by glycolysis scores revealed that HG cells exhibited higher stemness scores and chromosomal copy number variations. Cell-cell communication analysis revealed that, compared with LG cells, HG cells exhibited increased interaction frequency and strength with immune and stromal populations, indicating enhanced malignant epithelial-microenvironment crosstalk. Spatial transcriptomics analyses further revealed that glycolytic activity varied across normal colorectal tissue, primary CRC, and colorectal liver metastases, accompanied by progressive remodeling of epithelial-associated spatial niches and MIF-mediated intercellular communication. Bulk transcriptomic analysis identified a glycolysis-related prognostic signature with robust predictive performance, which served as an independent prognostic factor for overall survival in CRC cohorts. Collectively, these findings indicate that glycolytic heterogeneity is a key feature of CRC malignant epithelial cells and is closely associated with tumor progression, microenvironmental remodeling, and clinical outcomes.

Humans↗
PubMed2026

CCT2 defines a highly cisplatin-resistant and poor-prognosis subtype of lung adenocarcinoma.

Cisplatin-based chemotherapy is a standard treatment for lung adenocarcinoma (LUAD), yet acquired cisplatin resistance remains a marked cause of treatment failure. The molecular mechanisms driving cisplatin resistance in LUAD have not been fully elucidated. The present study integrated bulk transcriptomic data, genomic mutation profiles and single-cell RNA sequencing data to systematically investigate cisplatin resistance in LUAD. Resistance-associated genes were identified through differential expression, survival analysis and database integration. Unsupervised clustering was used to define cisplatin resistance-associated subtypes. Functional characteristics were explored using pathway enrichment, immune infiltration, tumor mutation burden and weighted gene co-expression network analysis. A machine learning framework incorporating 101 algorithms was applied to identify key genes and construct a prognostic model. Single-cell analyses and in vitro experiments were performed to validate the biological role of the core gene. Molecular docking and molecular dynamics simulations were conducted to identify potential therapeutic compounds. A total of two molecular subtypes with distinct cisplatin resistance levels and prognostic outcomes were identified. The high-resistance subtype exhibited enhanced cell cycle activity, DNA repair signaling and immune heterogeneity. Machine learning analysis revealed a five-gene signature, with chaperonin-containing TCP1 subunit 2 (CCT2) emerging as a key regulator of cisplatin resistance. Single-cell analyses showed that CCT2 was predominantly enriched in resistant epithelial cell subpopulations. Functional experiments demonstrated that CCT2 knockdown significantly inhibited cell proliferation and enhanced cisplatin sensitivity in LUAD cell lines. A number of candidate compounds targeting CCT2 exhibited stable binding in silico. The present findings identified CCT2 as a key mediator of cisplatin resistance in LUAD and provided potential therapeutic strategies to overcome chemotherapy resistance.

chaperonin-containing TCP-1 subunit 2↗
PubMed2024

Whole-genome sequences reveal zygotic composition in chimeric twins.

While most dizygotic twins have a dichorionic placenta, rare cases of dizygotic twins with a monochorionic placenta have been reported. The monochorionic placenta in dizygotic twins allows in utero exchange of embryonic cells, resulting in chimerism in the twins. In practice, this chimerism is incidentally identified in mixed ABO blood types or in the presence of cells with a discordant sex chromosome. Here, we applied whole-genome sequencing to one triplet and one twin family to precisely understand their zygotic compositions, using millions of genomic variants as barcodes of zygotic origins. Peripheral blood showed asymmetrical contributions from two sister zygotes, where one of the zygotes was the major clone in both twins. Single-cell RNA sequencing of peripheral blood tissues further showed differential contributions from the two sister zygotes across blood cell types. In contrast, buccal tissues were pure in genetic composition, suggesting that in utero cellular exchanges were confined to the blood tissues. Our study illustrates the cellular history of twinning during human development, which is critical for managing the health of chimeric individuals in the era of genomic medicine.

Humans↗
PubMed2025

RELA Haploinsufficiency Manifesting as an Atypical Phenotype of Crohn's Disease.

BACKGROUND: Mutations in RELA, a key component of NF-κB signaling, are associated with dysregulated immune responses and inflammatory disorders. While immunodeficiency phenotypes associated with RELA haploinsufficiency have been reported, gastrointestinal manifestations remain poorly described. This study aimed to characterize the clinical, genomic, and immunological features of a patient presenting with an atypical Crohn's-like phenotype driven by RELA haploinsufficiency. METHODS: Whole-exome sequencing was performed, and results were confirmed by Sanger sequencing. Protein modeling, Western blotting, immunofluorescence, and nuclear extract-based NF-κB activation assays were conducted to assess the functional impact of the identified variant. Immune profiling was performed using mass cytometry time of flight (CyTOF) and single-cell RNA sequencing (scRNA-seq) and compared to controls. RESULTS: We studied a 17-year-old male diagnosed with pan-enteric Crohn's disease (CD), perianal fistulas, chronic mucocutaneous candidiasis, and chronic lymphopenia. Sequencing identified a heterozygous missense variant in RELA (c.587T>C, p.V196A) that potentially impairs RelA (p65) protein stability, confirmed by reduced activity and diminished protein expression. CyTOF analysis revealed decreased circulating T regulatory cells (Tregs), absence of mucosal Tregs, high apoptotic rates, and elevated IFN-γ induced levels, while scRNA-seq demonstrated a robust type I/II interferon signature in multiple immune subsets. Dysregulated mucosal-associated invariant T (MAIT) and cytotoxic CD4+ T cells exhibited upregulation of IL23R and ADAM12, further linking RELA dysfunction to enhanced pro-inflammatory T cell response and tissue inflammation. CONCLUSION: This study links RELA haploinsufficiency with CD-like features, Th1/Th17 polarization, and interferon-driven inflammation, emphasizing the importance of genetic evaluation in patients with atypical or refractory IBD.

Humans↗
PubMed2026

Exploring the transcriptional crosstalk between adipose tissue and locoregional recurrence in breast cancer using independent component analysis.

Locoregional recurrence (LRR) poses a persistent clinical challenge in breast cancer, with emerging evidence implicating the tumor-associated adipose tissue in modulating recurrence risk. This study investigates shared transcriptional programs between adipose tissue and breast tumors and examines their association with disease-free survival (DFS), particularly in the context of reconstructive surgery where adipose tissue from different body compartments are commonly used. We analyzed bulk gene expression data from 5,691 breast tumors and 978 human adipose tissue samples from different body compartments using consensus-independent component analysis (c-ICA) to identify transcriptional components (TCs). Gene set enrichment analysis (GSEA) and copy number alteration profiling were used for biological annotation. Associations between TCs and DFS were evaluated through univariate Cox regression. Key findings were validated using spatial transcriptomic and single-cell RNA sequencing datasets. Among the 411 TCs identified, 332 showed biological enrichment, and 35 were significantly associated with DFS. Four DFS-associated TCs (TC257, TC350, TC371, TC400) were enriched for adipogenesis-related genes and exhibited heightened activity in high-grade, triple-negative tumors and in patients with elevated BMI. Notably, TC350 was highly active in adipose tissue from common reconstructive donor sites (abdomen, omentum, subcutis) but not in native breast adipose tissue. Spatial transcriptomic and single-cell analyses confirmed the increased activity of these adipogenesis-related TCs in tumor regions and adipose cells. TC350 included FABP4, a gene previously linked to poor prognosis in breast cancer and considered as a potential new therapeutic target. Adipose tissue-derived transcriptional programs influence breast cancer prognosis and this seems to differ by tissue origin. These findings generate a hypothesis that donor site selection for adipose tissue in reconstructive surgery may impact LRR risk through adipogenesis-associated mechanisms. Further research is warranted to elucidate the biological and clinical implications of adipose-tumor transcriptional interactions.

Humans↗
PubMed2025

From genetic causality to druggable targets: A multiomics framework identifies ZSCAN16 in gout pathogenesis.

ObjectiveGout is a prevalent form of inflammatory arthritis in which many patients respond suboptimally to current therapies. Drug development is hampered by a lack of genetically validated targets, leading to high clinical trial attrition. This study aimed to systematically identify and prioritize novel, druggable targets for gout via a multilayered genetic and functional genomics approach.MethodsWe performed two-sample Mendelian randomization (MR) using cis-expression quantitative trait locus (cis-eQTL) data and dual independent gout genome-wide association study (GWAS) cohorts (openGWAS and FinnGen). The candidate genes were subjected to a rigorous validation pipeline including Bayesian colocalization, phenome-wide association studies (PheWASs) to assess pleiotropy and on-target safety, and single-cell RNA sequencing (scRNA-seq) to delineate the cellular context. Molecular docking was used to evaluate the structural druggability of prioritized targets.ResultsMR analysis revealed 15 genes causally associated with gout. Colocalization analysis (PPH4 > 0.8) prioritized two targets: ZSCAN16 (risk-increasing, OR = 1.04, 95% CI [1.02-1.06]) and TRIM10 (protective, OR = 0.96, 95% CI [0.94-0.98]). Crucially, PheWAS revealed that ZSCAN16 is highly specific to gout, whereas TRIM10 exhibited extensive pleiotropy with hematological and cardiometabolic traits, indicating significant safety risks. Single-cell analysis provided orthogonal validation, demonstrating flare-specific upregulation of ZSCAN16 in cytotoxic T/NK cells. Molecular docking confirmed ZSCAN16 as a structurally druggable target, showing high-affinity binding with known compounds (e.g. digoxin, binding energy = -9.6 kcal/mol).ConclusionsOur study identifies ZSCAN16 as a high-potential, druggable therapeutic target for gout, highlighting its genetic influence on specific immune cell activities during acute flares. Conversely, TRIM10 was deprioritized owing to substantial pleiotropic liabilities and poor chemical tractability. These findings suggest that ZSCAN16 could play a crucial role in the pathogenesis of gout and may provide a valuable lead for future drug discovery efforts.

Humans↗
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

Methylation-Associated Differentiation Features Define Biological and Prognostic Heterogeneity in CMS4 Colorectal Cancer.

Consensus molecular subtype 4 (CMS4) colorectal cancer (CRC) is associated with an aggressive clinical course and poor survival, yet the biological basis of heterogeneity within this subtype remains incompletely understood. DNA methylation is an epigenetic mechanism involved in transcriptional regulation, cellular differentiation, and colorectal tumorigenesis. Here, we integrated single-cell RNA sequencing (scRNA-seq), bulk data, and promoter DNA methylation data to characterize CMS4-associated cancer cell states and methylation-related features. Using the scAB algorithm, we integrated scRNA-seq with bulk CMS4 data and identified CMS4-related cells distributed across multiple patients. Single-cell analyses of cell-cell communication and transcriptional regulation revealed a CMS4-related cancer cell population characterized by macrophage migration inhibitory factor (MIF)-centered intercellular communication, enhanced caudal type homeobox 1 (CDX1) and Kruppel-like factor 5 (KLF5) regulon activity, and gene modules enriched in differentiation-related pathways. CytoTRACE analysis further stratified CMS4 cancer cells into poorly and well-differentiated states, yielding 802 differentially expressed genes (DEGs). Linking these differentiation-associated DEGs with bulk expression and promoter methylation data identified 218 methylation-associated DEGs showing significant inverse methylation expression correlations, suggesting a link between differentiation-related heterogeneity and promoter methylation. Univariable Cox regression followed by LASSO regression further prioritized eight genes for construction of the methylation and differentiation-related prognostic model (MeDiff-PM). MeDiff-PM consistently stratified overall survival in the TCGA CMS4 cohort and two independent validation cohorts, with cutoff-independent continuous Cox analyses further supporting its prognostic association across cohorts. And MeDiff-PM remained prognostically significant after adjustment for available clinical variables. High MeDiff-PM risk scores were associated with activation of P53, WNT, and ubiquitin-mediated proteolysis pathways and with consistent predicted drug response differences for compounds across three CMS4 cohorts. While individual in silico knockout analysis suggested links between MeDiff-PM genes and metallothionein-related and immune-associated transcriptional responses. Collectively, these findings indicate that methylation-associated differentiation features represent a molecular dimension of intra-CMS4 heterogeneity and provide a biologically informed framework for prognostic stratification within CMS4 CRC.

Humans↗
PubMed2026

scATAnno: Automated Cell Type Annotation for Single-cell ATAC-seq Data.

Recent advances in single-cell epigenomic techniques have increased the demand for single-cell assay for transposase-accessible chromatin using sequencing (scATAC-seq) analysis. One key analytical task is to determine cell type identity based on epigenetic data. Here, we introduce scATAnno, a Python package designed to automatically annotate scATAC-seq data using large-scale scATAC-seq reference atlases. This workflow generates reference atlases from publicly available datasets, enabling accurate cell type annotation by integrating query data with reference atlases without the use of single-cell RNA sequencing (scRNA-seq) data. To enhance annotation accuracy, we incorporated k-nearest neighbors (KNN)-based and weighted distance-based uncertainty scores to effectively detect cell populations within the query data that are distinct from all cell types in the reference data. We compared and benchmarked scATAnno against five other published cell annotation approaches, demonstrating its superior performance across multiple datasets and metrics. We further showcased the utility of scATAnno across multiple datasets, including peripheral blood mononuclear cells (PBMCs), triple-negative breast cancer (TNBC), and basal cell carcinoma (BCC), and demonstrated that scATAnno accurately annotates cell types across diverse biological conditions. Overall, scATAnno is a useful tool for scATAC-seq reference atlas construction and cell type annotation and can facilitate the interpretation of new scATAC-seq datasets in complex biological systems. scATAnno is publicly available at https://scatanno-main.readthedocs.io/.

Single-Cell Analysis↗
PubMed2025

Founder Homozygous Nonsense CREB3 Variant and Variable-Onset Retinal Degeneration.

IMPORTANCE: Uncovering the genetic basis of inherited retinal diseases (IRDs) can enhance both diagnostic accuracy and the development of targeted treatment strategies. OBJECTIVE: To evaluate the association between a homozygous nonsense variant in CREB3 with IRDs. DESIGN, SETTING, AND PARTICIPANTS: Thirteen patients with a clinical diagnosis of retinitis pigmentosa or cone-rod degeneration were analyzed by whole-genome sequencing (WGS) and whole-exome sequencing (WES). Clinically, patients presented with 2 main phenotypes, rod-cone and cone-rod dystrophies, demonstrating variable electrophysiological and fundoscopic findings. Expression analysis was performed on patient-derived skin fibroblasts using the reverse transcription-polymerase chain reaction and Western blot analysis, and by interrogating previously published retinal single-cell RNA sequence data. Immunohistochemistry staining was performed on wild-type mouse retinal sections using an anti-CREB3 antibody. Patients with variable phenotypes of IRDs were recruited from 3 medical centers in Israel and Italy. Ophthalmologists clinically diagnosed patients at the relevant medical centers and referred them for genetic screening. WES and WGS were performed at different national and international centers, and the findings of the previously unreported gene were shared between investigators. EXPOSURES: CREB3 and IRDs. MAIN OUTCOMES AND MEASURES: The main outcome was evidence supporting an association between CREB3 and IRD. Measures included WES, WGS, and immunohistochemistry staining. RESULTS: A founder homozygous nonsense variant in CREB3 (c.881G>A, p.Trp294*) was identified in 13 patients from 4 unrelated families; 12 descendent from North-African Jewish origins and 1 from Italian origins. All patients manifested retinal degeneration with varying ages at onset. In patient-derived fibroblasts, the variant mRNA transcript generated a truncated CREB3 protein. Expression analysis and immunohistochemistry staining revealed CREB3 RNA and protein expression in various retinal cell types, indicating its vital role in photoreceptor function. CONCLUSIONS AND RELEVANCE: This study found an association between CREB3 and IRDs. CREB3 was previously shown to be upregulated following ultraviolet radiation. This might contribute to the extensive clinical variability observed in this relatively large cohort of homozygous patients with the same truncated variant.

Humans↗
PubMed2026

Single-cell capture of on-ART SIV transcription reveals TGF-β-mediated metabolic control of viral latency.

We previously demonstrated that blocking TGF-β with galunisertib, a safe, orally available small drug, reactivated latent SIV in vivo by shifting T cells toward a transitional effector phenotype. Here, we investigated the mechanisms underlying this effect using single-cell RNA sequencing, metabolic profiling, and high-dimensional spectral flow cytometry of samples from SIV-infected, antiretroviral therapy-treated (ART-treated) macaques before and after galunisertib. To characterize virus-transcribing, infected cells during ART, we developed a novel, sensitive SIV Transcripts Capture Assay (SCAP) that detected 127 SIV-expressing cells within lymph node single-cell transcriptome libraries. Galunisertib drove broad metabolic reprogramming in CD4+ T cells, with transcriptional upregulation of inflammatory and mitochondrial biosynthesis pathways, confirmed by Seahorse profiling. Metabolomics revealed increased energy metabolites and amino acids and enhanced metabolic flux without proliferation. SIV transcript-positive cells before galunisertib were metabolically quiescent compared with cells without detectable viral transcripts. After galunisertib, virus-expressing cells showed a dramatic metabolic activation, with upregulation of glycolysis, fatty acid metabolism, and TNF-α signaling. High-dimensional flow cytometry demonstrated effects beyond CD4+ T cells, including fewer tissue-resident memory T cells, but more inflammatory macrophages. In conclusion, SCAP represents a specific tool for characterizing rare SIV-infected cells transcribing virus during ART, and it reveals TGF-β as a key mediator of viral latency in vivo through metabolic suppression.

Virus Latency↗