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PubMed2026

Overexpression of TCF7L2 promotes the viability and migration of MHCC-97H human hepatocellular carcinoma cells by upregulating MT-ND4L.

BACKGROUND: Hepatocellular carcinoma (HCC) is a highly aggressive cancer with high metabolic adaptability. TCF7L2, a transcription factor implicated in type 2 diabetes and cancer, is overexpressed in HCC. However, its specific role in HCC metabolic reprogramming is not well defined. We aimed to elucidate the previously unrecognized molecular mechanisms through which TCF7L2 impacts HCC progression. METHODS: To investigate the function of TCF7L2, a stable MHCC-97H cell line with TCF7L2 overexpression was established via lentiviral transduction. Cell viability and migration were assessed by Cell Counting Kit-8 (CCK-8) and Transwell assays. Transcriptomic profiling [RNA sequencing (RNA-seq)] was performed to identify differentially expressed genes (DEGs). Functional enrichment analysis [Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG), Gene Set Enrichment Analysis (GSEA)] and bioinformatics promoter analysis (the JASPAR CORE database) were conducted. Clinical correlations, survival analysis, and tumor microenvironment (TME) interrogation were performed using The Cancer Genome Atlas Liver Hepatocellular Carcinoma (TCGA-LIHC) cohort and single-cell datasets [Human Protein Atlas (HPA), CellChat]. Drug sensitivity was predicted via the Genomics of Drug Sensitivity in Cancer (GDSC) database. RESULTS: TCF7L2 overexpression significantly promoted HCC cell proliferation and migration. Transcriptomic analysis revealed that TCF7L2 drives a profound metabolic shift, with key enrichments in lipid homeostasis, fatty acid β-oxidation, and the PI3K/Akt pathway. Mechanistically, TCF7L2 directly binds to the promoter of CPT1A, the rate-limiting enzyme of fatty acid oxidation, and indirectly upregulates the mitochondrial gene MT-ND4Lvia a strong positive correlation with the mitochondrial transcription factor TFAM. In clinical cohorts, TCF7L2 was overexpressed in HCC and its expression correlated positively with MT-ND4L, MKI67, and SNAI1, and served as a predictor of poor overall survival (OS). Furthermore, TCF7L2-high tumors were enriched in hepatic progenitor cell (HPC)-like niches, mediated by enhanced ANGPTL4 signaling. High TCF7L2 expression predicted increased sensitivity to PI3K/mTOR pathway inhibitors. CONCLUSIONS: TCF7L2 acts as a master metabolic regulator in HCC, coordinating lipid catabolism and mitochondrial biogenesis to drive aggressive tumor behavior. It further remodels the TME towards an HPC-like state and predicts sensitivity to metabolic-targeted therapies. These findings identify TCF7L2 as a key prognostic biomarker and a promising therapeutic target.

MHCC-97H hepatocellular carcinoma cells (MHCC-97H ↗

PubMed2025

BIWT: a bioinformatics walkthrough for embedding spatial multiomics in agent-based models for virtual cells.

SUMMARY: Whereas transcriptomic and spatial profiling offer static snapshots of tissue structure, mechanistic models use biological rules to predict how tissues evolve. We present the BioInformatics WalkThrough (BIWT) software to directly initialize spatial agent-based models from single-cell and spatial molecular data. We demonstrate how initialization strategies affect tumor-immune dynamics and spatial clustering, positioning BIWT as a software suite to generate data-driven virtual cells representing both experimental and clinical contexts. AVAILABILITY AND IMPLEMENTATION: The BIWT software is available at https://github.com/PhysiCell-Tools/PhysiCell-Studio. The sample dataset for running the BIWT is available at https://zenodo.org/records/16365625. The code and instructions for reproducing the use case example is available at https://github.com/drbergman/BIWT-Paper.

Software↗

PubMed2024

Gene expression profiles of endothelium, microglia and oligodendrocytes in hippocampus of post-stroke depression rat at single cell resolution.

Post-stroke depression (PSD) is a common but severe mental complication after stroke. However, the cellular and molecular understanding of PSD is still yet to be illustrated. In current study, we prepared PSD rat model (MD) via unilateral middle cerebral artery occlusion (MCAO) and chronic stress stimulation (DEPR), and isolated hippocampal tissues for single cell sequencing of 10x Genomics Chromium. First, we determined the presence of the increased cell population of endothelium and microglia and the compromised oligodendrocytes in MD compared to NC, MCAO and DEPR. The enriched functions of highly variable genes (HVGs) of endothelium and microglia suggested a reinforced blood-brain barrier in MD. Next, cell clusters of endothelium, microglia and oligodendrocytes were individually analyzed, and the subtypes with distinct functions were identified. The presence of expression profiles, intercellular communications and signaling pathways of these three cell populations of PSD displayed a similar but more aggressive appearance with DEPR compared to MCAO and NC. Taken together, this study characterized the specific gene profile of endothelium, microglia and oligodendrocytes of hippocampal PSD by single cell sequencing, emphasizing the crosstalk among them to provide theoretical basis for the in-depth mechanism research and drug therapy of PSD.

Animals↗

PubMed2027

Systematic Analysis of Tumor Microenvironment Using IOBR.

The Immuno-Oncology Biological Research (IOBR) package is an R-based analysis tool for exploring the tumor microenvironment (TME) and its influence on anti-tumor immunity. Built for high-throughput data-spanning both transcriptomic and genomic profiles-IOBR integrates six analytical modules, including transcriptomic data preprocessing, TME profiling, TME pattern identification, ligand-receptor interaction analysis, genome-TME interaction assessment, and visualization. In this chapter, we walk through a multi-omics workflow using example datasets, illustrating data preparation, distribution analyses, result interpretation, and graphical output. IOBR is open source and is available at https://github.com/IOBR/IOBR and a detailed GitBook ( https://iobr.github.io/book/ ) offers a complete manual and analysis guide for each function.

Tumor Microenvironment↗

PubMed2026

A novel lactylation-related gene signature deciphers the immunosuppressive microenvironment and stratifies precision therapy in colorectal cancer.

BACKGROUND: Colorectal cancer (CRC) remains a leading cause of cancer mortality, largely due to the heterogeneity of the tumor microenvironment (TME) and the limited efficacy of immunotherapy in microsatellite stable (MSS) tumors. Histone lactylation, a post-translational modification derived from the Warburg effect, serves as a critical bridge linking metabolic reprogramming to gene regulation and immune evasion; however, its specific prognostic value and clinical implications in CRC remain to be fully elucidated. METHODS: In this study, we systematically analyzed transcriptome profiling data from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) cohorts, supplemented by single-cell RNA sequencing (scRNA-seq) analysis and Human Protein Atlas (HPA) protein-level validation. By integrating univariate Cox regression, Least Absolute Shrinkage and Selection Operator (LASSO) analysis, and multivariate Cox regression, we constructed a novel lactylation-related gene (LRG) risk signature. We extensively evaluated the association between this risk signature and patient prognosis, immune infiltration patterns, somatic mutations, and therapeutic sensitivity. RESULTS: A robust 9-gene prognostic signature (DHRS7, SPR, MBD2, RBM17, CSRP2, S100A4, TMSB4X, TKT, COPS4) was identified and corroborated at the protein level. Patients with high risk scores exhibited significantly worse overall survival (OS) across the training and two independent validation cohorts. Immunogenomic and scRNA-seq analyses revealed that high-risk tumors were characterized by an immunosuppressive and stromal-dense microenvironment-with stromal cells exhibiting the highest lactylation risk scores-enriched with regulatory T cells (Tregs), and frequently harbored PIK3CA mutations. Differential expression analysis indicated that this immune exclusion is structurally maintained by enriched extracellular matrix (ECM) organization and TGF-β signaling. Conversely, low-risk tumors displayed an inflamed phenotype with active antitumor immunity. Pharmacogenomic prediction identified distinct therapeutic stratifications: low-risk patients exhibited significant sensitivity to standard chemotherapeutics (fluorouracil, oxaliplatin) and EGFR/HER2 inhibitors (e.g., lapatinib, erlotinib). In contrast, high-risk patients showed specific vulnerabilities to novel targeted agents, including PI3K pathway inhibitors (TG-100-115, XL765), microenvironment-modulating agents (sildenafil, GANT-61), and epigenetic inhibitors (UNC0638). CONCLUSION: We established a novel lactylation-related risk signature that effectively stratifies CRC patients by prognosis and TME characteristics. By elucidating the crosstalk between metabolic dysregulation, stromal barriers, and immune exclusion, this study provides potential biomarkers and stratified therapeutic strategies-ranging from standard chemotherapy to targeted metabolic and stromal interventions-to optimize precision medicine for CRC patients.

Colorectal cancer↗

PubMed2025

Fecal microbiota transplantation promotes type 2 mucosal immune responses with colonic epithelium proliferation in patients with recurrent Clostridioides difficile.

BACKGROUNDFecal microbiota transplantation (FMT) is the most effective therapy for recurrent Clostridioides difficile infection (rCDI), yet its mechanism of action remains poorly understood.METHODSWe report the results of a clinical trial of patients undergoing FMT therapy for rCDI (n = 16), which analyzed colon biopsies, plasma, PBMCs, and stool at the time of FMT and 2-month follow-up. Plasma and colon biopsy samples were also collected from healthy controls for comparison with patients with rCDI. Microbiome composition, colonic gene expression, and immune changes were evaluated through high-throughput sequencing and immunoprofiling via flow cytometry.RESULTSNo patients experienced recurrence at follow-up. FMT significantly altered the intestinal microbiome but had no significant impact on the systemic immune system. In contrast, FMT promoted broad changes in colonic transcriptional profiles compared with both pre-FMT and healthy control biopsies, inhibiting genes associated with proinflammatory signaling and upregulating type 2 immunity and proliferative pathways (Myc and mTORC1). FMT increased expression of IL-33 and the type 2 immune EGFR family ligand amphiregulin, potentially explaining upregulation of Myc and mTORC1 pathways. Spatial transcriptomics demonstrated that these changes were localized to the colonic epithelium. Comparison of transcriptional profiles with available single-cell gene sets determined that post-FMT biopsies were enriched in signatures associated with proliferative cell types while repressing signatures of differentiated colonocytes.CONCLUSIONWe conclude that FMT promotes proliferation of the colonic epithelium in patients with rCDI, which may drive regeneration and protect against subsequent CDI.TRIAL REGISTRATIONClinicaltrials.gov NCT02797288.FUNDINGThis work was funded by grants from the NIH.

Adult↗

PubMed2026

IDH2 clonal hematopoiesis and IKAROS loss cooperate in a B-ALL subtype after lenalidomide therapy for multiple myeloma.

Lenalidomide, a maintenance treatment in multiple myeloma first-line therapy, increases the risk of secondary malignancies, including B-cell precursor acute lymphoblastic leukemia (B-ALL). We present a comprehensive molecular characterization of 57 patients with lenalidomide-associated B-ALL (LenB-ALL), revealing 3 mutational subgroups: (1) TP53mt (30%); (2) IDH2mt (p.R140Q) (23%); and (3) other, including NRAS/KRASmt. Remarkably, IDH2 R140Q mutations were highly enriched in LenB-ALL compared with those in primary B-ALL (P< .001). Furthermore, IKZF1 intragenic deletions, often subclonal and likely RAG recombinase-mediated, were observed in 54% (7/13) of IDH2mt patients with LenB-ALL. IDH2 mutations were not restricted to the leukemic clone: they persisted during measurable residual disease-negative remission and were identified in lymphoid as well as myeloid cell populations using fluorescence-activated cell sorting and single-cell RNA sequencing. This indicates a preleukemic origin of the IDH2 mutation within the context of clonal hematopoiesis. Transcriptomic and DNA methylation analyses revealed a distinct gene expression profile and a DNA hypermethylation phenotype in IDH2mt LenB-ALL, including IDH2mt-specific as well as lenalidomide-associated features. We propose that lenalidomide promotes the expansion of IDH2-mutated clonal hematopoiesis and, via IKAROS downregulation, induces a maturation arrest at the B-cell precursor stage. Subsequent genetic or epigenetic alterations render leukemogenesis independent of ongoing lenalidomide exposure. All these data define IDH2mt B-ALL as a distinct molecular subtype that is markedly overrepresented after lenalidomide treatment and highlight clonal hematopoiesis as a key contributing factor in the development of LenB-ALL.

Humans↗

PubMed2026

Epigallocatechin gallate is associated with PDGFRB downregulation and altered PI3K-AKT signaling in gastric cancer.

BACKGROUND: Gastric cancer (GC) remains a major cause of cancer-related mortality worldwide. Epigallocatechin gallate (EGCG), a natural polyphenol derived from green tea, exhibits anticancer properties; however, its molecular targets and regulatory mechanisms in GC are not fully elucidated. This study aimed to identify candidate EGCG-associated genes in GC and generate a hypothesis for future mechanistic investigation. METHODS: Differentially expressed genes (DEGs) in GC were identified and intersected with EGCG-associated targets retrieved from The Cancer Genome Atlas (TCGA) and GeneCards public databases. Least absolute shrinkage and selection operator (LASSO) regression and Cox proportional hazards analyses were performed to screen prognostically relevant genes. Diagnostic performance was evaluated using receiver operating characteristic (ROC) curves. Functional enrichment analysis was conducted to explore biological significance. Public single-cell RNA sequencing datasets were analyzed to determine the cellular localization of platelet-derived growth factor receptor beta (PDGFRB), while DepMap transcriptomic data were used to assess its expression across GC cell lines. In vitro assays, 3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide (MTT), Transwell migration, and Western blotting, were performed to evaluate the biological effects of EGCG on GC-associated signaling pathways. RESULTS: Thirty-eight EGCG-associated DEGs were identified. Enrichment analysis revealed these genes were involved in cancer-associated pathways. LASSO-Cox modelling identified four candidate genes. Among them, PDGFRB was selected for further investigation based on its prognostic relevance and favorable diagnostic performance. PDGFRB expression was significantly higher in the TCGA genomically stable (GS) subtype than in the other molecular subtypes and was predominantly localized to cancer-associated fibroblasts (CAFs) and pericytes in single-cell RNA sequencing analysis. DepMap data demonstrated heterogeneous PDGFRB expression across GC cell lines. In vitro experiments showed that EGCG inhibited proliferation, migration, and invasion, reduced PDGFRB protein expression, and was associated with apoptosis-related protein changes and altered PI3K-AKT signaling. CONCLUSIONS: Our findings suggest that EGCG treatment was associated with reduced PDGFRB expression and altered PI3K-AKT signaling in GC cells. These findings identify PDGFRB as a candidate EGCG-associated gene and provide a hypothesis for future mechanistic investigation.

Gastric cancer (GC)↗

PubMed2026

SYT8 Drives Colorectal Cancer Progression and Immune Evasion via the SETD1A-H3K4me3 Axis.

By integrating transcriptomic data from The Cancer Genome Atlas, Gene Expression Omnibus, and a self-established colorectal cancer (CRC) cohort, it was identified that synaptotagmin 8 (SYT8) is significantly up-regulated in tumors and is predictive of poor prognosis. Single-cell RNA sequencing, immunohistochemistry, and immunofluorescence experiments demonstrate that SYT8 expression is largely confined to tumor cells, predominantly in the nucleus. Functional assays reveal that depletion of SYT8 impairs, whereas its overexpression enhances, CRC cell proliferation and invasion. Transcriptomic profiling indicates an enrichment of cell cycle and epithelial-mesenchymal transition signatures. Mechanistically, co-immunoprecipitation/mass spectrometry identifies SET domain containing 1A (SETD1A) as a direct SYT8-interacting partner. The SYT8-SETD1A axis forms a positive-feedback loop that increases histone H3 lysine 4 trimethylation (H3K4me3) levels and drives the transcription of protumorigenic genes. Immune profiling further indicates that high SYT8 expression correlates with increased regulatory T-cell infiltration, suggesting an immunosuppressive microenvironment and potential resistance to immunotherapy. Collectively, SYT8 promotes CRC progression through the SETD1A/H3K4me3-mediated activation of the cell cycle, induction of epithelial-mesenchymal transition, and remodeling of the immune microenvironment. Therefore, SYT8 is established as a prognostic biomarker and serves as a therapeutic target in colorectal cancer.

Humans↗

PubMed2026

Imaging-Guided Omics Technologies for Resolving Rare Cancer States and Advancing Nanomedicine.

The ability to resolve rare and transient cellular states is critical for understanding metastasis, immune evasion, and therapy resistance in cancer, yet these dynamic processes often escape detection by conventional sequencing and imaging approaches. Recent advances at the interface of nanotechnology, high-resolution live-cell imaging, and single-cell/spatial multiomics methods have enabled functional profiling of cells with unprecedented precision within their native microenvironment. In this Mini-Review, we highlight emerging nanoscale platforms that couple real-time phenotypic imaging with molecular readouts, such as FUNseq and CIN-seq, to directly link functional heterogeneity to transcriptomic, proteomic, and epigenomic information. By integrating nanoscale optical imaging, microengineered perturbation tools, and AI-driven computational analysis, these technologies open up new avenues for dissecting rare metastatic, therapy-resistant, or immune-evasive subpopulations. We further discuss how these next-generation imaging-guided single-cell and spatial omics platforms not only advance fundamental cancer biology but also create opportunities to accelerate the development of nanomedicine applications.

Humans↗

PubMed2025

PATTY corrects open chromatin bias for improved bulk and single-cell CUT&Tag profiling.

Precise profiling of epigenomes is essential for better understanding chromatin biology and gene regulation. Cleavage Under Targets & Tagmentation (CUT&Tag) is an efficient epigenomic profiling technique that can be performed on a low number of cells and at the single-cell level. With its growing adoption, CUT&Tag datasets spanning diverse biological systems are rapidly accumulating in the field. CUT&Tag assays use the hyperactive transposase Tn5 for DNA tagmentation. Tn5's preference toward accessible chromatin alters CUT&Tag sequence read distributions in the genome and introduces open chromatin bias that can confound downstream analysis, an issue more substantial in sparse single-cell data. We show that open chromatin bias extensively exists in published CUT&Tag datasets, including those generated with recently optimized high-salt protocols. To address this challenge, we present PATTY (Propensity Analyzer for Tn5 Transposase Yielded bias), a comprehensive computational method that corrects open chromatin bias in CUT&Tag data by leveraging accompanying ATAC-seq. By integrating transcriptomic and epigenomic data using machine learning and integrative modeling, we demonstrate that PATTY enables accurate and robust detection of occupancy sites for both active and repressive histone modifications, including H3K27ac, H3K27me3, and H3K9me3, with experimental validation. We further develop a single-cell CUT&Tag analysis framework built on PATTY and show improved cell clustering when using bias-corrected single-cell CUT&Tag data compared to using uncorrected data. Beyond CUT&Tag, PATTY sets a foundation for further development of bias correction methods for improving data analysis for all Tn5-based high-throughput assays.

Journal Article↗

PubMed2026

STX1B variant-specific synaptic dysfunction is associated with network hyperexcitability in human iPSC-derived neurons.

BACKGROUND: Variants in STX1B/syntaxin-1B are linked to a spectrum of fever-associated epilepsy syndromes. While studies in murine models have provided mechanistic insights, their relevance to human disease in a heterozygous context may be limited. METHODS: We investigated two pathogenic STX1B variants using isolated single neurons and neuronal network cultures derived from patient-specific induced pluripotent stem cells. These carried either a de novo p.G226R variant, associated with severe developmental epilepsy, or an InDel variant (p.K45delinsRCMIE/p.L46M) linked to a transient familial seizure syndrome. Synaptic function and network excitability were assessed using patch-clamp and multi-electrode array recordings, alongside morphological and transcriptomic profiling. FINDINGS: G226R exhibited both gain- and loss-of-function characteristics, with increased miniature excitatory postsynaptic current frequency in networks but not in autapses, and synaptic failure during sustained high-frequency stimulation. For the InDel variant, the predicted loss-of-function phenotype based on reduced syntaxin-1B levels was not detectable at the single-cell level, likely masked by compensatory synaptic upregulation. At the network level, however, both variants were associated with neuronal hyperexcitability, characterised by more frequent and prolonged bursting activity, with a much stronger phenotype in G226R-containing networks. Transcriptomic profiling revealed a differential dysregulation of synaptic and other neuronal genes. INTERPRETATION: The divergence between morphological, electrophysiological and transcriptomic findings suggests that compensatory mechanisms may contribute to network hyperexcitability. Initially engaged to maintain homoeostasis, they may ultimately contribute to a pathological network state. The graded severity of network alterations across STX1B variants correlates with the clinical phenotypes. FUNDING: BMBF (Treat ION-01GM2210A, SNAREopathies-01EW1809A), 2023 FEBS Summer Fellowship, Fortüne programme (2610-0-0), EKFS college precise.net, Open Access Publishing Fund of University of Tübingen.

Humans↗

PubMed2025

Identification of marginal zone B cells in head and neck cancer with immunomodulatory characteristics.

INTRODUCTION: Recently we observed high numbers of marginal zone B cells (MZBs) within murine head and neck squamous cell carcinoma (HNSCC) with immunosuppressive potential. To date, MZBs have not been linked to tumor development or tumor prevention. OBJECTIVES: Based on our previous findings the present study aimed to validate the presence of MZB in HNSCC and to investigate their possible implications in tumorigenesis and prognosis. METHODS: Flow cytometry was used to uncover MZB within tumors and blood of HNSCC patients. A single-cell RNA sequencing cohort of 118 HNSCC patients across different disease stages and 6 healthy donors (HDs) was compiled. Comparative transcriptomic profiling of B lymphocytes between HNSCC and HDs were performed. Downstream analysis, such as pathway enrichment, cell-cell communication, pseudotime trajectory inference, survival correlation, and spatial transcriptomics were applied. RESULTS: Two MZB subsets were revealed in tissues and blood of HNSCC patients and HDs. The tumor-associated MZBs were featured with hypoxia stress and viral-related hallmark genes. MZB-2, characterized by elevated expression of activation markers and immune-regulatory genes, displayed strong interactions with CD4+ T cells and antigen-presenting cells. These interactions were supported by costimulatory signals in HDs but were absent in HNSCC patients. Co-localization of MZB-2, germinal center B cell (GCB), and CD4+ follicular helper T cell (Tfh) was detected in HNSCC, suggesting the presence of an intratumoral MZB-Tfh-GCB axis. Clinically, MZB-2 abundance was associated with favorable prognosis in early-stage HNSCC, but not in advanced disease. Immunosuppressive gene signatures were not exclusive to MZBs, indicating that they do not represent a purely regulatory B cell phenotype. CONCLUSION: Our findings demonstrate an immunomodulatory role of MZBs in tumor immunity, balancing antigen presentation, cytokine signaling, and immune suppression. The association of MZB-2 with improved prognosis in early-stage HNSCC highlights its potential as a beneficial regulator of antitumor immunity during early tumor progression.

Humans↗

PubMed2024

Kick-starting the zygotic genome: licensors, specifiers, and beyond.

Zygotic genome activation (ZGA), the first transcription event following fertilization, kickstarts the embryonic program that takes over the control of early development from the maternal products. How ZGA occurs, especially in mammals, is poorly understood due to the limited amount of research materials. With the rapid development of single-cell and low-input technologies, remarkable progress made in the past decade has unveiled dramatic transitions of the epigenomes, transcriptomes, proteomes, and metabolomes associated with ZGA. Moreover, functional investigations are yielding insights into the key regulators of ZGA, among which two major classes of players are emerging: licensors and specifiers. Licensors would control the permission of transcription and its timing during ZGA. Accumulating evidence suggests that such licensors of ZGA include regulators of the transcription apparatus and nuclear gatekeepers. Specifiers would instruct the activation of specific genes during ZGA. These specifiers include key transcription factors present at this stage, often facilitated by epigenetic regulators. Based on data primarily from mammals but also results from other species, we discuss in this review how recent research sheds light on the molecular regulation of ZGA and its executors, including the licensors and specifiers.

Animals↗

PubMed2025

PATTY corrects open-chromatin bias for improved bulk and single-cell CUT&Tag profiling.

Precise profiling of epigenomes is essential for better understanding chromatin biology and gene regulation. Cleavage Under Targets & Tagmentation (CUT&Tag) is an efficient epigenomic profiling technique that can be performed on a low number of cells and at the single-cell level. With its growing adoption, CUT&Tag datasets spanning diverse biological systems are rapidly accumulating in the field. CUT&Tag assays use the hyperactive transposase Tn5 for DNA tagmentation. Tn5's preference toward accessible chromatin alters CUT&Tag sequence read distributions in the genome and introduces open-chromatin bias that can confound downstream analysis, an issue more substantial in sparse single-cell data. We show that open-chromatin bias extensively exists in published CUT&Tag datasets, including those generated with recently optimized high-salt protocols. To address this challenge, we present PATTY (Propensity Analyzer for Tn5 Transposase Yielded bias), a comprehensive computational method that corrects open-chromatin bias in CUT&Tag data by leveraging accompanying ATAC-seq. By integrating transcriptomic and epigenomic data using machine learning and integrative modeling, we demonstrate that PATTY enables accurate and robust detection of occupancy sites for both active and repressive histone modifications, including H3K27ac, H3K27me3, and H3K9me3, with experimental validation. We further develop a single-cell CUT&Tag analysis framework built on PATTY and show improved cell clustering when using bias-corrected single-cell CUT&Tag data compared to using uncorrected data. Beyond CUT&Tag, PATTY sets a foundation for further development of bias correction methods for improving data analysis for all Tn5-based high-throughput assays.

Journal Article↗

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

The machine-learning classifier ALLCatchR2 identifies 20 T-ALL subtypes across cohorts and age groups.

T-cell acute lymphoblastic leukemia (T-ALL) comprises molecularly diverse subtypes, but robust cross-cohort validations and operational gene-expression definitions are lacking. To establish a gene-expression-anchored framework for T-ALL subtyping, we aggregated 2314 transcriptomes (15 cohorts, age: 0.8-90.8 years). An extended unsupervised approach defined 17 main clusters and 3 subclusters in samples with high blast fractions. Supervised analyses added an overarching immature T-ALL (early T cell precursor [ETP]-like) definition and resolved the LMO2 γδ-like subtype. All clusters contained samples from at least two cohorts. Characteristic genomic driver enrichments were consistent across cohorts, while gene-expression clusters did not correspond exclusively to single driver events but also reflected developmental origins. A machine-learning classifier based on ALLCatchR, our B-cell acute lymphoblastic leukemia (B-ALL) classifier, identified these 20 transcriptomic subtypes and the immature T-ALL (ETP-like) signature with 0.995-1.0 accuracy in a validation set (n = 203). Testing the classifier on a second hold-out data set (n = 265 samples) showed that 92.7% of predictions matched with corresponding driver alterations. Across all samples, 83.2% of cases received high-confidence predictions, 7.3% candidate predictions, and 9.5% remained unclassified, largely because of low blast fractions. We identified a novel gene-expression cluster markedly enriched (P < 0.001) for clonal hematopoiesis mutations (IDH2 R140Q, DNMT3A) and a stem-/progenitor cell-like gene expression. This novel clonal hematopoiesis-related T-ALL subtype was observed in six cohorts and accounted for 8.9% of adults and 39.5% of patients aged >50 years. We extended ALLCatchR into ALLCatchR2, a free R package that now enables B-/T-lineage separation, gene-expression subtyping, blast estimation, and developmental annotation to harmonize T-ALL classification across studies and clinical contexts.

Journal Article↗

PubMed2026

Human Monocytic Models Reveal Genotype-Dependent Inflammatory Programs in VEXAS Syndrome.

OBJECTIVES: VEXAS syndrome is a severe X-linked autoinflammatory disorder caused by somatic mutations in ubiquitin-like modifier activating enzyme 1 (UBA1), with clinical outcomes that vary by UBA1 genotype. We aimed to elucidate genotype-specific inflammatory programs and identify potential therapeutic targets. METHODS: We conducted longitudinal deep phenotyping, including whole-blood RNA sequencing (RNA-seq) and clinical activity assessment. Peripheral blood samples were analyzed by single-cell RNA-seq. Human monocytic cell lines harboring each major UBA1 mutation (p.Met41Val, p.Met41Thr, or p.Met41Leu) were generated and subjected to transcriptomic and functional analyses. RESULTS: Thirteen patients with VEXAS syndrome contributed a total of 79 RNA-seq samples. Among genes upregulated in VEXAS syndrome, RNASE1 showed the strongest correlation with longitudinal disease activity (r = 0.70, FDR < 0.05) and was upregulated in patients' monocytes. In UBA1-mutant monocytic cell lines, genotype-dependent ubiquitination defects were observed in a graded manner (p.Met41Val > p.Met41Thr > p.Met41Leu), even in the absence of exogenous stimuli. These defects were accompanied by unfolded protein response activation, increased pro-inflammatory cytokine production, progressive cell death, and RNASE1 upregulation, all following the same graded pattern, recapitulating patient genotype-phenotype associations. Transcriptomic analyses demonstrated enrichment of pro-inflammatory, interferon, and necroptosis signatures in more severe genotypes. Notably, inhibition of receptor-interacting protein kinase 3 (RIPK3) markedly attenuated all pathological features, including RNASE1 upregulation. CONCLUSIONS: Our UBA1-mutant monocytic cell-line models, representing three distinct genotypes, recapitulate genotype-dependent inflammatory phenotypes that can be modulated by RIPK3 inhibition, providing a translational platform for mechanistic investigation and precision therapy development in VEXAS syndrome.

Journal Article↗