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Deciphering the Genetic Underpinnings of Liver Cirrhosis-Heart Failure Comorbidity Through Multi-Omics: CRIM1 as a Key Endothelial Mediator.

The co-occurrence of liver cirrhosis (LC) and heart failure (HF) poses considerable clinical challenges, yet the cellular and molecular determinants of this comorbidity remain poorly characterized. To address this, we developed an integrative multi-omics pipeline encompassing GWAS meta-analysis, gsMap-based spatial transcriptomic projection, GeneEnrich functional annotation, single-cell atlas construction, seismicGWAS and ECLIPSER cell-type scoring, eCAVIAR and fastenloc colocalization, hdWGCNA network inference, scTenifoldKnk in silico gene perturbation, and GCTA-COJO fine-mapping. Quality-controlled meta-analysis yielded 12,347,758 and 9,256,862 variant-level associations for LC and HF, respectively. Spatial projection confirmed preferential enrichment of disease signals within embryonic hepatic and cardiac compartments. Pathway analyses disclosed that LC-linked loci were concentrated in lipid metabolic programs, whereas HF-linked loci implicated mitochondrial bioenergetics and lysosomal degradation. At the cellular level, endothelial cells emerged as the dominant HF-associated population. Convergent evidence from five orthogonal algorithms pinpointed CRIM1 as the sole robustly supported shared gene, selectively enriched in HF endothelial cells; virtual perturbation further identified LCP1 and PTPRC as downstream regulatory nodes. Fine-mapping of the chromosome 2 locus harboring rs12476437 revealed multiple statistically independent signals in the vicinity of CRIM1. Collectively, these findings computationally prioritize the endothelial-CRIM1 axis as a previously unappreciated candidate mechanistic bridge between LC and HF requiring experimental validation.

Humans

Multinucleated Giant Cells in Human Pancreatic Cancer Are a Distinct Macrophage Population Undergoing a DNA Damage Response and Associated with an Aggressive Tumor Microenvironment.

Macrophages (Mϕ) constitute a dominant and functionally diverse immune population within the microenvironment of pancreatic ductal adenocarcinoma (PDAC), yet how Mϕ heterogeneity contributes to the tumor remains poorly defined. In an institutional cohort of 145 PDAC specimens, we identified a population of multinucleated giant cells (MGC) of Mϕ origin, an entity previously described in chronic inflammation but rarely in cancer. CD68+ MGCs were present in 28% of tumors, enriched in squamous, nonglandular regions, and more frequent after neoadjuvant chemotherapy. By integrating spatial transcriptomics and quantitative imaging, we defined the features of these cells, which, compared with MGCs in nonneoplastic inflammatory lesions, lacked canonical polarization markers (HLA-DR and CD163) and displayed a distinctive transcriptional program characterized by upregulation of the POLR2K, TUBA8, COX5B, and VDAC1 genes, which encode proteins involved in DNA repair, oxidative stress, and MYC signaling. Spatial analyses revealed activation of hypoxia and extracellular matrix-remodeling pathways in MGC-associated niches, and experimental hypoxia promoted MGC formation in vitro. Consistent with these data, we found that in the The Cancer Genome Atlas (TCGA) Pancreatic Adenocarcinoma (PAAD) dataset a Mϕ MGC gene signature was enriched in the squamous PDAC subtype and correlated with poorer overall survival (P = 0.018). Morphometric and immunofluorescence analyses further showed increased 53BP1+Ki67+ nuclei and nuclear atypia in MGCs, indicating ongoing proliferation despite DNA damage. Together, these data identify MGCs of Mϕ origin as an immune cell state shaped by hypoxia and stress signaling, associated with aggressive tumor phenotypes, and potentially exploitable as an immune classifier in PDAC.

Humans

SCMO: a deep learning model integrating the single-cell resolution TME ecosystem and multi-omics for survival prediction in CRC patients.

BACKGROUND: Colorectal cancer (CRC) remains a leading cause of global cancer mortality, highlighting the need for precise survival prediction to guide clinical decisions. Although tissue-level multi-omics is widely utilized for survival prediction, its limited resolution cannot capture tumor heterogeneity. Single-cell RNA sequencing (scRNA-seq) enables dissection of the tumor microenvironment (TME) at cellular resolution, supporting personalized prognostic assessment. METHODS: We collected 213 CRC scRNA-seq samples and established a CRC-specific TME atlas comprising 339,060 cells. Using this atlas as a reference, we deconvolved bulk RNA-seq data from TCGA-CRC cohort with the EcoTyper algorithm to reconstruct TME features. Clinical, genomic, and transcriptomic data were obtained from the Xena platform; microbial data were sourced from the BIC database. We integrated TME and multi-omics features through a self-normalizing neural network to construct a deep learning model (single-cell resolution TME ecosystem with multi-omics data [SCMO]) for survival prediction. To enhance interpretability, we utilized the Integrated Gradients algorithm and spatial transcriptomic data to analyze multi-omics and TME features. We performed anticancer drug screening with tumor necrosis factor receptor-associated protein 1 (TRAP1), a critical feature according to the Integrated Gradients algorithm, as a potential target. RESULTS: We identified 13 survival-related TME features from the CRC-specific atlas: 12 cell states and one multi-cellular ecosystem. SCMO, which combined TME and multi-omics features, improved survival prediction and outperformed existing methods, achieving a concordance index of 0.762. The SCMO demonstrated robust performance for long-term predictions, achieving areas under the curve (AUCs) of 0.752, 0.772, and 0.869 for 1-, 3-, and 5-year predictions in the training set, with corresponding test set AUCs of 0.639, 0.756, and 0.772. TME features from the SCMO model revealed that ecosystem density increased with CRC malignancy. Multi-omics features included TRAP1 as a potential drug target. Drug screening identified saikosaponin A as a novel TRAP1 inhibitor, and its anticancer activity was validated in vitro. We developed SCMO-Lite, a simplified model incorporating 12 high-attribution-weight multi-omics features, which demonstrated robust risk stratification. CONCLUSIONS: SCMO combines analytical precision with biological interpretability, offering novel insights for oncology survival prediction.

Humans

Spatiotemporal single-cell profiling reveals T cell clonal dynamics and phenotypic plasticity in human graft-versus-host disease.

Allogeneic hematopoietic cell transplantation cures hematologic diseases but is limited by acute graft‑versus‑host disease. How human T cell clones drive epithelial injury remains poorly mapped. We studied 31 transplant recipients, integrating longitudinal T cell antigen receptor (TCR) profiling with single-cell RNA sequencing/TCR sequencing and spatial transcriptomics to track T cell clonal dynamics. We developed DecompTCR to resolve temporal dynamics and adapted computational tools to map clone phenotypes and niches in tissue. Our analyses revealed that cyclophosphamide selectively depletes alloreactive clones, although insufficient early expansion leads to incomplete depletion and severe disease. Severe graft‑versus‑host disease is marked by persistent expansion of alloreactive clones, rewiring of homeostatic cell types and diversification of donor-derived CD8+ clonotypes that acquire Hobit (ZNF683)+ tissue‑resident memory T (TRM) cell programs during migration to epithelium. Spatial deconvolution identified CD8+ effector/Hobit+ TRM hubs near intestinal stem‑cell-rich crypt bases and crypt‑loss regions. This clonotype‑resolved framework links tissue‑instructed TRM cell remodeling to localized epithelial injury, nominating early-repertoire dynamics and spatial hub burden as biomarkers.

Journal Article

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

Multi-omics characterization of a GPRC5A+ epithelial subpopulation associated with malignant features in colorectal cancer.

BACKGROUND: Colorectal cancer (CRC) exhibits marked cellular heterogeneity, and the cellular context of malignancy-associated epithelial programs remains incompletely defined. METHODS: We integrated 2,993 CRC samples spanning bulk RNA-seq (n = 2,568; two OS/RFS cohorts), scRNA-seq (281,961 cells/152 specimens), spatial transcriptomics (n = 6), and proteomics (n = 267). Analyses included single-cell integration/annotation, GSVA/HALLMARK, interactome, pseudotime, and ligand-receptor mapping; functional CRISPR assays, EMT immunoblotting, and xenografts; TF profiling (SCENIC/JASPAR/ChIP-qPCR); and exploratory drug-response prediction (OncoPredict), cell-sensitivity assays, and docking/MD modeling. RESULTS: We constructed a stage-stratified single-cell atlas and resolved eleven malignant epithelial subsets, characterizing Epi_4 as late-stage-enriched with EMT, hypoxia, and inflammatory programs and adverse OS/RFS. GPRC5A marked this subset, which we define as GPRC5A+Epi; its expression rose from stage I→IV and was associated with poor outcomes across cohorts, with concordant spatial/proteomic observations. GPRC5A perturbation affected CRC proliferation, migration/invasion, EMT, and xenograft tumorigenicity, supporting a functionally important role in the tested models. SCENIC and ChIP-qPCR supported FOSL1 as an upstream regulator that occupies the GPRC5A promoter. Spatial and ligand-receptor analyses predicted close association and potentially reciprocal signaling between GPRC5A+Epi and POSTN+fibroblasts (COL1A1-SDC4, COL1A1/1A2-ITGA2/ITGB1, PPIA-BSG); concurrent high GPRC5A+Epi/POSTN+Fib signatures were associated with inferior OS/RFS. Drug-response analyses identified an association between GPRC5A status and trametinib sensitivity. Docking/MD produced a computational model of a possible trametinib-GPRC5A interaction, which remains experimentally unvalidated. CONCLUSIONS: GPRC5A⁺Epi is a malignancy-associated epithelial state in CRC, and GPRC5A is functionally important for malignant phenotypes in the tested models. Its inferred relationships with POSTN⁺ fibroblasts and the trametinib findings should be regarded as hypothesis-generating pending functional crosstalk, direct-binding, and therapeutic validation.

Humans

CRISPR-Enabled functional genomics in hPSCs-derived neural models for autism spectrum disorder.

Autism Spectrum Disorder (ASD) is a genetically heterogeneous neurodevelopmental condition in which hundreds of individually rare risk variants converge on a small number of shared biological pathways, including synaptic scaffolding, chromatin remodeling, excitation-inhibition balance, and cellular energy metabolism. Translating this genetic heterogeneity into mechanistic insight requires experimental systems capable of interrogating individual gene functions in human-relevant neural contexts at scale. CRISPR-enabled functional genomics in human pluripotent stem cell (hPSC)-derived neural models, spanning neural progenitors, cortical and inhibitory neurons, astrocytes, microglia, and brain organoids, provides precisely this capability. By integrating pooled perturbation screens with multimodal readouts including single-cell and spatial transcriptomics, chromatin accessibility profiling, proximity labeling proteomics, multi-electrode array electrophysiology, and metabolic flux analysis, these platforms enable systematic, causal mapping of ASD gene function at system resolution. Early applications have already revealed convergent mechanisms: BAF complex disruption expands the ventral progenitor pool and biases its fate toward oligodendrocyte and interneuron lineages; ADNP loss impairs microglial synaptic pruning through altered endocytic trafficking; and mTOR pathway dysregulation in PTEN- and TSC2-perturbed models links genetic risk directly to metabolic and mitochondrial dysfunction. Computational frameworks including MIMOSCA and SCEPTRE enable causal network reconstruction and pseudotime inference from these datasets, moving the field from gene lists toward pathway-level models of ASD pathobiology. Translational applications leverage isogenic iPSC panels and variant-level base and prime editing to stratify ASD variants by functional impact, informing gene therapy design for haploinsufficient targets such as CHD8 and SCN2A via AAV or antisense oligonucleotide delivery. Remaining challenges, including model developmental immaturity, batch variability, and the difficulty of modeling polygenic risk, are addressed by a roadmap integrating spatial perturbomics, AI-driven causal inference, and population-scale standardized biobanks. This review synthesizes the current state of CRISPR-based functional genomics in human stem cell neural models as a coherent experimental framework for converting ASD genetic associations into mechanistic understanding and therapeutic opportunity.

Humans

Deep FLASH-seq profiling of purified canine sensory neurons uncovers species-specific signatures relevant to pain and itch.

Naturally occurring pain and itch disorders in the domestic dog represent an important and underexploited opportunity for translational sensory neuroscience. These conditions largely mirror human disease, highlighting the need for detailed comparative understanding of canine somatosensory neurobiology. Here, we present a single-cell transcriptomic characterisation of the canine dorsal root ganglion (DRG), providing molecular insights into sensory neuron diversity in a species of direct veterinary and biomedical relevance. We develop a novel mechanical dissociation and fluorescence-activated cell sorting strategy enabling purification of intact whole neurons from adult canine DRG, followed by deep, full-length RNA sequencing using FLASH-seq. This approach yields high-quality transcriptional profiles with molecular depth analogous to deep neuronal profiling in human DRG, enabling resolution of neuronal identities and subtype-specific gene programs. Using these data, we identify canine sensory neuron clusters conforming to conserved principles of DRG molecular organization observed across species, including peptidergic and noncanonical peptidergic nociceptors, low-threshold mechanoreceptors, proprioceptors, and thermosensory populations. Cross-species comparisons with human and mouse DRG datasets reveal broad conservation of pain- and itch-relevant pathways and therapeutic targets, alongside biologically meaningful divergence. We further identify species-specific differences in subtype-restricted expression of the pharmacologically relevant receptors IL31RA and SSTR2 , which we validate using in situ hybridization and contextualize with human spatial transcriptomic data. Finally, we provide evidence that domestication-associated genes are nonrandomly enriched in specific sensory neurons, suggesting that evolutionary history may have shaped somatosensory function. These data represent a resource for comparative sensory neuroscience and inform translational interpretation of pain and itch therapeutics across species.

Animals

The domestication-associated WHP10 tandem cluster of amino acid transporter genes enhances whole-plant protein accumulation in maize.

Improving protein accumulation in maize is essential for sustainable agriculture, yet the regulatory mechanisms governing the intermediate "flow" of organic nitrogen remain elusive. Here, we show that the maize stem acts as a regulatory node for nitrogen allocation. By integrating spatial transcriptomics and metabolomics with quantitative genetics, we demonstrate that a transport-oriented stem program orchestrates the high-protein phenotype of the wild maize accession Ames21814. We identified a major locus, Whole-plant High Protein 10 (WHP10), that encodes a tandemly duplicated cluster of amino acid transporter genes. WHP10 exhibits strong vascular-biased expression, driven by promoter divergence that enhances the wild allele's activity. Functional assays and genetic validation support a model in which the WHP10 cluster facilitates the transport of multiple nitrogen-rich amino acids, thereby contributing to vascular-associated amino acid transport and post-uptake organic-nitrogen partitioning. Our findings establish stem flow as a regulatory layer for protein accumulation and identify WHP10 as a high-value target for precision breeding to enhance whole-plant protein accumulation without compromising grain yield.

Zea mays

Nrsn1-Smarcc1 Coupling Regulates Neural Stem Cell Differentiation and Chronic-phase Recovery After Ischemic Stroke.

Stroke remains a leading cause of long-term neurological disability worldwide, largely due to irreversible neuronal loss and the limited regenerative capacity of the adult mammalian brain. Neural stem cells (NSCs) in the adult brain possess the potential to generate new neurons after injury, yet the molecular mechanisms regulating their neuronal differentiation following ischemic insult remain incompletely understood. Here, integrating single-cell multi-omics analyses with spatial transcriptomics, we systematically delineated cell type-specific spatiotemporal dynamics in the striatum of a mouse model of ischemia-reperfusion injury. We identified Neurensin 1 (Nrsn1) as a gene markedly upregulated during NSC-derived neuronal differentiation in the recovery phase. Mechanistically, Foxa2 directly activates Nrsn1 transcription, whereas Nrsn1 promotes neuronal differentiation by facilitating the nuclear translocation of the chromatin-remodeling factor Smarcc1 in vitro. In vivo, both endogenous NSCs and transplanted NSCs overexpressing Nrsn1 significantly enhanced neuronal regeneration and improved functional recovery in mice subjected to middle cerebral artery occlusion and reperfusion (MCAO/R). Collectively, these findings identify Nrsn1 as a key regulator of NSC neuronal differentiation and uncover a Nrsn1-Smarcc1 coupling mechanism that promotes neural regeneration after ischemic brain injury, highlighting a potential molecular target for strategies aimed at enhancing post-stroke recovery.

Foxa2

Dietary Polyphenol Acteoside-Related Molecular Signatures in Clear Cell Renal Cell Carcinoma: Multi-Omics Profiling and Functional Validation of IMPDH1.

Clear cell renal cell carcinoma (ccRCC) is characterized by substantial metabolic and molecular heterogeneity, but the disease-relevant programs associated with acteoside, a dietary polyphenol, remain poorly understood. We integrated predicted acteoside targets with bulk, single-cell, and spatial transcriptomic data from ccRCC and combined molecular subtyping with cross-cohort machine-learning analysis. Acteoside-related signatures were preferentially enriched in malignant compartments and increased with tumor grade and stage. Consensus clustering identified two molecular subtypes with distinct biological and clinical features. C1 was associated with immune activation, metabolic activity, and more favorable survival, whereas C2 showed greater genomic instability, reduced renal epithelial differentiation, and poorer outcomes. We further benchmarked multiple machine-learning strategies and established a 10-gene prognostic model that retained predictive performance across independent cohorts, with IMPDH1 emerging as the strongest risk-associated feature. Functional experiments confirmed the biological relevance of IMPDH1: its knockdown suppressed ccRCC cell proliferation, DNA synthesis, colony formation, and migration, whereas overexpression produced the opposite effects. Together, these findings indicate that acteoside-related molecular signatures capture clinically relevant heterogeneity in ccRCC and provide a framework for linking dietary-polyphenol-related molecular space with tumor biology. The identification and functional validation of IMPDH1 further highlight its potential importance in ccRCC progression.

IMPDH1

High-Content CRISPR Screening: Methods and Applications.

Clustered regularly interspaced short palindromic repeats (CRISPR)-Cas9 screening has become a central technology in functional genomics, enabling genome-scale interrogation via pooled perturbations. Early CRISPR screens employed survival or simple phenotypic readouts to identify essential genes and drug resistance mechanisms. However, as biological questions have shifted toward understanding regulatory networks, cellular heterogeneity, and context-dependent gene functions, there has been increasing demand for screening strategies capable of capturing complex cellular phenotypes beyond cell fitness. Recent advances in single-cell sequencing, high-content imaging, and spatial transcriptomics have expanded the resolution of CRISPR screening by enabling multidimensional phenotypic characterization following genetic perturbation. By integrating pooled perturbations with diverse readouts, these approaches systematically map targeted gene edits to transcriptional states, cellular phenotypes, and microenvironmental contexts. Meanwhile, innovations in library design, delivery, and computational pipelines have further improved the robustness and interpretability of high-content screening platforms. This review synthesizes the methodological evolution of CRISPR screening, emphasizing advances in perturbation strategies, delivery systems, and multimodal readouts. Representative applications spanning oncology, immunotherapy, developmental biology, neurobiology, and infectious diseases are delineated to demonstrate refined gene network annotations. Additionally, existing technical bottlenecks, such as scalability, cost constraints, and in vivo limitations, are critically assessed. Finally, future directions are proposed to facilitate the development of precise medicine.

CRISPR screening

Multimodal risk assessment for oral potentially malignant disorders: Integrating patient-centered and specimen-derived data.

BACKGROUND: Oral potentially malignant disorders exhibit heterogeneous malignant transformation risk that clinical approaches fail to adequately predict. Histopathologic dysplasia grading, the reference standard of risk assessment, is associated with poor interobserver reliability and limited prognostic discrimination. It is necessary to define other potential patient- and tissue-associated risk modifiers to improve patient-specific disease prediction. TYPES OF STUDIES REVIEWED: PubMed was queried for patient- and specimen-derived factors as they relate to oral cancer and oral potentially malignant disorders, with preference for systematic review and meta-analysis articles published within the past 5 years. When not available, guidelines from the American Cancer Society, National Cancer Institute, or other national organizations or the most recent best articles were referenced to support the data presented. RESULTS: Within patient-associated factors, validated measures of tobacco and alcohol exposure, clinical lesion characteristics, systemic health factors including metabolic syndrome components, comorbidity risk, and dental health indexes were found. Within specimen-derived data, tissue-based analyses encompassing histopathology and advanced molecular profiling (genomic, epigenomic, transcriptomic, spatial approaches), blood-based germline and somatic mutation analysis, and saliva-based microbiome characterization and inflammatory biomarker assessment were addressed. PRACTICAL IMPLICATIONS: Malignant transformation reflects intersecting patient and specimen risk pathways that affect each patient differently; no single modality captures this complexity. Realizing precision prognostication in oral precancer will require coordinated expansion and standardization of data collection across research groups. This review is intended to guide covariate selection for prospective study design, improve reproducibility, and ultimately enable the development of validated multimodal risk prediction tools for clinical deployment.

Humans

Epigenetic and Transcriptional Regulatory Networks Underlying Psoriasis Pathogenesis.

Psoriasis is a chronic, immune-mediated dermatologic disorder characterized by the hyperproliferation of keratinocytes and dysregulated immune signaling. Although genome-wide association studies have identified susceptibility loci, the multifactorial nature of the disease underlines the importance of nongenetic regulatory mechanisms. Among these epigenetic modifications are those that critically link genetic predisposition with environmental stimuli. This review offers an in-depth overview of the current insights into the role of epigenetic regulation in the pathophysiology of psoriasis. Key mechanisms, including aberrant DNA methylation, histone post-translational modifications (eg, H3K27ac, H3K4me3), and dysregulated noncoding RNAs, are discussed in the context of inflammatory signaling and immune cell function. This review also explores how environmental factors such as UV radiation and air pollution induce the epigenetic reprogramming that perpetuates the proinflammatory state. Furthermore, it highlights the translational potential of targeting epigenetic regulators and epigenome-editing technologies, including clustered regularly interspaced short palindromic repeats (CRISPR) fusion systems, as precision therapeutic strategies. In parallel, advances in single-cell epigenomics, spatial transcriptomics, and the profiling of circulating biomarkers offer novel diagnostic tools. Despite advances, challenges persist, including the limited predictive value of preclinical models and variable epigenetic profiles. Positioning epigenetics as the bridge between genetic risk, environmental triggers, and therapeutic advances, this review presents a framework for precision medicine in psoriasis.

Humans

Characterizing the Discordance between AT-Rich Interacting Domain 1A Protein and Genotype in Endometrioid-Type Endometrial Tumors.

ARID1A is one of the most frequently mutated genes in endometrial cancer, with approximately 40% of patients harboring an ARID1A mutation. However, relatively little is known about how AT-rich interacting domain 1A (ARID1A) protein loss shapes endometrial cancer pathogenesis. Mounting evidence from other malignancies suggests that ARID1A protein can be regulated post-translationally, independent of genotype. However, most studies in endometrial cancer evaluate genotype alone, overlooking the potential for alternative mechanisms of ARID1A loss. To address this gap, ARID1A protein expression and genotype were examined in endometrioid tumors, and associated transcriptional changes were characterized. Evaluation of ARID1A protein in 71 human endometrioid tumors demonstrates that protein loss can occur regardless of ARID1A genotype. Retention or deficiency of ARID1A protein was not significantly related to variant allele frequency or location of mutation in human tumors with mutant ARID1A. A human endometrial cancer cell model suggests that ARID1A protein loss can occur through proteasomal degradation. Furthermore, ARID1A protein expression was found to be a predictor of worse overall survival in The Cancer Genome Atlas cohort of ARID1A wild-type endometrioid tumors. Spatial transcriptomics of 16 human endometrioid tumors revealed that both genotype and protein expression of ARID1A play a role in shaping unique transcriptional signatures in endometrial cancer and can be used to predict patient prognosis. Suggesting evaluation of ARID1A should not be done solely by sequencing techniques.

Humans

MIF-CD74 axis facilitates MDSC infiltration in the tumor microenvironment of pancreatic ductal adenocarcinoma.

Immune checkpoint inhibitors show insufficient efficacy against pancreatic ductal adenocarcinoma (PDAC). The tumor microenvironment (TME) has a remarkable influence on responsiveness to cancer immunotherapy. The aim of this study was to investigate immunosuppressive characteristics of TME in PDAC tissues. The flow cytometry (FCM) of PDAC surgical specimens revealed that the profile of tumor-infiltrating leukocytes was classified into myeloid cell- and T-cell-dominant subtypes; the myeloid subtype was associated with poorer patient outcomes. Myeloid-derived suppressor cells (MDSCs) showed the highest hazard ratio among various myeloid cell types. Single-cell RNA sequencing and FCM revealed that most MDSCs, but not lymphocytes, in PDAC tissues characteristically express CD74. Macrophage migration inhibitory factor (MIF), a CD74 ligand, was highly expressed in cancer-associated fibroblasts (CAFs) and cancer cells. Spatial transcriptomics demonstrated that the MIF-CD74+ myeloid cell interaction was recognized in CAF-dominant areas in PDAC tissue. CAFs expressing immune suppressor molecules such as MFAP5 and LRRC15 were consistent with MIF+ CAFs. Furthermore, MIF+ CAFs enhanced the migratory activity of MDSCs and promoted MDSC induction and activation. In the murine model, MDSCs were significantly increased in MIF-expressing PDAC tumors, as were CD74+ M-MDSCs per M-MDSC, confirming in vivo interaction between CD74 and MIF. MDSCs play a crucial role in creating an immunosuppressive TME in PDAC; the MIF-CD74 axis drives interactions between MDSCs and CAFs.

Humans

Integrative multi-omics reveals a fibroblast-centered, ZFHX3-prioritized regulatory framework linking sick sinus syndrome and atrial fibrillation.

OBJECTIVE: To define shared genetic and multi-scale mechanisms underlying comorbidity between sick sinus syndrome (SSS) and atrial fibrillation (AF). METHODS: We integrated genome-wide association study (GWAS) summary statistics for SSS and AF with Genotype-Tissue Expression (GTEx) expression and splicing quantitative trait loci (eQTL/sQTL), atrial single-cell and spatial transcriptomics, and epigenomics. We identified trait-relevant tissues and pathways, prioritized shared cell types, quantified genome-wide and local genetic sharing, detected joint loci by cross-trait meta-analysis, and linked loci to regulatory programs via colocalization and cell-prioritized co-expression networks. RESULTS: Both traits showed strongest enrichment in cardiac tissue, especially Heart Atrial Appendage. Fibroblasts from the left atrial appendage were consistently prioritized as the key shared cell population. SSS and AF displayed significant positive genome-wide genetic correlation, with multiple locally shared regions, including six major loci. Cross-trait meta-analysis identified eight joint-phenotype SNPs implicating four susceptibility genes. ZFHX3 was the leading tissue-cell-gene candidate, acting as a hub in fibroblast co-expression modules and colocalizing with cardiac regulatory signals. CONCLUSION: Shared liability for SSS and AF is highly tissue- and cell-specific, converging on regulatory networks in atrial appendage fibroblasts, with ZFHX3 serving as a central mechanistic and biomarker node.

Humans

PRDX1 facilitates USP7-dependent stabilization of SCD1 and promotes bladder cancer progression.

Bladder cancer is characterized by redox adaptation and metabolic plasticity, but the mechanisms linking these processes remain incompletely understood. Integrating bulk, single-cell, and spatial transcriptomic analyses, we identified PRDX1 as a malignant epithelial cell-associated factor linked to adverse outcome. Genetic gain- and loss-of-function studies showed that PRDX1 promoted proliferation, motility, and xenograft growth while limiting reactive oxygen species accumulation and mitochondrial apoptosis. Proteomic and biochemical analyses identified an association between PRDX1 and SCD1. PRDX1 prolonged the SCD1 protein half-life without detectably altering SCD1 transcript abundance and increased USP7-SCD1 co-precipitation. USP7 removed K48-linked polyubiquitin chains from SCD1 and prevented its proteasomal degradation, whereas catalytically inactive USP7 failed to deubiquitinate SCD1. Deletion of PRDX1 residues 157-199 weakened its association with SCD1 and reduced USP7-SCD1 co-precipitation. Depletion of SCD1 or USP7 suppressed PRDX1-dependent growth in vitro and in xenografts. These findings support a model in which PRDX1 facilitates USP7-dependent stabilization of SCD1 and promotes bladder cancer progression.

Bladder cancer