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Decoding the landscape of cell-type-specific co-expressed transcription factors in soybean.

Soybean (Glycine max) is an essential source of protein and oil with high nutritional value for human and animal consumption. To enhance our understanding of soybean biology, it is essential to have accurate information regarding the expression of each of its protein-coding genes. Here, we present Tabula Glycine max, a soybean single-cell resolution transcriptome atlas. This atlas comprises single-nucleus RNA-sequencing data from ten different G. max organs and morphological structures constituting the entire soybean plant. These nuclei are grouped into 156 different clusters based on their transcriptomic profiles. The breadth of various organs, tissues and cell types represented in Tabula Glycine max reveals that the pattern of co-expressed transcription factor genes is sufficient to define most cell types based on their function and organ of origin. Defining cell-type-specific co-expressed transcription factor genes offers a new perspective to engineer cell-type-specific programmes and enhance the biology of unique soybean cell types. This cellular resolution and breadth make the Tabula Glycine max an exceptional resource for the plant and soybean communities.

Journal Article↗

shinyDeepGxP: a user-friendly R shiny app for predicting surface protein abundance from scRNA-seq expression using deep learning in blood cells.

MOTIVATION: Understanding accurate immune cell heterogeneity and function in single-cell datasets requires access to protein-level information, which is often unavailable due to experimental limitations. RESULTS: We present shinyDeepGxP, an interactive web application featuring our deep learning model, DeepGxP, for predicting surface protein abundance from single-cell RNA-sequencing (scRNA-seq) data. This platform makes DeepGxP accessible to researchers without programming skills. Users can upload scRNA-seq count matrices and use "Predict Protein" to predict the abundance of 224 biologically relevant surface proteins. shinyDeepGxP provides visualizations to help identify distinct cell populations based on predicted protein profiles. Moreover, users can choose "Explore Model" to reveal key RNA predictors and their associated biological pathways for each protein. Overall, shinyDeepGxP is a user-friendly, freely available web tool that provides protein-level detail for RNA-only single-cell datasets, enabling multimodal discovery without additional experiments. AVAILABILITY AND IMPLEMENTATION: shinyDeepGxP can be launched on https://shiny.crc.pitt.edu/deepgxp/.

Journal Article↗

PROTRIDER: protein abundance outlier detection from mass spectrometry-based proteomics data with a conditional autoencoder.

MOTIVATION: Detection of gene regulatory aberrations enhances our ability to interpret the impact of inherited and acquired genetic variation for rare disease diagnostics and tumor characterization. While numerous methods for calling RNA expression outliers from RNA-sequencing data have been proposed, the establishment of protein expression outliers from mass spectrometry data is lacking. RESULTS: Here, we propose and assess various modeling approaches to call protein expression outliers across three datasets from rare disease diagnostics and oncology. We use as independent evidence the enrichment for outlier calls in matched RNA-seq samples and the enrichment for rare variants likely disrupting protein expression. We show that controlling for hidden confounders and technical covariates, while simultaneously modeling the occurrence of missing values, is largely beneficial and can be achieved using conditional autoencoders. Moreover, we find that the differences between experimental and fitted log-transformed intensities by such models exhibit heavy tails that are poorly captured with the Gaussian distribution and report stronger statistical calibration when instead using the Student's t-distribution. Our resulting method, PROTRIDER, outperformed baseline approaches based on raw log-intensities Z-scores, PCA, and isolation-based anomaly detection with Isolation forests. The application of PROTRIDER reveals significant enrichments of AlphaMissense pathogenic variants in protein expression outliers. Overall, PROTRIDER provides a method to confidently identify aberrantly expressed proteins applicable to rare disease diagnostics and cancer proteomics. AVAILABILITY AND IMPLEMENTATION: PROTRIDER is freely available at github.com/gagneurlab/PROTRIDER and also available on Zenodo under the DOI zenodo.15569781.

Proteomics↗

REACTOR: REgulon Activity analysis and Comparison Tool for single-cell transcriptOmics Research.

SUMMARY: We introduce REACTOR, a computational tool designed to detect differential activity of transcriptional regulators and their target genes (regulons) in single-cell RNA-sequencing data. It expands the currently available framework for regulon analysis by introducing a robust statistical test to detect differential regulon activity between conditions, such as disease versus control, with multiple replicates. By contrasting different conditions, REACTOR enables identification of key condition- and cell type-specific regulons. To demonstrate the use of REACTOR, we illustrate its performance in a publicly available COVID-19 dataset. AVAILABILITY: REACTOR R-package together with an implementation vignette are available at https://www.github.com/elolab/REACTOR.

Regulon↗

Mapping the causal chain from genetic risk variants to lipid dysmetabolism in Parkinson's disease.

The molecular pathways linking genetic variants to Parkinson's disease (PD) onset and progression remain incompletely defined; however, risk alleles in multiple genes, including GBA1, strongly implicate lipid metabolism. To systematically identify causal biomarker signatures, we analysed comprehensive metabolome profiles from blood plasma in 149 PD patients and 150 controls, along with complementary genetic, RNA-sequencing and metabolic data from other available clinical and pathologic cohorts. Using colocalization and summary-data-based Mendelian randomization, we tested whether expression and metabolic quantitative trait loci mediate the association between implicated genetic variants and PD risk. We further integrated differential metabolomics and proteomics from blood and brain to reveal pertinent mechanisms. We show that common PD risk variants at the serine palmitoyltransferase small subunit B (SPTSSB) locus, a key regulator of de novo sphingolipid biosynthesis, are associated with increased SPTSSB brain expression and elevated plasma ceramides. Additional analyses strongly support our hypothesis that a common SPTSSB causal variant is responsible for PD risk as well as the expression and metabolic quantitative trait loci. Multiple sphingolipids and fatty acid derivatives were perturbed in PD, and we identified both unique and shared features with the Alzheimer's disease metabolome. A PD acylcarnitine signature was further replicated in human post-mortem brain tissue, when comparing those with or without preclinical Lewy body pathology. Integrated analysis of complementary brain proteomic profiles revealed dysregulation of mitochondrial processes dependent on acylcarnitines, including fatty acid beta-oxidation, the tricarboxylic acid cycle and oxidative phosphorylation. Our results identify promising biomarkers and reveal a causal chain linking genetic variation to altered gene/protein expression, lipid dysmetabolism, and the manifestation of PD.

Humans↗

Elevated intron retention implicates neuroinflammation in brains of individuals with alcohol use disorder.

Intron retention, a form of alternative RNA splicing, can occur as part of normal gene regulation or result from disruption of the splicing machinery. Retained introns can potentially form double-stranded RNA, activating innate immune sensors and inflammation. This mechanism has been implicated in cancer but has not been studied in neuropsychiatric diseases like alcohol use disorder. We systematically analysed transcriptome-wide intron retention events in post-mortem brain tissue from 142 individuals (66 with alcohol use disorder and 76 controls), encompassing 320 region-specific samples from the superior frontal cortex, nucleus accumbens, central nucleus and basolateral amygdala. Analyses were adjusted for demographic, technical and biological covariates. Validation was performed in alcohol-preferring (P) rats using long-read sequencing. In complementary experiments, immunofluorescent staining was used to detect double-stranded RNA in rat brain tissue, while single-cell RNA-sequencing was performed to test activation of double-stranded RNA-sensing pathways in human brains. Brains from individuals with alcohol use disorder showed significantly higher total intron retention compared with controls, independent of age, with females showing greater increases than males. A total of 368 introns were positively associated with alcohol use disorder, and these introns were significantly longer and had weaker splice acceptor sites compared with non-associated introns. Genes harbouring these intron retention events were enriched in Purkinje neurons, visual cortex neurons and oligodendrocytes. Computational predictions indicated these long introns could form duplex RNA structures. Increased double-stranded RNA was confirmed experimentally in multiple brain regions of alcohol-consuming rats, where it co-localized primarily with neuronal nuclei and dendrites. In individuals with alcohol use disorder, we found that multiple pathways including double-stranded RNA responses, neuroinflammation, interferon and NF-κB signalling, adaptive immunity and apoptosis were activated. In addition, NeuN-positive neuronal counts significantly decreased in both the prefrontal and visual cortices. Furthermore, single-cell analysis demonstrated upregulation of TICAM1, the target of double-stranded RNA sensor TLR3, in oligodendrocytes, as well as widespread activation of downstream inflammatory pathways across glial and neuronal cell types. These findings provide the first evidence that chronic alcohol consumption promotes an overall increase of intron retention in the brain and is associated with the presence of double-stranded RNA. Furthermore, the double-stranded RNA may contribute to neuronal loss and brain pathology by activating a neuroinflammatory response.

alcohol use disorder↗

Immature Neutrophil Programs Associate With Burn Mortality and Extend Across Critical Illnesses.

Severe burns provoke a systemic "genomic storm," yet cell states associated with divergent outcomes remain unclear. We profiled blood cells by single-cell RNA-Sequencing (73 014 cells) from adult patients with burn injuries within postburn day 17 (n = 4) and healthy donors (n = 5), integrated data with bulk signatures of burn size, inhalation injury, and mortality, and evaluated clinical associations in the American Burn Association National Burn Repository. Burn was associated with emergency hematopoiesis marked by expansion of hematopoietic stem/progenitor-like cells, immature neutrophils, and plasmablast/plasma cell states, alongside depletion of naïve CD4+/CD8+ T cells and dendritic cells. Larger burns (>20% TBSA) showed enrichment of humoral transcriptional programs, including plasmablast/plasma cell activation and suppression of cytotoxic CD8+ T-cell states. In multivariable models, inhalation injury was a stronger predictor of death (adjusted odds ratio [OR] 1.9) than burn size (adjusted OR 1.1) and shared greater overlap with the most perturbed single cells in non-survivors; 55% of co-perturbed cells were neutrophils, implicating granulocyte dysregulation as a common lethal axis. We identified a neutrophil-specific 5-gene panel (OLFM4, RETN, LCN2, ARG1, and BTNL3) that discriminated survivors vs non-survivors after burns (area under the curve [AUC] > 0.9) and generalized to trauma (n = 158; AUC 0.81) and intensive care unit COVID-19 (n = 103; AUC 0.75), providing information orthogonal to conventional biomarkers and severity scores. Cytomorphology corroborated transcriptomic immaturity, with ~2-fold higher band neutrophils and larger neutrophil size in a fatal case. Computational drug-reversal analysis highlighted galectin-1 inhibition as a candidate modulator of mortality-associated neutrophil programs. Together, our findings suggest that immature neutrophils represent a shared immune feature across severe burns and other forms of critical illness.

Humans↗

BACH1 orchestrates macrophage state transitions to coordinate regenerative inflammation.

Efficient tissue regeneration requires the precise coordination of inflammatory and regenerative programs, principally mediated by monocyte-derived macrophages. However, the transcriptional wiring and epigenomic processes behind complex macrophage subtype specification and transition between the different states are not known. Here we have identified the transcriptional repressor BACH1 as a critical, cell-intrinsic regulator of monocyte-derived macrophage specification during skeletal muscle regeneration. Using a myeloid-specific BACH1 knockout mouse model, we demonstrate that BACH1 deficiency disrupts the temporal coordination of monocyte-to-macrophage differentiation, leading to aberrant macrophage subsets with concurrent opposing pro- and anti-inflammatory features. Single-cell RNA-sequencing profiling reveals that BACH1 controls a core transcriptional network, including Nfkb1, Cebpb, and interferon signaling, governing inflammatory resolution and functional macrophage specialization. Mechanistically, BACH1 loss accelerates macrophage differentiation but also affects its core cellular identity, resulting in sustained, rather than declining inflammatory programs including upregulation of Il1b and thus, defective tissue remodeling. These immune alterations compromise the paracrine landscape during regenerative inflammation and impair muscle stem cell differentiation. Our findings establish BACH1 as a molecular tuner or controller that integrates early innate immune signaling with regenerative output, positioning it as a central node linking transcriptional control, immune fate decisions, and tissue repair.

Animals↗

Tissue-Level Transcriptomic Entropy Reveals Organ-Specific Aging Patterns and Predicts Cancer Progression.

Although aging and cancer share complex molecular mechanisms, distinguishing causative factors from byproducts remains challenging. Here, we investigated the role of tissue transcriptomic entropy-a measure of transcriptional disorder-in aging and cancer processes by analyzing RNA-sequencing data from over 25,000 samples from human and mouse tissues. We found that entropy changes during aging are highly tissue-specific, with some tissues showing increased entropy while others exhibit decreased or stable entropy levels. Moreover, transcriptomic entropy strongly correlates with age-related processes, showing positive associations with proliferation, cellular senescence, somatic mutation burden, and cellular reprogramming, whereas it negatively correlates with stemness. In cancer, we observed that primary tumors generally display higher entropy than normal tissue, with its levels further increasing in metastatic stages. Cancer treatment modulated entropy patterns in multiple contexts, with changes suggesting a role for transcriptional complexity in tumor plasticity and therapy resistance. Elevated entropy levels predicted poor survival outcomes in multiple cancer types, suggesting its potential as a prognostic marker. Furthermore, differential expression analysis revealed that entropy-associated genes are enriched in developmental processes and depleted in metabolic pathways, indicating a possible link to cellular dedifferentiation. Finally, we found increased entropy in various age-related disorders beyond cancer, suggesting that transcriptomic entropy may be a common feature in age-related diseases. Our findings establish transcriptomic entropy as a fundamental parameter in aging and cancer progression, offering new insights into disease mechanisms.

Humans↗

Comparative Transcriptomic Analyses Identify Candidate Genes for Convergent Reproductive Shifts in a Bimodal Viviparous Amphibian.

Shifts in reproductive mode represent key evolutionary innovations that shape species' life histories and evolutionary trajectories. Species showing bimodal reproductive strategies with multiple independent origins offer a rare opportunity to gain insights into the adaptive processes and mechanisms underlying convergent traits. The fire salamander, Salamandra salamandra, is the only amphibian exhibiting intraspecific variation in reproductive mode across multiple independent reproductive shifts, enabling investigation of the transition between larviparity (females give birth to aquatic larvae) and pueriparity (females give birth to fully developed terrestrial juveniles) within a single species and across different timescales. Pueriparity is an adaptive innovation that skips the aquatic larval stage, allowing individuals to exploit habitats with no available water bodies. The fire salamander is larviparous across most of its range, but pueriparity has evolved independently at least three times: once in the early Pleistocene within S. s. bernardezi in the mountains of northern Spain, and more recently on two land-bridge islands (NW Spain) inhabited by S. s. gallaica. To identify candidate genes associated with these distinct reproductive modes, we compared gene expression profiles of the uterus and oviduct of pregnant females across two independent evolutionary transitions using RNA-sequencing. We detected shared changes in maternal gene expression among pueriparous S. s. bernardezi and S. s. gallaica relative to their larviparous counterparts, in addition to differences unique to each independent evolutionary transition. Functional enrichment analyses indicated that differentially expressed genes were associated with reproductive timing, angiogenesis, and maternal signalling, consistent with the phenotypic differences observed in the uterine environment and embryonic development between the two reproductive modes. This study represents an important first step towards understanding the genomic basis of the evolution of pueriparity in a remarkable bimodal reproductive system, and provides transcriptomic resources and candidate genes for future research into the genomic architecture underlying this poorly understood adaptive trait.

Animals↗

Thalamic NRXN1-mediated input to human cortical progenitors drives excitatory neurogenesis.

The human cerebral cortex develops through coordinated signals from within the cortex and from other brain regions, including the thalamus. However, how thalamic neuronal projections influence early human cortical development remains less well-understood. In this study, we fused cortical and thalamic organoids to investigate how thalamic input shapes the maturation of human cortical cells. Using single-nuclei RNA-sequencing and cellular imaging, we found that thalamic input increases the production of cortical excitatory neurons. We identify neurexin-1 (NRXN1) as a mediator of physical contact between thalamic axons and cortical outer radial glia. Genetic knockout of thalamic NRXN1 reduced these contacts and attenuated the production of upper-layer excitatory neurons. These findings reveal a mechanism by which thalamic input regulates human cortical progenitors and shapes excitatory neuron production during development.

Animals↗

Genomic diversity and thermal niches of Aspergillus molds disrupting rind formation of surface-ripened cheeses.

Filamentous fungi play important roles in the development of surface-ripened cheese microbial communities and contribute to the aesthetics and flavors of these products. Much is known about the diversity and ecology of desirable cheese fungi, but our understanding of the natural history of cheese spoilage molds is limited. The goal of this work was to characterize the genomic diversity of Aspergillus species contaminating artisan cheeses and to identify how the abiotic environment of cheese (the substrate itself and temperature) may constrain the growth of Aspergillus. Comparative genomics identified two main species of Aspergillus, A. westerdijkiae and A. ostianus, as the spoilage molds across three different facilities in the Northeastern United States that experienced contamination events. Multiple genomic types of A. westerdijkiae were found across the different cheese production facilities, indicating that these contamination events are not caused by a single clonal strain. All A. westerdijkiae isolates produced ochratoxin A, but concentrations varied greatly across strains. RNA-sequencing of A. westerdijkiae on nutrient-rich lab media (malt extract agar) versus cheese curd agar identified a suite of pathways enriched in expression on cheese, including degradation of amino and fatty acids. Experiments measuring growth over a range of temperatures identified that spoilage Aspergillus species have a higher optimal growth temperature compared to desirable fungal species in cheese rinds and are outcompeted by Penicillium species at temperatures lower than 15°C. Global fungal metabarcoding databases suggest that A. westerdijkiae is not normally found in natural habitats of the Northeastern United States, and it may be introduced to this region.IMPORTANCEOver the past decade, disruptive contamination events of Aspergillus spoilage molds have occurred at cheese production facilities in Massachusetts, Connecticut, and Vermont in the United States, causing aesthetic, flavor, and potential safety issues. Our work highlights independent introductions of different strains of A. westerdijkiae into multiple cheese facilities and suggests that temperature could be used to control the abundance of Aspergillus spoilage molds. Based on our analysis of the global distribution of A. westerdijkiae, it is not invading cheese facilities from local fungal populations and may be a contaminant in materials used for cheese production.

Aspergillus↗

Amino acid reprogramming and biofilm-specific tricarboxylate transporters in PET-degrading Piscinibacter sakaiensis.

Plastic-degrading bacteria predominantly colonize polymer surfaces as biofilms, yet it remains unclear whether the biofilm phenotype contributes to metabolism beyond retaining extracellular enzymes. Here, we combine population-level RNA-sequencing across three conditions-biofilm cells on polyethylene terephthalate (PET), planktonic cells incubated with PET, and planktonic cells on maltose-with single-cell Raman spectroscopy to characterize the PET response of Piscinibacter sakaiensis (formerly Ideonella sakaiensis). This integrated approach reveals two metabolically distinct response layers. A carbon-source-driven response shared by all PET-exposed cells is dominated by a broad amino acid reprogramming, led by upregulation of branched-chain amino acid transport genes, enhanced serine biosynthesis, and reduced chemotaxis. A biofilm-specific layer selectively induces tripartite tricarboxylate transporter genes from three distinct genomic loci. This transcriptional feature is accompanied by a single-cell phenotype consistent with a protein-rich and saturated membrane. These results suggest that biofilm formation is not limited to enzyme retention but is associated with selective activation of transport systems, consistent with a putative role in capturing PET-derived intermediates at the polymer interface. This two-layer model separates general metabolic adaptation to PET from biofilm-specific functions and provides a framework for understanding how surface-associated bacterial physiology contributes to plastic degradation.IMPORTANCEPolyethylene terephthalate (PET) degradation in natural and engineered environments is largely mediated by surface-attached microbial communities, yet the physiological role of biofilm state during plastic degradation remains poorly understood. Using the model PET degrader Piscinibacter sakaiensis, we show that biofilm-associated cells are not simply retained near the polymer surface but exhibit a distinct metabolic program characterized by selective induction of tripartite tricarboxylate transporters. In contrast, extensive amino acid reprogramming occurs in both biofilm and planktonic PET-exposed cells, indicating that it is driven by carbon source rather than surface attachment. These findings reveal that PET degradation involves two separable physiological layers: a general metabolic response to PET-derived carbon shared across cell phenotypes, and a biofilm-specific transport response potentially linked to substrate capture at the plastic interface. This work advances our understanding of how microbial physiology is organized during plastic biodegradation and identifies transport processes as previously unrecognized components of PET-degrading biofilms.

PET biodegradation↗

Follicular Lymphoma Transformation is Characterized by Cytokine-associated Remodeling of Stromal and Macrophage Compartments.

Across cancer, one of the most frequent examples of histologic transformation is the evolution of follicular lymphoma (FL) to an aggressive large cell lymphoma. Despite recent progress, understanding of the molecular and cellular underpinnings of transformation remains incomplete. Here, we dissect the interplay of tumor and microenvironment cell populations across transformation through a multimodal investigation of 95 FL and transformed FL (tFL) samples, including single-cell and bulk RNA-sequencing alongside spatial transcriptomics and proteomics, and validate findings across independent FL-tFL pairs. Upon transformation, fibroblasts and GPNMB+ macrophages increase while lymph-node organizing follicular dendritic and CCL21+ fibroblastic reticular cells were lost, resulting in an altered spatial distribution of cytokines that impacts T cell infiltration and macrophage differentiation and function. Secreted stromal and macrophage signals were further evident by non-invasive plasma proteomics. Taken together, our data reveal expansion of macrophages and fibroblasts as key features of transformation with potential diagnostic and therapeutic implications.

Journal Article↗

An integrated single-cell and spatial transcriptomic atlas of thyroid cancer progression identifies prognostic fibroblast subpopulations.

Although well-differentiated thyroid carcinoma (WDTC) is characterized by a robust treatment response, aggressive subtypes, such as anaplastic thyroid carcinoma (ATC), remain highly lethal. To understand thyroid cancer evolution in both children and adults, we analyzed single-cell transcriptomes of 423,733 cells from 81 samples and spatially resolved key tumor and microenvironment populations across 28 tumors with spatial transcriptomics, including rare and unique composite WDTC/ATC tumors and pediatric diffuse sclerosing thyroid carcinomas. Additionally, we identified gene signatures of stromal cell populations in 5 large thyroid cancer bulk RNA-sequencing cohorts. Through this multi-institutional effort, we defined a population of POSTN+ myofibroblast cancer-associated fibroblasts (myCAFs) that are intimately associated with invasive tumor cells and correlate with poor prognosis, lymph node metastasis, and disease progression in thyroid carcinoma. We also revealed a population of inflammatory CAFs that are distant to tumor cells and are found in the inflammatory stromal microenvironment of autoimmune thyroiditis. Together, our study provides spatial profiling of thyroid cancer evolution in samples with mixed WDTC/ATC histopathology and identifies a prognostic myCAF subtype with potential clinical utility in predicting aggressive disease in both children and adults.

Humans↗

Blood-derived gene expression profiles associated with dietary microalgae oil intake and methane emission variation in lambs.

BACKGROUND: Minimising methane (CH4) emissions from livestock production is a global priority, and feed modifications, such as supplementing diets with microalgae, have previously been shown to help reducing enteric CH4 production. This study explored blood-derived host gene expression profiles from twenty lambs supplemented with increasing levels of microalgae oil to investigate their transcriptional responses associated with varying microalgae oil levels while also exploring the host systemic responses towards varied CH4 productions. RESULTS: Findings revealed no significant changes in CH4 production with increasing levels of microalgae oil intake through phenotypic analysis (P = 0.18). However inter-individual variations in CH4 production ranged from 27.02 to 47.86 g/day throughout the study period. Blood RNA-Sequencing identified 64 significant genes including DHCR7, DHCR24, HMGCS1, INSIG1, LSS, MSMO1, and SQLE, which were involved in lipid metabolism, and steroid biosynthesis that became enriched alongside increasing microalgae oil intake levels thereby contributing to a positive impact on lambs' metabolic functions. Additionally, seven significant blood-expressed host genes (NME4, MARCHF3, PLXNB3, LOC132657460, LOC121819234, LOC105603087, LOC101116551) functionally enriched in nucleotide metabolic pathways and immune responses were identified to have significant positive associations with increasing CH4 production. Importantly, this study found no overlap between genes associated with microalgae oil intake and those linked to CH4 emissions. CONCLUSIONS: Findings suggest that microalgae oil intake and inter-individual variations in CH₄ production are associated with distinct blood-derived transcriptional responses. Although such signals should be interpreted as proxies for systemic host responses rather than direct measures of rumen-specific processes, these results emphasise the importance of considering host-associated molecular variations alongside dietary CH₄-mitigation strategies.

Animals↗

Genetics-Informed Mapping Identifies a CRIM1-Associated Endocardial Inflammatory Remodeling State in Acute Myocardial Infarction.

BACKGROUND Acute myocardial infarction (AMI) reflects inherited susceptibility and inflammatory remodeling, but the cellular contexts linking genetic risk to disease remain unclear. MATERIAL AND METHODS We integrated a meta-transcriptome-wide association study (TWAS) with a human cardiac single-nucleus RNA-sequencing atlas contained 11 individuals (5 AMI and 6 donor) to identify genetics-informed cellular programs. Composite program states were defined by global score quartiles. A fixed 5-gene panel was evaluated for nucleus-level endocardial low-transcriptional-state (Endo_LTS) vs endocardial high-transcriptional-state (Endo_HTS) discrimination within the AMI endocardium using 5-fold leave-1-patient-out cross-validation. Functional follow-up used CRIM1 silencing in hypoxia-treated human induced pluripotent stem cell (hiPSC)-derived endocardial endothelial-like cells and complementary peripheral blood analyses. RESULTS The endocardium exhibited the most prominent infarction-associated increase in TWAS-anchored program activity, with expansion of program-high states and higher CytoTRACE scores. A consensus 5-gene panel (RPS8, PLEC, CFDP1, CRIM1, TNS2) was identified. Among 2163 AMI endocardial nuclei from 5 patients, the state classifier included 364 Endo_LTS and 751 Endo_HTS nuclei; 1048 Endo_MTS nuclei were excluded. Pooled out-of-fold ROC-AUCs ranged from 0.665 to 0.831. The panel also showed discriminatory value in an independent peripheral-blood AMI-vs-control cohort. CRIM1 was prioritized as a candidate linked to the remodeling program. CRIM1 silencing attenuated ACTA2/alpha-SMA, vimentin, LDHA, CCL2, and VEGFA and partially restored CD31, whereas TGF-ß remained elevated. CONCLUSIONS These findings identify a genetics-informed endocardial inflammatory remodeling state in AMI and define a 5-gene surrogate of its activated state. CRIM1 is prioritized as a candidate linked to selected inflammatory, metabolic, and structural outputs. Persistent TGF-b elevation after CRIM1 silencing argues against a simple linear regulatory model and indicates that further mechanistic validation is required.

Humans↗

Malignant epithelial states drive immune dysfunction in ampulla of Vater carcinoma.

BACKGROUND: Ampulla of Vater (AoV) carcinoma is a rare malignancy arising at the junction of intestinal and pancreatobiliary epithelium. Its heterogeneous clinical behavior and histological diversity have hindered therapeutic advances, and the cellular basis of this heterogeneity remains unclear. We aimed to construct a single-cell transcriptomic atlas of AoV carcinoma, with a focus on identifying epithelial subtypes and their interactions with the tumor microenvironment (TME). METHODS: We performed single-cell RNA sequencing on eight primary AoV tumors and four matched normal tissues. Comprehensive clustering and transcriptomic analyses identified cell-type composition, epithelial heterogeneity, and tumor-immune interactions. Findings were validated using deconvolution of bulk RNA-seq data from 62 AoV carcinoma patients. Results Malignant epithelial cells were categorized into four distinct subtypes: Int-Wnt, PB-KRAS, Int-Hypoxia, and Cycling stage. PB-KRAS cells exhibited stem-like transcriptional programs and high genomic instability. Deconvolution analysis of bulk RNA-seq data from the independent AoV cohort revealed that enrichment of the PB-KRAS subtype correlated with tumor recurrence and poor survival. Our immune profiling analysis discovered a significant association between PB-KRAS subtype and GZMK+ CD8+ T cells, which are in a pre-dysfunctional state, alongside SPP1+ macrophages exhibiting immunosuppressive traits. Spatial transcriptome data further supports the immunosuppressive natures of TME around PB-KRAS subtype malignant epithelial cells in AoV carcinoma. CONCLUSIONS: Our study presents a single-cell atlas of AoV carcinoma, highlighting the molecular diversity of malignant epithelium and its association with the immune microenvironment. The PB-KRAS subtype emerges as a stem-like, immunosuppressive tumor state associated with poor prognosis, providing insights for future therapeutic targeting.

Ampulla of Vater carcinoma↗