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PubMed2025

Coalescing single-cell genomes and transcriptomes to decode breast cancer progression.

Understanding epithelial lineages of breast cancer and genotype-phenotype relationships requires direct measurements of the genome and transcriptome of the same single cells at scale. To achieve this, we developed wellDR-seq, a high-genomic-resolution, high-throughput method to simultaneously profile the genome and transcriptome of thousands of single cells. We profiled 33,646 single cells from 12 estrogen-receptor-positive breast cancers and identified ancestral subclones in multiple patients that showed a luminal hormone-responsive lineage, indicating a potential cell of origin. In contrast to bulk studies, wellDR-seq enabled the study of subclone-level gene-dosage relationships, which showed near-linear correlations in large chromosomal segments and extensive variation at the single-gene level. We identified dosage-sensitive and dosage-insensitive genes, including many breast cancer genes as well as sporadic copy-number aberrations in non-cancer cells. Overall, these data reveal complex relationships between copy number and gene expression in single cells, improving our understanding of breast cancer progression.

Breast Neoplasms↗

PubMed2026

Live-cell transcriptomics with engineered virus-like particles.

Transcriptomic profiling is widely applied to characterize cellular gene expression, yet existing approaches lyse cells and preclude direct analysis of transcriptional dynamics in the same sample over time. We addressed this limitation by engineering mammalian cells to "self-report" their transcriptional states via mRNA export in virus-like particles (VLPs). Repeated sampling of culture media from VLP-producing cell populations faithfully captured evolving transcriptional states in complex biological settings, including acute inflammatory stimulation of primary cell spheroids and multi-day differentiation of pluripotent stem cells. We engineered VLP components for multiplexed readouts from distinct cell types in co-culture and for tuning self-reported RNA profiles. Finally, we demonstrated the unique utility of self-reporting for selective longitudinal tracking of endothelial cell dynamics within the enclosed architecture of a microphysiological co-culture system to identify perivascular stroma-dependent temporal gene programs underlying vasculogenesis. Altogether, this work establishes cellular self-reporting as a broadly enabling technology for live-cell transcriptome-wide gene expression profiling.

RNA↗

PubMed2026

Integrative dual-track transcriptomics reveals stage-specific coordination, regulatory divergence, and HSP90AA1-associated remodeling in human folliculogenesis.

Human folliculogenesis depends on coordinated yet non-identical developmental remodeling in the oocyte and its surrounding granulosa cells. When these two compartments remain synchronized and when they diverge into lineage-specific regulatory states, however, remains incompletely resolved. Here we performed an integrative dual-track re-analysis of the human RNA-seq dataset GSE107746, modeling oocytes and granulosa cells as distinct but developmentally linked compartments across follicular progression. Analysis of 148 sequencing libraries showed that compartment identity was the dominant source of transcriptomic variation, supporting compartment-aware downstream interpretation. Within this framework, oocytes followed a relatively continuous developmental trajectory, with substantial transcriptional remodeling already evident across adjacent stages, whereas granulosa cells showed weaker early-stage contrasts but markedly stronger late-stage reorganization, particularly around the antral and preovulatory transitions. Functional enrichment indicated that oocyte maturation was associated with RNA-processing and broader genome-regulatory remodeling, whereas granulosa maturation was dominated by progressive mitochondrial and bioenergetic activation. Co-expression analysis showed that both compartments contained strong late-stage programmes together with inverse early-state modules, indicating a shared systems-level architecture of maturation, although the hub-gene composition and biological content of these programmes were largely compartment-specific. Machine-learning validation reinforced this asymmetry: oocyte stage classification was best recovered from a compact eigengene-based representation, whereas granulosa stage discrimination was better resolved by a broader differential-expression-derived feature set. At the gene level, HSP90AA1 emerged as a stage-associated marker with compartment-specific behavior, showing progressive attenuation across oocyte development, assignment to the selected oocyte blue module, and sharper transitional dynamics in granulosa cells. Together, these findings support a model in which human folliculogenesis proceeds through coordinated but non-equivalent transcriptomic remodeling, with shared developmental logic at the systems level but distinct molecular execution in germline and somatic compartments.

Co-expression networks↗

PubMed2026

Genomic and transcriptomic characterization of genes expressed at 20 MPa by the marine actinobacterium Kocuria flava.

A marine hydrocarbonoclastic actinobacterium Kocuria flava IOS11 was isolated from 3500 m deep-sea water of the Indian Ocean. The isolate efficiently degraded phenanthrene (250 mg/L) achieving 82 and 98% of degradation at 0.1 MPa and 20 MPa, respectively within a period of 5 days. Whole genome, transcriptomee and metabolomic analysis elucidated its phenanthrene biodegradation efficiency under in situ deep-sea conditions. The genome sequence comprises 3.47 Mb distributed across 88 scaffolds with a high GC content of 74.30%. The genome analysis encoded 3126 genes including 3052 protein coding sequences with functional annotation identifying a broad array of genes associated with PAHs degradation, environmental stress adaptation, biosurfactant and siderophore synthesis. Transcriptome profiling under 0.1 and 20 MPa conditions with phenanthrene as a sole carbon source revealed enhanced expression of hydrocarbon degrading genes, transporters, biosurfactant associated enzymes and stress responsive genes including integrases, DNA repair protein Rad, alanine ligase, heat and cold shock proteins under high pressure conditions underscoring the deep-sea adaptation capabilities of the strain. The degradation pathway of phenanthrene was proposed through integrated genome, transcriptome and metabolomic analysis. These studies provided K. flava IOS11 as a metabolically versatile and pressure adapted bacterium with promising potential for bioremediation application in extreme marine environment.

Transcriptome↗

PubMed2026

Single-cell transcriptomics on FFPE placenta: A novel method for comprehensive exploration of an entire placental section.

INTRODUCTION: The placenta's complex cellular diversity challenges traditional transcriptomic analyses. Single-cell RNA sequencing (scRNA-seq) offers breakthrough capabilities by enabling transcriptome profiling at the single-cell level. However, traditional scRNA-seq relies on fresh or frozen samples, which present practical storage and quality challenges. Applying scRNA-seq to Formalin-Fixed, Paraffin-Embedded (FFPE) placentas could harness archived samples for clinical insights. METHODS: We used 10x Genomics Flex technology to analyze 8 non-pathological placentas ranging from 21 + 6 weeks of gestation (WoG) to 39 + 4 WoG. RESULTS: Our approach identifies diverse cell populations and allows us to discern maternal from fetal cells. Despite sample size limitations, the method yields comparable data to prior fresh/frozen tissue studies and we complete these data by integrating new molecular markers. The potential to correlate single-cell results with histopathology enables us to conduct an in-depth analysis across entire placental sections by concurrently addressing both fetal and maternal cells. We could thus confirm molecular markers like KRT5/6 using immunohistochemistry by revisiting the slide. DISCUSSION: This innovation could aid in understanding focal anomalies observed on standard histology slides, thereby enhancing traditional histopathological assessments. Given its practicality, integrating our method into routine practice is both feasible and promising.

Differentially expressed genes (DEG)↗

PubMed2026

From dormancy to germination: Transcriptome analysis reveals the potential involvement of heat shock proteins in gibberellin-induced seed dormancy release in Solanum torvum.

Solanum torvum, a superior vegetable grafting rootstock and medicinal Solanaceae plant, exhibits strong seed dormancy, which limits its commercial cultivation. Among various strategies explored to improve the germination rate of S. torvum, exogenous application of gibberellin (GA) has been shown to be effective. In this study, a GA concentration of 2.5 mM was established as the optimal for breaking dormancy in S. torvum seeds. Transcriptome analysis of dry, water-soaked, GA-soaked, and GA-induced germinated seeds was conducted to investigate the molecular mechanism of GA-mediated dormancy release. During the soaking period, GA application significantly induced transcriptome changes in processes including protein processing, translation, and peptide biosynthesis. Concurrently, GA treatment promoted plant hormone signal transduction, enhanced DNA-binding transcription factor activity, and activated monocarboxylic acid biosynthetic process, all of which facilitated seed water absorption. Furthermore, the differentially expressed genes (DEGs) induced by GA during soaking primarily functioned in signal transduction or activation. While most of these DEGs returned to their pre-treatment expression levels before subsequent recovery, a subset persisted until seed germination. During radicle protrusion, the persistent DEGs were associated with energy metabolism and cell structure establishment. Notably, heat shock protein (HSP) genes showed dynamic expression across all stages (soaking, germination, and radicle penetration). Furthermore, by adjusting germination conditions, temperature was confirmed to be a necessary but not sufficient condition for GA-induced S. torvum seed germination. However, functional validation (e.g., using HSP inhibitors or genetic approaches) is still required to confirm the causal role of HSPs. Collectively, these findings not only clarify the molecular basis of GA-regulated seed dormancy breaking in S. torvum but also provide practical guidance for optimizing its commercial propagation protocols.

Gibberellins↗

PubMed2026

Comparative metabolomic and transcriptomic profiling of flavonoid diversity and antioxidant capacity in three Isatis species.

Flavonoids are key bioactive compounds in plants with significant health benefits. This study employs an integrated multi-omics approach to investigate flavonoid diversity and antioxidant capacity across three Isatis species: I. oblongata, I. tinctoria, and I. indigotica. Metabolomic profiling identified 200 flavonoids, with glycosides being the most abundant class. I. tinctoria exhibited the highest total flavonoid content and antioxidant activity, strongly correlated with the accumulation of 53 core differential flavonoid metabolites, most of which were glycosylated derivatives. Transcriptomic analysis revealed coordinated upregulation of phenylpropanoid pathway genes and specific UDP-glycosyltransferases (UGTs) in I. tinctoria, providing a genetic basis for its enhanced glycoside production. The study establishes a clear genotype-metabolite-phenotype linkage, highlighting glycosylation as a key mechanism underlying flavonoid-driven antioxidant superiority in Isatis. Although the current evidence is primarily correlative, the consistent and strong associations across independent transcriptomic, metabolomic, and antioxidant datasets provide a robust foundation for this conclusion. These findings offer new insights into the metabolic evolution and regulatory networks of flavonoids, with implications for breeding and metabolic engineering of high-value medicinal plants.

Flavonoids↗

PubMed2026

Attribution of PM2.5-Induced Transcriptomic Perturbation to Toxic Components.

Ambient fine particulate matter (PM2.5) is a chemically complex mixture whose health impacts are not fully captured by particle mass. Here, we developed an interpretable chemotranscriptomic framework to attribute PM2.5-induced molecular perturbations to toxicity-relevant components. PM2.5 collected from urban roadside and coastal environments was separated into whole, extractable, and unextractable fractions, characterized by LC/GC × GC-HRMS-based nontarget analysis and inductively coupled plasma mass spectrometry (ICP-MS), and evaluated using cytotoxicity testing and transcriptomic profiling in human bronchial epithelial cells. Urban PM2.5 exhibited greater cytotoxic potency per unit mass than coastal PM2.5, with extractable fractions accounting for most cytotoxic and pathway-level responses. Transcriptomics revealed distinct site-specific modes of action: urban PM2.5 preferentially induced oxidative stress, xenobiotic metabolism, and cell cycle suppression, consistent with acute, nonapoptotic injury, whereas coastal PM2.5 elicited weaker cytotoxicity but stronger interferon-mediated immune and apoptosis-related signaling. Integrating chemical abundance with pathway activity using random forest regression, SHAP interpretation, and mechanistic corroboration reduced 5,033 detected features to 444 pathway-linked candidate drivers. Fewer than 5% of features explained ∼95% of cumulative model contribution. Standard-confirmed contributors included plasticizer-related compounds, aromatic and heteroaromatic combustion products, and copper for urban PM2.5 and secondary/aged organics and nickel for coastal PM2.5. These findings support mechanism-informed prioritization of hazardous PM2.5 components beyond mass-based assessment.

Particulate Matter↗

PubMed2024

Transcriptomic pathology of neocortical microcircuit cell types across psychiatric disorders.

Psychiatric disorders such as major depressive disorder (MDD), bipolar disorder (BD), and schizophrenia (SCZ) are characterized by altered cognition and mood, brain functions that depend on information processing by cortical microcircuits. We hypothesized that psychiatric disorders would display cell type-specific transcriptional alterations in neuronal subpopulations that make up cortical microcircuits: excitatory pyramidal (PYR) neurons and vasoactive intestinal peptide- (VIP), somatostatin- (SST), and parvalbumin- (PVALB) expressing inhibitory interneurons. Using laser capture microdissection followed by RNA sequencing (LCM-seq), we performed cell type-specific molecular profiling of subgenual anterior cingulate cortex, a region implicated in mood and cognitive control. We sequenced libraries from 130 whole cells pooled per neuronal subtype (VIP, SST, PVALB, superficial and deep PYR) in 76 subjects from the University of Pittsburgh Brain Tissue Donation Program, evenly split between MDD, BD and SCZ subjects and healthy controls (totaling 380 bulk transcriptomes from ~50,000 neurons). We identified hundreds of differentially expressed (DE) genes and biological pathways across disorders and neuronal subtypes, with the vast majority in interneurons, particularly PVALB. While DE genes were unique to each cell type, there was a partial overlap across disorders for genes involved in the formation and maintenance of neuronal circuits. We observed coordinated alterations in biological pathways between select pairs of microcircuit cell types, also partially shared across disorders. Finally, DE genes coincided with known risk variants from psychiatric genome-wide association studies, suggesting cell type-specific convergence between genetic and transcriptomic risk for psychiatric disorders. Our study suggests transdiagnostic cortical microcircuit pathology in SCZ, BD, and MDD and sets the stage for larger-scale studies investigating how cell circuit-based changes contribute to shared psychiatric risk.

Humans↗

PubMed2025

Integrated histopathology, spatial and single cell transcriptomics resolve cellular drivers of early and late alveolar damage in COVID-19.

The most common cause of death due to COVID-19 remains respiratory failure. Yet, our understanding of the precise cellular and molecular changes underlying lung alveolar damage is limited. Here, we integrate single cell transcriptomic data of COVID-19 and donor lung tissue with spatial transcriptomic data stratifying histopathological stages of diffuse alveolar damage. We identify changes in cellular composition across progressive damage, including waves of molecularly distinct macrophages and depletion of epithelial and endothelial populations. Predicted markers of pathological states identify immunoregulatory signatures, including IFN-alpha and metallothionein signatures in early damage, and fibrosis-related collagens in late damage. Furthermore, we predict a fibrinolytic shutdown via endothelial upregulation of SERPINE1/PAI-1. Cell-cell interaction analysis revealed macrophage-derived SPP1/osteopontin signalling as a key regulator during early steps of alveolar damage. These results provide a comprehensive, spatially resolved atlas of alveolar damage progression in COVID-19, highlighting the cellular mechanisms underlying pro-inflammatory and pro-fibrotic pathways in severe disease.

COVID-19↗

PubMed2025

Ulmus minor response to Dutch elm disease: de novo transcriptome assembly and annotation.

Dutch elm disease (DED), caused by Ophiostoma novo-ulmi (ONU), has devastated elm populations across Europe and North America since the 20th century. In this work, a de novo transcriptome assembly of Ulmus minor in response to ONU is presented. We used two DED-resistant genotypes, MDV2.3 and VAD2, and one DED-susceptible genotype, MDV1, to capture responses to ONU at four time points post-inoculation (6, 24, 72, and 144 hours). RNA from collected samples was isolated and sequenced producing 60.88 M 100 bp paired-end reads per sample. We performed a de novo transcriptome assembly combining data from the three genotypes. The assembly was functionally annotated and validated through differential gene expression analysis of the response. This dataset provides a valuable resource for studying molecular mechanisms of DED resistance in elms, contributing to broadening our understanding of tree immunity and facilitating potential applications in functional annotation of future genome assemblies.

Transcriptome↗

PubMed2026

Chromosome level genome assembly and full-length transcriptome of blacktip trevally (Caranx heberi).

Caranx heberi (Bennett, 1830) commonly known as the blacktip trevally belongs to the family Carangidae and is a potential brackishwater aquaculture species. However, the limited genomic resources are hindering the efforts to study its genetic traits and their molecular basis. To bridge this gap, we generated a high-quality reference genome employing multiple sequencing strategies including PacBio Hifi reads (135x), Illumina short reads (150x), and Hi-C chromosome conformation capturing (180x). The high-quality genome assembly consisted of 159 scaffolds summing to 618.71 Mb and an N50 value of 26.72 Mb. Among these, 24 chromosome level scaffolds covered 97.5% of the total assembly. The genome contained 20.94% of repeat elements and 30,354 protein encoding genes. In addition, full-length transcriptomes were generated using the PacBio IsoSeq approach from seven tissues (gill, kidney, liver, muscle, heart, spleen, and intestine). The comprehensive genomic and transcriptomic resources developed in this study will facilitate the domestication and aquaculture development of C. heberi, as well as support research on its nutritional potential, ecological adaptations, and evolutionary biology.

Animals↗

PubMed2025

Spatial mutual nearest neighbors for spatial transcriptomics data.

MOTIVATION: Mutual nearest neighbors (MNN) is a widely used computational tool to perform batch correction for single-cell RNA-sequencing data. However, in applications such as spatial transcriptomics, it fails to take into account the 2D spatial information. RESULTS: Here, we present spatialMNN, an algorithm that integrates multiple spatial transcriptomic samples and identifies spatial domains. Our approach begins by building a k-nearest neighbors (kNN) graph based on the spatial coordinates, prunes noisy edges, and identifies niches to act as anchor points for each sample. Next, we construct a MNN graph across the samples to identify similar niches. Finally, the spatialMNN graph can be partitioned using existing algorithms, such as the Louvain algorithm to predict spatial domains across the tissue samples. We demonstrate the performance of spatialMNN using large datasets, including one with N = 31 10x Genomics Visium samples. We also evaluate the computing performance of spatialMNN to other popular spatial clustering methods. AVAILABILITY AND IMPLEMENTATION: Our software package is available on GitHub (https://github.com/Pixel-Dream/spatialMNN). The code is available on Zenodo (https://doi.org/10.5281/zenodo.15073963).

Algorithms↗

PubMed2023

Dynamics and variability of transcriptomic dysregulation in congenital myotonic dystrophy during pediatric development.

Myotonic dystrophy type 1 (DM1) is a multi-systemic disorder caused by expansion of CTG microsatellite repeats within DMPK. The most severe form, congenital myotonic dystrophy (CDM), has symptom onset at birth due to large intergenerational repeat expansions. Despite a common mutation, CDM individuals present with a distinct clinical phenotype and absence of common DM1 symptoms. Given the clinical divergence, it is unknown if the hallmark of DM1 pathology, dysregulation of alternative splicing (AS) due to sequestration of MBNL proteins within toxic CUG repeat RNAs, contributes to disease throughout pediatric development. To evaluate global transcriptomic dysregulation, RNA-seq was performed on 36 CDM skeletal muscle biopsies ages 2 weeks to 16 years, including two longitudinal samples. Fifty DM1 and adult/pediatric controls were also sequenced as comparative groups. Despite a large CTG expansion and shared age of onset, CDM individuals presented with a heterogenous, MBNL-dependent mis-splicing signature. Estimation of intracellular MBNL concentrations from splicing responses of select events correlated with total spliceopathy and revealed a distinct, triphasic pattern of AS dysregulation across pediatric development. CDM infants (< 2 years) possess severe mis-splicing that significantly improves in early childhood (2-8 years) independent of sex or CTG repeat load. Adolescent individuals (8-16 years) stratified into two populations with a full range of global splicing dysregulation. DMPK expression changes correlated with alterations in splicing severity during development. This study reveals the complex dynamics of the CDM muscle transcriptome and provides insights into new therapeutic strategies, timing of therapeutic intervention, and biomarker development.

Child, Preschool↗

PubMed2026

POU2F3 expression in lung squamous cell carcinoma: transcriptomic and immunohistochemical profiling with prognosis.

BACKGROUND: Lung squamous cell carcinoma (LUSC) lacks well-defined molecular targets. This study investigated the clinical and biological relevance of POU class 2 homeobox 3 (POU2F3), a tuft cell-associated transcription factor, in LUSC. METHODS: RNA sequencing data of patients with LUSC from The Cancer Genome Atlas (TCGA cohort, n = 190) was analysed and compared to a cohort of surgically resected cases analyzed via immunohistochemistry (IHC cohort, n = 137). Prognostic impact was assessed via survival analyses. Transcriptomic features, pathway enrichment, and immune profiles were evaluated via differentially expressed gene analysis, Gene Set Enrichment Analysis, and CIBERSORTx. RESULTS: High POU2F3 expression independently predicted poor overall survival in the TCGA cohort (HR = 2.06, 95% CI: 1.04-4.08, P = 0.039). In contrast, POU2F3 expression was not prognostic in the IHC cohort (P = 0.995). Morphologically, POU2F3-positive tumours were enriched for non-keratinizing and poorly differentiated subtypes. Transcriptomic analysis showed suppression of proliferation and immune-related pathways (FDR < 0.001), with suggestive enrichment of the TGF-β (FDR = 0.143) and p53 (FDR = 0.229) signaling pathways. On immune deconvolution, POU2F3-high tumours showed a nominal increase in activated dendritic cells, which did not withstand multiple testing correction. POU2F3 protein was detected in 12.4% of tumours and was significantly associated with p53 or RB1 abnormalities (single or double) (P = 0.028). CONCLUSIONS: POU2F3 marks a transcriptionally distinct, early-stage subtype of LUSC with keratinization-related features. Its prognostic relevance appears context-dependent and requires prospective validation in uniformly treated cohorts.

Humans↗

PubMed2026

Integrated Genomics and Transcriptomics Reveal Stable Resistance Loci and Candidate Genes for Powdery Mildew in Wheat.

Powdery mildew, caused by Blumeria graminis f. sp. tritici (Bgt), poses a substantial threat to global wheat production. Enhancing resistance through molecular breeding necessitates a comprehensive understanding of its genetic and molecular underpinnings. This study leveraged a 2-year phenotypic evaluation of 283 diverse wheat accessions combined with genome-wide association studies (GWAS) to pinpoint stable quantitative trait loci for powdery mildew resistance. We identified 52 robust resistance loci across the wheat genome, including seven novel loci consistently detected across four environments. Comparative transcriptome profiling of resistant and susceptible wheat lines revealed 95 differentially expressed genes, predominantly enriched in defense response, signal transduction, and transcription regulation pathways. By integrating the GWAS and transcriptomic data, we precisely identified three compelling candidate genes (TaPIP5K, TaPKG, and TaORR6) on chromosome 2A, which are implicated in cell wall reinforcement, jasmonic acid signaling, and reactive oxygen species scavenging, respectively. Further validation using expression analysis corroborated their pivotal roles in resistance. Our findings provide a rich repository of validated genetic markers, promising candidate genes, and superior resistant germplasms, offering critical resources to accelerate targeted molecular breeding efforts for durable powdery mildew resistance in wheat.

Blumeria graminis f. sp. tritici↗

PubMed2025

Hepatocyte dedifferentiation in 2D culture reveals extensive transcriptomic and proteomic rewiring.

BACKGROUND: Primary hepatocytes are commonly used in vitro to model liver metabolism, but prolonged culturing results in dedifferentiation and potentially limits the applicability of this model. METHODS: We characterized the transcriptome and proteome of full liver and primary hepatocytes as either freshly isolated cells or after 24 hours of 2D-culturing. RESULTS: We found that 2D-culturing for 24 hours changes more than 10,000 genes and 3000 proteins compared with freshly isolated cells, accompanied by a decrease in transcriptional heterogeneity and a loss of zonal markers. Moreover, there were changes in proteins associated with the extracellular matrix, in mitochondrial and ribosomal protein abundances, as well as an increase in the abundance of acute-phase response proteins. CONCLUSION: Collectively, primary mouse hepatocytes in culture rewire the transcriptome and proteome, which may affect the utility of this model to study physiological and molecular mechanisms related to the liver. We developed the Shiny app "Hepamorphosis" (https://cbmr.ku.dk/research/resources/shiny-apps/), which allows users to explore RNA/protein correlations, zonation profiles, and cell-type-specific transcription in full liver and cultured hepatocytes.

Hepatocytes↗

PubMed2026

Transcriptomic analysis identifies novel ferroptosis-related biomarkers and therapeutic targets in pulmonary arterial hypertension.

BACKGROUND: Ferroptosis plays a significant role in pulmonary arterial hypertension (PAH), although its underlying mechanisms and key pathogenic genes remain unclear. METHODS: Transcriptomic data from human PAH and control lung tissue were obtained from the Gene Expression Omnibus (GEO) database, whereas ferroptosis-related genes (FRGs) were sourced from the MsigDb and FerrDb databases. Differentially expressed FRGs (DE-FRGs) were identified through the intersection of FRGs with differentially expressed genes (DEGs). Functional enrichment analysis was performed using Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways. Key hub genes were identified through Least Absolute Shrinkage and Selection Operator (LASSO), support vector machine-recursive feature elimination (SVM-RFE), and weighted correlation network analysis (WGCNA). Gene set enrichment analysis (GSEA) was conducted to explore the functional roles and associated pathways of hub genes. The relationship between hub genes and immune infiltration was investigated. Expression levels of potential biomarkers were validated via Quantitative real-time polymerase chain reaction (qRT-PCR) and immunohistochemistry (IHC) in two PAH animal models (monocrotaline-induced and Sugen5416 plus hypoxia-induced PAH). Finally, molecular docking was employed to screen potential therapeutic compounds. RESULTS: A total of 133 DE-FRGs were identified, with KEGG and GO analyses highlighting their involvement in intracellular iron homeostasis and ferroptosis. Hub genes, notably FZD7 and NFE2, were identified using LASSO, SVM-RFE, and WGCNA. Immune infiltration analysis suggested that monocytes and neutrophils play key roles in PAH pathogenesis. Validation in PAH animal models showed significant upregulation of Fzd7 and downregulation of Nfe2 in lung tissues of both MCT- and SuHx-induced PAH models. Molecular docking identified tetrachlorodibenzodioxin (TCDD) has good binding affinity. CONCLUSION: In summary, we investigated two ferroptosis-related biomarkers, FZD7 and NFE2, in PAH using transcriptomics, offering new insights into molecular mechanisms and potential targeted therapies for the disease.

Ferroptosis↗