The heterogeneity and complex tumor microenvironment of lung adenocarcinoma lead to poor prognosis. Autophagy, as a key cellular process, interacts with tumor immune infiltration and jointly affects the progression of lung adenocarcinoma, but its core regulatory genes and mechanisms are still unclear.This study integrated three lung adenocarcinoma transcriptome datasets from the GEO database and performed cross-analysis with the human autophagy gene set to screen for differentially expressed autophagy-related genes. Identify core prognostic genes by constructing protein interaction networks and combining them with machine learning algorithms (Cox regression, SHAP analysis). Use the independent dataset GSE68465 to validate the model through a combination of 100 algorithms. Further elucidate the function, cellular localization, and association with smoking risk of core genes through enrichment analysis, immune infiltration assessment, single-cell transcriptome analysis, and network toxicology.A total of 276 shared autophagy‑related differentially expressed genes were identified. Using machine learning, five core genes-ENG, CDH1, KLF4, IL6, and MMP9-were selected. In the independent validation cohort, the prognostic model based on these genes demonstrated strong diagnostic performance (AUC > 0.9). Enrichment analysis revealed that the core genes were significantly enriched in pathways such as cellular senescence, autophagy, and FoxO signaling. Immune infiltration analysis showed that M1 macrophages and naïve B cells were significantly upregulated in tumor tissues, whereas resting dendritic cells were downregulated. Single‑cell analysis identified specific expression of genes including CDH1 and TGFB1 in type II alveolar cells and immune cells. Network toxicology and molecular docking confirmed that nicotine, a major component of cigarette smoke, exhibits high‑affinity binding to the core genes CDH1, HIF1A, KLF4, TGFB1, and BCL2.This study successfully identified and validated a robust prognostic feature consisting of five autophagy-related genes. These genes play a key role in the development of lung adenocarcinoma by regulating the tumor immune microenvironment, cell communication, and responding to external risk factors, providing new potential targets for prognosis prediction and targeted therapy.
Dystonia frequently coexists with Parkinson's disease (PD), yet the extent of genetic overlap remains insufficiently explored. The aim was to examine whether rare variants in dystonia-related genes are associated with PD or early-onset PD (EOPD). We curated 44 dystonia-related genes using the Online Mendelian Inheritance in Man (OMIM) and the Movement Disorder Society report on hereditary dystonia. Whole-genome sequencing data from 5315 PD patients, including 300 EOPD patients, and 36,902 controls across the Accelerating Medicines Partnership-Parkinson's Disease (AMP-PD) and UK Biobank European cohorts were analyzed. Rare-variant burden analysis was performed using the optimized sequence kernel association test (SKAT-O) and MetaSKAT. In the analyses of all PD patients, no association survived multiple-testing correction. Conversely, exploratory EOPD analyses identified five significant genes (ATP5MC3, DNAJC12, KMT2B, TBC1D24, TMEM151A); however, these signals were driven by small numbers of variants and were not robust to leave-one-variant-out analyses. Rare variants in dystonia-related genes are not major contributors to overall PD risk. Signals observed in the EOPD subset require replication in larger cohorts. © 2026 The Author(s). Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society.
Against the backdrop of accelerating population aging, the risk of neurodegenerative diseases (NDDs) has risen significantly. While brain structure plays a critical role in NDDs, the interplay between them remains unclear. This study employed Mendelian randomization (MR) to investigate potential causal relationships between brain structure, region-specific gene expression, and four NDDs - Alzheimer's disease (AD), Parkinson's disease (PD), amyotrophic lateral sclerosis (ALS), and multiple sclerosis (MS) - providing new directions and genetically informed hypotheses for disease research. MR analyses were conducted using inverse-variance weighted (IVW), MR-Egger, weighted median, weighted mode, and Wald ratio methods. Summary-data-based MR (SMR) was applied to identify brain genes influencing NDDs. We calculated F-statistics, 95% confidence intervals (CIs), odds ratios, and p-values. Sensitivity analyses included the heterogeneity I2 statistic, Cochran's Q test, Egger intercept test, MR-PRESSO, and leave-one-out validation. Data from 512 unsupervised deep-learning imaging phenotypes (UDIPs) were analyzed. Thirty-four UDIPs showed associations consistent with a potential causal role in AD, 56 in PD, 22 in ALS, and 92 in MS. After false discovery rate (FDR) correction, 4 remained significant for AD and PD, 3 for ALS, and 28 for MS (p < 0.05). Brain regions (excluding the cervical spinal cord C-1) exhibited shared causal genetic features across all four NDDs, primarily involving HLA-class genes. This study provides genetic evidence suggestive of potential causal associations between UDIPs, brain gene expression, and NDDs. These findings offer genetically predicted evidence that may generate hypotheses and inform future mechanistic research into NDD pathogenesis.
The expansion of invasive European wild boar (Sus scrofa scrofa) populations in Brazil and the increasing commercialization of this species raise concerns about their role as reservoirs of zoonotic and antimicrobial-resistant bacteria. This study aimed to determine the prevalence, antimicrobial resistance profiles, and detection of virulence and resistance genes in Escherichia coli and Salmonella spp. isolated from captive wild boars. A total of 100 rectal swab samples were collected from animals raised on commercial farms in Goiás State, Brazil. One Salmonella isolate (1%) was detected and identified as serotype O:6,8, showing phenotypic resistance to ampicillin, amoxicillin, and sulfonamides, but no virulence or resistance genes were detected. E. coli was isolated from 56% of samples, with 98.2% of isolates classified as multidrug-resistant and all presenting antimicrobial resistance index values above 0.2. High resistance rates were observed for sulfonamides (96.8%), tetracycline (92.1%), amoxicillin (87.3%), ampicillin (85.7%), doxycycline (81.0%), whereas most isolates remained susceptible to ceftriaxone. Virulence genes were detected in a subset of isolates, including tsh (29.8%), papC (12.3%), and iss (7.0%), with some isolates presenting gene combinations associated with increased pathogenic potential. The eae gene was not detected, and no β-hemolytic activity was observed. These findings indicate a low occurrence of Salmonella but a high prevalence of multidrug-resistant and potentially pathogenic E. coli in captive wild boars, highlighting their potential role as reservoirs of antimicrobial resistance within a One Health context.
Respiratory mucosal (RM) immunity is a highly specialized and dynamic network that safeguards the airways from inhaled pathogens while preserving tissue homeostasis. Acting as the body's first line of defense, RM immunity integrates immune tolerance, barrier protection, immune surveillance, tissue repair, and the establishment of long-term immunological memory. Dysregulation of these processes contributes to a broad spectrum of diseases, including acute viral and bacterial infections, fungal colonization, and chronic inflammatory disorders, highlighting the urgent need for effective preventive strategies targeting the respiratory mucosa. The unprecedented global impact of coronavirus disease 2019 (COVID-19) has further highlighted this need and catalyzed rapid advances in vaccines capable of inducing both local and systemic immunity at the respiratory portal of entry, alongside progress in inhalable antibody therapies. This review first summarizes the principal biological functions of the respiratory mucosa and the underlying mechanisms, followed by an overview of immune dysregulation associated with respiratory diseases. It then highlights recent advances in mucosal intervention strategies, with a particular focus on the development of RM vaccine platforms-including live-attenuated, inactivated, viral vector, protein subunit, and mRNA vaccines. It further discusses next-generation RM vaccine strategies emphasizing upper airway immunity, broadened antigen design and intranasal safety. Together, these advances provide a conceptual and translational framework for advancing RM-based interventions against respiratory pathogens.
Autophagy is an evolutionarily conserved process in eukaryotic cells that delivers intracellular components to lysosomes for degradation and recycling. Increasing evidence has elucidated the regulation of autophagy, highlighting its involvement in cellular metabolism, survival, and development, as well as its association with diverse physiological and pathological processes. There are often mutations in autophagy-regulating genes or abnormal autophagy function in multiple diseases, such as cancer, immune system diseases, and neurodegenerative diseases. Additionally, the regulation of the autophagy process shows potential therapeutic effects for these diseases. Several small molecules have been developed as autophagy regulators based on traditional drug discovery strategies, such as high-throughput screening, structure-activity relationship (SAR) optimization, and computer-aided drug design. Mechanistically, these compounds that bind specifically to such autophagy-related proteins or kinases can act as agonists or antagonists, with downstream consequences on the autophagy process. Several pharmacologic agents that regulate the autophagy process with extraordinary potential in disease treatment have come into clinical use. But most of these molecules still suffer from many obstacles, including low efficacy, low selectivity, poor pharmacokinetic profile, drug resistance, and toxicity. Moreover, some inappropriate and undruggable autophagy-related targets, as well as ubiquitous protein aggregates in neurodegenerative diseases, also bring serious challenges to the identification of small-molecule drugs. In this review, we briefly introduce autophagy and summarize its function and regulatory role in various diseases and disorders, and discuss the possibility of autophagy-targeted therapy in these diseases. The present review highlights current developments regarding the fundamental molecular mechanisms and signaling cascades of autophagy, while also addressing strategies for small-molecule-based therapeutic intervention.
Glycogen storage diseases (GSDs) are a group of inherited metabolic disorders characterized by impaired glycogen metabolism, primarily affecting the liver and muscles. A retrospective cross-sectional study was conducted. Medical records of 72 children afflicted with GSDs were reviewed for clinical features, family history, and consanguinity. Sequencing was performed using DNA samples from patients and their family members. Of the 72 patients, the median age at presentation was 5.0 months (interquartile range: 1.8-9.0). Common features included abdominal distension (97.2%), hepatomegaly (94.4%), doll-like facies (54.2%), and failure to thrive (53%). Other findings included acidotic breathing, developmental delay, vomiting, convulsions, and positive family history. All cases involved consanguinity. Thirty-eight pathogenic variants were identified across nine GSD-associated genes. Abdominal distension, hepatomegaly, and failure to thrive are key clinical indicators of GSDs. Genetic testing improves diagnostic accuracy and classification, and our findings expand the mutational spectrum of GSDs in Pakistan.
Vector-borne diseases in dogs are an emerging problem worldwide due to their frequency, morbidity, and zoonotic relevance. Since there are no previous studies determining the frequency of Ehrlichia canis and Rickettsia rickettsii infection in three neighborhoods of the city of Chihuahua, Mexico, using molecular detection techniques, the objective of the present study was to detect, by nested polymerase chain reaction (PCR), a fragment of the gp36 gene of E. canis and the ompA gene of R. rickettsii in tick-infested dogs captured at the canine control center of the city of Chihuahua, and to phylogenetically analyze the genotypes present. Blood samples were collected from 123 tick-infested dogs. DNA was extracted from peripheral blood leukocytes and used in nested PCR protocols. The results showed a positivity frequency of 16.2% (20/123) for E. canis and 3.2% (4/123) for R. rickettsii. Six sequenced samples corresponded to E. canis and four to R. rickettsii. Phylogenetic analysis showed a close relationship with sequences previously described in the United States. This is the first molecular identification confirming E. canis and R. rickettsii infection in tick-infested dogs from some neighborhoods of the Chihuahua city, Mexico.
The diagnosis of Parkinson's disease (PD) is currently clinical. While CSF-based α-synuclein Real-time quaking-induced conversion (RT-QuIC) assays have shown promising diagnostic performance in sporadic PD, accessible blood-based biomarkers for early diagnosis, prognosis, and disease monitoring remain limited. Evidence suggests that microRNAs in Extracellular vesicles (EV) are stable in circulation and may reflect disease-associated dysregulation. To identify a panel of dysregulated EV-microRNAs that are linked to PD pathogenesis and to validate them in plasma EVs. Dysregulated miRNAs in PD were identified from GEO datasets and from published high-throughput next-generation sequencing (NGS) data on plasma EV. Based on recurrence and biological relevance, five miRNAs were selected for validation. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis were conducted using Funrich, Enrichr, and Database for Annotation, Visualization and Integrated Discovery (DAVID), and further target gene analysis for hub genes was performed using Cytoscape. qRT-PCR was used for the validation of selected miRNAs. Comparative analysis of miRNAs in PD revealed 89 unique miRNAs. Integrated target prediction yielded 36 genes, among which the top 10 hub genes were identified using the protein-protein interaction network. KEGG and GO enrichment analyses indicate that the predicted target genes were significantly associated with cell-cell adhesion, endoplasmic reticulum protein processing, apoptosis, cellular senescence, and key pathways such as p53, MAPK, and FOXO signaling. RT-PCR revealed significant increase in hsa-let-7e-5p, hsa-miR-19b-3p, hsa-miR-24-3p and hsa-miR-331-5p in PD. The EV miRNAs, specifically, hsa-let-7e-5p, hsa-miR-19b-3p, hsa-miR-24-3p, and hsa-miR-331-5p are promising candidates for PD diagnosis as they are associated with regulatory pathways involved in PD pathogenesis.
Myasthenia Gravis (MG) is an autoimmune disease that damages the neuromuscular junction (NMJ), reduces the transmission of nerve impulses to muscles, and thus causes fluctuating muscle weakness and fatigue. The main types of MG are autoantibodies that target necessary components of the postsynaptic membrane, such as acetylcholine receptors (AChRs) and muscle-specific kinase (MuSK). The above immune-mediated alterations disrupt synaptic transmission and reduce muscle contraction. Study the molecular and cellular mechanisms of MG to find genes that regulate the immune system, cause inflammation, or affect NMJ homeostasis and may serve as biomarkers. These biomarkers can provide more information on the course of a disease and help to customise diagnosis and treatment according to this information. The transcriptomic data in this study were obtained from the Gene Expression Omnibus (GEO) database under accession number GSE85452 (GPL10558), which contains peripheral blood gene expression profiles of MG patients and healthy controls. Differential Expression Analysis was conducted to find genes in *M. fitumendi* related to MG. Preprocess and normalise the raw data before the following comparisons. Mendelian Randomisation (MR) was employed to investigate whether the candidate genes causally affected MG risk. PTGS2 was found to be a protective factor (OR < 1) and selected for further study. Gene set enrichment analysis (GSEA) was then carried out to identify related pathways, and single-sample gene set enrichment analysis (ssGSEA) was used to explore associations with the immune system. Single-cell RNA sequencing (scRNA-seq) was performed to find out which cells expressed PTGS2, how the proportions of different cell types in the MG microenvironment were changed, and what inter-cellular communication occurred. A network-based virtual PTGS2 overexpression analysis was also carried out in MG cells with scTenifoldNet. Single-cell gene regulatory networks were built from the raw count data and denoised by tensor decomposition. PTGS2 regulatory activity increased due to a doubling of the weight of the positive regulatory edge. Genes with an adjusted P-value <0.05 were regarded as significantly altered and subjected to KEGG and Gene Ontology enrichment analysis. Using a sensitive threshold of |log₂FC| > 0.38 for the initial screening of the MG transcriptome, a particular set of differentially expressed genes in patients was identified compared with healthy individuals. Mendelian Randomisation analysis also showed that PTGS2 is associated with a reduced risk of MG and has a negative causal association with the disease. Functional enrichment analysis linked PTGS2-associated molecular signatures to immune and inflammatory pathways. Immune infiltration analysis showed variations in the proportion of immune cells in MG, and PTGS2 expression was significantly correlated with several subsets of immune cells. Gene-disease association mapping links PTGS2 to multiple immune-related disorders. Single-cell RNA sequencing also showed cell-type-specific expression and different distributions of PTGS2 in MG patients and healthy controls. Overexpression of virtual PTGS2 mainly modified genes and pathways in the myeloid cell, such as IL-17 signalling, chemotaxis and neutrophil migration. Therefore, PTGS2 may be involved in the regulation of inflammatory myeloid responses in MG. Transcriptome and gene analysis identified PTGS2 as a protective gene for myasthenia gravis. PTGS2 is linked to immune-inflammatory signals, and single-cell data have identified specific cell types in the MG immune microenvironment that express it. Network-based virtual PTGS2 overexpression mainly altered myeloid-associated genes and pathways of IL-17 signalling, chemotaxis and neutrophil migration. PTGS2 may be a biomarker and a possible therapeutic target for MG.
Differential growth between the left (LV) and right ventricles (RV) is a cornerstone of normal heart morphogenesis after birth, leading to the relatively larger and dominant LV over RV in the adult heart regarding size and function. Yet, little is known about the factors that regulate this chamber-specific growth. We used both loss-and gain-of-function mouse models, achieved through genetic or pharmacological manipulation of IRE1α or Xbp1 in cardiomyocytes. We also used primary cultured neonatal cardiomyocytes to explore the roles of IRE1α, spliced Xbp1 (sXbp1: activated form), and newly identified sXbp1 downstream targets. In addition, we generated heart-specific mosaic mutant mouse models using CRISPR/Cas9/AAV9-based somatic mutagenesis to elucidate the roles of sXbp1 downstream targets in cardiomyocytes. Pharmacological inactivation of IRE1α and genetic depletion of Xbp1 resulted in a smaller LV size, due to decreased cardiomyocyte proliferation and hypertrophic growth, as well as increased cardiomyocyte death. These effects were not observed in the RV. Cardiomyocyte-specific induction of IRE1α or sXbp1 led to increased ventricular size in both ventricles, through enhanced cardiomyocyte proliferation and hypertrophic growth in both LV and RV, and reduced apoptosis in the RV. We identified two ER resident transmembrane proteins, Vimp and Rpn2, as direct binding partners of sXbp1 in targeted gene regulation at the chromatin level. CRISPR/Cas9/AAV9-based somatic mutagenesis mouse models for Vimp and Rpn2 revealed that both genes regulate cardiomyocyte proliferation, hypertrophic growth, and death. We also observed accumulated misfolded proteins in these two mutant hearts. Conclusions We demonstrate that the IRE1α-Xbp1-Vimp/Rpn2 axis regulates differential ventricular size between LV and RV during postnatal development by orchestrating cardiomyocyte proliferation, hypertrophic growth, and death through regulating protein homeostasis. What Is New: IRE1α-Xbp1 axis is dominantly activated in the LV cardiomyocyte during the postnatal period in mouse heart.IRE1α-Xbp1 mediated ER stress signaling increases cardiomyocyte proliferation and hypertrophic growth and decreases apoptosis in the postnatal period.Activated Xbp1 directly regulates LV-specific cardiomyocyte protein homeostasis via interaction with ER membrane targeted Vimp and Rpn2.What Are the Clinical Implications?: Differential heart growth patterns between the LV and RV are critical for normal morphogenesis and function of each ventricle.Control of protein homeostasis by modulating ER stress signaling could be a potential therapeutic approach for single-chamber heart diseases.
Esophageal squamous cell carcinoma (ESCC) is a highly aggressive malignancy with poor prognosis and limited therapeutic options. Ferroptosis, a regulated form of cell death characterized by iron-dependent lipid peroxidation, plays a crucial role in tumor progression and immune regulation. We integrated single-cell RNA sequencing (scRNA-seq) and bulk transcriptomic data to identify ferroptosis-active cellular subpopulations within the ESCC tumor microenvironment. A ferroptosis-related prognostic model was constructed using LASSO-Cox regression and validated across independent cohorts from TCGA and GEO. Associations with immune infiltration, tumor mutation burden, therapeutic response, and drug sensitivity were explored. Furthermore, functional experiments were conducted in vitro using the ESCC cell lines, and the four prognostic core genes were revalidated using an independent single-cell dataset, which was also fully confirmed in clinical ESCC tissue samples. In addition, Western blot analysis was performed to examine the expression levels of ferroptosis-related proteins following CDCA3 knockdown, and to further investigate the impact of CDCA3 depletion on the cellular response to the ferroptosis inducer RSL3. Four ferroptosis-related genes (CBS, CDCA3, GALNT14, and IDO1) were identified used to construct a robust risk model, effectively stratifying patients into high- and low-risk groups with significant differences in survival, immune infiltration, and predicted treatment response. In vitro experiments confirmed that CDCA3 knockdown significantly inhibited the proliferation and migration of ESCC cells and induced ferroptosis. GSE188900 single-cell sequencing data further confirmed that the aforementioned genes were significantly upregulated at single-cell resolution in tumor cells, with consistent validation in clinical ESCC tissue samples, Moreover,experimental results showed that knockdown of CDCA3 lead to the downregulation of ferroptosis inhibitor-related genes and upregulation of ferroptosis-promoting genes, thereby enhancing the sensitivity to RSL3-induced ferroptosis. Our study presents a single-cell-resolved ferroptosis gene signature with strong prognostic and therapeutic implications for ESCC. The signature was validated in clinical tissue samples, and this model lays the foundation for ferroptosis-targeted therapeutic strategies.
Lead (Pb) is associated with Alzheimer's disease (AD); however, the relationships between Pb and AD hippocampal transcription remains unclear. We evaluated overlap between Pb-response signatures and cell-type-independent AD transcriptomic signatures. Three toxicology studies (two neuronal cell lines, one mouse hippocampus) provided Pb-response genes. Five human postmortem hippocampal AD case-control transcriptional datasets (n=90 AD, n=106 normal cognition) were cell type deconvoluted and tested with beta regression. Differential gene expression, adjusted for age, sex, and estimated cell-types, were meta-analyzed. Overlapping Pb and AD genes and biological pathways were identified (p adj <0.05). Consistent Pb response was observed at 25 genes ( INPP5F , KIF20B , KIFC1 ) and 47 pathways (ensheathment of neurons, glial cell differentiation, regulation of nervous system processes). Relative to controls, AD samples had fewer neurons (-2.46%), greater microglia (0.42%), astrocytes (0.31%), oligodendrocytes (0.46%), and endothelial cells (0.95%), and 1,455 differentially expressed genes, which were enriched for cellular energy production and metabolism pathways. Six genes ( EHD3 , LAP3 , NRXN3 , PPP1R16B , RPL29 , THRA) and four pathways (synaptic vesicle maturation, vesicle docking) overlapped between Pb and AD. We identified overlapping Pb and AD transcriptomic signatures and pathways, providing molecular context for epidemiologic associations.
Allogeneic hematopoietic stem cell transplantation (allo-HSCT) is a critical treatment for pediatric acute myeloid leukemia (AML); however, relapse after transplantation remains a major challenge. This study aimed to evaluate the prognostic value of pre-transplant measurable residual disease (MRD) detected by multiparameter flow cytometry (MFC) and high-risk (HR) fusion genes on survival after transplantation. This single-center retrospective study included 80 newly diagnosed pediatric AML patients who underwent allo-HSCT during their first complete remission between October 2019 and October 2025. All patients were treated according to the C-HUANAN-AML 15 protocol prior to transplantation, with risk stratification and treatment decisions based on European LeukemiaNet criteria and serial MFC-MRD assessments. Cox regression models were employed for statistical analysis. With a median follow-up of 34.5 months, the 3-year disease-free survival (DFS) and overall survival (OS) rates were 85.5% ± 4.2% and 86.8% ± 4.1%, respectively. Univariate analysis identified several risk factors for inferior survival, but multivariate analysis confirmed pre-transplant MFC-MRD positivity as an independent adverse prognostic factor for both 3-year DFS and OS (DFS: HR = 14.304, 95%CI: 1.892-108.155, P = 0.010; OS: HR = 15.847, 95%CI: 2.036-123.328, P = 0.008). Among relapsed patients, the majority harbored HR fusion genes. Given the limited number of cases with specific HR fusion genes (e.g., NUP98 rearrangements, n = 4; FUS::ERG, n = 2), these subgroup findings are exploratory and require validation in larger cohorts. Pre-transplant MFC-MRD positivity is an independent adverse prognostic marker for survival in pediatric AML patients following allo-HSCT. Patients harboring HR fusion genes such as NUP98 rearrangements or FUS::ERG fusions may remain at risk of relapse even after successful transplantation, although this observation is based on a limited number of cases. These findings emphasize the importance of achieving deep remission to reduce tumor burden before transplantation and provide a rationale for intensified post-transplant management strategies, including maintenance therapy, for this HR population.
Traumatic brain injury (TBI) is a debilitating condition caused by one or more concussive insults to the head and is frequently observed in combat Veterans deployed in support of Operation Enduring Freedom (OEF) or Operation Iraqi Freedom (OIF). TBI is associated with impairment of cognitive function and development of post-traumatic stress disorder (PTSD), a psychiatric disorder. Currently, there are no validated biomarkers that can determine the detection of PTSD/TBI in circulation. In this regard, microRNAs (miRNAs) have emerged as specific and sensitive biomarkers in several central nervous system diseases and TBI. The current study evaluated the role of miRNA in circulation TBI and PTSD of OEF and OEF Veterans. While analyzed the expression profile of miRNAs in peripheral blood mononuclear cells (PBMCs) from an OEF/OIF veteran study cohort using a miRNA array and identified several miRNAs in PBMCs of TBI/PTSD compared with control subjects. We confirmed eight selective dysregulated miRNAs by independent quantitative real-time polymerase chain reaction (qRT-PCR) assays. Using bioinformatic tools, we further analyzed target gene function and enrichment analyses using Kyoto Encyclopedia of Genes and Genomes and gene ontology platforms. Based on unsupervised clustering analysis, we validated two miRNAs, miR-142-5p and miR-155-5p with their target genes like BDNF, Nrg1, and NR3C2 by qRT-PCR analyses. Our data suggested a potential link between these two miRNAs and their target genes.
The functional plasticity of tumor-associated macrophages (TAMs) is a critical determinant of the immunosuppressive microenvironment in cervical cancer, yet its integration into actionable prognostic frameworks remains limited. This study aimed to establish a TAM polarization-centered model and elucidate the mechanisms of underlying tumor-immune crosstalk. Bulk transcriptomics from The Cancer Genome Atlas (TCGA) were integrated with single-cell RNA sequencing (scRNA-seq) data (GSE208653). By combining weighted gene co-expression network analysis (WGCNA) with a multi-algorithm machine learning framework, a prognostic signature was constructed and independently validated in the Gene Expression Omnibus (GEO) GSE52903 cohort. Single-cell analysis resolved the cellular origins of signature genes, prioritizing tumor-enriched genes for validation. Protein-level expression was verified via immunohistochemistry (IHC) in a paired clinical cohort (n=39). Functional validation of the core gene was performed in vitro using cervical cancer cell lines co-cultured with THP-1-derived macrophages. Polarization was assessed via reverse transcription-quantitative polymerase chain reaction (RT-qPCR), Western blot (WB), enzyme-linked immunosorbent assay (ELISA), flow cytometry, and multiplex immunofluorescence (mIF). A robust five-gene prognostic signature (TP73, TFRC, SHC1, SCD, and PFKFB3) was developed, effectively stratifying patient survival. High risk scores correlated with a suppressed antitumor immune landscape and diminished predicted chemosensitivity to agents such as cisplatin. Single-cell analysis and IHC confirmed transferrin receptor (TFRC) as a tumor-intrinsic factor that is progressively upregulated during cervical carcinogenesis and enhances pro-M2 signaling. In vitro co-culture assays demonstrated that tumor-derived TFRC actively orchestrates an immunosuppressive M2-like macrophage niche, driving phenotypic shifts and pro-tumorigenic cytokine secretion, characterized by elevated interleukin-10 (IL-10) and reduced TNF-α. RT-qPCR analysis of 40 clinical specimens further confirmed a significant positive correlation between TFRC and the M2 marker Arg-1 at the mRNA level (r = 0.4961, P = 0.0011). This study establishes a cross-scale, biologically interpretable prognostic model linking macrophage plasticity to clinical outcomes. We identify TFRC as a pivotal metabolic-immune node through which tumor-intrinsic iron metabolism orchestrates an immunosuppressive niche, providing a foundation for novel therapeutic strategies in cervical cancer.
Buprenorphine is widely prescribed for opioid use disorder (OUD). In 2022, the U.S. FDA issued a safety warning on dental diseases associated with buprenorphine. While reports implicate increased caries risk, the microbial mechanisms remain unclear. To evaluate whether buprenorphine directly modulates Streptococcus mutans (S. mutans) virulence traits relevant to cariogenesis. S. mutans UA159 were exposed to buprenorphine. Planktonic growth, acidogenicity, acid tolerance, aggregation, and carbohydrate utilization were assessed. Biofilm biomass and extracellular polymeric substance (EPS) production were quantified in hydroxyapatite disc-based monospecies and saliva-derived microcosm models. Biofilm architecture was evaluated using fluorescence in situ hybridization (FISH). The expression of competence- and biofilm-associated genes (comC, comX, gcrR, gtfB, and gtfC) was measured by RT-qPCR. Buprenorphine did not affect planktonic growth, acid production, or carbohydrate metabolism. However, it increased biofilm biomass and EPS production. FISH imaging revealed denser matrix-rich biofilms with closer spatial integration of S. mutans. Gene expression showed upregulation of comC, comX, gcrR, gtfB, and gtfC, indicating enhanced quorum sensing, stress adaptation, and matrix synthesis. Buprenorphine promoted a biofilm-specific virulence program in S. mutans, fostering thicker, EPS-rich biofilms without altering planktonic physiology. These findings provide a mechanistic rationale for buprenorphine's association with caries risk. Buprenorphine triggered biofilm-specific virulence responses in Streptococcus mutans, increasing biofilm mass and extracellular matrix production without affecting growth or metabolism in planktonic culture. These mechanistic findings support clinical observations of severe caries in patients receiving buprenorphine therapy and underscore the need for proactive oral-health prevention in this population, as highlighted by the 2022 U.S. Food and Drug Administration safety warning.
Time-course single-cell RNA sequencing (scRNA-seq) data collected across ordered stages provide population-level snapshots of differentiation, disease progression, and aging. Supervised pseudotime methods use observed stage labels to reconstruct continuous progression but generally do not identify marker genes associated with changes from one stage to the next. Unsupervised pseudotime-based marker selection methods infer latent trajectories directly from expression data and identify trajectory-associated genes, but do not explicitly link these associations to the observed stages. We propose FusedFCR, a regularized forward continuation-ratio model that represents cellular progression through a sequence of conditional transitions across ordered stages. FusedFCR combines a lasso penalty for gene selection with a fusion penalty that encourages similar effects across adjacent transitions while allowing transient and direction-changing associations. The resulting transition-specific coefficients support interpretable gene selection and a continuous pseudotime-like projection anchored to the observed developmental stages. In simulations, FusedFCR accurately recovered gene-effect trajectories and improved predictive performance relative to alternative methods. Applied to mouse pancreatic beta-cell differentiation across seven time points and human extravillous trophoblast differentiation across four time points, FusedFCR identified biologically interpretable genes associated with distinct developmental transitions. Gene set enrichment analysis further revealed stage-specific pathway activity consistent with known developmental biology, while held-out stage-classification accuracy was competitive or superior across both datasets. Together, these results show that FusedFCR complements pseudotemporal ordering by identifying which molecular programs change and when those changes emerge along the developmental trajectory. An accompanying R package is available on GitHub.
Disruptions in purine metabolism contribute to a range of human diseases, from rare genetic disorders such as Lesch-Nyhan syndrome and xanthinuria to common conditions including gout and cancer. To better understand the metabolic networks that regulate purine homeostasis, we developed a Caenorhabditis elegans model of xanthine dehydrogenase ( xdh-1 ) deficiency. Remarkably, xdh-1 mutant animals form rare xanthine stones, recapitulating a hallmark of human xanthinuria. To uncover genetic regulators of purine homeostasis, we performed a forward genetic screen for mutations that exacerbate xanthine stone formation in xdh-1 mutants. This approach identified multiple loss-of-function alleles in a previously uncharacterized gene, which we named gda-1 . We show that gda-1 encodes an intestinal guanine deaminase that mediates a key enzymatic step in purine catabolism. The C. elegans genome also encodes a paralog, gda-2 , which shares guanine deaminase activity but is expressed in distinct tissues. While gda-2 can compensate for gda-1 loss in guanine metabolism, the two genes exhibit non-redundant roles in regulating xanthine accumulation and stone formation. Interestingly, our evolutionary analyses suggest that gda-2 was acquired by nematodes via horizontal gene transfer from bacteria. These findings reveal a spatially regulated purine catabolism pathway in C. elegans and suggest that acquisition of bacterial genes has shaped a core nematode metabolic network.
Lung adenocarcinoma is the most common subtype of lung cancer and a significant contributor to cancer mortality globally. This has driven the development of targeted therapies, particularly those aimed at genetic alterations in certain genes, such as EGFR and ALK. ERBB2 (HER2) has also emerged as a potential oncogenic driver and therapeutic target in lung adenocarcinoma. Notably, ERBB2 is in close proximity on chromosome 17 to GRB7 and MIEN1, which are potential contributors to invasion and metastasis. Using TCGA-LUAD (The Cancer Genome Atlas Lung Adenocarcinoma) and CPTAC-3 (Phase III of the Clinical Proteomic Tumor Analysis Consortium) lung adenocarcinoma datasets, copy number variations (CNVs) for GRB7, ERBB2, and MIEN1 and their associations with various survival parameters were obtained. Results indicated that increased copy number (CN) of MIEN1 was significantly associated with worse disease-free survival (DFS) in both TCGA-LUAD and CPTAC-3 lung adenocarcinoma datasets and was significantly associated with worse progression-free survival (PFS) in the TCGA-LUAD dataset. There is also evidence showing a similar relationship in cervical cancer, which also has established links to ERBB2. CNV analyses in the TCGA-CESC and CGCI-HTMCP-CC (Cancer Genome Characterization Initiative-HIV+ Tumor Molecular Characterization Project-Cervical Cancer) cervical cancer datasets revealed that only increased CN of MIEN1 was statistically significantly associated with worse overall survival (OS) in both datasets. These CNV analyses suggest that MIEN1 should be further investigated as a potential contributor to oncogenesis.