[Doctoral dissertations on nursing. In memory of Erna von Abendroth].
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Enhancer RNA (eRNA) has emerged as a key player in cancer biology, influencing various aspects of tumor development and progression. In this study, we investigated the role of eRNAs in kidney renal clear cell carcinoma (KIRC), the most common subtype of renal cell carcinoma. Leveraging high-throughput sequencing data and bioinformatics analysis, we identified differentially expressed eRNAs in KIRC and constructed eRNA-centric regulatory networks. Our findings revealed that up-regulated eRNAs in KIRC potentially regulate immune response and hypoxia pathways, while down-regulated eRNAs may impact ion transport, cell cycle, and metabolism. Furthermore, we developed a diagnostic prediction model based on eRNA expression profiles, demonstrating its effectiveness in KIRC diagnosis. Finally, we elucidated the regulatory mechanism of an eRNA (ENSR00000305834) on the expression of SLC15A2, a potential prognostic biomarker in KIRC, through bioinformatics analysis and in vitro validation experiments. In summary, Our study highlights the clinical significance of eRNAs in KIRC and underscores their potential as therapeutic targets.
Cereal genomes have undergone repeated polyploidization and transposable element (TE) proliferation, collectively generating complex regulatory landscapes. However, the evolutionary trajectories and functional implications of these landscapes remain largely unexplored. Using chromatin-bound RNA sequencing across seven cereal species, we systematically mapped 45,952 regulatory element transcripts (RETs), including 32,867 distal RETs corresponding to enhancer RNAs (eRNAs). Our analysis revealed that 56% of lineage-specific eRNAs originated from TE expansions, indicating that TEs serve as major reservoirs of species-specific regulatory innovation in cereals. Notably, we identified remarkable conservation in defense-related functions, root-specific expression, and TE-derived origins of eRNAs across both ancient and recent evolutionary layers of Triticeae, suggesting recurrent recruitment of TE-derived, root-associated regulatory elements throughout Triticeae evolution. Furthermore, we found that young eRNA pairs in hexaploid wheat with high sequence similarity, many originating from RLG_famc8.3 and DTC_famc4.3, exhibited pronounced root specificity and coordinated expression, suggesting targeted amplification and refinement of successful ancestral regulatory strategies established after Triticeae divergence. To facilitate community access, we developed Cereal-eRNAdb (http://bioinfo.cemps.ac.cn/Cereal-eRNAdb/), a comprehensive database integrating 69,426 eRNAs with functional annotations across 296 samples. Our findings suggest that TE-mediated innovation of root-specific eRNAs may contribute to Triticeae adaptation and provide a foundational resource for exploiting regulatory variation in cereal crop breeding.
Emerging evidence suggests that MYC binds RNAs, but its functional consequences remain unclear. Here, we integrate multiomics data and reveal that MYC broadly binds enhancer RNAs (eRNAs), which exhibit high cancer- and tissue-specific expression in cancer cell lines and patient tumors. Moreover, we developed a computational pipeline to identify potential cis-regulatory MYC-eRNA target genes, with most predicted eRNA-target pairs supported by RNA polymerase II-mediated chromatin interaction data. Among these, we functionally characterized MERG1 as an oncogenic eRNA that promotes breast cancer tumorigenesis. Mechanistically, MERG1 interacts with MYC to enhance its occupancy at the GREB1 promoter, driving chromatin remodeling and epigenetic activation. This process specifically amplifies GREB1 expression and promotes tumor progression. Last, nanoparticle-mediated delivery of antisense oligonucleotides targeting MERG1 suppresses MYC-mediated breast cancer growth. These results advance our understanding of the enhancer-driven regulation of gene expression and tumorigenesis and provide insights into the regulatory landscape of MYC in cancer.
Highly pathogenic avian influenza (HPAI) viruses pose an increasing threat to wildlife, livestock and human health, underscoring the need for scalable and early-warning surveillance systems. Environmental RNA (eRNA) monitoring offers a non-invasive, cost-effective alternative to traditional host-based sampling by detecting viral genetic material shed into the environment. Despite its utility, the relative performance of different environmental sampling approaches for avian influenza virus (AIV) detection remains poorly resolved. Here, we conducted a longitudinal study with monthly sampling over approximately one year across two urban waterfowl ponds in Aotearoa New Zealand to evaluate four eRNA sampling strategies - fresh faeces, sediment, active-filtered water and passive-filtered water - for their ability to detect AIV. Using a combination of metagenomic sequencing and RT-qPCR, we show that all sample types can detect AIV, although detections were highly inconsistent across sampling methods, locations and time points. While metagenomic sequencing provided valuable genomic data, including subtype identification and phylogenetic context, RT-qPCR exhibited greater sensitivity, with active-filtered water yielding the highest detection rates, and is currently the more cost-effective approach for large-scale surveillance. Notably, AIV detections were asynchronous among sample types and frequently lacked temporal concordance, suggesting that environmental heterogeneity, RNA persistence, and methodological detection limits strongly influence surveillance outcomes. Despite these inconsistencies, phylogenetic analyses revealed that detected viruses belong to established Australasian lineages, highlighting the ability of environmental surveillance to capture ecologically relevant viral diversity. Our findings demonstrate that while eRNA-based surveillance holds substantial promise as a complementary tool for AIV monitoring, its effectiveness is highly dependent on the environmental sampling strategies and laboratory detection methods used.
OBJECTIVES: Traditional periodontal therapy primarily focuses on bacterial biofilm control; however, recent evidence also suggests a critical role for the oral mycobiome. This study evaluated the clinical and ecological impact of a novel mouthwash formulation containing hyaluronic acid (HA), hydrogen peroxide (H2O2), and glycine on periodontal patients METHODS: This prospective, randomized split-mouth trial included 13 adult participants with periodontitis treated with HA-H2O2-glycine formula (BMG0703A) used twice a day for seven days. Subgingival plaque samples were collected from periodontal pocket and healthy control sites at baseline (T0) and one-week post-treatment (T1). Microbial and fungal communities were characterized using Next-Generation Sequencing (NGS) of the 16S rRNA and ITS2 regions. Linear Mixed Models (LMM) and Spearman correlation were used to assess taxonomic shifts and cross-kingdom relationships. RESULTS: Sequencing revealed a promising ecological shift: the bacteriome shifted from anaerobic dominance (Olsenella, Peptostreptococcus) toward a health-associated aerobic profile, with Rothia near-doubling (11.91% to 22.68%). The mycobiome underwent a "normalization" effect: Candida abundance decreased significantly (22.8% to 9.1%), while fungal Shannon diversity in pockets returned to healthy-site levels. Inter-kingdom analysis identified antagonistic relationships between expanding commensal bacteria and opportunistic fungi, suggesting that the intervention may help re-establish a protective bacterial niche. CONCLUSIONS: The HA-H2O2-glycine formulation seems to facilitate a rapid, cross-kingdom modulation of the subgingival niche. By reducing anaerobic pathogens and normalizing the mycobiome it appear to induce short-term changes, suggesting potential as adjunctive strategy in periodontal management. CLINICAL SIGNIFICANCE: The present work underlines the possible cross-Kingdom effects of a novel compound.
AIMS: The etiology of coronary artery Disease (CAD) appears different for men and women, yet insights into underlying sex-specific biological mechanisms are limited. We integrated genomic and proteomic analyses to investigate sex-specific associations of the plasma-proteome with CAD. METHODS AND RESULTS: In 40,829 UK Biobank participants (free-of-CAD, baseline-365 days thereafter; 55% women; mean age 56.9 ± 8.1 years), we examined associations between 2,922 plasma proteins and incident CAD over a median follow-up of 13.7 years (IQR 13.1-14.4) using multivariable-adjusted Cox proportional hazards models. Sex-specific analyses identified 440 female exclusive and 32 male exclusive proteins associated with incident CAD (FDR-corrected p < 0.05), revealing distinct pathway enrichments, including innate immune response in women and angiogenesis in men. Causality was assessed through combined and sex-stratified two-sample Mendelian randomization (MR) using inverse-variance-weighted analyses with genome wide association summary statistics from 422,108 men (61,969 cases) and 521,695 women (27,128 cases) (UK Biobank, FinnGen freeze 9). Integration of direct sex-protein interaction analyses with sex-combined MR identified 59 proteins with evidence for sex-specific causal effects. Four proteins demonstrated concordant directionality in sex-stratified MR analyses (n = 943,803) and multivariable regression models, namely CDKN2D, MYH9, and SKAP2 (women), and CTSH (men). To assess translational relevance, prioritized targets were further evaluated in secondary major adverse cardiovascular events among carotid endarterectomy patients (MACE; Athero-Express) and acute myocardial infarction (AMI; MISSION!) using plasma proteomics and ELISA. After further top-target identification in the context of MACE and AMI, clinical drug candidates were identified through a machine learning framework, including CTSH (men), and TNFRSF4 (both sexes). CONCLUSIONS: We identified sex-specific associations of proteins and biological pathways with incident CAD. Whereas the majority of proteins had consistent associations in both men and women, our findings suggest a degree of sex-specific pathogenesis with evidence for potential causality, opening new alleys for tailored prevention strategies and clinical cardiovascular risk management.
The X-linked TLR7 rs179008 T allele has been associated with altered antiviral immunity. Given their shared inflammatory pathways and higher pediatric mortality rates in Brazil during the pandemic, we investigated their association with multisystem inflammatory syndrome in children (MIS-C) together with Kawasaki disease (KS) following SARS-CoV-2 infection. A cross-sectional study (2021-2022) analyzed 73 hospitalized children (<13 years) with confirmed COVID-19. Genotyping for TLR7 rs179008, TLR8 (rs3764879, rs2407992), and TLR3 rs3775291 was performed via PCR and Sanger sequencing. MIS-C/KS cases were identified using CDC criteria, with severity classified by the need for ICU care. Statistical analysis included Fisher's exact test and relative risk (RR) calculations. Hemizygous boys carrying the TLR7 T allele had a 1.87-fold higher risk of MIS-C/KS (p = 0.007) and a 1.75-fold increased risk of severe or critical outcomes. The T allele frequency was 2.6× higher in MIS-C/KS cases versus other COVID-19 presentations. All fatalities occurred in boys (3/8 MIS-C cases) with one T-allele carrier. No associations were found for TLR8 or TLR3 variants. The TLR7 rs179008 T allele is a potential genetic risk factor for severe post-COVID-19 inflammatory syndromes in boys, likely due to impaired immune signaling. These findings highlight its utility as a biomarker for risk stratification in pediatric populations.