Interactive Database Research Articles

Molecular Mechanism of Finerenone in Treating Diabetic Nephropathy Based on Bioinformatics

Background: Diabetic Nephropathy (DN) is the leading cause of the end-stage renal disease (ESRD). Finerenone (with the molecular formula C21H22N4O3) is an oral non-steroidal mineralocorticoid antagonist (ns-MRA) that is both highly potent and has strong selectivity for the MR. At present, it has been used to treat DN. However, the molecular mechanism of finerenone in the treatment of diabetic nephropathy remains unclear. Objective: In this study, we employed bioinformatics approaches to investigate the molecular mechanism of finerenone as a novel therapeutic agent for the treatment of DN. Methods: We examined a number of databases, including GEO, DisGeNET, Genecards, and OMIM, to find putative genes linked to DN. We then employed the PubChem database and PharmMapper service platform to identify targets of finerenone. Further analysis was conducted using the DAVID database for enrichment analysis and the STRING database for protein-protein interaction (PPI) networks. Molecular docking (MD) was performed using AutoDockTools software, and results were visualized using PyMOL software. Results: In total, we identified 82 drug-disease targets, primarily associated with lipid and atherosclerosis, diabetic cardiomyopathy, MAPK signaling pathway, and PI3K-Akt signaling pathway. Our PPI network analysis and docking studies demonstrated good binding ability of finerenone to specific targets such as AKT1, MMP-9, IGF1, EGFR, CASP3, PPARG, ESR1, MMP-2, and KDR. Conclusion: Finerenone has the potential to reduce the progression of DN through various pathways, including lipid and atherosclerosis, diabetic cardiomyopathy, MAPK signaling pathway, and PI3KAkt signaling pathway. Moreover, it could exert anti-inflammatory and antifibrotic effects on specific targets, such as AKT1, MMP-9, IGF1, EGFR, CASP3, PPARG, ESR1, MMP-2, and KDR.

From inflammation to depression: key biomarkers for IBD-related major depressive disorder.

Inflammatory bowel disease (IBD) is a chronic, inflammatory, and autoimmune disorder, and its incidence of comorbid with major depressive disorder (MDD) is significantly higher than the general population. However, many patients lack proper recognition and necessary psychological health treatments. We aimed to identify potential biomarkers and mechanisms involved in the development of IBD comorbid with MDD (IBD-MDD). We utilized IBD and MDD-related datasets from the GEO database for differential gene expression analysis, protein-protein interaction (PPI) and pathway enrichment analysis, random forest algorithm, LASSO regression analysis, and construction of a disease prediction model. We assessed the accuracy of the model using ROC curve, explored potential mechanisms through immune infiltration analysis, and validated candidate biomarkers using peripheral blood samples from patients in our center's cohort. We identified 484 IBD-related secreted proteins and 142 key module genes associated with MDD. PPI analysis revealed two crucial modules primarily involved in inflammation and immune regulation. We identified four diagnostic genes (HGF, SPARC, ADAM12, and MMP8) from the 21 shared genes between IBD-related secreted proteins and MDD key module genes, constructed a nomogram model and confirmed its accuracy using ROC curve from an external independent dataset. Immune infiltration analysis revealed significant associations between the four diagnostic genes, and cellular immune dysregulation in MDD. Finally, we validated the expression patterns of the four diagnostic genes in our cohort. Our study discovered four candidate biomarkers for IBD-MDD, providing new insights for the diagnosis and therapeutic intervention of serum-based IBD comorbid with MDD.

Establishing an Interactive Sequence Database for Shiitake Cultivar Identification.

Shiitake mushrooms (Lentinula edodes) hold significant cultural and economic value, particularly in Asia where they are extensively cultivated. The diversification of shiitake cultivars, driven by the need to adapt to various climatic conditions and cultivation methods, has resulted in over 200 distinct cultivars. Reliable identification of these cultivars is crucial for breeding, intellectual property protection, and effective genetic resource management. Traditional morphological methods are inadequate due to their subjectivity and labor-intensive nature. This study leverages nanopore high-throughput sequencing to comprehensively analyze the rDNA regions (SSU, ITS, LSU, IGS) of 41 shiitake strains from Taiwan's Bioresource Collection and Research Center (BCRC), comprising 5 wild strains, 33 commercial strains, and 3 wild-commercial hybrids. Our results identified the IGS1 region as the most variable and suitable for cultivar differentiation. Consequently, we developed an interactive online database (https://github.com/Raingel/ShiitakeIGS1) that integrates 317 IGS1 sequences from Taiwan, Japan, and China. This platform allows users to upload their IGS1 sequences and identify similar cultivars through a user-friendly interface, enhancing the precision and efficiency of shiitake cultivar identification.

Molecular mechanisms of acquired idiopathic generalized anhidrosis: differential gene expression and potential therapeutic targets

Eccrine sweat glands are essential for thermoregulation. Acquired idiopathic generalized anhidrosis (AIGA) is a rare disorder characterized by the absence of sweating, leading to severe complications like heatstroke and skin dryness. The underlying etiology remains unknown, complicating diagnosis and treatment. This study aimed to elucidate the genetic mechanisms of AIGA by analysing the gene expression in eccrine sweat glands using the GSE193125 dataset from the NCBI Gene Expression Omnibus (GEO). This study identified differentially expressed genes (DEGs) (genes that show statistically significant differences in expression levels in AIGA), with JUN and CCN1 significantly downregulated in anhidrotic lesions of AIGA patients. Receiver operating characteristic (ROC) curve demonstrated the accuracy of these genes in classification (JUN = 0.88 and CCN1 = 0.77). Gene and protein interaction networks which are defined as networks of physical interactions between genes and proteins, constructed using GeneMANIA and STRING, revealed substantial physical interactions among them. Gene set enrichment analysis highlighted the neuroinflammatory and estrogen receptor signaling pathways are associated with this condition, suggesting hormonal regulation’s role in the anhidrosis mechanism. Key miRNAs, including hsa-let-7b-5p, hsa-miR-10b-5p, and hsa-miR-124-3p, are associated with the DEGs, underscoring the importance of post-transcriptional and transcriptional regulation. Through the Drug Gene Interaction Database (DGIdb), ciprofibrate is identified as a potential therapeutic agent targeting the JUN gene. Molecular docking confirmed a strong binding affinity between ciprofibrate and JUN, suggesting ciprofibrate could modulate JUN activity and regulate AIGA symptoms. ADMET analysis, which refers to the assessment of absorption, distribution, metabolism, excretion, and toxicity of a drug or compound, is crucial for evaluating its pharmacokinetic and safety profile. The analysis indicated that ciprofibrate has favourable pharmacokinetic properties and a relatively safe toxicity profile. This comprehensive bioinformatics approach, integrating gene expression analysis, miRNA identification, and drug interaction, provides valuable insights into anhidrosis molecular pathology and highlights ciprofibrate’s potential as a targeted therapeutic strategy. Despite limitations, including a small sample size and reliance on computational predictions, this study paves the way for further research and potential therapeutic interventions for AIGA.

Genomics-driven integrative analysis highlights immune-related plasma proteins for psychiatric disorders

BackgroundGenome-wide association studies (GWAS) have identified numerous variants associated with psychiatric disorders. However, it remains largely unknown on how GWAS risk variants contribute to psychiatric disorders. MethodsThrough integrating two largest, publicly available, independent protein quantitative trait loci datasets of plasma protein and nine large-scale GWAS summary statistics of psychiatric disorders, we first performed proteome-wide association study (PWAS) to identify psychiatric disorders-associated plasma proteins, followed by enrichment analysis to reveal the underlying biological processes and pathways. Then, we conducted Mendelian randomization (MR) and Bayesian colocalization (COLOC) analyses, with both discovery and parallel replication datasets, to further identify protein-disorder pairs with putatively causal relationships. We finally prioritized the potential drug targets using Drug Gene Interaction Database. ResultsPWAS totally identified 112 proteins, which were significantly enriched in biological processes relevant to immune regulation and response to stimulus including regulation of immune system process (adjusted P = 1.69 × 10−7) and response to external stimulus (adjusted P = 4.13 × 10−7), and viral infection related pathways, including COVID-19 (adjusted P = 2.94 × 10−2). MR and COLOC analysis further identified 26 potentially causal protein-disorder pairs in both discovery and replication analysis. Notably, eight protein-coding genes were immune-related, such as IRF3, CSK, and ACE, five among 16 druggable genes were reported to interact with drugs, including ACE, CSK, PSMB4, XPNPEP1, and MICB. ConclusionsOur findings highlighted the immunological hypothesis and identified potentially causal plasma proteins for psychiatric disorders, providing biological insights into the pathogenesis and benefit the development of preventive or therapeutic drugs for psychiatric disorders.

Characterization of a Highly Virulent Klebsiella michiganensis Strain Isolated from a Preterm Infant with Sepsis.

Klebsiella michiganensis is an opportunistic pathogen that causes an increasing number of serious infections. This study aimed to investigate the etiology of the severe clinical symptoms of sepsis in preterm infants and the characterization of K. michiganensis isolates. Whole-genome sequencing (WGS) was performed on three strains isolated from an infected preterm infant. Additionally, the genomic sequences of 534 K. michiganensis strains were obtained from the NCBI database. To gain deeper insights into these strains, we utilized the Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG), Clusters of Orthologous Groups (COG), and Pathogen Host Interactions (PHI) database annotation tools for comprehensive gene function analyses. Moreover, the multilocus sequence typing (MLST), EasyCGtree, and virulence factor database (VFDB) were employed to determine the sequence types (STs), construct phylogenetic trees, and identify potential virulence factors. Sequence analysis found that the three isolated strains had identical sequence characteristics and did not correspond to any of the known ST types. Virulence factor analysis revealed that the three strains harbored mrkABCDFHIJ, fimABCDEFGHIK, entABCDEFS, fepABCD, and capsule genes. These virulence factors are likely to play crucial roles in enhancing adhesion and metabolic capabilities, resisting phagocytosis (inducing immune cell damage), and ultimately contributing to prolonged bacteremia. The phylogenetic tree and comparative genomics of virulence factors showed the genetic and virulence factor diversity of the currently reported K. michiganensis strains. We identified a novel strain of K. michiganensis that exhibits high virulence and leads to severe septicemia phenotypes in preterm infants. Furthermore, comparative genomic analysis of previously reported K. michiganensis strains revealed the existence of three clades. This comprehensive analysis provides novel insights into the genetic relationships and virulence factor profiles of diverse strains of K. michiganensis. In future, it will be necessary to investigate the concept of the high virulence of K. michiganensis to determine the treatment method.

BOLA family genes are the drivers and potential biomarkers of survival in kidney renal clear cell carcinoma patients.

To analyze the diagnostic and prognostic potential of the BOLA gene family in kidney renal clear cell carcinoma (KIRC). This study is an observational study. The whole study was carried out at Prince Sattam bin Abdulaziz University, Al-Kharj, Saudi Arabia from January to November 2023. As it involves in silico and in vitro methods, ethical consent was not required. Various in silico and molecular experimental techniques were employed in this study. Significant up-regulation and hypomethylation of BOLA1, BOLA2, and BOLA3 were observed across 12 KIRC cell lines. Retrospective analysis of the cancer genome atlas program (TCGA)-KIRC cohorts confirmed hypomethylation of these genes in KIRC tissues. The cBioPortal analysis showed minimal genetic alterations, with amplification being the most common. Kaplan-Meier plotter data revealed that high BOLA1, BOLA2, and BOLA3 expression correlated with shorter overall survival and relapse-free survival in KIRC. Tumor-immune system interactions database analysis linked BOLA1 expression to immune and molecular subtypes. Gene silencing of BOLA1, BOLA2, and BOLA3 in 786-0 cells reduced cell growth and proliferation, enhancing wound healing capacity. BOLA genes may serve as diagnostic and prognostic markers in KIRC, offering insights into therapeutic targets and disease progression.

Mendelian randomization analysis of causal and druggable circulating inflammatory proteins in schizophrenia.

Schizophrenia (SZ) is a severe mental disorder with complex origins. Observational studies suggested that inflammatory factors may play a role in the pathophysiology of SZ and we aim to investigate the potential genetic connection between them by examining the causal impact of circulating inflammatory proteins on SZ. We utilized Mendelian randomization (MR) analysis to assess the causal relationship between circulating inflammatory proteins and SZ and the GWAS summary datasets were sourced from public databases. The SZ dataset comprised 74,776 cases and 101,023 controls, while the summary results for 91 plasma proteins in 14,824 participants were obtained through the Olink Target platform. Moreover, to identify and evaluate potential drug targets, we searched the Drug-Gene Interaction Database (DGIdb). The results of the MR study confirmed that nine inflammatory proteins had a causal effect on SZ. Among these proteins, IL1A (OR: 0.93), TNFB (OR: 0.94), TNFSF14 (OR: 0.96), and CD40 (OR: 0.95) exhibited protective effects against SZ. Conversely, CCL23 (OR: 1.04), CCL19 (OR: 1.04), 4EBP1 (OR: 1.06), TWEAK (OR: 1.08), and DNER (OR: 1.10) were associated with an increased risk of SZ. The MR-Egger and weighted median methods also supported the direction of these effects. According to the Gene-Drug analysis, LTA, IL1A, CD40, and 4EBP1 can serve as drug targets. Our study established causal relationships between circulating inflammatory proteins and SZ. It may be beneficial to personalize the treatment of SZ by incorporating inflammation management into the treatment regimen.

Real-world analysis of safety, tolerability, and adherence to nirmatrelvir-ritonavir (paxlovid) in primary care COVID-19 outpatients.

This retrospective cross-sectional study aims to evaluate the safety, tolerability, and adherence of patients prescribed Nirmatrelvir-ritonavir (Paxlovid) in outpatient settings, focusing on its use in managing category 2 COVID-19 patients across three primary healthcare clinics in Selangor, Malaysia. Data were collected from the Paxlovid pharmacy registry and medical records at Klinik Kesihatan Seksyen 7, Klinik Kesihatan Seksyen 19, and Klinik Kesihatan Kelana Jaya between April 1, 2022, and November 30, 2022. This study analysed data from 415 category 2 COVID-19 patients aged ≥ 18years. The primary and secondary outcomes included the assessment of patient demographics, Paxlovid dosing, current medication, changes in drug regimen, adherence, and adverse drug reactions (ADR). Pharmacists follow-ups were conducted on days 3 and 5 post-medication initiation. The majority (79.5%) of the cohort experienced ADR, predominantly dysgeusia, diarrhoea, body ache, vomiting, and nausea. Despite this, the ADRs were generally well-tolerated, with no severe impacts reported. High adherence was observed, with 96.9% of patients completing the 5-day regimen. The primary reasons for non-adherence included adverse effect intolerability, dosing ambiguity, forgetfulness, concerns about ADR, and perceived health improvement. Notable medications interacting with Paxlovid were simvastatin, amlodipine, and atorvastatin, and 21.7% of 23 concurrent medications were found not to comply with the recommended interventions by the University of Liverpool COVID-19 Drug Interaction database. Paxlovid demonstrates a high level of safety and tolerability in outpatient COVID-19 patients, with optimal adherence observed. This study underscores the vital role of healthcare professionals in managing Paxlovid within primary healthcare and highlights the need for broader research and direct patient involvement to enhance treatment strategies against COVID-19.

The mechanism of wen jing tang in the treatment of endometriosis: Insights from network pharmacology and experimental validation

BackgroundEndometriosis (EM) is a hormone-dependent condition marked by progressively severe secondary dysmenorrhea, significantly impacting patients' quality of life and overall health. Wen Jing Tang (WJT), a traditional Chinese medicinal formulation derived from the Synopsis of the Golden Chamber, has proven to be an effective therapeutic agent for EM. However, the precise molecular mechanisms underlying its efficacy remain unclear. ObjectiveThis study aims to elucidate the underlying mechanisms of WJT in the treatment of EM by integrating network pharmacology analysis with experimental validation. MethodsThe chemical constituents and target sites of WJT were obtained from the TCMSP database, while EM-related target genes were sourced from OMIM, TTD, GeneCards, and the DrugBank databases. A "herbs-components-targets" network was constructed using Cytoscape 3.9.1. The intersecting target genes of WJT and EM were then uploaded to the STRING database for protein-protein interaction (PPI) analysis. Subsequently, the common target genes were subjected to GO and KEGG enrichment analysis via the DAVID database. Molecular docking were employed to analyze the binding affinities between the top five core components and their respective targets. Additionally, ELISA were used to quantify the serum levels of IL-6, IL-1β, E2, and P in EM model rats. The expression levels of TNF-α, HIF1A, STAT3, and EGFR mRNA and proteins in ectopic endometrial tissue were assessed using q-PCR and Western blotting. ResultsA total of 250 chemical components and 553 targets were identified in WJT, while 3491 EM-related targets were screened from multiple databases. Among these, 187 common targets between WJT and EM were found, with quercetin, kaempferol, and beta-sitosterol emerging as the core chemical components, and AKT1, IL6, TNF, and IL1B identified as the key targets. These core components demonstrated strong binding affinities to the targets. GO and KEGG enrichment analyses revealed that the shared targets were primarily involved in the HIF1 signaling pathway. Furthermore, compared to the control group, the EM model rats exhibited an increased ectopic endometrial area, disordered glandular and stromal cells, and notable inflammatory infiltration. Serum levels of IL-6, IL-1β, E2, and P were significantly elevated (P < 0.01), and the expression of TNF-α, HIF1A, STAT3, and EGFR in the ectopic endometrium was markedly increased (P < 0.01). Following WJT intervention, the ectopic endometrial area in model rats was reduced, the morphology and structure of the endometrial cells showed improvement, and serum levels of IL-6, IL-1β, E2, and P were significantly decreased (P < 0.05). WJT also inhibited the expression of HIF1 pathway-related proteins TNF-α, HIF1A, STAT3, and EGFR (P < 0.05). ConclusionThe mechanism by which WJT prevents and treats EM may involve the reduction of inflammation through the inhibition of the HIF1 signaling pathway.

Transcriptomic analysis of rat prefrontal cortex following chronic stress induced by social isolation – Relevance to psychiatric and neurodevelopmental illness, and implications for treatment

Social isolation is an established risk factor for psychiatric illness, and became increasingly topical with the spread of SARS-CoV-2. We used RNA sequencing (RNA-Seq) to enable unbiased assessment of transcriptomic changes within the prefrontal cortex (PFC) of isolation-reared rats. To provide insight into the relevance of this manipulation for studying human illness, we compared differentially expressed genes (DEGs) and enriched biological functions against datasets involving post-mortem frontal cortical tissue from patients with psychiatric and neurodevelopmental illnesses. Sixteen male Sprague-Dawley rats were reared in groups of four or individually from weaning on postnatal day (PND) 22–24 until PFC tissue collection for RNA-Seq (PND64-66). We identified a total of 183 DEGs in isolates, of which 128 mirrored those in PFC tissue from patients with stress-related mental illnesses and/or neurodevelopmental conditions featuring social deficits. Seventy-one encode proteins classed as druggable by the gene-drug interaction database. Interestingly there are antagonists or inhibitors for the products of three of these up-regulated DEGs (Hrh3, Snca and Sod1) and agonists or activators for products of six of these down-regulated DEGs (Chrm4, Klf2, Lrrk2, Nr4a1, Nr4a3 and Prkca). Some have already undergone pre-clinical and clinical evaluation, and studies with the remainder may be warranted. Changes to Hrh3, Sod1, Chrm4, Lrrk2, Nr4a1 and Prkca were replicated in an independent cohort of sixteen male Sprague-Dawley rats via quantitative reverse transcription polymerase chain reaction (qRT-PCR). Our findings support the continued use of post-weaning isolation rearing to investigate the neurobiology of stress-related disorders and evaluate therapeutic targets.

What lies behind the large genome of Colletotrichum lindemuthianum.

Colletotrichum lindemuthianum is the etiological agent of anthracnose disease in common bean (Phaseolus vulgaris L.), noted for its ability to cause serious damage and significant pathogenic variability. This study reveals the features of the high-quality genome of C. lindemuthianum. Analysis showed improvements over the first assembly, with the refined genome having 119 scaffolds, ten times fewer than the first, and a 19% increase in gene number. The effector candidates increased by nearly 1.5 times. More than 40% of the amino acid sequences with homologs in the Pathogen-Host Interactions (PHI-base) database are linked to pathogenicity. Of 18 putative proteins identified as Chitinase-like Protein, six have a mutation in the enzyme catalytic motif, and three showed gene expression in the biotrophic phase, indicating they can act as effectors. Comparative genomic analyses with 30 other fungal species revealed that C. lindemuthianum is among the top three fungi encoding transport proteins. Seven Necrosis and Ethylene-Inducing Peptide 1 (Nep1)-Like Proteins (NLPs) are present in the C. lindemuthianum genome, but none had complete identity with the GHRHDWE conserved motif of NLPs; two were grouped with proteins that induce necrosis and may retain the capability to induce host necrosis. Colletotrichum species show a high number of secondary metabolite (SM) clusters, with C. lindemuthianum having 47 SM clusters. Approximately 60% of the C. lindemuthianum genome is composed of repetitive elements, a significantly higher proportion than in other fungi. These differences in transposable element (TE) numbers may explain why C. lindemuthianum has one of the largest genomes among the fungi analyzed. A significant portion of its genome comprises retroelements, particularly the Ty1/Copia superfamily, which accounts for 22% of the genome and represents 40% of the repetitive elements. The genomic profile features a remarkably high RIP-affected genomic proportion of 54.77%, indicating substantial RIP activity within this species. This high-quality genome of C. lindemuthianum, a significant pathogen in common bean cultivation, will support future research into this pathosystem, fostering a deeper understanding of the interaction between the fungus and its host.

Genetic and therapeutic for oral lichen planus and diabetes mellitus: a comprehensive study

BackgroundThis study employed a bidirectional Mendelian Randomization (MR) approach to explore the causal relationships between Oral Lichen Planus (OLP), diabetes mellitus (DM), and glycemic control. It also aims to identify potential pharmacological and herbal treatments that effectively address both OLP and the metabolic dysfunctions associated with DM.MethodsThis study employs a two-way MR approach to investigate the potential causal relationships between diabetes type and glycated hemoglobin (HbA1c) levels, and the risk of OLP. We analyzed differentially expressed genes from the OLP dataset in the Genomics Expression Omnibus (GEO) database, cross-referencing these with HbA1c-related genes for enrichment analysis. Additionally, the Drug-Gene Interaction Database (DGIdb) and Traditional Chinese Medicine Systems Pharmacology Database (TCMSP) were utilized to assess the effectiveness of specific drugs, herbs, and ingredients in treating OLP while managing blood glucose levels.ResultsThe MR analysis revealed a significant association between Type 1 Diabetes mellitus (T1DM) and an increased risk of OLP, unlike Type 2 Diabetes mellitus (T2DM). This finding indicates a unique immunological interaction in T1DM that may predispose individuals to OLP. The drug prediction analysis focused on core targets linked to OLP and HbA1c, evaluating the therapeutic potential of retinoic acid, prednisone, and thalidomide for treating OLP and regulating blood glucose levels. Additionally, herbal medicines such as Ecliptae herbaand Amygdalus communis vas, along with herbal ingredients like quercetin, luteolin, and 17-beta-estradiol, were identified for their anti-inflammatory properties and potential to mitigate metabolic dysfunction in diabetes.ConclusionThe study highlighted a complex interplay between diabetes and OLP, underscoring the efficacy of integrated therapeutic strategies that target both conditions. The findings suggest that both pharmaceutical and herbal treatments can effectively manage the clinical manifestations of OLP and associated metabolic challenges. This holistic approach to treatment could significantly enhance patient outcomes by addressing the interconnected aspects of these chronic conditions.

Familial adenomatous polyposis gene MUTYH mutations are identified in anaplastic thyroid carcinoma

Abstract Introduction/Objective Anaplastic thyroid carcinoma (ATC) is a rare aggressive disease unresponsive to treatment. Next-Generation Sequencing (NGS) allows identification of targets for precision therapies, such as BRAF, with implications in treating ATC. Our prior work identified ATC clusters with characteristic gene mutations and multiple previously unreported mutations. One of these is MUTYH, which is associated with colon (CRC), ovarian, breast, bladder, and duodenal carcinomas in MUTYH-associated polyposis (MAP). Its association with ATC is not defined. Methods/Case Report Exploratory analysis of pathogenic mutations in 727 ATC cases using a 324-gene panel (FoundationOneCDx) and an interactive visualization of association rules was conducted for informative maximal frequent patterns among mutated gene combinations to identify gene clusters including genes not commonly associated with ATC. TCGA database was reviewed for frequency of MUTYH mutations. My Cancer Genome and the Drug-Gene Interaction Database were used to identify potential targeted drugs for MUTYH gene-mutated cancers. Results (if a Case Study enter NA) NGS showed MUTYH short-variant mutations in 17 cases (2.34%). Germline MUTYH variants incidence is 1.43% in normal samples. 5 cases harbored only Y165C and 7 had only G382D, with 1 case having both Y165C and G382D. The other 4 cases contained sporadic truncating events in MUTYH. All instances of Y165C and G382D were predicted to be germline. 6 patients (35%) had BRAF co-mutations, correlating with expected frequency of ATC thought to transform from papillary carcinoma (PC). One case had only MUTYH mutation while a second had MUTYH with TERT and TP53. TCGA database contained 6(0.2%) cases of PC with MUTYH mutations (total 2871 MUTYH-mutated carcinomas), but no cases of ATC or other thyroid tumors were described. Conclusion MUTYH is a DNA repair enzyme linked to CRC and other cancers. MUTYH mutations occur in 6.7% of MAP patients and 1–2.2% of sporadic CRC cases that are mutually exclusive of BRAF mutations. While MAP increases the lifetime risk of CRC by over 60%, the link of MUTYH mutations to PC has only been observed in MAP and not been described outside of it. To our knowledge this is the first description of MUTYH mutations in ATC, especially without concurrent BRAF mutation (11 cases), suggesting MUTYH may independently contribute to pathogenesis of ATC. PARP inhibitors, PD-1/PD-L1 inhibitors, and ATR inhibitors demonstrate promising results in clinical trials of MUTYH-mutated cancers, warranting further research.

Drug-drug-interactions in patients with atrial fibrillation admitted to the emergency department.

Polypharmacy is a growing concern in healthcare systems. While available data on potential drug-drug interactions (pDDI) from emergency department (ED) patients is derived from heterogenous populations, this study specifically focused on patients with atrial fibrillation (AF). We hypothesized that patients with AF have similar comorbidities, receive similar drugs, and have similar pDDIs. The overarching aim was to highlight frequent pDDIs, providing practical guidance for treating healthcare professionals and consequently reduce the risk of adverse drug reactions. Two hundred patients ≥18years with AF, who received rate- or rhythm-controlling medication at the ED of the University Hospital Vienna, and who were on long-term medication before admission, were eligible. Long-term medication alone, as well as in combination with medication administered at the ED were analyzed for pDDIs using the Lexicomp® Drug interactions database. Within the long-term medication of patients', we identified 664 pDDIs. Drugs administered at the ED increased pDDIs more than 3-fold to 2085. Approximately, every fifth patient received a contraindicated drug combination (on average 0.24 per patient), while 70% received drug combinations for which therapy modifications are recommended (on average 1.59 per patient). The most frequently involved drugs included amiodarone, propofol, bisoprolol, enoxaparin, and acetylsalicylic acid. Increased risk of bleeding, QTc prolongation, and myopathy were among the most relevant potential consequences of these interactions. In conclusion, an optimization of medication would be advisable in almost every AF patient. Treating healthcare professionals should be cautious of drugs that increase bleeding risk, prolong QTc, or bear a risk for myopathy.

Determination of FGFR1 Functions in Cytarabine Treatment of Acute Myeloid Leukemia Through Bioinformatics Analysis

Aim: Among the most prevalent subtypes of acute leukemia is acute myeloid leukemia (LAML). Consequently, it is essential to understand the molecular causes of LAML and find its predictive and diagnostic biomarkers. The aim of this study is to determine the molecular functions of fibroblast growth factor receptor 1(FGFR1) involved in LAML pathogenesis and its potential therapeutic effect for AML treatment. Methods: The molecular docking interaction of the Cytarabine with its target FGFR1 was examined. The Gene Expression Profiling Interactive Analysis, version 2 (GEPIA2), and UALCAN tools database were used to obtain the LAML gene expression datasets. Gene functional annotation was performed to investigate the DEGs' possible role. Using the Interactive Gene database retrieval tool (STRING) and a few chosen hub modules from the GeneMANIA database, the protein- protein interaction (PPI) network were constructed. A survival analysis was performed on the effects of hub genes on the overall survival of LAML patients. Results: As a result of docking, a strong interaction was observed between cytarabine and FGFR1. It has been discovered that cytarabine can reverse FGFR1 expression. The survival study results showed an association between the prognosis of AML patients and one of the central genes, FGFR1. Conclusion: The expression profile and functions of FGFR1 were determined in LAML patients. It has been shown that FGFR1 can be a viable therapeutic target for LAML and a possible biomarker for diagnosis.

Creating an interactive database for nasopharyngeal carcinoma management: applying machine learning to evaluate metastasis and survival.

Nasopharyngeal carcinoma (NPC) patients frequently present with distant metastasis (DM), which is typically associated with poor prognosis. This study aims to develop and apply machine learning models to predict DM, overall survival (OS), and cancer-specific survival (CSS) in NPC patients to provide optimal tools for improved predictive accuracy and performance. We retrieved over 8,000 NPC patient samples with associated clinical information from the Surveillance, Epidemiology, and End Results (SEER) database. Utilizing two methods for handling missing values-imputation or deletion-we created various cohorts: DM-all, DM-slim, OS-all, OS-slim, CSS-all, and CSS-slim. Five machine learning models were deployed for the binary classification task of DM, and their performance was evaluated using the area under the curve (AUC). For the survival prediction tasks of OS and CSS, we constructed 45 combinations using nine survival machine learning algorithms. The Concordance Index (C-index), 5-year AUC, and Brier score assessed model accuracy. Patients were stratified into two risk groups for survival analysis, and the survival curves were presented. This study examines the relationships between clinical factors and survival in NPC patients. The analysis, visualized through forest plots, indicates that demographic and clinical variables like gender, marital status, tumor grade, and stage significantly affect metastatic risks and survival. Specifically, factors such as advanced stages increase metastasis and survival risks, while enhanced treatments improve survival rates. In the cohort for DM prediction, results revealed that the random forest model was the most effective, with an AUC of 0.687. In contrast, when predicting overall survival (OS), the random survival forest (RSF) model consistently showed superior performance with the highest mean C-index of 0.802, a 5-year AUC of 0.857, and a Brier score of 0.167. Similarly, for cancer-specific survival (CSS) prediction, the RSF model demonstrated a mean C-index of 0.822, a 5-year AUC of 0.884, and a Brier score of 0.165. An online Shiny server was developed to allow the models to be used freely and efficiently via http://npcml.shinyapps.io/NPCpre. This study successfully established an online tool by machine learning models for NPC metastasis and survival prediction, providing valuable references for clinicians.

7862 The Paradoxical Role Of ERFFI1 In Breast Cancer Progression Is Supported By Its Dynamic Protein Interactome

Abstract Disclosure: A. Ocampo: None. P.D. Bagamasbad: None. In breast cancer (BCa), glucocorticoid (GC) therapy is used in anti-emetic and palliative care. However, the effects of GC therapy in BCa are conflicting as it is beneficial for hormone-responsive luminal subtypes while it promotes tumor progression in more aggressive triple-negative BCa (TNBCs). A factor implicated in this paradoxical shift is the feedback inhibitor of epidermal growth factor receptor (EGFR) signaling, ERBB receptor feedback inhibitor 1 (ERRFI1). In BCa cell lines, ERRFI1 expression is directly regulated by GC receptor (GR). More interestingly, ERRFI1 was found to restrict the GC-enhanced proliferation in normal breast epithelia but enhances the GC-mediated pro-tumorigenic effects in highly aggressive TNBC. To identify the mechanism behind the shift in ERFFI1 function through BCa progression, ERRFI1 protein interactions in the luminal, HER2, and TNBC subtypes were analyzed by identifying differentially expressed proteins from each subtype using available proteome and interactome datasets from Integrated Interactions Database and followed by network and clustering analyses through STRING. The ERRFI1 interactome varied across the subtypes, and gene ontology analysis of the protein networks revealed progressive tumorigenic effects from the least aggressive luminal subtype to the most aggressive TNBC. The luminal BCa-ERRFI1 interactome showed metastatic potential that is countered by negative regulation of receptor tyrosine kinase (RTK) signaling. The HER2-ERRFI1 interactome highlighted the amplification of RTK signaling and its possible modulation through SRC while the TNBC-ERRFI1 interactome presents pro-oncogenic proteins implicated in drug resistance, angiogenesis, and EMT. Interestingly, the interactome also revealed a link between EGFR signaling and GR signaling possibly through ERRFI1, EGFR, and SFN. To determine the function of ERFFI1 in EGFR signaling in BCa, we generated stable ERRFI1 knockdown in different breast epithelial cell models through lentiviral transduction. Cells were then treated with EGF followed by gene expression analysis of known EGF-upregulated genes such as MYC, GSK3B, MCL1, and MMP9. We found that ERRFI1 knockdown enhanced the EGF-dependent induction of MYC and MMP9 in normal MCF10A cells and this effect was not observed in the TNBC MDA-MB-468 line, suggesting the loss of ERRFI1-mediated inhibition of EGFR signaling with BCa tumorigenic potential. Taken together, our findings suggest that the progressive loss of anti-tumorigenic function of ERRFI1 may be explained by its changing interactome in BCa molecular subtypes. Presentation: 6/3/2024

7862 The Paradoxical Role of ERFFI1 in Breast Cancer Progression Is Supported by Its Dynamic Protein Interactome

Abstract Disclosure: A. Ocampo: None. P.D. Bagamasbad: None. In breast cancer (BCa), glucocorticoid (GC) therapy is used in anti-emetic and palliative care. However, the effects of GC therapy in BCa are conflicting as it is beneficial for hormone-responsive luminal subtypes while it promotes tumor progression in more aggressive triple-negative BCa (TNBCs). A factor implicated in this paradoxical shift is the feedback inhibitor of epidermal growth factor receptor (EGFR) signaling, ERBB receptor feedback inhibitor 1 (ERRFI1). In BCa cell lines, ERRFI1 expression is directly regulated by GC receptor (GR). More interestingly, ERRFI1 was found to restrict the GC-enhanced proliferation in normal breast epithelia but enhances the GC-mediated pro-tumorigenic effects in highly aggressive TNBC. To identify the mechanism behind the shift in ERFFI1 function through BCa progression, ERRFI1 protein interactions in the luminal, HER2, and TNBC subtypes were analyzed by identifying differentially expressed proteins from each subtype using available proteome and interactome datasets from Integrated Interactions Database and followed by network and clustering analyses through STRING. The ERRFI1 interactome varied across the subtypes, and gene ontology analysis of the protein networks revealed progressive tumorigenic effects from the least aggressive luminal subtype to the most aggressive TNBC. The luminal BCa-ERRFI1 interactome showed metastatic potential that is countered by negative regulation of receptor tyrosine kinase (RTK) signaling. The HER2-ERRFI1 interactome highlighted the amplification of RTK signaling and its possible modulation through SRC while the TNBC-ERRFI1 interactome presents pro-oncogenic proteins implicated in drug resistance, angiogenesis, and EMT. Interestingly, the interactome also revealed a link between EGFR signaling and GR signaling possibly through ERRFI1, EGFR, and SFN. To determine the function of ERFFI1 in EGFR signaling in BCa, we generated stable ERRFI1 knockdown in different breast epithelial cell models through lentiviral transduction. Cells were then treated with EGF followed by gene expression analysis of known EGF-upregulated genes such as MYC, GSK3B, MCL1, and MMP9. We found that ERRFI1 knockdown enhanced the EGF-dependent induction of MYC and MMP9 in normal MCF10A cells and this effect was not observed in the TNBC MDA-MB-468 line, suggesting the loss of ERRFI1-mediated inhibition of EGFR signaling with BCa tumorigenic potential. Taken together, our findings suggest that the progressive loss of anti-tumorigenic function of ERRFI1 may be explained by its changing interactome in BCa molecular subtypes. Presentation: 6/3/2024

A systematic evidence map protocol for mapping global exposure to bisphenols and their alternatives and social and environmental justice implications

BackgroundBisphenol A (BPA) is one of the highest-volume chemicals produced worldwide, and human exposure to BPA is thought to be ubiquitous. Stricter regulations around the use of BPA have led many manufacturers to switch to other bisphenol chemicals with similar functions such as bisphenol S and F. Even though exposure to BPA, other bisphenol chemicals and bisphenol alternatives poses a health risk for humans, very little is known about the granular exposure levels of different populations around the world. AimThis systematic evidence map (SEM) will identify human studies reporting concentrations of bisphenols and their alternatives measured in human bio-samples with the aim to chart the global human exposure levels by country and population characteristics to identify research gaps and discuss any social and environmental injustice implications. Search strategy and eligibility criteriaMEDLINE®, Embase and Web of Science (WoS) databases as well as grey literature sources will be searched using predefined search strings. The database search results will be supplemented by backward and forward citation tracking on included studies. A scoping exercise conducted during planning identified 90 bisphenol chemicals and alternatives used in plastics. These include BPA, other bisphenol chemicals with/without similar functions to BPA as well as alternatives with similar functions to bisphenol chemicals. Eligible studies must report concentrations of at least one relevant bisphenol chemical/alternative measured in human bio-samples. Study selectionOnly primary studies published in English since 2010 will be considered. The title, abstract and keywords will be screened by the DistillerAI tool and two independent reviewers. Grey literature will be screened by two reviewers for inclusion and exclusion. The full text of the included studies will then be screened by two independent reviewers. Study appraisalStudy quality will not be evaluated in this SEM. Data extraction and codingData extraction and coding will be performed by two independent reviewers. Parameters of interest will include the following: study characteristics (e.g., year of publication, sampling timepoints and study design), population information (e.g., country, age, sex, ethnicity, number of participants) and exposure information (sources of exposure, bio-sample analyzed, chemical name, concentration, and detection frequencies). Synthesis and visualizationThe results will be presented using a narrative summary, tables, bar plots and color-coded maps. The interactive database will be available on a dedicated freely accessible website. Systematic map protocol registry and registration numberThis protocol has been registered on Open Science Framework (OSF) and is available at https://doi.org/10.17605/OSF.IO/MNWTD.