Background: Developmental and Epileptic Encephalopathy (DEE) is a severe and heterogeneous neurological disorder in infancy/early childhood. DEE’s genetic and phenotypic variability complicates diagnosis and treatment. This retrospective study aimed to identify genetic variants and explore genotype–phenotype correlations in children with DEE using a targeted epilepsy gene panel (TGP) and Whole Exome Sequencing (WES). Patients and Methods: Medical records of children who underwent custom-designed 55-gene TGP and WES were reviewed. The diagnostic yield of each method was determined based on the detection of pathogenic (P) and likely pathogenic (LP) variants. Results: A total of 129 patients (66 males, 63 females) underwent TGP, which identified P/LP variants in 29 cases (22.48%). Variants were detected in SCN1A, KCNQ2, STXBP1, CDKL5, PCDH19, PLCB1, WWOX, SCN2A, FGF12, HCN1, SCN8A, and SLC35A2. WES further identified several variants in children with West syndrome. A TSC1 variant was detected in a patient without cutaneous stigmata of tuberous sclerosis complex. The NALCN variant in a patient was linked to Infantile Hypotonia with Psychomotor Retardation and Characteristic Facies 1. A CTBP1 variant associated with extremely rare Hypotonia, Ataxia, Developmental Delay, and Tooth Enamel Defect Syndrome was detected in another patient. A PIEZO2 variant—associated with Marden–Walker syndrome—was found in a child with Early Infantile Developmental and Epileptic Encephalopathy. Conclusions: These findings highlight the extensive genetic heterogeneity and phenotypic variability of DEE. WES demonstrates substantial value in identifying novel gene-disease associations and may be considered as a first-tier diagnostic tool in epilepsy and DEE.

Background/Aim: Periodontitis is a prevalent multifactorial, oral infectious disease and is considered a high-risk factor for pancreatic cancer. Nevertheless, there is limited understanding of the underlying epigenetic mechanisms governing this relationship. The aim of this study was to identify dysregulated miRNAs associated with periodontitis and pancreatic cancer, along with their related genes, signaling pathways, and compounds. Materials and Methods: miRNA expression datasets for tissues affected by periodontitis and pancreatic cancer were obtained from the Gene Expression Omnibus database. miRNAs differentially expressed relative to normal tissues were detected, and those common to both datasets were determined. Further bioinformatics approaches were used to explore the association of common differentially expressed miRNAs with periodontitis and pancreatic cancer. Results: Twenty shared, differentially expressed miRNAs were identified; 14 exhibited similar expression patterns in both diseases. Among these common differentially expressed miRNAs, 10 were found to be overexpressed. hsa-miR-155, hsa-miR-186, hsa-miR-765, hsa-miR-211 and hsa-miR-375 were the top miRNA nodes in the gene network, with hsa-mir-155 being the sole miRNA node in the transcription factor network. Top candidate miRNA-dysregulated genes included superoxide dismutase 2 (SOD2), nuclear FMR1 interacting protein 2 (NUFIP2), SFT2 domain-containing 2 (SFT2D2), thioredoxin-interacting protein (TXNIP), and cyclin D1 (CCND1), while top dysregulated transcription factors were Argonaute RISC catalytic component 2 (AGO2), AKT serine/threonine kinase 1 (AKT1), BCL6 transcription repressor (BCL6), breakpoint cluster region (BCR), and BRCA1 DNA repair associated (BRCA1). Relevant compounds for targeting these emerged, including 5-fluorouracil, gemcitabine, doxorubicin, ascorbate, diethylstilbestrol, and temozolomide. Conclusion: Our study suggests candidate molecular mechanisms linking periodontitis to pancreatic cancer, highlighting potential compounds that may target both diseases. These findings provide a foundation for guiding future fundamental and clinical research.

Ovarian cancer (OC) is a common gynecological malignancy associated with high morbidity and generally poor prognosis despite treatment. The aim of this study was to understand the influence of gene expression differences and pathways in OC development and progression. One hundred and thirty-three OC samples and 34 normal ovarian tissues were included in the study from the Gene Expression Omnibus database. GeneSpring Software was used to obtain differentially expressed genes (DEGs) in all stages comparing tumor and normaltissue. DEGs were analyzed using the DAVID interface for Kyoto Encyclopedia of Genes and Genomes pathway analysis. Most most connected genes were selected as hub genes for each stage using the STRING application in Cytoscape software. DEGs were found to be associated with cell cycle and herpes simplex virus infection pathways. A total of 19 genes (ACTB, AKT1, ALB, CTNNB1, EGFR, EP300, ESR1, FN1, GAPDH, HSPA4, IL6, JUN, MYC, PTEN, RPS27A, SRC, TNF, TP53 and UBC) were identified as hub genes. Among the hub genes, the TP53 gene was found to have the highest level of connections in all stages. EGFR, RPS27A, and AKT1 were found to have high numbers of connections in stages II, III, and IV, respectively. The results of the current study may provide new insights into OC pathogenesis and suggest potential prognostic and therapeutic targets.

Epetraborole (EP) is a boron-containing antibiotic known for its effectiveness against gram-negative enteric bacteria and Mycobacterium species. It is designed to bind and inhibit the LeuS enzyme (Leucyl-tRNA Synthetase), which is encoded by the essential gene leuS in Escherichia coli. EP inhibits protein translation, impeding bacterial growth. However, when leuS is overexpressed in a recombinant plasmid, the amount of EP required for growth inhibition needs to be increased. This study explored the impact of EP on the transcriptome and proteome of E. coli overexpressing leuS, aiming to reveal additional gene and pathway insights beyond LeuS, shedding light on the biochemical players orchestrating the bacterium’s molecular response. 2D-PAGE Proteomics analysis identified four differentially regulated proteins influenced by EP in the leuS overexpression strain. Notably, LeuA and DeoA emerged as identified proteins. EP may affect LeuA in the cells overexpressing LeuS, which could result in truncated LeuA protein variants. Transcriptomics analyses, based on microarray data, revealed 23 up-regulated and 9 down-regulated genes responding to EP in the overexpression strain (p2). Based on the statistical analyses, the first five up-and down-regulated genes showing the highest fold differences in their mRNA levels are yiaW, mglB, narH, ybiO, flgB and yhdY, deoR, recX, yobB, potF, respectively. Analyses using the Omics Dashboard pathway and String indicate that the EP effect on the leuS overexpressing strain mainly induces alterations in the expression of genes related to the cell exterior, regulation, and response to stimuli. It is suggested that EP and higher levels of LeuS may interfere with the translational and transcriptional regulation of the expression of the leuA gene, which encodes the first enzyme, 2-isopropylmalate synthase, in L-leucine biosynthesis. This study offers new insights into the effects of EP on the bacterium, specifically when the level of the aminoacyl-tRNA synthetase LeuS is increased.

Background: This pilot study aimed to investigate the relationship between the breast tissue microbiota and breast cancer in Turkish women. We compared cancerous and adjacent normal breast tissues, as well as stool samples, obtained during breast-conserving surgery. Methods: In this prospective study, paired tumor and normal breast tissue samples, together with preoperative stool samples, were analyzed using 16S rRNA sequencing. Diversity indices and relative abundance differences were calculated, with effect sizes, 95% confidence intervals, and false discovery rate (FDR) corrections reported where appropriate. Results: A total of 22 patients with early-stage breast cancer were included (mean age 58.3 ± 12.7 years, mean BMI 28.9 ± 3.1 kg/m²). Distinct compositional shifts were observed between tumor and normal tissues, with Ruminococcus, Eubacterium, Actinobacteria (phylum), and Stenotrophomonas enriched in tumor samples, while Lactobacillus, Staphylococcus, Bifidobacterium, and Faecalibacterium were more abundant in normal tissues. No consistent associations were identified between fecal and breast tissue microbiota. Limitations: The small sample size, absence of healthy tissue or stool controls, and reliance on 16S rRNA sequencing limit the generalizability and functional interpretation of these findings. Conclusions: Despite these limitations, this study demonstrates localized microbial differences between tumor and adjacent normal breast tissues. Larger, multi-center studies with healthy controls and functional omics approaches are warranted to clarify the biological relevance and potential clinical implications.