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One of the critical challenges in managing colorectal cancer (CRC) is the development of oxaliplatin (OXP) resistance. Long non-coding RNAs (lncRNAs) have a crucial role in CRC progression and chemotherapy resistance, with exosomal lncRNAs emerging as potential biomarkers. This study aimed to predict key lncRNAs involved in OXP-resistance using in-silico methods and validate them using RT-qPCR methods in CRC cells and their isolated exosomes. Two public datasets, GSE42387 and GSE119481, were downloaded from the GEO database to identify differentially expressed genes (DEGs) and miRNAs (DEmiRNAs) associated with OXP-resistance in the HCT116 cell line. The analysis of GSE42387 revealed 210 DEGs, and GSE119481 identified 73 DEmiRNAs. A protein-protein interaction (PPI) network analysis of the DEGs identified 133 interconnected genes, from which the top ten genes with the highest degree scores were selected. By intersecting predicted miRNAs targeting these genes with the DEmiRNAs, 38 common miRNAs were found. Subsequently, 224 lncRNAs targeting these common miRNAs were predicted. LncRNA-miRNA-mRNA network were constructed and the top five lncRNAs with the highest degree scores were identified. Analysis using the Kaplan-Meier plotter database revealed that the key lncRNAs NEAT1, OIP5-AS1, and MALAT1 are significantly associated with the overall survival of CRC patients. To validate these lncRNAs, OXP-resistant HCT116 sub-cell line (HCT116/OXR) was developed by exposing parental HCT116 cells to gradually increasing concentrations of OXP. Exosomes derived from both HCT116 and HCT116/OXR cells were isolated and characterized utilizing dynamic light scattering (DLS), transmission electron microscopy (TEM), and Western blotting. RT-qPCR confirmed elevated levels of NEAT1, OIP5-AS1, and MALAT1 in HCT116/OXR cells and their exosomes compared to parental HCT116 cells and their exosomes. This study concludes that NEAT1, OIP5-AS1, and MALAT1 are associated with the OXP-resistance in CRC. The high levels of these lncRNAs in exosomes of resistant cells suggest their involvement in intercellular communication and resistance propagation. This positioning makes them promising biomarkers for OXP-resistance in CRC. [ABSTRACT FROM AUTHOR]

Background Acquired resistance to 5-fluorouracil (5-FU) frequently results in chemotherapy failure and disease recurrence in advanced colorectal cancer (CRC) patients. Research has demonstrated that dysregulation of long non-coding RNAs (lncRNAs) mediates the development of chemotherapy resistance in cancerous cells. The present study aims to identify key lncRNAs associated with 5-FU resistance in CRC using bioinformatic and experimental validation approaches. Methods The Gene Expression Omnibus (GEO) dataset GSE119481, which contains miRNA expression profiles of the parental CRC HCT116 cell line (HCT116/P) and its in-vitro established 5-FU-resistant sub-cell line (HCT116/FUR), was downloaded. Firstly, differentially expressed microRNAs (DEmiRNAs) between the parental and 5-FU resistance cells were identified. LncRNAs and mRNAs were then predicted using online databases. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses were performed to uncover relevant biological mechanisms and pathways. Networks integrating lncRNAs, miRNAs, and mRNAs interactions were constructed, and topological analyses were used to identify key lncRNAs associated with 5-FU resistance. An in-vitro model of the HCT116/FUR sub-cell line was developed by exposing the HCT116/P cell line to increasing concentrations of 5-FU. Finally, real-time quantitative PCR (RT-qPCR) was performed on total RNA extracted from the HCT116/P cell line and the HCT116/FUR sub-cell line to validate the in-silico predictions of key lncRNAs. Results A total of 32 DEmiRNAs were identified. Enrichment analysis demonstrated that these DEmiRNAs were mainly enriched in several cancer hallmark pathways that regulate cell growth, cell cycle, cell survival, inflammation, immune response, and apoptosis. The predictive analysis identified 237 unique lncRNAs and 123 mRNAs interacting with these DEmiRNAs. The pathway analysis indicated that most of these predicted genes were enriched in the cellular response to starvation, protein polyubiquitination, chromatin remodeling, and negative regulation of gene expression. Topological analyses of the lncRNA-miRNA-mRNA network highlighted the nuclear enriched abundant transcript 1 (NEAT1), metastasis-associated lung adenocarcinoma transcript 1 (MALAT1), and Opa interacting protein 5 antisense RNA 1 (OIP5-AS1) as central lncRNAs. Experimental analysis by RT-qPCR confirmed that the expression levels of NEAT1 and MALAT1 were significantly increased in HCT116/FUR cells compared to HCT116/P cells. However, no significant difference was observed in the OIP5-AS1 expression level between the two cells. Conclusion Our findings specifically highlight MALAT1 and NEAT1 as significant contributors to 5-FU resistance in CRC. These lncRNAs are promising biomarkers for diagnosing and predicting outcomes in CRC., Competing Interests: Human subjects: All authors have confirmed that this study did not involve human participants or tissue. Animal subjects: All authors have confirmed that this study did not involve animal subjects or tissue. Conflicts of interest: In compliance with the ICMJE uniform disclosure form, all authors declare the following: Payment/services info: This study was part of a PhD thesis, funded and supported by Tehran University of Medical Sciences (Grant no. 42069). Financial relationships: All authors have declared that they have no financial relationships at present or within the previous three years with any organizations that might have an interest in the submitted work. Other relationships: All authors have declared that there are no other relationships or activities that could appear to have influenced the submitted work., (Copyright © 2024, Sahebnasagh et al.)

Background: Methicillin-resistant Staphylococcus aureus (MRSA) is the main cause of hospital infection emerged over the last decades. Rapid detection of MRSA is important for patient care and proper usage of infection control. Detection of mecA genes (encoding resistance to methicillin and other similar antibiotics) and nuc genes (encoding staphylococcal thermostable nuclease) by PCR method is now considered for rapid identification of MRSA strain. The aim of this study was to determine the prevalence of MRSA isolated from patients in Tehran, Iran by PCR method for detection of mecA and nuc genes., Method: Phenotypic method such as microscopic and colony morphology and catalase and coagulase tests were used for identification of S. aureus isolates. DNA was extracted from all isolates and the presence of nuc and mecA gene was detected by PCR method. For determination of MRSA by phenotypic methods, oxacillin disk diffusion test were used. Data were analyzed by SPSS software., Results: Out of 126 clinical sample identified by phenotypic method, 101 isolates had nuc gene. In disk diffusion tests by oxacillin disk, 78.2% of isolates were considered to be MRSA, but in PCR method for mecA gene, 69% isolates were positive., Conclusions: The results showed a high prevalence of methicillin-resistance among S. aureus isolates. Identifying MRSA strains, isolating MRSA-positive patients and carrier's treatment in a hospital to prevent MRSA infection is important in limiting the spread of MRSA. The PCR method for detection of nuc and mecA genes has potential for rapid and accurate diagnosis of MRSA strains.