A Comprehensive Analysis for Expression, Diagnosis, and Prognosis of m5C Regulator in Breast Cancer and Its ncRNA-mRNA Regulatory Mechanism.
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ABSTRACT:
SUBMITTER: Liu J
PROVIDER: S-EPMC9257136 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:BackgroundCholangiocarcinoma (CHOL) is a malignant tumor that originates in the extrahepatic bile duct and can extend from the hilar region to the lower end of the common bile duct. The prognosis of CHOL patients is particularly poor; therefore, in this study, we screened mRNAs correlated with N6-methyladenosine (m6A) to construct a risk model for prognosis in CHOL.MethodsThe TCGA-CHOL dataset was applied to obtain and analyze the coexpression of 1281 m6A-related mRNAs, from which 14 were selected for further analysis through univariate proportional hazards (cox) regression analysis. Aryl hydrocarbon receptor interacting protein (AIP), CCAAT/enhancer binding protein beta (CEBPB), syndecan1 (SDC1), vacuolar protein sorting 25 homolog (VPS25) and syntaxin binding protein 2 (STXBP2) were then screened out through the least absolute shrinkage and selection operator (LASSO) and multivariate Cox regression analysis to develop a precise m6A-related mRNA prognosis risk model (MRMRPM) with an area under curve (AUC) of 0.908 and 0.923 after 1 and 2 years, respectively. We divided the samples into high-risk and low-risk groups using the m6A-related mRNA prognosis risk model.ResultsKaplan-Meier analysis indicated poor overall survival (OS) for the high-risk group. Two Gene Expression Omnibus (GEO) datasets (GSE89748 and GSE107943) were used to validate the risk model. The results of drug sensitivity and immune cell infiltration analysis showed that the risk model could serve as a prognosis index of potential immunotherapeutic characteristics and drug sensitivity. Furthermore, the proportion of resting dendritic cells and regulatory T cells was positively associated with an increased expression of four m6A-related mRNAs - AIP, CEBPB, SDC1, and VPS25 - in the high-risk CHOL group.ConclusionsOur findings suggest that this model can be a prognostic indicator for CHOL patients.
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Project description:Great improvement has been made in the diagnosis and therapy of breast cancer patients. However, the identification of biomarkers for early diagnosis, prognosis, therapy assessment and monitoring, including drug resistance and the early detection of micro-metastases, is still lacking. Recently, circulating microRNAs (miRNAs), circulating freely in the blood stream or entrapped in extracellular vesicles (EVs), have been shown to have a potential diagnostic, prognostic or predictive power. In this review, recent findings are summarized, both at a preclinical and clinical level, related to miRNA applicability in the context of breast cancer. Different aspects, including clinical and technical challenges, are discussed, describing the potentialities of miRNA use in breast cancer. Even though more methodological standardized studies conducted in larger and selected patient cohorts are needed to support the effective clinical utility of miRNA as biomarkers, they could represent novel and accessible tools to be transferred into clinical practice.
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Project description:Osteoarthritis (OA) is a common orthopedic degenerative disease, leading to high disability in activities of daily living. There remains an urgent need to identify the underlying mechanisms and identify new therapeutic targets in OA diagnosis and treatment. Circular RNAs (circRNAs) play a role in the development of multiple diseases. Many studies have reported that circRNAs regulate microRNAs (miRNAs) through an endogenous competitive mechanism. However, it remains unclear if an interplay between circRNAs, miRNAs, and target genes plays a deeper regulatory role in OA. Four datasets were downloaded from the GEO database, and differentially expressed circRNAs (DECs), differentially expressed miRNAs (DEMs), and differentially expressed genes (DEGs) were identified. Functional annotation and pathway enrichment analysis of DEGs and DECs were carried out to determine the main associated mechanism in OA. A protein–protein network (PPI) was constructed to analyze the function of, and to screen out, hub DEGs in OA. Based on the artificial intelligence prediction of protein crystal structures of two hub DEGs, TOP2A and PLK1, digitoxin and oxytetracycline were found to have the strongest affinity, respectively, with molecular docking. Subsequently, overlapping DEMs and miRNAs targeted by DECs obtained target DEMs (DETMs). Intersection of DEGs and genes targeted by DEMs obtained target DEGs (DETGs). Thus, a circRNA–miRNA–mRNA regulatory network was constructed from 16 circRNAs, 32 miRNAs, and 97 mRNAs. Three hub DECs have the largest number of regulated miRNAs and were verified through in vitro experiments. In addition, the expression level of 16 DECs was validated by RT-PCR. In conclusion, we constructed a circRNA–miRNA–mRNA regulatory network in OA and three new hub DECs, hsa_circ_0027914, hsa_circ_0101125, and hsa_circ_0102564, were identified as novel biomarkers for OA.
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