Comprehensive analysis of the mRNA-lncRNA co-expression profile and ceRNA networks patterns in chronic hepatitis B
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ABSTRACT:
ORGANISM(S): Homo sapiens
PROVIDER: GSE136343 | GEO | 2019/08/27
REPOSITORIES: GEO
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Project description:With 350 million carriers worldwide who may suffer from serious sequelae, including hepatocellular carcinoma, chronic hepatitis B virus (CHB) infection remains an important health issue. Current antiviral therapies hardly eradicate the virus. Therefore, there are still imperative need to develop new therapeutic strategies and predictors for treatment response to cure the disease and avoid futile treatment. By taking the advantage of having the paired liver biopsy samples of IFNalpha responders before/after treatment and pretreatment samples from responders and non-responders, we could characterize the intrahepatic expression profiles associated with necroinflammatory activity and the profiles/signature potentially predictive of response to IFNalpha therapy for CHB in this study.
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Project description:The early and accurate identification of predictive biomarkers for antiviral treatment efficacy remains a significant clinical challenge, particularly in the management of chronic hepatitis B (CHB). This study aimed to assess whether the plasma metabolome could reliably predict the success of antiviral therapy in CHB patients. We conducted a retrospective analysis on 56 treatment-naive CHB patients at the First Affiliated Hospital of Zhejiang University from December 2013 to March 2016. Patients were randomly assigned to either a discovery cohort (n=29) or a validation cohort (n=27) and underwent a 48-week treatment regimen of entecavir (ETV) and interferon-alpha (IFN-α). Based on the outcome of the treatment, patients were classified as HBeAg seroconversion either (High responders, Hrp) or the non-remission group (Low responder, Lrp). Our methodology involved an untargeted analysis of the amine/phenol and carboxylic acid submetabolomes in the CHB patients under treatment, utilizing chemical isotope labeling (CIL) techniques with liquid chromatography-mass spectrometry (LC-MS).Several metabolites were identified as having significant diagnostic potential for distinguishing Hrp from Lrp, with areas under the receiver operating characteristic curve (AUC) exceeding those typically clinical indicators. Notably, four metabolites, namely 2-methyl-3-ketovaleric acid, 2-ketohexanoic acid, 6-oxo-1,4,5,6-tetrahydronicotinic acid, and α-ketoisovaleric acid, demonstrated exceptionally high sensitivity and specificity in both cohorts, nearing 100%. In contrast, the clinical indicators, including HBcAb, log(HBsAg), and HBeAb, demonstrated lower and inconsistent sensitivity and specificity between the discovery and validation cohorts. Using HBcAb as a marker, the sensitivity was 87.5% with 76.9% specificity in the discovery cohort; however, the sensitivity dropped to 46.7% with 91.7% specificity in the validation cohort. Using log(HBsAg), the sensitivity was 84.6% with 69.2% specificity in the discovery cohort, compared to 85.7% sensitivity and 83.3% specificity in the validation cohort. For HBeAb, the separation of Hrp and Lrp had a sensitivity of 87.5% with 69.2% specificity in the discovery cohort, while the validation cohort showed 86.7% sensitivity and 91.7% specificity.
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Project description:BACKGROUND & AIMS: This study aimed to develop a pan-genotypic and multifunctional small interfering RNA (siRNA) against hepatitis B virus (HBV) with an efficient delivery system for treating chronic hepatitis B (CHB), and explore combined RNA interference (RNAi) and immune modulatory modalities for better viral control. METHODS: Twenty synthetic siRNAs targeting consensus motifs distributed across the whole HBV genome were designed and evaluated. The lipid nanoparticle (LNP) formulation was optimized by adopting HO-PEG2000-DMG lipid and modifying the molar ratio of traditional polyethylene glycol (PEG) lipid in LNP prescriptions. The efficacy and safety of this formulation in delivering siHBV (tLNP/siHBV) along with the mouse IL-2 (mIL-2) mRNA (tLNP/siHBVIL2) were evaluated in the rAAV-HBV1.3 mouse model. RESULTS: A siRNA combination (terms “siHBV”) with a genotypic coverage of 98.55% was selected, chemically modified, and encapsulated within an optimized LNP (tLNP) of high efficacy and security to fabricate a therapeutic formulation for CHB. The results revealed that tLNP/siHBV significantly reduced the expression of viral antigens and DNA (up to 3log10 reduction) in dose- and time-dependent manners at single-dose or multi-dose frequencies, with satisfactory safety profiles. Further studies showed that tLNP/siHBVIL2 enables additive antigenic and immune control of the virus, via introducing potent HBsAg clearance through RNAi and triggering strong HBV-specific CD4+ and CD8+ T cell responses by expressed mIL-2 protein. CONCLUSIONS: By adopting tLNP as nucleic acid nanocarriers, the co-delivery of siHBV and mIL-2 mRNA enables synergistic antigenic and immune control of HBV, thus offering a promising translational therapeutic strategy for treating CHB.
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Project description:Expression changes of competitive endogenous RNAs (ceRNAs) have been proposed to influence microRNA (miRNA) activity and thereby regulate other transcripts that contain miRNA binding sites. Here, we find that although miRNA levels define the extent of repression, they do not affect the magnitude of the ceRNA expression change required to observe derepression. Canonical 6-nt sites, which typically mediate modest repression, can nonetheless compete for miRNA binding, with potency ~20% of that observed for canonical 8-nt sites. Sites with extensive additional complementarity can be even more potent, but this occurs predominantly through miRNA degradation rather than competition. Cooperative binding of closely spaced sites for different miRNAs can also increase potency. These results provide quantitative insights into the stoichiometric relationship between miRNA and target abundance, target-site spacing and affinity requirements for ceRNA-mediated gene regulation and specify the unusual circumstances in which ceRNA-mediated gene regulation might be observed. Sixty-four mRNA profiles were generated of 1) primary hepatocytes of mice expressing variable levels of a recombinant Adenovirus expressing the transcript of AldolaseA (Ad-AldoA), containing sites matching miR-122, let-7, miR-192, miR-194 or a mutated site (no site) or 2) embryonic stem (ES) cells that were transfected with a Tet-inducible dual-color reporter construct expressing enhanced yellow fluorescent protein (eYFP) and mCherry that contains zero (0s) or three (3s) 8 nt miRNA seed matches for miR-293 or miR-92 in the 3� UTR. ES cells were sorted with a FACSAria IIIu flow cytometer into three bins based on their eYFP fluorescence intensity. All samples were sequenced in duplicates by an Illumina HiSeq 2500. Library preparation and sequencing were performed by Fasteris SA (Switzerland) or by the Functional Genomics Centre Zürich (FGCZ). Three small RNA profiles or either primary hepatocytes or embryonic stem cells were also generated by Solexa sequencing.
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Project description:Some ceRNA associated with lncRNA have been considered as possible diagnostic and therapeutic biomarkers for obstructive sleep apnea (OSA). We intend to identify the potential hub genes for the development of OSA, which will provide a foundation for the study of the molecular mechanism underlying OSA and for the diagnosis and treatment of OSA.We collected plasma samples from OSA patients and healthy controls for the detection of ceRNA using a chip. Based on the differential expression of lncRNA, we identified the target genes of miRNA that bind to lncRNAs. We then constructed lncRNA-related ceRNA networks, performed functional enrichment analysis and protein-protein interaction analysis, and performed internal and external validation of the expression levels of stable hub genes. Then, we conducted LASSO regression analysis on the stable hub genes, selected relatively significant genes to construct a simple and easy-to-use nomogram, validated the nomogram, and constructed the core ceRNA sub-network of key genes.We successfully identified 282 DElncRNAs and 380 DEmRNAs through differential analysis, and we constructed an OSA-related ceRNA network consisting of 292 miRNA-lncRNAs and 41 miRNA-mRNAs. Through PPI and hub gene selection, we obtained 7 additional robust hub genes, CCND2, WT1, E2F2, IRF1, BAZ2A, LAMC1, and DAB2. Using LASSO regression analysis, we created a nomogram with four predictors (CCND2, WT1, E2F2, and IRF1), and its area under the curve (AUC) is 1. Finally, we constructed a core ceRNA sub-network composed of 74 miRNA-lncRNA and 7 miRNA-mRNA nodes.Our study provides a new foundation for elucidating the molecular mechanism of lncRNA in OSA and for diagnosing and treating OSA.
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Project description:Comprehensive analysis of the mRNA-lncRNA co-expression profile and ceRNA networks patterns in chronic hepatitis B
| PRJNA562252 | ENA
Project description:With 350 million carriers worldwide who may suffer from serious sequelae, including hepatocellular carcinoma, chronic hepatitis B virus (CHB) infection remains an important health issue. Current antiviral therapies hardly eradicate the virus. Therefore, there are still imperative need to develop new therapeutic strategies and predictors for treatment response to cure the disease and avoid futile treatment. By taking the advantage of having the paired liver biopsy samples of IFNalpha responders before/after treatment and pretreatment samples from responders and non-responders, we could characterize the intrahepatic expression profiles associated with necroinflammatory activity and the profiles/signature potentially predictive of response to IFNalpha therapy for CHB in this study. RNA was extracted from pairedliver tissues for gene expression analysis. The gene expression profiles of seven paired liver biopsy samples of IFNalpha responders before/after treatment and other 3 pre- treatment samples were obtained by Affymatrix U133plus2 microarray. We also pooled samples of 11 responders and 11 non-responders to perform affymatrix EXON ST 1.0 array. This dataset is part of the TransQST collection.
2017-02-09 | E-GEOD-66698 | biostudies-arrayexpress