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1.
Life (Basel) ; 13(1)2022 Dec 27.
Article in English | MEDLINE | ID: mdl-36676027

ABSTRACT

Network theory has attracted much attention from the biological community because of its high efficacy in identifying tumor-associated genes. However, most researchers have focused on single networks of single omics, which have less predictive power. With the available multiomics data, multilayer networks can now be used in molecular research. In this study, we achieved this with the construction of a bilayer network of DNA methylation sites and RNAs. We applied the network model to five types of tumor data to identify key genes associated with tumors. Compared with the single network, the proposed bilayer network resulted in more tumor-associated DNA methylation sites and genes, which we verified with prognostic and KEGG enrichment analyses.

2.
Life Sci ; 203: 193-202, 2018 Jun 15.
Article in English | MEDLINE | ID: mdl-29705350

ABSTRACT

AIMS: The antihypertensive mechanism (s) of the epigallocatechin-3-gallate (EGCG), a major effective component in green tea, might associate with microRNAs (miRNAs). Here, we aimed to investigate which microRNA in aorta of spontaneously hypertensive rats (SHRs) were modulated by administration of EGCG and its mechanism. MAIN METHODS: The pharmacokinetic behaviors of EGCG and epigallocatechin (EGC) in Sprague-Dawley rats were analyzed by HPLC and DRUG AND STATISTICS software. Blood pressure of SHRs was monitored by the tail-cuff method, the miRNomes of aorta from SHRs was analyzed with deep sequencing, and expression of hypertension-associated miRNAs with significant change and their host genes and target genes were validated by real-time PCR and Western blot. KEY FINDINGS: The plasma deposition of EGCG and EGC best fitted a mono-compartmental model with maximum plasma concentration post-dose (Cmax, 6.65 vs 4.45 µg/ml) and the corresponding time (Tmax, 15 vs 10 min). Systolic blood pressure (SBP) of SHRs decreased to the lowest point by 34.04 mmHg and recovered by 23.39 mmHg after 15 and 30 min of administration at dose of 300 mg/kg BW EGCG, respectively, and it decreased again at 60 min and recovered at time 2 h. Total 35 upregulated and 18 downregulated miRNAs were identified compared to the control group (p < .01) after EGCG administration. Expression of hypertension-associated miRNA-126a-3p and miRNA-150-5p were further validated. In turn, their host gene and target genes were up-regulated and down-regulated, respectively. SIGNIFICANCE: Our results indicated that miRNA-150-5p might be involved in the antihypertensive effect of EGCG through SP1/AT1R pathway.


Subject(s)
Antihypertensive Agents/pharmacology , Aorta/metabolism , Catechin/analogs & derivatives , Gene Expression Regulation/drug effects , Hypertension/genetics , MicroRNAs/genetics , Tea/chemistry , Animals , Aorta/drug effects , Biomarkers/metabolism , Blood Pressure/drug effects , Catechin/pharmacology , Gene Expression Profiling , Hypertension/drug therapy , Hypertension/pathology , Male , Rats , Rats, Inbred SHR , Rats, Sprague-Dawley
3.
Article in English | MEDLINE | ID: mdl-26552436

ABSTRACT

The functional screening of compounds is an important topic in chemistry and biomedicine that can uncover the essential properties of compounds and provide information concerning their correct use. In this study, we investigated the bioactive compounds reported in Selleckchem, which were assigned to 22 pathways. A computational method was proposed to identify the pathways of the bioactive compounds. Unlike most existing methods that only consider compound structural information, the proposed method adopted both the structural and interaction information from the compounds. The total accuracy achieved by our method was 61.79% based on jackknife analysis of a dataset of 1,832 bioactive compounds. Its performance was quite good compared with that of other machine learning algorithms (with total accuracies less than 46%). Finally, some of the false positives obtained by the method were analyzed to investigate the likelihood of compounds being annotated to new pathways.


Subject(s)
Algorithms , Computational Biology , Molecular Dynamics Simulation , Small Molecule Libraries/chemistry , Databases, Chemical , High-Throughput Screening Assays , Machine Learning , Molecular Structure
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