Protective effect of peroxisome proliferator-activated receptor- in regulating the early inflammation response to extended hepatectomy from a comparative transcriptomic analysis

The regulation mechanism of small-for-size syndrome remains unclear. Thus, we aimed to analyze the molecular profiles following extended hepatectomy and identify the therapeutic target. Major hepatectomy and extended hepatectomy were performed in the rat model, and the remnant livers were obtained dynamically for the high-throughput transcriptome analysis to identify the differentially expressed genes (DEGs). The general framework for weighted gene co-expression network analysis (WGCNA) was employed to explore the expression patterns of DEGs. As result, WGCNA identified 10 distinct gene co-expression modules according to the correlation between module eigengene and different postoperative time-points. The magenta module and the lightcyan module were found positively correlated with not extended hepatectomy but major hepatectomy. In the lightcyan module, peroxisome proliferator-activated receptor- (PPAR) was selected and verified the down-regulation in the remnant liver following extended hepatectomy in rats and humans. Besides, administration of PPAR agonist attenuated hepatic inflammation injury while PPAR antagonist increased liver inflammation injury after extended hepatectomy in rats, marked by the significantly changed aminotransferases, tumor necrosis factor- and interleukin-6 levels in the plasm, and histological Suzuki criteria. Consequently, DEGs and their molecular profiles after extended hepatectomy were identified, and PPAR might be a potential therapy target for small-for-size syndrome.

Identifying ceRNA Networks Associated With the Susceptibility and Persistence of Atrial Fibrillation Through Weighted Gene Co-Expression Network Analysis

Background: Atrial fibrillation (AF) is the most common arrhythmia. We aimed to construct competing endogenous RNA (ceRNA) networks associated with the susceptibility and persistence of AF by applying the weighted gene co-expression network analysis (WGCNA) and prioritize key genes using the random walk with restart on multiplex networks (RWR-M) algorithm.Methods: RNA sequencing results from 235 left atrial appendage samples were downloaded from the GEO database. The top 5,000 lncRNAs/mRNAs with the highest variance were used to construct a gene co-expression network using the WGCNA method. AF susceptibility- or persistence-associated modules were identified by correlating the module eigengene with the atrial rhythm phenotype. Using a module-specific manner, ceRNA pairs of lncRNA–mRNA were predicted. The RWR-M algorithm was applied to calculate the proximity between lncRNAs and known AF protein-coding genes. Random forest classifiers, based on the expression value of key lncRNA-associated ceRNA pairs, were constructed and validated against an independent data set.Results: From the 21 identified modules, magenta and tan modules were associated with AF susceptibility, whereas turquoise and yellow modules were associated with AF persistence. ceRNA networks in magenta and tan modules were primarily involved in the inflammatory process, whereas ceRNA networks in turquoise and yellow modules were primarily associated with electrical remodeling. A total of 106 previously identified AF-associated protein-coding genes were found in the ceRNA networks, including 16 that were previously implicated in the genome-wide association study. Myocardial infarction–associated transcript (MIAT) and LINC00964 were prioritized as key lncRNAs through RWR-M. The classifiers based on their associated ceRNA pairs were able to distinguish AF from sinus rhythm with respective AUC values of 0.810 and 0.940 in the training set and 0.870 and 0.922 in the independent test set. The AF-related single-nucleotide polymorphism rs35006907 was found in the intronic region of LINC00964 and negatively regulated the LINC00964 expression.Conclusion: Our study constructed AF susceptibility- and persistence-associated ceRNA networks, linked genetics with epigenetics, identified MIAT and LINC00964 as key lncRNAs, and constructed random forest classifiers based on their associated ceRNA pairs. These results will help us to better understand the mechanisms underlying AF from the ceRNA perspective and provide candidate therapeutic and diagnostic tools.

High throughput circRNA sequencing analysis reveals novel insights into the mechanism of nitidine chloride against hepatocellular carcinoma

Nitidine chloride (NC) has been demonstrated to have an anticancer effect in hepatocellular carcinoma (HCC). However, the mechanism of action of NC against HCC remains largely unclear. In this study, three pairs of NC-treated and NC-untreated HCC xenograft tumour tissues were collected for circRNA sequencing analysis. In total, 297 circRNAs were differently expressed between the two groups, with 188 upregulated and 109 downregulated, among which hsa_circ_0088364 and hsa_circ_0090049 were validated by real-time quantitative polymerase chain reaction. The in vitro experiments showed that the two circRNAs inhibited the malignant biological behaviour of HCC, suggesting that they may play important roles in the development of HCC. To elucidate whether the two circRNAs function as “miRNA sponges” in HCC, we identified circRNA-miRNA and miRNA-mRNA interactions by using the CircInteractome and miRwalk, respectively. Subsequently, 857 miRNA-associated differently expressed genes in HCC were selected for weighted gene co-expression network analysis. Module Eigengene turquoise with 423 genes was found to be significantly related to the survival time, pathology grade and TNM stage of HCC patients. Gene functional enrichment analysis showed that the 423 genes mainly functioned in DNA replication- and cell cycle-related biological processes and signalling cascades. Eighteen hubgenes (SMARCD1, CBX1, HCFC1, RBM12B, RCC2, NUP205, ECT2, PRIM2, RBM28, COPS7B, PRRC2A, GPR107, ANKRD52, TUBA1B, ATXN7L3, FUS, MCM8 and RACGAP1) associated with clinical outcomes of HCC patients were then identified. These findings showed that the crosstalk between hsa_circ_0088364 and hsa_circ_0090049 and their competing mRNAs may play important roles in HCC, providing interesting clues into the potential of circRNAs as therapeutic targets of NC in HCC.