Objectives: Whether uric acid levels were associated with the progression of chronic kidney disease (CKD) remained controversial. This meta-analysis was aimed to assess the effect of lowering serum uric acid therapy on the progression of CKD to clarify the role of uric acid in the progression of CKD indirectly.Methods: Pubmed, Embase, the Cochrane library, CBM were searched for randomized controlled trials (RCTs) that assessed the efficiency of lowering serum uric acid therapy on the progression of CKD without language restriction. Summary estimates of weighted mean differences (WMDs) and relative risk (RR) were obtained by using random-effect or fixed-effect models. Sensitivity analyses were performed to identify the source of heterogeneity.Results: A total of 12 randomized controlled trials with 832 CKD participants were included in the analysis. Pooled estimate for eGFR was in favor of lowering serum uric acid therapy with a mean difference (MD) of 3.88 ml/min/1.73 m2, 95% CI 1.26–6.49 ml/min/1.73 m2, p = .004 and this was consistent with results for serum creatinine. The risk of worsening of kidney function or ESRD or death was significantly decreased in the treatment group compared to the control group (RR 0.39, 95% CI 0.28–0.52, p< .01).Conclusions: Uric acid-lowering therapy may be effective in retarding the progression of CKD. Further randomized controlled trials should be performed to confirm the effect of lowering serum uric acid therapy on the progression of CKD.

Triptolide is a major active component of Tripterygium wilfordii Hook F, which exerts marked immunosuppressive, anti-inflammatory and podocyte-protective effects. In this study, the ability of triptolide to inhibit inflammation and attenuate podocyte injury was examined in a rat model of diabetic nephropathy (DN). Type II diabetic rats with DN were treated with triptolide at a dose of 100 μg.kg−1.day−1. Following 8 weeks of triptolide treatment, the urine albumin level, kidney weight/body weight and the number of cells positive for ED-1 (a marker for rat mononuclear macrophages) in the kidney were assessed. The effects of triptolide on podocyte injury and chronic inflammation were analyzed using quantitative polymerase chain reaction (qPCR), western blotting and immunohistochemistry. Following triptolide treatment, the albuminuria in the type II diabetic rats was significantly reduced. Furthermore, the glomerular hypertrophy and foot process effacement were improved, and there was a recovery of the slit diaphragm associated with nephrin and podocin expression. The inflammation in the kidneys was also attenuated. Furthermore, triptolide significantly reduced the expression of transforming growth factor-β1 and osteopontin, and the infiltration of ED-1-positive cells into the kidney. The results demonstrated that triptolide markedly attenuated albuminuria and podocyte injury in the rat model of DN, which may have been correlated with the inhibition of inflammation and macrophage infiltration in the kidneys.

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Alterations of biological pathways can lead to oncogenesis. An overview of these oncogenic pathways would be highly valuable for researchers to reveal the pathogenic mechanism and develop novel therapeutic approaches for cancers. Here, we reviewed approximately 8500 literatures and documented experimentally validated cancer-pathway associations as benchmarking data set. This data resource includes 4709 manually curated relationships between 1557 paths and 49 cancers with 2427 upstream regulators in 7 species. Based on this resource, we first summarized the cancer-pathway associations and revealed some commonly deregulated pathways across tumor types. Then, we systematically analyzed these oncogenic pathways by integrating TCGA pan-cancer data sets. Multi-omics analysis showed oncogenic pathways may play different roles across tumor types under different omics contexts. We also charted the survival relevance landscape of oncogenic pathways in 26 tumor types, identified dominant omics features and found survival relevance for oncogenic pathways varied in tumor types and omics levels. Moreover, we predicted upstream regulators and constructed a hierarchical network model to understand the pathogenic mechanism of human cancers underlying oncogenic pathway context. Finally, we developed `CPAD’ (freely available at http://bio-bigdata.hrbmu.edu.cn/CPAD/), an online resource for exploring oncogenic pathways in human cancers, that integrated manually curated cancer-pathway associations, TCGA pan-cancer multi-omics data sets, drug–target data, drug sensitivity and multi-omics data for cancer cell lines. In summary, our study provides a comprehensive characterization of oncogenic pathways and also presents a valuable resource for investigating the pathogenesis of human cancer.