Proteome and Phosphoproteome Analyses Reveal the Kinase Regulatory Network Involved in Glycogen Synthesis Kinase 3ß.

Diabetic nephropathy is the most common chronic kidney disease in the world and the main cause of end-stage renal disease (ESRD). The structural integrity of podocytes is fundamental to the normal function of the glomerulus, and the role of glycogen synthase kinase 3ß (GSK-3ß) in podocytes is complicated. A thorough understanding of GSK-3ß is crucial to understand the mechanism of diabetic nephropathy. To analyze the roles of GSK-3ß in podocytes, GSK-3ß knockdown lentivirus by clustered regularly interspaced short palindromic repeats (CRISPR)-CRISPR-associated protein (Cas)9 was applied to establish stable cell lines. Mass spectrometry was utilized to search for differentially expressed proteins. Consequently, we found 34 proteins with higher levels and 115 proteins with lower levels in GSk-3ß knockdown cells than in control cells and identified 581 phosphosites with higher phosphorylation levels and 288 phosphosites with lower phosphorylation levels. We performed functional enrichment analysis of these proteins and phosphorylated proteins based on public databases. Enrichment analysis revealed that GSK-3ß participates in the spliceosome, Hippo signaling pathway, actin binding, structural molecule activity, and other pathways. Then, we used motif analysis of phosphate sites to determine 89 conserved motifs based on 1,068 phosphoserine (pS) sites and 15 conserved motifs in view of 104 phosphothreonine (pT) sites. Additionally, protein-protein interaction network analysis was carried out using the STRING database. Cytoscape's add-on Molecular Complex Detection (MCODE) was used to analyze key and core protein groups. In quantitative differential protein analysis, four MCODEs were obtained, and 22 MCODEs were obtained in the analysis of the phosphoproteome of differentially expressed proteins. Finally, we analyzed the kinase regulatory network in podocytes after GSK-3ß knockdown and identified 299 protein kinases and 3,460 significantly changed phosphorylation modification sites on 1,574 proteins. These results will be valuable for further research on GSK-3ß.

Determining the influence of high glucose on exosomal lncRNAs, mRNAs, circRNAs and miRNAs derived from human renal tubular epithelial cells.

Diabetic nephropathy is a lethal disease that can lead to chronic kidney disease and end-stage kidney disease. Exosomes, which are nanosized extracellular vesicles, are closely involved in intercellular communication. Most importantly, exosomes play critical roles in disease occurrence and development. However, the function of exosomes in diabetic nephropathy progression has not been fully elucidated. In the present study, we determined the expression profiles and differences of lncRNAs, mRNAs, circRNAs and miRNAs in exosomes derived from human renal tubular epithelial cells with or without high glucose (HG) treatment. A total of 169 lncRNAs, 885 mRNAs, 3 circRNAs and 152 miRNAs were differentially expressed in exosomes secreted by HG-challenged HK-2 cells (HG group) compared with controls (NC group). The functions of differentially expressed mRNAs, mRNAs colocalized or coexpressed with differentially expressed lncRNAs (DElncRNAs), potential target genes of miRNAs and source genes of circRNAs were investigated by Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis. According to these differentially expressed RNAs, we established an integrated circRNA-lncRNA-miRNA-mRNA regulatory network. In conclusion, our study suggested that exosomal lncRNAs, mRNAs, circRNAs and miRNAs participate in the progression of diabetic nephropathy and may be possible biomarkers and therapeutic targets in diabetic nephropathy.

Integrated Analysis of a Risk Score System Predicting Prognosis and a ceRNA Network for Differentially Expressed lncRNAs in Multiple Myeloma.

Long non-coding RNAs (lncRNAs) are non-protein-coding RNAs longer than 200 nucleotides. Accumulating evidence demonstrates that lncRNA is a potential biomarker for cancer diagnosis and prognosis. However, there are no prognostic biomarkers and lncRNA models for multiple myeloma (MM). Hence, it is necessary to screen novel lncRNA that can potentially participate in the initiation and progression of MM and consequently construct a risk score system for the disease. Raw microarray datasets were obtained from the Gene Expression Omnibus website. Weighted gene co-expression network analysis and principal component analysis identified 12 lncRNAs of interest. Then, univariate, least absolute shrinkage and selection operator Cox regression and multivariate Cox hazard regression analysis identified two lncRNAs (LINC00996 and LINC00525) that were formulated to construct a risk score system to predict survival. Receiver operating characteristic analysis certificated the superior performance in predicting 3-year overall survival (area under the curve = 0.829). The similar prognostic values of the two-lncRNA signature were also observed in the tested The Cancer Genome Atlas dataset. Furthermore, two other lncRNAs (LINC00324 and LINC01128) were differentially expressed between CD138+ plasma cells from normal donors and MM patients and were verified to be associated with cancer stage in the Gene Expression Omnibus dataset. A lncRNA-mediated competing endogenous RNA network, including 2 lncRNAs, 12 mitochondrial RNAs, and 103 target messenger RNAs, was constructed. In conclusion, we developed a two-lncRNA expression signature to predict the prognosis of MM and constructed a key lncRNA-based competing endogenous RNA network in MM. These lncRNAs were associated with survival and are probably involved in the occurrence and progression of MM.

Expression Profile Analysis of m6A RNA Methylation Regulators Indicates They Are Immune Signature Associated and Can Predict Survival in Kidney Renal Cell Carcinoma.

N6-Methyladenosine (m6A) refers to the methylation modification occurring at the nitrogen-6 position of adenosine. Many human physiological processes such as modulation of spermatogenesis are caused by m6A RNA modifications. However, the relationship between m6A RNA methylation regulators and kidney renal clear cell carcinoma (KIRC) remains rarely investigated. This work aimed to explore the influence of m6A RNA methylation regulators in KIRC. We examined abnormally expressed m6A RNA methylation regulators among different clinicopathological features of KIRC. We recognized three subgroups (KIRC1, KIRC2, and KIRC3) with significant differences in overall survival through consensus clustering of m6A RNA methylation regulators. Surprisingly, KIRC2 displayed elevated immune activity, but high proportions of immune-inhibitory cells (Tregs and myeloid-derived suppressor cell) based on single-sample gene set enrichment analysis (ssGSEA) and CIBERSORT analysis. Moreover, the KIRC2 subgroup had the lowest tumor mutation burden levels and the highest expression levels of 80% (12/15) of co-inhibitory molecules. Next, correlation analysis indicated that RBM15B expression was negatively correlated with multiple immune signatures, which was verified by ssGSEA and CIBERSORT analyses. Multiple immune-related and cancer-related pathways were enriched in the group with high RBM15B expression. Furthermore, a four-m6A RNA methylation regulator-based risk signature was constructed based on an ArrayExpress (E-MTAB-3267) dataset and confirmed in the The Cancer Genome Atlas (TCGA) testing cohort. In conclusion, our study successfully classified TCGA samples into three subgroups with different immune signatures, and suggested that the worse prognosis of KIRC2 is probably mediated by immune evasion. These findings will facilitate personalized immunotherapy in patients with KIRC. In addition, the risk score system was revealed as an independent prognostic marker that can predict survival in KIRC patients.