DataSheet1_N7-Methylguanosine-Related lncRNAs: Integrated Analysis Associated With Prognosis and Progression in Clear Cell Renal Cell Carcinoma.ZIP

N7-Methylguanosine (m7G) and long non-coding RNAs (lncRNAs) have been widely reported to play an important role in cancer. However, there is little known about the relationship between m7G-related lncRNAs and clear cell renal cell carcinoma (ccRCC). To find new potential biomarkers and construct an m7G-related lncRNA prognostic signature for ccRCC, we retrieved transcriptome data and clinical data from The Cancer Genome Atlas (TCGA), and divided the entire set into train set and test set with the ratio of 1:1 randomly. The m7G-related lncRNAs were identified by Pearson correlation analysis (|coefficients| > 0.4, and p < 0.001). Then we performed the univariate Cox regression and least absolute shrinkage and selection operator (LASSO) Cox regression analysis to construct a 12 m7G-related lncRNA prognostic signature. Next, principal component analysis (PCA), the Kaplan–Meier method, time-dependent receiver operating characteristics (ROC) were made to verify and evaluate the risk signature. A nomogram based on the risk signature and clinical parameters was developed and showed high accuracy and reliability for predicting the overall survival (OS). Functional enrichment analysis (GO, KEGG and GSEA) was used to investigate the potential biological pathways. We also performed the analysis of tumor mutation burden (TMB), immunological analysis including immune scores, immune cell infiltration (ICI), immune function, tumor immune escape (TIE) and immunotherapeutic drug in our study. In conclusion, using the 12 m7G-related lncRNA risk signature as a prognostic indicator may offer us insight into the oncogenesis and treatment response prediction of ccRCC.</p

DataSheet_1_Identification of copper-related biomarkers and potential molecule mechanism in diabetic nephropathy.zip

BackgroundDiabetic nephropathy (DN) is a chronic microvascular complication in patients with diabetes mellitus, which is the leading cause of end-stage renal disease. However, the role of copper-related genes (CRGs) in DN development remains unclear.Materials and methodsCRGs were acquired from the GeneCards and NCBI databases. Based on the GSE96804 and GSE111154 datasets from the GEO repository, we identified hub CRGs for DN progression by taking the intersection of differentially expressed CRGs (DECRGs) and genes in the key module from Weighted Gene Co-expression Network Analysis. The Maximal Clique Centrality algorithm was used to identify the key CRGs from hub CRGs. Transcriptional factors (TFs) and microRNAs (miRNAs) targeting hub CRGs were acquired from publicly available databases. The CIBERSORT algorithm was used to perform comparative immune cell infiltration analysis between normal and DN samples.ResultsEighty-two DECRGs were identified between normal and DN samples, as were 10 hub CRGs, namely PTGS2, DUSP1, JUN, FOS, S100A8, S100A12, NAIP, CLEC4E, CXCR1, and CXCR2. Thirty-nine TFs and 165 miRNAs potentially targeted these 10 hub CRGs. PTGS2 was identified as the key CRG and FOS as the most significant gene among all of DECRGs. RELA was identified as the hub TF interacting with PTGS2 by taking the intersection of potential TFs from the ChEA and JASPAR public databases. let-7b-5p was identified as the hub miRNA targeting PTGS2 by taking the intersection of miRNAs from the miRwalk, RNA22, RNAInter, TargetMiner, miRTarBase, and ENCORI databases. Similarly, CREB1, E2F1, and RELA were revealed as hub TFs for FOS, and miR-338-3p as the hub miRNA. Finally, compared with those in healthy samples, there are more infiltrating memory B cells, M1 macrophages, M2 macrophages, and resting mast cells and fewer infiltrating activated mast cells and neutrophils in DN samples (all pConclusionThe 10 identified hub copper-related genes provide insight into the mechanisms of DN development. It is beneficial to examine and understand the interaction between hub CRGs and potential regulatory molecules in DN. This knowledge may provide a novel theoretical foundation for the development of diagnostic biomarkers and copper-related therapy targets in DN.</p

Additional file 4: Figure S3. of The association between obstructive sleep apnea and metabolic syndrome: a systematic review and meta-analysis

Galbraith plot. (TIFF 44 kb

Data_Sheet_1_LncRNA NBR2 Inhibits the Malignancy of Thyroid Cancer, Associated With Enhancing the AMPK Signaling.docx

Long non-coding RNA NBR2 is a transcript of the neighbor of BRCA1 gene 2 and can regulate tumor development. However, there is little information on the role of NBR2 in the progression of thyroid cancers (TC). Here, we show that NBR2 expression is down-regulated in TC tissues and associated with histologic subtypes of TC. NBR2 expression was variably reduced in different TC cells. While NBR2 silencing significantly enhanced the malignancy of BCPAP cells by increasing cell proliferation, clonogenicity, wound healing, and invasion as well as tumor growth in vivo, and decreasing spontaneous apoptosis, NBR2 over-expression had opposite effects in BHT101 cells. Furthermore, treatment with A-769662 (a specific AMPK activator), like NBR2 over-expression, significantly attenuated the malignancy of BHT101 cells while treatment with Compound C (a specific AMPK inhibitor) significantly rescued that NBR2-reduced malignancy of BHT101 cells. In comparison with non-tumor thyroid epithelial Nthy-ori 3-1 cells, obviously increased GLUT-1 expression, but decreased AMPK and ACC phosphorylation were detected in TC cells. While NBR2 silencing further enhanced GLUT-1 expression and reduced AMPK and ACC phosphorylation as well as the EMT process in BCPAP cells. NBR2 over-expression also had opposite effects in BHT101 cells. Similar patterns of GLUT-1 expression and AMPK and ACC phosphorylation were detected in the different types of xenograft TC tumors in vivo. Therefore, such data indicated that NBR2 acted as a tumor suppressor of thyroid cancers associated with enhancing the AMPK signaling and NBR2 may be a potential biomarker and therapeutic target for thyroid cancers.</p

Cdk5 could phosphorylate the adjacent S1627 in the LRRK2 R1628P mutant.

a. The R1628P mutation increase the binding affinity of LRRK2 with Cdk5. Primary-cultured cortical neurons were transfected with vehicle or LRRK2 (WT, R1628P). After 24 h, the exogenous LRRK2 was immunoprecipitated using anti-HA antibody, and the level of bound Cdk5 was measured by Western blotting. The bottom panel shows the loading control of HA-LRRK2 and Cdk5 used in the lysates. b. Cdk5 phosphorylates Serine 1627 (S1627) in R1628P mutant. Recombinant GST-tagged LRRK2 (COR domain, amino acids 1535~1878), including wild-type (WT), R1628P mutant and S1627A:R1628P double mutant, were purified. The GST-tagged LRRK2 recombinant protein were phosphorylated by active Cdk5/p35 and γ-32P-ATP in vitro, and the phosphorylation signals were analyzed by autoradiography. (top panel, about 60KD). The same membrane was probed with anti‑GST, Cdk5 or p35 antibody as a loading control (bottom panel). c. Cdk5 phosphorylates S1627 in cells. The HA-tagged LRRK2 (WT, R1628P and S1627A:R1628P) plasmids were cotransfected with Cdk5 and p35 in HEK293 cells. After 24 h of transfection, the LRRK2 were immuneprecipitated using an anti-HA antibody from lysates, and phosphorylation of LRRK2 were measured by Western blotting using a phospho-(Serine/Threonine)-Proline (pS/TP) antibody and anti-LRRK2 phospho S935 antibody. HA-LRRK2, Cdk5, p35, and actin levels were determined by Western blotting as a loading control.</p

Parkinson-Related LRRK2 Mutation R1628P Enables Cdk5 Phosphorylation of LRRK2 and Upregulates Its Kinase Activity

<div><p>Background</p><p>Recent studies have linked certain single nucleotide polymorphisms in the <i>leucine-rich repeat kinase 2 (LRRK2)</i> gene with Parkinson’s disease (PD). Among the mutations, <i>LRRK2</i> c.4883G>C (R1628P) variant was identified to have a significant association with the risk of PD in ethnic Han-Chinese populations. But the molecular pathological mechanisms of R1628P mutation in PD is still unknown.</p><p>Principle Findings</p><p>Unlike other LRRK2 mutants in the Roc-COR-Kinase domain, the R1628P mutation didn’t alter the LRRK2 kinase activity and promote neuronal death directly. LRRK2 R1628P mutation increased the binding affinity of LRRK2 with Cyclin-dependent kinase 5 (Cdk5). Interestingly, R1628P mutation turned its adjacent amino acid residue S1627 on LRRK2 protein to a novel phosphorylation site of Cdk5, which could be defined as a typical type II (+) phosphorylation-related single nucleotide polymorphism. Importantly, we showed that the phosphorylation of S1627 by Cdk5 could activate the LRRK2 kinase, and neurons ectopically expressing R1628P displayed a higher sensitivity to 1-methyl-4-phenylpyridinium, a bioactive metabolite of environmental toxin MPTP, in a Cdk5-dependent manner.</p><p>Conclusion</p><p>Our data indicate that Parkinson-related LRRK2 mutation R1628P leads to Cdk5 phosphorylation of LRRK2 at S1627, which would upregulate the kinase activity of LRRK2 and consequently cause neuronal death.</p></div

Data_Sheet_2_LncRNA NBR2 Inhibits the Malignancy of Thyroid Cancer, Associated With Enhancing the AMPK Signaling.docx

Long non-coding RNA NBR2 is a transcript of the neighbor of BRCA1 gene 2 and can regulate tumor development. However, there is little information on the role of NBR2 in the progression of thyroid cancers (TC). Here, we show that NBR2 expression is down-regulated in TC tissues and associated with histologic subtypes of TC. NBR2 expression was variably reduced in different TC cells. While NBR2 silencing significantly enhanced the malignancy of BCPAP cells by increasing cell proliferation, clonogenicity, wound healing, and invasion as well as tumor growth in vivo, and decreasing spontaneous apoptosis, NBR2 over-expression had opposite effects in BHT101 cells. Furthermore, treatment with A-769662 (a specific AMPK activator), like NBR2 over-expression, significantly attenuated the malignancy of BHT101 cells while treatment with Compound C (a specific AMPK inhibitor) significantly rescued that NBR2-reduced malignancy of BHT101 cells. In comparison with non-tumor thyroid epithelial Nthy-ori 3-1 cells, obviously increased GLUT-1 expression, but decreased AMPK and ACC phosphorylation were detected in TC cells. While NBR2 silencing further enhanced GLUT-1 expression and reduced AMPK and ACC phosphorylation as well as the EMT process in BCPAP cells. NBR2 over-expression also had opposite effects in BHT101 cells. Similar patterns of GLUT-1 expression and AMPK and ACC phosphorylation were detected in the different types of xenograft TC tumors in vivo. Therefore, such data indicated that NBR2 acted as a tumor suppressor of thyroid cancers associated with enhancing the AMPK signaling and NBR2 may be a potential biomarker and therapeutic target for thyroid cancers.</p

The Schematic diagram shows that the R1628P genetic mutation of LRRK2 provide a potential “two-hit” target of environment toxic MPP+-induced Cdk5 activation, and Cdk5 could phosphorylate the adjacent amino residue S1627 of R1628P mutation, thus activate LRRK2 kinase activity and cause neuronal death.

<p>The Schematic diagram shows that the R1628P genetic mutation of LRRK2 provide a potential “two-hit” target of environment toxic MPP+-induced Cdk5 activation, and Cdk5 could phosphorylate the adjacent amino residue S1627 of R1628P mutation, thus activate LRRK2 kinase activity and cause neuronal death.</p

Additional file 3: Figure S2. of The association between obstructive sleep apnea and metabolic syndrome: a systematic review and meta-analysis

Funnel plots among all studies including two conference reports that were not subsequently published. Two conference reports referred by Velazquez, 2011 and Papatsimpas, 2011. (TIFF 45 kb

Additional file 2: Figure S1. of The association between obstructive sleep apnea and metabolic syndrome: a systematic review and meta-analysis

Meta-analysis for all studies including two conference reports that were not subsequently published. Two conference reports referred by Velazquez, 2011 and Papatsimpas, 2011. OR: odds ratio; CI: confidence interval. (TIFF 156 kb