Zhou Y.-M.,Shandong University |
Zheng P.-X.,Yangpu District Central Hospital |
Yang Y.-Q.,Shanghai JiaoTong University |
Ge Z.-M.,Shandong University |
Kang W.-Q.,Shandong University
International Journal of Molecular Medicine | Year: 2013
Atrial fibrillation (AF) is the most common form of sustained cardiac arrhythmia responsible for substantial morbidity and significantly increased mortality rates. A growing body of evidence documents the important role of genetic defects in the pathogenesis of AF. However, AF is a heterogeneous disease and the genetic determinants for AF in an overwhelming majority of patients remain unknown. In the present study, a cohort of 100 unrelated patients with lone AF and a total of 200 unrelated, ethnically matched healthy individuals used as controls, were recruited. The whole coding exons and splice junctions of the pituitary homeobox 2c (PITX2c) gene, which encodes a paired-like homeobox transcription factor required for normal cardiovascular morphogenesis, were sequenced in the 100 patients and 200 control subjects. The causative potential of the identified mutation of PITX2c was predicted by MutationTaster and PolyPhen-2. The functional characteristics of the PITX2c mutation were assayed using a dual-luciferase reporter assay system. Based on the results, a novel heterozygous PITX2c mutation (p.T97A) was identified in a patient with AF. The missense mutation was absent in the 400 reference chromosomes and was automatically predicted to be disease-causing. Multiple alignments of PITX2c protein sequences across species revealed that the altered amino acid was completely conserved evolutionarily. Functional analysis demonstrated that the mutant PITX2c protein was associated with significantly decreased transcriptional activity when compared with its wild-type counterpart. The findings of the present study firstly link the PITX2c loss-of-function mutation to lone AF, and provide novel insight into the molecular mechanisms underlying AF, suggesting the potential implications for the early prophylaxis and allele-specific therapy of this common type of arrhythmia.
Hu L.-L.,Shanghai University |
Li Z.,Yangpu District Central Hospital |
Wang K.,Shanghai University |
Niu S.,CAS Shanghai Institutes for Biological Sciences |
And 3 more authors.
Biopolymers | Year: 2011
Protein methylation, one of the most important post-translational modifications, typically takes place on arginine or lysine residue. The reversible modification involves a series of basic cellular processes. Identification of methyl proteins with their sites will facilitate the understanding of the molecular mechanism of methylation. Besides the experimental methods, computational predictions of methylated sites are much more desirable for their convenience and fast speed. Here, we propose a method dedicated to predicting methylated sites of proteins. Feature selection was made on sequence conservation, physicochemical/biochemical properties, and structural disorder by applying maximum relevance minimum redundancy and incremental feature selection methods. The prediction models were built according to nearest the neighbor algorithm and evaluated by the jackknife cross-validation. We built 11 and 9 predictors for methylarginine and methyllysine, respectively, and integrated them to predict methylated sites. As a result, the average prediction accuracies are 74.25%, 77.02% for methylarginine and methyllysine training sets, respectively. Feature analysis suggested evolutionary information, and physicochemical/biochemical properties play important roles in the recognition of methylated sites. These findings may provide valuable information for exploiting the mechanisms of methylation. Our method may serve as a useful tool for biologists to find the potential methylated sites of proteins. Copyright © 2011 Wiley Periodicals, Inc.
He Z.,CAS Shanghai Institutes for Biological Sciences |
He Z.,Fudan University |
Zhang J.,Yangpu District Central Hospital |
Shi X.-H.,CAS Shanghai Institutes for Biological Sciences |
And 6 more authors.
PLoS ONE | Year: 2010
Background: Study of drug-target interaction networks is an important topic for drug development. It is both time-consuming and costly to determine compound-protein interactions or potential drug-target interactions by experiments alone. As a complement, the in silico prediction methods can provide us with very useful information in a timely manner. Methods/Principal Findings:To realize this, drug compounds are encoded with functional groups and proteins encoded by biological features including biochemical and physicochemical properties. The optimal feature selection procedures are adopted by means of the mRMR (Maximum Relevance Minimum Redundancy) method. Instead of classifying the proteins as a whole family, target proteins are divided into four groups: enzymes, ion channels, G-protein- coupled receptors and nuclear receptors. Thus, four independent predictors are established using the Nearest Neighbor algorithm as their operation engine, with each to predict the interactions between drugs and one of the four protein groups. As a result, the overall success rates by the jackknife cross-validation tests achieved with the four predictors are 85.48%, 80.78%, 78.49%, and 85.66%, respectively. Conclusion/Significance: Our results indicate that the network prediction system thus established is quite promising and encouraging. © 2010 He et al.
Li S.,Wannan Medical College |
Xie Y.,Yangpu District Central Hospital |
Zhang W.,Wannan Medical College |
Gao J.,Hefei First Peoples Hospital |
And 5 more authors.
Journal of Surgical Research | Year: 2015
Background: Interferon alpha-inducible protein 27 (IFI27) is an interferon alpha-inducible protein, which was found to be upregulated in some cancers, such as breast cancer, squamous cell carcinoma, hepatocellular carcinoma, and serous ovarian carcinoma. However, the role of IFI27 in ovarian cancer remains to be elucidated. This study was designed to investigate the role of IFI27 in ovarian cancer tumorigenicity. Materials and methods: The expression of IFI27 was examined in ovarian cancer tissues and cell lines by real time quantitative reverse transcription polymerase chain reaction and immunohistochemistry. The cell migration and invasion was investigated by wound healing and transwell invasion assay. The epithelial-mesenchymal transition markers were detected by Western blotting and the stemness was evaluated by sphere formation. The tumor growth was examined in the athymic mice model. Results: We found that IFI27 is overexpressed in ovarian cancer and associated with patients' survival. Interestingly, we further observed that the expression of IFI27 was associated with the expression of mesenchymal marker vimentin in ovarian cancer. Overexpression of IFI27 induces epithelial-mesenchymal transition and promotes epithelial ovarian cancer cells migration and invasion, tumorigenicity, stemness, and drug resistance. Moreover, overexpression of IFI27 is associated with loss of miR-502 in ovarian cancer. Reexpression of miR-502 inhibits IFI27-induced tumorigenicity, migration, and drug resistance. Conclusions: These data suggested that IFI27 may be a potential target for developing novel diagnosis strategies and therapeutic interventions. © 2015 Elsevier Inc. All rights reserved.
Ke X.,Yangpu District Central Hospital |
Dou F.,Yangpu District Central Hospital |
Cheng Z.,Yangpu District Central Hospital |
Dai H.,Yangpu District Central Hospital |
And 4 more authors.
European Journal of Obstetrics Gynecology and Reproductive Biology | Year: 2013
Objective: To investigate the expression of cyclooxygenase-2 (COX-2) in uterine fibroids and healthy uterine smooth muscle as well as its role in the pathogenesis of uterine fibroids. Methods: We collected uterine fibroid tissues and their paired adjacent healthy uterine smooth muscle tissues from 30 cases of uterine fibroids. We used immunohistochemistry and quantitative real-time PCR, as well as western blot to detect COX-2 expression. Using the COX-2 inhibitors NS-398 and celecoxib, we observed the response to the inhibitors in the healthy and fibroid smooth muscle cell pairs. Results: COX-2 was detected by immunohistochemistry in both uterine fibroids and uterine smooth muscle, with higher immunoreactivity in uterine fibroids; the positive index of the smooth muscle cells was 11.90 and the positive index of uterine fibroids cells was 46.50 (P < 0.05). The expression of COX-2 mRNA in uterine fibroids was higher (0.122 ± 0.062) than in normal smooth muscle tissue (0.025 ± 0.009; P < 0.05). Also, the western blot results showed that COX-2 expression was significantly higher in uterine fibroid cases, as compared to the expression in uterine smooth muscle. Immunofluorescence showed that the occurrence of COX-2 was obviously higher in smooth muscle cells of uterine fibroids than in the healthy smooth muscle cells. NS-398 or celecoxib significantly inhibited the proliferation of smooth muscle cells of uterine fibroids, but did not inhibit the proliferation of healthy smooth muscle cells. Accordingly, NS-398 or celecoxib significantly reduced the expression of the downstream metabolite of COX-2, PGE2, in the smooth muscle cells of uterine fibroids, but not in healthy smooth muscle cells. Conclusion: COX-2 expression in uterine fibroids was significantly higher than in healthy uterine smooth muscles. The inhibition of COX-2 activity significantly reduced the proliferation of smooth muscle cells of the uterine fibroids, suggesting that COX-2 plays an important role in the pathogenesis of uterine fibroids. © 2013 Elsevier Ireland Ltd.