Identification and validation of key genes associated with non-small-cell lung cancer

Non-small-cell lung cancer (NSCLC) is one of the main causes of death induced by cancer globally. However, the molecular aberrations in NSCLC patients remain unclearly. In the present study, four messenger RNA microarray datasets (GSE18842, GSE40275, GSE43458, and GSE102287) were downloaded from the Gene Expression Omnibus (GEO) database. Differentially expressed genes (DEGs) between NSCLC tissues and adjacent lung tissues were obtained from GEO2R and the overlapping DEGs were identified. Moreover, functional and pathway enrichment were performed by Funrich, while the protein–protein interaction (PPI) network construction were obtained from STRING and hub genes were visualized and identified by Cytoscape software. Furthermore, validation, overall survival (OS) and tumor staging analysis of selected hub genes were performed by GEPIA. A total of 367 DEGs (95 upregulated and 272 downregulated) were obtained through gene integration analysis. The PPI network consisted of 94 nodes and 1036 edges in the upregulated DEGs and 272 nodes and 464 edges in the downregulated DEGs, respectively. The PPI network identified 46 upregulated and 27 downregulated hub genes among the DEGs, and six (such as CENPE, NCAPH, MYH11, LRRK2, HSD17B6, and A2M) of that have not been identified to be associated with NSCLC so far. Moreover, the expression differences of the mentioned hub genes were consistent with that in lung adenocarcinoma and lung squamous cell carcinoma in the TCGA database. Further analysis showed that all the six hub genes were associated with tumor staging except MYH11, while only the upregulated DEG CENPE was associated with the worse OS of patients with NSCLC. In conclusion, the current study showed that CENPE, NCAPH, MYH11, LRRK2, HSD17B6, and A2M might be the key genes contributed to tumorigenesis or tumor progression in NSCLC, further functional study is needed to explore the involved mechanisms.     

MiR-423-5p inhibition alleviates cardiomyocyte apoptosis and mitochondrial dysfunction caused by hypoxia/reoxygenation through activation of the wnt/β-catenin signaling pathway via targeting MYBL2

MicroRNA (miR) plays an integral role in cardiovascular diseases. M-iR-423-5p is aberrantly expressed in patients with myocardial infarction and heart failure. The aim of the present study was to study the roles and mechanisms of miR-423-5p in hypoxia/reoxygenation (H/R) mediated cardiomyocytes injury. H9C2 cells were transfected with negative control, miR-423-5p mimic, and inhibitor for 48 hr, followed by exposed to H/R condition. Cell apoptosis rate, caspase 3/7 activities, Bax and cleaved-caspase 3 (c-caspase 3) protein levels were assayed by flow cytometry, Caspase-Glo 3/7 Assay kit, western blot analysis, respectively. Furthermore, the mitochondrial membrane potential, adenosine triphosphate (ATP) content, reactive oxygen species (ROS) production, and Drp1 expression were also investigated. Furthermore, the dual-luciferase reporter assay was used to evaluate the relationship between miR-423-5p and Myb-related protein B (MYBL2). The roles of miR-423-5p in wnt/β-catenin were assessed by western blot analysis. The results revealed that H/R triggered miR-423-5p expression. Overexpression of miR-423-5p promoted cardiomyocyte apoptosis, enhanced the activities of caspase 3/7, upregulated the expression of Bax and c-caspase 3. miR-423-5p upregulation caused the loss of mitochondrial membrane potential and the reduction of ATP content, the augment of ROS production and Drp1 expression. However, the opposite trends were observed upon suppression of miR-423-5p. In addition, miR-423-5p could target the 3′ untranslated region of MYBL2. miR-423-5p depletion led to the activation of the wnt/β-catenin signaling pathway via targeting MYBL2. Knockdown of MYBL2 was obviously reversed the roles of miR-423-5p in apoptosis and mitochondrial dysfunction. Taken together, miR-423-5p suppression reduced H/R-induced cardiomyocytes injury through activation of the wnt/β-catenin signaling pathway via targeting MYBL2 in cardiomyocytes.     

High NEK2 confers to poor prognosis and contributes to cisplatin-based chemotherapy resistance in nasopharyngeal carcinoma

Nasopharyngeal carcinoma (NPC) is a common malignant tumor in southern China and Southeast Asia, but the molecular mechanism of its pathogenesis is poorly understood. Our previous work demonstrated that NEK2 is overexpressed in multiple cancers. However, how NEK2 involves in NPC development remains to be elucidated. In this study, we firstly identified NEK2, located at +1q32-q33, a late event in NPC pathogenesis, overexpressed in the stage III-IV and paired sequential recurrent patients with NPC by immunohistochemistry. Furthermore, Kaplan-Meier analysis indicated high NEK2 conferred an inferior overall survival in NPC. In addition, cisplatin experiments with cell counting kit-8, colony formation, and a xenograft mice model of NPC demonstrated that NEK2 contributed to proliferation and cisplatin resistance in vitro and in vivo. On the contrary, downregulation of NEK2 by short hairpin RNA inhibited NPC cell growth and increased the sensitivity of cisplatin treatment in vitro. Thus, increased expression of NEK2 protein could not be predicted for poor survival but used as a novel biomarker for recurrence of NPC. Targeting NEK2 has the potential to eradicate the cisplatin-based chemotherapy resistant NPC cells.     

Scalable remote homology detection and fold recognition in massive protein networks

The global connectivities in very large protein similarity networks contain traces of evolution among the proteins for detecting protein remote evolutionary relations or structural similarities. To investigate how well a protein network captures the evolutionary information, a key limitation is the intensive computation of pairwise sequence similarities needed to construct very large protein networks. In this article, we introduce label propagation on low-rank kernel approximation (LP-LOKA) for searching massively large protein networks. LP-LOKA propagates initial protein similarities in a low-rank graph by Nyström approximation without computing all pairwise similarities. With scalable parallel implementations based on distributed-memory using message-passing interface and Apache-Hadoop/Spark on cloud, LP-LOKA can search protein networks with one million proteins or more. In the experiments on Swiss-Prot/ADDA/CASP data, LP-LOKA significantly improved protein ranking over the widely used HMM-HMM or profile-sequence alignment methods utilizing large protein networks. It was observed that the larger the protein similarity network, the better the performance, especially on relatively small protein superfamilies and folds. The results suggest that computing massively large protein network is necessary to meet the growing need of annotating proteins from newly sequenced species and LP-LOKA is both scalable and accurate for searching massively large protein networks.     

双依他尼酸乙醇胺对谷胱甘肽S-转硫酶mu的选择性抑制作用

谷胱甘肽S-转移酶(GST)的同工酶mu(GSTM)高表达与卵巢癌顺铂耐药有关.以GST非选择性抑制剂依他尼酸设计二价潜抑制剂双依他尼酸乙醇胺(aminoethanol di-ethacrynic acid,ADEA),测定ADEA及其与还原型谷胱甘肽(glutathione,GSH)加合物对GST同工酶亚型A1、P1...