[Abstract unavailable

Recent high-throughput techniques have generated a flood of biological data in all aspects. The transformation and visualization of multi-dimensional and numerical gene or protein expression data in a single heatmap can provide a concise but comprehensive presentation of molecular dynamics under different conditions. In this work, we developed an easy-to-use tool named HemI (Heat map Illustrator), which can visualize either gene or protein expression data in heatmaps. Additionally, the heatmaps can be recolored, rescaled or rotated in a customized manner. In addition, HemI provides multiple clustering strategies for analyzing the data. Publication-quality figures can be exported directly. We propose that HemI can be a useful toolkit for conveniently visualizing and manipulating heatmaps. The stand-alone packages of HemI were implemented in Java and can be accessed at http://hemi.biocuckoo.org/down.php.

Small ubiquitin-like modifiers (SUMOs) regulate a variety of cellular processes through two distinct mechanisms, including covalent sumoylation and non-covalent SUMO interaction. The complexity of SUMO regulations has greatly hampered the large-scale identification of SUMO substrates or interaction partners on a proteome-wide level. In this work, we developed a new tool called GPS-SUMO for the prediction of both sumoylation sites and SUMO-interaction motifs (SIMs) in proteins. To obtain an accurate performance, a new generation group-based prediction system (GPS) algorithm integrated with Particle Swarm Optimization approach was applied. By critical evaluation and comparison, GPS-SUMO was demonstrated to be substantially superior against other existing tools and methods. With the help of GPS-SUMO, it is now possible to further investigate the relationship between sumoylation and SUMO interaction processes. A web service of GPS-SUMO was implemented in PHP + JavaScript and freely available at http://sumosp.biocuckoo.org.

law firm, and other from Equity Quotient outside the submitted work. Dr Jagsi serves on the board of directors of ASCO and as vice chair of the ethics committee of ASTRO. This work is entirely separate from those roles. No other disclosures were reported.

Background: Long noncoding RNAs (lncRNAs) play nonnegligible roles in the epigenetic regulation of cancer cells. This study aimed to identify a specific lncRNA that promotes the colorectal cancer (CRC) progression and could be a potential therapeutic target. Methods:We screened highly expressed lncRNAs in human CRC samples compared with their matched adjacent normal tissues. The proteins that interact with LINRIS (Long Intergenic Noncoding RNA for IGF2BP2 Stability) were confirmed by RNA pull-down and RNA immunoprecipitation (RIP) assays. The proliferation and metabolic alteration of CRC cells with LINRIS inhibited were tested in vitro and in vivo.Results: LINRIS was upregulated in CRC tissues from patients with poor overall survival (OS), and LINRIS inhibition led to the impaired CRC cell line growth. Moreover, knockdown of LINRIS resulted in a decreased level of insulin-like growth factor 2 mRNA-binding protein 2 (IGF2BP2), a newly found N 6 -methyladenosine (m 6 A) 'reader'. LINRIS blocked K139 ubiquitination of IGF2BP2, maintaining its stability. This process prevented the degradation of IGF2BP2 through the autophagy-lysosome pathway (ALP). Therefore, knockdown of LINRIS attenuated the downstream effects of IGF2BP2, especially MYC-mediated glycolysis in CRC cells. In addition, the transcription of LINRIS could be inhibited by GATA3 in CRC cells. In vivo experiments showed that the inhibition of LINRIS suppressed the proliferation of tumors in orthotopic models and in patient-derived xenograft (PDX) models.Conclusion: LINRIS is an independent prognostic biomarker for CRC. The LINRIS-IGF2BP2-MYC axis promotes the progression of CRC and is a promising therapeutic target.

As one of the most important and ubiquitous post-translational modifications (PTMs) of proteins, S-nitrosylation plays important roles in a variety of biological processes, including the regulation of cellular dynamics and plasticity. Identification of S-nitrosylated substrates with their exact sites is crucial for understanding the molecular mechanisms of S-nitrosylation. In contrast with labor-intensive and time-consuming experimental approaches, prediction of S-nitrosylation sites using computational methods could provide convenience and increased speed. In this work, we developed a novel software of GPS-SNO 1.0 for the prediction of S-nitrosylation sites. We greatly improved our previously developed algorithm and released the GPS 3.0 algorithm for GPS-SNO. By comparison, the prediction performance of GPS 3.0 algorithm was better than other methods, with an accuracy of 75.80%, a sensitivity of 53.57% and a specificity of 80.14%. As an application of GPS-SNO 1.0, we predicted putative S-nitrosylation sites for hundreds of potentially S-nitrosylated substrates for which the exact S-nitrosylation sites had not been experimentally determined. In this regard, GPS-SNO 1.0 should prove to be a useful tool for experimentalists. The online service and local packages of GPS-SNO were implemented in JAVA and are freely available at: http://sno.biocuckoo.org/.

N 6 -methyladenosine (m 6 A) modification is an important mechanism in miRNA processing and maturation, but the role of its aberrant regulation in human diseases remained unclear. Here, we demonstrate that oncogenic primary microRNA-25 (miR-25) in pancreatic duct epithelial cells can be excessively maturated by cigarette smoke condensate (CSC) via enhanced m 6 A modification that is mediated by NF-κB associated protein (NKAP). This modification is catalyzed by overexpressed methyltransferase-like 3 (METTL3) due to hypomethylation of the METTL3 promoter also caused by CSC. Mature miR-25, miR-25-3p, suppresses PH domain leucine-rich repeat protein phosphatase 2 (PHLPP2), resulting in the activation of oncogenic AKT-p70S6K signaling, which provokes malignant phenotypes of pancreatic cancer cells. High levels of miR-25-3p are detected in smokers and in pancreatic cancers tissues that are correlated with poor prognosis of pancreatic cancer patients. These results collectively indicate that cigarette smoke-induced miR-25-3p excessive maturation via m 6 A modification promotes the development and progression of pancreatic cancer.

As the most important post-translational modification of proteins, phosphorylation plays essential roles in all aspects of biological processes. Besides experimental approaches, computational prediction of phosphorylated proteins with their kinase-specific phosphorylation sites has also emerged as a popular strategy, for its low-cost, fast-speed and convenience. In this work, we developed a kinase-specific phosphorylation sites predictor of GPS 2.1 (Group-based Prediction System), with a novel but simple approach of motif length selection (MLS). By this approach, the robustness of the prediction system was greatly improved. All algorithms in GPS old versions were also reserved and integrated in GPS 2.1. The online service and local packages of GPS 2.1 were implemented in JAVA 1.5 (J2SE 5.0) and freely available for academic researches at: http://gps.biocuckoo.org.