14 research outputs found

    Deciphering glycosylation-driven prognostic insights and therapeutic prospects in glioblastoma through a comprehensive regulatory model

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    The oncogenesis and development of glioblastoma multiforme have been linked to glycosylation modifications, which are common post-translational protein modifications. Abnormal glycosyltransferase development leads to irregular glycosylation patterns, which hold clinical significance for GB prognosis. By utilizing both single-cell and bulk data, we developed a scoring system to assess glycosylation levels in GB. Moreover, a glycosylation-based signature was created to predict GB outcomes and therapy responsiveness. The study led to the development of an glyco-model incorporating nine key genes. This risk assessment tool effectively stratified GB patients into two distinct groups. Extensive validation through ROC analysis, RMST, and Kaplan-Meier (KM) survival analysis emphasized the model’s robust predictive capabilities. Additionally, a nomogram was constructed to predict survival rates at specific time intervals. The research revealed substantial disparities in immune cell infiltration between low-risk and high-risk groups, characterized by differences in immune cell abundance and elevated immune scores. Notably, the glyco-model predicted diverse responses to immune checkpoint inhibitors and drug therapies, with high-risk groups exhibiting a preference for immune checkpoint inhibitors and demonstrated superior responses to drug treatments. Furthermore, the study identified two potential drug targets and utilized Connectivity Map analysis to pinpoint promising therapeutic agents. Clofarabine and YM155 were identified as potent candidates for the treatment of high-risk GB. Our well-crafted glyco-model effectively discriminates patients by calculating the risk score, accurately predicting GB outcomes, and significantly enhancing prognostic assessment while identifying novel immunotherapeutic and chemotherapeutic strategies for GB treatment

    REMAS: a new regression model to identify alternative splicing events from exon array data

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    <p>Abstract</p> <p>Background</p> <p>Alternative splicing (AS) is an important regulatory mechanism for gene expression and protein diversity in eukaryotes. Previous studies have demonstrated that it can be causative for, or specific to splicing-related diseases. Understanding the regulation of AS will be helpful for diagnostic efforts and drug discoveries on those splicing-related diseases. As a novel exon-centric microarray platform, exon array enables a comprehensive analysis of AS by investigating the expression of known and predicted exons. Identifying of AS events from exon array has raised much attention, however, new and powerful algorithms for exon array data analysis are still absent till now.</p> <p>Results</p> <p>Here, we considered identifying of AS events in the framework of variable selection and developed a regression method for AS detection (REMAS). Firstly, features of alternatively spliced exons were scaled by reasonably defined variables. Secondly, we designed a hierarchical model which can represent gene structure and transcriptional influence to exons, and the lasso type penalties were introduced in calculation because of huge variable size. Thirdly, an iterative two-step algorithm was developed to select alternatively spliced genes and exons. To avoid negative effects introduced by small sample size, we ranked genes as parameters indicating their AS capabilities in an iterative manner. After that, both simulation and real data evaluation showed that REMAS could efficiently identify potential AS events, some of which had been validated by RT-PCR or supported by literature evidence.</p> <p>Conclusion</p> <p>As a new lasso regression algorithm based on hierarchical model, REMAS has been demonstrated as a reliable and effective method to identify AS events from exon array data.</p

    Turning dead leaves into an active multifunctional material as evaporator, photocatalyst, and bioplastic

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    Large numbers of leaves fall on the earth each autumn. The current treatments of dead leaves mainly involve completely destroying the biocomponents, which causes considerable energy consumption and environmental issues. It remains a challenge to convert waste leaves into useful materials without breaking down their biocomponents. Here, we turn red maple dead leaves into an active three-component multifunctional material by exploiting the role of whewellite biomineral for binding lignin and cellulose. Owing to its intense optical absorption spanning the full solar spectrum and the heterogeneous architecture for effective charge separation, films of this material show high performance in solar water evaporation, photocatalytic hydrogen production, and photocatalytic degradation of antibiotics. Furthermore, it also acts as a bioplastic with high mechanical strength, high-temperature tolerance, and biodegradable features. These findings pave the way for the efficient utilization of waste biomass and innovations of advanced materials

    Cuproptosis in glioblastoma: unveiling a novel prognostic model and therapeutic potential

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    Glioblastoma, a notably aggressive brain tumor, is characterized by a brief survival period and resistance to conventional therapeutic approaches. With the recent identification of “Cuproptosis,” a copper-dependent apoptosis mechanism, this study aimed to explore its role in glioblastoma prognosis and potential therapeutic implications. A comprehensive methodology was employed, starting with the identification and analysis of 65 cuproptosis-related genes. These genes were subjected to differential expression analyses between glioblastoma tissues and normal counterparts. A novel metric, the “CP-score,” was devised to quantify the cuproptosis response in glioblastoma patients. Building on this, a prognostic model, the CP-model, was developed using Cox regression techniques, designed to operate on both bulk and single-cell data. The differential expression analysis revealed 31 genes with distinct expression patterns in glioblastoma. The CP-score was markedly elevated in glioblastoma patients, suggesting an intensified cuproptosis response. The CP-model adeptly stratified patients into distinct risk categories, unveiling intricate associations between glioblastoma prognosis, immune response pathways, and the tumor’s immunological environment. Further analyses indicated that high-risk patients, as per the CP-model, exhibited heightened expression of certain immune checkpoints, suggesting potential therapeutic targets. Additionally, the model hinted at the possibility of personalized therapeutic strategies, with certain drugs showing increased efficacy in high-risk patients. The CP-model offers a promising tool for glioblastoma prognosis and therapeutic strategy development, emphasizing the potential of Cuproptosis in cancer treatment

    A proteomic view of Caenorhabditis elegans caused by short-term hypoxic stress

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    <p>Abstract</p> <p>Background</p> <p>The nematode <it>Caenorhabditis elegans </it>is both sensitive and tolerant to hypoxic stress, particularly when the evolutionarily conserved hypoxia response pathway HIF-1/EGL-9/VHL is involved. Hypoxia-induced changes in the expression of a number of genes have been analyzed using whole genome microarrays in <it>C. elegans</it>, but the changes at the protein level in response to hypoxic stress still remain unclear.</p> <p>Results</p> <p>Here, we utilized a quantitative proteomic approach to evaluate changes in the expression patterns of proteins during the early response to hypoxia in <it>C. elegans</it>. Two-dimensional difference gel electrophoresis (2D-DIGE) was used to compare the proteomic maps of wild type <it>C. elegans </it>strain N2 under a 4-h hypoxia treatment (0.2% oxygen) and under normoxia (control). A subsequent analysis by MALDI-TOF-TOF-MS revealed nineteen protein spots that were differentially expressed. Nine of the protein spots were significantly upregulated, and ten were downregulated upon hypoxic stress. Three of the upregulated proteins were involved in cytoskeletal function (LEV-11, MLC-1, ACT-4), while another three upregulated (ATP-2, ATP-5, VHA-8) were ATP synthases functionally related to energy metabolism. Four ribosomal proteins (RPL-7, RPL-8, RPL-21, RPS-8) were downregulated, indicating a decrease in the level of protein translation upon hypoxic stress. The overexpression of tropomyosin (LEV-11) was further validated by Western blot. In addition, the mutant strain of <it>lev-11(x12</it>) also showed a hypoxia-sensitive phenotype in subsequent analyses, confirming the proteomic findings.</p> <p>Conclusions</p> <p>Taken together, our data suggest that altered protein expression, structural protein remodeling, and the reduction of translation might play important roles in the early response to oxygen deprivation in <it>C. elegans</it>, and this information will help broaden our knowledge on the mechanism of hypoxia response.</p

    MPprimer: a program for reliable multiplex PCR primer design

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    <p>Abstract</p> <p>Background</p> <p>Multiplex PCR, defined as the simultaneous amplification of multiple regions of a DNA template or multiple DNA templates using more than one primer set (comprising a forward primer and a reverse primer) in one tube, has been widely used in diagnostic applications of clinical and environmental microbiology studies. However, primer design for multiplex PCR is still a challenging problem and several factors need to be considered. These problems include mis-priming due to nonspecific binding to non-target DNA templates, primer dimerization, and the inability to separate and purify DNA amplicons with similar electrophoretic mobility.</p> <p>Results</p> <p>A program named MPprimer was developed to help users for reliable multiplex PCR primer design. It employs the widely used primer design program Primer3 and the primer specificity evaluation program MFEprimer to design and evaluate the candidate primers based on genomic or transcript DNA database, followed by careful examination to avoid primer dimerization. The graph-expanding algorithm derived from the greedy algorithm was used to determine the optimal primer set combinations (PSCs) for multiplex PCR assay. In addition, MPprimer provides a virtual electrophotogram to help users choose the best PSC. The experimental validation from 2× to 5× plex PCR demonstrates the reliability of MPprimer. As another example, MPprimer is able to design the multiplex PCR primers for DMD (dystrophin gene which caused Duchenne Muscular Dystrophy), which has 79 exons, for 20×, 20×, 20×, 14×, and 5× plex PCR reactions in five tubes to detect underlying exon deletions.</p> <p>Conclusions</p> <p>MPprimer is a valuable tool for designing specific, non-dimerizing primer set combinations with constrained amplicons size for multiplex PCR assays.</p

    Transcription and splicing regulation in human umbilical vein endothelial cells under hypoxic stress conditions by exon array

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    <p>Abstract</p> <p>Background</p> <p>The balance between endothelial cell survival and apoptosis during stress is an important cellular process for vessel integrity and vascular homeostasis, and it is also pivotal in angiogenesis during the development of many vascular diseases. However, the underlying molecular mechanisms remain largely unknown. Although both transcription and alternative splicing are important in regulating gene expression in endothelial cells under stress, the regulatory mechanisms underlying this state and their interactions have not yet been studied on a genome-wide basis.</p> <p>Results</p> <p>Human umbilical vein endothelial cells (HUVECs) were treated with cobalt chloride (CoCl<sub>2</sub>) both to mimic hypoxia and to induce cell apoptosis and alternative splicing responses. Cell apoptosis rate analysis indicated that HUVECs exposed to 300 μM CoCl<sub>2 </sub>for 24 hrs were initially counterbalancing apoptosis with cell survival. We therefore used the Affymetrix exon array system to determine genome-wide transcript- and exon-level differential expression. Other than 1583 differentially expressed transcripts, 342 alternatively spliced exons were detected and classified by different splicing types. Sixteen alternatively spliced exons were validated by RT-PCR. Furthermore, direct evidence for the ongoing balance between HUVEC survival and apoptosis was provided by Gene Ontology (GO) and protein function, as well as protein domain and pathway enrichment analyses of the differentially expressed transcripts. Importantly, a novel molecular module, in which the heat shock protein (HSP) families play a significant role, was found to be activated under mimicked hypoxia conditions. In addition, 46% of the transcripts containing stress-modulated exons were differentially expressed, indicating the possibility of combinatorial regulation of transcription and splicing.</p> <p>Conclusion</p> <p>The exon array system effectively profiles gene expression and splicing on the genome-wide scale. Based on this approach, our data suggest that transcription and splicing not only regulate gene expression, but also carry out combinational regulation of the balance between survival and apoptosis of HUVECs under mimicked hypoxia conditions. Since cell survival following the apoptotic challenge is pivotal in angiogenesis during the development of many vascular diseases, our results may advance the knowledge of multilevel gene regulation in endothelial cells under physiological and pathological conditions.</p

    Reliability analysis of the Ahringer Caenorhabditis elegans RNAi feeding library: a guide for genome-wide screens

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    <p>Abstract</p> <p>Background</p> <p>The Ahringer <it>C. elegans </it>RNAi feeding library prepared by cloning genomic DNA fragments has been widely used in genome-wide analysis of gene function. However, the library has not been thoroughly validated by direct sequencing, and there are potential errors, including: 1) mis-annotation (the clone with the retired gene name should be remapped to the actual target gene); 2) nonspecific PCR amplification; 3) cross-RNAi; 4) mis-operation such as sample loading error, <it>etc</it>.</p> <p>Results</p> <p>Here we performed a reliability analysis on the Ahringer <it>C. elegans </it>RNAi feeding library, which contains 16,256 bacterial strains, using a bioinformatics approach. Results demonstrated that most (98.3%) of the bacterial strains in the library are reliable. However, we also found that 2,851 (17.54%) bacterial strains need to be re-annotated even they are reliable. Most of these bacterial strains are the clones having the retired gene names. Besides, 28 strains are grouped into unreliable category and 226 strains are marginal because of probably expressing unrelated double-stranded RNAs (dsRNAs). The accuracy of the prediction was further confirmed by direct sequencing analysis of 496 bacterial strains. Finally, a freely accessible database named CelRNAi (<url>http://biocompute.bmi.ac.cn/CelRNAi/</url>) was developed as a valuable complement resource for the feeding RNAi library by providing the predicted information on all bacterial strains. Moreover, submission of the direct sequencing result or any other annotations for the bacterial strains to the database are allowed and will be integrated into the CelRNAi database to improve the accuracy of the library. In addition, we provide five candidate primer sets for each of the unreliable and marginal bacterial strains for users to construct an alternative vector for their own RNAi studies.</p> <p>Conclusions</p> <p>Because of the potential unreliability of the Ahringer <it>C. elegans </it>RNAi feeding library, we strongly suggest the user examine the reliability information of the bacterial strains in the CelRNAi database before performing RNAi experiments, as well as the post-RNAi experiment analysis.</p

    REMAS: a new regression model to identify alternative splicing events from exon array data

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    Abstract Background Alternative splicing (AS) is an important regulatory mechanism for gene expression and protein diversity in eukaryotes. Previous studies have demonstrated that it can be causative for, or specific to splicing-related diseases. Understanding the regulation of AS will be helpful for diagnostic efforts and drug discoveries on those splicing-related diseases. As a novel exon-centric microarray platform, exon array enables a comprehensive analysis of AS by investigating the expression of known and predicted exons. Identifying of AS events from exon array has raised much attention, however, new and powerful algorithms for exon array data analysis are still absent till now. Results Here, we considered identifying of AS events in the framework of variable selection and developed a regression method for AS detection (REMAS). Firstly, features of alternatively spliced exons were scaled by reasonably defined variables. Secondly, we designed a hierarchical model which can represent gene structure and transcriptional influence to exons, and the lasso type penalties were introduced in calculation because of huge variable size. Thirdly, an iterative two-step algorithm was developed to select alternatively spliced genes and exons. To avoid negative effects introduced by small sample size, we ranked genes as parameters indicating their AS capabilities in an iterative manner. After that, both simulation and real data evaluation showed that REMAS could efficiently identify potential AS events, some of which had been validated by RT-PCR or supported by literature evidence. Conclusion As a new lasso regression algorithm based on hierarchical model, REMAS has been demonstrated as a reliable and effective method to identify AS events from exon array data.http://deepblue.lib.umich.edu/bitstream/2027.42/112933/1/12859_2009_Article_3201.pd
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