Dataset Information

Identification of the molecular basis of anti-cancer effect of Huaier.

ABSTRACT: Intervention type:DRUG. Intervention1:Huaier, Dose form:GRANULES, Route of administration:ORAL, intended dose regimen:20 to 60/day by either bulk or split for 3 months to extended term if necessary. Control intervention1:None. Primary outcome(s): For mRNA libraries, focus on mRNA studies. Data analysis includes sequencing data processing and basic sequencing data quality control, prediction of new transcripts, differential expression analysis of genes. Gene Ontology (GO) and the KEGG pathway database are used for annotation and enrichment analysis of up-regulated genes and down-regulated genes. For small RNA libraries, data analysis includes sequencing data process and sequencing data process QC, small RNA distribution across the genome, rRNA, tRNA, alignment with snRNA and snoRNA, construction of known miRNA expression pattern, prediction New miRNA and Study of their secondary structure Based on the expression pattern of miRNA, we perform not only GO / KEGG annotation and enrichment, but also different expression analysis.. Timepoint:RNA sequencing of 240 blood samples of 80 cases and its analysis, scheduled from June 30, 2022..

DISEASE(S): Cancers Such As Hepatocellular Carcinoma, Breast Cancer, Colorectal Cancer And Related Gastrointestinal Cancers, Urologic Cancers Including Prostate Cancer, Pancreas Cancer, And Lung Cancer), On Which A Significant Therapeutic Efficacy Of Huaier Has Been Reported. Special Remarks Is Emphasized On The Cancer Cases Designated To Be Related To Cancer Stem Cells

PROVIDER: 2612481 | ecrin-mdr-crc |

REPOSITORIES: ECRIN MDR

ACCESS DATA

Similar Datasets

Project description:Schmitz2014 - RNA triplex formation The model is parameterized using the parameters for gene CCDC3 from Supplementary Table S1. The two miRNAs which form the triplex together with CCDC3 are miR-551b and miR-138. This model is described in the article: Cooperative gene regulation by microRNA pairs and their identification using a computational workflow. Schmitz U, Lai X, Winter F, Wolkenhauer O, Vera J, Gupta SK. Nucleic Acids Res. 2014 Jul; 42(12): 7539-7552 Abstract: MicroRNAs (miRNAs) are an integral part of gene regulation at the post-transcriptional level. Recently, it has been shown that pairs of miRNAs can repress the translation of a target mRNA in a cooperative manner, which leads to an enhanced effectiveness and specificity in target repression. However, it remains unclear which miRNA pairs can synergize and which genes are target of cooperative miRNA regulation. In this paper, we present a computational workflow for the prediction and analysis of cooperating miRNAs and their mutual target genes, which we refer to as RNA triplexes. The workflow integrates methods of miRNA target prediction; triplex structure analysis; molecular dynamics simulations and mathematical modeling for a reliable prediction of functional RNA triplexes and target repression efficiency. In a case study we analyzed the human genome and identified several thousand targets of cooperative gene regulation. Our results suggest that miRNA cooperativity is a frequent mechanism for an enhanced target repression by pairs of miRNAs facilitating distinctive and fine-tuned target gene expression patterns. Human RNA triplexes predicted and characterized in this study are organized in a web resource at www.sbi.uni-rostock.de/triplexrna/. This model is hosted on BioModels Database and identified by: BIOMD0000000530. To cite BioModels Database, please use: BioModels Database: An enhanced, curated and annotated resource for published quantitative kinetic models. To the extent possible under law, all copyright and related or neighbouring rights to this encoded model have been dedicated to the public domain worldwide. Please refer to CC0 Public Domain Dedication for more information.

Project description:Over the past decades, Helicoverpa armigera nucleopolyhedrovirus (HearNPV) has been widely used for biocontrol of cotton bollworm, which is one of the most destructive pest insects in agriculture worldwide. However, the molecular mechanism underlying the interaction between HearNPV and host insects remains poorly understood. In this study, high throughput RNA-sequencing was integrated with label-free quantitative proteomics analysis to examine the dynamics of gene expression in the fat body of H. armigera larvae in response to challenge with HearNPV. RNA-sequencing-based transcriptomic analysis indicated that host gene expression was substantially altered, yielding 3,850 differentially expressed genes (DEGs), while no global transcriptional shut-off effects were observed in the fat body. Among the DEGs, 60 immunity-related genes were down-regulated after baculovirus infection, a finding that was consistent with the results of quantitative real-time RT-PCR (qRT-PCR). Gene ontology and functional classification demonstrated that the majority of down-regulated genes were enriched in gene cohorts involved in energy, carbohydrate, and amino acid metabolic pathways. Proteomics analysis identified differentially expressed proteins in the fat body, among which 76 were up-regulated, whereas 373 were significantly down-regulated upon infection. The down-regulated proteins are involved in metabolic pathways such as energy metabolism, carbohydrate metabolism (CM), and amino acid metabolism, in agreement with the RNA-seq data. Furthermore, correlation analysis suggested a strong association between the mRNA level and protein abundance in the H. armigera fat body. More importantly, the predicted gene interaction network indicated that a large subset of metabolic networks was significantly negatively regulated by viral infection, including CM-related enzymes such as aldolase, enolase, malate dehydrogenase and triose-phosphate isomerase. Taken together, transcriptomic combined with proteomic data elucidated that baculovirus established systemic infection of host larvae, and manipulated the host mainly by suppressing the host immune response and down-regulating metabolism to allow viral self-replication and proliferation. Therefore, this study provided important insights into the mechanism of host-baculovirus interaction.

Dataset Information

Identification of the molecular basis of anti-cancer effect of Huaier.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure