Project description:RNA-sequencing of the mRNA transcriptome in blood, across three time-points in severe psoriasis patients treated with the tumor necrosis factor (TNF) inhibitor, etanercept
Project description:The understanding of peripheral blood platelets as indicators of cancer progression and the significance of abnormal glycosylation in platelet function and related disorders are increasingly recognized. In this study, our analysis of a large cohort of liver cancer patients revealed decreased PLC and elevated PT as poor prognostic factors, emphasizing the association between platelets and liver cancer progression. Herein, we conducted platelet proteome and site-specific glycoproteome analysis, generating a dataset comprising 3,466 proteins with qualitative information and 3,199 proteins with quantitative information, and 3,419 site-specific glycans with qualitative information and 3,377 site-specific glycans with quantitative information from peripheral blood platelets of 30 HCC patients, 30 metastatic liver cancer patients, and 16 healthy controls. Integrated analysis revealed significant changes in platelet protein N-glycosylation in liver cancer patients. Further systems biology analysis and lectin pull-down-coupled ELISA assays in independent clinical samples confirmed two N-glycoproteins with specific glycan types, CO3 with high-mannose modification and ITB3 with sialylation, as potential biomarkers distinguishing normal individuals from liver cancer patients, highlighting the potential of platelet glycosylated proteins as biomarkers.
Project description:A large panel of 81 liver cancer cell models, designated as LIver cancer MOdel REpository (LIMORE) was constructed. These cell lines include 31 public cell lines and 50 new cell models establishend from Chinese liver cancer patients. Whole genome sequencing (WGS), exome sequencing (WES) and RNA sequencing (RNAseq) were performed to obtain the genetic information for these cell lines. These cell lines and associated data provide new models and also a rich resource for liver cancer.
Project description:Despite the large amounts of transcriptome data generated for many non-model organisms, there has been a much lesser uptake of individual genomic sequencing for detecting SNPs and determining haplotypes in these species. Transcriptome data represents a source of variant information, specifically for coding DNA, however there is little information on the accuracy, coverage and limitations of using transcriptomic data for the identification of single nucleotide polymorphisms (SNPs) in non-model organisms. To investigate this, we generated the first whole exome design for bovine using the Roche Nimblegen Developer system (Roche, USA) and used it to sequence and call SNPs from a lactating dairy cow model with genetically divergent fertility phenotypes (Fert+, n=8; Fert-, n=8). We compared these results to SNPs called from liver and muscle transcriptomes from the same animals. Our exome demonstrated 99.1% coverage of the target design of 56.7MB, whereas the transcriptomes only covered 60 and 54.5% of 44.2 and 42.8MB in liver and muscle respectively. We found that specificity of SNP detection in the transcriptome data is ~75% following basic hard-filtering, but could be increased marginally to ~80% by increasing the minimum threshold of reads covering a SNP, and number of samples in which it was found. Functional annotation of non-synonymous SNPs specific to both the high and low fertility phenotype identified immune response-related genes, supporting previous work that identified this process as key to the phenotype.