Project description:Non-small cell lung cancer (NSCLC, n=22) and normal adjacent control biopsies (n=18) from patients with lung cancer were obtained for Affymetrix GeneChip analysis. NSCLC samples were grouped into squamous cell carcinoma (SCC, n=11) and adenocarcinoma (AC, n=11) samples.
Project description:The existence of interactions between many cellular proteins and various polyanionic surfaces within a cell is now well-established. The functional role of such interactions, however, remains to be clearly defined. The existence of protein arrays, with a large selection of different kinds of proteins, provides a way to better address a number of aspects of this question. We have therefore investigated the interaction between five cellular polyanions (actin, tubulin, heparin, heparan sulfate (HS), and DNA) and approximately 5,000 human proteins using protein microarrays in an attempt to better understand the functional nature of such interaction(s). We demonstrate that a large number of polyanion binding proteins exist which contain multiply positively-charged regions, are often disordered, are involved in phosphorylation processes, and appear to play a role in protein-protein interaction networks. Considering the crowded nature of cellular interiors, we propose that polyanion binding proteins (PABPs) interact with a wide variety of polyanionic surfaces in cells in a functionally significant manner. Keywords: Protein-Protein, protein-polyanion Interaction
Project description:establishment of patient derived tumor xenografts from Asian gastric adenocarcinoma is driven by molecular selection with implications for anticancer agent testing
Project description:<p><strong>BACKGROUND:</strong> The human intestinal microbiome plays a central role in overall health status, especially in early life stages. 16S rRNA amplicon sequencing is used to profile its taxonomic composition; however, multiomic approaches have been proposed as the most accurate methods for study of the complexity of the gut microbiota. In this study, we propose an optimized method for bacterial diversity analysis that we validated and complemented with metabolomics by analyzing fecal samples.</p><p><strong>METHODS:</strong> Forty-eight different analytical combinations regarding (1) 16S rRNA variable region sequencing, (2) a feature selection approach, and (3) taxonomy assignment methods were tested. A total of 18 infant fecal samples grouped depending on the type of feeding were analyzed by the proposed 16S rRNA workflow and by metabolomic analysis.</p><p><strong>RESULTS:</strong> The results showed that the sole use of V4 region sequencing with ASV identification and VSEARCH for taxonomy assignment produced the most accurate results. The application of this workflow showed clear differences between fecal samples according to the type of feeding, which correlated with changes in the fecal metabolic profile.</p><p><strong>CONCLUSION:</strong> A multiomic approach using real fecal samples from 18 infants with different types of feeding demonstrated the effectiveness of the proposed 16S rRNA-amplicon sequencing workflow.</p>
Project description:To identify underlying mechanisms involved with metastasis formation in Wilms tumors (WTs), we performed comprehensive DNA methylation and gene expression analyses of matched normal kidney (NK), WT blastemal component, and metastatic tissues (MT) from patients treated under SIOP 2001 protocol. A linear Bayesian framework model identified 497 differentially methylated positions (DMPs) between groups that discriminated NK from WT, but MT samples were divided in two groups. Accordingly, methylation variance grouped NK and three MT samples tightly together and all WT with four MT samples that showed high variability. WT were hypomethylated compared to NK, and MT had a hypermethylated pattern compared to both groups. The methylation patterns were in agreement with methylases and demethylases expression. Methylation data pointed to the existence of two groups of metastases. While hierarchical clustering analysis based on the expression of all 2569 differentially expressed genes (DEGs) discriminated WT and MT from all NK samples, the hierarchical clustering based on the expression of 44 genes with a differentially methylated region (DMR) located in their promoter region revealed two groups: one containing all NKs and three MTs and one containing all WT and four MTs. Methylation changes might be controlling expression of genes associated with WT progression. The 44 genes are candidates to be further explored as a signature for metastasis formation in WT.