Project description:Solid tumors are complex organs comprising neoplastic cells and stroma, yet cancer cell lines remain widely used to study tumor biology, biomarkers and experimental therapy. Here, we performed a fully integrative analysis of global proteomic data comparing human colorectal cancer (CRC) cell lines to primary tumors and normal tissues. We found a significant, systematic difference between cell line and tumor proteomes, with a major contribution from tumor stroma proteomes. Nevertheless, cell lines overall mirrored the proteomic differences observed between tumors and normal tissues, in particular for genetic information processing and metabolic pathways, indicating that cell lines provide a system for the study of the intrinsic molecular programs in cancer cells. Intersection of cell line data with tumor data provided insights into tumor cell specific proteome alterations driven by genomic alterations. Our integration of cell line proteogenomic data with drug sensitivity data highlights the potential of proteomic data in predicting therapeutic response. We identified representative cell lines for the proteomic subtypes of primary tumors, and linked these to drug sensitivity data to identify subtype-specific drug candidates.
Project description:For the purpose of characterization of the 9p24 amplicon, we carried out high-resolution array CGH (Agilent 244K chip) analysis of four cancer cell lines, including three breast cancer cell lines, Colo824, HCC1954 and HCC70, and one esophageal cancer cell line, KYSE150.
Project description:The genomic loci with copy number alterations are known to harbor cancer genes. We investigated a comprehensive panel of gastric cancer cell lines for their genome-wide copy number alterations. Eighteen gastric cancer cell lines were profiled using Affymetrix 500K SNP arrays. For copy number calculation, seven independent normal blood samples were profiled together. The copy numbers were calculated genome-wide, in these cell lines with high resolution and reveal the cell line specific amplification and copy number changes.
Project description:High-resolution DNA methylation array analysis of human cancer samples and normal control tissue types Analisys of Differential Methylation Regions (DMRs) of human cancer samples and normal control tissue types performing high-resolution DNA methylation array analysis
Project description:Understanding the genetic mechanisms underlying natural variation in gene expression is a central goal of both medical and evolutionary genetics, and studies of expression quantitative trait loci (eQTLs) have become an important tool for achieving this goal. While all eQTL studies to date have assayed mRNA levels using expression microarrays, recent advances in RNA sequencing enable the analysis of transcript variation at unprecedented resolution. We sequenced RNA from 69 lymphoblastoid cell lines (LCLs) derived from unrelated Nigerian individuals that have been extensively genotyped by the International HapMap Project. Pooling data from all individuals, we generated a map of the transcriptional landscape of these cells, identifying extensive use of unannotated polyadenylation sites and over 100 novel putative protein-coding exons. Using the genotypes from the HapMap project, we identified over a thousand genes at which genetic variation influences overall expression levels or splicing. We demonstrate that eQTLs near genes generally act via a mechanism involving allele-specific expression, and that variation that influences the inclusion of an exon is enriched within or near the consensus splice sites. Our results illustrate the power of high-throughput sequencing for the joint analysis of variation in transcription, splicing, and allele-specific expression across individuals. RNA-Seq in 69 lymphoblastoid cell lines from multiple Yoruban HapMap individuals in at least two replicate lanes per individual
